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Speaker 1: I guess I grew up on an all day row.

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Speaker 1: Hey everybody, welcome to another edition of the Hunting Collective.

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Speaker 1: Hello Philip, hi Ben. I was just telling you, boy,

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Speaker 1: I feel like shit big time, and knowing you, the

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Speaker 1: first thing I assumed was well alcohol was involved, and

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Speaker 1: you were like, where did you get drunk last night?

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Speaker 1: I like, not really, but kind of it was an accident.

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Speaker 1: I was working in the yard all weekend, working hard

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Speaker 1: and you know, doing landscaping, doing building things, and uh,

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Speaker 1: it was hot, and then you know, last night is

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Speaker 1: it got cooled down? I think I have I have

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Speaker 1: a couple of beers. I'll go in the fridge and

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Speaker 1: GETO a couple of beers, and I'm drinking the beers

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Speaker 1: while I'm working. I'm thirsty. It's just been a long day.

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Speaker 1: And next thing I know, I had eight beers. It's

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Speaker 1: one of those things when it's when you're working outside

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Speaker 1: in the heat and you're drinking. Sometimes you don't realize

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Speaker 1: how much you're drinking until you up inside your house

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Speaker 1: and like take your sung glasses off and just stand

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Speaker 1: there for a second, and wasn't all it all? Just

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Speaker 1: yeah coming dirt. I just shook my head and I look.

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Speaker 1: I was like, all right, I'm drunk. Yeah, perfect, I'm

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Speaker 1: gonna go take a nap for about ten hours. So anyway,

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Speaker 1: I'm not at my best today. So I apologize to

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Speaker 1: everyone out there in th HC Land. Please, this is

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Speaker 1: a free show, free show. They can't you can't complain.

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Speaker 1: Give us a five star review on iTunes. Write something

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Speaker 1: really nice about this particular podcast. But we got it

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Speaker 1: really important things to do. So I'm gonna try to

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Speaker 1: perk up. Um. Maybe I'll start Maybe I'll have my

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Speaker 1: first sip of coffee later today or something like that

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Speaker 1: makes me feel better. Phil, I wish you would start

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Speaker 1: drinking coffee. I think that should be. That would be

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Speaker 1: like an event, a world changing event. I'm gonna call

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Speaker 1: the guys a black rifle coffee. And but like, can

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Speaker 1: we can we do a live event? Sure? I just

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Speaker 1: sit on the stage with a spotlight and I'm just

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Speaker 1: with a slowly bring the cup of coffee to my mouth,

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Speaker 1: slowly sip it and then and seen. That's it. It's

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Speaker 1: performance art. Yeah you should have. You could have done

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Speaker 1: it on some some public land and to get into

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Speaker 1: this contest, oh yeah, yeah. The Great American Outdoors contest.

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Speaker 1: Uh is over. It's over this one. Let's see, of

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Speaker 1: all the contests we've done, this is what if we're

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Speaker 1: going to count them off, it's like the fifth contest

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Speaker 1: we've done. We're gonna keep doing them. By the way,

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Speaker 1: so keep listening. Please tell your friends, um, this one

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Speaker 1: was not the most impressive via numbers, but the most

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Speaker 1: impressive via the effort, which is saying a lot because

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Speaker 1: motherfucker's have have made hand turkeys out of fly time

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Speaker 1: material and put them in wooden cases. Do you ever

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Speaker 1: see that, By the way, I didn't. In defense of

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Speaker 1: your listeners, this was the most I think you were

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Speaker 1: asking the most of them for this guy. The next time,

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Speaker 1: I'm just gonna be like, take a picture of yourself.

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Speaker 1: We need to, we need to. When I was drunk

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Speaker 1: last night, I had an idea for a contests and

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Speaker 1: I forgot it. I can't remember it now. That's too bad,

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Speaker 1: soul have been. It was really a good a good idea. Um.

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Speaker 1: We had this contest where you had to go. It

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Speaker 1: was a lot. You had to find a place that

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Speaker 1: was receiving or received funds from the l w c F,

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Speaker 1: the Land of Water Conservation Fund, and then you had

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Speaker 1: to go to it. So that's that's two that's two

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Speaker 1: steps already, and that's and that's not even the difficult part.

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Speaker 1: People are busy, that's right. And then you had to

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Speaker 1: make art when you got there. If any it could

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Speaker 1: have been. Most of you chose film. We received dozens

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Speaker 1: of films and I've picked the top three are films

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Speaker 1: that I've chosen. Um, some poetry, and then other people

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Speaker 1: just sending photos of them doing stuff. I was said

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Speaker 1: a lot of you people, this ain't gonna work on me.

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Speaker 1: It might work on you, Phil, it ain't gonna work

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Speaker 1: with me with pictures of your kids. Okay, even if

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Speaker 1: they're cute. There were some cute ones, but it's just

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Speaker 1: not gonna work on me. So don't try. Don't pander

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Speaker 1: to me with cute children on public lands. That's not

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Speaker 1: the points discussed. They are the bullshit. They are the future,

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Speaker 1: and you are introducing them to the wonderful splinters of

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Speaker 1: the American outdoors. But ben's not I'm not impressed. No,

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Speaker 1: I mean, it really is the embodiment of what we're

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Speaker 1: all about here at TCHC. I don't want to see it. No,

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Speaker 1: I don't want you to shove it in my face.

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Speaker 1: I don't need to see it. No, So we rather

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Speaker 1: than vote on these things, I just felt like they

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Speaker 1: were I felt like there were three that were so

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Speaker 1: exceptional and they were so lived long, So we can't

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Speaker 1: play that. Each of them is like four to five minutes,

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Speaker 1: so I can't play them all here for you, but

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Speaker 1: I've I'm gonna try to select clips that embodies the

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Speaker 1: video themselves and the person who turned that video into us.

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Speaker 1: But before we get to that, UM a couple updates

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Speaker 1: on the Great American Outdoors Act itself last Friday. This

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Speaker 1: past Friday, the House Rules Committee debated the Act the

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Speaker 1: lighted piece of legislation before being considered on the floor tomorrow.

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Speaker 1: So today's Tuesday. You're listening to this. I hope, I

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Speaker 1: hope you don't. You don't listen to this any other

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Speaker 1: day than when it comes out, So hopefully this is Tuesday.

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Speaker 1: So tomorrow is Wednesday. Then it's going to get votes

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Speaker 1: tomorrow starting between three and three thirty pm Eastern time.

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Speaker 1: But there during the meeting last Friday, the leadership denied

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Speaker 1: all amendments and kept the bill clean, which is important, Phil,

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Speaker 1: Do you know why, because then they can vote on it,

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Speaker 1: because if they had, if it had to have amendments,

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Speaker 1: it could get pushed back to the Senate and we

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Speaker 1: could be completely screwed. Because we don't want this thing

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Speaker 1: to go to November, because then the world will change

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Speaker 1: in a way that we do not. No, that's true. Okay.

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Speaker 1: All the words I just want to check because I'm

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Speaker 1: extremely hungover and you're making sense are the words. May

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Speaker 1: You're fine, You're doing great, all right. We're also just

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Speaker 1: just by the bye. We're back quarantined again kind of

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Speaker 1: a little bit. We're not allowed in the office, which is,

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Speaker 1: you know, more cases of COVID, more worries, gotta keep

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Speaker 1: steaven now healthy, can't have it sick are you guys?

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Speaker 1: We'll have a Netflix show, um, and so we're back,

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Speaker 1: but fill our pilling. Are allowed to come in the

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Speaker 1: studio and at social distance. And Phil tells me I

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Speaker 1: shouldn't tell all you guys this stuff. He says they

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Speaker 1: don't care. He says that all the time, but particularly

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Speaker 1: about this. They don't care about like our office situation.

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Speaker 1: So people have to completely tuned this out. Anyway, back

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Speaker 1: to the very important life changing once in a lifetime

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Speaker 1: legislation the Great American Outdoors Act. So just for review,

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Speaker 1: the Great American Outdoors that would fully dedicate nine million

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Speaker 1: dollars to the Land Order Conservation Fund every year in perpetuity.

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Speaker 1: And then it would address the twenty million dollar or yes,

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Speaker 1: twenty billion dollars and maintenance backlogs on public plans and

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Speaker 1: waters will be fixing ship out there, okay, fixing it

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Speaker 1: up for you. And so you're listening to this on Tuesday,

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Speaker 1: you need to go and call the capital switchboard two

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Speaker 1: O two two two four three one to one, or

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Speaker 1: you can use the legislator directory at BHA dot com.

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Speaker 1: Go there and find it, find your representatives direct number,

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Speaker 1: or like I said, called that switchboard number two O

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Speaker 1: two to two four three one to one and tell

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Speaker 1: them to pass the Great American Outdoors. I can tell him,

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Speaker 1: I care. Have you done that, y F? Phil? I have? Yeah? Yeah,

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Speaker 1: I look have you? Have you told me you did? Yeah?

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Speaker 1: I thought you were lying. No, I mean I haven't.

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Speaker 1: I did it once a while ago, back before things

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Speaker 1: are like as far along as they were now. It's

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Speaker 1: looking good, Phil. I'm I don't want to be one

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Speaker 1: of those guys who gets in a situation where I'm

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Speaker 1: too confident. I'm usually never too confident. I'm just just

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Speaker 1: the right amount of confident. But at this moment, I'm very,

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Speaker 1: very confident that by the time we talked to you

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Speaker 1: again next week, that we will have a bill headed

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Speaker 1: to Mr Trump's desk for signature. UM. And that's exciting

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Speaker 1: for all of us. So without further ado, we're gonna

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Speaker 1: announce the winner. Thank you so much, the first Light,

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Speaker 1: Thank you too, Nemo, and there's another one, Vortex. We

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Speaker 1: love you all equally. My synapses not firing, that's fine.

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Speaker 1: I'm proud of you for just just just being here.

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Speaker 1: So yeah, soldier through sometimes showing podcasting, some people say poising,

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Speaker 1: it's not a hard job. Check me out right now,

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Speaker 1: you know. I want for for all the listeners who

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Speaker 1: have real jobs, who if you showed up to work

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Speaker 1: drunk or hungover, you would be terminated or face face repercussions.

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Speaker 1: Just just no, no, I got a collared shirt on,

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Speaker 1: you do? Yeah? Sure? Yeah? I never wear a collared shirt.

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Speaker 1: Yeah I got I didn't. I couldn't find any like shoes,

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Speaker 1: so just my like dirty flip flop that's fine, um.

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Speaker 1: But from the waist up, I looked professional. You're doing great. Thanks,

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Speaker 1: Thanks um a lot of people. Thank you again to

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Speaker 1: everybody that sent things in. We appreciate you as always.

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Speaker 1: It's one of the things that makes this show the

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Speaker 1: most fun. It really makes worth getting up in the

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Speaker 1: morning and scratching, like scratching all the dirt out of

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Speaker 1: your eyes and barely being able to see for about

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Speaker 1: an hour and then getting yourself into the office. Um,

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Speaker 1: so what are we gonna do here? So we're gonna

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Speaker 1: start with the Vortex bhind us. Okay, now this is

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Speaker 1: third place. This third place, okay, but these are listeners

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Speaker 1: that you guys should all you're all gonna know. But

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Speaker 1: Mike Peterson, I'm gonna show you this. You've not seen

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Speaker 1: this before film. Okay, I'm gonna show you this. You

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Speaker 1: make sure that I mean, is this going to be

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Speaker 1: are people who cannot see the video? They they're still

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Speaker 1: going to enjoy this? No, okay, it might be worth

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Speaker 1: uploading some of this to like your instant. It's gonna

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Speaker 1: be on instant. Okay, good check it out on Instagram.

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Speaker 1: But it's not gonna you're not gonna have fun at

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Speaker 1: this point. It is Wednesday nine, Token Creek that's where

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Speaker 1: Mike Peterson is. Okay, who disclaim or nothing but feelings

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Speaker 1: were hurt in the making of this movie. I'm worried.

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Speaker 1: There's Mike. He's outside, he's dressed, he has American flag tanks.

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Speaker 1: A little day to be out of the park, do

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Speaker 1: some fishing, maybe get something for the front pan. I

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Speaker 1: couldn't ask for anything better. Yeah, popping up in a

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Speaker 1: white claw is a lemon? I think so. I think

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Speaker 1: it was a mango mangoes. Oh it is mad. Okay,

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Speaker 1: it would be a pretty good idea for a dog's name.

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Speaker 1: Not wrong. Shout out to Mike. What in the hell

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Speaker 1: is that dude didn't even bring a fishing pole? How

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Speaker 1: the hell is he's supposed to catch me dinner? Damn,

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Speaker 1: I'm gonna catch without a pole? Well, you cursed? Is

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Speaker 1: Is this some bitch drinking coffee? Starbucks coffee? We're gonna

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Speaker 1: fast forward to where he's now. He is dressed like

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Speaker 1: he's not dressed like a hipster. Okay, it's all an

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Speaker 1: oriole today. Still a hot drinking his coffee. Oh my god,

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Speaker 1: is that guy fishing? It's gonna come out here, torture fish,

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Speaker 1: poke holes in their mouth and that shirt. He he

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Speaker 1: totally voted for Trump. Well, I mean, at least Trump

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Speaker 1: says he's going to sign the Great American Outdoors Act. Oh,

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Speaker 1: I can't believe I found something I like about the guy.

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Speaker 1: At least he's having fun starring Mike Peterson, oh Man

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Speaker 1: and Mike Mike Peterson. Okay, that was great. Good job,

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Speaker 1: Mike Peterson is fantastic. Clause feels not clapping lapping the

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Speaker 1: two of us. It's not gonna sound good. Yeah, Mike

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Speaker 1: Peterson's like his piece of art was trying to tell

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Speaker 1: us that we're bringing people together. So gratulations, Mike Peters.

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Speaker 1: You're gonna be a parabor tex Binos. Send them right

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Speaker 1: to your damn house. You can use them to do

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Speaker 1: whatever you do. Who knows what you do. But thanks

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Speaker 1: for listening. As always, we appreciate you, buddy. I feel like, like, yeah,

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Speaker 1: I don't know if Mike's ever want anything, but he

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Speaker 1: always tries, and in this case he made it. He

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Speaker 1: made a good joke, He made a good funny. Now

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Speaker 1: this one is gonna be If you'll remember Greg Morrise

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Speaker 1: from his win. He was the guy that sent us

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Speaker 1: the video of him and his house in his robe,

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Speaker 1: and he had the picture of frame frame picture of squeakers.

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Speaker 1: Remember him recipe squeakers. This is the same guy. So

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Speaker 1: he's he's he's a second time winner. He knows what

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Speaker 1: makes us tick. And so he sent a video in

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Speaker 1: where he was calling. We said to call. I think

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Speaker 1: he didn't quite pick up what we meant by calling,

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Speaker 1: and so he made a video that goes a little

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Speaker 1: something like this. Hello called first Light. Nate answered, I'm good.

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Speaker 1: Thanks for going on. Do you guys um sell any

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Speaker 1: pants that like are okay to poop in? Sorry? Can

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Speaker 1: you repeat that? Man? Do you see pants that are

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Speaker 1: like okay to poop in? It depends on how running

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Speaker 1: it is, you know. No, I'm trying to see her

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Speaker 1: so because like I got this issue when I go

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Speaker 1: out in the woods and like I always poop my pants.

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Speaker 1: Oh man, that's too bad. So you do you don't?

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Speaker 1: You don't sell anything that's like okay to poop in.

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Speaker 1: I can't say i'd recommend any pant, but I'm sure

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Speaker 1: they'd hold up just fine to your normal set. Okay,

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Speaker 1: can I can you can I leave that as a

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Speaker 1: recommendation or something that like it's maybe something you guys

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Speaker 1: could look into you guys come highly recommended. That's the

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Speaker 1: only reason I'm calling you. Yeah, I'll mark it down, man,

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Speaker 1: No problem. What's your name? It's um Janice and last

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Speaker 1: names Ronella. Okay, is really the star of this It

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Speaker 1: is really the star of that show. So now he's out,

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Speaker 1: he says, call himber two. He's at masson Ault State

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Speaker 1: Park in Plymouth, Massachusetts as LWC I funded. But scouting

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Speaker 1: right now. Um, the onyx app, you guys, do you

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Speaker 1: guys have like a feature that shows where the deer are?

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Speaker 1: What do you mean by that? Like where the deer are?

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Speaker 1: Like don't don't you guys have like like a GPS

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Speaker 1: system that shows where the deer are? Like, um, like no,

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Speaker 1: like you where a dear would be on on the map? Yeah,

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Speaker 1: like if like where he is? Like I opened up

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Speaker 1: on X maps and then it says there's a deer

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Speaker 1: here and a deer here. No, no, we we don't

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Speaker 1: have that, all right? Can I can I put in

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Speaker 1: a recommendation for that that question? And uh forget he

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Speaker 1: is heard? Anything that can be done to you know,

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Speaker 1: considering putting something that you know you were the dear. Yeah,

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Speaker 1: I think that would be like a huge, huge help

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Speaker 1: for like I don't know, for trying to find these

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Speaker 1: these employees deserve raise customers always real, definitely. All right,

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Speaker 1: can I give you my name? My name's my name's

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Speaker 1: My first name is Phil son of a. Last name

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Speaker 1: is engineer silence. All right, thank you so much. You

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Speaker 1: have a YouTube, man. Third call is that Greg. I'm

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Speaker 1: a part of your district and I was just calling

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Speaker 1: to encourage you to vote on the Great American Outdoors

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Speaker 1: Act with no changes or um clauses in there, just

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Speaker 1: as the bill states. So thank you very much and

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Speaker 1: appreciate it. And then there was an ending American Probably

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Speaker 1: all right, everybody, well done, Greg. I was going to

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Speaker 1: give you the NEMO tent, but I felt like I

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Speaker 1: want to I'm gonna reverse and give you the first

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Speaker 1: like kid, and I want you I want Greg, I

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Speaker 1: want you to call Nate after shifting in the pants.

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Speaker 1: I want you to just call Nate and he'll help

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Speaker 1: you with your kid. Okay, So that was well done, man, Yeah,

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Speaker 1: I um well done. I'd say that was that. That

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Speaker 1: was a there's some prank calls I think that are

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Speaker 1: just just mean, unnecessary cruel. I thought that was that

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Speaker 1: was reasonable. Reason on the dude from Hoyt is my favorite.

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Speaker 1: I'll put that in the queue. Yes, sure, And then

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Speaker 1: you feel bad because I when I used to work

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Speaker 1: at Yeah yeah, So the customer service people just want

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Speaker 1: to give him a hug when you see him, like,

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Speaker 1: I can never do it. She could. I can't do it.

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Speaker 1: I could never do it. There's no way, no I

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Speaker 1: we at one time when I was a kid, I

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Speaker 1: prank called a Walmart with some friends and I said

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Speaker 1: I was allergic to follic acid and I needed a

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Speaker 1: breakfast cereal that did not contain follic acid. And we

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Speaker 1: had this woman on the line for over an hour. Well,

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Speaker 1: she looked at the ingredients of every cereal. It turns

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Speaker 1: out they all have falic acid. This poor woman, probably

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Speaker 1: making minimum wage at a Walmart. I feel so bad

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Speaker 1: about she probably went home she was like, Oh what

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Speaker 1: a day, honey. He's like, what happened? Some douche bag?

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Speaker 1: All that maybe go over folic acid for an hour.

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Speaker 1: We've all we've all had things. We also like the

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Speaker 1: the reaction to Janice, right right, all right? If he

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Speaker 1: didn't already figure this out, all right? Well, thanks to

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Speaker 1: Nate from first light and to Mike and Greg and

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Speaker 1: the last but not leasing. Now, this last one is uplifting.

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Speaker 1: It that's not really funny at all, um, but it's uplifting.

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Speaker 1: And so the final entry it's another video. It's a

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Speaker 1: long video, so I'm not gonna be able to play

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Speaker 1: the whole thing for you, but I did ask the

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Speaker 1: guys from Get Connected Outdoors to send me a clip

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Speaker 1: that I could play that they felt it was the

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Speaker 1: best part of their video. Essentially, it's a four minute

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Speaker 1: video of all types of people from all shapes and sizes,

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Speaker 1: and they're all out there saying like I am recreated,

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Speaker 1: like playing golf and swimming and ship like, oh look

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Speaker 1: here I am on the place. It's really good. Trust me.

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Speaker 1: That's I probably didn't do it. Sorry, guys, I didn't

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Speaker 1: do it. If you're like us and you grew up

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Speaker 1: playing on local playgrounds, If you enjoyed the great outdoors

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Speaker 1: through active these such as hiking, fishing, canoeing, or hunting,

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Speaker 1: or your home, your children for grandchildren will be able

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Speaker 1: to enjoy any of these things, then the Great American

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Speaker 1: Outdoors Act is one that you should polly support birds

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Speaker 1: in the background. Will you be contributing to the betterment

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Speaker 1: of society for generations to come. You will also be

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Speaker 1: saying yes to the betterment of the lands, waters, and animals.

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Speaker 1: We don't care for simling. Thank you and remember to

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Speaker 1: get connected outdoors. Boom wow who that's like an ad

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Speaker 1: I would see on YouTube. Unbelievable, filled in and clap

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Speaker 1: at all. That was great man. Um, let's see I

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Speaker 1: there's there's another clip because it keeps it goes for

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Speaker 1: a while. What else we got here? Great American Outdoors

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Speaker 1: Act is made up of very important parts the Land

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Speaker 1: and Water Conservation Fund, your marks million dollars per year

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Speaker 1: for things such as creating access to our public lands

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00:19:58,840 --> 00:20:02,399
Speaker 1: and waters, for fiding protection for our drinking water supplies,

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Speaker 1: providing ball fields and playgrounds for our local cities and

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00:20:05,720 --> 00:20:10,359
Speaker 1: parks across the country, and many more conservation efforts. The

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Speaker 1: other park addressed divert maintenance projects and federal lands across

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Speaker 1: the country. The projects that will be included are things

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Speaker 1: such as fixing roads in our various national parks and

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Speaker 1: work on natural population restoration projects for various fishing game animals,

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Speaker 1: the removal of graffitia trash throughout hundreds of properties, and

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Speaker 1: much more and these projects will be overseen by the

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Speaker 1: National Park Service. The forests they got logoishing is great

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Speaker 1: du europe land management of Indian education and will be

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Speaker 1: funded for five somebody right until we got billion dollars

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Speaker 1: to the National Park Service and the public land Legacy restorations.

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Speaker 1: Dude is awesome food man, chee fucking tattoos. Yeah, feeling

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Speaker 1: good about the well researched. If you watch the news,

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Speaker 1: you might think that videos like this aren't even possible,

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Speaker 1: that people couldn't even be inspired to make such a

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Speaker 1: piece of work. But here they are because of the

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Speaker 1: Great American Indoors Act, because of you feel because of HC.

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Speaker 1: And so thank you everybody. Thank you to the guys

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Speaker 1: that get connected outdoors Um, Alex and Zach I believe

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Speaker 1: right yep, Zack and Alex for for doing that. You

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Speaker 1: should probably go find them on YouTube and while share

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Speaker 1: the length of that video so you can watch the

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Speaker 1: whole thing. It is really cool for them to not

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Speaker 1: only I wonder if they had licensed that music, but

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Speaker 1: get all the people in their lives together to celebrate

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Speaker 1: the Great American Outdoors Act. So you guys are gonna

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Speaker 1: I'll try to make sure we get you a couple

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Speaker 1: of of Nemo tents because there's two of you that

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Speaker 1: made the video. Um, we'll do what we can for that.

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Speaker 1: Either way, you're a winner and winning is all that

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Speaker 1: matters here at play. The jingle is there? No, no,

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Speaker 1: we don't have a jingle fan, Okay, there's no jingles, um,

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Speaker 1: So make sure you make a phone call, make sure

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Speaker 1: you read an email, make sure you post on social media,

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Speaker 1: and make sure you're talking about the great American doors,

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Speaker 1: that great American doors. Act Boy, Phil, this is gonna

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00:22:12,280 --> 00:22:14,400
Speaker 1: be an edit for you. He just used to leave

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Speaker 1: all the mistakes I've made in. That's fine, though, I'm

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Speaker 1: gonna ask for a raise. This has been drinking too much.

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Speaker 1: It was accidental. I didn't I was working hard for

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Speaker 1: my family. Okay, Um, But without further ado, we got

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Speaker 1: a long one today, so we'll get to the interview

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Speaker 1: ports in the show. I will just say this, this

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Speaker 1: is one of my favorite conversations I've had in a while,

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Speaker 1: and there's a lot of reasons for that. Now, Phil,

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Speaker 1: you haven't have you listened to it yet? Now yet

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Speaker 1: you're you will right after this. It is on the

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Speaker 1: docket for the day all right, you're gonna love it.

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Speaker 1: We I doctor. I met Dr Dan Staylor actually conveniently

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Speaker 1: at the b h A ND Virtual Rendevoo. Met is

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Speaker 1: a is a term. That's how that's how we meet

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Speaker 1: in this year. Loosely. Um so, but he's a predator

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Speaker 1: biologists out there in the Yellowstone National Park, and I

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Speaker 1: would just say this we've had We've talked a lot

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Speaker 1: about Yellowstone. We talked a lot about in the conversation

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Speaker 1: with Dan, like what it is, what it means to people.

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Speaker 1: Is it flawed in its presentation of wild places or

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Speaker 1: is it an ambassador of wild places to people that

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Speaker 1: can't go there or don't go there, don't live in proximity.

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Speaker 1: Regardless of that, every time I go to Yellowston National Park,

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00:23:24,600 --> 00:23:26,920
Speaker 1: it shows off in some way. It shows how why

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00:23:26,920 --> 00:23:30,080
Speaker 1: it's a special place. It shows why people need to

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Speaker 1: visit there and see it before they die. So, um

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00:23:34,080 --> 00:23:35,919
Speaker 1: that maybe a little bit to present. We're all gonna die,

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00:23:35,960 --> 00:23:37,399
Speaker 1: but before you do, you should go to the Yellston

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Speaker 1: National Park. We went just for a like a half

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Speaker 1: a day early in the morning, got up, drove to

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Speaker 1: meet Dan. We're gonna go use some GPS data point clusters.

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Speaker 1: To go see possible kill site from a mountain lion

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Speaker 1: named M to two zero that they've been tracking since May.

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Speaker 1: So this is a mountain lion by the bye, that's

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Speaker 1: that's had seventeen kills in the sense may since I

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Speaker 1: was like May five seventeen, it's killed seventeen animals. UM,

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Speaker 1: mostly elk calves or neonates as they call them. But

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00:24:10,840 --> 00:24:13,359
Speaker 1: the neo ate just means under a month old. And

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00:24:13,440 --> 00:24:15,080
Speaker 1: so it was cool to go and do that. But

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Speaker 1: along the way we saw coyote making a scrape, We

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Speaker 1: saw a bunch of antelope going to water across this

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Speaker 1: this beautiful vista we had. UM, we then did find

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Speaker 1: the kill site. We then found a police piece of

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Speaker 1: black obsidian napped arrowhead that you would never find anywhere else.

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Speaker 1: I've never found anywhere else right where we sat to

423
00:24:39,840 --> 00:24:43,480
Speaker 1: the podcast, and UM, a bunch of elk came through

424
00:24:43,680 --> 00:24:47,040
Speaker 1: during it. You hear the interruption now we had So

425
00:24:47,280 --> 00:24:49,399
Speaker 1: it's just we were there for half a morning. UM

426
00:24:49,480 --> 00:24:51,520
Speaker 1: found some elk sheds on the way out, things like that.

427
00:24:51,560 --> 00:24:54,440
Speaker 1: So Yellowstone is always showing off. But this, this conversation

428
00:24:54,480 --> 00:24:56,959
Speaker 1: is important for a lot of reasons. It's important because

429
00:24:57,520 --> 00:24:59,520
Speaker 1: we did a little in the field work, we learned

430
00:24:59,760 --> 00:25:03,080
Speaker 1: how important the work of guys like Dr Dan are.

431
00:25:03,720 --> 00:25:06,439
Speaker 1: And then we talked about predators, why they should be

432
00:25:06,440 --> 00:25:08,359
Speaker 1: in the landscape, what they mean to us, what we

433
00:25:08,480 --> 00:25:11,120
Speaker 1: learned about them, what we have yet to learn about them,

434
00:25:11,160 --> 00:25:15,240
Speaker 1: and why they kind of start and end the conversation

435
00:25:15,240 --> 00:25:20,119
Speaker 1: in our culture about managing wildlife through hunting. Why we

436
00:25:20,119 --> 00:25:22,600
Speaker 1: should why we shouldn't. Nobody's arguing that we should kill

437
00:25:22,720 --> 00:25:25,359
Speaker 1: deer or not kill deer. In most places, there's a few,

438
00:25:25,800 --> 00:25:28,640
Speaker 1: but the argument whether we should hunt and kill grizzly bears,

439
00:25:28,720 --> 00:25:32,920
Speaker 1: hunt and killed wolves um rages on. And so we

440
00:25:32,920 --> 00:25:34,879
Speaker 1: we addressed a lot of those topics you will enjoy.

441
00:25:34,880 --> 00:25:37,119
Speaker 1: I'm gonna take you out to the field to the

442
00:25:37,160 --> 00:25:41,120
Speaker 1: middle of nowhere in Yellis from National Park, where Dan

443
00:25:41,160 --> 00:25:49,199
Speaker 1: and I are trying to find a cougar kill. Enjoy.

444
00:25:50,560 --> 00:25:55,800
Speaker 1: So Dan, we're overlooking gardener, right, gardener, gardener Montin I

445
00:25:55,800 --> 00:25:58,640
Speaker 1: always wonder if I'm in Wyoming. We are right now

446
00:25:58,760 --> 00:26:01,919
Speaker 1: actually at the parallel straight down to our right, so

447
00:26:01,960 --> 00:26:04,280
Speaker 1: we're hard to say if we're in Montano Wamy right

448
00:26:04,280 --> 00:26:09,239
Speaker 1: now we're right on the um. Quickly describes just like

449
00:26:09,520 --> 00:26:11,679
Speaker 1: what we're looking at here. So we're looking at what

450
00:26:11,680 --> 00:26:15,520
Speaker 1: we do is the gardener basin, uh, the northern range

451
00:26:15,560 --> 00:26:18,720
Speaker 1: of of yellow Stone, and UH it is one of

452
00:26:18,760 --> 00:26:22,959
Speaker 1: the premier wintering areas for UH, A large a lot

453
00:26:23,040 --> 00:26:26,600
Speaker 1: of yellow Stones, ungulates, um, elk, you know, the hoofed animals,

454
00:26:26,600 --> 00:26:29,119
Speaker 1: the yelk, the prong horn, big corn sheet, mule deer,

455
00:26:29,440 --> 00:26:32,920
Speaker 1: some white tailed deer, bison, of course. UH. And you're

456
00:26:32,960 --> 00:26:34,440
Speaker 1: looking at it right here. We're in the heart and

457
00:26:34,480 --> 00:26:36,840
Speaker 1: soul of it. And UH it's incredibly important part of

458
00:26:36,840 --> 00:26:40,920
Speaker 1: this system. UH sustains a lot of the migratory herds

459
00:26:40,960 --> 00:26:42,720
Speaker 1: that use this area and depend upon it on winter

460
00:26:42,800 --> 00:26:47,240
Speaker 1: because of its lower elevation, less snowpack forage availability. UM.

461
00:26:47,320 --> 00:26:49,119
Speaker 1: Of course we're here in July, so we're looking at

462
00:26:49,400 --> 00:26:52,400
Speaker 1: summer range starting to dry out. We've had some wet

463
00:26:52,480 --> 00:26:55,199
Speaker 1: you know, pretty wet spring, but in early summer, but

464
00:26:55,240 --> 00:26:57,399
Speaker 1: starting to get round as it does. You got this

465
00:26:57,440 --> 00:26:59,720
Speaker 1: little band of prong horn here and this is you

466
00:26:59,760 --> 00:27:01,960
Speaker 1: know where you see a lot of the prong horn summering.

467
00:27:02,359 --> 00:27:04,959
Speaker 1: In the wintertime, they'll also settle into these lowlands right

468
00:27:04,960 --> 00:27:07,960
Speaker 1: here in front of us. But UM, Yellowstone River of course,

469
00:27:07,960 --> 00:27:11,040
Speaker 1: cuts out of the park right there. Um, and that's

470
00:27:11,040 --> 00:27:12,960
Speaker 1: the court of that migratory funnel for a lot of

471
00:27:12,960 --> 00:27:16,480
Speaker 1: those uh ulis, particularly the elk herd, the Northern elk

472
00:27:16,480 --> 00:27:20,960
Speaker 1: herd kind of one of the most uh controversial, culturally

473
00:27:21,880 --> 00:27:24,720
Speaker 1: significant elk herds in the region. Really always has been.

474
00:27:25,080 --> 00:27:27,040
Speaker 1: It's always been a big source of debate. We'll talk

475
00:27:27,080 --> 00:27:30,800
Speaker 1: about that later, but um, but yeah, it's quite a

476
00:27:30,880 --> 00:27:33,159
Speaker 1: quite an area, is you know. I always think of

477
00:27:33,160 --> 00:27:35,560
Speaker 1: this area sort of our you know, our American serengetti.

478
00:27:36,359 --> 00:27:37,879
Speaker 1: I live just across the way there. You can kind

479
00:27:37,880 --> 00:27:38,920
Speaker 1: of see my house on the other side of the

480
00:27:38,960 --> 00:27:41,639
Speaker 1: valley above the town of Gardener there and uh, you know,

481
00:27:41,640 --> 00:27:44,000
Speaker 1: it's not uncommon to look down and see you know,

482
00:27:44,119 --> 00:27:47,920
Speaker 1: everything bison, pronghorn, big horn, sheet deer, alcohol within your

483
00:27:48,680 --> 00:27:52,160
Speaker 1: uh have you shed packs of wolves? Use these uh cougars.

484
00:27:52,680 --> 00:27:54,640
Speaker 1: It's all cougar country. Do you ever feel like you're

485
00:27:54,640 --> 00:27:57,960
Speaker 1: in a time machine? Absolutely? I mean childhood dream living

486
00:27:57,960 --> 00:27:59,960
Speaker 1: in a place like this where you could go back

487
00:28:00,000 --> 00:28:02,800
Speaker 1: in time and see what the landscape looked across our

488
00:28:02,880 --> 00:28:06,400
Speaker 1: great country. Um, we've got a vignette of it right here. Yeah,

489
00:28:06,400 --> 00:28:09,879
Speaker 1: this river just kind of connects everything and brings everything

490
00:28:09,920 --> 00:28:12,240
Speaker 1: together to stand here and no, we're headed to a

491
00:28:12,280 --> 00:28:15,040
Speaker 1: possible kill site for a mountain lion and see a

492
00:28:15,119 --> 00:28:18,880
Speaker 1: fawn antelope and a couple of a couple of doughs.

493
00:28:18,920 --> 00:28:21,320
Speaker 1: By the looks of it. Um, this is you know,

494
00:28:21,840 --> 00:28:24,159
Speaker 1: you never know what you're gonna see in Yellowstone and

495
00:28:24,200 --> 00:28:28,080
Speaker 1: you've kind of got back door pass. I imagine, absolutely

496
00:28:28,280 --> 00:28:31,280
Speaker 1: feel very lucky to live here. Let's go see what

497
00:28:31,280 --> 00:28:35,439
Speaker 1: we can find. We've got a coyote about what seventy

498
00:28:35,760 --> 00:28:39,280
Speaker 1: yards He didn't even seem like he cares much about us.

499
00:28:39,320 --> 00:28:41,920
Speaker 1: What's he doing? It looks like a younger coy out,

500
00:28:42,000 --> 00:28:45,120
Speaker 1: maybe a yearling or something. He's a could be in

501
00:28:45,120 --> 00:28:46,960
Speaker 1: this area because there's a carcass here. We're not. We've

502
00:28:46,960 --> 00:28:50,680
Speaker 1: got sixty yards from that cluster of that cougars kill site,

503
00:28:50,680 --> 00:28:53,800
Speaker 1: and so he might be um lingering around. It could

504
00:28:53,800 --> 00:28:55,320
Speaker 1: be just a good spot for him. But I just

505
00:28:55,320 --> 00:28:58,840
Speaker 1: some do a little scrape scent mark there not that

506
00:28:58,840 --> 00:29:00,600
Speaker 1: far away, so he probably sees us, and maybe he's

507
00:29:00,640 --> 00:29:02,760
Speaker 1: just curious. Of course, these guys in the park are

508
00:29:02,760 --> 00:29:05,080
Speaker 1: and getting bullets lobbed at him. Some a little bit

509
00:29:05,160 --> 00:29:07,880
Speaker 1: more curious, a little more curious. It's like he's got

510
00:29:07,920 --> 00:29:09,840
Speaker 1: a little bit of a scrappy tail. There's summer coat

511
00:29:09,880 --> 00:29:13,760
Speaker 1: and he goes trotting off. It looks like a young one.

512
00:29:14,080 --> 00:29:16,360
Speaker 1: I mean, I know that there's an adversary relationship between

513
00:29:16,440 --> 00:29:19,480
Speaker 1: wolves and yeah, yeah, you know, if there's a Mountain

514
00:29:19,480 --> 00:29:22,480
Speaker 1: lion kill site today, they will they will kill coyotes

515
00:29:22,520 --> 00:29:24,880
Speaker 1: and they'll eat them. Unlike wolves, wolves just kill him

516
00:29:24,880 --> 00:29:27,000
Speaker 1: to kind of get him out of the picture. Cougars

517
00:29:27,000 --> 00:29:29,720
Speaker 1: will actually feed on him and it's typically is around

518
00:29:29,720 --> 00:29:32,520
Speaker 1: to kill site. They're not actively hunting them, but they're opportunistic.

519
00:29:33,360 --> 00:29:35,400
Speaker 1: Of course, you can hear ground squirrels right now around us,

520
00:29:35,400 --> 00:29:38,800
Speaker 1: so he's probably hunting ground squirrels. Yeah, he does. It's

521
00:29:38,800 --> 00:29:40,800
Speaker 1: so interesting to be in a place like this and

522
00:29:40,840 --> 00:29:43,240
Speaker 1: to see a coyer that normally, if he was living

523
00:29:43,280 --> 00:29:45,680
Speaker 1: on a ranch down in the valley, he gone gone,

524
00:29:47,040 --> 00:29:52,720
Speaker 1: be gone, or he'd be gone. It is yeah, yeah, exactly,

525
00:29:53,120 --> 00:29:58,360
Speaker 1: yeah site. That is so what we're doing here, Ben

526
00:29:58,480 --> 00:30:02,920
Speaker 1: is we've got um oh maybe ten or so GPS

527
00:30:03,000 --> 00:30:06,440
Speaker 1: points that were logged by the caller that this male

528
00:30:06,520 --> 00:30:10,120
Speaker 1: lion wears his numbers M two twenty we callered him

529
00:30:10,120 --> 00:30:13,200
Speaker 1: this winner. Um. We actually called him out by Tower Falls.

530
00:30:13,240 --> 00:30:16,520
Speaker 1: So it's a good twenty some one miles UM to

531
00:30:16,600 --> 00:30:19,680
Speaker 1: the south of us here, and that was probably the

532
00:30:19,680 --> 00:30:21,840
Speaker 1: core of his winter range. He was about I think

533
00:30:21,880 --> 00:30:24,160
Speaker 1: we aged him about three and a half four years

534
00:30:24,200 --> 00:30:27,200
Speaker 1: of age. It was about a hundred and forty pounds UM.

535
00:30:27,320 --> 00:30:29,680
Speaker 1: And you know that's a younger Tom here. He's stuck

536
00:30:29,680 --> 00:30:32,600
Speaker 1: around this summer. So we've seen too in our population

537
00:30:32,720 --> 00:30:35,840
Speaker 1: have right now, UM, a bunch of younger males coming

538
00:30:35,840 --> 00:30:38,680
Speaker 1: into this area. We did catch just the other day

539
00:30:38,680 --> 00:30:40,440
Speaker 1: over on that cliff band and back of us a

540
00:30:40,520 --> 00:30:44,280
Speaker 1: big old, gnarly scarred up um mature tom one of

541
00:30:44,320 --> 00:30:47,240
Speaker 1: our remote cameras. So he's probably the king around here.

542
00:30:47,240 --> 00:30:49,280
Speaker 1: But these younger males are coming in and sorting out

543
00:30:49,320 --> 00:30:52,240
Speaker 1: where they might slip in and establish a territory. And

544
00:30:52,280 --> 00:30:54,800
Speaker 1: this male cougar we've been following the last sixties some

545
00:30:54,880 --> 00:30:58,480
Speaker 1: odd days for predation work. UM, he's ranged everywhere from

546
00:30:58,560 --> 00:31:03,400
Speaker 1: here uh out about fifteen twenty miles that way down

547
00:31:03,480 --> 00:31:05,880
Speaker 1: into the Yellowstone River quarter in the Black Canyon of

548
00:31:05,880 --> 00:31:07,840
Speaker 1: the Yellowstone which is up and over that ridge right

549
00:31:07,880 --> 00:31:10,960
Speaker 1: behind us. UM and he's just been looping around here

550
00:31:11,120 --> 00:31:14,600
Speaker 1: for summer, making his kills, making his living and established

551
00:31:14,600 --> 00:31:18,440
Speaker 1: maybe his territory. UM. And this is the last cluster

552
00:31:18,520 --> 00:31:23,160
Speaker 1: of our predation sequence. So uh. Ultimately the objective of

553
00:31:23,200 --> 00:31:26,600
Speaker 1: this work has been to understand cougar food habits and

554
00:31:26,640 --> 00:31:29,520
Speaker 1: predation patterns and kill rate. You know, how often are

555
00:31:29,520 --> 00:31:34,160
Speaker 1: they killing? What are they feeding on? Uh? And that

556
00:31:34,280 --> 00:31:37,560
Speaker 1: feeds into our long term monitoring. That then we can

557
00:31:37,640 --> 00:31:42,920
Speaker 1: more accurately understand what role do cougars play here and Yellowstone? Well,

558
00:31:42,960 --> 00:31:45,920
Speaker 1: I mean too, you know how many cluster sites like

559
00:31:45,960 --> 00:31:49,640
Speaker 1: this will you visit on a single line in that time? Yeah?

560
00:31:49,640 --> 00:31:51,840
Speaker 1: And over that sixty days? This is a guess without

561
00:31:51,880 --> 00:31:54,320
Speaker 1: looking at the numbers, I think a couple hundred clusters.

562
00:31:54,320 --> 00:31:57,400
Speaker 1: We've searched some clusters, you know. We run the data

563
00:31:57,440 --> 00:31:59,840
Speaker 1: that was Basically the way these GPS callers work is

564
00:31:59,840 --> 00:32:03,200
Speaker 1: they a UM last about two years based on how

565
00:32:03,200 --> 00:32:05,600
Speaker 1: we have a program that's dictated by the battery life

566
00:32:05,960 --> 00:32:11,120
Speaker 1: of the caller. It is getting a fix every hour UM,

567
00:32:11,160 --> 00:32:15,480
Speaker 1: around the clock UM, and it uploads the data via

568
00:32:15,520 --> 00:32:18,400
Speaker 1: a satellite that we can access on the computer so

569
00:32:18,440 --> 00:32:20,480
Speaker 1: we can check in. It's not real time but it's

570
00:32:20,560 --> 00:32:23,160
Speaker 1: usually lags by twelve to twenty four hours. What we

571
00:32:23,200 --> 00:32:24,680
Speaker 1: do is we wait for a better week's worth of

572
00:32:24,800 --> 00:32:28,600
Speaker 1: data to to accumulate, then we run it through a

573
00:32:29,520 --> 00:32:33,280
Speaker 1: uh what we call a cluster model that basically identifies

574
00:32:33,360 --> 00:32:37,000
Speaker 1: any cluster where you have two points GPS points within

575
00:32:37,000 --> 00:32:41,840
Speaker 1: two of one another and within six days. So what's

576
00:32:42,400 --> 00:32:45,480
Speaker 1: beautiful about this technology to study predation cougars is when

577
00:32:45,480 --> 00:32:47,800
Speaker 1: a cougar makes a kill, you know that you tend

578
00:32:47,800 --> 00:32:50,120
Speaker 1: to cash it, and if they're not displaced by a

579
00:32:50,160 --> 00:32:52,719
Speaker 1: bear pack of wolves, they will tend to stay on

580
00:32:52,720 --> 00:32:54,720
Speaker 1: it for several days until it's used up. Of course,

581
00:32:54,720 --> 00:32:57,120
Speaker 1: that depends on the size. If it's a small newborn fawn,

582
00:32:57,200 --> 00:32:59,280
Speaker 1: they might only be there for half a day before

583
00:32:59,320 --> 00:33:02,000
Speaker 1: it's gone. If it's a you know, an adult cow walk,

584
00:33:02,040 --> 00:33:04,680
Speaker 1: they might be there for four or five days. And

585
00:33:05,240 --> 00:33:08,400
Speaker 1: but cougar clusters are usually really or kills are easily

586
00:33:08,440 --> 00:33:10,480
Speaker 1: to identify with cougars because once they make a cluster,

587
00:33:10,560 --> 00:33:12,640
Speaker 1: they're really kind of hone in on it once in

588
00:33:12,680 --> 00:33:15,400
Speaker 1: a while, and particularly with males, they tend to be

589
00:33:15,400 --> 00:33:19,280
Speaker 1: a little bit more exploratory and travel during kill events

590
00:33:19,280 --> 00:33:22,400
Speaker 1: where they'll make a kill. For example, this male killed

591
00:33:22,720 --> 00:33:24,680
Speaker 1: a couple of weeks ago an adult cowalk down below

592
00:33:24,760 --> 00:33:27,600
Speaker 1: us here um, and he would go all the way

593
00:33:27,680 --> 00:33:31,000
Speaker 1: during the day, travel all the way up oh a

594
00:33:31,080 --> 00:33:33,800
Speaker 1: mile and a half that way to bed up in

595
00:33:33,800 --> 00:33:37,160
Speaker 1: the cliffs. I mean just And for cougar they're they're

596
00:33:37,200 --> 00:33:39,760
Speaker 1: all about concealing and being secretive, and that's a big

597
00:33:39,760 --> 00:33:42,240
Speaker 1: part of their success, particularly the lansk like a landscape

598
00:33:42,240 --> 00:33:44,600
Speaker 1: like Yellowstone where you get grizzly bears, black bears and

599
00:33:44,600 --> 00:33:47,200
Speaker 1: wolves that are always trying to find food and they're

600
00:33:47,200 --> 00:33:51,080
Speaker 1: easily easily can displace sugars, and so he is, you know,

601
00:33:51,280 --> 00:33:54,160
Speaker 1: his mo has to get somewhere safe and secure, out

602
00:33:54,160 --> 00:33:56,840
Speaker 1: of sight. Um. And males tend to do that. Sometimes

603
00:33:56,920 --> 00:33:59,160
Speaker 1: males will also feed for a day and then do

604
00:33:59,200 --> 00:34:01,640
Speaker 1: a big travel for a day and then come back

605
00:34:01,640 --> 00:34:04,600
Speaker 1: to a kill site. Females that make kills, female cuers

606
00:34:04,600 --> 00:34:07,600
Speaker 1: tend to stick right there. Um. They also can get

607
00:34:07,600 --> 00:34:09,560
Speaker 1: displaced of course too, and they have the whole risk

608
00:34:09,600 --> 00:34:12,239
Speaker 1: if they've got kittens where there's a risk of mortality.

609
00:34:12,280 --> 00:34:14,959
Speaker 1: There if a pack of wolves or another cougar even

610
00:34:15,080 --> 00:34:18,520
Speaker 1: or a black bear grizzly beer comes in but um.

611
00:34:18,560 --> 00:34:21,120
Speaker 1: But yeah, so a couple hundred clusters over the last

612
00:34:21,160 --> 00:34:24,000
Speaker 1: sixty days. Uh. You know, I don't know how many kills. Again,

613
00:34:24,040 --> 00:34:25,560
Speaker 1: I'd have to look and see how many of that is.

614
00:34:25,600 --> 00:34:29,240
Speaker 1: But this male has been killing primarily elk um. Of course,

615
00:34:29,760 --> 00:34:32,560
Speaker 1: this study was set up designed during the peak having

616
00:34:32,680 --> 00:34:35,080
Speaker 1: period June first and Yale soon. It is thought to

617
00:34:35,120 --> 00:34:37,640
Speaker 1: be sort of our our major you know, pulse of

618
00:34:37,640 --> 00:34:40,680
Speaker 1: of elk calves average um caving date. Some are born

619
00:34:40,760 --> 00:34:42,719
Speaker 1: late May, some are you know, born last couple of

620
00:34:42,760 --> 00:34:45,600
Speaker 1: weeks even um, but usually around June one, and so

621
00:34:45,640 --> 00:34:48,200
Speaker 1: we kind of set this up to understand what, you know,

622
00:34:48,239 --> 00:34:50,600
Speaker 1: how many elk halves are getting. Um. So his diet

623
00:34:50,640 --> 00:34:53,719
Speaker 1: has been I would say, primarily elk calves. But he's

624
00:34:53,760 --> 00:34:57,680
Speaker 1: killed a couple of spike bowls yearlings, um bull elk.

625
00:34:58,120 --> 00:35:00,680
Speaker 1: He uh killed the mule deer phone on last week,

626
00:35:00,760 --> 00:35:05,320
Speaker 1: newborn muleer fawn. Um. You know, cougar diets pretty pretty buried.

627
00:35:05,400 --> 00:35:07,759
Speaker 1: He really kind of depends what's available to them. But

628
00:35:07,880 --> 00:35:09,920
Speaker 1: this time of the year, young of the year, Uh,

629
00:35:10,040 --> 00:35:13,799
Speaker 1: fawns and calves are they're just easy, they're safer pray

630
00:35:13,880 --> 00:35:17,520
Speaker 1: package for them to take down and handle and um

631
00:35:17,640 --> 00:35:19,879
Speaker 1: and uh so yeah, that's kind of what we tend

632
00:35:19,880 --> 00:35:22,319
Speaker 1: to find. It's not a bad place for cougar to live, No,

633
00:35:22,600 --> 00:35:25,520
Speaker 1: not at all. It's gorgeous right here, and they have

634
00:35:25,600 --> 00:35:27,960
Speaker 1: access to good hunting grounds but also you know, good

635
00:35:28,040 --> 00:35:38,759
Speaker 1: escape train very much part of it. So we're so

636
00:35:38,800 --> 00:35:42,440
Speaker 1: you think that it's possible from here, and we're in

637
00:35:42,440 --> 00:35:46,680
Speaker 1: this patch of juniper and this looks like probably a

638
00:35:46,680 --> 00:35:49,640
Speaker 1: bedside up in here, and what we'll do and usually

639
00:35:49,680 --> 00:35:52,799
Speaker 1: we can find hair where they bed. Um, there's enough

640
00:35:52,840 --> 00:35:55,239
Speaker 1: points here and I don't just look at the map

641
00:35:55,239 --> 00:35:56,680
Speaker 1: because they're kind of scattered. You get a little bit

642
00:35:56,680 --> 00:35:59,600
Speaker 1: of error from the GPS caller, but it looks like

643
00:35:59,640 --> 00:36:02,400
Speaker 1: bulk of points are just through here. But well, I

644
00:36:02,400 --> 00:36:04,359
Speaker 1: think that's a batch light there. We'll come sack that out.

645
00:36:08,680 --> 00:36:17,759
Speaker 1: Oh yeah, so here we have elk calf. Yeah, um,

646
00:36:18,280 --> 00:36:20,839
Speaker 1: imagine that newborn. You know, that's just what you would

647
00:36:20,840 --> 00:36:25,000
Speaker 1: predict here. And this is pretty classic. I mean, there's

648
00:36:25,040 --> 00:36:27,440
Speaker 1: not much left right, You've got what we're looking at

649
00:36:27,480 --> 00:36:30,520
Speaker 1: here is the lower mandible. And of course you can

650
00:36:30,560 --> 00:36:32,719
Speaker 1: easily identify it's a calf because you don't have the

651
00:36:32,760 --> 00:36:36,160
Speaker 1: teeth eruption. Um. Of course it's small too. It's only

652
00:36:36,800 --> 00:36:39,200
Speaker 1: about four and a half inches long from the tip

653
00:36:39,360 --> 00:36:41,240
Speaker 1: down through the mandible. And you can see where they

654
00:36:41,280 --> 00:36:44,560
Speaker 1: they don't um, you know, they won't crunch up the teeth.

655
00:36:44,560 --> 00:36:49,160
Speaker 1: That's just an indigestible, hard to chew and crunch up. Um.

656
00:36:49,200 --> 00:36:51,920
Speaker 1: But and then we see the skull cap here, So

657
00:36:52,000 --> 00:36:54,600
Speaker 1: that crunched right into the skull cap. Of course, the

658
00:36:54,680 --> 00:36:57,239
Speaker 1: brain would be a you know, nutrient rich source of

659
00:36:57,280 --> 00:37:02,279
Speaker 1: food for any meat eater. Um. And so they were

660
00:37:02,320 --> 00:37:04,719
Speaker 1: quick to that. Coot lion was quick to feed on that.

661
00:37:05,120 --> 00:37:08,719
Speaker 1: And then we've got a front leg, the hoof the

662
00:37:08,760 --> 00:37:12,160
Speaker 1: lower leg. But you can see, um, you know, they've

663
00:37:12,160 --> 00:37:14,359
Speaker 1: crunched through it, you know, cougar's jaw. I mean, they

664
00:37:14,360 --> 00:37:16,759
Speaker 1: have a really powerful bite force. Uh. They have a

665
00:37:16,760 --> 00:37:21,120
Speaker 1: short rostrum, a short jaw, big powerful muscles, master muscles

666
00:37:21,120 --> 00:37:23,040
Speaker 1: that wrap around the outside of their fet heads and

667
00:37:23,080 --> 00:37:26,600
Speaker 1: attached to the top of their skull and their teeth

668
00:37:26,640 --> 00:37:29,520
Speaker 1: of course, their carnassial teeth, their mowlers, premolars, top and

669
00:37:29,520 --> 00:37:33,120
Speaker 1: bottom make that really powerful bite force. So they're pretty

670
00:37:33,120 --> 00:37:35,080
Speaker 1: big bone crunchers and eaters, and they do get a

671
00:37:35,080 --> 00:37:37,360
Speaker 1: lot of nutrients from that, both from the bone itself

672
00:37:37,440 --> 00:37:42,160
Speaker 1: and from the marrow inside um. And this is pretty classic.

673
00:37:42,280 --> 00:37:45,239
Speaker 1: You mean, you know, a cougar that kills an elk

674
00:37:45,280 --> 00:37:48,480
Speaker 1: calf will leave typically about this behind, which is just

675
00:37:48,520 --> 00:37:51,800
Speaker 1: a bunch of bone shards, the teeth, top of the skull,

676
00:37:52,080 --> 00:37:56,719
Speaker 1: lower leg, everything. And what we'll do here is we'll

677
00:37:56,719 --> 00:37:59,320
Speaker 1: look around and see if we see uh bear scot.

678
00:38:00,719 --> 00:38:03,880
Speaker 1: My guess is, you know, with a smaller prey package

679
00:38:03,920 --> 00:38:05,880
Speaker 1: like this, you know this is an elk calf, probably

680
00:38:05,880 --> 00:38:08,120
Speaker 1: born in the first couple of weeks of June, early June,

681
00:38:08,840 --> 00:38:11,960
Speaker 1: and this was kill was made on June July six,

682
00:38:12,080 --> 00:38:14,600
Speaker 1: so maybe it was about a month old. It was

683
00:38:14,719 --> 00:38:17,279
Speaker 1: probably you know, bet it could have been at that

684
00:38:17,320 --> 00:38:19,520
Speaker 1: stage where it was hiding and mom was off grazing

685
00:38:19,560 --> 00:38:21,120
Speaker 1: and coming back to nurse. Or it could have just

686
00:38:21,239 --> 00:38:25,359
Speaker 1: been taken down right here with this lion watching as

687
00:38:25,400 --> 00:38:27,600
Speaker 1: a group of cows, maybe filtered through in the evening

688
00:38:27,680 --> 00:38:30,320
Speaker 1: or at night feeding through here. I'll look at the data.

689
00:38:30,400 --> 00:38:32,719
Speaker 1: I think this cluster started in the middle of the night,

690
00:38:32,719 --> 00:38:34,480
Speaker 1: which is more typical when cougars are out in the

691
00:38:34,520 --> 00:38:37,280
Speaker 1: landscape hunting. They're active at night. Hunting. So you imagine

692
00:38:37,320 --> 00:38:41,040
Speaker 1: that the calving grounds are here. It's like maybe this

693
00:38:41,080 --> 00:38:43,879
Speaker 1: elk was born in this little in this general area. Yeah,

694
00:38:43,920 --> 00:38:45,719
Speaker 1: I mean a month old. It could have been born,

695
00:38:45,800 --> 00:38:47,880
Speaker 1: you know, within a mile here, I would say, in

696
00:38:47,920 --> 00:38:50,799
Speaker 1: this at this area. But um you know, at that

697
00:38:50,840 --> 00:38:53,640
Speaker 1: first month of life, they're pretty. They're pretty saying pretty

698
00:38:53,640 --> 00:38:55,319
Speaker 1: close to where they were born and less mom wants

699
00:38:55,320 --> 00:38:57,000
Speaker 1: to get up and move to summer range with it.

700
00:38:57,760 --> 00:39:01,560
Speaker 1: Um Uh. This gardener based scenarios important cabin grounds for

701
00:39:01,600 --> 00:39:03,799
Speaker 1: cow for sure. But what we'll do here is take

702
00:39:03,840 --> 00:39:05,160
Speaker 1: a look and see if we see and he saw.

703
00:39:05,320 --> 00:39:06,840
Speaker 1: What I always try to do is we try to

704
00:39:06,880 --> 00:39:10,640
Speaker 1: determine was this cougar displaced by a larger carnivore and

705
00:39:10,680 --> 00:39:12,800
Speaker 1: that would either be a black bear, grizzly or Brett

706
00:39:12,840 --> 00:39:15,560
Speaker 1: pack of wolves. Based on how long he was here

707
00:39:15,640 --> 00:39:17,520
Speaker 1: and the size of this, I would say he probably

708
00:39:17,520 --> 00:39:20,960
Speaker 1: got most of this. You'll get ravens and magpies, eagles

709
00:39:21,000 --> 00:39:24,600
Speaker 1: sometimes that come in. But you know the specialty of cougars,

710
00:39:24,640 --> 00:39:26,880
Speaker 1: of of what they're known for is cashing and concealing

711
00:39:26,920 --> 00:39:29,719
Speaker 1: their prey. And that's a real uh, it's an adaptation

712
00:39:29,800 --> 00:39:32,799
Speaker 1: to really protect the food harder and food resources. You

713
00:39:32,800 --> 00:39:34,439
Speaker 1: can see here on the edge of this thick patch

714
00:39:34,520 --> 00:39:37,799
Speaker 1: of conifer. My guess is usually see a pile of

715
00:39:37,800 --> 00:39:39,879
Speaker 1: grass where it was buried, and right here behind us

716
00:39:40,560 --> 00:39:43,960
Speaker 1: um in this shaded area. Probably it was doubt it

717
00:39:44,080 --> 00:39:46,719
Speaker 1: was back a year, I would guess maybe fed in

718
00:39:46,800 --> 00:39:50,719
Speaker 1: right here. Plenty of shape of concealment bone shards in here,

719
00:39:50,760 --> 00:39:54,960
Speaker 1: so this is probably where he dragged it to feed on,

720
00:39:55,040 --> 00:39:57,200
Speaker 1: and you can see where it perfectly concealed. You know,

721
00:39:57,360 --> 00:40:00,520
Speaker 1: ravens and magpies will have a hard time finding this um.

722
00:40:00,880 --> 00:40:02,560
Speaker 1: A little bit of tufts of hair there. This is

723
00:40:02,600 --> 00:40:06,080
Speaker 1: the end of the scapula he chewed up um. So

724
00:40:06,160 --> 00:40:09,480
Speaker 1: he would pull that calf back in here cash, Yeah,

725
00:40:09,520 --> 00:40:11,160
Speaker 1: he might bury it. You know what we find with

726
00:40:11,160 --> 00:40:13,760
Speaker 1: with calves is they it's a small enough a newborn

727
00:40:13,800 --> 00:40:16,239
Speaker 1: calf is small enough that they might not necessarily cash it.

728
00:40:16,320 --> 00:40:19,360
Speaker 1: They'll just start feeding on it. Certainly with anything larger

729
00:40:19,360 --> 00:40:22,279
Speaker 1: than an elk calf, they almost automatically begin cashing even

730
00:40:22,320 --> 00:40:26,359
Speaker 1: before they feed, at least dragging to cover. So that's

731
00:40:26,360 --> 00:40:28,040
Speaker 1: what that's what he did here. I don't see any

732
00:40:28,719 --> 00:40:31,200
Speaker 1: scott you know, this area could have a blackber add there.

733
00:40:31,560 --> 00:40:33,680
Speaker 1: I'm guessing he got most of the bottle mass on

734
00:40:33,800 --> 00:40:36,800
Speaker 1: this calf, which would be I don't know, a newborn

735
00:40:36,800 --> 00:40:43,800
Speaker 1: elk calf is gonna, you know, be twenty some us meat. Um,

736
00:40:44,000 --> 00:40:46,680
Speaker 1: so a good meal, good meal. We how long would

737
00:40:46,680 --> 00:40:48,520
Speaker 1: that satiate him for? Was he going to go, like

738
00:40:48,560 --> 00:40:51,760
Speaker 1: you said, go off a couple of miles just typically

739
00:40:51,760 --> 00:40:54,239
Speaker 1: we fine? And this is again long term. I'm kind

740
00:40:54,239 --> 00:40:55,920
Speaker 1: of giving you averages here, but just give you an

741
00:40:55,960 --> 00:40:59,760
Speaker 1: idea an adult male cougar. Of course, with cougar life history,

742
00:40:59,800 --> 00:41:02,399
Speaker 1: they don't play any role in feeding young. They're off

743
00:41:02,400 --> 00:41:04,320
Speaker 1: on their own and they only associate with females to

744
00:41:04,360 --> 00:41:08,640
Speaker 1: breed females or the caretaker. They're the hard working single mom.

745
00:41:08,880 --> 00:41:12,560
Speaker 1: The males breed the female usually in late and Yellowstone

746
00:41:12,560 --> 00:41:15,000
Speaker 1: in late winter, although female cougars could get bred any

747
00:41:15,000 --> 00:41:17,560
Speaker 1: time of the year. They they cycle extracycle once every

748
00:41:17,560 --> 00:41:20,839
Speaker 1: twenty eight days or so. Um. But we can see

749
00:41:20,840 --> 00:41:22,719
Speaker 1: a birthing pulse in May, June and July in a

750
00:41:22,760 --> 00:41:24,800
Speaker 1: place like Yellowstone because that's when a lot of foods

751
00:41:24,800 --> 00:41:27,239
Speaker 1: out for moms. But a male like this typically will

752
00:41:27,239 --> 00:41:29,640
Speaker 1: make a kill on average every seven to ten days.

753
00:41:30,440 --> 00:41:32,320
Speaker 1: Of course, at all is dictated by the size of

754
00:41:32,360 --> 00:41:35,000
Speaker 1: the prey package, as small el cap will sustain him

755
00:41:35,040 --> 00:41:39,120
Speaker 1: for less time than a large animal. Um. I forget

756
00:41:39,239 --> 00:41:42,760
Speaker 1: exactly when his last kill was. Oh I do remembers

757
00:41:42,840 --> 00:41:45,680
Speaker 1: yesterday we searched it. It It was about four miles that way.

758
00:41:46,320 --> 00:41:50,200
Speaker 1: It was a sealing bull elk and there's a lot

759
00:41:50,239 --> 00:41:51,919
Speaker 1: of black bear scout around it. And he was only

760
00:41:52,200 --> 00:41:54,280
Speaker 1: at that site for about fifteen hours. So my guess

761
00:41:54,280 --> 00:41:56,319
Speaker 1: is what happened is he killed that was kicked off

762
00:41:56,320 --> 00:41:58,719
Speaker 1: by a bear, came down here, made this kill a

763
00:41:58,760 --> 00:42:01,160
Speaker 1: little more time here. So you're like c S. I

764
00:42:02,320 --> 00:42:04,560
Speaker 1: most very much, very much. I mean it's really the

765
00:42:04,680 --> 00:42:07,320
Speaker 1: fun to come to these sites, look for the clues,

766
00:42:07,360 --> 00:42:09,280
Speaker 1: look for the evidence, try to piece the story together.

767
00:42:09,800 --> 00:42:13,000
Speaker 1: Of course, we have the old school field biology. I mean,

768
00:42:13,120 --> 00:42:16,120
Speaker 1: biologists have been doing this with carnival research for uh,

769
00:42:16,200 --> 00:42:18,759
Speaker 1: you know, fifty sixty seventy years. I mean we can

770
00:42:18,760 --> 00:42:21,239
Speaker 1: go back to you know, our ancestors, you know, out

771
00:42:21,239 --> 00:42:23,440
Speaker 1: there using the same techniques to try to piece together

772
00:42:24,280 --> 00:42:27,120
Speaker 1: where prey was or where competitors like carnivores were, So

773
00:42:27,800 --> 00:42:31,280
Speaker 1: we emplay those same tactics today. But we also benefit

774
00:42:31,280 --> 00:42:33,000
Speaker 1: from the technology. I mean you see me I locked

775
00:42:33,000 --> 00:42:35,400
Speaker 1: in here with a GPS unit I had as GPS

776
00:42:35,520 --> 00:42:38,480
Speaker 1: data loaded in here, we can come right to the site. Uh.

777
00:42:38,520 --> 00:42:41,799
Speaker 1: It's a really powerful tool to get accurate data on

778
00:42:41,920 --> 00:42:44,160
Speaker 1: what these animals are doing. And as you said it,

779
00:42:44,200 --> 00:42:48,000
Speaker 1: to imagine it's from some people not as not as

780
00:42:48,080 --> 00:42:54,080
Speaker 1: exciting as hunting, but incredibly important to our our general

781
00:42:54,120 --> 00:42:57,520
Speaker 1: knowledge base on how predation happens. Right absolutely. I mean

782
00:42:57,880 --> 00:43:03,000
Speaker 1: there's so uh so many opinions and thoughts about what

783
00:43:03,080 --> 00:43:05,640
Speaker 1: carnivores are doing and how they hunt and how they

784
00:43:05,680 --> 00:43:08,279
Speaker 1: feed and what impis they have, and we all have

785
00:43:08,400 --> 00:43:13,560
Speaker 1: those opinions. Um And I think what we as scientists

786
00:43:14,160 --> 00:43:18,400
Speaker 1: really cherish is having you know, data right to to

787
00:43:18,560 --> 00:43:22,480
Speaker 1: really critically evaluate it and truly understand what's going on,

788
00:43:23,160 --> 00:43:26,800
Speaker 1: um you know, without without you know, cougars are a

789
00:43:26,800 --> 00:43:28,680
Speaker 1: great example in Yellowstone. You know, in the last twenty

790
00:43:28,680 --> 00:43:32,000
Speaker 1: five years wolves have come back, right and that was

791
00:43:32,080 --> 00:43:36,760
Speaker 1: a huge, uh conservation success story. It was very controversial,

792
00:43:36,800 --> 00:43:40,520
Speaker 1: it is to this day. Um and And but I

793
00:43:40,560 --> 00:43:43,520
Speaker 1: think what we've really learned is having really good information

794
00:43:43,560 --> 00:43:46,120
Speaker 1: about what role and animal like a wolf or cougar

795
00:43:46,200 --> 00:43:48,680
Speaker 1: has helps us better understand how to either whether we

796
00:43:48,880 --> 00:43:50,799
Speaker 1: want to manage them, whether we don't want to manage them,

797
00:43:50,840 --> 00:43:52,320
Speaker 1: like in a place like Yellowson, where we just stepped

798
00:43:52,320 --> 00:43:55,040
Speaker 1: back and let nature take its course. We don't have

799
00:43:55,080 --> 00:43:58,600
Speaker 1: the luxury of having protective preserves around our country like Yellowstone.

800
00:43:58,680 --> 00:44:02,160
Speaker 1: So those of us that live in this area and

801
00:44:02,440 --> 00:44:05,000
Speaker 1: hunt and fish and enjoy the landscape and our public

802
00:44:05,080 --> 00:44:08,480
Speaker 1: lands and and um, we have to coexist with all

803
00:44:08,520 --> 00:44:11,560
Speaker 1: these animals, whether they're elk or cougars, and and you know,

804
00:44:11,560 --> 00:44:14,799
Speaker 1: the more understanding we have of them, the better we

805
00:44:14,840 --> 00:44:18,400
Speaker 1: are at living with them and protecting them, and um,

806
00:44:18,600 --> 00:44:22,600
Speaker 1: understanding what impacts we have on them and what our

807
00:44:22,640 --> 00:44:25,480
Speaker 1: activities as humans have. So it's all feeds into that,

808
00:44:25,520 --> 00:44:28,239
Speaker 1: and it's really incredibly important. And you're definitely kind of

809
00:44:28,280 --> 00:44:31,960
Speaker 1: at the you know, kind of the nexus of we

810
00:44:32,160 --> 00:44:37,080
Speaker 1: as Americans are drawn to these charismatic predators. We can

811
00:44:37,120 --> 00:44:40,320
Speaker 1: explore that all day long, but we're definitely drawn to them.

812
00:44:40,360 --> 00:44:42,520
Speaker 1: Some people are drawn to them in a more sympathetic way,

813
00:44:43,080 --> 00:44:46,319
Speaker 1: some people in a more logical way and more pragmatic way.

814
00:44:46,400 --> 00:44:49,120
Speaker 1: Some people um based on you know, a lot of

815
00:44:49,200 --> 00:44:50,759
Speaker 1: hunters as we were talking about walking up here. A

816
00:44:50,800 --> 00:44:54,879
Speaker 1: lot of hunters are drawn to them from the propaganda

817
00:44:55,000 --> 00:44:57,640
Speaker 1: of you know, the last century where we needed to

818
00:44:57,719 --> 00:44:59,560
Speaker 1: kill them all and displace them so we could ranch

819
00:44:59,600 --> 00:45:04,480
Speaker 1: and live in relative without you know, bears and cougars

820
00:45:04,560 --> 00:45:07,840
Speaker 1: killing our killing our calves and killing our cows and

821
00:45:07,920 --> 00:45:10,960
Speaker 1: killing our profits. So it's you kind of sit at

822
00:45:10,960 --> 00:45:15,200
Speaker 1: this strange, you know, nexus of all those things happening together,

823
00:45:15,719 --> 00:45:17,759
Speaker 1: and they all have influence, they do. And we you know,

824
00:45:17,800 --> 00:45:20,319
Speaker 1: we have you know, our our our species. We have

825
00:45:20,400 --> 00:45:24,600
Speaker 1: this rich evolutionary history with these animals, right. Um. You know,

826
00:45:24,640 --> 00:45:28,399
Speaker 1: our ancestors competed with them for space, for food, they

827
00:45:28,480 --> 00:45:32,640
Speaker 1: killed us, We killed them. That still happens today. Uh.

828
00:45:33,000 --> 00:45:34,960
Speaker 1: And you know they would kind of represent this sort

829
00:45:35,000 --> 00:45:39,480
Speaker 1: of stubborn, nagging conflict uh. And they can be very

830
00:45:39,520 --> 00:45:43,200
Speaker 1: difficult to live with. Um, there's no doubt about it. UM.

831
00:45:43,440 --> 00:45:46,279
Speaker 1: And And if we look at the history of carnivores

832
00:45:46,320 --> 00:45:49,200
Speaker 1: and how we've interacted with them and treated them, and

833
00:45:49,600 --> 00:45:52,160
Speaker 1: you know, modern history the last couple hundred years, it

834
00:45:52,200 --> 00:45:56,560
Speaker 1: really has been shifted from one of complete persecution, uh,

835
00:45:56,800 --> 00:46:00,200
Speaker 1: just viewing them as not being uh just a born

836
00:46:00,239 --> 00:46:02,040
Speaker 1: in our side they shouldn't be here. Let's get rid

837
00:46:02,080 --> 00:46:04,799
Speaker 1: of them. The place will be better. Um, we'll have

838
00:46:04,840 --> 00:46:08,399
Speaker 1: more of this, well more of that, and uh we

839
00:46:08,520 --> 00:46:11,759
Speaker 1: spent um a large part of early human history and

840
00:46:11,920 --> 00:46:14,359
Speaker 1: on these landscapes and the great yelostone getting rid of them.

841
00:46:14,719 --> 00:46:17,360
Speaker 1: You know, you look at Teddy roosevelt journeys here to

842
00:46:17,440 --> 00:46:20,120
Speaker 1: Yelloston only eighteen hundreds, eighteen nineties. He came here and

843
00:46:20,120 --> 00:46:23,160
Speaker 1: there's this great uh story that he writes about and

844
00:46:23,200 --> 00:46:25,040
Speaker 1: it's in the park archives of him here wanting to

845
00:46:25,040 --> 00:46:26,919
Speaker 1: come in hunt a cougar. It was a very big,

846
00:46:26,960 --> 00:46:28,960
Speaker 1: poor part of the course he was, you know, as

847
00:46:29,080 --> 00:46:31,040
Speaker 1: many people know his rich history as a hunter and

848
00:46:31,040 --> 00:46:34,319
Speaker 1: as a conservationist, and um, it was really interesting see

849
00:46:34,320 --> 00:46:38,319
Speaker 1: Teddy Roosevelt shift about predators and carnivores from his experiences

850
00:46:38,360 --> 00:46:41,279
Speaker 1: here in Yellowstone National Park and when he came here

851
00:46:41,320 --> 00:46:44,960
Speaker 1: to this area on the eighteen nineties, I think was

852
00:46:45,000 --> 00:46:47,560
Speaker 1: one of his first visits in this area. Um, he

853
00:46:47,600 --> 00:46:50,400
Speaker 1: wanted to hunt sugar, He wanted to hunt elk um.

854
00:46:50,440 --> 00:46:52,560
Speaker 1: You know when he wrote about this landscape, he wrote

855
00:46:52,560 --> 00:46:55,120
Speaker 1: about Yellowstone being this kind of last reserve for the

856
00:46:55,160 --> 00:46:58,560
Speaker 1: elk Right, he didn't talk about how predators had eradicated

857
00:46:58,600 --> 00:47:00,480
Speaker 1: the elk. He talked about how market hunting and he

858
00:47:00,560 --> 00:47:03,319
Speaker 1: was very accurate in his perception of understanding, you know,

859
00:47:03,400 --> 00:47:06,680
Speaker 1: we almost lost, you know, an elk on this landscape

860
00:47:06,680 --> 00:47:08,920
Speaker 1: because of market hunting in this region. Yelsen really kind

861
00:47:08,920 --> 00:47:12,720
Speaker 1: of epitomizes that. And you look at Teddy Roosevelt's early

862
00:47:12,840 --> 00:47:16,320
Speaker 1: observations of carnivores here, and he particularly was interested in

863
00:47:16,360 --> 00:47:19,400
Speaker 1: the cougar um and he had a shift and he

864
00:47:19,440 --> 00:47:20,960
Speaker 1: came back and wanting to hunt of cougar. There was

865
00:47:21,000 --> 00:47:23,080
Speaker 1: a lot of worry about public perception what that would

866
00:47:23,080 --> 00:47:25,640
Speaker 1: look like of killing something in the park, and there's

867
00:47:25,640 --> 00:47:28,440
Speaker 1: a lot of politics involved with going back and forth

868
00:47:28,560 --> 00:47:31,720
Speaker 1: and um. In the end, you know, he was finally

869
00:47:31,760 --> 00:47:33,640
Speaker 1: at a point where he advocated like, look, maybe we

870
00:47:33,680 --> 00:47:36,160
Speaker 1: should not be hunting cougars and yellowstone. And what he

871
00:47:36,200 --> 00:47:39,480
Speaker 1: saw was an elk heerd that started to increase in abundance.

872
00:47:39,520 --> 00:47:42,399
Speaker 1: He saw some severe winners and winter starvation. Of course,

873
00:47:42,400 --> 00:47:45,560
Speaker 1: he had experienced with cattle starvation on his ranch um

874
00:47:46,080 --> 00:47:49,240
Speaker 1: out in the west and where he saw the devastating

875
00:47:49,239 --> 00:47:52,000
Speaker 1: effects of winter and um and he was seeing an

876
00:47:52,000 --> 00:47:54,359
Speaker 1: elk hered here with an abundant elk hered and elk

877
00:47:54,440 --> 00:47:56,640
Speaker 1: just dying and suffering. And then he also was like,

878
00:47:56,880 --> 00:47:59,880
Speaker 1: you know, maybe maybe predators player role here. Uh, And

879
00:48:00,000 --> 00:48:02,080
Speaker 1: that was very wise. It wasn't a popular opinion at

880
00:48:02,080 --> 00:48:05,399
Speaker 1: the time. UM. And you know, he and George berg

881
00:48:05,400 --> 00:48:08,800
Speaker 1: Grennell really you know, started the stage of understanding how

882
00:48:09,239 --> 00:48:11,359
Speaker 1: you can have landscapes with predators. Now, don't get me wrong,

883
00:48:11,400 --> 00:48:16,120
Speaker 1: he's still haunting predators, um, but he was early, uh

884
00:48:16,520 --> 00:48:20,279
Speaker 1: in his time to recognize that these landscapes um that

885
00:48:20,440 --> 00:48:22,960
Speaker 1: have predators, you know, might benefit by that. Well. And

886
00:48:23,000 --> 00:48:26,920
Speaker 1: this is where there's so many you know, fissures and

887
00:48:27,200 --> 00:48:29,319
Speaker 1: these lines of thinking that take you places. But one

888
00:48:29,360 --> 00:48:31,600
Speaker 1: of the things I think of that I've heard I

889
00:48:31,640 --> 00:48:34,840
Speaker 1: said a lot is the term ecosystem services, Like what

890
00:48:34,840 --> 00:48:36,840
Speaker 1: what are these what role are these play? And that

891
00:48:36,880 --> 00:48:39,120
Speaker 1: gets into I'd love to talk a little bit about

892
00:48:39,160 --> 00:48:42,399
Speaker 1: like trophic cascade and some of these ideas where each

893
00:48:42,440 --> 00:48:46,600
Speaker 1: one of these animals plays some role here removal of

894
00:48:46,640 --> 00:48:49,319
Speaker 1: that role you know nature boards of vacuum, right, So

895
00:48:49,440 --> 00:48:53,160
Speaker 1: removing all the predators does create you know, a different

896
00:48:53,160 --> 00:48:56,560
Speaker 1: ecological environment, because that's an it's an interesting thing. But

897
00:48:57,080 --> 00:48:59,719
Speaker 1: you know, moreover what is it like to be an

898
00:48:59,719 --> 00:49:02,640
Speaker 1: elk without a wolf? What is it like to be

899
00:49:03,080 --> 00:49:05,840
Speaker 1: a wolf without an elk? Um? And so these animals

900
00:49:06,200 --> 00:49:08,200
Speaker 1: kind of are made to be what they've always been

901
00:49:08,200 --> 00:49:10,799
Speaker 1: by the presence of that other species exactly. You know

902
00:49:10,840 --> 00:49:13,360
Speaker 1: what so many of the traits that we as hunters admire,

903
00:49:13,719 --> 00:49:16,239
Speaker 1: and these animals that um you know, many people are

904
00:49:16,280 --> 00:49:19,080
Speaker 1: just so passionate about having experience without the landscape and

905
00:49:19,800 --> 00:49:23,160
Speaker 1: have been shaped through predation. You know, predation is one

906
00:49:23,200 --> 00:49:26,640
Speaker 1: of the most powerful ecological forces that has shaped life

907
00:49:26,640 --> 00:49:31,600
Speaker 1: on earth for million severes, shaped us. And uh. You

908
00:49:31,640 --> 00:49:34,560
Speaker 1: know what we know about an animal like a wolf,

909
00:49:34,560 --> 00:49:37,680
Speaker 1: for a cougar and having predator populations interacting with prey

910
00:49:37,840 --> 00:49:42,680
Speaker 1: is that you know, they largely um uh depend on

911
00:49:42,800 --> 00:49:45,279
Speaker 1: vulnerable prey, you know, the young, the old, the sick

912
00:49:45,320 --> 00:49:47,520
Speaker 1: of the week. That has time and time again, every

913
00:49:47,520 --> 00:49:50,759
Speaker 1: predator study has continued to demonstrate that they can't kill

914
00:49:50,800 --> 00:49:52,799
Speaker 1: anything they want. And I'd like to talk about that later,

915
00:49:52,880 --> 00:49:55,400
Speaker 1: sort of the limits of predatory ability of these carnivores,

916
00:49:55,400 --> 00:49:59,279
Speaker 1: because I think that's very misunderstood. Um concept of how

917
00:49:59,360 --> 00:50:02,520
Speaker 1: these animals hunt and what it takes to feed themselves.

918
00:50:02,520 --> 00:50:06,080
Speaker 1: But you know, through predation, Um, you get a lower

919
00:50:06,480 --> 00:50:11,000
Speaker 1: prey abundance, you get a culling uh you uh, you

920
00:50:11,080 --> 00:50:15,439
Speaker 1: have uh in the end, tend to have an ungulate herd,

921
00:50:15,480 --> 00:50:18,360
Speaker 1: a prey population her that is healthier. But whatever metric

922
00:50:18,440 --> 00:50:22,680
Speaker 1: you look at, whether it be productivity, recruitment, reproductive success,

923
00:50:22,719 --> 00:50:26,080
Speaker 1: body condition. There of course many other factors that shape

924
00:50:26,080 --> 00:50:30,120
Speaker 1: that weather bottom up processes like forage quality. I mean,

925
00:50:30,200 --> 00:50:33,040
Speaker 1: car predation is only one part of that story, of course,

926
00:50:33,040 --> 00:50:35,000
Speaker 1: but it's a it's a vitally important part of it.

927
00:50:35,360 --> 00:50:38,640
Speaker 1: And in terms of how food webs operate, you know,

928
00:50:38,719 --> 00:50:42,480
Speaker 1: nutrient cycling, you know, through that top down pressure of predation.

929
00:50:42,520 --> 00:50:45,200
Speaker 1: Do you have nutrients going through this whole system? If

930
00:50:45,239 --> 00:50:46,560
Speaker 1: we look here at this site in front of us,

931
00:50:46,560 --> 00:50:48,800
Speaker 1: you've got this elk half remains, there's not much left,

932
00:50:49,200 --> 00:50:51,560
Speaker 1: but you're gonna get nutrients leaching from whatever is left

933
00:50:51,560 --> 00:50:53,480
Speaker 1: there down into the soils. That's gonna be important for

934
00:50:53,480 --> 00:50:56,560
Speaker 1: these group of plants here in this area, for you know,

935
00:50:56,640 --> 00:50:58,960
Speaker 1: hundreds of species of invertebrate that come into the site

936
00:50:59,000 --> 00:51:02,879
Speaker 1: and depend upon that beatles flies, um, you know, it's

937
00:51:03,000 --> 00:51:06,319
Speaker 1: just all part of that nutrient cycling from top down

938
00:51:06,680 --> 00:51:09,399
Speaker 1: to bottom up right now, the mosquitoes are depending on me.

939
00:51:10,480 --> 00:51:12,640
Speaker 1: I got the right blood type at seas for for that.

940
00:51:12,680 --> 00:51:15,200
Speaker 1: But yeah, I mean it's such an interesting what drives

941
00:51:15,200 --> 00:51:16,520
Speaker 1: me too. When I was telling you coming up here,

942
00:51:16,520 --> 00:51:18,120
Speaker 1: I'm like, if my wife would let me and I

943
00:51:18,160 --> 00:51:20,640
Speaker 1: never get independently wealthy, I'm gonna. I'm gonna become a

944
00:51:20,680 --> 00:51:23,160
Speaker 1: wildlife biologist because of what you said. There's so many

945
00:51:23,160 --> 00:51:27,720
Speaker 1: elements to your job. C. S. I. Yellowstone, but also

946
00:51:27,840 --> 00:51:31,759
Speaker 1: just understanding all of the very nuanced ways that these

947
00:51:31,760 --> 00:51:34,560
Speaker 1: things interact, you know, which I think for somebody that

948
00:51:34,640 --> 00:51:37,160
Speaker 1: listens to this show or has heard us talk about

949
00:51:37,200 --> 00:51:40,960
Speaker 1: paleo anthropology and zoology and all these other things that

950
00:51:41,000 --> 00:51:44,560
Speaker 1: are tangential to hunting or parallel to the activity, you

951
00:51:44,600 --> 00:51:46,560
Speaker 1: start to just get immersed in this world that is

952
00:51:46,680 --> 00:51:49,680
Speaker 1: endless and ever changing, and it's just like it's cause

953
00:51:49,719 --> 00:51:53,120
Speaker 1: and effect and it's complex. And I think that in

954
00:51:53,200 --> 00:51:57,040
Speaker 1: itself is part of the challenge of um. When we

955
00:51:57,080 --> 00:51:59,920
Speaker 1: talk about predators and their impacts on prey, there's no

956
00:52:00,160 --> 00:52:03,000
Speaker 1: one simple answer to it. You know, what's happening here

957
00:52:03,000 --> 00:52:05,360
Speaker 1: in Yellowstone is not necessarily what's happening, you know in

958
00:52:05,400 --> 00:52:10,799
Speaker 1: the bitter route of Montana. What's happening here under our management,

959
00:52:10,800 --> 00:52:13,759
Speaker 1: the Park Services Management gold Mission, which is stepping back

960
00:52:13,840 --> 00:52:17,880
Speaker 1: natural regulation. We don't manage carnivore numbers. We don't manage

961
00:52:18,120 --> 00:52:21,080
Speaker 1: elk numbers now, of course, you know human you know,

962
00:52:21,120 --> 00:52:23,960
Speaker 1: we think of Yellowstone is sort of this pristine baseline

963
00:52:24,000 --> 00:52:27,160
Speaker 1: wild place and it very much is relative to what

964
00:52:27,400 --> 00:52:30,400
Speaker 1: is around us. Right, but there's still human impacts here, right,

965
00:52:30,440 --> 00:52:32,959
Speaker 1: I mean, I mean we've got right now in the park,

966
00:52:33,000 --> 00:52:35,279
Speaker 1: you know, probably thirty thousand people driving around right now.

967
00:52:35,360 --> 00:52:38,160
Speaker 1: We'll have you know, several million visitors to the system

968
00:52:38,200 --> 00:52:42,240
Speaker 1: this year. We've got development, We've got uh, landscape changes,

969
00:52:42,239 --> 00:52:46,240
Speaker 1: we've got climate change. There's so many things operating together,

970
00:52:46,960 --> 00:52:50,520
Speaker 1: and it's very difficult to give a SoundBite, bulleted you know,

971
00:52:50,600 --> 00:52:53,600
Speaker 1: bullet point, you know, simple answer to you know, hey,

972
00:52:53,640 --> 00:52:56,920
Speaker 1: what impact do wolves have on elk um or cougars

973
00:52:56,960 --> 00:52:59,960
Speaker 1: have on elk or uh? You know what's driving elk

974
00:53:00,000 --> 00:53:03,440
Speaker 1: population dynamics? Place like Yellowstone where we have one of

975
00:53:03,440 --> 00:53:07,480
Speaker 1: our most abundant and diverse carnivore assemblages, we have one

976
00:53:07,520 --> 00:53:11,719
Speaker 1: of our most robust, intact large mammal terrestrial systems with

977
00:53:11,800 --> 00:53:14,040
Speaker 1: bison and prong horn and big horn, sheep and mule

978
00:53:14,080 --> 00:53:19,480
Speaker 1: deer and moose and elk, all interacting on these landscapes. UM.

979
00:53:19,480 --> 00:53:22,799
Speaker 1: Truly lucky to have this landscape, but it is complex, uh,

980
00:53:22,840 --> 00:53:25,640
Speaker 1: And our job as biologists of scientists is to try

981
00:53:25,640 --> 00:53:29,120
Speaker 1: to tease out what how things are working here, what

982
00:53:29,880 --> 00:53:33,279
Speaker 1: is shaping the structure and function of Yellowstone? Um. And

983
00:53:33,320 --> 00:53:35,680
Speaker 1: it provides a great baseline to then look at places

984
00:53:35,719 --> 00:53:38,800
Speaker 1: outside of a protector preserve like Yellowstone, whether it's the

985
00:53:38,840 --> 00:53:41,960
Speaker 1: Greater Yellows, Greater Yellosoone ecosystem, whether it's the rock other

986
00:53:42,000 --> 00:53:44,480
Speaker 1: parts of the Rocky Mountain West. I mean, you name it.

987
00:53:44,520 --> 00:53:48,719
Speaker 1: I mean it provides an incredibly valuable reference point to

988
00:53:48,760 --> 00:53:50,719
Speaker 1: compare it with other places. I like that you say

989
00:53:50,760 --> 00:53:52,640
Speaker 1: that too, because when I first started coming here, I

990
00:53:52,680 --> 00:53:55,560
Speaker 1: was a little depressed by the lines of traffic and

991
00:53:55,600 --> 00:53:58,040
Speaker 1: the people jumping out in their flip flops and their

992
00:53:58,040 --> 00:54:01,040
Speaker 1: board shorts, sick pictures of Buffalo and I my I

993
00:54:01,040 --> 00:54:03,239
Speaker 1: had this conversation with my wife, and I think she

994
00:54:03,360 --> 00:54:05,240
Speaker 1: felt it was a little reductive, like this is beautiful,

995
00:54:05,280 --> 00:54:07,080
Speaker 1: why are you here to kind of like stomp on

996
00:54:07,160 --> 00:54:08,960
Speaker 1: this thing? And then it was explained to me, I

997
00:54:09,000 --> 00:54:10,799
Speaker 1: can't remember who explained it, that the park is kind

998
00:54:10,800 --> 00:54:14,760
Speaker 1: of like an ambassador to wild places. It's not completely wild,

999
00:54:15,000 --> 00:54:17,640
Speaker 1: but allows people to kind of see and appreciate these

1000
00:54:17,640 --> 00:54:20,160
Speaker 1: wild animals in these places in a way that you

1001
00:54:20,239 --> 00:54:22,520
Speaker 1: might if you were, you know, kind of going to

1002
00:54:22,560 --> 00:54:26,800
Speaker 1: amusement park. Um or is it right? So that's it's

1003
00:54:26,840 --> 00:54:29,479
Speaker 1: important for somebody like me. I'm sure you you hate

1004
00:54:29,520 --> 00:54:33,280
Speaker 1: to see those types of interactions, but you do understand

1005
00:54:33,280 --> 00:54:35,520
Speaker 1: that even in your work, it's like, like you said,

1006
00:54:35,560 --> 00:54:39,600
Speaker 1: a reference point for you know, the Galton National Forest

1007
00:54:39,840 --> 00:54:43,680
Speaker 1: and other places that we need to understand. We've lost

1008
00:54:43,719 --> 00:54:48,000
Speaker 1: so much of our natural landscapes, of wild nature across

1009
00:54:48,400 --> 00:54:52,439
Speaker 1: um so many parts of our world right and and

1010
00:54:52,480 --> 00:54:57,160
Speaker 1: thank goodness for for the strong conservation efforts of the

1011
00:54:57,200 --> 00:54:59,799
Speaker 1: last hundred years. I mean, look at what's happening right

1012
00:54:59,800 --> 00:55:03,560
Speaker 1: now and with a great American Conservation Outdoors Act. And

1013
00:55:04,040 --> 00:55:07,799
Speaker 1: we are you know, as a country, we value, we

1014
00:55:07,880 --> 00:55:12,000
Speaker 1: place a high value on nature and wild ecosystems. And

1015
00:55:12,480 --> 00:55:14,400
Speaker 1: you might have a family from an urban area that

1016
00:55:14,480 --> 00:55:18,200
Speaker 1: has no uh really doesn't have a clear concept what

1017
00:55:18,239 --> 00:55:19,759
Speaker 1: that means or how much that was part of their

1018
00:55:19,800 --> 00:55:23,600
Speaker 1: heritage necessarily, but they can come to Yellowstone and and

1019
00:55:23,640 --> 00:55:25,480
Speaker 1: for a day or two they get a glimpse of what,

1020
00:55:26,120 --> 00:55:29,560
Speaker 1: you know, what what nature is like and what it's

1021
00:55:29,560 --> 00:55:31,920
Speaker 1: been like in so many places. And it's different from

1022
00:55:31,920 --> 00:55:34,000
Speaker 1: the nature in their backyards. It's different from the nature

1023
00:55:34,000 --> 00:55:36,600
Speaker 1: in their community parks. Those are all incredibly important things

1024
00:55:36,600 --> 00:55:39,120
Speaker 1: that we tap into for our spirit and our soul.

1025
00:55:39,160 --> 00:55:43,279
Speaker 1: But you know, Yellowstone is this vignette of what much

1026
00:55:43,280 --> 00:55:46,080
Speaker 1: in North America look like for thousands and thousands of years,

1027
00:55:46,080 --> 00:55:49,040
Speaker 1: and it's truly special in that regard. People can understand

1028
00:55:49,040 --> 00:55:52,480
Speaker 1: why they're drawn to the wild places and understand how

1029
00:55:52,480 --> 00:55:55,080
Speaker 1: exciting is to see something like a buffalo walking across

1030
00:55:55,520 --> 00:55:58,400
Speaker 1: you know, a meadow and Yellowstone with a you know,

1031
00:55:58,840 --> 00:56:01,800
Speaker 1: with a paint pot, you know, bubbling behind it or

1032
00:56:02,200 --> 00:56:04,160
Speaker 1: whatever they can see like, I'm drawn to that. I

1033
00:56:04,280 --> 00:56:06,160
Speaker 1: value that. Maybe I don't know why because I don't

1034
00:56:06,160 --> 00:56:08,600
Speaker 1: see it every day, Maybe don't have this intricate understanding

1035
00:56:08,600 --> 00:56:11,920
Speaker 1: of this value system, But man, I feel something and

1036
00:56:11,960 --> 00:56:15,240
Speaker 1: it's real, it's raw, it's not fake, it's not phony.

1037
00:56:15,280 --> 00:56:17,640
Speaker 1: There's so much fake and funny in our world today,

1038
00:56:17,840 --> 00:56:20,000
Speaker 1: and and to come to a place I mean, look

1039
00:56:20,040 --> 00:56:22,279
Speaker 1: at us for sitting here looking at a hoof and

1040
00:56:22,320 --> 00:56:24,680
Speaker 1: a lower leg of an elk calf at a hundred

1041
00:56:24,680 --> 00:56:27,319
Speaker 1: and fifty pound cougar fed on last week, and it

1042
00:56:27,320 --> 00:56:30,920
Speaker 1: doesn't get any more you know, wild and real than that. Well,

1043
00:56:30,960 --> 00:56:33,799
Speaker 1: even walking up here, you're like, thank you. Yeah, Yellowstone

1044
00:56:33,840 --> 00:56:36,759
Speaker 1: never seems to disappoint in terms of wildlife. You walk

1045
00:56:36,840 --> 00:56:40,719
Speaker 1: up here, there's analo pronghorn, analope kind of grazing, and

1046
00:56:40,719 --> 00:56:44,000
Speaker 1: then we see a juvenile coyo kind of prancing along

1047
00:56:44,239 --> 00:56:45,960
Speaker 1: doing his thing. And we come up here, and who

1048
00:56:45,960 --> 00:56:47,799
Speaker 1: knows what else you'll run into. We run past an

1049
00:56:47,840 --> 00:56:50,759
Speaker 1: elk shed down there. So yeah, you could walk around

1050
00:56:50,800 --> 00:56:53,480
Speaker 1: in other pieces of public ground in this country and

1051
00:56:53,560 --> 00:56:57,440
Speaker 1: not have those experiences in a full day. And so

1052
00:56:57,520 --> 00:57:01,240
Speaker 1: it's it's Yellowstone. I've never been, and somewhere in Yellowstone

1053
00:57:01,239 --> 00:57:03,680
Speaker 1: where it didn't kind of show off its value exactly,

1054
00:57:04,280 --> 00:57:07,319
Speaker 1: like hey, look look all this stuff, look at what

1055
00:57:07,400 --> 00:57:09,680
Speaker 1: we what we are. And then you know, certainly we

1056
00:57:09,680 --> 00:57:12,280
Speaker 1: can talk more about kind of the very human struggle

1057
00:57:12,360 --> 00:57:16,360
Speaker 1: to understand what we are impact to all these wild places,

1058
00:57:16,400 --> 00:57:20,240
Speaker 1: to all these animals. And now we have recently, you know,

1059
00:57:20,360 --> 00:57:25,960
Speaker 1: the the judges, the judge's decision to take the Yellowstone

1060
00:57:26,720 --> 00:57:30,240
Speaker 1: the Yellowstone grizzly bear population and put them back on

1061
00:57:30,280 --> 00:57:33,560
Speaker 1: the endangered species list, and a similar debate around wolves

1062
00:57:33,560 --> 00:57:36,960
Speaker 1: in Colorado? Should we introduce wolves to Colorado? So you

1063
00:57:37,000 --> 00:57:40,160
Speaker 1: know all this stuff, and it's you know when I

1064
00:57:40,160 --> 00:57:41,800
Speaker 1: I would say this, and I think maybe you feel

1065
00:57:41,800 --> 00:57:44,880
Speaker 1: it too. As a hunter, there's kind of like the

1066
00:57:44,880 --> 00:57:49,600
Speaker 1: baseline opinion. There's like the standard hunter opinion, no wolves,

1067
00:57:50,240 --> 00:57:53,560
Speaker 1: the standard hunter opinion, let's hunt grizzly bears. Yeah. I

1068
00:57:53,640 --> 00:57:56,280
Speaker 1: understand those opinions. I agree with them in a lot

1069
00:57:56,280 --> 00:57:58,160
Speaker 1: of ways, but I'm also driven to like, what, don't

1070
00:57:58,160 --> 00:58:00,920
Speaker 1: I know? What am I not being at here? What

1071
00:58:01,000 --> 00:58:04,960
Speaker 1: about these predators? Am I missing? Um? And so hopefully

1072
00:58:05,040 --> 00:58:08,480
Speaker 1: we can talk about that more too. For sure, Well

1073
00:58:08,560 --> 00:58:11,480
Speaker 1: let's let's do some more investigating, then we'll go take

1074
00:58:11,480 --> 00:58:24,960
Speaker 1: a seat and talk more. All right, Dan, We're we're

1075
00:58:25,040 --> 00:58:29,400
Speaker 1: up here now, sitting overlooking what you called the Serengetti,

1076
00:58:29,640 --> 00:58:32,880
Speaker 1: which I like the description, and funny enough, we you'll

1077
00:58:32,880 --> 00:58:34,880
Speaker 1: hear some wind there as you're listening. We're sitting on

1078
00:58:34,920 --> 00:58:39,320
Speaker 1: a little a little shelf on a ridge, um overlooking

1079
00:58:39,480 --> 00:58:42,680
Speaker 1: the Yellowstone river that runs down into gardener and um,

1080
00:58:43,600 --> 00:58:46,760
Speaker 1: it's interesting. We just found just walked up here, sat

1081
00:58:46,760 --> 00:58:50,000
Speaker 1: down for a nice place to to do this, and

1082
00:58:50,120 --> 00:58:55,800
Speaker 1: here's a is a piece like a napped partial uh

1083
00:58:56,160 --> 00:58:59,920
Speaker 1: arrowhead that's black of sitting like the most beautiful black

1084
00:59:00,040 --> 00:59:03,040
Speaker 1: up city and I've ever seen. It's gorgeous. Some ancient

1085
00:59:03,120 --> 00:59:06,000
Speaker 1: human hunter we just got done searching a cluster of

1086
00:59:06,080 --> 00:59:09,959
Speaker 1: a cougar and found where he prayed on an elk calf.

1087
00:59:10,720 --> 00:59:16,120
Speaker 1: And here we are looking at some ancient Yellowstone human hunter. Yeah,

1088
00:59:16,280 --> 00:59:18,960
Speaker 1: the tools of his trade. Yeah, there's a little kind

1089
00:59:18,960 --> 00:59:22,040
Speaker 1: of a bench in front of us that, you know,

1090
00:59:22,080 --> 00:59:23,880
Speaker 1: a little it looks almost like a little bowl, and

1091
00:59:24,640 --> 00:59:27,320
Speaker 1: that's turning into a meadow. And you can imagine that

1092
00:59:27,360 --> 00:59:29,640
Speaker 1: ancient hunter's family might have been down there cooking up

1093
00:59:30,480 --> 00:59:32,680
Speaker 1: some ancient food while he was out trying to find more.

1094
00:59:33,720 --> 00:59:36,600
Speaker 1: It's really neat about Yellowstone Oubsidian is you know, there's

1095
00:59:36,800 --> 00:59:39,360
Speaker 1: there's various sources throughout the park. One of the most

1096
00:59:39,600 --> 00:59:43,480
Speaker 1: prominent is Obsidian Cliff as you head south towards Norris Junction,

1097
00:59:43,520 --> 00:59:46,080
Speaker 1: and um, you know they've traced you can you know

1098
00:59:46,120 --> 00:59:49,560
Speaker 1: there's a unique chemical signature to obsidian from that region

1099
00:59:49,640 --> 00:59:52,120
Speaker 1: and and you can use it to trace subsidian throughout

1100
00:59:52,160 --> 00:59:57,600
Speaker 1: and uh, this was incredibly important source material for weapons,

1101
00:59:57,720 --> 01:00:01,040
Speaker 1: um for many tribes, and it was traded. And you know,

1102
01:00:01,120 --> 01:00:03,120
Speaker 1: Yellowstone a cidy and from a city and cliff has

1103
01:00:03,120 --> 01:00:05,320
Speaker 1: been found all the way out into the Great Plains,

1104
01:00:05,400 --> 01:00:08,400
Speaker 1: so many places and in the epicenter of that. As

1105
01:00:08,400 --> 01:00:09,960
Speaker 1: I was just saying down there at the at the

1106
01:00:10,040 --> 01:00:15,640
Speaker 1: kill site, you know, Yellowstone never seems never seems to disappoint,

1107
01:00:16,000 --> 01:00:17,960
Speaker 1: you know, with its with his ability to kind of

1108
01:00:17,960 --> 01:00:20,560
Speaker 1: provide these little moments for you, you know, whether it's

1109
01:00:20,560 --> 01:00:22,560
Speaker 1: whether you're a tourist or like yourself, you spend all

1110
01:00:22,600 --> 01:00:24,840
Speaker 1: this time doing this, you know, I would like it.

1111
01:00:24,960 --> 01:00:27,640
Speaker 1: Right now, I could see a bunch of antelope kind

1112
01:00:27,640 --> 01:00:30,360
Speaker 1: of gather around a little watering hole there. It's like

1113
01:00:30,360 --> 01:00:34,440
Speaker 1: a nice place of a hunter wanted to, uh kind

1114
01:00:34,480 --> 01:00:36,960
Speaker 1: of either an ancient or modern hunt. You wanted to.

1115
01:00:37,640 --> 01:00:39,400
Speaker 1: I wanted to take a look at an antelope. That'd

1116
01:00:39,400 --> 01:00:41,960
Speaker 1: be a place to get be. But we already kind

1117
01:00:42,000 --> 01:00:43,880
Speaker 1: of you know, as we were down there looking around,

1118
01:00:44,640 --> 01:00:48,320
Speaker 1: we talked a lot about kind of learning about these animals.

1119
01:00:48,320 --> 01:00:50,800
Speaker 1: And as much as we as I like to highlight

1120
01:00:50,960 --> 01:00:53,760
Speaker 1: some of the more societal and cultural and even in

1121
01:00:53,800 --> 01:00:57,800
Speaker 1: the wildlife management UM. Since some of the debates some

1122
01:00:57,880 --> 01:00:59,840
Speaker 1: of the issues around these animals. What I think what

1123
01:01:00,080 --> 01:01:03,120
Speaker 1: really we can do it moreover is learn a little

1124
01:01:03,160 --> 01:01:06,880
Speaker 1: bit about them, um, what they do, why they do it,

1125
01:01:07,120 --> 01:01:09,960
Speaker 1: what you've learned about not only their predation habits, but

1126
01:01:10,000 --> 01:01:13,280
Speaker 1: their personalities and what they mean to these ecosystems. And

1127
01:01:13,320 --> 01:01:15,840
Speaker 1: then what that can tell us as we go out

1128
01:01:15,880 --> 01:01:18,320
Speaker 1: into the world and have these debates talk about these

1129
01:01:18,440 --> 01:01:21,000
Speaker 1: very important issues trying to figure out where these animals

1130
01:01:21,000 --> 01:01:25,400
Speaker 1: belong um and what we should do to help manage Yeah,

1131
01:01:25,480 --> 01:01:27,920
Speaker 1: I mean, you know, carnivores really do, as we were mentioning,

1132
01:01:27,960 --> 01:01:34,240
Speaker 1: really represent this, uh, very misunderstood group of animals, in

1133
01:01:34,360 --> 01:01:36,720
Speaker 1: large part because of that long history we have with

1134
01:01:36,760 --> 01:01:41,040
Speaker 1: them as a competitor um. There's an element of fear

1135
01:01:41,240 --> 01:01:43,600
Speaker 1: when you don't know about something, and you know, much

1136
01:01:43,640 --> 01:01:45,760
Speaker 1: of that fear is rooted in our ancient psyche because

1137
01:01:45,760 --> 01:01:47,920
Speaker 1: of really having to compete and live with these animals

1138
01:01:47,920 --> 01:01:50,280
Speaker 1: and co exists with them. And in the modern day,

1139
01:01:50,320 --> 01:01:52,720
Speaker 1: I mean, let's carry it over, uh, And there's a

1140
01:01:52,760 --> 01:01:56,520
Speaker 1: great deal of misunderstanding about them. Everyone's got opinions about wolves, right,

1141
01:01:57,000 --> 01:02:00,480
Speaker 1: we all do. UM. And when you have an animal

1142
01:02:00,520 --> 01:02:02,760
Speaker 1: that can be difficult to live with, letther it be

1143
01:02:02,800 --> 01:02:06,680
Speaker 1: a grizzly wolf, of cougar, any of these large carnivores UM.

1144
01:02:06,720 --> 01:02:12,520
Speaker 1: You know, those opinions, UH can really cloud how we

1145
01:02:12,560 --> 01:02:15,120
Speaker 1: can co exist with them and whether that means you know,

1146
01:02:15,160 --> 01:02:19,120
Speaker 1: at what level, uh can a population be hunted, what

1147
01:02:19,280 --> 01:02:23,240
Speaker 1: levels should a population be protected? Just the truth about

1148
01:02:23,280 --> 01:02:26,240
Speaker 1: what role they play? UM. And you know, you can

1149
01:02:26,240 --> 01:02:30,640
Speaker 1: look at both extreme sides of of opinions about these animals.

1150
01:02:30,960 --> 01:02:34,200
Speaker 1: You know, the prominent wolf biologists um L David Meach

1151
01:02:34,280 --> 01:02:36,640
Speaker 1: wrote an article number years ago about wolves neither being

1152
01:02:36,680 --> 01:02:39,920
Speaker 1: saints nor centers UH and really tried to, you know,

1153
01:02:40,040 --> 01:02:43,880
Speaker 1: demonstrate to a wider audience this idea that we place

1154
01:02:44,160 --> 01:02:47,120
Speaker 1: a lot of value judgment on these animals. And you know,

1155
01:02:47,120 --> 01:02:49,440
Speaker 1: we always those of us that were closely with these animals.

1156
01:02:49,480 --> 01:02:51,680
Speaker 1: You know, we always talk about the fact that there

1157
01:02:52,440 --> 01:02:56,560
Speaker 1: very few people start conversations about wolves about what they

1158
01:02:56,600 --> 01:02:58,520
Speaker 1: they can't do. It's always like what they can do, Like,

1159
01:02:58,560 --> 01:03:01,320
Speaker 1: look how great they are for these eCos systems, Look

1160
01:03:01,320 --> 01:03:04,680
Speaker 1: how bad they are for these ecosystems. Um. That's why

1161
01:03:04,720 --> 01:03:06,560
Speaker 1: I love that that piece of it because as we

1162
01:03:06,560 --> 01:03:09,200
Speaker 1: were walking up here a game, we're talking about what

1163
01:03:09,400 --> 01:03:12,000
Speaker 1: I want to try to get away from and and

1164
01:03:12,160 --> 01:03:14,080
Speaker 1: shirk is this idea that I have to come to

1165
01:03:14,200 --> 01:03:18,400
Speaker 1: these these very important issues, especially you know what we

1166
01:03:18,480 --> 01:03:22,320
Speaker 1: do with wolves and bears, grizzly bears especially, come to

1167
01:03:22,400 --> 01:03:26,160
Speaker 1: these very important issues with an idea that I'm defending

1168
01:03:26,720 --> 01:03:29,720
Speaker 1: or an idea that I'm trying to um, you know,

1169
01:03:29,800 --> 01:03:33,439
Speaker 1: favor agreement with. And and that's what you know, we

1170
01:03:33,440 --> 01:03:35,360
Speaker 1: we try to shirk and go away from. And I

1171
01:03:35,400 --> 01:03:37,600
Speaker 1: think that you're understanding what these animals do here in

1172
01:03:37,680 --> 01:03:41,720
Speaker 1: Yellowstone is a foundational element to approaching these issues with

1173
01:03:42,120 --> 01:03:44,320
Speaker 1: what do we know about these animals? What do we

1174
01:03:44,360 --> 01:03:47,000
Speaker 1: know about what they can't do, what they can do right?

1175
01:03:47,040 --> 01:03:49,919
Speaker 1: And then and then move forward with trying to make

1176
01:03:50,360 --> 01:03:55,680
Speaker 1: an educated decision, which as is, in a complex environment,

1177
01:03:55,720 --> 01:03:59,480
Speaker 1: and there maybe isn't one right answer, um, because as

1178
01:03:59,480 --> 01:04:01,400
Speaker 1: you well know, left biology and wild life manager is

1179
01:04:01,440 --> 01:04:04,920
Speaker 1: always shifting and changing. So then maybe we could just

1180
01:04:04,920 --> 01:04:07,080
Speaker 1: take a quick look at the history of carnivores shore

1181
01:04:07,120 --> 01:04:09,200
Speaker 1: to set the stage, and then we can let you

1182
01:04:09,240 --> 01:04:11,400
Speaker 1: know and you tell me if if that works for you,

1183
01:04:11,480 --> 01:04:14,080
Speaker 1: But you know it provides a good based on understanding.

1184
01:04:14,240 --> 01:04:16,280
Speaker 1: You know, how we got, you know, a couple of

1185
01:04:16,320 --> 01:04:18,120
Speaker 1: thousand years ago of having a system with all his

1186
01:04:18,280 --> 01:04:21,840
Speaker 1: pieces together to a system that was um largely degraded

1187
01:04:21,840 --> 01:04:24,560
Speaker 1: through the removal of carnivores, a heavy management of elk

1188
01:04:24,640 --> 01:04:27,760
Speaker 1: and other species too. Now in two thousand and twenty,

1189
01:04:27,800 --> 01:04:31,320
Speaker 1: we're looking at a yellow Stone that is operating largely

1190
01:04:31,440 --> 01:04:35,080
Speaker 1: unfettered by heavy management and human human impacts. Let's let's

1191
01:04:35,080 --> 01:04:37,600
Speaker 1: maybe start with where we are, just very briefly, where

1192
01:04:37,600 --> 01:04:39,240
Speaker 1: we are today because we'll run back up here. But

1193
01:04:39,320 --> 01:04:43,960
Speaker 1: where we are today and your estimation, let's say outside

1194
01:04:43,960 --> 01:04:48,160
Speaker 1: of Yellowstone, you know, predators and their native habitats and

1195
01:04:48,160 --> 01:04:51,080
Speaker 1: and where you know, how would you paint that picture

1196
01:04:51,120 --> 01:04:53,400
Speaker 1: for everyone? Because again we're kind of at the seat

1197
01:04:53,400 --> 01:04:55,640
Speaker 1: of it all here. But how do you think about

1198
01:04:55,680 --> 01:04:57,760
Speaker 1: it as a biologist, you know, as a biologist, if

1199
01:04:57,760 --> 01:04:59,920
Speaker 1: you look and you just look at North America or

1200
01:04:59,920 --> 01:05:02,360
Speaker 1: the United States, Um, you know, let's let's choose the

1201
01:05:02,360 --> 01:05:05,160
Speaker 1: little Lower forty A Okay, you know, we're looking at

1202
01:05:05,200 --> 01:05:09,000
Speaker 1: a landscape that used to be rich in large carnivores

1203
01:05:09,120 --> 01:05:11,120
Speaker 1: from the west coast of the East Coast to the

1204
01:05:11,120 --> 01:05:14,480
Speaker 1: border with Canada down into Mexico. And that was a

1205
01:05:14,560 --> 01:05:19,600
Speaker 1: landscape defined by wolves, by cougars, by jaguars in the south,

1206
01:05:19,920 --> 01:05:22,880
Speaker 1: by grizzly bears, black bears, um. And then of course

1207
01:05:22,880 --> 01:05:26,520
Speaker 1: those you know, middle sized carnivores, coyotes and um. And

1208
01:05:26,520 --> 01:05:28,240
Speaker 1: then they were everywhere. I mean, if you just look

1209
01:05:28,280 --> 01:05:30,760
Speaker 1: at the cougar, it is the most widely historically, the

1210
01:05:30,800 --> 01:05:34,160
Speaker 1: most widely distributed large carnivore in the western hemisphere, all

1211
01:05:34,200 --> 01:05:36,000
Speaker 1: the way up into the Yukon down to the tip

1212
01:05:36,000 --> 01:05:39,000
Speaker 1: of South America. The gray wolf in North America were

1213
01:05:39,000 --> 01:05:44,680
Speaker 1: the most widely distributed large carnivores um. And today we

1214
01:05:44,880 --> 01:05:46,840
Speaker 1: see just we'll just choose one of those. We see

1215
01:05:46,880 --> 01:05:49,080
Speaker 1: the cougar largely restricted to the western side of the

1216
01:05:49,160 --> 01:05:52,000
Speaker 1: United States. We have healthy, robust populations and many of

1217
01:05:52,000 --> 01:05:55,240
Speaker 1: our western states, UM, they're not you know, they're they're

1218
01:05:55,280 --> 01:05:58,880
Speaker 1: at threatened areas for sure, UM, very healthy. In other parts.

1219
01:05:59,560 --> 01:06:02,680
Speaker 1: The gray wolf largely restricted to the Rocky Mountain West.

1220
01:06:02,760 --> 01:06:04,920
Speaker 1: We have the small pocket of wolves down in the

1221
01:06:04,960 --> 01:06:10,280
Speaker 1: American Southwest, and the Mexican wolf subspecies and we have wolves,

1222
01:06:10,320 --> 01:06:13,960
Speaker 1: of course, the great late steaks um um, but very

1223
01:06:14,000 --> 01:06:17,840
Speaker 1: much restricted from their former range. Grizzly bears incredibly restricted, right,

1224
01:06:17,920 --> 01:06:20,160
Speaker 1: you know, we're looking at bears and and really small

1225
01:06:20,240 --> 01:06:24,240
Speaker 1: population areas the Greater Yellowstone, on the Glacier Area National

1226
01:06:24,280 --> 01:06:27,480
Speaker 1: Park Area and in northwest Montana. So you know, we

1227
01:06:27,600 --> 01:06:32,000
Speaker 1: see carnivores today, uh, in a very small proportion of

1228
01:06:32,000 --> 01:06:36,000
Speaker 1: the historic representation on these landscapes. UM. In a place

1229
01:06:36,040 --> 01:06:38,640
Speaker 1: like Yellowstone, of course, that was a we you know,

1230
01:06:38,680 --> 01:06:43,480
Speaker 1: we can celebrate, uh that we now have restored carnivores

1231
01:06:43,520 --> 01:06:46,680
Speaker 1: back to this landscape really and only the last thirty years.

1232
01:06:47,160 --> 01:06:51,480
Speaker 1: Of course the historic wolf re introduction ninety six cougar

1233
01:06:51,560 --> 01:06:53,720
Speaker 1: is an actually recolonized on their own in the eighties.

1234
01:06:54,160 --> 01:06:58,280
Speaker 1: Grizzly bears benefiting from the Endangered Species Act, recovering in

1235
01:06:58,400 --> 01:07:01,120
Speaker 1: very much a large part of the Greater Yellowstone and

1236
01:07:01,160 --> 01:07:04,560
Speaker 1: doing very well now. Um. And we can really tout

1237
01:07:04,920 --> 01:07:09,000
Speaker 1: our hard conservation efforts as a society to getting where

1238
01:07:09,000 --> 01:07:12,720
Speaker 1: we are today. Um. Yellowstone is as rich in its

1239
01:07:12,720 --> 01:07:14,960
Speaker 1: carnivores simblage as it has been in the last hundred

1240
01:07:15,000 --> 01:07:18,000
Speaker 1: and fifty years. UM. And and so that's where we

1241
01:07:18,040 --> 01:07:21,800
Speaker 1: are are today. Um, but in many places where they

1242
01:07:21,880 --> 01:07:23,600
Speaker 1: used to be, they are to cross the country and

1243
01:07:23,640 --> 01:07:25,920
Speaker 1: of course you can't have carnivores in many parts of

1244
01:07:25,920 --> 01:07:30,240
Speaker 1: the country anymore. Um. Um biologically you know that the

1245
01:07:30,280 --> 01:07:32,320
Speaker 1: ecology of the landscape just isn't there for them. But

1246
01:07:32,360 --> 01:07:36,360
Speaker 1: also more importantly socially, um. You know, we talked about

1247
01:07:36,360 --> 01:07:40,160
Speaker 1: carnivores being this sort of stubborn, nagging, conflict challenge to

1248
01:07:40,160 --> 01:07:43,040
Speaker 1: coexist with and live with, and and we've learned a

1249
01:07:43,040 --> 01:07:46,440
Speaker 1: lot on how to do so. Um. But for those reasons, um,

1250
01:07:46,600 --> 01:07:48,680
Speaker 1: you know, they have trouble being in a lot of

1251
01:07:48,680 --> 01:07:50,480
Speaker 1: places where they used to be and it never will

1252
01:07:50,520 --> 01:07:54,600
Speaker 1: be again and so um. But that's where we are today. Uh.

1253
01:07:54,640 --> 01:07:56,040
Speaker 1: And I think, how do you see, you know, we're

1254
01:07:56,080 --> 01:08:00,120
Speaker 1: here looking at a mountain killsite. I could probably I

1255
01:08:00,120 --> 01:08:02,800
Speaker 1: spend enough time by the Hollywood sign, I would probably

1256
01:08:02,880 --> 01:08:05,960
Speaker 1: check out a similar animal. And and I think that

1257
01:08:06,080 --> 01:08:08,960
Speaker 1: just denotes something to think about as we go through

1258
01:08:08,960 --> 01:08:12,440
Speaker 1: this conversation. You know, on both sides of that fence,

1259
01:08:13,440 --> 01:08:17,320
Speaker 1: you have, you know, an environmentalist a protectionist view that says,

1260
01:08:17,400 --> 01:08:20,080
Speaker 1: let's you know, we're not gonna hunt these animals yet.

1261
01:08:20,160 --> 01:08:22,519
Speaker 1: You know, the hunter would say, well, we have to

1262
01:08:22,560 --> 01:08:25,519
Speaker 1: manage this population in these urban areas. You're probably gonna

1263
01:08:25,520 --> 01:08:28,519
Speaker 1: have to kill these animals anyway. UM, why not allow

1264
01:08:28,600 --> 01:08:31,479
Speaker 1: hunters to take part in that? And I think that's

1265
01:08:31,520 --> 01:08:33,280
Speaker 1: one that you know, we talked about all the time.

1266
01:08:33,560 --> 01:08:37,360
Speaker 1: You know, how they're they're building wildlife underpasses and overpasses

1267
01:08:37,400 --> 01:08:41,200
Speaker 1: and many highways in California, and so there's you know

1268
01:08:41,280 --> 01:08:43,240
Speaker 1: that that dynamic is an important thing to think of.

1269
01:08:43,320 --> 01:08:46,479
Speaker 1: I think it is. I think where what we've learned

1270
01:08:46,479 --> 01:08:49,640
Speaker 1: a great deal about is actually just how well we

1271
01:08:49,760 --> 01:08:57,040
Speaker 1: can coexist with large carnivores UH, given certain um um

1272
01:08:57,160 --> 01:09:01,000
Speaker 1: baseline needs for both human and the carnivorre You. Carnivores

1273
01:09:01,040 --> 01:09:06,200
Speaker 1: need uh food obviously, they need space to live in,

1274
01:09:06,479 --> 01:09:10,200
Speaker 1: and most importantly, they need to live in the landscape

1275
01:09:10,200 --> 01:09:15,120
Speaker 1: where there is not human persecution for them to be successful. UM.

1276
01:09:15,280 --> 01:09:21,479
Speaker 1: Humans need uh safety and security UM, because you know,

1277
01:09:21,520 --> 01:09:24,439
Speaker 1: carnivores can be a risk. You know, any wildlife can

1278
01:09:24,439 --> 01:09:26,439
Speaker 1: be a risk of person. Um. There are lots of

1279
01:09:26,520 --> 01:09:28,960
Speaker 1: risk in our lives every day that we face UM.

1280
01:09:29,080 --> 01:09:30,960
Speaker 1: And and so if you kind of take those things

1281
01:09:30,960 --> 01:09:33,280
Speaker 1: into consideration on both what the carnivores needs are and

1282
01:09:33,320 --> 01:09:36,080
Speaker 1: what the human needs are um as as sort of

1283
01:09:36,120 --> 01:09:39,639
Speaker 1: your framework, we still have a great capacity to coexist

1284
01:09:39,760 --> 01:09:42,240
Speaker 1: with them. And yes, here we are in a wild

1285
01:09:42,640 --> 01:09:44,639
Speaker 1: you know, national park, and we've got a cougar kill

1286
01:09:44,680 --> 01:09:46,160
Speaker 1: down below us. But you're right, you could be in

1287
01:09:46,200 --> 01:09:50,320
Speaker 1: Griffith Park outside the Hollywood sign and come across us

1288
01:09:50,439 --> 01:09:53,840
Speaker 1: the identical looking you know kill a deer kill in

1289
01:09:53,840 --> 01:09:58,600
Speaker 1: that area, but perhaps and poodle and um, you know,

1290
01:09:58,640 --> 01:10:01,840
Speaker 1: and what a mountain lion needs in in southern California's

1291
01:10:01,840 --> 01:10:04,120
Speaker 1: ability to move across the landscape without getting hit by

1292
01:10:04,120 --> 01:10:06,759
Speaker 1: a car, uh, to be able to not get poisoned

1293
01:10:06,760 --> 01:10:09,960
Speaker 1: by rodenticide UM, which is it was, which is a

1294
01:10:10,080 --> 01:10:12,360
Speaker 1: challenge in some of these urban areas where they interact

1295
01:10:12,439 --> 01:10:15,560
Speaker 1: so UM and and A in a capacity and willingness

1296
01:10:15,560 --> 01:10:18,280
Speaker 1: for humans to be tolerant of them. And that's a

1297
01:10:18,280 --> 01:10:20,120
Speaker 1: hard thing. And that's what we struggle, I think the

1298
01:10:20,120 --> 01:10:24,439
Speaker 1: most with is the sort of the societal acceptance of

1299
01:10:24,439 --> 01:10:27,760
Speaker 1: of coexisting, the willingness to UM. Case some point right

1300
01:10:27,760 --> 01:10:30,840
Speaker 1: here the town of gardner Um, you know, a couple

1301
01:10:30,840 --> 01:10:33,400
Speaker 1: of weeks are about a month ago, there was a

1302
01:10:33,400 --> 01:10:36,760
Speaker 1: a cougar in town, a cougar family in town Um

1303
01:10:36,880 --> 01:10:39,439
Speaker 1: and the state of Montana, following their management plan, did

1304
01:10:39,479 --> 01:10:41,920
Speaker 1: the best they could to deal with the situation. It

1305
01:10:42,000 --> 01:10:44,880
Speaker 1: was in someone's backyardy to kill the deer. It probably

1306
01:10:44,880 --> 01:10:47,479
Speaker 1: wasn't a threat to anyone. Uh, probably would have moved

1307
01:10:47,520 --> 01:10:50,760
Speaker 1: on eventually after made it's kill um. But you know,

1308
01:10:50,800 --> 01:10:52,800
Speaker 1: there was a concern by a particular landowner, and the

1309
01:10:52,800 --> 01:10:56,519
Speaker 1: state responded and and that cat was removed. And many

1310
01:10:56,520 --> 01:10:58,639
Speaker 1: people in the community struggled with that. You know, how

1311
01:10:58,640 --> 01:11:00,600
Speaker 1: do we can't we do bad or we're Gardener with

1312
01:11:00,640 --> 01:11:02,519
Speaker 1: the edge of the National Park. But others said, hey,

1313
01:11:02,600 --> 01:11:05,400
Speaker 1: you know, I was worried. Uh, it was in my backyard.

1314
01:11:05,479 --> 01:11:08,080
Speaker 1: I was in threat and um and you know that's

1315
01:11:08,240 --> 01:11:10,320
Speaker 1: sort of a day and a day out sort of

1316
01:11:10,400 --> 01:11:13,040
Speaker 1: example of what we deal with. I think it's much

1317
01:11:13,080 --> 01:11:17,320
Speaker 1: more accepting for people to have carnivores where we are

1318
01:11:17,360 --> 01:11:20,320
Speaker 1: around us, obviously, than when you're in an urban area

1319
01:11:20,400 --> 01:11:23,200
Speaker 1: or even a small, uh mountain town like Gardener. Would

1320
01:11:23,200 --> 01:11:26,120
Speaker 1: you say it's easier, it's easier for it to go

1321
01:11:26,240 --> 01:11:28,960
Speaker 1: that way. It seems to me it's easier because because

1322
01:11:28,960 --> 01:11:31,280
Speaker 1: everybody you're run into as soon as you feel unsafe,

1323
01:11:31,360 --> 01:11:33,200
Speaker 1: you want to you want to halt that feeling, you

1324
01:11:33,240 --> 01:11:36,000
Speaker 1: want to stop that threat. That's that's as natural for us,

1325
01:11:36,040 --> 01:11:38,280
Speaker 1: as natural as for a predator want to kill a

1326
01:11:38,320 --> 01:11:41,240
Speaker 1: deer in somebody's backyard. So I think that's probably the

1327
01:11:41,280 --> 01:11:45,599
Speaker 1: easier way out, the more human way out, which sets

1328
01:11:45,680 --> 01:11:49,679
Speaker 1: up it's harder to coexist. Right. People don't want to

1329
01:11:49,840 --> 01:11:53,280
Speaker 1: have to make those decisions. And again that decision being made,

1330
01:11:54,120 --> 01:11:56,320
Speaker 1: it's easy to say, I want all all mountain lions

1331
01:11:56,360 --> 01:11:58,240
Speaker 1: to live until there's one in your backyard much on

1332
01:11:58,320 --> 01:12:01,200
Speaker 1: it deer, Yeah right, And you know, and I think

1333
01:12:01,200 --> 01:12:03,320
Speaker 1: part of that is education. I mean, I think the

1334
01:12:03,360 --> 01:12:05,040
Speaker 1: more we learned about and the more we learned about,

1335
01:12:05,040 --> 01:12:06,640
Speaker 1: you know, what are the real risks of having this

1336
01:12:06,720 --> 01:12:10,080
Speaker 1: cougar in my back there? Um? And uh, you know,

1337
01:12:10,120 --> 01:12:12,320
Speaker 1: we don't want a wild animal like a cougar just

1338
01:12:12,360 --> 01:12:14,559
Speaker 1: hanging around town. And there can be you know, things

1339
01:12:14,560 --> 01:12:17,360
Speaker 1: like habituation that occur more commonly with things like bears

1340
01:12:17,439 --> 01:12:20,280
Speaker 1: or coyotes. But um, as soon as that line is

1341
01:12:20,360 --> 01:12:23,960
Speaker 1: crossed with habituation and food reward. Um. And that wasn't

1342
01:12:23,960 --> 01:12:25,760
Speaker 1: the case with this particular example I just gave. But

1343
01:12:25,800 --> 01:12:28,320
Speaker 1: that is a common case. Um. A black bear was

1344
01:12:28,360 --> 01:12:30,479
Speaker 1: just removed in Yellowstone a couple of days ago at

1345
01:12:30,479 --> 01:12:33,000
Speaker 1: a campsite because it came into camp and and started

1346
01:12:33,000 --> 01:12:36,160
Speaker 1: feeding on campers. It actually bet a woman. It was habituated,

1347
01:12:36,200 --> 01:12:39,519
Speaker 1: it was food habituated. She's okay, fortunately, and they park

1348
01:12:39,680 --> 01:12:41,960
Speaker 1: acted quickly and remove that bear. Um. And that is

1349
01:12:42,000 --> 01:12:43,760
Speaker 1: a bear that has gotten a food reward. And so

1350
01:12:44,040 --> 01:12:45,600
Speaker 1: you know, we struggle with that every day in a

1351
01:12:45,600 --> 01:12:47,960
Speaker 1: place like Yellowstone. Is how do we keep Yellowstone wild

1352
01:12:48,200 --> 01:12:51,360
Speaker 1: yet still provide that visitor enjoyment and carnival. You know,

1353
01:12:51,560 --> 01:12:53,120
Speaker 1: we can look at the person going up close to

1354
01:12:53,120 --> 01:12:54,840
Speaker 1: the bison, we can look at the person going close

1355
01:12:54,880 --> 01:12:58,000
Speaker 1: to the elk, people approaching bears. That just that excitement

1356
01:12:58,040 --> 01:13:00,439
Speaker 1: that experienced with wild nature is so for into so

1357
01:13:00,439 --> 01:13:04,760
Speaker 1: many people that you forget. Um. Yeah, the reasoning goes

1358
01:13:04,800 --> 01:13:06,760
Speaker 1: out the window. And so we struggle with that as

1359
01:13:06,800 --> 01:13:09,439
Speaker 1: a park. Yet you know, at it's our core, we

1360
01:13:09,560 --> 01:13:15,160
Speaker 1: really value having a place where people can still experience that. Well,

1361
01:13:15,200 --> 01:13:17,799
Speaker 1: I've said this, you're probably more you're probably more inclined

1362
01:13:17,840 --> 01:13:19,960
Speaker 1: to say no comment to this, but I'm I can

1363
01:13:20,000 --> 01:13:22,800
Speaker 1: say what I want. So I have thought about this

1364
01:13:22,920 --> 01:13:25,000
Speaker 1: and I thought like, well, okay, we're talking earlier about

1365
01:13:25,720 --> 01:13:28,360
Speaker 1: Yellowstone is like an ambassador to wild places for folks

1366
01:13:28,360 --> 01:13:30,639
Speaker 1: that that don't get to see this, that don't get

1367
01:13:30,680 --> 01:13:32,559
Speaker 1: to experience this, and kind of a more visceral level,

1368
01:13:33,120 --> 01:13:35,200
Speaker 1: I think maybe Yellowstone is like listen, I'll let you

1369
01:13:35,240 --> 01:13:37,240
Speaker 1: have that relationship with me, but I'm gonna take a

1370
01:13:37,240 --> 01:13:39,599
Speaker 1: few of you. A few of you're gonna get bitten,

1371
01:13:39,960 --> 01:13:42,320
Speaker 1: a couple of you're gonna get gored. This is the

1372
01:13:42,360 --> 01:13:44,719
Speaker 1: tax that you must pay for me to allow you

1373
01:13:45,240 --> 01:13:48,160
Speaker 1: to come here with your RVs and with your and

1374
01:13:48,160 --> 01:13:50,800
Speaker 1: and to act like this is just a drive by wilderness,

1375
01:13:51,400 --> 01:13:54,040
Speaker 1: and the wilderness is like not. But here's some reality,

1376
01:13:54,200 --> 01:13:56,479
Speaker 1: because that's for us to kind of treat it that

1377
01:13:56,520 --> 01:13:59,080
Speaker 1: way as humans, that that it that is, there is

1378
01:13:59,120 --> 01:14:02,040
Speaker 1: some amusement to be game, There is some like that's

1379
01:14:02,080 --> 01:14:04,519
Speaker 1: that again, we've discussed the value of that, given the

1380
01:14:04,560 --> 01:14:09,800
Speaker 1: disconnection with these landscapes, but also reality of nature every

1381
01:14:09,800 --> 01:14:12,639
Speaker 1: once in a while just decides to show itself, which

1382
01:14:12,680 --> 01:14:15,160
Speaker 1: is an interesting dynamic. And then and that you know,

1383
01:14:15,200 --> 01:14:20,240
Speaker 1: as as managers, uh, in Yellowstone, we struggle, Many people

1384
01:14:20,240 --> 01:14:22,559
Speaker 1: struggle and have through history in this park is is

1385
01:14:22,560 --> 01:14:25,439
Speaker 1: what is wild? What is natural? What is pristine? What

1386
01:14:25,560 --> 01:14:27,840
Speaker 1: is wildness? And you know, the best we can do

1387
01:14:27,920 --> 01:14:30,439
Speaker 1: when it comes to things like wildlife, for example, is

1388
01:14:30,439 --> 01:14:33,240
Speaker 1: is really you know, some people come out here and

1389
01:14:33,280 --> 01:14:35,519
Speaker 1: see a bison grazing near the road, or you know,

1390
01:14:35,560 --> 01:14:37,439
Speaker 1: I see a radio colored wolf. We get this a

1391
01:14:37,520 --> 01:14:41,640
Speaker 1: law and into them that's somehow less wild. Um. You know,

1392
01:14:41,680 --> 01:14:43,599
Speaker 1: I always battle that back by saying, you know, what's

1393
01:14:43,600 --> 01:14:47,040
Speaker 1: about that wolf that's wearing a collar, that bison grazing

1394
01:14:47,040 --> 01:14:49,400
Speaker 1: on the lawn and mammoth? I mean, what's not wild

1395
01:14:49,439 --> 01:14:52,439
Speaker 1: about those animals? Having to survive the four seasons of

1396
01:14:52,520 --> 01:14:55,240
Speaker 1: the Greater Yale Soune ecosystem. A wolf has to run

1397
01:14:55,320 --> 01:14:57,360
Speaker 1: up every couple of days and and grab onto an

1398
01:14:57,360 --> 01:15:00,080
Speaker 1: elk with its mouth and take it down, a it

1399
01:15:00,120 --> 01:15:03,720
Speaker 1: off a grizzly bear. At what's not wild about that?

1400
01:15:03,800 --> 01:15:05,680
Speaker 1: But you know, when I think at a core, when

1401
01:15:05,720 --> 01:15:08,880
Speaker 1: we define wildness and our animals here and yes we

1402
01:15:08,920 --> 01:15:11,479
Speaker 1: have human tolerance, we do have habituation in some cases.

1403
01:15:11,479 --> 01:15:14,880
Speaker 1: But you know, having an animal that can live out

1404
01:15:14,880 --> 01:15:20,280
Speaker 1: its life under the natural ecological subject to the ecological

1405
01:15:20,280 --> 01:15:25,280
Speaker 1: forces of nature, you know, surviving, feeding, raising young breeding

1406
01:15:25,880 --> 01:15:29,760
Speaker 1: um and and largely protected from human impacts. That's really

1407
01:15:29,760 --> 01:15:33,120
Speaker 1: what we're striving for. And and and you know, vast

1408
01:15:33,479 --> 01:15:35,559
Speaker 1: majority of what you see with the els one's wildlife

1409
01:15:35,600 --> 01:15:38,960
Speaker 1: adheres to that, um and and that's that's what we're

1410
01:15:38,960 --> 01:15:41,160
Speaker 1: trying to promote and protect here. And you could push

1411
01:15:41,200 --> 01:15:43,040
Speaker 1: back on that, but like the least wild thing about

1412
01:15:43,040 --> 01:15:46,400
Speaker 1: it is you. Yeah, you're the least wild thing about

1413
01:15:46,439 --> 01:15:48,640
Speaker 1: this wilderness. And that's something that we all just have

1414
01:15:48,680 --> 01:15:51,040
Speaker 1: to live with. We're never going back. We're not going

1415
01:15:51,080 --> 01:15:53,280
Speaker 1: to go back. Um and in order do we want

1416
01:15:53,320 --> 01:15:55,599
Speaker 1: to go back, UM, So we just have to live

1417
01:15:55,640 --> 01:15:57,960
Speaker 1: with this dichotomy and work with it as you have

1418
01:15:58,000 --> 01:16:01,000
Speaker 1: to every day. I'm sure UM to understand this place

1419
01:16:01,280 --> 01:16:03,639
Speaker 1: and people, you know, they there's a there's a thirst,

1420
01:16:03,960 --> 01:16:08,080
Speaker 1: there's a desire UM where whatever background you come from,

1421
01:16:08,120 --> 01:16:11,000
Speaker 1: whatever landscape you grew up in, urban or wild or otherwise,

1422
01:16:11,000 --> 01:16:14,280
Speaker 1: when you come to a place like Yellowstone, UM, there

1423
01:16:14,360 --> 01:16:17,920
Speaker 1: is this thirst for you know, raw wild nature and

1424
01:16:17,920 --> 01:16:20,920
Speaker 1: and and and you have that opportunity to experience that here.

1425
01:16:20,920 --> 01:16:23,599
Speaker 1: And people deal with that in different ways and um

1426
01:16:23,680 --> 01:16:25,840
Speaker 1: embrace it in different ways, but you know, it really

1427
01:16:25,920 --> 01:16:28,360
Speaker 1: is the treasure of this place is is. And you know,

1428
01:16:28,479 --> 01:16:30,160
Speaker 1: those of us that live are fortunate to live in

1429
01:16:30,160 --> 01:16:33,000
Speaker 1: these wild areas in general, in a place like Montana,

1430
01:16:33,040 --> 01:16:35,840
Speaker 1: we we do see that all all the time. Um.

1431
01:16:35,920 --> 01:16:38,240
Speaker 1: But for many this is their one shot at that

1432
01:16:38,320 --> 01:16:40,640
Speaker 1: maybe there once in a lifetime opportunity. And and I

1433
01:16:40,640 --> 01:16:42,800
Speaker 1: think that resonates with many people. And I was telling you,

1434
01:16:42,800 --> 01:16:44,760
Speaker 1: you know, as a as a kid from the East

1435
01:16:44,800 --> 01:16:47,559
Speaker 1: Coast to come out here. And I was telling you

1436
01:16:47,640 --> 01:16:50,519
Speaker 1: some stories when we first met down there in Mammoth.

1437
01:16:51,120 --> 01:16:53,679
Speaker 1: I've seen wolves, we see, we saw wolves, bear hunting

1438
01:16:53,720 --> 01:16:55,720
Speaker 1: this year. We heard a wolf how while I was

1439
01:16:55,760 --> 01:16:57,479
Speaker 1: having a trail camera a couple of weeks ago with

1440
01:16:57,560 --> 01:17:00,599
Speaker 1: a with a buddy of mine. We've seen wolf tracks,

1441
01:17:00,640 --> 01:17:03,800
Speaker 1: We've seen grizzly tracks, we've seen grizzly scat. All of

1442
01:17:03,840 --> 01:17:08,639
Speaker 1: these like represent this seminal experience that kind of can

1443
01:17:08,720 --> 01:17:12,680
Speaker 1: only happen in proximity to the rocky mountains, you know.

1444
01:17:13,000 --> 01:17:16,000
Speaker 1: And and that's what I think brings people like you

1445
01:17:16,040 --> 01:17:21,320
Speaker 1: and I you're from Connecticut original I'm sorry, um here

1446
01:17:21,400 --> 01:17:24,599
Speaker 1: because you know you understand, like you know the place

1447
01:17:24,640 --> 01:17:28,839
Speaker 1: to scene and you understand these ideas. I grew up dreaming,

1448
01:17:30,080 --> 01:17:33,120
Speaker 1: dreaming of being on a landscape with in place to

1449
01:17:33,160 --> 01:17:36,160
Speaker 1: see landscape, and yellow sounds the closest thing I've come

1450
01:17:36,160 --> 01:17:38,120
Speaker 1: to that. Well, and then you think of I used

1451
01:17:38,120 --> 01:17:41,000
Speaker 1: to I grew up watching like Lonesome Dub. If only

1452
01:17:41,040 --> 01:17:44,200
Speaker 1: I could ride a horse from Texas from the Del

1453
01:17:44,320 --> 01:17:47,840
Speaker 1: Rio all the way up to the Montana. You know,

1454
01:17:47,880 --> 01:17:50,400
Speaker 1: it's a bad to Paradise Valley. I phone couldn't do that,

1455
01:17:50,439 --> 01:17:53,080
Speaker 1: but it certainly could drive a you all, and so

1456
01:17:53,280 --> 01:17:55,439
Speaker 1: that's what we did. But yeah, I mean, so to

1457
01:17:55,760 --> 01:17:59,320
Speaker 1: back to these the animals themselves, and you know we understand.

1458
01:18:00,040 --> 01:18:01,760
Speaker 1: I think maybe I'll start like what you've learned about

1459
01:18:01,760 --> 01:18:04,200
Speaker 1: these animals and then maybe move through their roles in

1460
01:18:04,240 --> 01:18:08,160
Speaker 1: the ecosystem, because that's that's ultimately the connective tissue too.

1461
01:18:08,000 --> 01:18:13,000
Speaker 1: To the debate. Um in your job, describe like your

1462
01:18:13,040 --> 01:18:16,400
Speaker 1: interactions with these predators, what predators you interact with most,

1463
01:18:16,439 --> 01:18:18,720
Speaker 1: and kind of like go through each one and then

1464
01:18:18,840 --> 01:18:20,880
Speaker 1: you know, well let's talk about kind of what you've learned.

1465
01:18:22,120 --> 01:18:24,320
Speaker 1: So my job here in Yellowstone is uh for the

1466
01:18:24,360 --> 01:18:27,080
Speaker 1: Park Services. I'm a wildlife biologists and I've been here

1467
01:18:27,120 --> 01:18:30,760
Speaker 1: for twenty three years and throughout that whole career, I've

1468
01:18:30,840 --> 01:18:35,920
Speaker 1: largely been involved with the Yelsen Wolf Project UM and

1469
01:18:35,920 --> 01:18:38,920
Speaker 1: and as well as the Yellowstone cougars here and those

1470
01:18:38,920 --> 01:18:42,439
Speaker 1: are my two chief roles in addition to overseeing and

1471
01:18:42,479 --> 01:18:46,080
Speaker 1: help um UH manage the elk research program. And of

1472
01:18:46,120 --> 01:18:49,719
Speaker 1: course those three animals, wolves, cougars and elk are sort

1473
01:18:49,720 --> 01:18:52,800
Speaker 1: of that trifecta of predator prey dynamics here in in

1474
01:18:52,840 --> 01:18:56,160
Speaker 1: this ecosystem, and ultimately our goal is to understand of

1475
01:18:56,200 --> 01:18:58,679
Speaker 1: course wolves. I came in here year and a half

1476
01:18:58,680 --> 01:19:02,080
Speaker 1: after the last wolf wolves were brought that down from Canada,

1477
01:19:02,400 --> 01:19:06,240
Speaker 1: released from pens um And and from that moment forward,

1478
01:19:06,520 --> 01:19:09,720
Speaker 1: UH the Olsome Wolf Project had the vision early on

1479
01:19:09,880 --> 01:19:13,880
Speaker 1: project leader Doug Smith Mike Phillips. Originally Doug Smith took

1480
01:19:13,920 --> 01:19:18,439
Speaker 1: over UH in n UM. That vision that we've had

1481
01:19:18,479 --> 01:19:20,680
Speaker 1: throughout the last twenty five years is to is to

1482
01:19:20,800 --> 01:19:23,679
Speaker 1: understand this wonderful experiment of bringing back a carnivore after

1483
01:19:23,680 --> 01:19:26,360
Speaker 1: it has gone for seventy years and and understanding its

1484
01:19:26,360 --> 01:19:32,360
Speaker 1: biology and furthermore it's relationship with its primary prey being elk.

1485
01:19:32,479 --> 01:19:35,479
Speaker 1: Of course other species to our program is meant to

1486
01:19:35,520 --> 01:19:39,040
Speaker 1: be a broad view of wolf biology, but more importantly,

1487
01:19:39,080 --> 01:19:42,880
Speaker 1: community ecology, like all the pieces put together, that's really

1488
01:19:42,920 --> 01:19:45,720
Speaker 1: the value. That's a very important term. You know, I

1489
01:19:45,760 --> 01:19:48,400
Speaker 1: don't think of myself as a wolf biologist or cougar biologist,

1490
01:19:48,400 --> 01:19:52,280
Speaker 1: but a biologist trying to understand how uh these carnivores

1491
01:19:52,320 --> 01:19:55,639
Speaker 1: and their prey interact on this landscape. Um and and

1492
01:19:55,680 --> 01:19:58,240
Speaker 1: so you know, a big part of that work is

1493
01:19:58,360 --> 01:20:01,200
Speaker 1: a lot of hard data c action every year, every winter,

1494
01:20:01,280 --> 01:20:04,479
Speaker 1: every summer, UH studies that have been put in place

1495
01:20:04,520 --> 01:20:07,680
Speaker 1: from the very beginning to study uh these animals. And

1496
01:20:07,760 --> 01:20:10,240
Speaker 1: big part of that is understanding their population dynamics, so

1497
01:20:10,400 --> 01:20:15,640
Speaker 1: counting them um uh and um understanding and take a

1498
01:20:15,640 --> 01:20:17,439
Speaker 1: little breaks, just take a brain of conversation. We've got

1499
01:20:17,479 --> 01:20:20,479
Speaker 1: a couple of elk running glass of elk here. You know,

1500
01:20:20,520 --> 01:20:23,880
Speaker 1: I caught them earlier running down that drainage. They seem

1501
01:20:23,960 --> 01:20:26,120
Speaker 1: to be moving pretty good. And I don't know if

1502
01:20:26,120 --> 01:20:30,240
Speaker 1: they're just something pushed them out of that drainage trying

1503
01:20:30,240 --> 01:20:32,880
Speaker 1: to get into new area. The flies are bugging them.

1504
01:20:33,000 --> 01:20:35,240
Speaker 1: They're moving down here. There's a little bit of water. Yeah,

1505
01:20:35,280 --> 01:20:37,720
Speaker 1: that could be the area, that cool marshy area. It

1506
01:20:37,800 --> 01:20:39,360
Speaker 1: is cooler down there in the bottom or that hill

1507
01:20:39,439 --> 01:20:42,200
Speaker 1: site was for sure. But yeah, as as I was,

1508
01:20:42,479 --> 01:20:44,080
Speaker 1: I just was, as I'm sitting here, I'm like, we're

1509
01:20:44,080 --> 01:20:49,000
Speaker 1: not seeing much. We're gonna see something. It's it's to

1510
01:20:50,280 --> 01:20:54,519
Speaker 1: that one in the back, younger one calf, but yearling,

1511
01:20:54,960 --> 01:20:57,200
Speaker 1: yearling and then you know an adult. Maybe it's from

1512
01:20:57,280 --> 01:21:02,040
Speaker 1: all three or four year old. Yeah, looking cow, that's great. Yeah,

1513
01:21:02,080 --> 01:21:04,760
Speaker 1: I drew a b tag for cow's right up the

1514
01:21:04,760 --> 01:21:12,920
Speaker 1: Paradise Valley. Um uh so so yeah. So you know,

1515
01:21:12,920 --> 01:21:14,920
Speaker 1: one of the main goals is, you know, counting the predators.

1516
01:21:14,920 --> 01:21:16,320
Speaker 1: How many do we have, how many wolves we have,

1517
01:21:16,360 --> 01:21:19,040
Speaker 1: how many cougars we have? And that's that's harder than

1518
01:21:19,080 --> 01:21:20,599
Speaker 1: you think. It requires a lot of work, you know.

1519
01:21:20,640 --> 01:21:23,639
Speaker 1: With with wolves, the best tool we have to account

1520
01:21:23,640 --> 01:21:26,640
Speaker 1: of his coloring them. Each year we use a helicopter.

1521
01:21:26,880 --> 01:21:29,679
Speaker 1: We dart wolves from the helicopter, we put a collar

1522
01:21:29,760 --> 01:21:32,439
Speaker 1: on them. We try to get a couple individuals within

1523
01:21:32,479 --> 01:21:35,240
Speaker 1: a pack wearing collars and that allows us throughout the

1524
01:21:35,360 --> 01:21:37,840
Speaker 1: year to follow that pack. We monitor them from there.

1525
01:21:38,040 --> 01:21:40,760
Speaker 1: From the ground. Yellowstone is, of course one of the

1526
01:21:40,800 --> 01:21:43,799
Speaker 1: best place to view wild wolves, and so our studies

1527
01:21:43,800 --> 01:21:46,719
Speaker 1: have been largely observational in addition to the radio collars,

1528
01:21:46,720 --> 01:21:48,720
Speaker 1: and that's really given us very accurate counts. How many

1529
01:21:48,720 --> 01:21:51,160
Speaker 1: packs do we have, how many wolves we have in

1530
01:21:51,160 --> 01:21:53,320
Speaker 1: a pack, who are the breeders, how many pups are born,

1531
01:21:53,360 --> 01:21:55,599
Speaker 1: how many pups survive, And that's kind of the heart

1532
01:21:55,600 --> 01:21:58,640
Speaker 1: and soul of understanding their population dynamics UM. And then

1533
01:21:58,640 --> 01:22:00,800
Speaker 1: we want to understand their food habits and and so

1534
01:22:00,880 --> 01:22:04,560
Speaker 1: we do primarily two main field seasons in the wintertime

1535
01:22:04,600 --> 01:22:07,360
Speaker 1: in the summertime, and we do a thirty day predation

1536
01:22:07,360 --> 01:22:10,400
Speaker 1: steady early winter, thirty consecutive days. Early winter. Of course

1537
01:22:10,400 --> 01:22:12,439
Speaker 1: elk are in their best shape. They've come off a

1538
01:22:12,479 --> 01:22:15,439
Speaker 1: summer and fall of good forage, good fat reserves. They're

1539
01:22:15,520 --> 01:22:17,600
Speaker 1: much more difficult for wolves to kill. And then we

1540
01:22:17,640 --> 01:22:19,479
Speaker 1: look at it for thirty days in the month of March,

1541
01:22:19,520 --> 01:22:21,639
Speaker 1: that's the tail and winter. That's when elk are most

1542
01:22:21,720 --> 01:22:25,760
Speaker 1: vulnerable to winter in predation. They're kind of exhausting body reserves,

1543
01:22:26,000 --> 01:22:27,840
Speaker 1: and so we try to understand those book ends of

1544
01:22:27,840 --> 01:22:30,879
Speaker 1: the winter season to to see what that winter effect

1545
01:22:30,960 --> 01:22:33,120
Speaker 1: is of predation. We also do the same work and

1546
01:22:33,160 --> 01:22:35,519
Speaker 1: made June and July for predation again to look at

1547
01:22:36,320 --> 01:22:38,760
Speaker 1: what those summer predation patterns are and that's what made

1548
01:22:38,840 --> 01:22:41,519
Speaker 1: Yellowstone unique. And really we've embraced both old school field

1549
01:22:41,520 --> 01:22:45,040
Speaker 1: biology as well as technology like GPS callers. We still

1550
01:22:45,040 --> 01:22:47,840
Speaker 1: rely on the you know, the classical bush pilot that

1551
01:22:47,840 --> 01:22:50,200
Speaker 1: flies the super cub for us. Over the years, we've

1552
01:22:50,200 --> 01:22:54,280
Speaker 1: had some really talented UM, magnificent pilots UM and you know,

1553
01:22:54,439 --> 01:22:56,559
Speaker 1: and we take on volunteer technicians in the winter, in

1554
01:22:56,560 --> 01:22:59,880
Speaker 1: the summer, and and you know, thousands and thousands of hours,

1555
01:23:00,000 --> 01:23:02,960
Speaker 1: thousands and thousands of miles over twenty five years has

1556
01:23:03,000 --> 01:23:05,679
Speaker 1: given us probably one of the best pictures of predation

1557
01:23:05,880 --> 01:23:09,360
Speaker 1: in a predator pray system worldwide. We're very proud of

1558
01:23:09,360 --> 01:23:11,920
Speaker 1: that and UM and and so that's what we do

1559
01:23:11,960 --> 01:23:15,280
Speaker 1: with bowls. With cougars. There's been different periods of cougar research.

1560
01:23:15,560 --> 01:23:17,920
Speaker 1: They did not get reintroduced yelse and they came back

1561
01:23:17,960 --> 01:23:19,799
Speaker 1: on their own in the eighties. That you know, cougar's

1562
01:23:19,840 --> 01:23:23,200
Speaker 1: benefited by becoming a you could say their conservation is

1563
01:23:23,280 --> 01:23:27,679
Speaker 1: largely benefited by a UM becoming a trophy, having trophy

1564
01:23:27,720 --> 01:23:30,240
Speaker 1: game status. There are also protections in place in the

1565
01:23:30,280 --> 01:23:32,559
Speaker 1: sixties and seventies, and many of the document in Western

1566
01:23:32,600 --> 01:23:37,240
Speaker 1: states bounties were eliminated. They became quota systems and regulated

1567
01:23:37,280 --> 01:23:40,160
Speaker 1: and seasons, and that set the stage for their recovery

1568
01:23:40,160 --> 01:23:41,880
Speaker 1: to a place like Yellowstone. So they kind of crept

1569
01:23:42,320 --> 01:23:44,760
Speaker 1: crept back in on their own. Uh. And there are

1570
01:23:44,920 --> 01:23:48,719
Speaker 1: several phases of research that occurred in the late eighties

1571
01:23:48,720 --> 01:23:51,559
Speaker 1: prior to wolves being reintroduced. It created this wonderful experiment

1572
01:23:51,560 --> 01:23:53,720
Speaker 1: and then look at what happens when you reintroduce a

1573
01:23:53,800 --> 01:23:56,679
Speaker 1: top predator, another predator who's a major competitor the wolf.

1574
01:23:57,240 --> 01:23:59,040
Speaker 1: And so then there was a wonderful study led by

1575
01:23:59,080 --> 01:24:03,360
Speaker 1: Tony Ruth, fabulous biologists that let that study post wolf

1576
01:24:03,400 --> 01:24:06,160
Speaker 1: ree introduction for about six years. Uh. And then I

1577
01:24:06,160 --> 01:24:08,200
Speaker 1: started back up the study in two thousand and fourteen,

1578
01:24:08,280 --> 01:24:10,280
Speaker 1: which is still ongoing now. And so we've had these

1579
01:24:10,320 --> 01:24:13,000
Speaker 1: little uh snippets of cougars and the same thing. How

1580
01:24:13,040 --> 01:24:15,439
Speaker 1: many do we have and what are their food habits?

1581
01:24:16,040 --> 01:24:19,360
Speaker 1: Does that include the trophic cascade kind of this? Can

1582
01:24:19,400 --> 01:24:21,200
Speaker 1: you explain that? I guess I always mentioned that I

1583
01:24:21,240 --> 01:24:26,000
Speaker 1: want so you know, Yellowstone has um I'd say the

1584
01:24:26,040 --> 01:24:31,120
Speaker 1: first real ecological study that, well, there's a couple, but

1585
01:24:31,160 --> 01:24:33,000
Speaker 1: one of the ones that might be most familiar to

1586
01:24:33,080 --> 01:24:36,160
Speaker 1: students from high school biology. It would be the work

1587
01:24:36,200 --> 01:24:39,559
Speaker 1: in the marine systems with sea otters and urchins and

1588
01:24:39,680 --> 01:24:43,040
Speaker 1: kelp forests and understanding what happens when you disrupt a

1589
01:24:43,439 --> 01:24:45,960
Speaker 1: food web relatively simple food web structure where you have

1590
01:24:45,960 --> 01:24:49,280
Speaker 1: a top predator, you have its primary prey, the herbivore,

1591
01:24:49,680 --> 01:24:54,400
Speaker 1: and then you have the first level of the food web,

1592
01:24:54,439 --> 01:24:57,720
Speaker 1: which is the plant that those herbivores depend on, and

1593
01:24:57,800 --> 01:25:00,760
Speaker 1: what happens when you disrupt that link and the idea

1594
01:25:00,800 --> 01:25:03,439
Speaker 1: of a trophic cascade as you have these top down

1595
01:25:03,560 --> 01:25:08,920
Speaker 1: influences occurring where a predator can influence both its prey

1596
01:25:09,040 --> 01:25:12,000
Speaker 1: through direct killing or let's say behavioral changes. So we

1597
01:25:12,080 --> 01:25:14,839
Speaker 1: have you know, sort of um direct and indirect effects

1598
01:25:14,840 --> 01:25:18,559
Speaker 1: on its primary prey, which can infect linked effects down

1599
01:25:18,560 --> 01:25:21,240
Speaker 1: to that next trophic level, which would be the vegetation community.

1600
01:25:21,280 --> 01:25:23,400
Speaker 1: So in a place like Yellowstone, sort of the classic

1601
01:25:24,200 --> 01:25:26,920
Speaker 1: UH story that's out there is that you know, with

1602
01:25:27,040 --> 01:25:31,080
Speaker 1: the absence of top predator wolves and cougars for seventy years,

1603
01:25:31,120 --> 01:25:37,040
Speaker 1: are elk herd um became credibly abundant, overabundant, you could say,

1604
01:25:37,560 --> 01:25:41,599
Speaker 1: and that started having impacts on on forage and one

1605
01:25:41,600 --> 01:25:43,680
Speaker 1: of the focuses of that story has been on the

1606
01:25:43,680 --> 01:25:45,800
Speaker 1: woody brows you know, right below us here we see

1607
01:25:45,800 --> 01:25:48,639
Speaker 1: our aspen stands. You know, you've got your cotton woods,

1608
01:25:48,640 --> 01:25:51,840
Speaker 1: you have your willow communities. Those are relatively a small

1609
01:25:51,920 --> 01:25:54,320
Speaker 1: part of the Northern Range ecosystem is more of a

1610
01:25:54,360 --> 01:25:57,799
Speaker 1: grassland system, especially here, but it has been an important

1611
01:25:57,800 --> 01:26:00,360
Speaker 1: part of the history here. You know, there's certainly beaver's

1612
01:26:00,360 --> 01:26:03,240
Speaker 1: player role there, uh in that history of of willow

1613
01:26:03,280 --> 01:26:05,479
Speaker 1: and asthmen. Uh if you go back through the park's

1614
01:26:05,520 --> 01:26:08,880
Speaker 1: history and their elimination. But essentially, what the idea was

1615
01:26:08,920 --> 01:26:11,400
Speaker 1: that in the absence of the top predator, you had

1616
01:26:11,479 --> 01:26:14,559
Speaker 1: overgrazing or over browsing in this sense of this woody browse,

1617
01:26:14,560 --> 01:26:18,160
Speaker 1: and that basically suppressed these vegetation communities which are incredibly

1618
01:26:18,160 --> 01:26:22,640
Speaker 1: important to many species, whether it's songbirds, beavers, aquatic insects.

1619
01:26:22,720 --> 01:26:24,960
Speaker 1: You know, these are you know, really important aspects of

1620
01:26:25,000 --> 01:26:28,519
Speaker 1: these woody browse communities. But um and and with in

1621
01:26:28,560 --> 01:26:31,960
Speaker 1: the restoration of carnivores and the focus has been on wolves,

1622
01:26:31,960 --> 01:26:35,040
Speaker 1: with the trophic Cascade story, you kind of restored that.

1623
01:26:35,160 --> 01:26:36,840
Speaker 1: You know, I always hate the balance of nature, but

1624
01:26:36,960 --> 01:26:39,320
Speaker 1: nature is never quite in balance. UM, but you know

1625
01:26:39,360 --> 01:26:41,800
Speaker 1: the concept that most people are familiar with. You restored

1626
01:26:41,840 --> 01:26:45,200
Speaker 1: that relationship between the links of your top predator, your

1627
01:26:45,200 --> 01:26:48,760
Speaker 1: primary consumer, and then your primary productivity, your plants. And

1628
01:26:48,800 --> 01:26:52,920
Speaker 1: in doing so, UM, you restricted the brows. You started

1629
01:26:52,960 --> 01:26:55,719
Speaker 1: having willow and woody browse communities coming back, growing back,

1630
01:26:56,040 --> 01:26:59,840
Speaker 1: and that became very popularized the story of trophic cascade.

1631
01:27:00,160 --> 01:27:03,760
Speaker 1: There's signs in the park I've seen before to educational signs,

1632
01:27:03,800 --> 01:27:07,439
Speaker 1: you know, National geographic television shows that that of course,

1633
01:27:07,479 --> 01:27:11,120
Speaker 1: that famous or infamous YouTube video of how wolves have

1634
01:27:11,240 --> 01:27:14,320
Speaker 1: changed the rivers UM. You know, taking a very complex issition,

1635
01:27:14,400 --> 01:27:16,880
Speaker 1: trying to boil it into something simple. UM. You know,

1636
01:27:16,960 --> 01:27:20,479
Speaker 1: really what we view of what's happened in this landscape

1637
01:27:20,520 --> 01:27:23,120
Speaker 1: relative to trophic cascades as we do believe that the

1638
01:27:23,240 --> 01:27:27,360
Speaker 1: restoration of wolves, but more importantly the restoration of our

1639
01:27:27,439 --> 01:27:31,160
Speaker 1: carnivore community as a whole. Grizzly bears, UH, cougars and

1640
01:27:31,280 --> 01:27:37,800
Speaker 1: wolves have UM shifted that dynamic between UM elk behavior

1641
01:27:37,920 --> 01:27:41,960
Speaker 1: browsing patterns. And yes, you have seen some vegetative communities

1642
01:27:42,000 --> 01:27:45,200
Speaker 1: like willows and aspens and cotton woods UM start recovering

1643
01:27:45,640 --> 01:27:49,160
Speaker 1: because of those roles of those carnivores. Now there's other

1644
01:27:49,200 --> 01:27:52,120
Speaker 1: things that play, you know. I think what is the

1645
01:27:52,160 --> 01:27:55,120
Speaker 1: misconception about trophic cascades is that is a wolf triggered

1646
01:27:55,160 --> 01:27:59,240
Speaker 1: trophic cascade. And because people see what the major difference

1647
01:27:59,360 --> 01:28:03,240
Speaker 1: was is that, you know, mid nineties, wolves are reintroduced.

1648
01:28:03,720 --> 01:28:06,000
Speaker 1: That's when a lot of some of these starting studies

1649
01:28:06,040 --> 01:28:08,720
Speaker 1: took place to start measuring growth of aspen and willow rebounding.

1650
01:28:08,920 --> 01:28:10,800
Speaker 1: And it is true wolves have been an important part

1651
01:28:10,840 --> 01:28:14,840
Speaker 1: of that story. They helped uh bring back down the

1652
01:28:15,280 --> 01:28:18,240
Speaker 1: high density elk populations, lowering them. But along with wolves

1653
01:28:18,280 --> 01:28:21,800
Speaker 1: were cougar predation, grizzly beer, predation on black beer, predation

1654
01:28:21,840 --> 01:28:24,080
Speaker 1: on elk has, coyotes, And of course let's not forget

1655
01:28:24,160 --> 01:28:26,040
Speaker 1: right over here to our left as we look outside

1656
01:28:26,080 --> 01:28:28,280
Speaker 1: the park, this is the gardener based in Eagle Creek.

1657
01:28:28,640 --> 01:28:31,000
Speaker 1: This was the heart and soul of the Montana Fish

1658
01:28:31,000 --> 01:28:33,519
Speaker 1: willand Parks Gardener. Elk Late Hunt which is started in

1659
01:28:33,560 --> 01:28:36,840
Speaker 1: nineteen seventy six designed to reduce the number of elk

1660
01:28:36,880 --> 01:28:38,800
Speaker 1: in the northern herd, and that hunt went all the

1661
01:28:38,800 --> 01:28:41,960
Speaker 1: way up through two thousand nine, and so you have

1662
01:28:42,120 --> 01:28:46,720
Speaker 1: basically this perfect storm of of predation, pressure from multiple carnivores,

1663
01:28:47,360 --> 01:28:50,479
Speaker 1: human hunting effects which have been important here. And then

1664
01:28:50,520 --> 01:28:52,960
Speaker 1: you have your factors of such as severe winners and

1665
01:28:53,040 --> 01:28:55,720
Speaker 1: drought which have had impacts on our elk herds as well.

1666
01:28:55,800 --> 01:28:58,799
Speaker 1: So the story of trophic cascades is not the simple

1667
01:28:58,880 --> 01:29:01,479
Speaker 1: story that you offer has been often popularizes the wolves

1668
01:29:01,520 --> 01:29:05,080
Speaker 1: have caused this whole landscape to change. Wolves are certainly

1669
01:29:05,240 --> 01:29:07,320
Speaker 1: part of the tipping point there and maybe a necessary

1670
01:29:07,360 --> 01:29:09,800
Speaker 1: part of that story. Um, but they aren't the only

1671
01:29:10,200 --> 01:29:12,840
Speaker 1: complex any more. As you say, like you get into

1672
01:29:12,840 --> 01:29:15,440
Speaker 1: this idea where if I'm trying to defend the existence

1673
01:29:15,479 --> 01:29:18,760
Speaker 1: of wolves or the in this case kind of like

1674
01:29:19,160 --> 01:29:22,479
Speaker 1: the manifestation of more wolf introductions in different states, I

1675
01:29:22,600 --> 01:29:25,760
Speaker 1: might take this idea of trophic cascade and boil it

1676
01:29:25,800 --> 01:29:29,080
Speaker 1: down and use it as my justification for the thing

1677
01:29:29,200 --> 01:29:32,799
Speaker 1: that I ultimately want, you know. Conversely, I might argue,

1678
01:29:33,040 --> 01:29:35,400
Speaker 1: if I'm I want less wolves on the landscape, that

1679
01:29:35,479 --> 01:29:37,840
Speaker 1: they didn't you have more elk, that they didn't play

1680
01:29:38,240 --> 01:29:40,680
Speaker 1: as big a role, and that you know, and so

1681
01:29:40,800 --> 01:29:43,280
Speaker 1: they're there. That's the danger in all of this. And

1682
01:29:43,280 --> 01:29:45,360
Speaker 1: I'm sure, as as someone who lives this and breathes

1683
01:29:45,400 --> 01:29:47,440
Speaker 1: it every day. It's it's I'm sure it's a frustration

1684
01:29:47,439 --> 01:29:50,280
Speaker 1: because I will say I have talked to several biologists

1685
01:29:50,280 --> 01:29:53,120
Speaker 1: that kind of cringe when you say trophic because I

1686
01:29:53,120 --> 01:29:56,120
Speaker 1: think they would probably say, well, you just kind of phrases,

1687
01:29:56,200 --> 01:29:59,320
Speaker 1: you know, it's like an oversimplification of this idea that

1688
01:29:59,400 --> 01:30:02,240
Speaker 1: can be a to whatever narrative someone's trying. We have

1689
01:30:02,280 --> 01:30:04,439
Speaker 1: to embrace the controversy. We have to embrace the debate.

1690
01:30:04,479 --> 01:30:06,519
Speaker 1: That's what science is all about, and that's our job

1691
01:30:06,560 --> 01:30:09,960
Speaker 1: as scientists is right now, you have, um a number

1692
01:30:10,000 --> 01:30:12,040
Speaker 1: of competing voices out there that have worked in this

1693
01:30:12,080 --> 01:30:14,479
Speaker 1: ecosystem over the last you know, a couple of decades

1694
01:30:14,520 --> 01:30:16,920
Speaker 1: to kind of tease apart, you know what has occurred

1695
01:30:16,920 --> 01:30:19,760
Speaker 1: when it comes to that trophic cascade debate issue. And

1696
01:30:19,800 --> 01:30:22,240
Speaker 1: I think there's a lot we all agree on and

1697
01:30:22,240 --> 01:30:24,040
Speaker 1: there's some that we disagree on. And actually we have

1698
01:30:24,080 --> 01:30:26,800
Speaker 1: a forthcoming book. Um, we'll do a little promotion of

1699
01:30:26,840 --> 01:30:29,040
Speaker 1: it right now, if that's okay, And that's University of

1700
01:30:29,120 --> 01:30:32,200
Speaker 1: Chicago Press that's coming out in November. It's called Yellowstone Wolves,

1701
01:30:32,200 --> 01:30:35,320
Speaker 1: Science and Discovery in our world's first National Park. And

1702
01:30:35,439 --> 01:30:38,519
Speaker 1: myself Doug Smith and McNulty were the editors, and we've

1703
01:30:38,520 --> 01:30:41,320
Speaker 1: brought together all these collaborators of study wolves here in

1704
01:30:41,320 --> 01:30:44,519
Speaker 1: the last twenty five years, different voices coming together, uh

1705
01:30:44,560 --> 01:30:47,000
Speaker 1: to tell the story of Yellowstone Wolves from our perspective,

1706
01:30:47,000 --> 01:30:48,840
Speaker 1: the people involved with it for the last twenty five years.

1707
01:30:48,920 --> 01:30:51,240
Speaker 1: And one of the things we're very proud about in

1708
01:30:51,280 --> 01:30:53,559
Speaker 1: that book because we have a chapter on trophic cascades

1709
01:30:53,960 --> 01:30:56,280
Speaker 1: that is co authored by many of the competing voices.

1710
01:30:56,320 --> 01:31:02,880
Speaker 1: We wrangled everyone together down how dare you have competing narrative? Say?

1711
01:31:02,960 --> 01:31:05,120
Speaker 1: It was challenging, but um, I think in the end

1712
01:31:05,160 --> 01:31:07,600
Speaker 1: we hope that that provides a great understanding to the

1713
01:31:07,600 --> 01:31:10,360
Speaker 1: public to understand that it is complex or different ideas,

1714
01:31:10,520 --> 01:31:12,640
Speaker 1: and that's the beauty of science. It's self corrective. We

1715
01:31:12,720 --> 01:31:15,439
Speaker 1: as we collect more data, as we study things longer term,

1716
01:31:15,520 --> 01:31:19,360
Speaker 1: we get a uh, we crystallize and we'll never completely understand,

1717
01:31:19,360 --> 01:31:22,120
Speaker 1: we may never understand it fully, but we get a

1718
01:31:22,200 --> 01:31:24,360
Speaker 1: closer to the truth. And that's kind of our our

1719
01:31:24,360 --> 01:31:27,240
Speaker 1: goal here. And I think it's okay. We don't need

1720
01:31:27,320 --> 01:31:31,000
Speaker 1: to use wolves as the justification. UH. We don't have

1721
01:31:31,080 --> 01:31:33,480
Speaker 1: to use a story like trophic cascades as a justification

1722
01:31:33,560 --> 01:31:35,639
Speaker 1: have them back on the landscape. And there's many reasons

1723
01:31:35,640 --> 01:31:38,080
Speaker 1: why wolves should be back on the landscape. Um, just

1724
01:31:38,160 --> 01:31:41,519
Speaker 1: their role as a predator and food webs. Outside of

1725
01:31:41,560 --> 01:31:44,200
Speaker 1: the specific example of tropic cascade, it would be enough

1726
01:31:44,240 --> 01:31:47,560
Speaker 1: reason to restore them to many landscapes. Um do you

1727
01:31:47,640 --> 01:31:51,599
Speaker 1: feel so? One thing I've always wondered is like they

1728
01:31:51,680 --> 01:31:54,720
Speaker 1: say a grizzly bear, the mountain lion, cougar and the

1729
01:31:54,760 --> 01:31:58,679
Speaker 1: mount line and a wolf, and say those three things

1730
01:31:58,680 --> 01:32:00,719
Speaker 1: that exist in this landscape that we're in right now.

1731
01:32:00,840 --> 01:32:05,120
Speaker 1: Do they all provide very similar ecosystem services? We we

1732
01:32:05,160 --> 01:32:07,320
Speaker 1: know the predation part of it, but would you lump

1733
01:32:07,400 --> 01:32:11,280
Speaker 1: them all into one kind of service? Or they're based

1734
01:32:11,320 --> 01:32:14,040
Speaker 1: on their habits, based on how they predate. Are their

1735
01:32:14,160 --> 01:32:17,040
Speaker 1: their nuanced differences in what they provide to a landscape

1736
01:32:17,080 --> 01:32:20,120
Speaker 1: that maybe a wolf. Sure, there's definitely nuanced differences. I mean,

1737
01:32:20,240 --> 01:32:24,719
Speaker 1: for example, bears are sleeping half the year, right half

1738
01:32:24,720 --> 01:32:28,000
Speaker 1: the year they're out of the picture for example. Um,

1739
01:32:28,280 --> 01:32:30,000
Speaker 1: you know a little bit of exaggeration, maybe a little

1740
01:32:30,040 --> 01:32:31,479
Speaker 1: less than half the year, but you know it's part

1741
01:32:31,479 --> 01:32:33,639
Speaker 1: of their natural history that you know, they go into

1742
01:32:33,960 --> 01:32:36,920
Speaker 1: a state where they're not on the landscape. UM. When

1743
01:32:36,960 --> 01:32:40,400
Speaker 1: you actually look at their role in elk heer dynamics,

1744
01:32:40,400 --> 01:32:44,240
Speaker 1: they are incredibly important. They are the leading cause for

1745
01:32:44,400 --> 01:32:47,800
Speaker 1: most studies that study multiple multiple carnivore predation in in

1746
01:32:48,080 --> 01:32:51,360
Speaker 1: elk systems. Doesn't matter if it's yellow Stone or other

1747
01:32:51,360 --> 01:32:53,880
Speaker 1: parts of the Rocky Man in West Grizzly bears and

1748
01:32:53,960 --> 01:33:00,320
Speaker 1: blackbirds combined. Black bears combined are um the primary predators

1749
01:33:00,320 --> 01:33:03,160
Speaker 1: on newborn elk calfs, much more so than wolves, much

1750
01:33:03,200 --> 01:33:05,200
Speaker 1: more sore than cougar Zoom and grant. We just visited

1751
01:33:05,240 --> 01:33:09,000
Speaker 1: a cougar killed elk calf, but um, that first month

1752
01:33:09,040 --> 01:33:11,719
Speaker 1: of the elk calf's life, it's biggest concerned is probably

1753
01:33:11,720 --> 01:33:16,000
Speaker 1: a bear. UM. Wolves and cougars less so but still important.

1754
01:33:16,880 --> 01:33:18,960
Speaker 1: Then you look at a wolf and a cougar. They're

1755
01:33:18,960 --> 01:33:21,160
Speaker 1: on the landscape year around and as that you know,

1756
01:33:21,320 --> 01:33:23,439
Speaker 1: just choosing elk calf story as an example. They're born

1757
01:33:23,439 --> 01:33:25,639
Speaker 1: into half the running the gauntlet of bears and and

1758
01:33:25,640 --> 01:33:29,120
Speaker 1: and cougars and wolves, and then by fall late summer

1759
01:33:29,840 --> 01:33:33,280
Speaker 1: bears are less of a predatory role because calves can

1760
01:33:33,280 --> 01:33:35,800
Speaker 1: out run them. UM. And then you get into winter

1761
01:33:35,880 --> 01:33:37,880
Speaker 1: and bears are sleeping in them. Wolves and cougars step

1762
01:33:37,960 --> 01:33:40,160
Speaker 1: up their role in elk calf predation and play an

1763
01:33:40,160 --> 01:33:42,400
Speaker 1: important role in elk calf recruitment into the next into

1764
01:33:42,439 --> 01:33:45,040
Speaker 1: the herd. And so they play a slightly different role.

1765
01:33:45,080 --> 01:33:48,280
Speaker 1: You can also look at their hunting styles. Um. You know,

1766
01:33:48,320 --> 01:33:50,679
Speaker 1: we'll just to choose cougars and wolves as as examples.

1767
01:33:50,720 --> 01:33:54,360
Speaker 1: Wolves are what we call coursing group hunters. Coursing me running.

1768
01:33:54,360 --> 01:33:56,600
Speaker 1: They get their prey to run. Their success as a

1769
01:33:56,680 --> 01:34:00,640
Speaker 1: hunter is really dependent on finding vulnerable prey. Okay, and

1770
01:34:00,680 --> 01:34:04,240
Speaker 1: that means young, old, sick, week slower, um, And we

1771
01:34:04,240 --> 01:34:05,640
Speaker 1: can talk a little bit more about I think it's

1772
01:34:05,640 --> 01:34:07,439
Speaker 1: a really important thing to talk about, so I'll leave

1773
01:34:07,479 --> 01:34:10,920
Speaker 1: that off for a second. Uh. Cougars, in contrasts, are

1774
01:34:11,000 --> 01:34:14,080
Speaker 1: ambush solitary hunters, and they tend to hunt more and

1775
01:34:14,160 --> 01:34:16,559
Speaker 1: steep forest a terrain at night. Wolves tend to hunt

1776
01:34:16,560 --> 01:34:19,120
Speaker 1: more in the open valley bottoms, crepuscuarly dawn and dust.

1777
01:34:19,479 --> 01:34:22,160
Speaker 1: And so they are the nuance there is that they

1778
01:34:22,439 --> 01:34:24,719
Speaker 1: are all hunting the same elk herd, but at different

1779
01:34:24,720 --> 01:34:28,280
Speaker 1: times and in different habitats. Okay, and and so but

1780
01:34:28,720 --> 01:34:30,120
Speaker 1: you know, you pull back from that a little bit,

1781
01:34:30,120 --> 01:34:33,640
Speaker 1: and yes, I would say that ecosystem services they're similarly

1782
01:34:33,720 --> 01:34:39,800
Speaker 1: providing is through predation, uh, through uh, reducing densities high

1783
01:34:39,840 --> 01:34:43,479
Speaker 1: densities of the ungulate, their primary prey. Uh. And then

1784
01:34:43,520 --> 01:34:46,479
Speaker 1: how that then ripples through the food webs and nutrient

1785
01:34:46,520 --> 01:34:49,800
Speaker 1: recycling um. And so in that sense, they all share

1786
01:34:49,840 --> 01:34:52,360
Speaker 1: that common denominator. Yeah, that's that's kind of what you know.

1787
01:34:52,880 --> 01:34:55,120
Speaker 1: It's nice to hear it. So simply put, they're gone

1788
01:34:55,200 --> 01:34:57,320
Speaker 1: for half the year because it does because when I

1789
01:34:57,360 --> 01:35:00,520
Speaker 1: think about this and it goes to that trophic cascade discussion,

1790
01:35:00,760 --> 01:35:04,000
Speaker 1: there's so it's such a dynamic situation where the application

1791
01:35:04,040 --> 01:35:08,040
Speaker 1: of predation is happening, you know, different wavelengths, different different

1792
01:35:09,680 --> 01:35:11,439
Speaker 1: So yeah, and just the kind of cap stone that

1793
01:35:11,479 --> 01:35:13,240
Speaker 1: I guess that idea that there was a wolf triggered

1794
01:35:13,280 --> 01:35:16,400
Speaker 1: trophic cascade here in Yellowstone. Uh, those of us that

1795
01:35:16,439 --> 01:35:19,439
Speaker 1: have been steadiness istem for a long time would rather

1796
01:35:19,520 --> 01:35:22,720
Speaker 1: have people understand that it's a multi carnivore and you

1797
01:35:22,760 --> 01:35:25,800
Speaker 1: can include human hunters into this story. And here's why

1798
01:35:25,880 --> 01:35:29,040
Speaker 1: is that the part of the nuanced debate of what

1799
01:35:29,160 --> 01:35:32,280
Speaker 1: role carnivores have had is through the numerical effects on

1800
01:35:32,320 --> 01:35:35,439
Speaker 1: the elk, in other words, have the changes in woody brows.

1801
01:35:35,960 --> 01:35:38,559
Speaker 1: The popular story that you've heard is that these ungulates

1802
01:35:38,600 --> 01:35:41,240
Speaker 1: live in this landscape of fear okay, and they're avoiding

1803
01:35:41,240 --> 01:35:43,960
Speaker 1: these areas because they're worried about being killed, and as

1804
01:35:44,000 --> 01:35:46,720
Speaker 1: a result you get willower aspment regenerating. There is some

1805
01:35:47,360 --> 01:35:48,920
Speaker 1: little truth to that, and I can expand on that

1806
01:35:48,920 --> 01:35:54,160
Speaker 1: in a second, but really what the uh the prevalence

1807
01:35:54,200 --> 01:35:56,960
Speaker 1: of data suggests is that's there are behavioral effects on

1808
01:35:57,000 --> 01:35:59,599
Speaker 1: elk by carnivores. There is predation risk that plays a role,

1809
01:35:59,800 --> 01:36:03,160
Speaker 1: but it's probably largely been a numerical effect of the

1810
01:36:03,200 --> 01:36:06,960
Speaker 1: combined effects of carnivores that have influenced that those vegetation

1811
01:36:06,960 --> 01:36:12,040
Speaker 1: communities by bringing down your ungulate densities and and bears, wolves, cougars,

1812
01:36:12,160 --> 01:36:15,360
Speaker 1: and human hunters have all been an important part of

1813
01:36:15,400 --> 01:36:18,360
Speaker 1: the story of how our northern herd has been reduced,

1814
01:36:18,640 --> 01:36:22,160
Speaker 1: and they've those different carnivores or the human effects have

1815
01:36:22,400 --> 01:36:26,040
Speaker 1: played different strength through time. You could argue our data

1816
01:36:26,080 --> 01:36:29,400
Speaker 1: shows nicely that in the first seven or eight years

1817
01:36:29,400 --> 01:36:32,280
Speaker 1: of wolf recovery, wolves played a relatively small role in

1818
01:36:32,280 --> 01:36:35,240
Speaker 1: the decline of elk, And that's a very common misunderstanding.

1819
01:36:35,240 --> 01:36:36,960
Speaker 1: It was assumed that if you look at your just

1820
01:36:37,080 --> 01:36:41,479
Speaker 1: your raw numbers, elk herd was over twenty thousand. Four

1821
01:36:41,479 --> 01:36:43,400
Speaker 1: teen moles were put on the landscape and boom, your

1822
01:36:43,400 --> 01:36:46,200
Speaker 1: hard dropped. Well, fourteen wolves had no effect on that drop.

1823
01:36:46,320 --> 01:36:48,120
Speaker 1: That really didn't. There's just too many elk and non

1824
01:36:48,240 --> 01:36:52,559
Speaker 1: enough wolves. There was several couple thousand elk being harvested,

1825
01:36:52,680 --> 01:36:55,559
Speaker 1: there were cougars operating, there were grizzly bears operating. Then

1826
01:36:55,600 --> 01:36:58,439
Speaker 1: you had you know, severe Winner of nine seven knocked

1827
01:36:58,479 --> 01:37:00,519
Speaker 1: that herd down. My first spring here in a well, nineteen,

1828
01:37:00,560 --> 01:37:02,240
Speaker 1: I'll never forget it. And when my first hikes I

1829
01:37:02,240 --> 01:37:05,040
Speaker 1: ever did when I moved out here, um from Vermont,

1830
01:37:05,680 --> 01:37:08,160
Speaker 1: was in this April hiked r I can see the

1831
01:37:08,200 --> 01:37:10,439
Speaker 1: trail right across the valley here, hiked up the Black

1832
01:37:10,479 --> 01:37:15,320
Speaker 1: can in the Yellowstone. It was April, and I probably

1833
01:37:15,400 --> 01:37:17,760
Speaker 1: counted in that first two three miles of that hike.

1834
01:37:18,000 --> 01:37:21,040
Speaker 1: I don't know thirty dead elk, just it is. They're

1835
01:37:21,120 --> 01:37:23,960
Speaker 1: just winter kill everywhere. Um and then we and so

1836
01:37:24,160 --> 01:37:26,479
Speaker 1: winter has has a big effect on these ungulates. And

1837
01:37:26,479 --> 01:37:28,960
Speaker 1: then you can look at summer productivity in the drought

1838
01:37:29,040 --> 01:37:30,960
Speaker 1: of two thousand and two thousand seven here in this

1839
01:37:31,120 --> 01:37:35,759
Speaker 1: landscape uh affected forage quality UH and that's incredibly important

1840
01:37:35,800 --> 01:37:40,439
Speaker 1: for caffrecruitment and cow body condition for pregnancy and survival.

1841
01:37:40,600 --> 01:37:43,760
Speaker 1: So you've got a lot of things operating here. And

1842
01:37:43,920 --> 01:37:46,880
Speaker 1: that's why part of our roles and when we talk

1843
01:37:46,920 --> 01:37:50,720
Speaker 1: about things like trophic cascades or what role do predators have,

1844
01:37:50,880 --> 01:37:53,559
Speaker 1: you have to put it into context of other factors,

1845
01:37:54,040 --> 01:37:56,280
Speaker 1: and so to think about connecting that, and this is

1846
01:37:56,360 --> 01:38:01,679
Speaker 1: often the discussion with hunters. If if the human element,

1847
01:38:01,840 --> 01:38:06,160
Speaker 1: as you say so nicely fits with the wild predation element,

1848
01:38:07,080 --> 01:38:11,640
Speaker 1: how then would you connect the human management of the predators?

1849
01:38:11,880 --> 01:38:14,240
Speaker 1: Because I think that's that's really if this was you know,

1850
01:38:14,240 --> 01:38:15,920
Speaker 1: if we're gonna be real corny and say the circle

1851
01:38:15,960 --> 01:38:20,120
Speaker 1: of how do you think that in this application obviously

1852
01:38:20,200 --> 01:38:23,479
Speaker 1: not here in Yellowstone, but like in in just in general.

1853
01:38:23,560 --> 01:38:26,120
Speaker 1: If if if this wasn't a national park and there

1854
01:38:26,320 --> 01:38:29,960
Speaker 1: was human hunting and wolf tags, and yeah, that's what

1855
01:38:30,080 --> 01:38:32,560
Speaker 1: you know right up? The value there is sure, you know,

1856
01:38:32,680 --> 01:38:36,120
Speaker 1: I mean, this is a great question, and you know,

1857
01:38:36,200 --> 01:38:38,280
Speaker 1: there's there's a lot of different thoughts on this and

1858
01:38:38,320 --> 01:38:41,040
Speaker 1: obviously a lot of different philosophies on this, and and

1859
01:38:41,160 --> 01:38:43,400
Speaker 1: Yellowstone is a great reference point to it because we

1860
01:38:43,600 --> 01:38:49,599
Speaker 1: often hear yeah from hunters or from even state game agencies. UM.

1861
01:38:49,880 --> 01:38:53,040
Speaker 1: Largely because of the perception of it is that carnivores

1862
01:38:53,120 --> 01:38:56,000
Speaker 1: need to be managed. This idea that you know, in

1863
01:38:56,160 --> 01:38:58,240
Speaker 1: order to protect deer and elk, you know, you have

1864
01:38:58,400 --> 01:39:02,080
Speaker 1: to manage your carnivores. And depending on the anth, how

1865
01:39:02,120 --> 01:39:06,880
Speaker 1: you answer that question depends on your values, your societal view,

1866
01:39:07,160 --> 01:39:12,559
Speaker 1: maybe your cultural political views. From a biological standpoint, UM,

1867
01:39:12,800 --> 01:39:16,120
Speaker 1: it's very difficult to defend this idea that if you

1868
01:39:16,200 --> 01:39:19,000
Speaker 1: don't manage your carnivores, your system will collapse, You'll run

1869
01:39:19,040 --> 01:39:21,160
Speaker 1: out of food, the elk and deer won't be there anymore.

1870
01:39:21,200 --> 01:39:24,160
Speaker 1: Because one, let's just look at yellow Stone. We don't

1871
01:39:24,160 --> 01:39:26,400
Speaker 1: manage our carnivores here, not to say they're not influenced

1872
01:39:26,439 --> 01:39:29,160
Speaker 1: by outside effects. Because we have a trans boundary population.

1873
01:39:29,200 --> 01:39:32,479
Speaker 1: Our boles move out of the protection out onto this landscape.

1874
01:39:32,520 --> 01:39:35,800
Speaker 1: Hearing are subject to to legal hunting. UM. It doesn't

1875
01:39:35,800 --> 01:39:37,800
Speaker 1: play a big role in our population by any means,

1876
01:39:37,840 --> 01:39:41,200
Speaker 1: but it can can alter things slightly. UM. But you know,

1877
01:39:41,320 --> 01:39:44,560
Speaker 1: we have today. A in this can change. But we

1878
01:39:44,640 --> 01:39:47,160
Speaker 1: have today what we view as incredibly dense and healthy

1879
01:39:47,200 --> 01:39:50,479
Speaker 1: carnivore population, and we have a very healthy elk population

1880
01:39:51,160 --> 01:39:54,360
Speaker 1: um in the Greater Yelsa and ecosystem. Despite all these carnivores,

1881
01:39:54,640 --> 01:39:56,439
Speaker 1: you pull back and you look at much of the

1882
01:39:56,520 --> 01:39:59,680
Speaker 1: Rocky Mountain West and you look at elkhurt. Let's just

1883
01:39:59,760 --> 01:40:01,880
Speaker 1: choose for example, you look at elk hered objectives and

1884
01:40:01,960 --> 01:40:05,599
Speaker 1: many parts of the Idaho, Montana, Wyoming and most by

1885
01:40:05,640 --> 01:40:08,320
Speaker 1: far the vast majority of hunting districts elkords are at

1886
01:40:08,400 --> 01:40:11,120
Speaker 1: or above objective. And that is under a landscape now

1887
01:40:11,280 --> 01:40:15,760
Speaker 1: that has bears, wolves, and cougars everywhere. And and now

1888
01:40:15,840 --> 01:40:18,320
Speaker 1: you could argue that well they're out objective or above

1889
01:40:18,360 --> 01:40:20,439
Speaker 1: objectives in these areas because there is hunting, there is

1890
01:40:20,560 --> 01:40:23,040
Speaker 1: some illegal take, there's wildlife services that plays a role

1891
01:40:23,080 --> 01:40:26,120
Speaker 1: with lifestyle control when it comes to carnivores um and

1892
01:40:26,360 --> 01:40:28,760
Speaker 1: and so I I think, you know, just to boil

1893
01:40:28,800 --> 01:40:31,880
Speaker 1: it down to a very simple thought process. Look, I

1894
01:40:31,960 --> 01:40:34,800
Speaker 1: think you can have it all. Yeah, I really do.

1895
01:40:34,920 --> 01:40:37,920
Speaker 1: I believe that done properly, and you can give a

1896
01:40:38,000 --> 01:40:41,160
Speaker 1: lot of credit. I would say to state agencies that

1897
01:40:41,240 --> 01:40:44,360
Speaker 1: are struggling with how you handle carnivore recovery. Of course,

1898
01:40:44,439 --> 01:40:47,360
Speaker 1: the major constituent would be people that might be more

1899
01:40:47,400 --> 01:40:50,080
Speaker 1: prone to being anti carnivore, let's face it, and that

1900
01:40:50,280 --> 01:40:53,400
Speaker 1: a lot of a lot of that could be through misunderstanding, misperception,

1901
01:40:53,640 --> 01:40:58,479
Speaker 1: or culture or background or personal experience. Um. But the

1902
01:40:58,560 --> 01:41:01,760
Speaker 1: state agencies are wrangling with you know, this is a

1903
01:41:01,800 --> 01:41:05,000
Speaker 1: contentious topic. How do we how do we meet the

1904
01:41:05,080 --> 01:41:09,280
Speaker 1: desires and needs of our public, which is one segment

1905
01:41:09,320 --> 01:41:12,920
Speaker 1: of population, with other stakeholders which are equally I would

1906
01:41:13,000 --> 01:41:15,840
Speaker 1: argue as important to the long term success of conservation.

1907
01:41:16,000 --> 01:41:18,080
Speaker 1: Can I here's a question I have in regards to that.

1908
01:41:18,120 --> 01:41:20,040
Speaker 1: I think about this quite often. And this may be

1909
01:41:20,120 --> 01:41:22,479
Speaker 1: a devil's advocate, you know, for a hunting podcast, this

1910
01:41:22,560 --> 01:41:25,360
Speaker 1: might be playing the devil's advocate a little bit. Um.

1911
01:41:25,600 --> 01:41:32,599
Speaker 1: State game agencies funded up sometimes sixty even maybe even

1912
01:41:32,640 --> 01:41:35,320
Speaker 1: more in some cases. Um, but that's generally the number

1913
01:41:35,320 --> 01:41:39,599
Speaker 1: I've heard from American system of conservation funding, which includes

1914
01:41:39,680 --> 01:41:43,400
Speaker 1: license sales, Pittman, Robertson dollars, Tinkle Johnson dollars, all that

1915
01:41:43,439 --> 01:41:46,560
Speaker 1: stuff going into fund these agencies, and so they have

1916
01:41:47,400 --> 01:41:50,639
Speaker 1: you know, you see, are three programs that are meant

1917
01:41:50,680 --> 01:41:53,040
Speaker 1: to get more hunters in there because they need those dollars.

1918
01:41:53,680 --> 01:41:56,720
Speaker 1: What does that do in your opinion to how those

1919
01:41:56,760 --> 01:42:00,960
Speaker 1: game agencies think about their constituencies. Well, sure, I mean,

1920
01:42:01,200 --> 01:42:03,240
Speaker 1: you know, I'm a park service biologist, and I don't

1921
01:42:03,240 --> 01:42:05,360
Speaker 1: want to come off and I and I don't. I'm

1922
01:42:05,360 --> 01:42:08,280
Speaker 1: also a Montana resident, and I believe strongly in the

1923
01:42:08,520 --> 01:42:12,080
Speaker 1: in the in the UM, the need for our state

1924
01:42:12,120 --> 01:42:15,840
Speaker 1: agencies to have the resources and tools to do the

1925
01:42:15,920 --> 01:42:19,200
Speaker 1: job they have to do to manage UM, the public

1926
01:42:19,280 --> 01:42:22,280
Speaker 1: trust the wildlife heritage that we all have. I think

1927
01:42:22,600 --> 01:42:25,920
Speaker 1: there's no doubt about it. There's a rich history, predominantly

1928
01:42:26,280 --> 01:42:29,439
Speaker 1: of support through the hunting community, sportsmen and women who

1929
01:42:29,520 --> 01:42:33,320
Speaker 1: have contributed financially and activism greatly to the success of

1930
01:42:33,360 --> 01:42:36,400
Speaker 1: wildlife conservation in our country hands down. I think where

1931
01:42:36,439 --> 01:42:38,960
Speaker 1: we're entering is into a phase in our world now

1932
01:42:39,040 --> 01:42:44,120
Speaker 1: where we need to acknowledge that and celebrate that UM.

1933
01:42:44,200 --> 01:42:47,000
Speaker 1: But we also need to provide opportunities for other stakeholders

1934
01:42:47,080 --> 01:42:50,400
Speaker 1: to buy in. And we can look at the issue here,

1935
01:42:51,040 --> 01:42:53,800
Speaker 1: the very contentious, hotly debated issue of wolf conservation in

1936
01:42:53,840 --> 01:42:56,320
Speaker 1: the state of Montana, which I'm most familiar with, and

1937
01:42:57,200 --> 01:42:59,920
Speaker 1: you have seen in recent years the efforts of sort

1938
01:43:00,040 --> 01:43:03,880
Speaker 1: of non consumptive stakeholders that maybe aren't even anti wolf

1939
01:43:03,960 --> 01:43:07,280
Speaker 1: hunting as much as hey, we want a voice to uh,

1940
01:43:07,760 --> 01:43:10,120
Speaker 1: please provide us some opportunity for buying into this. We

1941
01:43:10,200 --> 01:43:12,640
Speaker 1: want to see it at the table. And if you

1942
01:43:12,760 --> 01:43:16,800
Speaker 1: look at the you know, the vision of the state

1943
01:43:16,880 --> 01:43:19,120
Speaker 1: agencies as they'll say, you know, we we want all

1944
01:43:19,160 --> 01:43:22,240
Speaker 1: stakeholders to have a voice. I think what we're learning

1945
01:43:22,400 --> 01:43:25,040
Speaker 1: is that how do we transition to an industry not

1946
01:43:25,120 --> 01:43:27,479
Speaker 1: an inditsty. How do we transition from a culture of

1947
01:43:27,560 --> 01:43:31,479
Speaker 1: where it's largely been supported financially uh and religiously by

1948
01:43:31,680 --> 01:43:33,960
Speaker 1: sportsmen and women that are hunters and fishermen. How do

1949
01:43:34,080 --> 01:43:35,920
Speaker 1: we now expand that which is a great need. I

1950
01:43:36,000 --> 01:43:39,200
Speaker 1: think we're at a real important tipping point where we

1951
01:43:40,000 --> 01:43:43,479
Speaker 1: would be well served to embrace all stakeholders who may

1952
01:43:43,560 --> 01:43:47,120
Speaker 1: have slightly different values and views on wildlife and how

1953
01:43:47,160 --> 01:43:49,160
Speaker 1: they be managed. They might not totally agree with one

1954
01:43:49,200 --> 01:43:52,559
Speaker 1: another um, but they agree on many things and they

1955
01:43:52,720 --> 01:43:55,280
Speaker 1: want a lot of the same things, and we need

1956
01:43:55,360 --> 01:43:57,840
Speaker 1: to capitalize on that energy. And I think we're seeing

1957
01:43:57,920 --> 01:44:00,680
Speaker 1: that more and more right I mean, my experience with

1958
01:44:00,880 --> 01:44:02,720
Speaker 1: in my time out here in the Rocky Mountain West

1959
01:44:02,800 --> 01:44:07,040
Speaker 1: has seeing that transition. We're talking earlier about organizations like

1960
01:44:07,160 --> 01:44:10,439
Speaker 1: Meat Eater or b h A back Anglers, and I

1961
01:44:10,520 --> 01:44:13,479
Speaker 1: think it's tapped into an energy and a resource of

1962
01:44:13,560 --> 01:44:16,720
Speaker 1: bringing people together that might be on slightly different sides

1963
01:44:16,760 --> 01:44:21,760
Speaker 1: of an issue. Hanging out with Patagonia shows up, like

1964
01:44:21,800 --> 01:44:24,439
Speaker 1: what's up you Van, He's like, yeah, I'm anti predator hunting.

1965
01:44:24,479 --> 01:44:28,479
Speaker 1: We're like, okay, We're willing to tolerate that and talk

1966
01:44:28,560 --> 01:44:31,280
Speaker 1: about that because we share this value for the landscape.

1967
01:44:31,400 --> 01:44:33,720
Speaker 1: That's a tough thing. Admittedly, I would say, oh it is,

1968
01:44:33,880 --> 01:44:37,960
Speaker 1: and it's seen it, it's it's I would say this

1969
01:44:38,080 --> 01:44:40,639
Speaker 1: is one of those issues where I'm like almost right

1970
01:44:40,720 --> 01:44:42,880
Speaker 1: on the cutting edge of it, right on the split,

1971
01:44:43,000 --> 01:44:46,560
Speaker 1: because I want to say I want all voices to

1972
01:44:46,600 --> 01:44:49,559
Speaker 1: come in. You gotta have these competing ideals that all

1973
01:44:49,680 --> 01:44:52,559
Speaker 1: that are all grounded on value, valuing wildlife and right

1974
01:44:52,880 --> 01:44:54,960
Speaker 1: and you gotta have these competing approaches to the to

1975
01:44:55,080 --> 01:44:57,120
Speaker 1: how to express that value and how to manage it.

1976
01:44:57,840 --> 01:44:59,760
Speaker 1: At the same time, you look at states like Colorado

1977
01:45:00,080 --> 01:45:02,960
Speaker 1: even Oregon where you know, ups we lost spring Bear,

1978
01:45:03,040 --> 01:45:06,320
Speaker 1: hunting whoops, we lost this. We lost hunting with dogs, Whoops,

1979
01:45:06,400 --> 01:45:10,640
Speaker 1: we lost. And so I I can see both. I

1980
01:45:10,680 --> 01:45:14,360
Speaker 1: see the philosophical need for this, but I wonder and

1981
01:45:14,439 --> 01:45:16,120
Speaker 1: again I think that's what I'm here to try to do,

1982
01:45:16,840 --> 01:45:18,600
Speaker 1: and and having you on as a big part of

1983
01:45:18,680 --> 01:45:21,720
Speaker 1: that is to get people to understand how complex this is.

1984
01:45:22,560 --> 01:45:27,360
Speaker 1: And I think from a defending hunting standpoint, I always

1985
01:45:27,400 --> 01:45:29,280
Speaker 1: come to the table like I want everybody to understand

1986
01:45:29,320 --> 01:45:32,040
Speaker 1: the value of this, even those that come into it,

1987
01:45:32,320 --> 01:45:34,839
Speaker 1: like you said, not necessarily anti hunting, but more valuing

1988
01:45:34,880 --> 01:45:38,320
Speaker 1: the wildlife for what it is, not what it gives

1989
01:45:38,360 --> 01:45:40,880
Speaker 1: you exactly. And you know, and that come back to

1990
01:45:41,600 --> 01:45:43,320
Speaker 1: the point maybe before I do think we can have

1991
01:45:43,960 --> 01:45:46,080
Speaker 1: a little bit of everything, and maybe not all in

1992
01:45:46,200 --> 01:45:48,519
Speaker 1: one place. I mean, you know, we've got a place

1993
01:45:48,560 --> 01:45:54,960
Speaker 1: like yellow Stone Um where carnivores are protected, ungulates are protected. Course,

1994
01:45:54,960 --> 01:45:57,280
Speaker 1: they're transpouncy, they migrate, they move over large areas, but

1995
01:45:57,840 --> 01:46:00,680
Speaker 1: we don't have many places like that are study is

1996
01:46:00,800 --> 01:46:03,000
Speaker 1: probably one of the own, one of the few studies

1997
01:46:03,080 --> 01:46:08,519
Speaker 1: worldwide of an UH wolf population that is not under

1998
01:46:08,600 --> 01:46:11,360
Speaker 1: some level of human exploitation. And even then we can't

1999
01:46:11,400 --> 01:46:13,519
Speaker 1: say that because each year we lose a couple of

2000
01:46:13,520 --> 01:46:16,560
Speaker 1: wolves from packs primarily living in Yellowstone that spend that

2001
01:46:16,600 --> 01:46:18,800
Speaker 1: one day and they travel out onto a place like

2002
01:46:18,880 --> 01:46:21,240
Speaker 1: across the valley here and they're subject to illegal harvest

2003
01:46:21,240 --> 01:46:23,519
Speaker 1: where we get a legal take. And again I come

2004
01:46:23,560 --> 01:46:25,719
Speaker 1: back to that point that that has not we haven't

2005
01:46:26,240 --> 01:46:28,960
Speaker 1: shown or believed to have an important population impacts on

2006
01:46:29,040 --> 01:46:33,040
Speaker 1: the park wolf packs, but can disrupt natural social structure,

2007
01:46:33,080 --> 01:46:36,920
Speaker 1: which we our mission is to preserve. UM. But you know,

2008
01:46:38,120 --> 01:46:41,439
Speaker 1: when you go outside a protected preserve, there's very few

2009
01:46:41,479 --> 01:46:44,200
Speaker 1: places out there on the landscape where you have that

2010
01:46:44,400 --> 01:46:47,160
Speaker 1: full protection. And I think it'd be great if we

2011
01:46:47,200 --> 01:46:50,439
Speaker 1: had more of those um and UM. But I also

2012
01:46:50,520 --> 01:46:52,559
Speaker 1: think that there's places where you're not gonna have carnivores

2013
01:46:52,640 --> 01:46:54,160
Speaker 1: or can't have carnivores, and then you're gonna have all

2014
01:46:54,160 --> 01:46:58,280
Speaker 1: the places in between where um, you could have sustainable

2015
01:46:58,680 --> 01:47:01,200
Speaker 1: some level of sustainable car of war hunting. They some

2016
01:47:01,320 --> 01:47:04,519
Speaker 1: would argue for that, and the populations would do okay,

2017
01:47:05,240 --> 01:47:07,880
Speaker 1: uh and be resilient. I mean, these animals are incredibly

2018
01:47:08,000 --> 01:47:13,400
Speaker 1: resilient by nature, UM and and that's why we see uh,

2019
01:47:13,840 --> 01:47:18,000
Speaker 1: you know, stable UM carnivore populations in many areas where

2020
01:47:18,000 --> 01:47:21,160
Speaker 1: they aren't overharvested, and likewise you would see stable angular

2021
01:47:21,240 --> 01:47:23,680
Speaker 1: herds in many of those same areas. So, UM, I

2022
01:47:23,840 --> 01:47:27,840
Speaker 1: think if we work together more um different stakeholder groups

2023
01:47:27,880 --> 01:47:30,680
Speaker 1: different and come together and try to find compromise on

2024
01:47:30,800 --> 01:47:33,680
Speaker 1: both sides, that will service very well in the end

2025
01:47:33,720 --> 01:47:36,280
Speaker 1: in terms of ultimately what we want a lot of

2026
01:47:36,400 --> 01:47:38,599
Speaker 1: us is to preserve wild nature. Yeah. And I think

2027
01:47:38,800 --> 01:47:41,800
Speaker 1: as we talked about UM, and I could say this

2028
01:47:41,840 --> 01:47:45,360
Speaker 1: because you know, but I think in Dr Vlarious Geist

2029
01:47:45,439 --> 01:47:50,320
Speaker 1: would would love to I was texting me the other

2030
01:47:50,400 --> 01:47:53,040
Speaker 1: day about doing another podcast and I was very excited

2031
01:47:53,040 --> 01:47:55,679
Speaker 1: to talk to him. When we first talked, and again

2032
01:47:56,600 --> 01:47:59,840
Speaker 1: he is, let's just I'll just say I'll say it

2033
01:48:00,000 --> 01:48:03,679
Speaker 1: personally like. He was very anti wolf when we spoke.

2034
01:48:03,720 --> 01:48:06,559
Speaker 1: He talked about predator pits, He talked about hydada disease.

2035
01:48:06,600 --> 01:48:10,600
Speaker 1: I hope I always say that, right, UM, and this like,

2036
01:48:10,720 --> 01:48:13,479
Speaker 1: and he explained to me it was informed by a

2037
01:48:13,600 --> 01:48:16,400
Speaker 1: lot of things he had he had experienced in Russia

2038
01:48:17,000 --> 01:48:20,560
Speaker 1: with some wolves over there, and so his explaining of

2039
01:48:20,600 --> 01:48:23,639
Speaker 1: his world view was kind of shaped that way. UM.

2040
01:48:24,280 --> 01:48:26,000
Speaker 1: Your world view, I'm sure is in a lot of

2041
01:48:26,040 --> 01:48:28,760
Speaker 1: ways shaped to what you've seen here, and so again

2042
01:48:28,800 --> 01:48:31,599
Speaker 1: I fall I go back to when when we slot

2043
01:48:31,680 --> 01:48:37,080
Speaker 1: in these charismatic mega fauna into these very controversial, very

2044
01:48:37,160 --> 01:48:40,400
Speaker 1: emotional topics, where everybody comes to it with a different perspective,

2045
01:48:40,439 --> 01:48:42,960
Speaker 1: in a different worldview. You can you can come into

2046
01:48:43,000 --> 01:48:46,680
Speaker 1: these debates right where where we're not we're kind of

2047
01:48:46,720 --> 01:48:49,559
Speaker 1: talking past each other a little bit. And I think,

2048
01:48:50,000 --> 01:48:53,200
Speaker 1: you know, what are a person like myself? Job is

2049
01:48:53,280 --> 01:48:56,920
Speaker 1: here is too try to provide, you know, the basic

2050
01:48:57,200 --> 01:49:00,800
Speaker 1: biological truth about how these systems work. And first of off,

2051
01:49:00,880 --> 01:49:02,880
Speaker 1: we have to you have to fully admit we really

2052
01:49:02,960 --> 01:49:07,280
Speaker 1: don't understand nearly just as people wish we did. Uh.

2053
01:49:07,400 --> 01:49:09,320
Speaker 1: And that's a very hard thing to explain someone when

2054
01:49:09,439 --> 01:49:11,720
Speaker 1: you know what happened to the Elkert or what world

2055
01:49:11,840 --> 01:49:14,280
Speaker 1: will you know? Sometimes you as you get into the details,

2056
01:49:14,320 --> 01:49:16,439
Speaker 1: you have to say, I don't know. But I think

2057
01:49:16,720 --> 01:49:18,720
Speaker 1: what we can say and what we've learned a lot

2058
01:49:18,840 --> 01:49:20,840
Speaker 1: from studying wolves in a place like yellow zonn or

2059
01:49:20,880 --> 01:49:26,360
Speaker 1: cougars is is we've definitely added more accurate understanding of

2060
01:49:26,640 --> 01:49:33,880
Speaker 1: predation and and and what role they play. I always

2061
01:49:33,920 --> 01:49:35,680
Speaker 1: try to come back to the biology and explain it.

2062
01:49:35,720 --> 01:49:38,000
Speaker 1: And I think and and I don't know if you

2063
01:49:38,040 --> 01:49:39,840
Speaker 1: want to talk about this now or or have the

2064
01:49:39,880 --> 01:49:44,000
Speaker 1: conversation go, uh, we should talk more about the animals themselves,

2065
01:49:44,000 --> 01:49:46,559
Speaker 1: because I generally my mistake is I'm like, let's talk

2066
01:49:46,600 --> 01:49:50,080
Speaker 1: about the idea. But I think you have so much

2067
01:49:50,080 --> 01:49:53,040
Speaker 1: information on mountain lions and wolves and what they are

2068
01:49:53,280 --> 01:49:56,280
Speaker 1: and like what they really do. Um. And again I

2069
01:49:56,320 --> 01:49:58,280
Speaker 1: said I said this earlier. I think that's a big

2070
01:49:58,360 --> 01:50:00,280
Speaker 1: part of what I like to learn. I think, you

2071
01:50:00,360 --> 01:50:02,960
Speaker 1: know what I really like talking about wolf hunting behavior

2072
01:50:03,240 --> 01:50:05,439
Speaker 1: and cougar hunting behavior. Want to talk about that. There's

2073
01:50:05,880 --> 01:50:08,240
Speaker 1: there's a lot of misperception out there. We sat to

2074
01:50:08,360 --> 01:50:10,599
Speaker 1: sort of hold the wolf up on this pedestal as

2075
01:50:10,680 --> 01:50:14,800
Speaker 1: being sort of this mythological Uh. I think that's Liam

2076
01:50:14,880 --> 01:50:18,479
Speaker 1: Neeson's fault. Yeah, maybe so. I mean, you know, we

2077
01:50:18,600 --> 01:50:20,160
Speaker 1: wrote about in our books sort of like we kind

2078
01:50:20,200 --> 01:50:22,360
Speaker 1: of equate wolf predation is sort of like to these

2079
01:50:22,720 --> 01:50:25,880
Speaker 1: sort of mythological forces like Moby Dick or tornadoes and

2080
01:50:26,240 --> 01:50:29,400
Speaker 1: having these just sort of and you always hear, always

2081
01:50:29,439 --> 01:50:31,720
Speaker 1: hear the stories about, you know, how wolves did this

2082
01:50:31,800 --> 01:50:34,479
Speaker 1: and how wolves did that. And you know, we've studied

2083
01:50:34,479 --> 01:50:38,240
Speaker 1: wolf hunting behavior for twenty five years, and we've studied

2084
01:50:38,280 --> 01:50:40,360
Speaker 1: it by watching them do it, which is so rare

2085
01:50:40,560 --> 01:50:44,120
Speaker 1: in a predator study maybe outside of Africa. And we've

2086
01:50:44,520 --> 01:50:48,280
Speaker 1: you know, I personally have witnessed um fifty sixty seven.

2087
01:50:48,320 --> 01:50:50,160
Speaker 1: I can't and you lose track of how many direct

2088
01:50:50,280 --> 01:50:52,920
Speaker 1: kills from beginning to end. Our teams have watched thousands

2089
01:50:52,960 --> 01:50:55,800
Speaker 1: of hours of wolves hunting elk and bison, um and

2090
01:50:56,080 --> 01:50:58,840
Speaker 1: and through that, and we've collected data and we've analyzed it,

2091
01:50:58,880 --> 01:51:02,240
Speaker 1: and we've really kind of pieced out, uh, out of

2092
01:51:02,479 --> 01:51:06,599
Speaker 1: the complexity of that issue of really fundamentally how wolves hunt.

2093
01:51:06,640 --> 01:51:10,000
Speaker 1: And I think one of the biggest takeaway messages is that, um,

2094
01:51:10,479 --> 01:51:13,400
Speaker 1: they're very much limited by their biology and their behavior

2095
01:51:13,439 --> 01:51:16,519
Speaker 1: to be good of hunters. They are very challenged by

2096
01:51:16,600 --> 01:51:19,120
Speaker 1: hunting and getting their food and and and so let

2097
01:51:19,200 --> 01:51:20,439
Speaker 1: me just kind of go through a couple of key

2098
01:51:20,479 --> 01:51:24,640
Speaker 1: aspects to their biology and they're like, yeah, so, you know,

2099
01:51:25,240 --> 01:51:27,720
Speaker 1: first of all, they're limited very much by their just

2100
01:51:27,800 --> 01:51:30,680
Speaker 1: physical biology. I mean, they are a sort of a

2101
01:51:30,760 --> 01:51:34,080
Speaker 1: jack of all trade sort of an animal. They have Essentially,

2102
01:51:34,800 --> 01:51:38,880
Speaker 1: their skeletal structure is such that they they're hunting and

2103
01:51:39,000 --> 01:51:42,599
Speaker 1: killing tools are primarily their their teeth right, their jaw,

2104
01:51:42,720 --> 01:51:46,800
Speaker 1: what's in their mouth, and their endurance and ability to

2105
01:51:46,960 --> 01:51:51,280
Speaker 1: run and move the way they do. And but because

2106
01:51:51,320 --> 01:51:54,240
Speaker 1: of that there it's very difficult for them to kill

2107
01:51:54,560 --> 01:51:56,880
Speaker 1: something five times or size. And when we look at

2108
01:51:56,920 --> 01:52:00,439
Speaker 1: a place like Yale, soon about their preise elk. Okay,

2109
01:52:00,960 --> 01:52:03,800
Speaker 1: their next most common food type is bison, and the

2110
01:52:03,920 --> 01:52:06,439
Speaker 1: majority of biomass they get from bison isn't from killing

2111
01:52:06,520 --> 01:52:08,800
Speaker 1: them directly, although they do hunt and kill bison. It

2112
01:52:08,920 --> 01:52:11,880
Speaker 1: is through scavenging on bison, and we've seen more and

2113
01:52:11,960 --> 01:52:13,840
Speaker 1: more of that in recent years, and I'll talk about

2114
01:52:13,880 --> 01:52:16,320
Speaker 1: that after. But so they're limited by their ability they

2115
01:52:16,400 --> 01:52:19,080
Speaker 1: have to approach a prey animal. Let's say they approach

2116
01:52:19,080 --> 01:52:21,240
Speaker 1: a group of elk. They use their sense of smell,

2117
01:52:21,360 --> 01:52:24,000
Speaker 1: they're great olfaction, they have okay eyesight, it's not great

2118
01:52:24,000 --> 01:52:27,120
Speaker 1: at night, pretty decent during the day. They have to

2119
01:52:27,640 --> 01:52:31,040
Speaker 1: find prey first, and then once they find prey, they

2120
01:52:31,120 --> 01:52:33,719
Speaker 1: have to engage with that prey and that process involves

2121
01:52:33,840 --> 01:52:37,360
Speaker 1: watching and then they start running, and by running they

2122
01:52:37,400 --> 01:52:39,439
Speaker 1: try to figure out, Okay, I'm approaching this group, out

2123
01:52:39,479 --> 01:52:42,120
Speaker 1: which one is going to be that the less risky

2124
01:52:42,200 --> 01:52:44,280
Speaker 1: to kill. There are very risk averse. They've evolved to

2125
01:52:44,320 --> 01:52:46,479
Speaker 1: be risk averse. Is very dangerous and difficult for them

2126
01:52:47,080 --> 01:52:50,000
Speaker 1: to run up to something. I think about it. You're

2127
01:52:50,120 --> 01:52:52,000
Speaker 1: from your own perspective. If you were to run up

2128
01:52:52,000 --> 01:52:54,080
Speaker 1: to an elk and open your mouth and try to

2129
01:52:54,120 --> 01:52:57,400
Speaker 1: grab onto its mind quarter and pull it down, just

2130
01:52:57,560 --> 01:53:01,280
Speaker 1: they think about dangerous and physically uh difficult that would be.

2131
01:53:01,360 --> 01:53:04,759
Speaker 1: And that's um. And that's for an animal out on averages.

2132
01:53:04,800 --> 01:53:07,240
Speaker 1: You know, males are about pounds, females are about a

2133
01:53:07,320 --> 01:53:09,720
Speaker 1: hundred and UM. So they have to do that and

2134
01:53:10,120 --> 01:53:14,479
Speaker 1: and and there. As a result, they're only successful doing

2135
01:53:14,560 --> 01:53:17,360
Speaker 1: that when they hunt adult elk about fifteen or so

2136
01:53:17,479 --> 01:53:20,519
Speaker 1: percent of the time. So think about doing a task

2137
01:53:20,680 --> 01:53:23,840
Speaker 1: at work, ben Jee, we'd like to see your performance

2138
01:53:23,920 --> 01:53:27,560
Speaker 1: step up a little bit. You're only at about fift efficiency.

2139
01:53:30,000 --> 01:53:33,560
Speaker 1: You went last long. So you know, these animals just

2140
01:53:33,760 --> 01:53:35,400
Speaker 1: to get their meal, it's very difficult for them. So

2141
01:53:35,520 --> 01:53:38,800
Speaker 1: what they need is vulnerable prey and vulnerability manifests itself

2142
01:53:38,840 --> 01:53:41,360
Speaker 1: in a number of ways. Uh. Young animals like an

2143
01:53:41,360 --> 01:53:44,720
Speaker 1: elk calf that's easy and not dangerous to pull down. UM,

2144
01:53:45,040 --> 01:53:49,479
Speaker 1: an old injured animal that's weak and easy for the

2145
01:53:49,520 --> 01:53:53,599
Speaker 1: wolves to grab and pull down um and or something sick,

2146
01:53:53,800 --> 01:53:56,120
Speaker 1: or something stuck or trapped or in a terrain trap.

2147
01:53:56,560 --> 01:53:59,920
Speaker 1: Outside of that, uh by and far, the elk get

2148
01:54:00,040 --> 01:54:03,439
Speaker 1: away most of the time. And when they do engage,

2149
01:54:03,479 --> 01:54:05,720
Speaker 1: they have to grab on, and they have a long

2150
01:54:05,880 --> 01:54:07,960
Speaker 1: rostrum and as a result, and they have teeth running

2151
01:54:07,960 --> 01:54:10,040
Speaker 1: down that they grab on with their incisors and they

2152
01:54:10,120 --> 01:54:13,160
Speaker 1: use their canines to puncture and and grab and restrain,

2153
01:54:13,520 --> 01:54:16,360
Speaker 1: and they're getting yanked and jerked and kicked um and

2154
01:54:16,439 --> 01:54:19,240
Speaker 1: they have to hold on. And their real benefit as

2155
01:54:19,240 --> 01:54:21,920
Speaker 1: a hunter is that they hunting groups, and so it

2156
01:54:22,080 --> 01:54:25,519
Speaker 1: is by having at least one several other animals come

2157
01:54:25,560 --> 01:54:28,160
Speaker 1: and help them and to overpower that animal that they

2158
01:54:28,240 --> 01:54:29,800
Speaker 1: might be fighting with. The pull down to the ground.

2159
01:54:30,200 --> 01:54:32,600
Speaker 1: You now, that is their most common prayer. And yellowstone bison,

2160
01:54:32,680 --> 01:54:35,360
Speaker 1: you can imagine it's even more difficult to pull down

2161
01:54:35,400 --> 01:54:38,720
Speaker 1: a bison, and so most often they fail when they

2162
01:54:38,760 --> 01:54:43,040
Speaker 1: attempt their encounters, aren't successful buying far the majority of

2163
01:54:43,040 --> 01:54:46,560
Speaker 1: the time, and and so that right from the get

2164
01:54:46,640 --> 01:54:50,360
Speaker 1: go limits their ability to be a runaway predator UM.

2165
01:54:50,520 --> 01:54:53,360
Speaker 1: And that's why elk aren't wolf bait. Okay, they have

2166
01:54:53,480 --> 01:54:58,520
Speaker 1: the ability to uh handle predation risk on the landscape

2167
01:54:58,560 --> 01:55:01,880
Speaker 1: because buying law the majority of the time, and any

2168
01:55:01,920 --> 01:55:05,200
Speaker 1: individual out is going to survive their encounter with wolves. Um.

2169
01:55:06,080 --> 01:55:09,600
Speaker 1: And so there's that one aspect unlike a cougar that

2170
01:55:09,680 --> 01:55:13,360
Speaker 1: has retractile claus um. We call the word is superating.

2171
01:55:13,400 --> 01:55:17,880
Speaker 1: I love that word. It's rotating uh wrists um. They

2172
01:55:17,960 --> 01:55:21,240
Speaker 1: have that super and cougars have supernating risks, retractile claus

2173
01:55:21,760 --> 01:55:24,520
Speaker 1: and really incredibly powerful for limbs. They don't have the

2174
01:55:24,600 --> 01:55:27,480
Speaker 1: endurance of the wolf. They have short, quick bursts, They

2175
01:55:27,560 --> 01:55:30,680
Speaker 1: stalk their ambush hunters, they sneak up and pounce um.

2176
01:55:30,920 --> 01:55:34,360
Speaker 1: Very different hunting style and as a result they and

2177
01:55:34,480 --> 01:55:36,000
Speaker 1: we don't know this. We hope from you also and

2178
01:55:36,080 --> 01:55:38,000
Speaker 1: to get this data because of the special GPS colors,

2179
01:55:38,040 --> 01:55:40,720
Speaker 1: were using these accelerometer colors where we can measure and

2180
01:55:40,840 --> 01:55:43,840
Speaker 1: see hunting events and see how often they're successful from

2181
01:55:43,880 --> 01:55:45,720
Speaker 1: the surge and the data from the GPS scholars, but

2182
01:55:46,080 --> 01:55:49,280
Speaker 1: we believe in general that most biologist studying cougars would

2183
01:55:49,400 --> 01:55:52,160
Speaker 1: would argue that they're probably have a greater success per

2184
01:55:52,280 --> 01:55:54,400
Speaker 1: encounter with prey than do wolves. Okay, so they're very

2185
01:55:54,440 --> 01:55:57,440
Speaker 1: different in that that hunting style. UM. And so you know,

2186
01:55:57,560 --> 01:56:00,480
Speaker 1: again back to the wolves are really their successes the predators.

2187
01:56:00,640 --> 01:56:03,280
Speaker 1: They need vulnerable prayer to be successful. So that's calves,

2188
01:56:03,360 --> 01:56:07,280
Speaker 1: that's old cows, um bowl elk in late winter or

2189
01:56:07,320 --> 01:56:09,720
Speaker 1: in the fall if they've exhausted reserves from the rut

2190
01:56:10,360 --> 01:56:13,880
Speaker 1: are more vulnerable. And so from the get go the

2191
01:56:13,960 --> 01:56:17,000
Speaker 1: wolves are by far at the disadvantagement the encounter elk um.

2192
01:56:17,480 --> 01:56:19,800
Speaker 1: But obviously they're successful. They would survive if not, and

2193
01:56:19,840 --> 01:56:22,320
Speaker 1: they do that through group hunting. They do that through

2194
01:56:22,320 --> 01:56:24,640
Speaker 1: a division of labor. What we've learned in Yellowstone is

2195
01:56:24,720 --> 01:56:26,760
Speaker 1: that we know a lot about our packs and who

2196
01:56:26,800 --> 01:56:29,160
Speaker 1: the individuals are, their age, their sex. We can estimate

2197
01:56:29,200 --> 01:56:31,680
Speaker 1: their body weight because they wolves follow sort of body

2198
01:56:31,720 --> 01:56:34,640
Speaker 1: growth pattern UM that we have from all our hundreds

2199
01:56:34,640 --> 01:56:36,640
Speaker 1: of wolves. We've weighed and measured and known their ages,

2200
01:56:36,680 --> 01:56:39,400
Speaker 1: so we can kind of understand the role of body size,

2201
01:56:39,480 --> 01:56:42,280
Speaker 1: sex and age class. And what we've learned is that um,

2202
01:56:42,440 --> 01:56:44,080
Speaker 1: the best hunters in a wolf packer the two to

2203
01:56:44,160 --> 01:56:46,840
Speaker 1: three year olds kind of that sort of combination of

2204
01:56:46,960 --> 01:56:50,080
Speaker 1: experience hunting but sort of youthful vigor and body size,

2205
01:56:50,520 --> 01:56:53,800
Speaker 1: males uh tend to have a higher probability of success

2206
01:56:53,880 --> 01:56:56,360
Speaker 1: than females. Of course, they hunt together, so sometimes you

2207
01:56:56,400 --> 01:56:59,000
Speaker 1: have to tease that out. You typically find those two

2208
01:56:59,040 --> 01:57:01,120
Speaker 1: to three year old younger wolves on average being the

2209
01:57:01,240 --> 01:57:03,560
Speaker 1: fleet or of foot, the faster they select out, the

2210
01:57:03,640 --> 01:57:07,400
Speaker 1: one they grab and restrain, and then the large dominant

2211
01:57:07,440 --> 01:57:09,360
Speaker 1: breeding mail or the older doll mails will come up

2212
01:57:09,360 --> 01:57:12,520
Speaker 1: and use their larger body mass that weight to help

2213
01:57:12,600 --> 01:57:14,480
Speaker 1: pull that animal down. So it really is a division

2214
01:57:14,520 --> 01:57:17,240
Speaker 1: of labor. We also see an age effect. Just as

2215
01:57:17,360 --> 01:57:19,560
Speaker 1: the younger wolves are the better hunters, the pups are

2216
01:57:19,600 --> 01:57:21,200
Speaker 1: just kind of learning the first year of their life

2217
01:57:21,240 --> 01:57:23,520
Speaker 1: and not great hunters. We also find what we call

2218
01:57:23,560 --> 01:57:26,840
Speaker 1: predatory sinescence as about age five or six. Wolves have

2219
01:57:26,960 --> 01:57:29,040
Speaker 1: a very short life history. They don't live that long.

2220
01:57:29,280 --> 01:57:32,560
Speaker 1: Average lifespan is about five um, so they're not a

2221
01:57:32,600 --> 01:57:34,920
Speaker 1: long live carnivore, less so than cougars, which on average

2222
01:57:34,960 --> 01:57:37,840
Speaker 1: live you know, a dozen or so years. And what

2223
01:57:38,000 --> 01:57:40,720
Speaker 1: we see is that their participation in a hunt, their

2224
01:57:40,880 --> 01:57:44,200
Speaker 1: their ability to be successful at capture and takedown starts

2225
01:57:44,240 --> 01:57:46,960
Speaker 1: declining after at age five or six, and we see

2226
01:57:47,080 --> 01:57:49,600
Speaker 1: that changing of aging. You know, humans go through that

2227
01:57:49,720 --> 01:57:52,080
Speaker 1: too at a slightly different scale. Any any man wal

2228
01:57:52,200 --> 01:57:55,080
Speaker 1: does UM and that predatory sinessnce And we've actually looked

2229
01:57:55,120 --> 01:57:58,640
Speaker 1: at their blood profile, We've looked at physiological responses where

2230
01:57:58,640 --> 01:58:01,440
Speaker 1: you can look at the effects of aging on on

2231
01:58:01,520 --> 01:58:04,640
Speaker 1: wolf behavior and it's very clear cut. They age quickly

2232
01:58:04,720 --> 01:58:06,440
Speaker 1: and then they're just not of effective as doing what

2233
01:58:06,560 --> 01:58:09,640
Speaker 1: they do. So UM that has implications for you know,

2234
01:58:10,160 --> 01:58:13,040
Speaker 1: for impacts on elk. If you've got a wolf population

2235
01:58:13,120 --> 01:58:16,880
Speaker 1: that is constantly being hunted and managed and knocked down,

2236
01:58:16,960 --> 01:58:18,920
Speaker 1: you're gonna have a younger age class or the kind

2237
01:58:18,920 --> 01:58:21,680
Speaker 1: of the best hunters of the population. And so place

2238
01:58:21,800 --> 01:58:24,200
Speaker 1: like Yellowstone we see more age classes and that in

2239
01:58:24,280 --> 01:58:26,560
Speaker 1: the end we believe has an effect on their impacts

2240
01:58:26,600 --> 01:58:29,120
Speaker 1: overall in elk UM It might be subtle, but we

2241
01:58:29,160 --> 01:58:31,720
Speaker 1: think it's a real effect UM. And so you've got

2242
01:58:31,800 --> 01:58:35,200
Speaker 1: those different aspects of their biology that really shows their

2243
01:58:35,240 --> 01:58:39,400
Speaker 1: limits to success. We see seasonal effects on vulnerability. Of course,

2244
01:58:39,480 --> 01:58:43,480
Speaker 1: summertime Elk cafe neones the newborns are very vulnerable predation,

2245
01:58:43,680 --> 01:58:47,440
Speaker 1: but their mother is not UM. An adult cow elk

2246
01:58:47,520 --> 01:58:51,840
Speaker 1: and Yellowstone UH is largely invincible to wolf predation from

2247
01:58:51,880 --> 01:58:54,560
Speaker 1: the ages of two to about twelve and unless she

2248
01:58:54,680 --> 01:58:57,040
Speaker 1: gets herself in a pickle and makes a bad choice

2249
01:58:57,200 --> 01:58:59,560
Speaker 1: or gets in a wrong spot. But by and large,

2250
01:58:59,640 --> 01:59:03,200
Speaker 1: those bulls don't kill those um elk. In fact, our

2251
01:59:03,280 --> 01:59:06,760
Speaker 1: data for twenty five years has flat curve. Average age

2252
01:59:06,760 --> 01:59:10,040
Speaker 1: of a of a cow elk kill in northern Yellowstone

2253
01:59:10,120 --> 01:59:13,800
Speaker 1: is fourteen and that is not changed in twenty five years. Yes,

2254
01:59:13,880 --> 01:59:16,680
Speaker 1: they kill primate cows occasionally. Yes, they kill a twenty

2255
01:59:16,720 --> 01:59:18,560
Speaker 1: five year old cow. We've had twenty five year old

2256
01:59:18,600 --> 01:59:21,160
Speaker 1: cows and Yellowstone. We just had a collared cow elk

2257
01:59:21,280 --> 01:59:23,280
Speaker 1: that was died this winter at twenty five and a

2258
01:59:23,320 --> 01:59:26,040
Speaker 1: half years old. Think about that, a cow elk that

2259
01:59:26,200 --> 01:59:28,800
Speaker 1: was born in ninety four, the summer before wolves showed up.

2260
01:59:30,280 --> 01:59:34,800
Speaker 1: Voter for Bill Clinton voted her survived her whole life

2261
01:59:34,880 --> 01:59:37,400
Speaker 1: through a gauntlet of carnivores, pumped out a bunch of calves.

2262
01:59:37,880 --> 01:59:39,600
Speaker 1: Many of those didn't make it, and we're killed by

2263
01:59:39,640 --> 01:59:43,000
Speaker 1: carnivores perhaps or other factors that that calves died from,

2264
01:59:43,360 --> 01:59:45,800
Speaker 1: but lived her entire life on this landscape of carnivores

2265
01:59:45,840 --> 01:59:47,360
Speaker 1: and in the end was killed by a pack of

2266
01:59:48,280 --> 01:59:50,360
Speaker 1: and a half years old. There's so much here as

2267
01:59:50,400 --> 01:59:52,280
Speaker 1: I listened to all, you know, like as you just

2268
01:59:52,360 --> 01:59:55,720
Speaker 1: kind of like dump this information, like there's just such

2269
01:59:55,720 --> 01:59:58,680
Speaker 1: a wealth of experience. I'm here trying to like make

2270
01:59:58,760 --> 02:00:01,480
Speaker 1: some connective and I'm sure a lot of listeners are

2271
02:00:01,560 --> 02:00:03,880
Speaker 1: doing the same thing. And as I listen to talk

2272
02:00:03,920 --> 02:00:07,520
Speaker 1: about the ineffective predation of wolves and what they're able

2273
02:00:07,600 --> 02:00:10,560
Speaker 1: to do, um, it fits into the kind of this

2274
02:00:10,720 --> 02:00:16,440
Speaker 1: ecological idea that they are kind of literally eating at

2275
02:00:16,480 --> 02:00:20,120
Speaker 1: the edges from a population. It's the core. I'm just

2276
02:00:20,200 --> 02:00:24,040
Speaker 1: trying to articulately just I can, like the core population

2277
02:00:25,160 --> 02:00:30,280
Speaker 1: is not immune but largely immune to this predation, which

2278
02:00:30,320 --> 02:00:33,520
Speaker 1: allows both of these things to exist at the same time.

2279
02:00:34,440 --> 02:00:37,560
Speaker 1: And what might sound like a hyperbole, but is is

2280
02:00:37,640 --> 02:00:41,560
Speaker 1: some harmonic um you know, relationship. And the important part

2281
02:00:41,600 --> 02:00:44,440
Speaker 1: of the link there to to make is this. For

2282
02:00:44,720 --> 02:00:49,960
Speaker 1: an elk herd to grow or maintain a certain population size,

2283
02:00:50,000 --> 02:00:53,640
Speaker 1: you have to have two main two main things adult

2284
02:00:53,720 --> 02:00:59,280
Speaker 1: cow survival and caffree cruman Okay, bullolker, you know bull

2285
02:00:59,320 --> 02:01:01,360
Speaker 1: out are important to uh to us as hunters, right,

2286
02:01:01,440 --> 02:01:03,760
Speaker 1: I mean that's often the target for many, not all,

2287
02:01:04,040 --> 02:01:05,880
Speaker 1: many of us prefer to get a cow for me,

2288
02:01:06,040 --> 02:01:10,120
Speaker 1: but um, there's you can't deny the uh significance of

2289
02:01:10,160 --> 02:01:12,640
Speaker 1: bull elkin of population, of course, but for an elk

2290
02:01:12,680 --> 02:01:15,920
Speaker 1: herd itself, it's dynamic is largely driven by adult cow

2291
02:01:16,000 --> 02:01:19,520
Speaker 1: survival and elk calf recruitment. And so the reason we

2292
02:01:19,680 --> 02:01:22,320
Speaker 1: have what we see as a robust elk herd in

2293
02:01:22,360 --> 02:01:24,600
Speaker 1: this landscape despite this high bunths of carnivores, is that

2294
02:01:24,640 --> 02:01:27,120
Speaker 1: if you just look at the wolf's impact, is their

2295
02:01:27,160 --> 02:01:30,720
Speaker 1: biggest role on the trajectory of our elk herd is

2296
02:01:30,760 --> 02:01:33,560
Speaker 1: through killing elk calves, which impacts how many individuals are

2297
02:01:33,600 --> 02:01:38,240
Speaker 1: recruited into that herd and how long a cow elk survives,

2298
02:01:38,280 --> 02:01:41,480
Speaker 1: and and the longer she survives through those primary ages,

2299
02:01:41,560 --> 02:01:44,920
Speaker 1: more calves she cranks out. What we find here is

2300
02:01:45,120 --> 02:01:47,840
Speaker 1: high pregnancy rates of our cow elk and yellow stone

2301
02:01:49,160 --> 02:01:53,440
Speaker 1: more but of prime h cows are pregnant each year. Um,

2302
02:01:53,520 --> 02:01:57,120
Speaker 1: they're cranking out calves each year. At about age twelve thirteen,

2303
02:01:57,160 --> 02:01:59,600
Speaker 1: you start seeing what we call preproductive senescence, where they

2304
02:02:00,040 --> 02:02:02,720
Speaker 1: pregnancy races started declining, and the data is very strong

2305
02:02:02,880 --> 02:02:06,560
Speaker 1: in this and they probably stopped producing calves every year

2306
02:02:06,640 --> 02:02:10,440
Speaker 1: and start alternating and then probably stopped producing calves all together.

2307
02:02:10,880 --> 02:02:13,160
Speaker 1: So the fact that the average age of a cow

2308
02:02:13,240 --> 02:02:16,480
Speaker 1: we kill and Yellowstone Northern herd is a fourteen year

2309
02:02:16,480 --> 02:02:19,440
Speaker 1: old cow, she's at that point where she is less

2310
02:02:19,480 --> 02:02:22,880
Speaker 1: important to her dynamics than the prime h cow, the

2311
02:02:22,960 --> 02:02:26,040
Speaker 1: average agent. I don't make this to pick hunters human

2312
02:02:26,120 --> 02:02:29,360
Speaker 1: hunters versus wolves, but just did the data's uh, just

2313
02:02:29,480 --> 02:02:32,320
Speaker 1: to explain the data uh during the gardener Lei hunters,

2314
02:02:32,320 --> 02:02:34,879
Speaker 1: all this great data collected by the State will Montana,

2315
02:02:34,960 --> 02:02:39,600
Speaker 1: State will uh Montana um fish, wildlife and parks, and

2316
02:02:39,840 --> 02:02:42,040
Speaker 1: the average age of the cow l carves did during

2317
02:02:42,080 --> 02:02:44,800
Speaker 1: the gardener Leig hunt all those years was about six.

2318
02:02:45,000 --> 02:02:46,960
Speaker 1: You know, that's a prime ate cow, incredibly important to

2319
02:02:47,000 --> 02:02:50,800
Speaker 1: el caffre recruitment. So when you look at the reason

2320
02:02:50,880 --> 02:02:53,400
Speaker 1: that wolves haven't caused his help her to crash is

2321
02:02:53,440 --> 02:02:56,640
Speaker 1: that there's still enough cows each year that are surviving

2322
02:02:56,720 --> 02:02:59,720
Speaker 1: from year one to year two putting out a calf.

2323
02:02:59,800 --> 02:03:03,280
Speaker 1: Now you know, fifty to sev those calves aren't gonna

2324
02:03:03,280 --> 02:03:05,600
Speaker 1: make it till adulthood. They're gonna get killed by carnivores,

2325
02:03:05,600 --> 02:03:09,560
Speaker 1: They're gonna die from weather, disease, drowning, you name it.

2326
02:03:09,640 --> 02:03:12,680
Speaker 1: All factors um, But as long as enough of those

2327
02:03:12,720 --> 02:03:15,440
Speaker 1: calves survived, you can have a stable herder growing. So

2328
02:03:16,440 --> 02:03:19,520
Speaker 1: that helps put that perspective of the limits of wolf

2329
02:03:19,600 --> 02:03:22,800
Speaker 1: hunting ability into perspectives that that's why you can have

2330
02:03:22,960 --> 02:03:25,680
Speaker 1: a stable elk herd and still have a fair bit

2331
02:03:25,720 --> 02:03:29,120
Speaker 1: of wolf predation. It depends on which elk they're killing. Um.

2332
02:03:29,440 --> 02:03:32,960
Speaker 1: And as we know, uh, you know, a few bowls

2333
02:03:33,000 --> 02:03:35,040
Speaker 1: can breed a lot of cows. So yes, wolves are

2334
02:03:35,040 --> 02:03:37,919
Speaker 1: going to kill mature bull elk. That again, their success

2335
02:03:38,000 --> 02:03:41,600
Speaker 1: at killing bull elk is largely driven by seasonal vulnerability

2336
02:03:41,760 --> 02:03:45,480
Speaker 1: late winter. Now let's remember bull elk have weapons. And

2337
02:03:45,560 --> 02:03:47,680
Speaker 1: this is another great finding we had from Yellowstones. We

2338
02:03:47,800 --> 02:03:51,960
Speaker 1: this really neat study on wolves in late winter in

2339
02:03:52,120 --> 02:03:56,040
Speaker 1: March when elk transition from antler to dropping their ambers.

2340
02:03:56,160 --> 02:03:58,200
Speaker 1: This is a really fascinating study led by one of

2341
02:03:58,240 --> 02:04:01,480
Speaker 1: our long term researchers, Matt Matts. He's a finishing his

2342
02:04:01,640 --> 02:04:04,800
Speaker 1: doctoral degree at University of Montanadism took the initiative years

2343
02:04:04,840 --> 02:04:08,200
Speaker 1: ago to start collecting this observation data during our winter studies.

2344
02:04:08,240 --> 02:04:11,080
Speaker 1: Where the data we started collecting was looking at when

2345
02:04:11,160 --> 02:04:14,760
Speaker 1: wolves attack bull out groups, do they select the pedical

2346
02:04:14,800 --> 02:04:17,040
Speaker 1: bulls are the ones wearing anidlers, and we found that

2347
02:04:17,280 --> 02:04:21,040
Speaker 1: they were. There was significantly greater selection for pedal for

2348
02:04:21,200 --> 02:04:24,600
Speaker 1: pedical bowls than antler bulls. The ironic part of this

2349
02:04:24,720 --> 02:04:28,040
Speaker 1: story is is that we think of wolves needing vulnerable

2350
02:04:28,080 --> 02:04:30,440
Speaker 1: prey to be successful, and when you look at the

2351
02:04:30,560 --> 02:04:34,080
Speaker 1: bulls that dropped their antlers first, they are in better condition.

2352
02:04:34,400 --> 02:04:37,760
Speaker 1: You know, bull antler growth and bull reproductive success, as

2353
02:04:37,840 --> 02:04:41,840
Speaker 1: we all know, is driven by antler size. Um uh.

2354
02:04:42,000 --> 02:04:45,360
Speaker 1: It is the primary selective forces sexual selection with antlers

2355
02:04:45,400 --> 02:04:48,440
Speaker 1: and ungulates. But secondarily, we believe they've served as a

2356
02:04:48,480 --> 02:04:51,280
Speaker 1: predatory defense and Yelso we're able to demonstrate that whereas

2357
02:04:51,280 --> 02:04:55,480
Speaker 1: that wolves would, given the choice, which makes sense, go

2358
02:04:55,720 --> 02:04:58,320
Speaker 1: for the one that wasn't wearing the ailers, and ironically

2359
02:04:58,360 --> 02:05:00,440
Speaker 1: they were the bulls in better condition. But the trade

2360
02:05:00,480 --> 02:05:02,480
Speaker 1: off there was that I'm from a wolfs per side

2361
02:05:02,480 --> 02:05:04,200
Speaker 1: and I'm less likely to get gore because we see

2362
02:05:04,240 --> 02:05:05,880
Speaker 1: bowls do this. They stand their ground, they put their

2363
02:05:05,880 --> 02:05:10,160
Speaker 1: antlers down. We've had wolves die from getting gored from elk,

2364
02:05:10,560 --> 02:05:12,800
Speaker 1: from bison, so we know it is it is a

2365
02:05:12,880 --> 02:05:15,200
Speaker 1: real risk to them, and we have this really sweet

2366
02:05:15,280 --> 02:05:19,800
Speaker 1: data set that demonstrated that antler retention in elk is

2367
02:05:19,880 --> 02:05:22,560
Speaker 1: probably being driven by wolf predation over the thousands of years,

2368
02:05:22,600 --> 02:05:24,800
Speaker 1: because they are the primary prey. And many of these

2369
02:05:24,800 --> 02:05:27,000
Speaker 1: systems where there's wolves and elk for thousands of years

2370
02:05:27,920 --> 02:05:30,720
Speaker 1: and things like mule deer, white till dear moose drop

2371
02:05:30,920 --> 02:05:33,920
Speaker 1: much earlier in the winter. Not that they aren't prey

2372
02:05:34,040 --> 02:05:35,720
Speaker 1: the wolves, they certainly are, but if elk are the

2373
02:05:35,800 --> 02:05:39,040
Speaker 1: primary prey, it's probably was a selective pressure in part

2374
02:05:39,440 --> 02:05:42,000
Speaker 1: for retaining antlers for longer, because if you have your

2375
02:05:42,040 --> 02:05:44,000
Speaker 1: antlers on your head, you're less likely to be killed

2376
02:05:44,040 --> 02:05:45,440
Speaker 1: by wolves. Now are they Are they growing them back

2377
02:05:45,480 --> 02:05:47,880
Speaker 1: earlier as well? As does that make sense where they're

2378
02:05:47,880 --> 02:05:51,640
Speaker 1: being hunted less by wolves at that time, because so, yeah,

2379
02:05:52,160 --> 02:05:54,320
Speaker 1: so I don't know about if they're going back earlier

2380
02:05:54,400 --> 02:05:57,200
Speaker 1: or not. You know, they are obviously earlier. Antler growth

2381
02:05:57,280 --> 02:06:01,040
Speaker 1: is starting immediately once they're shed, and that nutrient that

2382
02:06:01,040 --> 02:06:03,680
Speaker 1: blood vessels start pumping in, and that's of course antler

2383
02:06:03,720 --> 02:06:06,200
Speaker 1: being one of the fastest growing tissues in the animal kingdom.

2384
02:06:06,600 --> 02:06:08,960
Speaker 1: And you know, but of course the sooner you start growing,

2385
02:06:09,000 --> 02:06:11,080
Speaker 1: the bigger your antlers can get. So there is a

2386
02:06:11,320 --> 02:06:14,840
Speaker 1: again probably driven by sexual selection to grow to drop early,

2387
02:06:15,120 --> 02:06:17,240
Speaker 1: and if you drop early, you'll grow bigger and that

2388
02:06:17,560 --> 02:06:20,440
Speaker 1: theoretically will enhance your reproductive success in the fall. But

2389
02:06:20,600 --> 02:06:26,040
Speaker 1: wolves have tip have like inserted themselves into that story

2390
02:06:26,040 --> 02:06:28,960
Speaker 1: a little bit, we believe, through evolutionary history, which is

2391
02:06:29,000 --> 02:06:30,880
Speaker 1: so that's another really cool part of it. So, you know,

2392
02:06:30,960 --> 02:06:32,600
Speaker 1: all in all, kind of what I just went through

2393
02:06:32,640 --> 02:06:34,600
Speaker 1: is sort of demonstrating that wolves need vulnerable pray to

2394
02:06:34,640 --> 02:06:38,200
Speaker 1: be successful by and large, UM, and there are limits

2395
02:06:38,240 --> 02:06:40,680
Speaker 1: to their ability as a hunter. And that is why

2396
02:06:41,480 --> 02:06:45,920
Speaker 1: you are unlikely um to have in most places sort

2397
02:06:45,960 --> 02:06:48,840
Speaker 1: of a runaway predation, a sort of wiping out of

2398
02:06:48,880 --> 02:06:51,840
Speaker 1: an ungulate her. Yeah, they're just not able to do it.

2399
02:06:52,240 --> 02:06:55,240
Speaker 1: They just are not capable of doing it. Yeah. And

2400
02:06:55,320 --> 02:06:57,960
Speaker 1: I think as I sit here too, and I'm thinking about,

2401
02:06:58,520 --> 02:07:00,600
Speaker 1: you know, the totality of all the converse stations I've had.

2402
02:07:00,640 --> 02:07:04,360
Speaker 1: This is episode one thirty five or so. We I

2403
02:07:04,480 --> 02:07:06,600
Speaker 1: had a conversation with the guy named Douce Shon's Mentana

2404
02:07:06,640 --> 02:07:10,280
Speaker 1: who lives in Bozeman. He's a photographer but originally came

2405
02:07:10,320 --> 02:07:13,880
Speaker 1: from Czechosto, Fakia, and over there they had a like

2406
02:07:13,920 --> 02:07:18,040
Speaker 1: a traditional idea that the hunter was revered in the

2407
02:07:18,120 --> 02:07:21,880
Speaker 1: community because of his knowledge, because well, because of his

2408
02:07:22,040 --> 02:07:25,640
Speaker 1: responsibility to have a knowledge of the ecosystem, to know

2409
02:07:26,120 --> 02:07:28,640
Speaker 1: which animals need to be plucked off the landscape, to

2410
02:07:28,760 --> 02:07:32,040
Speaker 1: know what the predation was happening, to really understand and

2411
02:07:32,240 --> 02:07:36,440
Speaker 1: and provide value to their community from their understanding of

2412
02:07:36,640 --> 02:07:39,640
Speaker 1: what they had to do to maintain these healthy populations

2413
02:07:39,920 --> 02:07:41,680
Speaker 1: as a hunter, and this was kind of a traditional

2414
02:07:41,960 --> 02:07:43,480
Speaker 1: forget the term that he used that that was a

2415
02:07:43,600 --> 02:07:46,800
Speaker 1: check term. Um, But it was interesting to hear him

2416
02:07:46,840 --> 02:07:50,440
Speaker 1: say that. And it's interesting to hear this information that

2417
02:07:51,360 --> 02:07:53,960
Speaker 1: not many hunters really know, and not many people, not

2418
02:07:54,040 --> 02:07:57,600
Speaker 1: many biologists are able to suss out study. So as

2419
02:07:57,640 --> 02:07:59,760
Speaker 1: a hunter, you understand, Okay, this is what wolves are

2420
02:07:59,760 --> 02:08:02,280
Speaker 1: doing to these herds, regardless of what I can do

2421
02:08:02,400 --> 02:08:05,640
Speaker 1: with this tag. It's interesting to me too then that

2422
02:08:05,800 --> 02:08:09,960
Speaker 1: greater understanding. It's kind of the responsibility of a hunter

2423
02:08:10,040 --> 02:08:12,400
Speaker 1: in the modern in the modern shirt to understand, like

2424
02:08:12,480 --> 02:08:14,920
Speaker 1: what are all the dynamics here? Um, if I have

2425
02:08:14,960 --> 02:08:16,720
Speaker 1: a cow tag and I have a bull tag, what

2426
02:08:16,800 --> 02:08:18,720
Speaker 1: do I do with those things? Yeah? I mean I

2427
02:08:18,800 --> 02:08:21,600
Speaker 1: think you know, and I those of us that spend

2428
02:08:21,640 --> 02:08:24,000
Speaker 1: time hunting out It is hard to do and we

2429
02:08:24,160 --> 02:08:27,640
Speaker 1: have tools much more so than wold. So, UM, you

2430
02:08:27,720 --> 02:08:30,800
Speaker 1: know many people like myself, you know, a bird in

2431
02:08:30,840 --> 02:08:33,880
Speaker 1: the hand. Ye, my, here's my chance. And you can't

2432
02:08:33,920 --> 02:08:37,520
Speaker 1: be selective and you aren't selective and um and other people,

2433
02:08:37,920 --> 02:08:40,120
Speaker 1: UM either might be a better hunter or be able

2434
02:08:40,120 --> 02:08:42,960
Speaker 1: to hunt and U have more time to hunt or

2435
02:08:43,080 --> 02:08:45,080
Speaker 1: be able to hunt in a place that um, they've

2436
02:08:45,080 --> 02:08:47,400
Speaker 1: really learned the patterns and can be more selective, and

2437
02:08:47,480 --> 02:08:49,240
Speaker 1: they might decide like, no, I really want to go

2438
02:08:49,400 --> 02:08:51,360
Speaker 1: for this sort of an animal this year. But but

2439
02:08:51,400 --> 02:08:54,040
Speaker 1: you would imagine if you know graduate level hunting, if

2440
02:08:54,080 --> 02:08:57,040
Speaker 1: you start out, you know, there's these philosophies that hunters

2441
02:08:57,120 --> 02:08:59,960
Speaker 1: go through stages being that hunters start. If you start

2442
02:09:00,000 --> 02:09:01,600
Speaker 1: it as a hunter when you were a child, you

2443
02:09:01,680 --> 02:09:04,839
Speaker 1: go through these stages right, well you imagine, I imagine

2444
02:09:04,880 --> 02:09:07,120
Speaker 1: that even my own I'm sure your evolution has a

2445
02:09:07,200 --> 02:09:10,360
Speaker 1: hunter mine as well. You go through these stages of

2446
02:09:10,520 --> 02:09:13,960
Speaker 1: understanding and appreciation and value, and you would hope that

2447
02:09:14,040 --> 02:09:16,080
Speaker 1: you'd be able to, you know, listen to this. Everybody

2448
02:09:16,160 --> 02:09:18,720
Speaker 1: that is out there learned to hunt or is brand

2449
02:09:18,760 --> 02:09:21,560
Speaker 1: new that you know this is something is it that

2450
02:09:21,640 --> 02:09:27,000
Speaker 1: has value beyond just the understanding of wolves has value

2451
02:09:27,040 --> 02:09:30,360
Speaker 1: to your you know, to your role, to what you

2452
02:09:30,440 --> 02:09:32,400
Speaker 1: can do and what you can't do based on what

2453
02:09:32,680 --> 02:09:35,800
Speaker 1: other predation factors exist. And I would encourage anyone that

2454
02:09:36,120 --> 02:09:39,080
Speaker 1: is passionate about, you know, the landscape they hunt on

2455
02:09:39,280 --> 02:09:42,760
Speaker 1: to to learn about the local ecosystem there, and you know,

2456
02:09:42,840 --> 02:09:45,760
Speaker 1: talk to your local biologists that spend a lot of

2457
02:09:45,840 --> 02:09:47,680
Speaker 1: time in the ground. I mean, you know, I don't

2458
02:09:47,680 --> 02:09:51,240
Speaker 1: want to demean or diminish the experience that hunters have.

2459
02:09:51,560 --> 02:09:53,760
Speaker 1: I mean we let's face it, when you have boots

2460
02:09:53,800 --> 02:09:56,440
Speaker 1: on the ground, you spend time out there, you inherently

2461
02:09:56,800 --> 02:10:00,600
Speaker 1: learn and pick up a lot of things um about

2462
02:10:00,720 --> 02:10:03,600
Speaker 1: the landscape and the animals. And that knowledge is irreplaceable

2463
02:10:03,680 --> 02:10:06,880
Speaker 1: to any scientists, data point, to any uh you know,

2464
02:10:07,040 --> 02:10:09,840
Speaker 1: so you embrace that, but also take advantage to you know,

2465
02:10:09,880 --> 02:10:12,120
Speaker 1: I encourage people to really learn about what's happening in

2466
02:10:12,160 --> 02:10:14,440
Speaker 1: that particular hunt unit they're going into. You know, what

2467
02:10:14,560 --> 02:10:17,600
Speaker 1: are our wolf populations, like, what are our sugar populations? Like?

2468
02:10:18,000 --> 02:10:20,520
Speaker 1: You know, what role may they have? Our bears, cougars,

2469
02:10:20,560 --> 02:10:22,040
Speaker 1: and wolves all playing a role at different times of

2470
02:10:22,080 --> 02:10:25,240
Speaker 1: the year. What is my role as a human hunter

2471
02:10:25,480 --> 02:10:28,200
Speaker 1: as part of that story? To um, what did the

2472
02:10:28,600 --> 02:10:30,480
Speaker 1: habitat to do this year? What was the winner like,

2473
02:10:30,640 --> 02:10:33,280
Speaker 1: what was the summer precip like? And and not being

2474
02:10:33,360 --> 02:10:36,920
Speaker 1: so quick to jump to that one convenient scapegoat of

2475
02:10:36,960 --> 02:10:39,200
Speaker 1: why you may not have filled your tag. Well, I

2476
02:10:39,320 --> 02:10:41,400
Speaker 1: hear this all the time. You know, while I was

2477
02:10:41,640 --> 02:10:43,080
Speaker 1: in this area and all I saw were wolf and

2478
02:10:43,120 --> 02:10:44,960
Speaker 1: cougar tracks, So you know, there's no good it's not

2479
02:10:45,000 --> 02:10:47,800
Speaker 1: good hunting. I mean, I've been hunting here in the

2480
02:10:47,880 --> 02:10:52,480
Speaker 1: gardener basin for the last twenty years, and um, you know,

2481
02:10:52,560 --> 02:10:55,160
Speaker 1: every day where I hunt, you know that one of

2482
02:10:55,160 --> 02:10:57,840
Speaker 1: the most things I enjoy the most is coming across

2483
02:10:57,880 --> 02:11:00,680
Speaker 1: that cougar wolf track. And you know, I just know

2484
02:11:00,880 --> 02:11:03,560
Speaker 1: that there's also elk and deer out there well as well,

2485
02:11:03,560 --> 02:11:08,120
Speaker 1: because that's why they're there. Um, and you know, trying

2486
02:11:08,200 --> 02:11:11,200
Speaker 1: to understand how all those different pieces fit together. Now,

2487
02:11:11,480 --> 02:11:13,640
Speaker 1: you know, I'm not trying to paint this picture to say, well,

2488
02:11:14,080 --> 02:11:17,760
Speaker 1: don't have an effect. They don't impact elk. They certainly do.

2489
02:11:17,880 --> 02:11:19,400
Speaker 1: And that's you know, part of the story of Yellowstone

2490
02:11:19,440 --> 02:11:21,680
Speaker 1: is that, yeah, they reduced the elk herd. You could

2491
02:11:21,760 --> 02:11:24,760
Speaker 1: say in the years where we didn't have carnivores, and

2492
02:11:24,880 --> 02:11:27,480
Speaker 1: even the gardener leigh hunt could only do so much

2493
02:11:27,840 --> 02:11:31,040
Speaker 1: to reduce the hunt. And what you had is an

2494
02:11:31,120 --> 02:11:34,200
Speaker 1: elk herd that was probably uh. And when we know this,

2495
02:11:34,400 --> 02:11:36,600
Speaker 1: we've got good data on this of density dependence, we

2496
02:11:36,680 --> 02:11:39,840
Speaker 1: call it. When you have high density ungular herds, you

2497
02:11:39,920 --> 02:11:42,880
Speaker 1: tend to have a poor body condition, more competition for

2498
02:11:42,960 --> 02:11:47,920
Speaker 1: available food, um, you tend to have um bigger effects

2499
02:11:47,920 --> 02:11:51,680
Speaker 1: of winter die offs. In a system absence of top

2500
02:11:51,800 --> 02:11:55,640
Speaker 1: predators and natural predators, you tend to have more large

2501
02:11:55,760 --> 02:11:58,720
Speaker 1: scale variation in your booms and your bust and your crashes.

2502
02:11:59,160 --> 02:12:01,520
Speaker 1: And when you have a system where your top predators

2503
02:12:01,560 --> 02:12:04,000
Speaker 1: are in place, it dampens that. And so if you

2504
02:12:04,080 --> 02:12:06,720
Speaker 1: look at the elk herd and Yellowstone over since the

2505
02:12:06,840 --> 02:12:09,880
Speaker 1: nineteen twenties when the first counts really started, you see

2506
02:12:09,960 --> 02:12:12,080
Speaker 1: in the absence of carnivores, you know, carnivores are removed

2507
02:12:12,080 --> 02:12:14,120
Speaker 1: from this landscape. And let's just use the northern herd

2508
02:12:14,160 --> 02:12:17,960
Speaker 1: as an example. UM that elk herds started climbing in

2509
02:12:18,080 --> 02:12:21,920
Speaker 1: high numbers by the nineteen twenty five. The last cougars

2510
02:12:21,960 --> 02:12:23,560
Speaker 1: were thought to have killed the last wolves were thought

2511
02:12:23,560 --> 02:12:26,200
Speaker 1: to have been killed in the park. You saw that

2512
02:12:26,240 --> 02:12:28,640
Speaker 1: northern arangelkhorts starting to climb, and then the park stepped

2513
02:12:28,680 --> 02:12:31,400
Speaker 1: in and said, well, wait, we need to start doing something.

2514
02:12:31,440 --> 02:12:32,880
Speaker 1: Even Teddy Rose about when he was here in the

2515
02:12:32,880 --> 02:12:35,840
Speaker 1: early nineteen hundreds recognized they had all these starving elk.

2516
02:12:35,880 --> 02:12:39,240
Speaker 1: What the park do? They started feeding alfalfa um, They

2517
02:12:39,320 --> 02:12:43,240
Speaker 1: started translocating and calling. Do do the listeners realize? This

2518
02:12:43,320 --> 02:12:45,480
Speaker 1: is a really great part of Yelow's story about fifteen

2519
02:12:45,560 --> 02:12:49,000
Speaker 1: thousand elk over the years between the nineteen twenties and

2520
02:12:49,440 --> 02:12:52,680
Speaker 1: nineteen and nineteen sixties. Over fifteen about fifteen elk where

2521
02:12:52,720 --> 02:12:57,440
Speaker 1: translocated from Yellowstone National Park as the source population for

2522
02:12:57,560 --> 02:13:02,200
Speaker 1: elk throughout uh, not just United States, but Canada, Argentina.

2523
02:13:02,400 --> 02:13:06,240
Speaker 1: Places where you see elk now can and most places

2524
02:13:06,280 --> 02:13:10,160
Speaker 1: linked back to Yellowstone. And and so the park was

2525
02:13:10,240 --> 02:13:15,080
Speaker 1: involved in heavy management of our elk herds, you know, calling, shooting, translocations,

2526
02:13:15,760 --> 02:13:20,160
Speaker 1: and then it became out of public favor and the

2527
02:13:20,920 --> 02:13:23,160
Speaker 1: Park Service went into in the sixties this idea of

2528
02:13:23,240 --> 02:13:27,120
Speaker 1: natural regulation. Let's stop the calling, let's stop the translocation,

2529
02:13:27,200 --> 02:13:30,600
Speaker 1: let's step back, let's go into natural regulations. See what happens. Well,

2530
02:13:30,720 --> 02:13:33,880
Speaker 1: then what happened is we still didn't have carnivores boom

2531
02:13:33,920 --> 02:13:35,760
Speaker 1: that Elkord just started climbing. And I'm just talking about

2532
02:13:35,760 --> 02:13:37,520
Speaker 1: the Northern herd. There are the Elkords that use yellowstone

2533
02:13:37,560 --> 02:13:39,120
Speaker 1: as well, and I'm sure many of them went through

2534
02:13:39,160 --> 02:13:42,440
Speaker 1: similar changes. Uh, the Northern Ranges are best Northern herds

2535
02:13:42,480 --> 02:13:45,120
Speaker 1: are best studied herd long term, and we have that

2536
02:13:45,280 --> 02:13:48,920
Speaker 1: heard get incredibly high abundance, high densities, and we saw

2537
02:13:49,480 --> 02:13:53,560
Speaker 1: on average probably body condition, pregnancy rates go down, more competition,

2538
02:13:53,640 --> 02:13:56,760
Speaker 1: and so you know what we have today is there's

2539
02:13:56,800 --> 02:13:59,400
Speaker 1: no doubt about it. And for the foreseeable future. You know,

2540
02:13:59,520 --> 02:14:02,760
Speaker 1: the days twenty elk in the northern herd are gone. Um.

2541
02:14:03,280 --> 02:14:05,880
Speaker 1: You know that has cultural significance, of course, but from

2542
02:14:05,920 --> 02:14:09,640
Speaker 1: a biological standpoint, UM, we have what we believe is

2543
02:14:09,720 --> 02:14:14,920
Speaker 1: a incredibly healthy, stable, robust Elk herd right now. Our

2544
02:14:15,000 --> 02:14:18,120
Speaker 1: population estimation is about eight thousand seven eight thousand elk.

2545
02:14:18,600 --> 02:14:20,840
Speaker 1: We count elk every year by doing a one day

2546
02:14:21,040 --> 02:14:22,520
Speaker 1: you go up in an airplane, you count as many

2547
02:14:22,560 --> 02:14:24,040
Speaker 1: elk because you see on the landscape and one day

2548
02:14:24,040 --> 02:14:28,800
Speaker 1: from multiple planes. It is a um, a very imprecise

2549
02:14:29,520 --> 02:14:32,040
Speaker 1: uh techniques, So everyone kind of hangs her hat on,

2550
02:14:32,160 --> 02:14:34,160
Speaker 1: like this year there are three thousand four in ninety

2551
02:14:34,160 --> 02:14:36,720
Speaker 1: two elknelso, and then the northern herd, well, it's a

2552
02:14:36,840 --> 02:14:39,200
Speaker 1: it's a minimum estimate, it's account. And what we do

2553
02:14:39,320 --> 02:14:42,120
Speaker 1: is we apply tools that biologists used call that siteability

2554
02:14:42,440 --> 02:14:46,400
Speaker 1: correction factor. Where, um, you you are only counting a

2555
02:14:46,440 --> 02:14:48,720
Speaker 1: minimum number of the elk. Your your probability of count

2556
02:14:49,120 --> 02:14:52,240
Speaker 1: pcent is always going to be less, you know, and

2557
02:14:52,400 --> 02:14:55,000
Speaker 1: and so you are basically trying to understand, Okay, here's

2558
02:14:55,000 --> 02:14:58,160
Speaker 1: our count what is our siteability and so, um, this

2559
02:14:58,320 --> 02:15:00,960
Speaker 1: last year, about six thousand count elk we're counted during

2560
02:15:01,000 --> 02:15:03,120
Speaker 1: the that day, that one day count, and that includes

2561
02:15:03,200 --> 02:15:06,160
Speaker 1: the elk that are wintering north of the park up

2562
02:15:06,200 --> 02:15:09,640
Speaker 1: towards Dome Mountain and Paradise Valley. And what that translates

2563
02:15:09,720 --> 02:15:12,040
Speaker 1: into based on our side ability index is closer to

2564
02:15:12,120 --> 02:15:14,880
Speaker 1: a herd size about eight thousand, okay, so, and our

2565
02:15:14,920 --> 02:15:18,360
Speaker 1: herd has kind of the decline is stabilized. Um, some

2566
02:15:18,560 --> 02:15:20,360
Speaker 1: years we have good counts, some year we have bad counts.

2567
02:15:20,360 --> 02:15:23,040
Speaker 1: So when you try to correct for those imprecise counting

2568
02:15:23,080 --> 02:15:25,200
Speaker 1: methods of the airplane counts. You know, we have a

2569
02:15:25,280 --> 02:15:28,600
Speaker 1: herd that is stable and if not slightly increasing. What

2570
02:15:28,800 --> 02:15:30,440
Speaker 1: is the future hole We don't know what is going

2571
02:15:30,480 --> 02:15:32,960
Speaker 1: to be the role of chronic wasting disease. We believe

2572
02:15:33,000 --> 02:15:35,560
Speaker 1: carnivores might play an important role in there. That's yet

2573
02:15:35,600 --> 02:15:37,880
Speaker 1: to be determined. Yell soon will be a great place

2574
02:15:37,960 --> 02:15:40,880
Speaker 1: to study that should it show up here. Um. What

2575
02:15:40,960 --> 02:15:43,560
Speaker 1: it's going to be, the effective climate change of future droughts,

2576
02:15:43,600 --> 02:15:46,920
Speaker 1: of future winter severities. UM, We'll wrangle with this for

2577
02:15:47,040 --> 02:15:50,200
Speaker 1: decades to come. UM. But I think we are starting

2578
02:15:50,240 --> 02:15:53,680
Speaker 1: to hone in a little bit more closely on teasing

2579
02:15:53,720 --> 02:15:56,080
Speaker 1: out what the role of wolves are, what the role

2580
02:15:56,120 --> 02:15:59,400
Speaker 1: of cougars are, what the role of bears are, what

2581
02:15:59,440 --> 02:16:02,200
Speaker 1: the role of human and hunting is, and and and

2582
02:16:02,760 --> 02:16:05,960
Speaker 1: if we continue with get a lot of stakeholder involvement

2583
02:16:06,080 --> 02:16:09,600
Speaker 1: of different walks of life and values and views, we

2584
02:16:09,680 --> 02:16:11,600
Speaker 1: will be best served to keep this research going on

2585
02:16:11,720 --> 02:16:14,000
Speaker 1: into the future. And we hope that that helps better

2586
02:16:14,120 --> 02:16:18,880
Speaker 1: understand how we manage our elk herds, how we manage carnivores, UM,

2587
02:16:18,960 --> 02:16:22,720
Speaker 1: what level of hunting can be at play, um and um.

2588
02:16:23,200 --> 02:16:24,720
Speaker 1: And we have to remember that we've got to be

2589
02:16:24,800 --> 02:16:27,800
Speaker 1: cautious of not to apply you know, everything we're finding

2590
02:16:27,800 --> 02:16:30,560
Speaker 1: about Yellowstone to other parts of the greater yellow soonne

2591
02:16:30,560 --> 02:16:34,879
Speaker 1: ecosystem and then beyond um for example, Uh, it would

2592
02:16:34,920 --> 02:16:37,879
Speaker 1: be hard to argue that you will see strong trophic

2593
02:16:37,920 --> 02:16:40,680
Speaker 1: cascade effects and many parts of the Rocky Mountain West

2594
02:16:40,720 --> 02:16:44,440
Speaker 1: where carnivores are restored, just because humans still play such

2595
02:16:44,440 --> 02:16:47,680
Speaker 1: a large role in both carnivores and ungulates, and so

2596
02:16:48,320 --> 02:16:51,039
Speaker 1: you know, even in yellow Stone where humans are largely

2597
02:16:51,080 --> 02:16:54,960
Speaker 1: out of the picture, we still wrangle with what the

2598
02:16:55,000 --> 02:16:58,960
Speaker 1: relative effects are on that that particular issue. So we

2599
02:16:59,120 --> 02:17:02,160
Speaker 1: can't expect to see strong effects outside of a place

2600
02:17:02,200 --> 02:17:05,480
Speaker 1: where you know, carnivore levels probably densities are being kept

2601
02:17:05,560 --> 02:17:10,400
Speaker 1: lower because management. UM. Anyway, that's a huge part of

2602
02:17:10,440 --> 02:17:12,040
Speaker 1: it too. And I think as as you as you're

2603
02:17:12,080 --> 02:17:13,920
Speaker 1: kind of walking through this, you're answering all my questions

2604
02:17:13,920 --> 02:17:15,960
Speaker 1: before I have as I think, so, I think, you know,

2605
02:17:16,080 --> 02:17:18,760
Speaker 1: a lot of this is to go a little bit

2606
02:17:18,879 --> 02:17:23,880
Speaker 1: back to you know, this is ever evolving. Um, the

2607
02:17:24,040 --> 02:17:28,320
Speaker 1: knowledge base is ever evolving, and so there isn't there

2608
02:17:28,360 --> 02:17:30,160
Speaker 1: is ever gonna be one answer, you know, So I

2609
02:17:30,200 --> 02:17:33,000
Speaker 1: think the next the next thing everybody is wondering. You

2610
02:17:33,120 --> 02:17:34,640
Speaker 1: just touched on it a little bit, is what's the

2611
02:17:34,760 --> 02:17:37,560
Speaker 1: future of all this as we see, as we use

2612
02:17:37,680 --> 02:17:39,440
Speaker 1: this landscape that we're looking at it right now, this

2613
02:17:39,720 --> 02:17:42,840
Speaker 1: this vast serengetti that we're looking at that has enjoyed,

2614
02:17:43,440 --> 02:17:46,320
Speaker 1: you know, this reintroduction of wolves and being able to

2615
02:17:46,400 --> 02:17:48,640
Speaker 1: kind of see it like you do. Then you think

2616
02:17:48,640 --> 02:17:51,400
Speaker 1: of the future of of wildlife management. We have We

2617
02:17:51,520 --> 02:17:54,160
Speaker 1: have ballot box biology going on in Colorado right now

2618
02:17:54,200 --> 02:17:57,039
Speaker 1: where they want to put a referendum to introduce wolves.

2619
02:17:57,360 --> 02:18:00,480
Speaker 1: You have this Greater Yellowstone ecosystem situation with the grizzly

2620
02:18:00,520 --> 02:18:03,520
Speaker 1: bear population where the argument is less like should the

2621
02:18:03,560 --> 02:18:07,160
Speaker 1: grizzly bears be there? And can hunting play a role

2622
02:18:07,400 --> 02:18:10,560
Speaker 1: in managing them? So there's an argument there. Just to

2623
02:18:10,640 --> 02:18:13,160
Speaker 1: maybe crystallize it and correct me if I'm if I'm

2624
02:18:13,200 --> 02:18:15,600
Speaker 1: off here, the the argument for keeping them on the

2625
02:18:15,680 --> 02:18:18,440
Speaker 1: endangered species list is if you kill a certain number

2626
02:18:18,480 --> 02:18:20,920
Speaker 1: of them, they may not be able to be feeder

2627
02:18:21,000 --> 02:18:25,520
Speaker 1: populations for other very important um grizzly bear populations outside

2628
02:18:25,560 --> 02:18:28,360
Speaker 1: of this ecosystem. So that like, do you have these

2629
02:18:28,480 --> 02:18:33,480
Speaker 1: little pockets of debate that I'm sure we'll continue. UM.

2630
02:18:33,640 --> 02:18:36,520
Speaker 1: But over time, I imagine that the battle too to

2631
02:18:36,720 --> 02:18:40,200
Speaker 1: protect these animals, to hunt them, to include them, to

2632
02:18:40,400 --> 02:18:43,600
Speaker 1: dis you know, to not include them is going to

2633
02:18:44,360 --> 02:18:47,880
Speaker 1: you know, only intensify as we experiment. It's quite sober,

2634
02:18:48,040 --> 02:18:51,800
Speaker 1: I mean, because there's so many things out of our control.

2635
02:18:51,959 --> 02:18:56,279
Speaker 1: I mean, we can talk about management and what actions

2636
02:18:56,320 --> 02:18:58,600
Speaker 1: can managers play, whether it be in a national park

2637
02:18:58,680 --> 02:19:01,280
Speaker 1: and some more hands off a pro to a state

2638
02:19:01,360 --> 02:19:05,119
Speaker 1: agency that is challenged with managing a variety of species

2639
02:19:05,160 --> 02:19:09,480
Speaker 1: into one landscape. UM. But the things that we can't control,

2640
02:19:09,520 --> 02:19:11,160
Speaker 1: I mean, look what our country is going through right now.

2641
02:19:11,800 --> 02:19:14,440
Speaker 1: We covered the unforeseen effects of a disease outbreak and

2642
02:19:14,480 --> 02:19:19,680
Speaker 1: our wildlife populations, the unforeseen impacts of climate change. UM.

2643
02:19:19,800 --> 02:19:21,680
Speaker 1: And so we can look at the debate of what

2644
02:19:21,800 --> 02:19:24,680
Speaker 1: we should do with the grizzly bear and you know,

2645
02:19:24,840 --> 02:19:29,480
Speaker 1: can they can sustain hunting and and ultimately comes down

2646
02:19:29,600 --> 02:19:33,560
Speaker 1: to is um. You know, bears will be removed because

2647
02:19:33,600 --> 02:19:36,600
Speaker 1: of the challenges of coexisting with them on a human

2648
02:19:36,680 --> 02:19:40,600
Speaker 1: dominated landscape and what's the best way to manage And

2649
02:19:40,640 --> 02:19:43,800
Speaker 1: I'm not going to enter into a gressing discussion necessarily, UM,

2650
02:19:43,879 --> 02:19:46,880
Speaker 1: but you know, just the you know, the discussion revolves

2651
02:19:46,920 --> 02:19:50,640
Speaker 1: around how many bears can uh die and can we

2652
02:19:50,959 --> 02:19:55,080
Speaker 1: still uh you know, have a sustainable, healthy population as

2653
02:19:55,120 --> 02:19:57,440
Speaker 1: well as the potential to be connected, which is a

2654
02:19:57,520 --> 02:20:00,880
Speaker 1: very important part of so many species lar scale biologies,

2655
02:20:00,920 --> 02:20:03,800
Speaker 1: that are they connected to other populations. And I think

2656
02:20:03,879 --> 02:20:05,520
Speaker 1: it kind of we can kind of whittle it right

2657
02:20:05,560 --> 02:20:08,600
Speaker 1: down to the basic question of what are we willing

2658
02:20:08,680 --> 02:20:12,320
Speaker 1: to lose? Are we willing to lose grizzly bears from

2659
02:20:12,360 --> 02:20:15,680
Speaker 1: our landscapes because we jump the gun on something or

2660
02:20:15,840 --> 02:20:19,120
Speaker 1: we or maybe um, we wouldn't lose it, And let's

2661
02:20:19,160 --> 02:20:21,720
Speaker 1: have that discussion too. Maybe there is hunting of bears,

2662
02:20:21,800 --> 02:20:24,200
Speaker 1: and then we can still have all of what we want.

2663
02:20:24,320 --> 02:20:26,840
Speaker 1: We can have a population that's healthy and robust, we

2664
02:20:26,920 --> 02:20:29,560
Speaker 1: can still have some connectivity, and you know that will

2665
02:20:29,600 --> 02:20:32,040
Speaker 1: come up with some creative ways of having tolerance and

2666
02:20:32,080 --> 02:20:34,640
Speaker 1: allowing bears to move across the landscape in these areas.

2667
02:20:35,080 --> 02:20:37,680
Speaker 1: In these areas, we're going to be less tolerant. Um.

2668
02:20:38,520 --> 02:20:42,080
Speaker 1: Those are those aren't biological questions. Those are social questions,

2669
02:20:42,120 --> 02:20:45,800
Speaker 1: the political questions, value societal value questions. That's why you know,

2670
02:20:45,879 --> 02:20:48,080
Speaker 1: sitting here with you and trying to you know, I,

2671
02:20:48,240 --> 02:20:49,920
Speaker 1: like I said, I come come at this with a

2672
02:20:50,000 --> 02:20:52,879
Speaker 1: certain idea and that when I think about grizzly bears

2673
02:20:53,000 --> 02:20:55,760
Speaker 1: or even wolves, I think, you know, I think about

2674
02:20:56,080 --> 02:20:59,640
Speaker 1: the North American model of wildlife conservation. You know, one

2675
02:20:59,680 --> 02:21:01,520
Speaker 1: of the tenants is that we're going to use science

2676
02:21:01,560 --> 02:21:05,280
Speaker 1: and wildlife biology to to kind of meter this all out.

2677
02:21:05,640 --> 02:21:08,200
Speaker 1: And that's going to be the foundational level of how

2678
02:21:08,320 --> 02:21:10,800
Speaker 1: we go about what what can we take off the landscape?

2679
02:21:10,840 --> 02:21:14,000
Speaker 1: What can we you know, what is approachable in terms

2680
02:21:14,040 --> 02:21:17,200
Speaker 1: of both carnivores and ungults and in all game species,

2681
02:21:17,800 --> 02:21:19,520
Speaker 1: you know, and what we say is a game species

2682
02:21:19,520 --> 02:21:22,000
Speaker 1: and what's not um and then you look at like

2683
02:21:22,120 --> 02:21:23,920
Speaker 1: the history of it, and I want to say this

2684
02:21:24,120 --> 02:21:27,160
Speaker 1: and and this is what I when I think about

2685
02:21:27,200 --> 02:21:29,960
Speaker 1: that modelo conservation, I want to say that the application

2686
02:21:30,120 --> 02:21:33,440
Speaker 1: of those ideas, those tenants, however, they may change over time.

2687
02:21:33,480 --> 02:21:35,120
Speaker 1: And I would argue that some of them need to

2688
02:21:35,959 --> 02:21:39,160
Speaker 1: um need to be updated. But however they change over time.

2689
02:21:39,240 --> 02:21:42,640
Speaker 1: The application of these value this value system, however, it

2690
02:21:42,720 --> 02:21:46,520
Speaker 1: will you know, morph The core tenants have been good

2691
02:21:46,640 --> 02:21:49,800
Speaker 1: for elk, they've been good for turkeys, they've been good

2692
02:21:49,879 --> 02:21:53,880
Speaker 1: for deer um and so the application of those same

2693
02:21:54,000 --> 02:21:58,119
Speaker 1: ideas to carnivores seems to me to be logical. Now,

2694
02:21:58,680 --> 02:22:02,040
Speaker 1: that's that's only the starting point from my thought process.

2695
02:22:02,120 --> 02:22:03,880
Speaker 1: And then talking to you, what I'm trying to do is,

2696
02:22:04,520 --> 02:22:06,960
Speaker 1: you know, knock holes in that and understand where that

2697
02:22:07,160 --> 02:22:11,480
Speaker 1: maybe isn't an apple's apples comparison, and given where we

2698
02:22:11,560 --> 02:22:13,760
Speaker 1: are as a society, it's not as easy as that.

2699
02:22:13,840 --> 02:22:16,360
Speaker 1: I know. Yeah, well, if we just look at the

2700
02:22:16,440 --> 02:22:19,280
Speaker 1: history of carnival recovery here, it hasn't been the North

2701
02:22:19,320 --> 02:22:22,600
Speaker 1: American model that has saved them. Let's saved them is

2702
02:22:22,800 --> 02:22:25,640
Speaker 1: the Endangered Species Act, right, and then we can we

2703
02:22:25,720 --> 02:22:27,640
Speaker 1: can point to other things like the Clean Air and

2704
02:22:27,680 --> 02:22:31,920
Speaker 1: Water Act. I mean, having healthy ecosystems, having protections where

2705
02:22:31,959 --> 02:22:35,360
Speaker 1: they weren't being hunted. That's what was good for carnivores. Now,

2706
02:22:35,560 --> 02:22:39,160
Speaker 1: whether that that change their future is a different question

2707
02:22:39,280 --> 02:22:43,720
Speaker 1: because so and I think that's where you kind of

2708
02:22:43,760 --> 02:22:46,920
Speaker 1: alluded to this. There's some papers that have been published,

2709
02:22:47,640 --> 02:22:51,160
Speaker 1: uh more of a philosophical approach to the North American

2710
02:22:51,200 --> 02:22:53,400
Speaker 1: model conservation, why it's flawed, why it needs to change.

2711
02:22:53,440 --> 02:22:56,760
Speaker 1: There's some great stuff out there. Um, I think those

2712
02:22:57,120 --> 02:23:02,320
Speaker 1: arguments have indicated in and and try to help people

2713
02:23:02,400 --> 02:23:05,280
Speaker 1: understand that, Yes, that model has worked really well for

2714
02:23:05,360 --> 02:23:07,680
Speaker 1: so many species and is still a great baseline for

2715
02:23:07,800 --> 02:23:11,360
Speaker 1: many agencies to operate under who are charged with that

2716
02:23:11,480 --> 02:23:15,760
Speaker 1: public trust of wildlife. Um. But let's not forget the

2717
02:23:15,840 --> 02:23:18,920
Speaker 1: significant role of other things outside of that model that

2718
02:23:19,000 --> 02:23:21,880
Speaker 1: have been a key role of conservation. That kind of

2719
02:23:21,920 --> 02:23:23,600
Speaker 1: comes back to this idea you and I were talking

2720
02:23:23,600 --> 02:23:27,680
Speaker 1: about before, is you know, should other stakeholders get by

2721
02:23:27,760 --> 02:23:29,720
Speaker 1: in and helping make decisions. And that's where I do

2722
02:23:29,879 --> 02:23:31,879
Speaker 1: think we have an opportunity to modernize, and we are

2723
02:23:31,959 --> 02:23:35,800
Speaker 1: in many ways modernizing how we move forward with managing wildlife,

2724
02:23:35,840 --> 02:23:38,800
Speaker 1: and I think with that will come tough conversations between

2725
02:23:38,879 --> 02:23:42,480
Speaker 1: people of different views about hunting to come together and say, Okay,

2726
02:23:42,560 --> 02:23:45,720
Speaker 1: I don't agree with carnivore hunting, or I do agree

2727
02:23:45,760 --> 02:23:47,840
Speaker 1: with it, or I think it should be done this

2728
02:23:47,920 --> 02:23:50,000
Speaker 1: way or shouldn't be done. All those are very challenging

2729
02:23:50,040 --> 02:23:52,000
Speaker 1: discussions to have to get everyone at the table, but

2730
02:23:52,040 --> 02:23:57,200
Speaker 1: they're necessary ones, um, and I think you know they

2731
02:23:57,240 --> 02:24:00,400
Speaker 1: won't be easy and there aren't obvious answers, but the

2732
02:24:00,520 --> 02:24:03,000
Speaker 1: discussions have to happen, and people need to come to

2733
02:24:03,080 --> 02:24:06,840
Speaker 1: the table willing to give up something but also fight

2734
02:24:06,920 --> 02:24:08,880
Speaker 1: for something that they think is important. Sure, And I

2735
02:24:08,920 --> 02:24:11,080
Speaker 1: think that's a huge part of this conversation too, because

2736
02:24:11,080 --> 02:24:13,720
Speaker 1: I come to this not as a person I've said

2737
02:24:13,760 --> 02:24:15,240
Speaker 1: this in the past, not as a person who desires

2738
02:24:15,280 --> 02:24:17,160
Speaker 1: to shoot a wolf. I don't desire to shoot a

2739
02:24:17,160 --> 02:24:20,080
Speaker 1: grizzly bear. Um, I don't. Necessary Well, I kind of

2740
02:24:20,120 --> 02:24:21,720
Speaker 1: desire to shoot a mountain line because I can eat

2741
02:24:21,720 --> 02:24:23,680
Speaker 1: it and it's it's pretty tasty. I've had it many times,

2742
02:24:23,800 --> 02:24:26,280
Speaker 1: never killed one, but I've eaten it many many times.

2743
02:24:27,040 --> 02:24:29,280
Speaker 1: And so as my value system kind of shifts through

2744
02:24:29,400 --> 02:24:31,760
Speaker 1: these ideas, I'm not it's not that I have a

2745
02:24:31,840 --> 02:24:34,480
Speaker 1: desire to hunt wolves. I have a desire to come

2746
02:24:34,560 --> 02:24:39,120
Speaker 1: to a place where both sidedly, politically and biologically, we

2747
02:24:39,240 --> 02:24:42,440
Speaker 1: can all make it the right decision based on the

2748
02:24:42,560 --> 02:24:47,120
Speaker 1: right evidence. As we know it's in every every biological

2749
02:24:47,160 --> 02:24:49,200
Speaker 1: decision here is imperfect because we don't know enough. You

2750
02:24:49,320 --> 02:24:51,960
Speaker 1: never will. So that's how I think of it. I'm

2751
02:24:52,000 --> 02:24:54,360
Speaker 1: not saying, God damn it. I want to be able

2752
02:24:54,400 --> 02:24:56,440
Speaker 1: to my kids to hunt wolves and my kids to

2753
02:24:56,520 --> 02:24:58,560
Speaker 1: hunt grizzly bears. They've got to be able to do that,

2754
02:24:58,800 --> 02:25:03,200
Speaker 1: and I'm gonna fight for I want the hunting because

2755
02:25:03,200 --> 02:25:05,440
Speaker 1: I think this ultimately what gets hunters and me as

2756
02:25:05,440 --> 02:25:09,600
Speaker 1: a as somebody who really cares about the community further along. Anyway,

2757
02:25:09,840 --> 02:25:14,400
Speaker 1: if we're able to independently prove look, you know, rather

2758
02:25:14,959 --> 02:25:16,680
Speaker 1: what I want or don't want. If if if you

2759
02:25:16,840 --> 02:25:20,680
Speaker 1: as a biology can independently prove hunting applied in this

2760
02:25:20,840 --> 02:25:25,200
Speaker 1: fashion is of positive, a long lasting positive. And it's

2761
02:25:25,200 --> 02:25:27,959
Speaker 1: better for me because it's because it's a more sound

2762
02:25:28,680 --> 02:25:32,119
Speaker 1: way to make that decision. Um. And so that's that's

2763
02:25:32,120 --> 02:25:34,240
Speaker 1: where I love the idea and I and I do

2764
02:25:34,440 --> 02:25:36,960
Speaker 1: think the limit we have is with science is that

2765
02:25:37,720 --> 02:25:41,880
Speaker 1: it provides a pathway to a certain point. It provides uh,

2766
02:25:42,080 --> 02:25:45,480
Speaker 1: factual information about how a system might be operating with

2767
02:25:46,000 --> 02:25:49,160
Speaker 1: predator and prey for example, UM, but it reaches a

2768
02:25:49,240 --> 02:25:53,520
Speaker 1: point where beyond that it can no longer provide the guidance.

2769
02:25:54,000 --> 02:25:55,760
Speaker 1: And that's why it is only one part of the

2770
02:25:55,840 --> 02:25:58,640
Speaker 1: tenant of the North American modeling and based on scientific data.

2771
02:25:58,720 --> 02:26:00,920
Speaker 1: And you could argue that it's not applied as much

2772
02:26:00,920 --> 02:26:05,160
Speaker 1: as it should uh and and um, but you can

2773
02:26:05,240 --> 02:26:07,200
Speaker 1: argue that in many cases that it is applied as

2774
02:26:07,240 --> 02:26:10,360
Speaker 1: it is uh necessary to apply and adequately enough, so

2775
02:26:11,120 --> 02:26:13,400
Speaker 1: and and it then it does come down to what

2776
02:26:13,800 --> 02:26:16,200
Speaker 1: does society want? What do they we choose to do,

2777
02:26:16,400 --> 02:26:19,320
Speaker 1: And then your argument to use science to defend for

2778
02:26:19,320 --> 02:26:22,360
Speaker 1: a certain action kind of goes to the side. And

2779
02:26:22,480 --> 02:26:24,680
Speaker 1: so we just have to be cognizant of the fact

2780
02:26:24,720 --> 02:26:27,480
Speaker 1: that the job as science is to just provide um

2781
02:26:27,640 --> 02:26:31,160
Speaker 1: an understanding, a better understanding that then provides sort of

2782
02:26:31,200 --> 02:26:34,119
Speaker 1: a benchmark by which someone, then a society can decide

2783
02:26:34,160 --> 02:26:36,040
Speaker 1: and come together, what are our values? What do we

2784
02:26:36,080 --> 02:26:39,560
Speaker 1: want to see? You know, you know some believe I

2785
02:26:39,959 --> 02:26:41,920
Speaker 1: believe this as well, that it would be nice to

2786
02:26:42,040 --> 02:26:44,880
Speaker 1: see um because and again this comes down to, I

2787
02:26:44,920 --> 02:26:48,080
Speaker 1: think the misperception about how carnivores are on the landscape,

2788
02:26:48,120 --> 02:26:51,160
Speaker 1: bowls and cougars, and you often hear you see this

2789
02:26:51,240 --> 02:26:54,039
Speaker 1: all the time on social media posts, even some prominent

2790
02:26:54,120 --> 02:26:56,160
Speaker 1: celebrity hunters that you know, I have a lot of

2791
02:26:56,200 --> 02:26:57,720
Speaker 1: respect for. You see the comments where you know, I

2792
02:26:57,760 --> 02:26:59,520
Speaker 1: show a picture them with a dead wolf or a

2793
02:26:59,560 --> 02:27:03,760
Speaker 1: dead coup here, and you're comments like, uh, you know,

2794
02:27:03,800 --> 02:27:06,800
Speaker 1: one less dear killer like doing your part and and

2795
02:27:06,920 --> 02:27:09,640
Speaker 1: it would be nice to see a greater segment of

2796
02:27:09,680 --> 02:27:14,480
Speaker 1: the hunting community come to appreciate, um, the carnivores role

2797
02:27:14,520 --> 02:27:17,000
Speaker 1: and their importance in being on the landscape. And and

2798
02:27:17,280 --> 02:27:19,240
Speaker 1: and I think you are seeing that I've heard. And

2799
02:27:19,320 --> 02:27:22,680
Speaker 1: I think more and more we are learning that you know,

2800
02:27:22,760 --> 02:27:25,360
Speaker 1: And we've now lived in this great an ecosystem for

2801
02:27:25,520 --> 02:27:29,080
Speaker 1: a quarter of a century with intact, robust carnival population

2802
02:27:29,160 --> 02:27:32,120
Speaker 1: in the sun rises every day, and we still get

2803
02:27:32,160 --> 02:27:35,359
Speaker 1: our elk tags filled and have wonderful experience on the landscape.

2804
02:27:35,440 --> 02:27:38,920
Speaker 1: And um, again, I think we can have a little

2805
02:27:38,959 --> 02:27:41,360
Speaker 1: bit of everything. Yeah, and I think we've had Dan

2806
02:27:41,440 --> 02:27:45,760
Speaker 1: flores on a day. He talks about cuts in much

2807
02:27:45,800 --> 02:27:50,959
Speaker 1: the same fashion. Um. And again, like nature abhors a vacuum,

2808
02:27:51,280 --> 02:27:55,000
Speaker 1: and so this carnivorous need, this this trophic need to

2809
02:27:55,120 --> 02:27:57,880
Speaker 1: kind of to balance it, you know, an ecosystem in

2810
02:27:57,959 --> 02:28:00,400
Speaker 1: that way is always there for me. And I think

2811
02:28:01,240 --> 02:28:02,880
Speaker 1: if anybody cares what I have to say, But like

2812
02:28:02,879 --> 02:28:05,039
Speaker 1: the way I try to think, and I've evolved as

2813
02:28:05,080 --> 02:28:08,160
Speaker 1: a hunter, and I would articulate like the voice says,

2814
02:28:08,200 --> 02:28:10,160
Speaker 1: like what are what's your job as a hunter? You know,

2815
02:28:10,280 --> 02:28:12,440
Speaker 1: what do you what do you think is the value

2816
02:28:12,480 --> 02:28:15,640
Speaker 1: you provide? Personally, or what's the philosophy that you moved

2817
02:28:15,680 --> 02:28:17,560
Speaker 1: through the world with when you're out looking for an animal,

2818
02:28:18,560 --> 02:28:22,000
Speaker 1: And and increasingly I think of like I'm here for

2819
02:28:22,200 --> 02:28:27,000
Speaker 1: ecological health, Like I'm here for I need to understand biodiversity.

2820
02:28:27,040 --> 02:28:30,480
Speaker 1: I need to understand like predation. I need to understand

2821
02:28:30,480 --> 02:28:32,840
Speaker 1: all these things because if I can be an agent

2822
02:28:32,959 --> 02:28:35,280
Speaker 1: for the health of this ecosystem that I live in

2823
02:28:35,400 --> 02:28:37,800
Speaker 1: and care about so much about, there'll be so many

2824
02:28:37,879 --> 02:28:41,080
Speaker 1: other things that are benefits from that that I maybe

2825
02:28:41,120 --> 02:28:43,000
Speaker 1: I'm not gonna see if I don't care about the

2826
02:28:43,200 --> 02:28:45,240
Speaker 1: entire picture. If I'm just like I'm gonna go over

2827
02:28:45,320 --> 02:28:47,120
Speaker 1: that Elk lives, I'm gonna shoot it, I'm gonna eat it.

2828
02:28:47,160 --> 02:28:50,320
Speaker 1: I'm gonna celebrate the meat itself. I'm gonna celebrate essentially

2829
02:28:50,400 --> 02:28:54,039
Speaker 1: like the game, like quality of hunting, the adventure, the challenge,

2830
02:28:57,360 --> 02:29:00,040
Speaker 1: all those parts are are all things that I and

2831
02:29:00,200 --> 02:29:04,200
Speaker 1: used to kind of paint the picture. But when it

2832
02:29:04,280 --> 02:29:06,760
Speaker 1: comes down to like what is my purpose, my purpose

2833
02:29:07,040 --> 02:29:10,640
Speaker 1: in to the world for hunting? Like and I also

2834
02:29:10,760 --> 02:29:14,080
Speaker 1: often think people are asking anti hunters and non hunters

2835
02:29:14,080 --> 02:29:16,880
Speaker 1: are asking why is hunting good for society? Or you

2836
02:29:17,080 --> 02:29:19,960
Speaker 1: need to take society off why is hunting good? And

2837
02:29:20,000 --> 02:29:22,120
Speaker 1: if you can answer that question, like me, as a hunter,

2838
02:29:22,360 --> 02:29:24,800
Speaker 1: I care about the health of an ecosystem. And if

2839
02:29:24,879 --> 02:29:27,800
Speaker 1: every hunter kind of started to adopt this thinking, then

2840
02:29:27,879 --> 02:29:30,560
Speaker 1: we would have a bunch of agents of these ecosystems

2841
02:29:30,600 --> 02:29:32,640
Speaker 1: going out and trying to understand it. And I think

2842
02:29:32,680 --> 02:29:36,000
Speaker 1: we would have more of what we more of what

2843
02:29:36,160 --> 02:29:39,040
Speaker 1: we all really enjoy as a hunter being out there

2844
02:29:39,080 --> 02:29:41,320
Speaker 1: on the landscape. We'd have that in more places. And

2845
02:29:42,080 --> 02:29:46,360
Speaker 1: um and you know, understanding that the choices we make

2846
02:29:46,760 --> 02:29:49,800
Speaker 1: as a hunter ripple throughout. I mean, just think about

2847
02:29:49,840 --> 02:29:52,520
Speaker 1: I think about how many few beef cattle I've eaten

2848
02:29:53,240 --> 02:29:55,200
Speaker 1: over the lat and it's not that I love that,

2849
02:29:56,520 --> 02:30:00,480
Speaker 1: and but I just think of that small part of

2850
02:30:00,600 --> 02:30:03,840
Speaker 1: the last twenty years of my diet, in my connection

2851
02:30:03,879 --> 02:30:07,000
Speaker 1: to my food that as a hunter, that has linked

2852
02:30:07,080 --> 02:30:09,240
Speaker 1: me to wanting to have a landscape like this, but

2853
02:30:09,360 --> 02:30:11,840
Speaker 1: also also wanting to see that wolf and cooker track

2854
02:30:11,879 --> 02:30:16,039
Speaker 1: out there. And and you know, so it goes beyond

2855
02:30:16,560 --> 02:30:19,320
Speaker 1: all those really important things that I also identify with

2856
02:30:19,400 --> 02:30:21,760
Speaker 1: that you just listed off of. You know, what why

2857
02:30:21,879 --> 02:30:24,760
Speaker 1: you hunt and why it's important to you. Um, And

2858
02:30:24,879 --> 02:30:28,000
Speaker 1: it goes beyond that, I mean, And and we all

2859
02:30:28,080 --> 02:30:30,320
Speaker 1: make choices every day in life to do things, whether

2860
02:30:30,360 --> 02:30:34,680
Speaker 1: it's to own a phone, uh, drive a car, buy

2861
02:30:34,760 --> 02:30:37,440
Speaker 1: meat from a store, hunt meat from the land, don't

2862
02:30:37,440 --> 02:30:40,120
Speaker 1: eat meat at all. And they all are easy to

2863
02:30:40,280 --> 02:30:43,920
Speaker 1: justify from your perspective, And but they can all have

2864
02:30:44,800 --> 02:30:48,920
Speaker 1: um reasons to argue and it too and so um yeah,

2865
02:30:49,000 --> 02:30:51,480
Speaker 1: I mean I'm simple, especially out of here. No, not

2866
02:30:51,640 --> 02:30:57,040
Speaker 1: at all and and um so yeah, I mean where

2867
02:30:57,080 --> 02:30:59,199
Speaker 1: does that leave us? It leaves us with this idea

2868
02:30:59,320 --> 02:31:04,440
Speaker 1: that my perspective. If the better we understand how the

2869
02:31:04,640 --> 02:31:08,680
Speaker 1: role of predation fits on these landscapes from natural carnivores, um,

2870
02:31:08,879 --> 02:31:11,320
Speaker 1: those of us that are hunters who can appreciate and

2871
02:31:11,400 --> 02:31:15,640
Speaker 1: identify and maybe truly admire that element of those carnivores,

2872
02:31:15,680 --> 02:31:17,880
Speaker 1: because there's something in that that we are either jealous

2873
02:31:17,959 --> 02:31:22,480
Speaker 1: of or in or enamored with or admire. Um, the

2874
02:31:22,560 --> 02:31:25,320
Speaker 1: better we understand that and those truths, I think, the um,

2875
02:31:25,720 --> 02:31:27,560
Speaker 1: you know, the better we will fit in as humans

2876
02:31:27,600 --> 02:31:31,400
Speaker 1: on that same landscape and and have more of those landscapes. Yeah.

2877
02:31:31,480 --> 02:31:33,760
Speaker 1: And as we continue like these conversations are important to

2878
02:31:33,840 --> 02:31:36,560
Speaker 1: unpack these things and continue to run at these hard

2879
02:31:36,640 --> 02:31:39,400
Speaker 1: issues and say like I'm not gonna and I'm gonna

2880
02:31:40,040 --> 02:31:42,640
Speaker 1: instead of avoiding this because I would tell you I'm

2881
02:31:42,879 --> 02:31:44,440
Speaker 1: I'm not going to go out there and shoot a wolf,

2882
02:31:44,480 --> 02:31:48,440
Speaker 1: so what do I care? Um, but having the kind

2883
02:31:48,480 --> 02:31:51,040
Speaker 1: of you know, worldview where you're like, I want to

2884
02:31:51,120 --> 02:31:53,160
Speaker 1: kind of tackle these tougher issues because they do inform

2885
02:31:53,240 --> 02:31:55,560
Speaker 1: the rest of the thing I love to do. Um,

2886
02:31:56,400 --> 02:31:58,760
Speaker 1: you know, and then not again, I come back to this,

2887
02:31:58,840 --> 02:32:02,240
Speaker 1: I'll continue to I like to challenge my own I

2888
02:32:02,280 --> 02:32:04,800
Speaker 1: think the most interesting conversations are one that challenge your

2889
02:32:04,840 --> 02:32:08,760
Speaker 1: own assumptions or your own bubble think, or you're like

2890
02:32:08,840 --> 02:32:10,800
Speaker 1: the assumptions of all the people around you that tell

2891
02:32:10,879 --> 02:32:12,720
Speaker 1: you that, you know, in this case, wolves are bad.

2892
02:32:13,600 --> 02:32:16,080
Speaker 1: Wolves are bad, and I agree with you. I've seen

2893
02:32:16,120 --> 02:32:19,520
Speaker 1: a lot of hunters in my purviews say like the

2894
02:32:19,560 --> 02:32:21,160
Speaker 1: grip and grow with the wolf is to say like,

2895
02:32:21,640 --> 02:32:24,920
Speaker 1: you're welcome, we did it, we did it together. There's

2896
02:32:24,959 --> 02:32:28,680
Speaker 1: three more. You're like, yeah, maybe, But that all that

2897
02:32:28,760 --> 02:32:31,160
Speaker 1: does is bolster the argument of the anti hunter who

2898
02:32:31,160 --> 02:32:33,360
Speaker 1: says you're just out there because you're killing wolves because

2899
02:32:33,400 --> 02:32:35,360
Speaker 1: you want more. Dear, You're not, You're not doing that

2900
02:32:35,640 --> 02:32:39,480
Speaker 1: for conservation, wildlife management. And I've always struggled with the

2901
02:32:41,040 --> 02:32:42,560
Speaker 1: with the idea and this is my you know, I

2902
02:32:42,600 --> 02:32:45,960
Speaker 1: think any hunter can relate to this, that internal debate

2903
02:32:46,080 --> 02:32:48,360
Speaker 1: of you know, killing an animal, taking life of an animal,

2904
02:32:48,400 --> 02:32:49,960
Speaker 1: and when you come to that choice of the hunt,

2905
02:32:50,000 --> 02:32:53,000
Speaker 1: when you do that, it's always that internal struggle for many,

2906
02:32:53,160 --> 02:32:56,760
Speaker 1: myself included, and um, but you know, and you had

2907
02:32:56,800 --> 02:32:59,120
Speaker 1: this such a deep admiration in sense of wanting to

2908
02:32:59,760 --> 02:33:02,080
Speaker 1: make sure that these animals are out there in the landscape.

2909
02:33:02,240 --> 02:33:06,160
Speaker 1: I'm always sort of struck by how many people have

2910
02:33:06,480 --> 02:33:10,360
Speaker 1: an hatred for a wild animal. I mean, I guess

2911
02:33:10,400 --> 02:33:12,880
Speaker 1: I have just never experienced that or can't comprehend that

2912
02:33:13,040 --> 02:33:15,520
Speaker 1: of how you can love one sort of animal then

2913
02:33:15,560 --> 02:33:17,480
Speaker 1: see another and I have an actual hatred in your

2914
02:33:17,520 --> 02:33:20,120
Speaker 1: heart for it. Um. I struggle with that and trying

2915
02:33:20,120 --> 02:33:23,080
Speaker 1: to understand where that comes from, and deep it is,

2916
02:33:23,160 --> 02:33:26,480
Speaker 1: deep seated. And um you know, because you know someone

2917
02:33:26,920 --> 02:33:28,960
Speaker 1: could argue to me, while you you kill an elk,

2918
02:33:29,080 --> 02:33:30,879
Speaker 1: you must not like them, or you must be okay

2919
02:33:30,959 --> 02:33:34,440
Speaker 1: with just taking the life, and um, you know it

2920
02:33:34,480 --> 02:33:36,360
Speaker 1: could be further from the truth. And you know that's

2921
02:33:36,400 --> 02:33:38,280
Speaker 1: always hard to defend to someone that hasn't gone through

2922
02:33:38,320 --> 02:33:41,320
Speaker 1: that or haven't had that experience. But um, it is

2923
02:33:41,400 --> 02:33:45,240
Speaker 1: interesting that there are some people that feel hatred in

2924
02:33:45,320 --> 02:33:48,280
Speaker 1: their hearts towards a wild animal that's just out there

2925
02:33:48,320 --> 02:33:50,360
Speaker 1: doing its things well that you do for a job,

2926
02:33:51,040 --> 02:33:54,240
Speaker 1: Thank you for a job. There's people that have unhealthy

2927
02:33:54,760 --> 02:33:59,240
Speaker 1: admiration and love for wolves. Yeah, and it totally skip over.

2928
02:34:00,800 --> 02:34:03,320
Speaker 1: Here's the dichotomy I think it's worth talking about. There's

2929
02:34:03,959 --> 02:34:06,680
Speaker 1: a lot of people on the environmentalist protectionist side that

2930
02:34:06,840 --> 02:34:12,320
Speaker 1: have this overwhelming love for these animals and anthropomorphize them

2931
02:34:12,879 --> 02:34:15,120
Speaker 1: and make them out to be something they're not. And

2932
02:34:15,200 --> 02:34:18,760
Speaker 1: then conversely to that, you have hunters or some of

2933
02:34:18,840 --> 02:34:22,879
Speaker 1: my friends where like nature is Metal, where they're like wait, wait, wait,

2934
02:34:23,240 --> 02:34:27,360
Speaker 1: look how look how awful they are, or look at

2935
02:34:27,440 --> 02:34:31,160
Speaker 1: how bloodthirsty they are, or look at how what they

2936
02:34:31,280 --> 02:34:33,279
Speaker 1: really do. I mean, you think you love an animal

2937
02:34:33,320 --> 02:34:36,120
Speaker 1: that would rip an elk out of, you know, the

2938
02:34:36,200 --> 02:34:41,320
Speaker 1: birthing canal of a cow and eat it alive. Essentially, Um,

2939
02:34:41,480 --> 02:34:44,920
Speaker 1: you love that? Um I hate that because it's due

2940
02:34:44,959 --> 02:34:47,320
Speaker 1: in that to an animal that I hunt. Somewhere in

2941
02:34:47,400 --> 02:34:50,040
Speaker 1: the middle of that is the truth, right somewhere in

2942
02:34:50,080 --> 02:34:52,119
Speaker 1: the middle of that is the truth and an understanding

2943
02:34:52,120 --> 02:34:54,320
Speaker 1: the animal, which you help people with just in this

2944
02:34:54,440 --> 02:34:58,080
Speaker 1: conversation is a beginning of of not having either of

2945
02:34:58,200 --> 02:35:02,040
Speaker 1: those unhealthy views, you know. And that's what happens when

2946
02:35:02,080 --> 02:35:05,520
Speaker 1: we apply human emotion and judgment and value onto the

2947
02:35:05,760 --> 02:35:09,320
Speaker 1: lives of wild animals. I mean wolves, you know, simply put,

2948
02:35:09,360 --> 02:35:11,560
Speaker 1: are not good or bad. They do what they do

2949
02:35:12,000 --> 02:35:14,520
Speaker 1: because they've been doing for thousands of years and that's

2950
02:35:15,480 --> 02:35:19,160
Speaker 1: how they've been successful. And um. And you know, as

2951
02:35:19,200 --> 02:35:21,080
Speaker 1: soon as we come in there with some judgment of

2952
02:35:21,280 --> 02:35:24,360
Speaker 1: this is good or this is bad. Uh, that's when

2953
02:35:24,920 --> 02:35:29,480
Speaker 1: you know, the human perspective will drive how we then

2954
02:35:29,640 --> 02:35:32,840
Speaker 1: choose to live or not live with these animals. Sou

2955
02:35:33,400 --> 02:35:36,320
Speaker 1: But I you know, I do think as we uh,

2956
02:35:37,280 --> 02:35:40,560
Speaker 1: look at what we almost lost for wildlife, for a

2957
02:35:40,600 --> 02:35:46,000
Speaker 1: wildlife heritage, habitat landscapes, and what we're losing every day. Um,

2958
02:35:47,080 --> 02:35:49,840
Speaker 1: if we can remind ourselves when we get a place

2959
02:35:49,879 --> 02:35:53,800
Speaker 1: like a yellow Stone of that, you know, wouldn't it

2960
02:35:53,800 --> 02:35:55,400
Speaker 1: be great to have more of this or this is

2961
02:35:55,480 --> 02:35:57,560
Speaker 1: what it used to be in many places and and

2962
02:35:58,200 --> 02:36:00,320
Speaker 1: and appreciate that and learned from that in and maybe

2963
02:36:00,360 --> 02:36:04,199
Speaker 1: apply that to you know, reaching out beyond the boundary

2964
02:36:04,240 --> 02:36:07,120
Speaker 1: of a protective preserve like Yellowstone and going onto, for example,

2965
02:36:07,160 --> 02:36:09,640
Speaker 1: our public lands where you know, I look across here,

2966
02:36:10,640 --> 02:36:13,240
Speaker 1: across the boundary Yelsta National Park and the Custer Gallatin

2967
02:36:13,320 --> 02:36:15,760
Speaker 1: Forest up there, and I can see the very spot

2968
02:36:15,840 --> 02:36:19,199
Speaker 1: this fall where I was fortunate during our archery season

2969
02:36:19,280 --> 02:36:22,320
Speaker 1: to to just to get a magnificent, beautiful bowl in

2970
02:36:22,440 --> 02:36:26,240
Speaker 1: my backyard on public land, and and I just it

2971
02:36:26,360 --> 02:36:29,040
Speaker 1: was this very emotional thing for me to look down

2972
02:36:29,160 --> 02:36:31,240
Speaker 1: on this landscape I've spent my career as a biologist,

2973
02:36:31,240 --> 02:36:34,240
Speaker 1: look around someone that's passionate about hunting, feeding, my family

2974
02:36:34,320 --> 02:36:37,200
Speaker 1: being part of that community as well, uh and having

2975
02:36:37,280 --> 02:36:39,640
Speaker 1: it all pulled together, and just feel how lucky that

2976
02:36:39,760 --> 02:36:43,160
Speaker 1: I'm living in a time when um, I can experience

2977
02:36:43,200 --> 02:36:46,800
Speaker 1: all this uh in one in one place, because there's

2978
02:36:46,840 --> 02:36:49,240
Speaker 1: so many places where that can't and that's not even

2979
02:36:49,280 --> 02:36:51,320
Speaker 1: possible in oh my gosh. Yeah. And if if in

2980
02:36:51,560 --> 02:36:54,440
Speaker 1: humanity and hundreds of years from now we moved past

2981
02:36:54,520 --> 02:36:56,680
Speaker 1: this thing that you and I like to do, then

2982
02:36:56,720 --> 02:36:59,120
Speaker 1: at least we were here. At least we were the

2983
02:36:59,200 --> 02:37:01,680
Speaker 1: last vestige of of enjoying it. The one day it

2984
02:37:01,720 --> 02:37:03,400
Speaker 1: will be the young kids. Instead of dreaming about the

2985
02:37:03,440 --> 02:37:09,320
Speaker 1: places scene, they'll be dreaming about we gotta get through.

2986
02:37:11,120 --> 02:37:14,879
Speaker 1: They won't be dreaing ab back in Clinton era. Um well,

2987
02:37:14,959 --> 02:37:17,080
Speaker 1: thanks man, I really appreciate it. Plug your book one

2988
02:37:17,080 --> 02:37:18,960
Speaker 1: more time and tell people when it's coming out and

2989
02:37:19,000 --> 02:37:21,119
Speaker 1: where they can get it. So we have a book

2990
02:37:21,120 --> 02:37:23,800
Speaker 1: coming out called Yellowstone Wolves, Science and Discovery in our

2991
02:37:23,800 --> 02:37:27,480
Speaker 1: world's first national Park, University of Chicago Press. It was

2992
02:37:27,560 --> 02:37:29,920
Speaker 1: a five year effort to pull together twenty five years

2993
02:37:30,080 --> 02:37:34,040
Speaker 1: summary of synthesizing the story of wolves back in Yellowstone.

2994
02:37:34,760 --> 02:37:37,440
Speaker 1: There's we We've tried to write the book so it's

2995
02:37:37,520 --> 02:37:40,600
Speaker 1: very accessible to the lay audience. We've synthesized the science,

2996
02:37:40,680 --> 02:37:44,040
Speaker 1: referenced our per reviewed science publications, but tried to do storytelling.

2997
02:37:44,720 --> 02:37:46,520
Speaker 1: Storytelling is at the heart of so much of what

2998
02:37:46,680 --> 02:37:49,800
Speaker 1: our human cultures do and the value importance, and as scientists,

2999
02:37:49,840 --> 02:37:52,480
Speaker 1: we need to tell our story, tell the wolves story,

3000
02:37:53,040 --> 02:37:58,000
Speaker 1: and we have. The book really encompasses everything from predator prey, genetics, disease,

3001
02:37:58,080 --> 02:38:01,960
Speaker 1: the history of bringing wolf us back, um the human

3002
02:38:02,200 --> 02:38:05,600
Speaker 1: wolf dimension. We even have a wonderful chapter describing sort

3003
02:38:05,640 --> 02:38:09,680
Speaker 1: of the challenges in and of trans boundary management of

3004
02:38:09,680 --> 02:38:13,400
Speaker 1: wolves across a park and in public lands outside the park,

3005
02:38:14,000 --> 02:38:16,560
Speaker 1: bringing a lot of different voices together, men and women

3006
02:38:16,600 --> 02:38:20,119
Speaker 1: that have been involved with the story of of Yellowstone Wolves. Uh,

3007
02:38:20,280 --> 02:38:22,120
Speaker 1: we're very proud of it. We hope a lot of people,

3008
02:38:22,800 --> 02:38:25,720
Speaker 1: uh get their hands on it. It's will be available

3009
02:38:25,760 --> 02:38:30,119
Speaker 1: in November. Um, a very affordable book, whopping thirty five

3010
02:38:30,200 --> 02:38:34,640
Speaker 1: dollars and uh, we're excited for people to hear the story. Yeah,

3011
02:38:34,760 --> 02:38:37,360
Speaker 1: me too. I'm I'm glad to be I guess we

3012
02:38:37,400 --> 02:38:39,360
Speaker 1: could be like signing off from a ridge in the

3013
02:38:39,440 --> 02:38:42,840
Speaker 1: Yellowstone serengetti. Um, but well, thanks for taking me out here.

3014
02:38:42,879 --> 02:38:45,840
Speaker 1: Thank you for including me and what you do every day.

3015
02:38:45,920 --> 02:38:47,920
Speaker 1: And as I tell my wife, I'm going to try

3016
02:38:47,959 --> 02:38:50,360
Speaker 1: to If I podcasting thing don't work out, I'm gonna

3017
02:38:50,400 --> 02:38:52,440
Speaker 1: go back to school. All right now, we'll take you

3018
02:38:52,480 --> 02:38:55,000
Speaker 1: on as a technician next winter. So all right, man, thanks,

3019
02:38:55,080 --> 02:39:05,840
Speaker 1: all right, Thanks Ben, Bye bye. That's it. That's all

3020
02:39:05,840 --> 02:39:08,360
Speaker 1: another episode th HC in the books. Thank you to

3021
02:39:08,480 --> 02:39:11,000
Speaker 1: Dr Dan Staylor. Thank you to everybody at Yellowstone National

3022
02:39:11,040 --> 02:39:13,920
Speaker 1: Park for doing what you're doing. Riding the great outlet

3023
02:39:14,040 --> 02:39:17,640
Speaker 1: for us to have these discussions. They're very important and

3024
02:39:17,760 --> 02:39:21,640
Speaker 1: we will continue to track grizzly bears and h wyoming

3025
02:39:21,680 --> 02:39:25,440
Speaker 1: the Greater Yellstone ecosystem, continue to track wolves in Colorado,

3026
02:39:26,080 --> 02:39:28,200
Speaker 1: and wolves and grizzly bears and everything else here where

3027
02:39:28,240 --> 02:39:32,039
Speaker 1: we live in Montana and across the Rocky Mountain region.

3028
02:39:32,680 --> 02:39:33,920
Speaker 1: But it was fun, man, that was one of my

3029
02:39:33,959 --> 02:39:37,560
Speaker 1: favorite conversations. So hopefully, um, you guys got out of

3030
02:39:37,600 --> 02:39:40,959
Speaker 1: it what I did, which is is simply that predators,

3031
02:39:41,520 --> 02:39:45,720
Speaker 1: apex predators, charismatic megafauna, however you want to call them, um,

3032
02:39:46,520 --> 02:39:49,080
Speaker 1: have a place in our culture for a reason. Right, Phil,

3033
02:39:49,720 --> 02:39:52,000
Speaker 1: That's right, that's it. That's all you had to say.

3034
02:39:52,800 --> 02:39:54,640
Speaker 1: It's a long once. We're gonna keep it short again.

3035
02:39:54,720 --> 02:39:58,680
Speaker 1: Thanks to everybody for sending in your videos, your poems,

3036
02:39:58,760 --> 02:40:02,640
Speaker 1: everything for the Great American Doors Contest. Make sure you

3037
02:40:02,720 --> 02:40:06,560
Speaker 1: go call the switchboard, call your representative. Times running out.

3038
02:40:06,760 --> 02:40:09,240
Speaker 1: This is important and once we get across the line,

3039
02:40:09,240 --> 02:40:13,760
Speaker 1: we can all celebrate together with a nice white claw. Um.

3040
02:40:14,240 --> 02:40:15,800
Speaker 1: And by the bye, Phil, have you had the pure

3041
02:40:15,840 --> 02:40:20,520
Speaker 1: white claw? The unflavored white claws? No, there, that's one

3042
02:40:20,600 --> 02:40:22,840
Speaker 1: I haven't had. They also have these lower calorie run

3043
02:40:23,080 --> 02:40:25,160
Speaker 1: ones that come in different flavors. That I've had the

3044
02:40:25,200 --> 02:40:27,880
Speaker 1: seventy cow ones. Yeah, they got pineapple, they got clement

3045
02:40:28,080 --> 02:40:30,360
Speaker 1: I haven't had those. Are those good? Clementine is good,

3046
02:40:30,840 --> 02:40:34,280
Speaker 1: pineapples are right, pineapple sounds good. The pure one is dogshit.

3047
02:40:34,840 --> 02:40:37,840
Speaker 1: Well sure, it's just like a sparkling water that even

3048
02:40:37,920 --> 02:40:41,200
Speaker 1: if even a little kick, even if one day, which

3049
02:40:41,280 --> 02:40:45,160
Speaker 1: this may never happen, if White Claw sponsors the show,

3050
02:40:47,600 --> 02:40:49,320
Speaker 1: they're not warm. We're not gonna do ads for pure

3051
02:40:50,240 --> 02:40:52,120
Speaker 1: because I drink my White Claw because I want to,

3052
02:40:52,320 --> 02:40:54,120
Speaker 1: I don't. I want to argue with you about the flavors.

3053
02:40:54,440 --> 02:40:56,920
Speaker 1: And if there's no flavor, then what can we argue about?

3054
02:40:56,959 --> 02:40:58,760
Speaker 1: There's nothing to argue. I think I would argue pure

3055
02:40:58,800 --> 02:41:00,840
Speaker 1: as a flavor, and I would say you're not. I

3056
02:41:00,840 --> 02:41:03,520
Speaker 1: would say you're not in any position thinking that no

3057
02:41:03,720 --> 02:41:06,720
Speaker 1: flavor is a flavor. Yes, you're not in a position

3058
02:41:06,760 --> 02:41:11,039
Speaker 1: to be making demands about your non existent White Claw

3059
02:41:11,120 --> 02:41:13,960
Speaker 1: ad campaign. I'm saying, if they eventually come around, they're

3060
02:41:13,959 --> 02:41:16,040
Speaker 1: gonna want to get on board. They'll pay me and

3061
02:41:16,080 --> 02:41:18,440
Speaker 1: they'll be like, it's a full on I probably won't

3062
02:41:18,440 --> 02:41:20,360
Speaker 1: and calling it pure, what's more pure about it? You

3063
02:41:20,400 --> 02:41:23,000
Speaker 1: didn't put the flavor in it Does that make it pure?

3064
02:41:25,000 --> 02:41:28,760
Speaker 1: What should it be called? I don't know. She should

3065
02:41:28,800 --> 02:41:33,520
Speaker 1: be called nothing. What's the flavor? Nothing? Nothing, Seltzer water.

3066
02:41:34,240 --> 02:41:42,480
Speaker 1: They come on, man, white claw, pure my ass? All right?

3067
02:41:42,480 --> 02:41:47,160
Speaker 1: Well next week because I can't go a week without

3068
02:41:47,320 --> 02:42:01,840
Speaker 1: doing right drinking in heaven