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Speaker 1: Oh hey, welcome to the Hunting Collective. To me Ben

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Speaker 1: O'Brien here with Phil the Engineer. Hello, and it's another week,

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Speaker 1: episode eighty six, and this one is a great one.

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Speaker 1: It's about the coyote, or the coyote or the coyote,

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Speaker 1: however you choose to say it. And this came up.

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Speaker 1: This topic came up recently. I mean, the coyote is

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Speaker 1: obviously something we're all interested in, but the topic came

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Speaker 1: up recently around hunters and how they feel about predators.

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Speaker 1: Do we feel like they're competing with us for our

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Speaker 1: beautiful and delicious deer and elk and moose and things

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Speaker 1: like that. So this is perfect have Dan Flores in here.

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Speaker 1: We also had Sam Longdern, Anthony Lakata and Spencer new

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Speaker 1: Art who came from different parts of the world completely

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Speaker 1: messed up where they're actually from, but they came from

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Speaker 1: different parts of our country and so I want to

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Speaker 1: have their perspective on what they thought about coyotes, their

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Speaker 1: experiences and all that stuff. And and before we get gone,

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Speaker 1: speaking of what's been happening in my life, I shot

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Speaker 1: a mule deer last week. It's my first ever resident

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Speaker 1: mule deer in Montana. It was a little bit of

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Speaker 1: interesting story. So next episode, I'm gonna tell you that story.

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Speaker 1: Some people have been asking for me to tell the story.

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Speaker 1: It's a story where I I did simultaneously great at

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Speaker 1: hunting and also terrible, And so stick around for that.

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Speaker 1: Maybe next episode or sometime when I get around to

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Speaker 1: uh swallow my pride and telling you all about it.

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Speaker 1: But for now, it's coo and it's episode eighty six.

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Speaker 1: Let's go. I guess I grew up on an older road,

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Speaker 1: a paredal to the meadows. I always did what I've

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

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

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Speaker 1: And I grew up fast. I guess I grew up.

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Speaker 1: I mean, they have a thousand things inside of my

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Speaker 1: head I wish I ain't seen. And now I just

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Speaker 1: wounded to a real bad dream of being a lack

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Speaker 1: of coming in a part of the steams. But thank

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Speaker 1: you Jack Daniel. Hey everybody, episode eighty six, with the

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Speaker 1: Hunting Collective coming at you from freezing cold bos in Montana,

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Speaker 1: it's like negative degrees out of everybody, very cold October

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Speaker 1: nine below in Belgrade. When I got up this o,

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Speaker 1: my Lord and Heaven fills upper lip is warmer than

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Speaker 1: most preparing preparing. It's filling in nicely. It's filling it nicely.

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Speaker 1: Anthony Cotta, could you please describe fills mustache as it

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Speaker 1: currently sits um. It's it's really gathered steam over the

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Speaker 1: last couple of days and coming to its home. Are

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Speaker 1: you fertilizing it with something? No, it just knew it

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Speaker 1: was being underestimated and it came out fighting. Gary. Gary's

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Speaker 1: good to me. It looks like mini magnum this morning. Yeah,

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Speaker 1: it's you can see it for more than five ft away.

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Speaker 1: Now that's true. I don't want to. I don't want

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Speaker 1: to like try to wipe it off like I did,

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Speaker 1: or like it's something on your lip, man, let's scrub

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Speaker 1: it real harder'll fall off. Well, it's not about the

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Speaker 1: density either. It's very skin toned. It's like, yeah, that's

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Speaker 1: the main problem. Yeah, we've been talking about that super

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Speaker 1: That's that's where it derives its creepiness from it from

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Speaker 1: its from its color. It's like somebody cloned your eyebrow

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Speaker 1: and then put it on top of your lips like that. Yeah,

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Speaker 1: nic third eyebrow. I'll take it mouth brow. Well. I

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Speaker 1: we're joined by Sam Longer. Hey Sam, Hey Ben. How's

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Speaker 1: it going? Oh it's going pretty pretty good? Pretty good?

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Speaker 1: Looking forward to Halloween. Yeah, what are you gonna be?

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Speaker 1: I could well, I guess this will air later. I'm

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Speaker 1: gonna be Yosemite. Sam, that's gonna be. You're gonna shave

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Speaker 1: down those stash bet your ass. You're an innovator. Oh boy,

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Speaker 1: Spencer new Heart, what are you going to be? I

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Speaker 1: don't know if this is going to resonate with everyone,

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Speaker 1: but I'm gonna be a hooter. Right, he's got he's

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Speaker 1: got the beard. I've got the beard. I've got the suspenders,

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Speaker 1: that got the black pants, have got the hat. You're

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Speaker 1: gonna get a lot of questions. I need to explain.

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Speaker 1: I grew up in a small town in southeastern South

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Speaker 1: Dakota where we had one of the biggest hood right

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Speaker 1: populations like in the nation. There we had five colonies

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Speaker 1: within like ten miles of my hometown, and so when

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Speaker 1: I would dress up like a hood right and go

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Speaker 1: out for Halloween, people just thought I was a hood

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Speaker 1: or right. It wasn't like costume people would be like

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Speaker 1: from Jamesville, Maxwell, which one yeah, so we'll see how

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Speaker 1: that goes over. And yeah, if you go up to

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Speaker 1: as lowest town, people will think the exact same thing

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Speaker 1: because they're everywhere up there. But you got to learn

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Speaker 1: how how a lot of Montana's pronounce it, Who do right?

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Speaker 1: Who the right? Who do right? Where I'm from in Maryland, similar,

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Speaker 1: there's a fair modelm here, though in Montana. There's a

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Speaker 1: lot of them here in Montana. It might hit. Don't

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Speaker 1: accidentally stumble into a colony and just stay. I already

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Speaker 1: have close. I was gonna hang out. This is this

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Speaker 1: will you're not breaking any news or after well, I'm

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Speaker 1: breaking the news to to the staff here, I guess please. Yeah, okay,

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Speaker 1: well we've gone over how Seth and I were gonna

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Speaker 1: be Doc Holiday and wider, like a realistic take. It's

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Speaker 1: gonna be fun. That's gone. He's gonna be gone tomorrow.

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Speaker 1: He's not dead times West. Um, he had a beautiful mustache.

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Speaker 1: I'll take your Instagram follows. He was he was following

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Speaker 1: the weather. He's chasing tornadoes and um. But no, so

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Speaker 1: I'm still going to do a cowboy thing, but I'm

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Speaker 1: going to be Doc Calaladay. It's a white cloth themed cowboy. Yes,

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Speaker 1: that takes it. I've got some construction to do tonight. Um,

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Speaker 1: without giving anything away, it's gonna be it's gonna be fun. Yeah, Okay,

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Speaker 1: I'm speechless. Yeah, I'm speech Thank you, thank you for

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Speaker 1: your service film. I'm your Huckleberry flavor. I'm your black chair.

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Speaker 1: I thought of this. I'm your mango. I'm your natural line, which,

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Speaker 1: of course you don't want to do that. That's a

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Speaker 1: terrible disagree, disagree. I'm a natural line man. Oh yeah, sure,

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Speaker 1: are I'm already Are you gonna be um, you're you're

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Speaker 1: we're the only two Well I was gonna say we're

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Speaker 1: only two fathers fills a father. But yeah, I gotta

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Speaker 1: rethink mine. I gotta think that's something I can wear.

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Speaker 1: Um that will still come through with a lot of

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Speaker 1: outer layers. If it's gonna be this cold, that'll work. Um.

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Speaker 1: Were you planning something that was like pretty skimpy. Yes,

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Speaker 1: I usually do the sexy whatever thing. That's kind of

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Speaker 1: my my thing, Like uh, um no my plan. Um.

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Speaker 1: I have to rethinking, honestly, because I was going to

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Speaker 1: be an angry clown, which is kind of a go

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Speaker 1: to for me. It's kind of my thing, Yes, right

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Speaker 1: in my wheelhouse. Angry, so glad you're rethinking that. But

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Speaker 1: I have to film something tomorrow in the makeup just

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Speaker 1: takes like days, so I got to rethink that. Well.

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Speaker 1: I just I just started laughing when I saw that

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Speaker 1: email from Annie that we're all filming and supposed to

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Speaker 1: supposed to look serious for once in a filming thing.

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Speaker 1: I'm like that, that's immediately before the hell the costume party.

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Speaker 1: I'm gonna have a big ridiculous mustache. I'm gonna have

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Speaker 1: to find a way to put white claws into my costume. Yeah,

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Speaker 1: if you want to. You didn't tell ye? What about you?

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Speaker 1: I'm just gonna be a t Rex. You know, there's

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Speaker 1: a big blow up. T Rex is the fans. It's simple,

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Speaker 1: but I find hilarious because I'm definitely funny. I'm definitely

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Speaker 1: gonna be chasing Dot Claude day around whacky with my tail.

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Speaker 1: We needed you, like those time lapses where people chase

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Speaker 1: each other. Yeah, yeah, has anybody been watching the World Series? Spencer?

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Speaker 1: You probably have like baseball? Sports ball fan your sport?

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Speaker 1: You like sports ball? It was a great game last night.

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Speaker 1: I keep getting emails. I got at least one email

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Speaker 1: that says I look like Adam Eaton m burn. What

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Speaker 1: a loser. It's a burn for him. I don't know

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Speaker 1: who that is. Jacob Holtzford and said, how has been

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Speaker 1: able to both be in Montana bagging Muley Bucks and

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Speaker 1: in Houston banging Dingers. That's not It could be worse.

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Speaker 1: I would love to be on and playing in the

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Speaker 1: World Series right now, playing in the World Series. Um,

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Speaker 1: we're not supposed to talk about sports, right yeahs not here.

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Speaker 1: We're supposed to be Steves listening to this probably got

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Speaker 1: Mike Son at the table. He might he might. Anyway,

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Speaker 1: it is a good World Series. Last night, game tonight,

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Speaker 1: Game seven. Stoked for to Game Seven's always good, It's

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Speaker 1: always good. I'm looking for the Gnats to win. Tell

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Speaker 1: me what happens. Yeah, you're not gonna be into it,

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Speaker 1: all right. We need to record to scenarios one where

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Speaker 1: we predict the Nationals win. Don't predict the Astra tonight.

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Speaker 1: Phil can cut it up, Okay, Phil, Astros are definitely

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Speaker 1: gonna win. I'm thinking probably four to two. Take a

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Speaker 1: quick break here, Nationals definitely gonna win, thinking probably three

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Speaker 1: to one or something like that. So either you like,

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Speaker 1: I'm a big, big Nationals fan. Okay, I'll make that

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Speaker 1: flawless cut that up for me. Thanks man. It's really

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Speaker 1: this is the podcasts become more magical since Phil has joined.

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Speaker 1: There's a lot of things that we can Can you

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Speaker 1: just put any sound effect right here? Boom, yep, I'm

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Speaker 1: huckle better. That was fun, right, that was fun? Yeah,

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Speaker 1: that sounded great, unbelievable. Um. Last week we had Clay

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Speaker 1: Nucome on. You guys all know Clay yep, and Clay

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Speaker 1: uh said a lot of things, but Clay was he

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Speaker 1: came from the camp of we should support all legal hunting.

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Speaker 1: That was that was what Clay was a dream for, right,

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Speaker 1: any legal method of hunting. We should We shouldn't give

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Speaker 1: up anymore the shifting baseline theory, like we shouldn't give

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Speaker 1: up any more of our culture because people don't agree

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Speaker 1: with it. Guard the gate, Guard the gates, what he

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Speaker 1: kept saying. Adam Smith wrote in and just said, um,

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Speaker 1: a lot of things what he said. As for the

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Speaker 1: most recent THHD with Clay nucom, I want to say

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Speaker 1: I agree with the sentiment of everything you guys said,

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Speaker 1: but the one thing I didn't agree with was clay

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Speaker 1: statement about supporting every legal method of hunting, although I

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Speaker 1: can't think of a legal method of take that I

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Speaker 1: have a problem with. I would never ask someone to

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Speaker 1: compromise their moral compass to support something I believe in.

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Speaker 1: So that was most of that conversation. That he goes

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Speaker 1: on to talk about trapping coyotes, which we're gonna talk about. Um,

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Speaker 1: and so I think all all of today's topics are

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Speaker 1: kind of woven into this topic. So, um, Sam, you

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Speaker 1: want to give us your thoughts on compromise and hunting

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Speaker 1: and legality and all that good stuff. Oh man, you

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Speaker 1: told me to just think about coyotes. Yeah, but this

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Speaker 1: is it's all a part of it. Yeah, yeah, I

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Speaker 1: I uh, you know, I like Clay a lot, and

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Speaker 1: I think he gives one of the most impassioned defenses

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Speaker 1: of bear hunting out there and has at least altered

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Speaker 1: my perspective UM and hesitance about hunting bears over bait

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Speaker 1: and with hounds. Um that said, I I don't I

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Speaker 1: don't think you should believe in something or support something

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Speaker 1: simply because it's legal, because uh, laws change, governments change.

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Speaker 1: Like that's as much in Flux as any other you know,

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Speaker 1: any other thing in the world. But like, I think

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Speaker 1: ethics are a little bit more steady. Um and I

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Speaker 1: and so I don't. I don't think that's a good justification.

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Speaker 1: I think things should be should be justified on their

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Speaker 1: own merits, not simply leaning on the grounds of the

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Speaker 1: current laws surrounding them. Yeah, he brings up Adam brings

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Speaker 1: up kyote contests. Has been he has zero problem with

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Speaker 1: prayer control, but he has problem with kyote contests, right,

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Speaker 1: the optics of it, but also the practice of it.

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Speaker 1: Right well, yeah, and and and for by by Clay's

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Speaker 1: own standard there, I mean you could perhaps say that, like,

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Speaker 1: you know, there are states that are trying to currently

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Speaker 1: trying to ban coyote contests. I think New York and

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Speaker 1: New Mexico could be wrong about that. But so if

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Speaker 1: they go ahead and ban those, then they're illegal. Thus

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Speaker 1: should you not support them? So like where where where

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Speaker 1: are we drawing the where are we drawing the line

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Speaker 1: with legal win and legal how? Um? And I think

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Speaker 1: it's incumbent upon hunters too. Like laws, you know, we

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Speaker 1: need to adjust to the changing times in the connected

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Speaker 1: world we now live in and be cognizant of the

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Speaker 1: optics of what we're doing. And um, I think I

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Speaker 1: think everything we do as hunters needs to be defensible

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Speaker 1: in a in a conservation um, in a conservationist light,

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Speaker 1: and and some some things, uh, you know, veer a

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Speaker 1: little bit more towards just kind of blood thirstiness and killing,

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Speaker 1: and it's just it's it's less Uh, it's it's not

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Speaker 1: something that it stands on shaky ground, I think. And

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Speaker 1: so we need to be we need to be highly

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Speaker 1: aware of that if we are to grow our ranks

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Speaker 1: in persist as a culture. Yeah, there's a lot of it.

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Speaker 1: My my feeling is we're always kind of moving and

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Speaker 1: shifting what we do based on like cultural norms. And

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Speaker 1: the thing accept that ideology is we're just it's uncomfortable

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Speaker 1: to admit that. Right, there's things that we don't do

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Speaker 1: that we're being done fifty years ago. I mean, we're

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Speaker 1: not going to like gaff a shark and have like

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Speaker 1: two gaffed sharks on the dock. We're just not gonna

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Speaker 1: do that, Like we're not doing We're not doing that

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Speaker 1: because we were We're snowflakes and we want to change

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Speaker 1: how we think and feel. We're doing that because things

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Speaker 1: are our world has shifted. We have perspectives have changed,

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Speaker 1: experience has changed, like the natural world has changed. So

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Speaker 1: we're not going to just kind of follow along with

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Speaker 1: the same kind of like everything is legal, this is

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Speaker 1: all good. We we've always done it, we should always

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Speaker 1: do it. Yeah, And animal populations are fluctuated as well

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Speaker 1: alongside those laws and and our ethics. And you know,

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Speaker 1: take sharks for example, worldwide, their populations are greatly diminished,

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Speaker 1: and so you know, while shark finning might have been

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Speaker 1: you know, acceptable at one point, maybe it isn't anymore

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Speaker 1: because it's pretty wasteful and there aren't as many of

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Speaker 1: those animals as there once were. And as you'll hear

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Speaker 1: from Dan Flores here in a little bit, he's talking

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Speaker 1: about trying to understand the history of an animal. Right.

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Speaker 1: For us to think that we could remove the coy

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Speaker 1: out from any ecosystem, he feels, and I agree, it's

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Speaker 1: pretty foolish. I mean, it's to remove any to remove

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Speaker 1: predatory you know, canids from any ecosystem was was our

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Speaker 1: was our idea. We came up with it. We said,

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Speaker 1: let's get rid of all these things. We don't want

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Speaker 1: the competition. And so then when they started to move

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Speaker 1: back into places like the East Coast. Then we're throwing

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Speaker 1: our hands up, like what what do we do? We

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Speaker 1: kill them all? What do we do now? His argument,

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Speaker 1: which is pretty is a pretty good one, is like

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Speaker 1: the history the national world was never going to tolerate

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Speaker 1: no predators, and so tis were just a vehicle for

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Speaker 1: the regeneration of something that us humans decided that we

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Speaker 1: didn't want their um for many reasons. And so that's

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Speaker 1: a good start to that conversation. But I wanted to

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Speaker 1: have us all here today because we all come from

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Speaker 1: different places. Sam's from Montana. I'm from from Washington, Washington.

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Speaker 1: Do you live in Montana? Now? Correct? When you grew

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Speaker 1: up in the East coast, Anthony, you get to the

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Speaker 1: west is all one? You don't know what states? We

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Speaker 1: um trying to save myself there, New Jersey. I'm from Pennsylvania.

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Speaker 1: Let me correct, let's let's actually correct that I'm just

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Speaker 1: gonna stay from Montana, Pennsylvania, Maryland, South Dakota. I get

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Speaker 1: one right, I got my own, like the damn it, das.

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Speaker 1: I don't know where anybody's from Washington State, alright, jesus man,

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Speaker 1: I don't know. I don't know where any I was

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Speaker 1: close at least in each of my guesses, you got

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Speaker 1: yourself right, got myself right? I think I have to

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Speaker 1: think about it now. Anyway, we're all we're all from

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Speaker 1: different parts of the country, UM, And growing up, we

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Speaker 1: all hunted. We all, I'm sure have experiences of coyotes

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Speaker 1: either having been on the landscape or moving back into

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Speaker 1: um where we lived and where we hunted growing up.

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Speaker 1: And so it's it's interesting kind of different experiences. And

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Speaker 1: we talked with Dan a little bit about that being

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Speaker 1: a unique experience. Kyotes are now in all the forty

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Speaker 1: eight states. They'll eventually find their way to Hawaii, I'm sure, um.

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Speaker 1: And and so we're not gonna reverse that. We're not

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Speaker 1: gonna go back in time. I don't believe in reverse

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Speaker 1: that things. But we've all lived in a generation where

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Speaker 1: we saw, you know, at some level of matriculation of

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Speaker 1: the kirot aross the country. So I think it's a

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Speaker 1: it's a it's interesting to at least talk about that.

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Speaker 1: So um I we did talk Dan and I talked

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Speaker 1: about my first experience of seeing kayites for the first

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Speaker 1: time when I was a kid, um and my Dad's saying,

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Speaker 1: I haven't seen those around for a while. UM, that'd

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Speaker 1: been interesting to me. So, Anthony, do you have first

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Speaker 1: memories of when kaya started to Yeah? Absolutely, Uh. I

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Speaker 1: grew up in a real world part of Pennsylvania and

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Speaker 1: um always hunted. And when I was growing up in

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Speaker 1: hunting in the late eighties and early nineties, UM, especially

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Speaker 1: the beginning part of that, it was very rare to

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Speaker 1: see a kyote or to hear one. Like if you

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Speaker 1: saw one while you're hunting, you told everybody, you know, hey,

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Speaker 1: guess what I saw kyo? Um, you know, And in

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Speaker 1: the course of ten fifteen years, now I see kyos

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Speaker 1: probably about half the time I'm out hunting. UM. So definitely,

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Speaker 1: they've they've they've come into the landscape, and UM, there

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Speaker 1: was a lot of concern about what they're doing to

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Speaker 1: deer populations, and Pennsylvania has done a really great job

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Speaker 1: doing h fond mortality studies. And you know, what's what's

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Speaker 1: really interesting is what they found they've done these studies

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Speaker 1: a couple of times, is that half of all fonds

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Speaker 1: die from predators. From predator and mortality. And the big

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Speaker 1: three in Pennsylvania are uh, bobcats, coyotes and black bears

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Speaker 1: and black bears kill more fawns than coyotes do. Um.

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Speaker 1: And it's funny because when people talk about the deer

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Speaker 1: population and to cut to the takeaway, it's, um, it's

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Speaker 1: not having a it's not decreasing deer numbers. Um. They

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Speaker 1: feel that, you know, if deer numbers were down, that

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Speaker 1: is not the way to manage it. It's just not

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Speaker 1: very effective. It would be through hunter harvest. But it's funny. Um,

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Speaker 1: you know, people worry about having too many kyotes, what

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Speaker 1: they're doing a deer. Nobody says that about black bears.

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Speaker 1: Everybody wants more bears, and the bears are eating more

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Speaker 1: deer than the coyotes do. Yeah, it's all about what

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Speaker 1: we think about the animal right. And Dan goes into

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Speaker 1: kind of like some of the propaganda at the turn

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Speaker 1: of the century later about you know, what do we

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Speaker 1: do with kyats are to scourge to the west. You know,

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Speaker 1: kayots are vermin, and that like some of that is

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Speaker 1: baked into our psyche, right, so we think about them

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Speaker 1: in certain ways. And it's it was interesting to me

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Speaker 1: similar like we we have we tend to I think

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Speaker 1: in hunting, and I made this mistake before of saying

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Speaker 1: like all hunters are worried about balance. That's probably not true,

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Speaker 1: definitely not true. I'm not a monolith. But when you

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Speaker 1: see there was there's a public piece of ground and

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Speaker 1: I hunted growing up, Well, there was less turkeys one

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Speaker 1: year and more coyotes. We went turkey hut there and

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Speaker 1: called in three kyots with a box. Call right, And

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Speaker 1: so my my first inclinations we like coyotes man eating

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Speaker 1: all the turkeys, killing all the turkeys, killing all the deer.

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Speaker 1: We gotta shoot all the kyots, he used. We talked

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Speaker 1: to a state game manager and he said the winner

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Speaker 1: was terrible, was the worst winner in fifty years in

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Speaker 1: that area. So winter kill was unbelievable for pretty much

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Speaker 1: everything that that that walks up there. And so I

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Speaker 1: was immediately, well, I saw kyots and no turkeys. Here's

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Speaker 1: what's going on. And so I think we just maybe

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Speaker 1: tend to apply that stuff to those situations because it

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Speaker 1: just makes it makes sense. It may not always be true,

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Speaker 1: and certainly in this case it doesn't seem to be.

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Speaker 1: Um Spencer Mark Kenyon wrote an article for our website

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Speaker 1: that got people a little fired up, and it was

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Speaker 1: called should you kill coyotes while deer hunting. Um, there's

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Speaker 1: a lot of reaction to that. Was there not? There was?

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Speaker 1: And when we posted this on social we kind of

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Speaker 1: pose the question that Mark opens the article with, and

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Speaker 1: it's like it's opening morning, You're sitting in the deer

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Speaker 1: blind and a coyote is at fifty yards? Are you

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Speaker 1: going to shoot it? And that got a lot of

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Speaker 1: reaction both ways saying absolutely and absolutely not. And I

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Speaker 1: think that is like a strange question that is like

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Speaker 1: a weird one where you will get passion response from both. Say,

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Speaker 1: you were out deer hunting in the fall, and you

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Speaker 1: also have a turkey tag and a turkey walks by,

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Speaker 1: You're gonna shoot that turkey. But everybody says, yeah, you

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Speaker 1: have a bear tag in. A bear walks about, You're

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Speaker 1: gonna shoot that bear probably, But a kyo walks by. Um,

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Speaker 1: it's like a lot of people on the fence. So

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Speaker 1: that the pro being that or excuse me, the campus

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Speaker 1: says absolutely for them, it's like the deer hunt now

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Speaker 1: becomes a kyote hunt because you kill that coyote. Um,

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Speaker 1: your goal is to have more deer and so you

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Speaker 1: just got rid of something that is going to boost

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Speaker 1: deer populations. It's like that's why people were doing people

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Speaker 1: who didn't want to do it. Uh, the reward just

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Speaker 1: isn't worth the risk that you've buggered up the rest

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Speaker 1: of the morning. Um. You know a lot of people

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Speaker 1: say the only thing worse than the smell of a

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Speaker 1: coyote is the smell of a dead coyote. Um, So

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Speaker 1: why would you do that on opening morning and potentially

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Speaker 1: risk you know, the deer in the air of spooky Yeah,

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Speaker 1: it's um you know. To me, I I've I've I've

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Speaker 1: come across that scenario many many times, and I almost

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Speaker 1: not almost, I don't think I've ever shot the kyote. Well,

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Speaker 1: deer hunting because I'm deer hunting. I have shot coyotes.

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Speaker 1: I have Kyle hunter, I've killed kyots. To me, that's

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Speaker 1: a different kind of hunt. When I'm Kyle hunting, I'm

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Speaker 1: calling him in. I'm It's a different thing that I'm doing,

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Speaker 1: and I'm doing it for different reasons. Um. You know,

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Speaker 1: it's it's a it's a different activity. And so that's

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Speaker 1: why if I shoot one just while I'm deer hunting,

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Speaker 1: I am afraid of messing up my my dear hunt.

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Speaker 1: I don't know if it will or not. But it's

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Speaker 1: also that's not why I'm there. If I want to go,

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Speaker 1: uh hunt kyotes, I'm gonnahunt kyotes, not just you know,

402
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Speaker 1: take one from a deer stand. Yeah, I mean there's

403
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Speaker 1: some level of like are you are you opportunistic? But

404
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Speaker 1: to me, it comes down to what when I read

405
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Speaker 1: all the comments on social and we talked about this

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Speaker 1: briefly with uh fucking Barry Gilbert keeps coming back, but

407
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Speaker 1: Barry Gilbert and I just I just said, look, I

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Speaker 1: don't think. I don't think in general, none of the

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Speaker 1: hunters that I know have a hatred for predators, right,

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Speaker 1: whether we're talking grizzlies or um coyotes or wolves or whatever.

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Speaker 1: And his the connotation that he was laying out there

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Speaker 1: was basically that we don't want the competition for the deer.

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Speaker 1: We want to deal to ourselves. We want to kill

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Speaker 1: all the deer. We don't want anything out there that's

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Speaker 1: gonna mess with that balance. Um My, my general point was,

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Speaker 1: I think we're all out there for balance. We went

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Speaker 1: to the right number of cryouts, the right number of

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Speaker 1: dear the right number you know, so we're not But

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Speaker 1: I got hammered by a lot of listeners saying like,

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Speaker 1: you're not right. Just go to the Arizona Face Hunting

421
00:23:19,880 --> 00:23:22,160
Speaker 1: Facebook page and you're gonna see that there's a bunch

422
00:23:22,160 --> 00:23:24,800
Speaker 1: of people are like, kill all the cyouds, more coyote contests,

423
00:23:24,880 --> 00:23:27,560
Speaker 1: more hounds with for kiods, more whatever, whatever to rid

424
00:23:27,640 --> 00:23:30,280
Speaker 1: this country of the scourage of kyods um. And you'll

425
00:23:30,320 --> 00:23:32,000
Speaker 1: hear from Dan Floors what he thinks about that. But

426
00:23:32,040 --> 00:23:33,760
Speaker 1: I'm interested in what everybody else that what you guys

427
00:23:33,840 --> 00:23:37,960
Speaker 1: think about KOs? Why why is this happening? Well, I

428
00:23:38,040 --> 00:23:40,359
Speaker 1: think I think something we should address, which I think

429
00:23:40,480 --> 00:23:42,359
Speaker 1: is the elephant in the room in this discussion, is

430
00:23:42,400 --> 00:23:46,560
Speaker 1: that the science is relatively clear that hunting for coyotes

431
00:23:47,040 --> 00:23:52,639
Speaker 1: does absolutely nothing to lower their population, and in certain

432
00:23:52,720 --> 00:23:56,320
Speaker 1: instance instances, there's there are there are like pure viewed

433
00:23:56,320 --> 00:24:01,119
Speaker 1: studies that suggest that coyote hunting for for sport, not

434
00:24:01,359 --> 00:24:05,480
Speaker 1: like for lethal removal, can actually boost pop populations because

435
00:24:05,480 --> 00:24:08,920
Speaker 1: a lot of times you're gonna be killing the like

436
00:24:09,320 --> 00:24:14,280
Speaker 1: the the matriarch of the patriarch of the area, which

437
00:24:14,440 --> 00:24:20,200
Speaker 1: throws the rest of the population into turmoil, and and

438
00:24:20,720 --> 00:24:25,280
Speaker 1: and we'll actually can actually boost um pop rates um,

439
00:24:25,840 --> 00:24:27,600
Speaker 1: and and there's all sorts of there's all sorts of

440
00:24:27,600 --> 00:24:30,080
Speaker 1: studies about that. I've had this conversation a million times

441
00:24:30,119 --> 00:24:32,760
Speaker 1: with people, and and some hunters you just see their

442
00:24:32,840 --> 00:24:35,199
Speaker 1: like eyes roll back in their head when you when

443
00:24:35,240 --> 00:24:37,040
Speaker 1: you say that. And I'm sure that's happening to a

444
00:24:37,080 --> 00:24:39,720
Speaker 1: lot of people right now, but I encourage you. I

445
00:24:39,800 --> 00:24:42,080
Speaker 1: wish I looked up the studies beforehand, but I'd be happy,

446
00:24:42,240 --> 00:24:46,040
Speaker 1: happy to dig that up again. Yeah, I'm sure. I'm

447
00:24:46,080 --> 00:24:48,920
Speaker 1: sure he does. But you know, and some people see

448
00:24:48,960 --> 00:24:51,560
Speaker 1: it as you know, it's you know, kind of one

449
00:24:51,600 --> 00:24:53,920
Speaker 1: to one, like you kill a coyote, there's one less coyote,

450
00:24:54,200 --> 00:24:57,960
Speaker 1: Like how the math couldn't be more simple, idiot. But

451
00:24:58,280 --> 00:25:00,440
Speaker 1: I've talked to a number of biologists about this and

452
00:25:00,480 --> 00:25:02,720
Speaker 1: they're like, yeah, guys, it's it's the same with with

453
00:25:02,880 --> 00:25:05,320
Speaker 1: wild boars, you know, where like a lot of states

454
00:25:05,359 --> 00:25:10,600
Speaker 1: are banning board hunting because because hunters are bringing them

455
00:25:10,600 --> 00:25:13,720
Speaker 1: in and hunters have zero effect on populations, because you

456
00:25:13,840 --> 00:25:16,119
Speaker 1: go out and shoot three coyotes in a day, like

457
00:25:16,320 --> 00:25:19,800
Speaker 1: there's you know that area hunting probably has fifty. Yeah. Yeah,

458
00:25:19,880 --> 00:25:21,440
Speaker 1: there's a couple of things to that. We talked about

459
00:25:21,560 --> 00:25:24,200
Speaker 1: then a little bit about mixed messages that state game

460
00:25:24,200 --> 00:25:28,119
Speaker 1: agencies are sending, you know, and so you go to

461
00:25:28,480 --> 00:25:30,840
Speaker 1: say Wyoming, where they'll pay a bounty for you to

462
00:25:30,920 --> 00:25:32,960
Speaker 1: kill one, right, and there's other states where you still

463
00:25:32,960 --> 00:25:34,760
Speaker 1: have to have a trapper's license to even hunt them,

464
00:25:35,080 --> 00:25:36,760
Speaker 1: you know, which were classes going to the library and

465
00:25:36,800 --> 00:25:39,920
Speaker 1: paying money to take the class. And so we you know,

466
00:25:40,160 --> 00:25:43,119
Speaker 1: as a country, we kind of have a prescription for

467
00:25:43,440 --> 00:25:45,520
Speaker 1: unglits and deer. We know kind of what we're gonna do.

468
00:25:45,600 --> 00:25:47,800
Speaker 1: We're gonna survey a carry capacity, and we're gonna sign

469
00:25:48,520 --> 00:25:51,680
Speaker 1: tags based based on a number of structures with coyotes.

470
00:25:51,720 --> 00:25:53,560
Speaker 1: It's like it's a little bit all over the board

471
00:25:54,720 --> 00:25:56,960
Speaker 1: we have. There is I'm sure within not only the

472
00:25:57,000 --> 00:26:00,960
Speaker 1: biologist community, but within game manager communities and state game

473
00:26:01,000 --> 00:26:04,680
Speaker 1: agencies different opinions about this. And it's clear based on

474
00:26:05,000 --> 00:26:08,199
Speaker 1: what's out there as far as UM regulations, I mean,

475
00:26:08,320 --> 00:26:10,560
Speaker 1: they're all over the place, and there was there was

476
00:26:10,560 --> 00:26:12,200
Speaker 1: a time when I think I wanted to get it

477
00:26:12,240 --> 00:26:15,040
Speaker 1: wrong in North Carolina had a bounty UM not too

478
00:26:15,119 --> 00:26:18,120
Speaker 1: long ago. So I mean that's to me, as somebody

479
00:26:18,160 --> 00:26:20,360
Speaker 1: who always has talked about our model conservation this one's

480
00:26:20,400 --> 00:26:22,320
Speaker 1: kind it's thrown off a little bit because there isn't

481
00:26:22,359 --> 00:26:25,320
Speaker 1: one way that this is handled. Yeah, absolutely, And and

482
00:26:25,400 --> 00:26:28,119
Speaker 1: a lot of people in the in the especially in

483
00:26:28,160 --> 00:26:30,119
Speaker 1: the context of what Mark wrote about, a lot of

484
00:26:30,200 --> 00:26:32,280
Speaker 1: people want to give themselves a big old pat on

485
00:26:32,359 --> 00:26:35,080
Speaker 1: the back for killing that coyote. And I know, I

486
00:26:35,200 --> 00:26:37,399
Speaker 1: know guys who who, like you know, go out in

487
00:26:37,440 --> 00:26:41,720
Speaker 1: a weekend in February and kill twenty of them and

488
00:26:41,880 --> 00:26:44,720
Speaker 1: they are just high on life and they're like the

489
00:26:44,840 --> 00:26:49,080
Speaker 1: saviors of hunt deer hunting in Montana. And and I

490
00:26:49,240 --> 00:26:55,399
Speaker 1: think that that perspective is you know, is questionable at best,

491
00:26:55,720 --> 00:26:59,680
Speaker 1: but many game departments are encouraging they are that and

492
00:26:59,760 --> 00:27:01,879
Speaker 1: you know, and I think I think there are you know,

493
00:27:01,960 --> 00:27:04,840
Speaker 1: there's also folds to this because some people are are

494
00:27:04,920 --> 00:27:08,120
Speaker 1: doing it around calving time for ranchers, and ranchers will

495
00:27:08,200 --> 00:27:10,680
Speaker 1: give you a pad on the back for for going

496
00:27:10,680 --> 00:27:14,040
Speaker 1: out and hunting coyotes around their their birthing cows. And

497
00:27:14,119 --> 00:27:15,840
Speaker 1: so there, I mean, there's there's a lot of different

498
00:27:15,880 --> 00:27:19,320
Speaker 1: contexts we can talk about here. And and problem coyotes,

499
00:27:19,400 --> 00:27:22,360
Speaker 1: Like if it's an individual you're targeting that's causing problems,

500
00:27:22,400 --> 00:27:25,119
Speaker 1: then sure, maybe that that is beneficial to you or

501
00:27:26,080 --> 00:27:29,040
Speaker 1: an agriculture. But you'll hear that later from from Dan Flores.

502
00:27:29,200 --> 00:27:32,320
Speaker 1: He he feels like there are just like individual humans

503
00:27:32,359 --> 00:27:34,879
Speaker 1: that are issues that cause issues that are individual or

504
00:27:34,920 --> 00:27:38,040
Speaker 1: groups of coyotes that become problematic and to target those.

505
00:27:38,160 --> 00:27:41,359
Speaker 1: He feels is um is proper based on balance and

506
00:27:41,480 --> 00:27:45,200
Speaker 1: coaptation things like that. But for me, there's two two

507
00:27:45,240 --> 00:27:47,840
Speaker 1: other points that we should talk about. One, we love

508
00:27:47,920 --> 00:27:50,359
Speaker 1: it when the gloves come off, like we love it.

509
00:27:50,560 --> 00:27:54,359
Speaker 1: I'm sorry, but people, humans, we have all these like

510
00:27:54,680 --> 00:27:57,600
Speaker 1: value systems and structures build around killing stuff. Boy do

511
00:27:57,680 --> 00:28:00,480
Speaker 1: we love it when somebody says kill them all? Like

512
00:28:01,640 --> 00:28:03,920
Speaker 1: it is clear? And so I think that is that

513
00:28:04,160 --> 00:28:07,000
Speaker 1: feeling is disc It is connected to like I'm a

514
00:28:07,080 --> 00:28:09,160
Speaker 1: hero for killing a kid, right, So there's a connection

515
00:28:09,240 --> 00:28:11,080
Speaker 1: there that you have to tell yourself you're doing it

516
00:28:11,640 --> 00:28:15,720
Speaker 1: for this reason, regardless of what information surrounds what you're doing.

517
00:28:16,000 --> 00:28:18,600
Speaker 1: It's like a mob mentality. Man. It's like when when

518
00:28:18,640 --> 00:28:21,320
Speaker 1: people say there's no rules, they go smashing grocery store wind.

519
00:28:21,520 --> 00:28:23,119
Speaker 1: It's the same thing. And then there's the other, like

520
00:28:23,359 --> 00:28:27,600
Speaker 1: nature is metal idea that like we gotta let people

521
00:28:27,680 --> 00:28:29,880
Speaker 1: know how terrible it is for a fallon to get

522
00:28:30,000 --> 00:28:32,120
Speaker 1: ripped out and eating up by a pack of coyotes

523
00:28:32,240 --> 00:28:34,800
Speaker 1: or whatever. So there's we we also want to like

524
00:28:34,920 --> 00:28:40,240
Speaker 1: acknowledge predatory instincts and predators, the predators in the wild,

525
00:28:40,320 --> 00:28:43,200
Speaker 1: and and how harsh that is and not not water

526
00:28:43,320 --> 00:28:46,560
Speaker 1: that down. So when that engenders the feeling of oh,

527
00:28:46,640 --> 00:28:49,040
Speaker 1: I shot a shot a coyote. I saved a fawn

528
00:28:49,200 --> 00:28:53,520
Speaker 1: from this terrible death. Um, I'm there's mercy in that.

529
00:28:53,680 --> 00:28:55,320
Speaker 1: So all that ship is wrapped up, I'm sure. And

530
00:28:55,360 --> 00:28:59,000
Speaker 1: the more modern the issue we have with kayads, Yeah,

531
00:28:59,080 --> 00:29:01,760
Speaker 1: it's like you're old. Okay, your season is only two

532
00:29:01,800 --> 00:29:03,680
Speaker 1: weeks long, you have to get a tag. You can

533
00:29:03,760 --> 00:29:05,280
Speaker 1: only do this, You can only do that for most

534
00:29:05,320 --> 00:29:10,520
Speaker 1: of hunting coyotes all year long, no close seasons, it

535
00:29:10,600 --> 00:29:12,600
Speaker 1: all night. It makes you think like, oh, yeah, you

536
00:29:12,640 --> 00:29:14,520
Speaker 1: could do it at night. You could use electronic college,

537
00:29:14,520 --> 00:29:17,000
Speaker 1: you could do all these things you can't do otherwise.

538
00:29:17,040 --> 00:29:20,400
Speaker 1: So it just makes you think, um, well, jeez man,

539
00:29:20,880 --> 00:29:23,040
Speaker 1: you know it must be okay, or you know there

540
00:29:23,080 --> 00:29:25,120
Speaker 1: must be way way too many of them or something.

541
00:29:25,160 --> 00:29:27,760
Speaker 1: If that's how the professionals are setting it up. And

542
00:29:27,840 --> 00:29:30,880
Speaker 1: that's this how it goes back to I saw another

543
00:29:31,960 --> 00:29:33,880
Speaker 1: hunting celebrities say the same thing the other day, like,

544
00:29:33,960 --> 00:29:36,160
Speaker 1: if it's legal, we should support it rally around your

545
00:29:36,240 --> 00:29:40,160
Speaker 1: hunting Brotherren. I'm cool. That's a real simple, real simplistic

546
00:29:40,240 --> 00:29:43,400
Speaker 1: way to express hunting. Like it's easy to go. Yeah,

547
00:29:43,840 --> 00:29:48,120
Speaker 1: who yeah, everybody's awesome solidarity And I get it, man,

548
00:29:48,240 --> 00:29:50,920
Speaker 1: I get that feeling. I have that feeling too, But

549
00:29:51,120 --> 00:29:53,640
Speaker 1: like you can't escape these issues. You're not gonna walk

550
00:29:53,680 --> 00:29:55,280
Speaker 1: away from this stuff. But you know, to go back

551
00:29:55,320 --> 00:29:57,360
Speaker 1: to where we started. It's like, you know, all based

552
00:29:57,400 --> 00:30:00,280
Speaker 1: on the science and whatnot, there's lots of kai outs.

553
00:30:00,640 --> 00:30:03,320
Speaker 1: Um they're not going away. They're part of the ecosystem.

554
00:30:03,360 --> 00:30:05,760
Speaker 1: I don't think they should go away, but um, people

555
00:30:05,800 --> 00:30:08,440
Speaker 1: want to hunt them. Great, you know that. I and

556
00:30:08,760 --> 00:30:11,400
Speaker 1: as I said, I do a little bit of kyote hunting. Um,

557
00:30:12,040 --> 00:30:14,640
Speaker 1: it's not going to have that impact positive and or

558
00:30:14,720 --> 00:30:16,960
Speaker 1: negative either way. You know, we've done the right way.

559
00:30:17,120 --> 00:30:18,960
Speaker 1: And I said, and I said this and just being

560
00:30:19,000 --> 00:30:22,640
Speaker 1: flat honest to Dan, and you'll hear it. I just said,

561
00:30:24,080 --> 00:30:25,840
Speaker 1: I'm at a point right now with coyotes in my

562
00:30:25,920 --> 00:30:28,120
Speaker 1: own hunting where I have a question rather than an

563
00:30:28,160 --> 00:30:30,920
Speaker 1: answer like my question is, yeah, I could shoot him.

564
00:30:30,960 --> 00:30:32,760
Speaker 1: I've always shot him. I've shot plenty of them. I

565
00:30:32,840 --> 00:30:35,480
Speaker 1: hunted for him specifically, I've called him in, I've done

566
00:30:35,480 --> 00:30:39,360
Speaker 1: all these things. Um, I'm just at a point right

567
00:30:39,360 --> 00:30:40,840
Speaker 1: now where i have a question like, what the hell

568
00:30:42,000 --> 00:30:44,120
Speaker 1: if all these things that I'm hearing and reading about

569
00:30:44,160 --> 00:30:46,040
Speaker 1: these period of studies and what Dan has to say

570
00:30:46,360 --> 00:30:50,040
Speaker 1: are true. I'm just kind of question should I shoot him?

571
00:30:50,880 --> 00:30:54,280
Speaker 1: And if I do, why, and when it's just more

572
00:30:54,280 --> 00:30:56,280
Speaker 1: of a question than it is what what I used

573
00:30:56,280 --> 00:30:58,200
Speaker 1: to think of not too long ago was like if

574
00:30:58,200 --> 00:31:00,520
Speaker 1: I see one, I'll shoot it. I I'd like to

575
00:31:00,640 --> 00:31:03,440
Speaker 1: I'd like to introduce a different kind of philosophical track

576
00:31:03,520 --> 00:31:05,440
Speaker 1: with this. And maybe you covered this with Dan, but

577
00:31:05,720 --> 00:31:09,400
Speaker 1: you know, in the context of hunting, Um, I'm not

578
00:31:09,560 --> 00:31:14,160
Speaker 1: I'm not certain that that, you know, saving dear Fonds

579
00:31:15,080 --> 00:31:19,000
Speaker 1: is like the only possible rationale out there, Like the

580
00:31:19,360 --> 00:31:22,520
Speaker 1: way I've I've actually never shot a coyote. I've taken

581
00:31:22,600 --> 00:31:24,960
Speaker 1: shots at them. I've also passed a lot of shots

582
00:31:25,000 --> 00:31:27,560
Speaker 1: at them. I passed one with my bow that I

583
00:31:27,600 --> 00:31:29,520
Speaker 1: had dead to rights a couple of weeks ago because

584
00:31:29,560 --> 00:31:32,880
Speaker 1: I saw that it was nuzzling puppies. Um, so i'd like,

585
00:31:33,200 --> 00:31:36,440
Speaker 1: you know, stopped, stopped me. But I've shot I've shot foxes,

586
00:31:37,120 --> 00:31:42,320
Speaker 1: um and bears, and I think, um, I think for

587
00:31:43,680 --> 00:31:50,040
Speaker 1: is has an inherent value approaching that of meat if

588
00:31:50,080 --> 00:31:53,000
Speaker 1: you're going to do something useful with it. And I

589
00:31:53,120 --> 00:31:56,320
Speaker 1: think that has a has a rich history in this country.

590
00:31:56,400 --> 00:32:00,480
Speaker 1: It was for trappers that first, uh Cal and I

591
00:32:01,640 --> 00:32:05,960
Speaker 1: the you know the West, and um, I've seen a

592
00:32:06,040 --> 00:32:08,000
Speaker 1: lot of people do a lot of really cool stuff

593
00:32:08,000 --> 00:32:13,760
Speaker 1: with coyote for and I think that is some justification.

594
00:32:13,920 --> 00:32:16,720
Speaker 1: I don't know if it completely or not, um, but

595
00:32:16,840 --> 00:32:19,440
Speaker 1: I think that is a valid is a valid used

596
00:32:19,480 --> 00:32:21,680
Speaker 1: for it because because you know, another another thing people

597
00:32:21,680 --> 00:32:23,480
Speaker 1: will say is like, well you do you eat it?

598
00:32:23,760 --> 00:32:26,720
Speaker 1: Like okay, so then you know you you lose all

599
00:32:27,720 --> 00:32:29,600
Speaker 1: rationale if you don't eat it. But I think if

600
00:32:29,640 --> 00:32:32,160
Speaker 1: you're if you're using using a pelt, then that's that's

601
00:32:32,160 --> 00:32:33,920
Speaker 1: still a valid use of that animal. And then you

602
00:32:34,000 --> 00:32:37,080
Speaker 1: can divorce it from like this bullshit of like I'm

603
00:32:37,160 --> 00:32:40,600
Speaker 1: saving the the the ecosystem by killing this kyo. No,

604
00:32:40,680 --> 00:32:42,280
Speaker 1: it's like I wanted to kill it and I wanted

605
00:32:42,320 --> 00:32:44,520
Speaker 1: to do something with it cool with it. Yeah, and

606
00:32:44,680 --> 00:32:47,440
Speaker 1: it's kind of unique to kyotes. Like somebody doesn't trap

607
00:32:47,520 --> 00:32:50,280
Speaker 1: beavers and then be like got one and just let

608
00:32:50,320 --> 00:32:53,040
Speaker 1: it lay there. Walk away from a beaver. You always

609
00:32:53,040 --> 00:32:55,080
Speaker 1: see dead Kyle's hung up on like a fence post

610
00:32:55,240 --> 00:32:58,160
Speaker 1: or something. It's like it's like bow fishing, you know,

611
00:32:58,360 --> 00:33:00,960
Speaker 1: it's kind of the same thing that. Uh, it's more

612
00:33:01,000 --> 00:33:04,480
Speaker 1: about like the the activity and and the shooting and

613
00:33:04,560 --> 00:33:07,160
Speaker 1: stuff than it is about the product that you have

614
00:33:07,280 --> 00:33:09,960
Speaker 1: when you're done. It's kind of unique to like those

615
00:33:10,000 --> 00:33:12,600
Speaker 1: two things. Yeah, that that, and I think there's you know,

616
00:33:12,720 --> 00:33:14,920
Speaker 1: if you want to address the polls here, you got

617
00:33:15,040 --> 00:33:17,440
Speaker 1: the kill them all kind of thing, and then you've

618
00:33:17,440 --> 00:33:19,160
Speaker 1: got the hunters like I'm not gonna kill one because

619
00:33:19,280 --> 00:33:22,080
Speaker 1: there's no purpose. I'm not gonna eat it. There isn't

620
00:33:22,520 --> 00:33:26,000
Speaker 1: you know, there isn't this urge from the ecosystem to

621
00:33:26,040 --> 00:33:28,400
Speaker 1: have me eliminate them. It's not really doing. And so

622
00:33:28,520 --> 00:33:31,280
Speaker 1: there's there's those two poles. I'm somewhere in the middle personally,

623
00:33:31,640 --> 00:33:34,360
Speaker 1: you know, like that's where I just just to be honest,

624
00:33:34,400 --> 00:33:38,080
Speaker 1: I could raw Ross say. You know, hunting is killings

625
00:33:38,160 --> 00:33:40,840
Speaker 1: is a tool for for game managers and tool for

626
00:33:40,880 --> 00:33:42,600
Speaker 1: state agencies and we should continue to do it. I

627
00:33:42,720 --> 00:33:47,600
Speaker 1: do believe that philosophically, but personally it's hard for me

628
00:33:47,680 --> 00:33:49,880
Speaker 1: to just to look at a kid and think I

629
00:33:50,000 --> 00:33:52,120
Speaker 1: better shoot that if I don't have in any tent.

630
00:33:52,400 --> 00:33:54,680
Speaker 1: I think Sam's you know, point is important one man.

631
00:33:54,760 --> 00:33:56,560
Speaker 1: I mean, I I hunt coyotes in the winter for

632
00:33:57,880 --> 00:34:01,400
Speaker 1: um callment in calling calling them in, and man, I've

633
00:34:01,800 --> 00:34:05,920
Speaker 1: my brother made a terrific quiver for his cedar arrows

634
00:34:06,000 --> 00:34:07,800
Speaker 1: for his long bow out of one of the hides.

635
00:34:08,040 --> 00:34:10,680
Speaker 1: Um others we skin out and will sell hide do

636
00:34:10,800 --> 00:34:12,879
Speaker 1: not make it a lot of money, but like it's used.

637
00:34:13,040 --> 00:34:16,040
Speaker 1: I mean the expensive Parker that I have that I

638
00:34:16,160 --> 00:34:19,680
Speaker 1: almost want to put on now in October kyat rough

639
00:34:19,760 --> 00:34:23,120
Speaker 1: around the Hood, you know, like, um, you know the

640
00:34:23,200 --> 00:34:28,080
Speaker 1: first pretty magnificent Absolutely, yeah, it could be so beautiful. Yeah,

641
00:34:28,160 --> 00:34:31,120
Speaker 1: And I think this. You know, these kind of conversations,

642
00:34:31,520 --> 00:34:34,040
Speaker 1: especially when they're just boiled down and honest, can be

643
00:34:34,200 --> 00:34:36,759
Speaker 1: kind of used from either camp. Either can't can pull

644
00:34:36,800 --> 00:34:39,920
Speaker 1: it and say oh you you know you believe what

645
00:34:39,960 --> 00:34:41,719
Speaker 1: I believe or you don't believe what I believe. But

646
00:34:41,800 --> 00:34:44,480
Speaker 1: in this case, um, if I went out there and

647
00:34:44,520 --> 00:34:47,279
Speaker 1: I'm like I want to make X out of fur,

648
00:34:47,880 --> 00:34:50,200
Speaker 1: and I need to get three coyotes. Man, that's do

649
00:34:50,320 --> 00:34:53,200
Speaker 1: that all day. UM, And I think trapping is absolutely

650
00:34:53,600 --> 00:34:57,439
Speaker 1: necessary um and a good thing. And they're extremely hard

651
00:34:57,480 --> 00:34:59,520
Speaker 1: to trap. Yeah too, I've got I've got a good

652
00:34:59,560 --> 00:35:02,360
Speaker 1: buddy and uh down by Shardan Wyoming who does a

653
00:35:02,400 --> 00:35:05,160
Speaker 1: lot of trapping. He gets several foxes a year and

654
00:35:05,200 --> 00:35:07,359
Speaker 1: he's starting to get all sorts of stuff, getting good

655
00:35:07,440 --> 00:35:10,439
Speaker 1: at it, and he still can't crack the code on coyotes. Yeah. Yeah,

656
00:35:10,480 --> 00:35:13,000
Speaker 1: I think there's there's that element, right, there's the that's

657
00:35:13,040 --> 00:35:16,360
Speaker 1: the value we have for for that, for that UM pursuit.

658
00:35:16,760 --> 00:35:19,000
Speaker 1: And then the version of you guys, what do you

659
00:35:19,040 --> 00:35:22,040
Speaker 1: guys think about uh? Dan Floors' version of it, where

660
00:35:22,680 --> 00:35:24,680
Speaker 1: he feels like there's no reason to kill a coyote

661
00:35:24,719 --> 00:35:28,480
Speaker 1: unless there's a problem with with it on a predation level,

662
00:35:28,560 --> 00:35:31,200
Speaker 1: like it's whacking your calves or it's going into town.

663
00:35:32,520 --> 00:35:34,920
Speaker 1: That's kind of what he I believe the number he uses,

664
00:35:35,880 --> 00:35:40,200
Speaker 1: but he talking about, UM, what he feels like the

665
00:35:40,280 --> 00:35:43,200
Speaker 1: proper prescription is for how we interact, you know, with

666
00:35:43,320 --> 00:35:45,359
Speaker 1: coyotes on a level of when do we kill him

667
00:35:45,360 --> 00:35:47,719
Speaker 1: in why so he he's saying, when they're a problem,

668
00:35:47,800 --> 00:35:50,839
Speaker 1: shoot him if they're not leaving b I mean, I think,

669
00:35:51,000 --> 00:35:53,080
Speaker 1: you know, if if you're gonna shoot kyotes, is how

670
00:35:53,120 --> 00:35:55,520
Speaker 1: a reason to do it? I just I disagree with him.

671
00:35:55,960 --> 00:36:00,520
Speaker 1: I hunt other predators, predators, I hunt bears. Um. I

672
00:36:00,680 --> 00:36:03,520
Speaker 1: enjoy kyle hunting because it is challenging. Uh. I do

673
00:36:03,640 --> 00:36:05,320
Speaker 1: skin them out and sell a fur. But I'm not

674
00:36:05,520 --> 00:36:07,839
Speaker 1: gonna just shoot one and let it away while I'm

675
00:36:07,840 --> 00:36:11,680
Speaker 1: in a deer stand thinking I'm doing some good. That why.

676
00:36:11,920 --> 00:36:14,200
Speaker 1: I mean, you know, I just don't. I don't want

677
00:36:14,200 --> 00:36:16,600
Speaker 1: to do that. I'd rather I've let kyotes go. I

678
00:36:16,719 --> 00:36:20,120
Speaker 1: enjoy watching them, That's that's fine. Um, but I don't

679
00:36:20,120 --> 00:36:22,520
Speaker 1: agree with that that, you know, there's no reason to

680
00:36:22,880 --> 00:36:27,399
Speaker 1: hunt them. Spencer talk about you like you're a deer hunter.

681
00:36:28,440 --> 00:36:31,960
Speaker 1: You're a Midwestern guy, right, you are every man? Yeah,

682
00:36:32,200 --> 00:36:38,080
Speaker 1: you're from where you from, North Dakota, right, Yeah, Kyle

683
00:36:38,200 --> 00:36:40,280
Speaker 1: hunting is like very much a part of the culture

684
00:36:40,440 --> 00:36:43,760
Speaker 1: where I came from, because two big things in rural

685
00:36:43,800 --> 00:36:48,120
Speaker 1: South Dakota are pheasant hunting and cattle farming. And so

686
00:36:48,840 --> 00:36:51,600
Speaker 1: like my in laws are cattle farmers. And when it's

687
00:36:51,640 --> 00:36:54,480
Speaker 1: having season and they hear a pack of coyotes and

688
00:36:54,520 --> 00:36:56,400
Speaker 1: the shelter bell behind the farm. It's like a bit

689
00:36:56,480 --> 00:37:00,640
Speaker 1: of dread there. And so to those guys, um, and

690
00:37:00,719 --> 00:37:03,880
Speaker 1: to the people who enjoy pheasant hunting, whether or not,

691
00:37:04,640 --> 00:37:06,719
Speaker 1: it's probably the same thing as the deer numbers that

692
00:37:06,800 --> 00:37:10,360
Speaker 1: you kill a coyote, you're not saving a whole covey

693
00:37:10,400 --> 00:37:12,920
Speaker 1: of pheasants or whatever. It's probably the same thing, um.

694
00:37:13,600 --> 00:37:15,680
Speaker 1: But but in their head it's the math, like Sam

695
00:37:15,760 --> 00:37:17,480
Speaker 1: said that you get rid of a coyote, you are

696
00:37:17,520 --> 00:37:20,480
Speaker 1: saving a calf, you're saving a fawn, You're saving a

697
00:37:20,560 --> 00:37:24,440
Speaker 1: brute of pheasants. Um. So it would be hypocritical for

698
00:37:24,480 --> 00:37:27,799
Speaker 1: me to say that you should in kyot hunt because

699
00:37:27,800 --> 00:37:30,160
Speaker 1: I've done it a bunch. I enjoy the hell out

700
00:37:30,200 --> 00:37:33,200
Speaker 1: of it. It's like some of the most exciting van

701
00:37:33,280 --> 00:37:35,359
Speaker 1: to trick a kayah and like see that then come

702
00:37:35,440 --> 00:37:40,120
Speaker 1: running in and shoot it. It's uh so damn faun.

703
00:37:41,040 --> 00:37:44,080
Speaker 1: So I'll do it. But I've like also in the

704
00:37:44,200 --> 00:37:48,359
Speaker 1: last few years, been like this kind of feels wasteful, um.

705
00:37:48,719 --> 00:37:51,879
Speaker 1: And it's kind of came to that with some bow

706
00:37:51,960 --> 00:37:54,239
Speaker 1: fishing as well. I really like bow fishing. I don't

707
00:37:54,239 --> 00:37:56,000
Speaker 1: feel that bad if I like shoot a carp or

708
00:37:56,080 --> 00:37:58,400
Speaker 1: something like that. But if I'm just like killing a

709
00:37:58,440 --> 00:38:00,759
Speaker 1: bunch of guar buffalo to litle bit different because like

710
00:38:00,760 --> 00:38:03,960
Speaker 1: their native species, they're there, I'm not eating them. Um,

711
00:38:04,280 --> 00:38:06,800
Speaker 1: So I'm like, man, I'm just like a wasteful person

712
00:38:07,080 --> 00:38:11,400
Speaker 1: when I'm doing this. And so with coyotes, uh, I'm

713
00:38:11,440 --> 00:38:14,440
Speaker 1: certainly more selective. I currently have four coyote hams and

714
00:38:14,600 --> 00:38:17,799
Speaker 1: four kyle backstraps in my freezer. We're going to cook

715
00:38:17,880 --> 00:38:19,880
Speaker 1: those at some point, and I feel like that's going

716
00:38:19,920 --> 00:38:22,160
Speaker 1: to kind of turn me somewhere or the other like, oh,

717
00:38:22,239 --> 00:38:24,080
Speaker 1: you can eat this, This is fine. So then it

718
00:38:24,160 --> 00:38:26,560
Speaker 1: doesn't feel so bad when I go out and and

719
00:38:26,719 --> 00:38:30,720
Speaker 1: kill a kyote knowing that I am not like helping

720
00:38:31,480 --> 00:38:34,680
Speaker 1: mother nature or something. Yeah, I think that's that's a

721
00:38:34,760 --> 00:38:40,280
Speaker 1: pretty good that's a pretty good analogy for or example

722
00:38:40,280 --> 00:38:41,920
Speaker 1: of how kind of all we all feel. I mean,

723
00:38:41,920 --> 00:38:44,680
Speaker 1: I grew up, Yeah, if you saw a kier, you

724
00:38:44,719 --> 00:38:47,680
Speaker 1: shot one. And then when I got into the hunting industry,

725
00:38:47,719 --> 00:38:49,239
Speaker 1: I got invited on a lot of kirot hunts, and

726
00:38:49,239 --> 00:38:50,719
Speaker 1: I went on a lot of cloud hunts and had

727
00:38:50,760 --> 00:38:53,640
Speaker 1: a great time calling them in, learning, learning their habits,

728
00:38:53,719 --> 00:38:56,839
Speaker 1: understanding what they do. I mean, that's a pretty damn

729
00:38:56,880 --> 00:38:59,000
Speaker 1: cool thing in and of itself, Understanding what the coyote

730
00:38:59,080 --> 00:39:01,560
Speaker 1: is and what they do and why they do what

731
00:39:01,640 --> 00:39:05,680
Speaker 1: they do. So, um, I think that's a pretty common

732
00:39:05,960 --> 00:39:07,839
Speaker 1: I would say that's just kind of right where I'm at.

733
00:39:08,280 --> 00:39:10,200
Speaker 1: I think that has a lot of validity. Yeah, and

734
00:39:10,440 --> 00:39:13,080
Speaker 1: and and I think part of you know, what doesn't

735
00:39:13,120 --> 00:39:16,799
Speaker 1: get mentioned in the context of predator control a good

736
00:39:17,960 --> 00:39:21,160
Speaker 1: deal is that you know, you're you're kind of putting

737
00:39:21,200 --> 00:39:24,160
Speaker 1: the fear of man in the in the population. And

738
00:39:24,640 --> 00:39:27,320
Speaker 1: in my mind, that's part of the value of the

739
00:39:27,440 --> 00:39:32,000
Speaker 1: proposed grizzly hunt, not to veer into even more uh,

740
00:39:32,440 --> 00:39:36,279
Speaker 1: conflict written territory. That's what that that's actually the name

741
00:39:36,320 --> 00:39:40,359
Speaker 1: of this podcast could be conflict ridden territory. But just fine.

742
00:39:40,719 --> 00:39:43,360
Speaker 1: But but you know, like where where I grew up

743
00:39:43,400 --> 00:39:48,120
Speaker 1: in in western Washington, we we thought that coyote hunting

744
00:39:48,239 --> 00:39:51,719
Speaker 1: and and hazing was good to perpect people's dogs and

745
00:39:51,800 --> 00:39:56,360
Speaker 1: cats and in you know, cattle ranching communities, like just

746
00:39:56,719 --> 00:40:01,000
Speaker 1: ripping shots at them at seven yards I think probably

747
00:40:01,320 --> 00:40:04,000
Speaker 1: helps those ranchers in some small way if they're doing

748
00:40:04,080 --> 00:40:07,560
Speaker 1: it consistently to make those coyotes think twice about coming

749
00:40:07,600 --> 00:40:12,600
Speaker 1: into the paddock to to mess with newly dropped calves.

750
00:40:12,719 --> 00:40:15,400
Speaker 1: And I mean, I'm sure it doesn't do anything for pheasants,

751
00:40:15,840 --> 00:40:19,840
Speaker 1: but um, you know they are they are very sneaky

752
00:40:19,920 --> 00:40:23,759
Speaker 1: and they can be extremely bold. Um And I think

753
00:40:23,800 --> 00:40:26,040
Speaker 1: in a lot of the you know, the suburban community

754
00:40:26,239 --> 00:40:30,040
Speaker 1: communities on the West and East coast, um, more hunting

755
00:40:30,920 --> 00:40:34,120
Speaker 1: and more pressure on them certainly could have a positive

756
00:40:34,160 --> 00:40:38,920
Speaker 1: and impact for reducing um, you know, conflicts with pets

757
00:40:39,000 --> 00:40:42,200
Speaker 1: and with people for sure. Yeah, yeah, there's a there's

758
00:40:42,200 --> 00:40:44,120
Speaker 1: a lot of angles. We're gonna get to Dan Flores.

759
00:40:44,160 --> 00:40:47,080
Speaker 1: He he brings a lot to the table in regards

760
00:40:47,120 --> 00:40:49,439
Speaker 1: to this specifically, in my mind, kind of the history

761
00:40:49,440 --> 00:40:52,480
Speaker 1: of the animal, some of our cultural ideas around the

762
00:40:52,520 --> 00:40:55,279
Speaker 1: animal um and can give us a little bit better

763
00:40:55,320 --> 00:40:57,560
Speaker 1: perspective in which to make these decisions. And that's the

764
00:40:57,600 --> 00:40:59,279
Speaker 1: reason I wanted to have them in here because my

765
00:40:59,440 --> 00:41:02,480
Speaker 1: personal feeling, much like Spencer saying it, because it's just

766
00:41:02,600 --> 00:41:04,799
Speaker 1: shifted a bit over the years. It went from one

767
00:41:05,440 --> 00:41:07,480
Speaker 1: one idea to another idea to now kind of a

768
00:41:08,000 --> 00:41:11,719
Speaker 1: you know, a more nebulous feeling about the animal, and

769
00:41:11,840 --> 00:41:14,440
Speaker 1: so it's good to have perspectives from folks like Dan.

770
00:41:15,760 --> 00:41:19,200
Speaker 1: But first, Phil, first play the work sharp. Not a

771
00:41:19,239 --> 00:41:23,480
Speaker 1: sharp moment, jingle, please work sharp. Not a sharp moment

772
00:41:23,800 --> 00:41:29,239
Speaker 1: sharp so you don't have to all right. Number four

773
00:41:30,200 --> 00:41:33,319
Speaker 1: not a sharp moment. We came last week. We had

774
00:41:33,360 --> 00:41:36,840
Speaker 1: a breast injury, We had a skunk running, and we

775
00:41:36,960 --> 00:41:41,319
Speaker 1: had truck stuck. Stuck truck stuck truck. Number four comes

776
00:41:41,440 --> 00:41:45,279
Speaker 1: from Chad Holder. Chad, there is a lot of things,

777
00:41:45,320 --> 00:41:47,319
Speaker 1: but I'm gonna kick it right off. He was born

778
00:41:47,320 --> 00:41:51,200
Speaker 1: in Utah. Of course, he loved hunting and loved the outdoors.

779
00:41:51,520 --> 00:41:55,680
Speaker 1: His one older brother, one younger brother. He's a middle child.

780
00:41:55,680 --> 00:41:57,320
Speaker 1: There plenty of times he got picked on by his

781
00:41:57,400 --> 00:42:01,080
Speaker 1: older brother, and he passes things down. Needs to say,

782
00:42:01,520 --> 00:42:04,080
Speaker 1: there wasn't too many serious moments. There's plenty of laughs.

783
00:42:05,080 --> 00:42:11,840
Speaker 1: The story begins in November. This is recent recent, not

784
00:42:12,040 --> 00:42:16,239
Speaker 1: so sharp. Recently. My older brother had an antler list

785
00:42:16,320 --> 00:42:18,880
Speaker 1: tag and a unit that I was somewhat familiar with,

786
00:42:19,320 --> 00:42:21,319
Speaker 1: so I was asked to join on a three day hunt.

787
00:42:21,840 --> 00:42:24,320
Speaker 1: First evening we saw a few elk, but it was

788
00:42:24,400 --> 00:42:27,480
Speaker 1: too dark to go after them the next morning, not

789
00:42:27,640 --> 00:42:30,839
Speaker 1: an elk to be found. That evening, we were driving

790
00:42:30,840 --> 00:42:32,440
Speaker 1: to go check a new area and came across a

791
00:42:32,560 --> 00:42:35,400
Speaker 1: herd of elk grazing in a clearing just off a

792
00:42:35,480 --> 00:42:38,200
Speaker 1: dirt road. My brother jumped out of the truck and

793
00:42:38,320 --> 00:42:40,200
Speaker 1: made his way to the small group of trees, too

794
00:42:40,239 --> 00:42:44,120
Speaker 1: close to close the distance and take the shot. He

795
00:42:44,200 --> 00:42:47,600
Speaker 1: picked out a cow, pull the trigger and missed. Second

796
00:42:47,640 --> 00:42:49,879
Speaker 1: shot at three or fifty yards, he hit the cow.

797
00:42:50,480 --> 00:42:52,719
Speaker 1: The herd took off and we made our way up

798
00:42:52,760 --> 00:42:56,320
Speaker 1: to where she was standing. We found blood. We followed

799
00:42:56,320 --> 00:42:58,480
Speaker 1: blood for five yards and could hear the elk in

800
00:42:58,520 --> 00:43:01,560
Speaker 1: the trees. Decided to act out and come back in

801
00:43:01,640 --> 00:43:05,960
Speaker 1: the morning because we weren't sure where the bullet struck. Devastated,

802
00:43:06,440 --> 00:43:09,400
Speaker 1: We made our way back to camp and decided to

803
00:43:09,760 --> 00:43:12,799
Speaker 1: heat up my sister in law's homemade mule deer chile

804
00:43:12,920 --> 00:43:16,359
Speaker 1: with lapenos. That's where this gets interesting, Phil, I think

805
00:43:16,400 --> 00:43:20,440
Speaker 1: it just sounds delicious gelapanos. Looking back, this may not

806
00:43:21,239 --> 00:43:23,719
Speaker 1: have been the best meal choice to consume, knowing we

807
00:43:23,800 --> 00:43:26,680
Speaker 1: needed to trail and elk the next morning, but as

808
00:43:26,719 --> 00:43:29,080
Speaker 1: you know, a warm, hearty meal on the cold night

809
00:43:29,160 --> 00:43:32,399
Speaker 1: seemed great. It still seems great. I don't see any

810
00:43:32,440 --> 00:43:35,120
Speaker 1: problems with this meal. So far in the so far okay.

811
00:43:35,400 --> 00:43:37,640
Speaker 1: The next morning we decided to pick up the blood trail,

812
00:43:37,880 --> 00:43:40,959
Speaker 1: and I noticed the cow left the herd shortly after.

813
00:43:41,080 --> 00:43:43,799
Speaker 1: We called it a night. Following behind my brother who

814
00:43:43,840 --> 00:43:46,480
Speaker 1: had a rifle. We were about a half mile on

815
00:43:46,600 --> 00:43:49,160
Speaker 1: her trail, with the wind blowing or right at us.

816
00:43:50,239 --> 00:43:53,440
Speaker 1: Just then I got a whiff of something that smelled

817
00:43:53,520 --> 00:43:56,680
Speaker 1: like something had died, But then it quickly went away.

818
00:43:58,840 --> 00:44:01,880
Speaker 1: Not much after that, I kept getting a terrible smell.

819
00:44:02,800 --> 00:44:06,200
Speaker 1: I whispered to my brother to stop. He looked at

820
00:44:06,239 --> 00:44:09,799
Speaker 1: me as the wafting smell hit my nostrils, and I said,

821
00:44:10,160 --> 00:44:14,359
Speaker 1: I smell something dead. My brother started to laugh harder

822
00:44:14,400 --> 00:44:17,319
Speaker 1: than I had ever seen him laugh. I couldn't figure

823
00:44:17,360 --> 00:44:21,480
Speaker 1: out why it was so funny. Apparently the chili had

824
00:44:21,600 --> 00:44:23,879
Speaker 1: some kind of reaction in his gut that caused him

825
00:44:23,920 --> 00:44:27,359
Speaker 1: to have the worst smelling gas known to the human man.

826
00:44:28,760 --> 00:44:30,680
Speaker 1: What I was what was wafting in my nose was

827
00:44:30,760 --> 00:44:32,800
Speaker 1: not the smell of a dead elk, but the smell

828
00:44:32,920 --> 00:44:36,320
Speaker 1: of his rotting insides. It's one thing to have a

829
00:44:36,400 --> 00:44:39,640
Speaker 1: sibling fart and you smell it. It's another thing when

830
00:44:39,719 --> 00:44:41,960
Speaker 1: you have when you think you're being an amazing tracker,

831
00:44:42,400 --> 00:44:45,240
Speaker 1: but all the while smelling something that came from another

832
00:44:45,320 --> 00:44:52,520
Speaker 1: person's butt hole. Some detail there. Unfortunately, we never found

833
00:44:52,560 --> 00:44:54,919
Speaker 1: the cow. She picked back up with a small herd

834
00:44:54,920 --> 00:44:57,080
Speaker 1: of elk, and after trailing her another mile of no

835
00:44:57,239 --> 00:44:59,440
Speaker 1: blood and just tracks, we decided to call it quits,

836
00:45:00,120 --> 00:45:02,720
Speaker 1: even with what time left in the season. He punched

837
00:45:02,760 --> 00:45:06,120
Speaker 1: his tag as to not be tempted to hunt again later.

838
00:45:06,920 --> 00:45:09,440
Speaker 1: That's pretty cool, needless to say. When in the mountains,

839
00:45:09,520 --> 00:45:11,439
Speaker 1: my brother likes to ask if I smell something dead.

840
00:45:12,239 --> 00:45:15,080
Speaker 1: I now know that when I hear that question to

841
00:45:15,239 --> 00:45:20,920
Speaker 1: not waft the air into my face. It's a good one.

842
00:45:21,000 --> 00:45:25,400
Speaker 1: Play the jingle sh not so sharp moment so you

843
00:45:25,640 --> 00:45:30,480
Speaker 1: don't have that was a good one. So chat holder,

844
00:45:31,080 --> 00:45:34,200
Speaker 1: We're going to send you of work, sharp field sharpener

845
00:45:34,280 --> 00:45:37,600
Speaker 1: for all your troubles. Send send me some of that chili. Yeah,

846
00:45:38,120 --> 00:45:39,320
Speaker 1: Phil and I would like to get some of that

847
00:45:39,480 --> 00:45:42,279
Speaker 1: hallapeno chili. Yes, please have that right here in the

848
00:45:42,320 --> 00:45:45,120
Speaker 1: podcast studio. We'll eat it on Mike, Eat it on

849
00:45:45,280 --> 00:45:49,879
Speaker 1: Mike and podcast where We're just wafting aired towards each

850
00:45:49,920 --> 00:45:53,360
Speaker 1: other's faces. All right, we're gonna get to a great,

851
00:45:53,520 --> 00:45:56,000
Speaker 1: great interview with a great great man. His name is

852
00:45:56,080 --> 00:45:59,680
Speaker 1: Dan Flores. He wrote a book called American Coot Coyote

853
00:45:59,760 --> 00:46:03,200
Speaker 1: on how you say it? Uh and in the West Coast.

854
00:46:03,320 --> 00:46:07,520
Speaker 1: Kid here it's coyote coyote. Yes, it's not wildly coyotepe.

855
00:46:08,160 --> 00:46:12,320
Speaker 1: All right, we're gonna go to Dan Flores a great interview.

856
00:46:13,160 --> 00:46:22,400
Speaker 1: Listen up. I guess I grew up on an alder row. Dan. Welcome,

857
00:46:22,520 --> 00:46:25,080
Speaker 1: Welcome to meet Eater. Thank you bad. It's a pleasure

858
00:46:25,080 --> 00:46:27,000
Speaker 1: to be here. Since the first time you've been to

859
00:46:27,280 --> 00:46:29,320
Speaker 1: I guess not welcome to meet Eater. That would be

860
00:46:29,400 --> 00:46:32,239
Speaker 1: a improper way to introduce you, because you've been You've

861
00:46:32,280 --> 00:46:33,960
Speaker 1: known Steven Ronella for quite a while, and you've been

862
00:46:33,960 --> 00:46:36,239
Speaker 1: a part of the Mediator brand for for years. I

863
00:46:36,280 --> 00:46:38,279
Speaker 1: mean I first listened to your podcast with Steve couple

864
00:46:38,280 --> 00:46:42,000
Speaker 1: of years ago, back in you got to know a

865
00:46:42,040 --> 00:46:44,800
Speaker 1: little bit about your work. But you have an interesting

866
00:46:44,880 --> 00:46:47,319
Speaker 1: history all around. But I think we should briefly get

867
00:46:47,400 --> 00:46:49,440
Speaker 1: to your history with Steve so you can come for

868
00:46:49,560 --> 00:46:52,680
Speaker 1: off on that. Then you have some some story stories

869
00:46:52,719 --> 00:46:55,719
Speaker 1: of post graduate Steve kind of what it was like

870
00:46:55,800 --> 00:46:58,600
Speaker 1: to know the man back then. Our listeners will be interested.

871
00:46:58,640 --> 00:47:00,520
Speaker 1: I'm sure to hear some of those stories. Well, I'm

872
00:47:00,560 --> 00:47:04,799
Speaker 1: one of the rare people who has known Steve since

873
00:47:04,920 --> 00:47:08,640
Speaker 1: the day when he was actually a graduate student. Um.

874
00:47:08,880 --> 00:47:11,840
Speaker 1: I was at the University of Montana, uh, professor in

875
00:47:11,880 --> 00:47:15,600
Speaker 1: the history department. Steve was graduate student in creative writing.

876
00:47:16,360 --> 00:47:20,480
Speaker 1: And because I taught environmental history and especially the environmental

877
00:47:20,560 --> 00:47:22,640
Speaker 1: history of the West, and he was interested in the

878
00:47:23,120 --> 00:47:25,959
Speaker 1: things that I was doing, he uh took a couple

879
00:47:25,960 --> 00:47:28,600
Speaker 1: of classes with me. I ended up serving actually on

880
00:47:28,800 --> 00:47:33,319
Speaker 1: his thesis committee. Uh and uh it's kind of helped

881
00:47:33,360 --> 00:47:36,880
Speaker 1: him get through graduation. But as I was telling you

882
00:47:37,400 --> 00:47:39,719
Speaker 1: a little earlier, I mean, I, you know, Steve and

883
00:47:39,760 --> 00:47:42,120
Speaker 1: I became friends back in those days. So I got

884
00:47:42,200 --> 00:47:45,440
Speaker 1: to have a few uh sort of small adventures with him,

885
00:47:45,920 --> 00:47:49,040
Speaker 1: meeting him at various bars in town and and uh

886
00:47:49,719 --> 00:47:52,440
Speaker 1: listening to tall tales. I mean, we some of our

887
00:47:52,480 --> 00:47:55,200
Speaker 1: early conversations. I had published a kind of a major

888
00:47:55,360 --> 00:47:58,800
Speaker 1: article in a academic journal about bison, and he was

889
00:47:58,880 --> 00:48:01,600
Speaker 1: already interested in a bison story, and so we would

890
00:48:01,680 --> 00:48:04,640
Speaker 1: sit in bars and uh and drink beer and talk

891
00:48:04,680 --> 00:48:08,760
Speaker 1: about Buffalo and where I think he was probably brainstorming

892
00:48:08,880 --> 00:48:12,560
Speaker 1: his Buffalo book of that. But uh, yeah, he was

893
00:48:12,920 --> 00:48:18,640
Speaker 1: an interesting, uh an unusual, almost eccentric graduate student who

894
00:48:18,680 --> 00:48:23,000
Speaker 1: would invite you over for dinners to eat squirrel that

895
00:48:23,120 --> 00:48:25,799
Speaker 1: he had peppered with a pellet gun in his backyard.

896
00:48:26,280 --> 00:48:28,160
Speaker 1: And uh, you know, there were a lot of interesting

897
00:48:28,239 --> 00:48:30,160
Speaker 1: people at the University of Mountain in those days, but

898
00:48:30,480 --> 00:48:33,719
Speaker 1: I don't think anybody quite rose to that level. And

899
00:48:33,760 --> 00:48:36,600
Speaker 1: I would, like I said, I've I've chosen to join

900
00:48:36,960 --> 00:48:38,560
Speaker 1: that man in this venture. So it's good to have

901
00:48:38,600 --> 00:48:40,800
Speaker 1: a little insight to what what he was before I

902
00:48:40,880 --> 00:48:44,080
Speaker 1: knew him. But there's a lot of your history that

903
00:48:44,120 --> 00:48:46,560
Speaker 1: we gotta get to. And like I was saying before,

904
00:48:46,600 --> 00:48:49,759
Speaker 1: we hopefully folks that have either listened to the Joe

905
00:48:49,880 --> 00:48:52,719
Speaker 1: Rogan podcast that you were on or listen to the

906
00:48:52,760 --> 00:48:55,880
Speaker 1: Mediator podcasts that you're on, are generally familiar with your

907
00:48:55,920 --> 00:48:59,320
Speaker 1: book Coyote America kind of your work in that realm.

908
00:48:59,400 --> 00:49:01,440
Speaker 1: But what I wanted to do, maybe differently in this

909
00:49:01,520 --> 00:49:03,680
Speaker 1: is just find a little bit about you and how

910
00:49:03,760 --> 00:49:07,160
Speaker 1: you got to that point one when you met Steve,

911
00:49:07,200 --> 00:49:10,600
Speaker 1: when you're deeply you know, immersed in the history of

912
00:49:10,680 --> 00:49:14,480
Speaker 1: this country and like the wild places Florida and fauna,

913
00:49:14,480 --> 00:49:17,400
Speaker 1: and how you got interested in that and why it became,

914
00:49:18,000 --> 00:49:20,400
Speaker 1: you know, something that mattered in your life. And so

915
00:49:20,560 --> 00:49:23,080
Speaker 1: it's all starts. You're telling me some stories about Louisiana.

916
00:49:23,719 --> 00:49:26,839
Speaker 1: It all starts. And as a boy in Louisiana, where

917
00:49:26,920 --> 00:49:29,640
Speaker 1: where were you born? Exactly? Well, I was born in

918
00:49:29,719 --> 00:49:32,799
Speaker 1: a place that most of your listeners will have never

919
00:49:32,920 --> 00:49:37,480
Speaker 1: heard of, a town called vivian Uh in northwestern Louisiana,

920
00:49:37,600 --> 00:49:41,359
Speaker 1: which is just up north of Streeports. My family had

921
00:49:41,440 --> 00:49:46,360
Speaker 1: been in Louisiana really since the founding of Louisiana. My

922
00:49:46,719 --> 00:49:49,839
Speaker 1: first ancestors had gotten there in seventeen sixteen, so we've

923
00:49:49,880 --> 00:49:52,960
Speaker 1: actually been there for more than three hundred years um.

924
00:49:53,680 --> 00:49:56,960
Speaker 1: But we had moved. We had been in the Nakadash area,

925
00:49:57,000 --> 00:49:59,959
Speaker 1: which is the original European town in Louisiana, so before

926
00:50:00,080 --> 00:50:02,560
Speaker 1: years older than New Orleans. It's a beautiful area too. Yeah,

927
00:50:02,600 --> 00:50:05,279
Speaker 1: it's really a pretty area. And so that's where my

928
00:50:05,520 --> 00:50:09,959
Speaker 1: family was from, from Nackos. But we had moved during

929
00:50:10,040 --> 00:50:13,440
Speaker 1: the thirties up to the Shreveport area because my granddad

930
00:50:13,480 --> 00:50:15,839
Speaker 1: had gotten a job of standard oil when the East

931
00:50:15,880 --> 00:50:19,120
Speaker 1: Texas oil field came in, And so that's where I

932
00:50:19,480 --> 00:50:24,760
Speaker 1: ended up growing up in northwestern Louisiana, with East Texas

933
00:50:24,800 --> 00:50:28,320
Speaker 1: about four or five miles away and Arkansas about about

934
00:50:28,360 --> 00:50:31,720
Speaker 1: the same distance way, and it was kind of as

935
00:50:31,760 --> 00:50:34,800
Speaker 1: a kid, I was always somewhat proud to be in

936
00:50:35,280 --> 00:50:39,160
Speaker 1: Louisiana with its interesting colonial history rather than those other

937
00:50:39,200 --> 00:50:41,400
Speaker 1: two places. Yeah, and it's got a rich is not

938
00:50:41,520 --> 00:50:45,399
Speaker 1: only rich history, but a rich culture, you know that. Yeah,

939
00:50:45,480 --> 00:50:48,000
Speaker 1: that we all understand kind of in the lexicon of

940
00:50:48,320 --> 00:50:51,719
Speaker 1: of American culture as a whole. We understand like these

941
00:50:51,880 --> 00:50:54,840
Speaker 1: these micro points that are very interesting. Texas has a

942
00:50:54,960 --> 00:50:57,400
Speaker 1: very interesting culture, but I think Louisiana maybe at the

943
00:50:57,440 --> 00:50:59,640
Speaker 1: top of the list. There's a reason that every reality

944
00:50:59,680 --> 00:51:02,959
Speaker 1: show the Discovery Channel is dudes in Louisiana doing something.

945
00:51:03,120 --> 00:51:08,120
Speaker 1: Oh yeah, those dudes are pretty far out for one thing. Yeah,

946
00:51:08,400 --> 00:51:10,920
Speaker 1: it's got an interesting history. I mean it starts as

947
00:51:10,960 --> 00:51:14,480
Speaker 1: a French colony. Uh, It's Louisiana is owned by Spain

948
00:51:14,680 --> 00:51:16,919
Speaker 1: for about forty years. I mean a lot of people

949
00:51:17,000 --> 00:51:21,160
Speaker 1: don't know that, but um, I mean when the United

950
00:51:21,160 --> 00:51:27,359
Speaker 1: States requires Louisiana from France from Napoleon in eighteen oh three. Um,

951
00:51:27,640 --> 00:51:31,080
Speaker 1: in order for Napoleon to sell Louisiana to the United States,

952
00:51:31,360 --> 00:51:35,080
Speaker 1: he had to get it back from Spain two years earlier,

953
00:51:35,440 --> 00:51:38,279
Speaker 1: because Spain had had it up until eighteen hundred. So

954
00:51:38,960 --> 00:51:41,880
Speaker 1: it's got a very interesting mix. New Orleans was a

955
00:51:41,960 --> 00:51:44,200
Speaker 1: kind of a cause of fault in place that attracted

956
00:51:44,239 --> 00:51:47,880
Speaker 1: folks like San Francisco from all over the world. I

957
00:51:47,960 --> 00:51:50,919
Speaker 1: mean there's an Irish quarter in New Orleans, and there's

958
00:51:50,920 --> 00:51:54,799
Speaker 1: an Italian quarter, and so it's a it's always been

959
00:51:54,880 --> 00:51:59,600
Speaker 1: a kind of an interesting mix of people and uh,

960
00:51:59,680 --> 00:52:03,279
Speaker 1: with a lot of different languages spoken. I mean, Um,

961
00:52:04,239 --> 00:52:07,719
Speaker 1: I didn't grow up speaking French, but two or three

962
00:52:07,760 --> 00:52:11,000
Speaker 1: generations back in my family they still spoke French. They

963
00:52:11,040 --> 00:52:13,719
Speaker 1: were Catholics. I mean it was the you know, the

964
00:52:13,880 --> 00:52:19,239
Speaker 1: classic kind of Louisiana colonial world that my family came through. Yeah,

965
00:52:19,360 --> 00:52:22,640
Speaker 1: and your your first kind of introduction to the outside

966
00:52:22,680 --> 00:52:24,600
Speaker 1: world in Louisiana. I'm sure there's a lot of past

967
00:52:24,719 --> 00:52:27,000
Speaker 1: you could take, But what do you remember your first

968
00:52:27,080 --> 00:52:30,640
Speaker 1: kind of as a child, you know, insights into going

969
00:52:30,680 --> 00:52:36,480
Speaker 1: outside doing things in Louisiana. Well, I remember, um, I

970
00:52:36,560 --> 00:52:40,759
Speaker 1: remember having to in order to see out of the

971
00:52:41,160 --> 00:52:45,160
Speaker 1: thickness of the forest. Uh. Finding a hill which I

972
00:52:45,280 --> 00:52:47,480
Speaker 1: located when I was probably about seven eight years old

973
00:52:47,560 --> 00:52:50,920
Speaker 1: riding my bicycle, I found one of the highest hills

974
00:52:51,400 --> 00:52:54,080
Speaker 1: in the Red River Valley, on the edge of the

975
00:52:54,120 --> 00:52:57,480
Speaker 1: Red River Valley, and I would go ride my bicycle

976
00:52:57,560 --> 00:52:59,239
Speaker 1: to this hill, climb up to the top of it,

977
00:52:59,600 --> 00:53:02,320
Speaker 1: and then climbed to the top of the highest tree

978
00:53:02,719 --> 00:53:05,680
Speaker 1: on that hill so I could get above the vegetation

979
00:53:06,280 --> 00:53:09,920
Speaker 1: and see out across the landscape, I mean, And that

980
00:53:10,080 --> 00:53:13,960
Speaker 1: became kind of a uh, kind of a touchstone for

981
00:53:14,160 --> 00:53:16,360
Speaker 1: me for many, many years, even when I was in

982
00:53:16,880 --> 00:53:19,400
Speaker 1: college and graduate school. Almost every time I would go

983
00:53:19,480 --> 00:53:22,160
Speaker 1: back to Louisiana to see my folks, I would go

984
00:53:22,400 --> 00:53:25,080
Speaker 1: to that particular hill and climb up in that tree

985
00:53:25,719 --> 00:53:28,640
Speaker 1: just so I could get a view of the country.

986
00:53:28,719 --> 00:53:32,200
Speaker 1: Because I think what I was hungry for was what

987
00:53:32,400 --> 00:53:35,520
Speaker 1: I ultimately found by moving to the west, which was

988
00:53:35,719 --> 00:53:40,080
Speaker 1: a way to get to see the countryside spread out

989
00:53:40,280 --> 00:53:44,439
Speaker 1: for miles and miles distant. And uh, I mean, there's

990
00:53:44,920 --> 00:53:48,080
Speaker 1: there's kind of an explanation really in my own experiences

991
00:53:48,120 --> 00:53:50,000
Speaker 1: as a kid for why that happened. When I was

992
00:53:50,120 --> 00:53:52,239
Speaker 1: four years old, and I didn't find this out until

993
00:53:52,239 --> 00:53:54,920
Speaker 1: I was about thirty eight. Going back to Louisiana to

994
00:53:55,040 --> 00:53:58,400
Speaker 1: a family reunion, I mentioned to an aunt of mine that,

995
00:53:58,800 --> 00:54:00,799
Speaker 1: you know, I'd just been fast and with the West

996
00:54:00,840 --> 00:54:03,600
Speaker 1: and it dreamed about the West since I was four

997
00:54:03,680 --> 00:54:06,080
Speaker 1: or five or six years old. And she said, well,

998
00:54:06,120 --> 00:54:07,680
Speaker 1: I wonder if that had anything to do with the

999
00:54:07,760 --> 00:54:10,759
Speaker 1: fact that we took you out to West Texas in

1000
00:54:10,840 --> 00:54:15,759
Speaker 1: New Mexico when you were four I and all of

1001
00:54:15,800 --> 00:54:17,920
Speaker 1: a sudden it began to come back to me. They

1002
00:54:17,960 --> 00:54:21,640
Speaker 1: were my earliest memories as a kid of being at

1003
00:54:21,719 --> 00:54:26,440
Speaker 1: the foot of big, towering red cliffs with a cobalt

1004
00:54:26,600 --> 00:54:30,759
Speaker 1: blue sky and these white cotton ball clouds in the sky,

1005
00:54:31,520 --> 00:54:34,360
Speaker 1: and I had I knew that landscape wasn't in Louisiana,

1006
00:54:35,200 --> 00:54:37,920
Speaker 1: and suddenly I realized it was because when I was

1007
00:54:38,040 --> 00:54:40,520
Speaker 1: four years old, my family had taken me to the

1008
00:54:40,600 --> 00:54:43,799
Speaker 1: West and that had given me a fascination I never

1009
00:54:43,920 --> 00:54:47,000
Speaker 1: really let go of. Yeah, that's interesting when you think

1010
00:54:47,040 --> 00:54:49,000
Speaker 1: of why, you know, why is you do these things?

1011
00:54:49,040 --> 00:54:52,000
Speaker 1: And what what about a singular visit when you were

1012
00:54:52,000 --> 00:54:53,560
Speaker 1: four years old? Of all the things in the four

1013
00:54:53,640 --> 00:54:57,560
Speaker 1: year old psyche that could attach itself to like your

1014
00:54:57,640 --> 00:55:00,800
Speaker 1: future motivations. Why is it that that that picture you

1015
00:55:00,880 --> 00:55:03,880
Speaker 1: just so well painted is exactly, you know, kind of

1016
00:55:03,960 --> 00:55:06,680
Speaker 1: what led you later in life, much later in life,

1017
00:55:06,719 --> 00:55:08,880
Speaker 1: becomes kind of a motive to go west. And I

1018
00:55:09,000 --> 00:55:11,239
Speaker 1: think probably, you know, as I've looked back on it

1019
00:55:11,360 --> 00:55:15,360
Speaker 1: and thought about it and tried to pull those memories

1020
00:55:15,520 --> 00:55:18,880
Speaker 1: up from my deep subconscious I think it probably had

1021
00:55:18,920 --> 00:55:21,160
Speaker 1: to do with the fact that that landscape was so

1022
00:55:21,400 --> 00:55:27,000
Speaker 1: dramatically different in the West than this green, verdant, densely

1023
00:55:27,160 --> 00:55:31,560
Speaker 1: vegetated world that I had grown up. Uh and in Louisiana. Yeah,

1024
00:55:32,160 --> 00:55:35,120
Speaker 1: And that's one thing that's it's interesting. I mean, you

1025
00:55:35,239 --> 00:55:38,200
Speaker 1: end up as a history of America, of the American West,

1026
00:55:38,280 --> 00:55:42,560
Speaker 1: professor of all these things coming from that talk about

1027
00:55:43,040 --> 00:55:47,120
Speaker 1: in Louisiana, your experiences outside, Like who drove those things

1028
00:55:47,200 --> 00:55:50,200
Speaker 1: for you? Was it? Was it your parents? Was it friends? Like?

1029
00:55:50,440 --> 00:55:53,040
Speaker 1: What what was the core of your of your going

1030
00:55:53,080 --> 00:55:56,279
Speaker 1: outside and being interested in the outside world when you're

1031
00:55:56,520 --> 00:55:59,719
Speaker 1: coming up. Well, part of it was growing up in

1032
00:55:59,800 --> 00:56:05,879
Speaker 1: a small town where the margins of the forest were

1033
00:56:06,360 --> 00:56:10,719
Speaker 1: within a couple of hundred yards of my parents home,

1034
00:56:11,239 --> 00:56:15,560
Speaker 1: and so as soon as they began as my parents

1035
00:56:15,640 --> 00:56:18,359
Speaker 1: began to let me, you know, venture out a little

1036
00:56:18,400 --> 00:56:22,919
Speaker 1: bit on a bicycle are walking. I mean, I immediately

1037
00:56:23,120 --> 00:56:26,600
Speaker 1: was drawn to the streams and the woods and the

1038
00:56:26,719 --> 00:56:31,520
Speaker 1: bayous that were just very easily accessible to a kid

1039
00:56:32,120 --> 00:56:36,200
Speaker 1: just walking fifteen or twenty minutes away from home. Um.

1040
00:56:36,480 --> 00:56:43,680
Speaker 1: It wasn't that my parents are grandparents were particularly outdoorsy.

1041
00:56:44,200 --> 00:56:47,480
Speaker 1: I mean my dad was. He was way into sports

1042
00:56:47,760 --> 00:56:51,480
Speaker 1: and uh and I mean and I played uh football,

1043
00:56:51,560 --> 00:56:54,040
Speaker 1: basketball and baseball in high school. And so I did

1044
00:56:54,120 --> 00:56:56,960
Speaker 1: all the things you know, that he was interested in,

1045
00:56:57,080 --> 00:56:59,920
Speaker 1: and that I was certainly interested in too. I had

1046
00:57:00,239 --> 00:57:06,920
Speaker 1: an older brother who was also, um, probably more interested

1047
00:57:07,000 --> 00:57:10,719
Speaker 1: in nature and the wilds than mom and dad were,

1048
00:57:11,120 --> 00:57:13,600
Speaker 1: and he provided a little bit of a kind of

1049
00:57:13,719 --> 00:57:17,200
Speaker 1: a an incentive to follow in his footsteps. But I

1050
00:57:17,280 --> 00:57:20,640
Speaker 1: mean he for example, when he was fourteen fifteen years old,

1051
00:57:20,720 --> 00:57:23,200
Speaker 1: he and his friends built a cabin out in the

1052
00:57:23,280 --> 00:57:26,440
Speaker 1: woods on my granddad's land a couple of miles away.

1053
00:57:26,880 --> 00:57:29,360
Speaker 1: And I mean I did the same thing when I

1054
00:57:29,560 --> 00:57:32,720
Speaker 1: was about that age. Buddies of mine and I were

1055
00:57:32,800 --> 00:57:35,040
Speaker 1: always roaming through the woods looking for a place to

1056
00:57:35,080 --> 00:57:37,920
Speaker 1: build a cabin. Uh. And we did that uh and

1057
00:57:38,000 --> 00:57:39,920
Speaker 1: we burned it up the very first night we stayed

1058
00:57:39,960 --> 00:57:43,800
Speaker 1: in it. But uh so, I think in a way,

1059
00:57:43,840 --> 00:57:47,840
Speaker 1: my brother probably played some role in in uh luring

1060
00:57:47,920 --> 00:57:49,680
Speaker 1: me out, But a lot of it was just the

1061
00:57:49,800 --> 00:57:52,880
Speaker 1: accessibility of it, you know. And I was in a

1062
00:57:53,000 --> 00:57:55,000
Speaker 1: town that was small enough that we couldn't even feel

1063
00:57:55,040 --> 00:57:57,080
Speaker 1: one baseball team in the summer a little too to

1064
00:57:57,160 --> 00:58:00,320
Speaker 1: play one another, And so you had to enter attain

1065
00:58:00,440 --> 00:58:04,800
Speaker 1: yourself pretty much. And I basically entertained myself by going

1066
00:58:04,840 --> 00:58:08,080
Speaker 1: out in nature and reading. I mean, I read a

1067
00:58:08,160 --> 00:58:11,920
Speaker 1: lot of books as a kid. I sort of I

1068
00:58:12,120 --> 00:58:16,200
Speaker 1: roamed the larger world through the pages of literature. I mean,

1069
00:58:16,280 --> 00:58:20,040
Speaker 1: we had a local library. Uh my dad became the

1070
00:58:20,120 --> 00:58:24,320
Speaker 1: librarian after he retired, and uh so I would read

1071
00:58:24,520 --> 00:58:27,120
Speaker 1: twenty or thirty or forty books every summer and and

1072
00:58:27,400 --> 00:58:30,000
Speaker 1: uh and mornings and evenings, and when it was a

1073
00:58:30,040 --> 00:58:33,160
Speaker 1: little easier to be outside and a humid, hot place

1074
00:58:33,280 --> 00:58:37,040
Speaker 1: like Louisiana, I would go out into the woods Louisia.

1075
00:58:37,080 --> 00:58:39,480
Speaker 1: I spent a lot of time in Louisiana. You setting

1076
00:58:39,480 --> 00:58:42,040
Speaker 1: my ass off. Do you you feel like we had

1077
00:58:42,080 --> 00:58:47,040
Speaker 1: a herpetologist last episode, Harry Green, we're talking about him

1078
00:58:47,040 --> 00:58:50,440
Speaker 1: a little bit at launch today. He talked about when

1079
00:58:50,440 --> 00:58:52,560
Speaker 1: I was asking him these same types of questions a

1080
00:58:52,640 --> 00:58:56,480
Speaker 1: little bit, exploring the genesis of his like wondering about nature,

1081
00:58:57,480 --> 00:58:59,760
Speaker 1: and he talked about picking up a box turtle and saying, mom,

1082
00:58:59,800 --> 00:59:02,720
Speaker 1: why doesn't have ears? And like that. It seemed to

1083
00:59:02,760 --> 00:59:04,720
Speaker 1: me that he was interested in the micro, the micro

1084
00:59:04,880 --> 00:59:08,560
Speaker 1: details of being outside. And maybe correct me if I'm wrong,

1085
00:59:08,600 --> 00:59:10,840
Speaker 1: but it seems like you were more interested in the vastness,

1086
00:59:10,960 --> 00:59:13,800
Speaker 1: like the perspective that it gave, rather than maybe the

1087
00:59:13,880 --> 00:59:19,520
Speaker 1: intricate details. Is that true? I think that's probably true. Um,

1088
00:59:20,280 --> 00:59:23,520
Speaker 1: I mean I was. I was interested in the in

1089
00:59:23,600 --> 00:59:27,320
Speaker 1: the small details for sure. I mean because I I

1090
00:59:27,440 --> 00:59:33,880
Speaker 1: paid attention to two birds I found uh and very

1091
00:59:33,960 --> 00:59:39,920
Speaker 1: closely looked at the feather patterns and arrangements on flickers

1092
00:59:40,040 --> 00:59:44,200
Speaker 1: and meadow larks, and so I I was. I was

1093
00:59:44,280 --> 00:59:49,080
Speaker 1: certainly focused on my new details. But I think in

1094
00:59:49,320 --> 00:59:53,240
Speaker 1: terms of landscape, what I was endlessly trying to do

1095
00:59:53,880 --> 00:59:58,000
Speaker 1: in a place that was so enclosed was get a

1096
00:59:58,600 --> 01:00:03,640
Speaker 1: larger look at some of the patterns of the topography.

1097
01:00:03,880 --> 01:00:08,000
Speaker 1: And Louisiana was so dense with vegetation that it was

1098
01:00:08,240 --> 01:00:11,040
Speaker 1: hard to get that. I mean, you sometimes couldn't see

1099
01:00:11,080 --> 01:00:13,520
Speaker 1: more than a hundred feet through the woods, and it

1100
01:00:13,680 --> 01:00:16,640
Speaker 1: was you You didn't know you were climbing on a hill,

1101
01:00:16,840 --> 01:00:19,120
Speaker 1: for example, until you were halfway up it, and then

1102
01:00:19,200 --> 01:00:22,000
Speaker 1: you you began to realize, just as a result of

1103
01:00:22,080 --> 01:00:25,840
Speaker 1: the ascent, that the topography had changed. So for some reason,

1104
01:00:25,920 --> 01:00:29,800
Speaker 1: and I'm not quite sure exactly why I was intrigued

1105
01:00:29,880 --> 01:00:34,640
Speaker 1: by topography and views big views. I mean, I've sort

1106
01:00:34,680 --> 01:00:37,360
Speaker 1: of speculated in a couple of my books that it

1107
01:00:37,440 --> 01:00:39,920
Speaker 1: has something to do with, you know, genetic memories. I mean,

1108
01:00:39,960 --> 01:00:42,400
Speaker 1: I think people all over the world, because we evolved

1109
01:00:42,480 --> 01:00:47,680
Speaker 1: in on the African savannah, what we find really compelling

1110
01:00:47,880 --> 01:00:51,320
Speaker 1: everywhere in the world are open landscapes where you have

1111
01:00:51,960 --> 01:00:55,560
Speaker 1: herds of animals and predators and that sort of thing.

1112
01:00:55,640 --> 01:00:58,800
Speaker 1: And I think, without understanding why I wanted to do that,

1113
01:00:59,400 --> 01:01:02,960
Speaker 1: I always had this need to be able to see. Yeah,

1114
01:01:03,240 --> 01:01:05,680
Speaker 1: and when you do you know, a weekly podcast like

1115
01:01:05,760 --> 01:01:07,520
Speaker 1: I do you all we often repeat things, so I

1116
01:01:07,600 --> 01:01:10,400
Speaker 1: apologize the listeners, but it's the same as we We've taught.

1117
01:01:10,480 --> 01:01:14,280
Speaker 1: Had some conversations around human evolutionary biology, where like, why

1118
01:01:14,360 --> 01:01:16,480
Speaker 1: does a little kid pick up a rock? And why

1119
01:01:16,520 --> 01:01:19,520
Speaker 1: does it? Why is his first thought before he even

1120
01:01:19,560 --> 01:01:21,320
Speaker 1: thought about what he's gonna do with that rocky, it's

1121
01:01:21,440 --> 01:01:24,880
Speaker 1: hurling it through the air. Why is he doing that? Well?

1122
01:01:24,880 --> 01:01:27,160
Speaker 1: Because that's what on the African Savannah, that's how we

1123
01:01:27,240 --> 01:01:30,480
Speaker 1: first understood that we could affect things that weren't directly

1124
01:01:30,560 --> 01:01:33,360
Speaker 1: in front of us much the same way. So I

1125
01:01:33,400 --> 01:01:36,000
Speaker 1: think it's important to explore those thoughts that we've had

1126
01:01:36,080 --> 01:01:38,280
Speaker 1: when we were you know, you've you've written so much

1127
01:01:38,320 --> 01:01:41,040
Speaker 1: an impact that so many people, so many people this

1128
01:01:41,120 --> 01:01:45,400
Speaker 1: audience and others, about American history and about some some species,

1129
01:01:45,480 --> 01:01:48,320
Speaker 1: like the Code and in their history. It's important to

1130
01:01:48,360 --> 01:01:51,160
Speaker 1: understanding those things like why why you bent that way

1131
01:01:51,480 --> 01:01:53,960
Speaker 1: when you did? And I always managed somewhere in my

1132
01:01:54,120 --> 01:01:58,600
Speaker 1: books to get some paragraphs or pages have that ilk

1133
01:01:58,760 --> 01:02:03,240
Speaker 1: in because I think it's important to understand who we

1134
01:02:03,400 --> 01:02:07,520
Speaker 1: are as a species, because it helps us get a

1135
01:02:07,600 --> 01:02:09,760
Speaker 1: handle on our motives on why we do some of

1136
01:02:09,800 --> 01:02:12,640
Speaker 1: the things we do. One of your favorite from Coyote

1137
01:02:12,720 --> 01:02:19,120
Speaker 1: America your books was published one of the favorite passages,

1138
01:02:19,160 --> 01:02:21,520
Speaker 1: and you're talking about being in as a boy, being

1139
01:02:21,520 --> 01:02:25,000
Speaker 1: in suburban Louisiana reading the newspaper and you had you

1140
01:02:25,080 --> 01:02:27,640
Speaker 1: had an encounter with a couple of coyotes. Tell people

1141
01:02:27,680 --> 01:02:32,120
Speaker 1: about that one. Well, I was, I was, I think

1142
01:02:32,160 --> 01:02:37,160
Speaker 1: about thirteen years old. UM and so uh and this

1143
01:02:37,360 --> 01:02:42,160
Speaker 1: is probably this is this probably planted the seed of

1144
01:02:42,720 --> 01:02:46,560
Speaker 1: ultimately writing a book about these animals. UM. I had

1145
01:02:46,680 --> 01:02:51,560
Speaker 1: seen the year before Walt Disney. Um. It was called

1146
01:02:51,600 --> 01:02:54,880
Speaker 1: Walt Disney Presents. At the time, it hadn't quite yet

1147
01:02:54,960 --> 01:02:58,880
Speaker 1: become the Wonderful World of Color. But Walt Disney did

1148
01:02:59,480 --> 01:03:03,960
Speaker 1: the first to what became six of his coyote films

1149
01:03:04,040 --> 01:03:06,000
Speaker 1: in the sixties and seventies, and it was called The

1150
01:03:06,120 --> 01:03:09,800
Speaker 1: Coyotes Lament. And I had sat and watched it. It's

1151
01:03:09,880 --> 01:03:14,440
Speaker 1: this kind of hour long animated cartoon where Walt Disney's

1152
01:03:14,680 --> 01:03:17,960
Speaker 1: the size it. He's going to tell the coyote side

1153
01:03:18,040 --> 01:03:21,040
Speaker 1: of the story of American settlement. And so it's kind

1154
01:03:21,040 --> 01:03:24,000
Speaker 1: of a remarkable film. You can, by the way, Google

1155
01:03:24,040 --> 01:03:27,840
Speaker 1: it's on YouTube. You can watch it. Um. And so

1156
01:03:28,680 --> 01:03:32,000
Speaker 1: I had watched that. I was fascinated by what I

1157
01:03:32,120 --> 01:03:34,320
Speaker 1: had seen. I was fascinated with the animals. But of

1158
01:03:34,400 --> 01:03:37,320
Speaker 1: course the film portrays these animals as animals of the West.

1159
01:03:37,960 --> 01:03:39,920
Speaker 1: And you know, since I had been four or five

1160
01:03:40,000 --> 01:03:42,840
Speaker 1: years old. I've been intrigued by the West, and I

1161
01:03:42,960 --> 01:03:46,880
Speaker 1: had had the experience UH some time along then of

1162
01:03:47,560 --> 01:03:52,080
Speaker 1: UH driving with my folks down Highway one and UH

1163
01:03:52,200 --> 01:03:55,160
Speaker 1: south of Shreveport or north of Shreveport, I think, and

1164
01:03:55,280 --> 01:03:58,520
Speaker 1: we had seen a cane had run over on the road,

1165
01:03:58,600 --> 01:04:00,520
Speaker 1: and I could tell as we went by it wasn't

1166
01:04:00,800 --> 01:04:02,960
Speaker 1: a dog, And so I made my folks stopped car,

1167
01:04:03,040 --> 01:04:04,440
Speaker 1: I got out and went out and looked, and it

1168
01:04:04,560 --> 01:04:07,320
Speaker 1: was a gray fox. And I've been really intrigued by

1169
01:04:08,560 --> 01:04:10,919
Speaker 1: looking at this animal. In fact, I think I made

1170
01:04:11,080 --> 01:04:12,840
Speaker 1: Mom and Dad open the trunk and let me take

1171
01:04:12,880 --> 01:04:14,640
Speaker 1: it home, and I scanned it and made a rug

1172
01:04:14,720 --> 01:04:17,240
Speaker 1: out of it, and I was really intrigued by it.

1173
01:04:17,840 --> 01:04:20,560
Speaker 1: And so I mentioned to a local hardware store owner

1174
01:04:20,600 --> 01:04:24,040
Speaker 1: a few days later that you know, I'd love to

1175
01:04:24,160 --> 01:04:27,160
Speaker 1: see a fox out in the woods, and he said, well,

1176
01:04:27,400 --> 01:04:31,320
Speaker 1: you know, we just got this thing in It's only

1177
01:04:31,400 --> 01:04:34,280
Speaker 1: a couple of bucks. Why don't you buy it. It's

1178
01:04:34,400 --> 01:04:37,640
Speaker 1: a it's a call that sounds like a dying rabbit,

1179
01:04:38,280 --> 01:04:40,120
Speaker 1: and you could take it out in the woods and

1180
01:04:40,160 --> 01:04:41,800
Speaker 1: you might be able to call up a fox and

1181
01:04:41,880 --> 01:04:44,880
Speaker 1: see one. So I paid two dollars for this thing,

1182
01:04:45,120 --> 01:04:48,200
Speaker 1: and a few days later rode my bicycle out climbed

1183
01:04:48,280 --> 01:04:50,640
Speaker 1: up in this OTLD deer stand that I knew about,

1184
01:04:52,000 --> 01:04:54,680
Speaker 1: blew about three or four times on this call, not

1185
01:04:54,840 --> 01:04:57,360
Speaker 1: of course knowing exactly what a dying rabbit sounded like.

1186
01:04:57,560 --> 01:05:00,040
Speaker 1: But you didn't have to be too accurate with it

1187
01:05:00,240 --> 01:05:04,959
Speaker 1: turned out, because within about thirty seconds this animal comes

1188
01:05:05,120 --> 01:05:09,240
Speaker 1: trotting out of the woods about seventy five yards from me,

1189
01:05:09,600 --> 01:05:12,720
Speaker 1: headed straight for the tree I was sitting in, and

1190
01:05:12,760 --> 01:05:15,360
Speaker 1: I mean it was coming with a purpose. Its ears

1191
01:05:15,440 --> 01:05:19,160
Speaker 1: were up. I still remember these vivid sort of orange

1192
01:05:19,280 --> 01:05:23,520
Speaker 1: yellow eyes. Uh. It crossed through a clearing where the

1193
01:05:23,640 --> 01:05:25,760
Speaker 1: sun was shining, and I could see this kind of

1194
01:05:25,880 --> 01:05:30,040
Speaker 1: chestnut fur rippling on it, and I was absolutely thunderstruck

1195
01:05:30,120 --> 01:05:32,280
Speaker 1: by the side of it. And it got within about

1196
01:05:32,400 --> 01:05:35,120
Speaker 1: probably twenty ft of the tree, and I think some

1197
01:05:35,280 --> 01:05:37,560
Speaker 1: sort of down draft maybe took my scent to it,

1198
01:05:37,840 --> 01:05:40,280
Speaker 1: and all of a sudden, just as purposefully as it

1199
01:05:40,360 --> 01:05:44,000
Speaker 1: was coming towards me, it whirled and took off, loping

1200
01:05:44,120 --> 01:05:47,560
Speaker 1: back the direction it had come, and was in characteristic

1201
01:05:47,640 --> 01:05:51,360
Speaker 1: while cane and fashion, looking back over its shoulder, trying

1202
01:05:51,440 --> 01:05:54,560
Speaker 1: to discern where the danger was coming from that it

1203
01:05:54,640 --> 01:05:57,560
Speaker 1: had smelled, And so I watched this thing lope out

1204
01:05:57,600 --> 01:06:00,840
Speaker 1: of sight and sat there shake like a leaf for

1205
01:06:00,920 --> 01:06:03,600
Speaker 1: about three or four minutes, and then I climbed down

1206
01:06:03,640 --> 01:06:05,120
Speaker 1: from the tree and went home and wrote a letter

1207
01:06:05,160 --> 01:06:08,520
Speaker 1: to louising In Parks and Wildlife and said, I think

1208
01:06:08,560 --> 01:06:12,120
Speaker 1: I saw a wolf in Cattle Parish today. And I

1209
01:06:12,240 --> 01:06:15,560
Speaker 1: got a letter back about about two weeks later where

1210
01:06:15,920 --> 01:06:18,960
Speaker 1: someone in that department said, well, you might have seen

1211
01:06:19,040 --> 01:06:21,320
Speaker 1: a wolf. I mean, we think there might still be

1212
01:06:21,640 --> 01:06:24,360
Speaker 1: some red wolves up in that part of the state,

1213
01:06:24,960 --> 01:06:27,680
Speaker 1: but it's much more likely that what you saw was

1214
01:06:28,040 --> 01:06:33,320
Speaker 1: a coyote, because those animals are now colonizing Louisianna. And

1215
01:06:33,560 --> 01:06:36,080
Speaker 1: I thought, I mean, so I'm thirteen years old. I

1216
01:06:36,240 --> 01:06:39,200
Speaker 1: thought that was the most remarkable thing I've ever heard.

1217
01:06:39,320 --> 01:06:42,280
Speaker 1: These are animals from the desert. I already knew what

1218
01:06:42,440 --> 01:06:46,200
Speaker 1: are they doing in my home state and in the

1219
01:06:46,320 --> 01:06:51,600
Speaker 1: bayous and swamps around me. And so what that became was,

1220
01:06:52,480 --> 01:06:56,360
Speaker 1: as I began to understand the coyote story, what I

1221
01:06:56,440 --> 01:07:00,480
Speaker 1: realized was I had been I was lucky enough to

1222
01:07:00,680 --> 01:07:04,080
Speaker 1: be in the right place at the right time to

1223
01:07:04,320 --> 01:07:09,920
Speaker 1: witness this expansion of coyotes out of the West across

1224
01:07:10,480 --> 01:07:14,200
Speaker 1: the eastern United States, so that over the next you know,

1225
01:07:14,360 --> 01:07:18,160
Speaker 1: as I ride in Coyote America, they colonized their forty

1226
01:07:18,240 --> 01:07:21,440
Speaker 1: nine state and that leaves Hawaii out. They'll make it.

1227
01:07:21,480 --> 01:07:26,000
Speaker 1: They're they're figuring it out right now, I promise you know.

1228
01:07:26,280 --> 01:07:29,440
Speaker 1: They're probably stowing away on a ship and if they do,

1229
01:07:29,640 --> 01:07:33,280
Speaker 1: those those nine ays or not ever going to survive.

1230
01:07:33,480 --> 01:07:38,280
Speaker 1: But uh, they colonize their forty nine state in twenty

1231
01:07:38,440 --> 01:07:41,760
Speaker 1: which was Delaware in it's and that's what interests me

1232
01:07:41,840 --> 01:07:45,080
Speaker 1: so much about this. There's like an intersection in your life,

1233
01:07:46,120 --> 01:07:50,120
Speaker 1: my life, my father's life. It's just like this generate,

1234
01:07:50,200 --> 01:07:54,919
Speaker 1: this very unique generational story, and that I'm thirty three,

1235
01:07:56,000 --> 01:07:59,200
Speaker 1: you know, my generation is kind of coming up in

1236
01:07:59,320 --> 01:08:02,800
Speaker 1: the air where those states have been colonized. Your generation

1237
01:08:02,880 --> 01:08:05,240
Speaker 1: prior has kind of seen the colonization. But there's this

1238
01:08:05,440 --> 01:08:09,920
Speaker 1: interesting intersection between I would say our two generations where

1239
01:08:10,000 --> 01:08:12,680
Speaker 1: we've been able to witness the change in this landscape,

1240
01:08:12,880 --> 01:08:15,720
Speaker 1: the immense change of this landscape that's come from the

1241
01:08:15,800 --> 01:08:18,760
Speaker 1: introduction of the coyote in many places east of the Mississippi,

1242
01:08:19,479 --> 01:08:22,720
Speaker 1: you know, and I remember I have a story of

1243
01:08:22,760 --> 01:08:24,760
Speaker 1: a very small piece of steak ground in Maryland that

1244
01:08:24,840 --> 01:08:28,200
Speaker 1: we watched it be takeover by taken over by coyotes.

1245
01:08:28,360 --> 01:08:31,320
Speaker 1: We watched it over years, over decades, not realizing what

1246
01:08:31,520 --> 01:08:36,439
Speaker 1: was happening, but coming to later understand the impact that

1247
01:08:36,600 --> 01:08:39,519
Speaker 1: it had had, not really knowing it. And so that's

1248
01:08:39,520 --> 01:08:41,920
Speaker 1: why I think coyotes they are part of our psyche

1249
01:08:42,000 --> 01:08:44,400
Speaker 1: for a lot of reasons. But there. But I think

1250
01:08:44,880 --> 01:08:47,200
Speaker 1: those of us that are hunters or even just outdoorsmen

1251
01:08:47,240 --> 01:08:50,519
Speaker 1: that have seen this matriculation over these decades, or the

1252
01:08:50,800 --> 01:08:54,360
Speaker 1: less than less than that in some cases. Ah, it's

1253
01:08:54,360 --> 01:08:57,120
Speaker 1: an amazing story of the natural world and in our

1254
01:08:57,200 --> 01:09:03,080
Speaker 1: generational theme. Yeah, well, it's um their version of manifest destiny,

1255
01:09:03,439 --> 01:09:07,120
Speaker 1: except they went from west to east, and you know,

1256
01:09:07,360 --> 01:09:11,400
Speaker 1: and the reasons they did it are are numerous. But

1257
01:09:11,920 --> 01:09:13,880
Speaker 1: I mean, one of the fascinating parts of the story

1258
01:09:13,960 --> 01:09:18,680
Speaker 1: is that their range now not only encompasses all the

1259
01:09:18,800 --> 01:09:23,519
Speaker 1: provinces of Canada, Alaska, all the states of the Lower

1260
01:09:23,600 --> 01:09:27,080
Speaker 1: forty eight all forty nine UM or forty eight in

1261
01:09:27,120 --> 01:09:30,880
Speaker 1: the Lord Lord forty eight, but they have become the

1262
01:09:31,000 --> 01:09:37,280
Speaker 1: first mammal we think since the Pleistocene to cross the

1263
01:09:37,479 --> 01:09:42,120
Speaker 1: Isthmus of Panama and began to colonize South America. So

1264
01:09:42,280 --> 01:09:46,200
Speaker 1: their range now is more than seven thousand miles north

1265
01:09:46,320 --> 01:09:50,360
Speaker 1: and south. And when Europeans got here five hundred years ago,

1266
01:09:50,520 --> 01:09:54,920
Speaker 1: this was an animal that was confined to basically about

1267
01:09:55,240 --> 01:10:02,520
Speaker 1: from Mexico City northward into the prairie of Alberta and Saskatchewan,

1268
01:10:03,080 --> 01:10:07,640
Speaker 1: but probably not as far north as Calgary is. And

1269
01:10:07,840 --> 01:10:11,519
Speaker 1: so that that expansion has all happened since we've been here. Yeah,

1270
01:10:11,560 --> 01:10:14,759
Speaker 1: and you called the cody how like the original anthem

1271
01:10:15,200 --> 01:10:19,160
Speaker 1: of North America. Well, one million years that's exactly right. Yeah,

1272
01:10:19,760 --> 01:10:22,760
Speaker 1: and it and again it always just strikes me as

1273
01:10:22,800 --> 01:10:25,599
Speaker 1: excited to me about this conversation and about thinking about coyotes,

1274
01:10:25,760 --> 01:10:30,800
Speaker 1: how much has changed over the last decades. Well, it's uh,

1275
01:10:30,960 --> 01:10:33,080
Speaker 1: you know, what I tried to do with Coyote America

1276
01:10:33,240 --> 01:10:37,280
Speaker 1: was basically to tell the biography of this animal because

1277
01:10:38,040 --> 01:10:41,000
Speaker 1: I came to know over the years as I you know,

1278
01:10:41,200 --> 01:10:43,720
Speaker 1: my fascination obviously went back to the time I was

1279
01:10:43,840 --> 01:10:47,639
Speaker 1: thirteen years old and began to see them and understand

1280
01:10:47,720 --> 01:10:51,320
Speaker 1: that they were expanding their range. But over time, as

1281
01:10:51,400 --> 01:10:56,280
Speaker 1: I and I became educated, began to read intensively about

1282
01:10:57,000 --> 01:11:02,080
Speaker 1: the animals of North America, especially animals in the West Um.

1283
01:11:02,280 --> 01:11:06,280
Speaker 1: I began to realize that of all the creatures in

1284
01:11:07,560 --> 01:11:13,479
Speaker 1: North America, there's really not another one aside from us,

1285
01:11:13,880 --> 01:11:17,960
Speaker 1: aside from we human beings, that has a biography that

1286
01:11:18,120 --> 01:11:22,559
Speaker 1: can match this animals. And I mean it's more than

1287
01:11:22,760 --> 01:11:26,320
Speaker 1: five million years old. The candid family evolved five point

1288
01:11:26,400 --> 01:11:29,720
Speaker 1: three million years ago as a North American family. I mean,

1289
01:11:29,840 --> 01:11:33,400
Speaker 1: some of the great animal uh families of the world

1290
01:11:33,560 --> 01:11:38,479
Speaker 1: basically evolved in North America after the chickslob impact, the

1291
01:11:38,680 --> 01:11:43,800
Speaker 1: impact that destroyed the dinosaurs nearly completely fried life in

1292
01:11:43,920 --> 01:11:47,120
Speaker 1: North America because of the angle of the hit um.

1293
01:11:47,560 --> 01:11:51,799
Speaker 1: And out of that recreation of life in North America

1294
01:11:52,040 --> 01:11:56,719
Speaker 1: came the camel family, the horse family, the canted family,

1295
01:11:56,800 --> 01:12:00,360
Speaker 1: among many others, and so cana. It's all the canons

1296
01:12:00,360 --> 01:12:02,800
Speaker 1: of the world come out of North America, origins from

1297
01:12:02,880 --> 01:12:05,320
Speaker 1: five point three million years ago, and many of them

1298
01:12:05,439 --> 01:12:08,679
Speaker 1: leave North America go around the world. They go to Africa,

1299
01:12:08,800 --> 01:12:10,439
Speaker 1: they go to the Middle East, they go to Asia,

1300
01:12:10,720 --> 01:12:14,120
Speaker 1: they go to Europe. The coyote, however, is one of

1301
01:12:14,280 --> 01:12:18,840
Speaker 1: these North American canads that never leaves North America. So

1302
01:12:19,520 --> 01:12:23,160
Speaker 1: it is about as American an animal as it is

1303
01:12:23,240 --> 01:12:28,240
Speaker 1: possible to be. And as I began kind of brainstorming

1304
01:12:28,280 --> 01:12:31,000
Speaker 1: the idea for this book and and realizing some of

1305
01:12:31,080 --> 01:12:35,920
Speaker 1: these things, what I realized would make a book about

1306
01:12:36,680 --> 01:12:42,519
Speaker 1: coyotes and hopefully an important book for for modern people

1307
01:12:42,560 --> 01:12:46,519
Speaker 1: in the twenty first century, is that hardly any of us,

1308
01:12:47,080 --> 01:12:49,320
Speaker 1: whether we live in the west, the East, the south,

1309
01:12:49,720 --> 01:12:54,880
Speaker 1: the northeast, hardly any of us knows anything about coyotes.

1310
01:12:55,439 --> 01:12:58,040
Speaker 1: I mean, we know that Indians told stories about them,

1311
01:12:58,680 --> 01:13:02,040
Speaker 1: we know that they how we know that one used

1312
01:13:02,040 --> 01:13:05,360
Speaker 1: to fall off cliffs repeatedly on Saturday morning cartoons, and

1313
01:13:05,479 --> 01:13:10,320
Speaker 1: that's kind of about all anybody knew about those animals.

1314
01:13:10,360 --> 01:13:13,599
Speaker 1: And so I realized, as these animals are spreading across

1315
01:13:13,680 --> 01:13:17,280
Speaker 1: the continent into one new place after another, and people

1316
01:13:17,600 --> 01:13:19,960
Speaker 1: are seeing them for the first time, it might be

1317
01:13:20,240 --> 01:13:23,599
Speaker 1: an important thing not just for people who are seeing

1318
01:13:23,640 --> 01:13:25,680
Speaker 1: them for the first time, but even for Westerners who

1319
01:13:25,720 --> 01:13:28,240
Speaker 1: have been around them and haven't paid much attention to them,

1320
01:13:29,320 --> 01:13:33,200
Speaker 1: to actually know something about their story. And so that's

1321
01:13:33,280 --> 01:13:34,840
Speaker 1: kind of what I tried to do with that now,

1322
01:13:34,920 --> 01:13:37,599
Speaker 1: and it's done brilliantly, and they think there's so many

1323
01:13:37,680 --> 01:13:39,479
Speaker 1: things that are overlaid in the book, and then just

1324
01:13:39,560 --> 01:13:42,800
Speaker 1: in the subject of the kyo, it's natural history is

1325
01:13:42,880 --> 01:13:45,120
Speaker 1: one thing that I think you highlight that really doesn't

1326
01:13:45,640 --> 01:13:48,360
Speaker 1: that really isn't apparent to most of us. It wasn't

1327
01:13:48,520 --> 01:13:50,320
Speaker 1: to me at the time reading your book and being

1328
01:13:50,360 --> 01:13:53,960
Speaker 1: introduced to your work. I've spent my life outside and

1329
01:13:54,160 --> 01:13:56,200
Speaker 1: had experienced kais for the first time and at the

1330
01:13:56,240 --> 01:13:59,000
Speaker 1: same about the same age you did, and in kind

1331
01:13:59,000 --> 01:14:00,960
Speaker 1: of the same way, you know, like, what is this thing?

1332
01:14:01,080 --> 01:14:03,519
Speaker 1: Why is it chasing turkeys around that I'm trying to hunt?

1333
01:14:03,560 --> 01:14:05,479
Speaker 1: Why is it chasing the geese out of the field?

1334
01:14:05,560 --> 01:14:07,920
Speaker 1: Why is it? Why is this thing that doesn't look

1335
01:14:07,960 --> 01:14:10,840
Speaker 1: like it belongs here here? And then it leads you

1336
01:14:10,960 --> 01:14:13,760
Speaker 1: to learn other things, But the deep knowledge of the

1337
01:14:13,840 --> 01:14:15,720
Speaker 1: naturalistry of the cop just isn't there, for I think

1338
01:14:15,760 --> 01:14:19,160
Speaker 1: for most most hunters are most outdoors men. So there's

1339
01:14:19,200 --> 01:14:21,320
Speaker 1: that piece of it, But then there's you overlay on

1340
01:14:21,400 --> 01:14:25,760
Speaker 1: top of that the cultural significance with natives and then

1341
01:14:25,840 --> 01:14:28,640
Speaker 1: with our own weird popular culture and how it's kind

1342
01:14:28,680 --> 01:14:32,519
Speaker 1: of twisted and done all these things to the kyot.

1343
01:14:32,760 --> 01:14:34,600
Speaker 1: And if you start to overlay those and in your

1344
01:14:34,640 --> 01:14:36,320
Speaker 1: book does as well. You start to overlay all that

1345
01:14:36,439 --> 01:14:38,720
Speaker 1: kind of unpack it on. It's an it's an astounding

1346
01:14:38,760 --> 01:14:41,840
Speaker 1: account of the animal. It just really is. And I

1347
01:14:41,920 --> 01:14:44,479
Speaker 1: think it runs up against something that we briefly talked about.

1348
01:14:44,560 --> 01:14:48,360
Speaker 1: But the modern in the modern sense, the hunting audience.

1349
01:14:50,120 --> 01:14:51,519
Speaker 1: I don't know if you could break it up into

1350
01:14:51,560 --> 01:14:54,680
Speaker 1: certain camps, but there's certain individuals who see a coy

1351
01:14:54,760 --> 01:14:59,760
Speaker 1: out and think there's hatred, there's negativity, there's a lot

1352
01:14:59,840 --> 01:15:03,599
Speaker 1: of things emotions that are swept up because we hunt unglets,

1353
01:15:03,720 --> 01:15:07,840
Speaker 1: white tailed deer, moose, caribou, elk these are the things

1354
01:15:07,880 --> 01:15:11,120
Speaker 1: that we know intimately. We tellt our model of conservation

1355
01:15:11,400 --> 01:15:15,400
Speaker 1: as having recovered these things. And then so I think,

1356
01:15:15,520 --> 01:15:19,560
Speaker 1: very naturally, here comes this idea that here's this marauding

1357
01:15:21,000 --> 01:15:23,800
Speaker 1: kina that doesn't belong here, that wasn't here before, that's

1358
01:15:23,840 --> 01:15:28,640
Speaker 1: coming into compete with us on many levels, both you know,

1359
01:15:28,760 --> 01:15:32,200
Speaker 1: tangibly and sometimes intangibly, and so that's I think where

1360
01:15:32,280 --> 01:15:34,840
Speaker 1: we currently are, and so I think maybe we can

1361
01:15:34,880 --> 01:15:37,680
Speaker 1: work backwards to that. But we we had a lot

1362
01:15:37,760 --> 01:15:41,200
Speaker 1: of people right into a recent article we posted on

1363
01:15:41,280 --> 01:15:43,439
Speaker 1: the mediator dot com and it asked a pretty simple

1364
01:15:43,520 --> 01:15:47,959
Speaker 1: question for a hunter, which is should you shoot coyotes

1365
01:15:48,000 --> 01:15:51,120
Speaker 1: while deer hunting? And to me it's like, oh, that's

1366
01:15:51,120 --> 01:15:56,080
Speaker 1: a pretty simple question, but it evoked some pretty interesting

1367
01:15:56,200 --> 01:16:01,439
Speaker 1: responses in people. Um, A lot of them negative. And

1368
01:16:01,520 --> 01:16:05,160
Speaker 1: so do you have any feeling on you know, not

1369
01:16:05,240 --> 01:16:07,160
Speaker 1: you don't even have to dress the modern hunter, but like,

1370
01:16:07,360 --> 01:16:10,920
Speaker 1: what are the origins of these negative feelings and why

1371
01:16:11,040 --> 01:16:14,000
Speaker 1: might they be there? Based only you're not well? I mean,

1372
01:16:14,160 --> 01:16:16,640
Speaker 1: I think I can at least shed a little bit of,

1373
01:16:17,200 --> 01:16:21,040
Speaker 1: you know, a little bit of context on it. Um.

1374
01:16:22,880 --> 01:16:29,080
Speaker 1: So in the biography, I was mentioning before Europeans arrive

1375
01:16:29,439 --> 01:16:38,040
Speaker 1: with flocks of sheep and herds of cattle and hogs

1376
01:16:38,600 --> 01:16:46,280
Speaker 1: and chickens, in other words, before people with domestic animals

1377
01:16:46,720 --> 01:16:51,760
Speaker 1: come to North America, we have ten thousand years of

1378
01:16:52,320 --> 01:16:55,000
Speaker 1: native people in North America. And you have to remember

1379
01:16:55,120 --> 01:16:57,920
Speaker 1: at that time that the coyote is is west of

1380
01:16:57,960 --> 01:17:03,000
Speaker 1: the Mississippi River. It we have ten thousand years of

1381
01:17:03,600 --> 01:17:09,680
Speaker 1: native people everywhere that coyotes range, not looking at it

1382
01:17:10,439 --> 01:17:17,680
Speaker 1: as a competitor predator, but as a sacred animal that

1383
01:17:18,000 --> 01:17:21,120
Speaker 1: serves as a kind of an avatar, a stand in

1384
01:17:21,400 --> 01:17:24,160
Speaker 1: for humans in the world. So I mean one of

1385
01:17:24,240 --> 01:17:27,479
Speaker 1: the In fact, it's the first chapter in Coyote America,

1386
01:17:27,520 --> 01:17:31,519
Speaker 1: which is called Old Man America. Old Man America is

1387
01:17:31,800 --> 01:17:38,719
Speaker 1: the coyote. It's the the lead subject, the lead literary

1388
01:17:38,880 --> 01:17:44,679
Speaker 1: figure in the oldest literature, the oldest stories from this continent,

1389
01:17:45,479 --> 01:17:50,000
Speaker 1: the oldest stories we have from North America, which I

1390
01:17:50,120 --> 01:17:52,360
Speaker 1: think probably go back to the end of the Plaza

1391
01:17:52,439 --> 01:17:56,559
Speaker 1: st ten thousand years ago, are of a coyote deity

1392
01:17:57,160 --> 01:18:00,439
Speaker 1: who serves as a stand in for humans. And so

1393
01:18:01,680 --> 01:18:05,040
Speaker 1: thousands of these stories, by about a hundred and twenty

1394
01:18:05,160 --> 01:18:09,960
Speaker 1: years ago are preserved through oral tradition by native people,

1395
01:18:10,040 --> 01:18:12,760
Speaker 1: and hundred and twenty years ago start getting collected by

1396
01:18:13,080 --> 01:18:17,440
Speaker 1: anthropologists and ethnographers and become the basis of this coyote

1397
01:18:18,200 --> 01:18:22,280
Speaker 1: literature that we have. And in none of those stories

1398
01:18:22,520 --> 01:18:28,040
Speaker 1: do native people seem to resent that the coyote occasionally

1399
01:18:28,240 --> 01:18:32,160
Speaker 1: kills a fawn or certainly, I mean most of the

1400
01:18:32,479 --> 01:18:34,920
Speaker 1: rock art that you see of coyote with prey, it's

1401
01:18:34,960 --> 01:18:37,880
Speaker 1: usually small prey. It's usually rabbits or something like that.

1402
01:18:38,400 --> 01:18:41,160
Speaker 1: But I mean Indians are clearly aware that coyotes kill

1403
01:18:41,280 --> 01:18:45,920
Speaker 1: fawns and they'll kill big horn sheep, lambs, and it's

1404
01:18:46,000 --> 01:18:49,960
Speaker 1: difficult for coyotes, even in pacts to kill large animals.

1405
01:18:50,040 --> 01:18:52,720
Speaker 1: I mean they're not these are not very big animals. Uh.

1406
01:18:52,800 --> 01:18:57,000
Speaker 1: Coyotes are you know, thirty thirty five pounds at least

1407
01:18:57,080 --> 01:19:00,439
Speaker 1: in the West at the most. But there's not a

1408
01:19:00,640 --> 01:19:05,800
Speaker 1: sense of that among native people. When Europeans come over though,

1409
01:19:05,880 --> 01:19:10,640
Speaker 1: with domesticated animals, I mean, Europeans arrived without any preconceived

1410
01:19:10,680 --> 01:19:13,479
Speaker 1: notions about coyotes because there aren't any in Europe. But

1411
01:19:13,600 --> 01:19:18,880
Speaker 1: Europeans know about wolves, and we arrive with this many

1412
01:19:19,120 --> 01:19:24,439
Speaker 1: centuries deep antagonism towards wolves, and as soon as we

1413
01:19:25,040 --> 01:19:30,120
Speaker 1: land on the Atlantic shore or in the desert Southwest

1414
01:19:30,439 --> 01:19:33,599
Speaker 1: or California in the case of the Spaniards, everybody kind

1415
01:19:33,640 --> 01:19:36,400
Speaker 1: of begins to make war on the wolf population. But

1416
01:19:36,520 --> 01:19:39,000
Speaker 1: we kind of don't know exactly what to what to

1417
01:19:39,080 --> 01:19:43,519
Speaker 1: think about coyotes for a while. But to me, the

1418
01:19:44,720 --> 01:19:47,800
Speaker 1: the negative attitudes that I think a lot of people

1419
01:19:48,400 --> 01:19:52,720
Speaker 1: sort of have inherited without thinking about the origins of them,

1420
01:19:53,160 --> 01:19:57,280
Speaker 1: with respect to both wolves and particularly coyotes, I mean,

1421
01:19:57,320 --> 01:20:02,479
Speaker 1: the wolf negativity. They go back centuries from European origins

1422
01:20:02,560 --> 01:20:05,760
Speaker 1: handed down from you know, from family to family over time.

1423
01:20:06,800 --> 01:20:10,679
Speaker 1: But with coyotes, I think the negativity actually goes back

1424
01:20:10,760 --> 01:20:15,200
Speaker 1: to the Bureau of Biological Survey and its public relations

1425
01:20:15,320 --> 01:20:19,240
Speaker 1: campaigns in the twenties and thirties when wolves have been

1426
01:20:19,320 --> 01:20:22,640
Speaker 1: taken care of, and the Biological Survey, which is the

1427
01:20:22,720 --> 01:20:26,559
Speaker 1: federal agency that's going to quote solve the predator problem

1428
01:20:26,760 --> 01:20:31,400
Speaker 1: for for people who are raising stock, decide that the

1429
01:20:31,520 --> 01:20:36,040
Speaker 1: coyote is actually the arch predator, and so they put

1430
01:20:36,160 --> 01:20:42,120
Speaker 1: out just one canned newspaper article and one pamphlet after

1431
01:20:42,200 --> 01:20:47,000
Speaker 1: another arguing that coyotes are vermin and actually convince Congress

1432
01:20:47,040 --> 01:20:51,360
Speaker 1: to pass an act in that gives the Biological Survey

1433
01:20:51,479 --> 01:20:55,679
Speaker 1: ten million dollars to try to eradicate coyotes in North America.

1434
01:20:56,200 --> 01:21:00,560
Speaker 1: And so I think a lot of people today, I

1435
01:21:00,600 --> 01:21:04,560
Speaker 1: mean a hundred years later, have kind of absorbed that

1436
01:21:04,880 --> 01:21:09,240
Speaker 1: public relations campaign from the nineteen twenties, thirties and forties

1437
01:21:09,680 --> 01:21:12,879
Speaker 1: where a government agency was trying to convince the American

1438
01:21:12,960 --> 01:21:16,400
Speaker 1: population that this is an animal that deserves to be eradicated.

1439
01:21:16,960 --> 01:21:20,439
Speaker 1: Now you know people who So I did a talk

1440
01:21:20,800 --> 01:21:24,000
Speaker 1: in South Carolina a year or two ago, and everyone

1441
01:21:24,120 --> 01:21:28,479
Speaker 1: there was really concerned about coyotes being recent arrivals in

1442
01:21:28,640 --> 01:21:32,200
Speaker 1: South Carolina and killing fauns and making it more difficult

1443
01:21:32,280 --> 01:21:35,120
Speaker 1: for hunters to to get their deer during the deer season.

1444
01:21:35,600 --> 01:21:39,639
Speaker 1: I will say that they're in most of the Eastern States.

1445
01:21:39,760 --> 01:21:42,560
Speaker 1: In the Southern States, the argument is the coyotes a

1446
01:21:42,640 --> 01:21:46,960
Speaker 1: brand new animal on the scene. Uh, it's an invasive

1447
01:21:47,000 --> 01:21:50,200
Speaker 1: and intrusive animal and it's screwing everything up, and so

1448
01:21:51,200 --> 01:21:54,080
Speaker 1: I have an additional reason to be piste off at coyotes.

1449
01:21:55,640 --> 01:22:00,400
Speaker 1: I'll also point out that in the West, hunters don't

1450
01:22:00,600 --> 01:22:04,200
Speaker 1: regard coyotes as an invasive, brand new animal, but they

1451
01:22:04,280 --> 01:22:08,240
Speaker 1: often I was gonna say, there's there's so many things

1452
01:22:08,280 --> 01:22:11,320
Speaker 1: that are paradoxical about the way we see coyotes, and

1453
01:22:11,360 --> 01:22:13,200
Speaker 1: I think you've just laid it out well right there.

1454
01:22:13,320 --> 01:22:16,200
Speaker 1: The totem of the coyote is the jokester, the trickster,

1455
01:22:16,960 --> 01:22:20,840
Speaker 1: like the sly creature. But then there's also the and

1456
01:22:20,920 --> 01:22:25,040
Speaker 1: the paradox is it's also this evil, marauding, go anywhere,

1457
01:22:25,240 --> 01:22:29,439
Speaker 1: adaptable predator. And as you say, there is a bounties

1458
01:22:29,479 --> 01:22:31,559
Speaker 1: There has been in the past bounties on the coyotes

1459
01:22:31,680 --> 01:22:34,479
Speaker 1: set by state fishing game and Wyoming, but also in

1460
01:22:34,640 --> 01:22:38,800
Speaker 1: North Carolina, for example, and in Utah. And so as

1461
01:22:38,840 --> 01:22:43,040
Speaker 1: a hunter, when you're going around traveling around, you certainly see,

1462
01:22:43,960 --> 01:22:47,160
Speaker 1: you know, an aggressive stance taken by our state game

1463
01:22:47,360 --> 01:22:52,120
Speaker 1: officials on these animals. And so within the way that

1464
01:22:52,200 --> 01:22:55,200
Speaker 1: we think about hunting, that's we kind of would follow that,

1465
01:22:55,840 --> 01:22:57,560
Speaker 1: you know, and all sense in all senses of the

1466
01:22:57,600 --> 01:22:59,479
Speaker 1: world follow the idea that, well, if they're paying us

1467
01:22:59,479 --> 01:23:01,280
Speaker 1: a bounty to kill him in Wyoming, we better kill

1468
01:23:01,360 --> 01:23:04,640
Speaker 1: everyone that we see well, because we're doing good for

1469
01:23:05,320 --> 01:23:07,400
Speaker 1: for the state, and the state bologists are telling us

1470
01:23:07,439 --> 01:23:09,360
Speaker 1: this is right. So I mean, there's there certainly has

1471
01:23:09,400 --> 01:23:13,200
Speaker 1: been a paradoxical expression within the hunting community, but the

1472
01:23:13,320 --> 01:23:17,880
Speaker 1: culture at large is it's amazing. Well, the culture at large,

1473
01:23:17,960 --> 01:23:21,080
Speaker 1: I think, um and I think the hunting community falls

1474
01:23:21,160 --> 01:23:25,439
Speaker 1: into this category, has not been keeping up with the

1475
01:23:25,520 --> 01:23:29,640
Speaker 1: scientific literature about these animals. And that's part of it.

1476
01:23:29,880 --> 01:23:33,960
Speaker 1: So you know, I'm not going to say that, Okay,

1477
01:23:34,120 --> 01:23:37,519
Speaker 1: a hunter who sees a coyote trot by when he's

1478
01:23:37,520 --> 01:23:42,479
Speaker 1: in a deer stand and shoots it is engaging in

1479
01:23:42,840 --> 01:23:49,040
Speaker 1: a wrong headed act because I think relying on the

1480
01:23:49,439 --> 01:23:53,520
Speaker 1: knowledge that we've handed down over the last several decades,

1481
01:23:53,840 --> 01:23:56,599
Speaker 1: that would be the logical thing to do. I mean,

1482
01:23:56,680 --> 01:24:01,200
Speaker 1: I I argue in Coyote America that, how however, if

1483
01:24:01,280 --> 01:24:05,400
Speaker 1: you keep up with the modern literature on this animal,

1484
01:24:06,080 --> 01:24:09,479
Speaker 1: what you quickly realize, uh, and you don't have to

1485
01:24:09,600 --> 01:24:12,040
Speaker 1: read a lot of it. But what I'll just offer

1486
01:24:12,160 --> 01:24:15,160
Speaker 1: one example to the Utah example. But what you quickly

1487
01:24:15,280 --> 01:24:19,200
Speaker 1: realize is that the supposition that coyotes are making it

1488
01:24:19,360 --> 01:24:22,120
Speaker 1: more difficult for you to get your deer in the

1489
01:24:22,240 --> 01:24:27,439
Speaker 1: fall is likely unfounded, and shooting one that's trotting by

1490
01:24:27,600 --> 01:24:34,679
Speaker 1: under your dear stand basically is um, it's an act

1491
01:24:35,120 --> 01:24:40,760
Speaker 1: that really is not warranted by the science. Is there

1492
01:24:40,800 --> 01:24:43,080
Speaker 1: something there, an analogy that you would use to to

1493
01:24:43,400 --> 01:24:46,760
Speaker 1: give people to understand like how this is actually going down?

1494
01:24:46,800 --> 01:24:49,120
Speaker 1: Because I think we're talking about this earlier. I think

1495
01:24:49,720 --> 01:24:53,559
Speaker 1: as these ideas that you're speaking of are introduced, like here, hey,

1496
01:24:53,600 --> 01:24:56,120
Speaker 1: here's a study that says this about kids, shoot more,

1497
01:24:56,200 --> 01:24:59,360
Speaker 1: get more. That the kind of pushback that you would

1498
01:24:59,360 --> 01:25:02,960
Speaker 1: expect from you know, the core belief systems around KYO

1499
01:25:03,280 --> 01:25:06,639
Speaker 1: is there. It's like, WHOA, don't try to tell me, well, yeah,

1500
01:25:06,840 --> 01:25:09,880
Speaker 1: and so I mean as I said in Utah, Utah

1501
01:25:10,000 --> 01:25:13,600
Speaker 1: five years ago passed a mule Deer Protection Act, And

1502
01:25:13,680 --> 01:25:17,840
Speaker 1: so Utah is giving hunters, uh people, anybody who shoots

1503
01:25:17,840 --> 01:25:19,360
Speaker 1: at coyote. You don't have to be a hunter with

1504
01:25:19,439 --> 01:25:22,479
Speaker 1: a license. Anybody who shots a coyote gets a fifty

1505
01:25:22,520 --> 01:25:25,320
Speaker 1: dollar bounty if they present it to a state office

1506
01:25:25,880 --> 01:25:30,160
Speaker 1: under the Mule Deer Protection Act. The irony of the

1507
01:25:30,280 --> 01:25:32,960
Speaker 1: passage of this mule Deer Protection Act, and so far

1508
01:25:33,760 --> 01:25:35,960
Speaker 1: the last figures I saw are about a year old.

1509
01:25:36,040 --> 01:25:40,040
Speaker 1: But but a year ago, four years into the passage

1510
01:25:40,080 --> 01:25:43,760
Speaker 1: of that act, Utah had bountied thirty eight thousand coyotes

1511
01:25:43,920 --> 01:25:46,960
Speaker 1: under the Mule Deer Protection Act. The irony of the

1512
01:25:47,160 --> 01:25:51,600
Speaker 1: passage of that act by the Utah legislature was that

1513
01:25:51,960 --> 01:25:56,080
Speaker 1: it came within a year of the publication of a

1514
01:25:56,439 --> 01:26:01,160
Speaker 1: major study that had been done in nearby southeastern Idaho,

1515
01:26:01,800 --> 01:26:06,880
Speaker 1: the bordering state, that argued over a ten year study

1516
01:26:07,640 --> 01:26:13,120
Speaker 1: that coyotes actually play little, are virtually no role in

1517
01:26:13,360 --> 01:26:18,120
Speaker 1: mule deer demographics. That coyotes, to be sure, may end

1518
01:26:18,240 --> 01:26:21,439
Speaker 1: up killing a few lambs as a result of severe

1519
01:26:21,680 --> 01:26:26,040
Speaker 1: winners that weakens the herd and weakens lambs and makes

1520
01:26:26,080 --> 01:26:29,960
Speaker 1: them easier to catch, but that coyotes don't really have

1521
01:26:30,439 --> 01:26:34,400
Speaker 1: any effect usually if there's not a severe winner on

1522
01:26:34,720 --> 01:26:39,040
Speaker 1: mule deer populations. That study was published in a major

1523
01:26:39,360 --> 01:26:43,720
Speaker 1: journal a year before the Utah legislature passed this act,

1524
01:26:44,080 --> 01:26:47,479
Speaker 1: and either they weren't aware of it are they just decided, which,

1525
01:26:47,520 --> 01:26:49,560
Speaker 1: of course is something that we tend to do a

1526
01:26:49,640 --> 01:26:54,200
Speaker 1: little bit these days. I don't like that science, now

1527
01:26:54,360 --> 01:26:56,720
Speaker 1: I don't. I'm not gonna believe that science, and so

1528
01:26:56,880 --> 01:26:58,800
Speaker 1: I'm gonna go ahead and do what I wanted. Yeah,

1529
01:26:58,800 --> 01:27:03,000
Speaker 1: we've driven ourselves into like this weird skepticism culture, where well,

1530
01:27:03,120 --> 01:27:05,400
Speaker 1: that's that scientific journal must have had a they must

1531
01:27:05,439 --> 01:27:07,560
Speaker 1: have had a reason. Sure they had a bias of

1532
01:27:07,640 --> 01:27:09,519
Speaker 1: some kinds. And when they're like, when they're doing that,

1533
01:27:09,640 --> 01:27:13,560
Speaker 1: are they talking? Fawn recruitment is the major factor in

1534
01:27:13,680 --> 01:27:15,880
Speaker 1: all those things? I mean, because that's that's the picture

1535
01:27:15,880 --> 01:27:17,880
Speaker 1: of the kite that we normally get. They're they're killing

1536
01:27:17,920 --> 01:27:19,800
Speaker 1: fawns as soon as they hit the dirt. They're praying

1537
01:27:19,880 --> 01:27:25,559
Speaker 1: upon fawns when at crucial times in the season, crucial

1538
01:27:25,640 --> 01:27:29,160
Speaker 1: times and their maturation. Is that really where this comes

1539
01:27:29,240 --> 01:27:32,439
Speaker 1: down to like is fawn recruitment that like damaged that

1540
01:27:32,640 --> 01:27:36,880
Speaker 1: much by kyo wellulation. According to this study and some

1541
01:27:37,040 --> 01:27:41,120
Speaker 1: of the first studies that were done on coyote predation

1542
01:27:41,439 --> 01:27:44,639
Speaker 1: on game animals by the Murray brothers in the nineteen

1543
01:27:44,680 --> 01:27:50,960
Speaker 1: thirties in Jackson Hole and in Yellowstone Park, the Mury

1544
01:27:51,080 --> 01:27:55,320
Speaker 1: brothers argued and the the people who did this study

1545
01:27:55,400 --> 01:28:01,760
Speaker 1: in Idaho followed the same line of reasoning. The truth is,

1546
01:28:04,080 --> 01:28:08,559
Speaker 1: we've got a myopic view of the history of North America.

1547
01:28:09,280 --> 01:28:13,360
Speaker 1: We from European backgrounds have only been here for five

1548
01:28:13,479 --> 01:28:19,799
Speaker 1: hundred years. Somehow, coyotes and mule deer coyotes and bighorn

1549
01:28:19,920 --> 01:28:24,599
Speaker 1: sheep coyotes and white tailed deer coyotes and prom horns

1550
01:28:25,280 --> 01:28:32,560
Speaker 1: have affected a symbiotic balance between predation and pray that

1551
01:28:32,720 --> 01:28:36,439
Speaker 1: has lasted. Coyotes evolved into their present species a million

1552
01:28:36,520 --> 01:28:40,360
Speaker 1: years ago, so it's lasted for a million years. We've

1553
01:28:40,400 --> 01:28:42,680
Speaker 1: only been here five hundred years, and we've sort of

1554
01:28:42,800 --> 01:28:46,280
Speaker 1: arrived with the idea that, Okay, we're gonna fix everything

1555
01:28:46,400 --> 01:28:48,320
Speaker 1: that's wrong with North America, and one of the things

1556
01:28:48,320 --> 01:28:50,560
Speaker 1: we're gonna do is to get rid of the predators.

1557
01:28:51,000 --> 01:28:54,599
Speaker 1: When we're actually we actually introduced ourselves into a system

1558
01:28:54,880 --> 01:28:56,920
Speaker 1: that was a million years old. I mean, I'll give

1559
01:28:56,920 --> 01:28:59,679
Speaker 1: you an example with prong horns. How prom horns deal

1560
01:29:00,080 --> 01:29:03,880
Speaker 1: with coyote predation. Prom warns, of course, as adults have

1561
01:29:04,160 --> 01:29:08,240
Speaker 1: no no predators because all their predators died out in

1562
01:29:08,280 --> 01:29:12,519
Speaker 1: the Pleistocene. Prong horns can run sixty five hour and

1563
01:29:12,720 --> 01:29:16,240
Speaker 1: coyotes and wolves can only run forty three miles an hour,

1564
01:29:16,560 --> 01:29:19,880
Speaker 1: So adult pronghorns can get away from anything that chases them.

1565
01:29:20,320 --> 01:29:24,960
Speaker 1: But what coyotes do do is prey on funds, so

1566
01:29:25,640 --> 01:29:30,720
Speaker 1: prom horns long ago developed the ability to survive that predation.

1567
01:29:31,280 --> 01:29:34,920
Speaker 1: They have twins with the idea that the coyotes are

1568
01:29:34,920 --> 01:29:37,680
Speaker 1: probably going to get one and I'm going to get

1569
01:29:37,760 --> 01:29:41,200
Speaker 1: one up to replace me in the genetic streame. Uh As.

1570
01:29:41,360 --> 01:29:43,800
Speaker 1: I've written a couple of times about this. It's the

1571
01:29:43,920 --> 01:29:47,040
Speaker 1: prong horns strategy as an air and a spare, and

1572
01:29:47,160 --> 01:29:49,760
Speaker 1: the spare is probably the one that the coyotes are

1573
01:29:49,800 --> 01:29:53,719
Speaker 1: going to get. So what I think, in a way

1574
01:29:53,880 --> 01:29:58,680
Speaker 1: is happening with the hunting community and this lingering animosity,

1575
01:29:59,439 --> 01:30:03,400
Speaker 1: which is obviously old, because what hunting is is it's

1576
01:30:03,439 --> 01:30:07,040
Speaker 1: actually being a predator. And if you're a predator, you

1577
01:30:07,160 --> 01:30:12,040
Speaker 1: resent other predators getting involved in the game. But what

1578
01:30:12,200 --> 01:30:16,959
Speaker 1: I think has made it particularly pronounced in North America

1579
01:30:17,680 --> 01:30:21,439
Speaker 1: is that by a hundred years or so ago, we

1580
01:30:21,600 --> 01:30:25,599
Speaker 1: had eliminated all the predators, and when we created our

1581
01:30:25,800 --> 01:30:30,439
Speaker 1: modern game laws and bag limits, it was based on

1582
01:30:30,520 --> 01:30:35,280
Speaker 1: the idea that human predators would replace the natural ones,

1583
01:30:35,439 --> 01:30:41,160
Speaker 1: that humans would replace cougars and gray wolves and coyotes

1584
01:30:41,280 --> 01:30:44,360
Speaker 1: and whatever else you have out there. And so we

1585
01:30:44,680 --> 01:30:48,240
Speaker 1: sort of went from the early twentieth century until just

1586
01:30:48,400 --> 01:30:53,400
Speaker 1: the last couple of decades in this completely artificial situation

1587
01:30:53,880 --> 01:30:57,200
Speaker 1: where the natural predators of North America were so beaten

1588
01:30:57,280 --> 01:31:01,080
Speaker 1: back that we had no competition. And now that the

1589
01:31:01,240 --> 01:31:03,960
Speaker 1: predators are coming back and we're getting back to what

1590
01:31:04,160 --> 01:31:08,760
Speaker 1: is actually a more natural condition, everybody is screaming and

1591
01:31:08,840 --> 01:31:11,920
Speaker 1: bitching about so the wolves are going to get my elk.

1592
01:31:12,720 --> 01:31:14,920
Speaker 1: But what we've been used to for the last tunder

1593
01:31:14,920 --> 01:31:17,679
Speaker 1: of years is something that's not natural. It's been artificial.

1594
01:31:18,120 --> 01:31:20,519
Speaker 1: So how do you you know? Because I think there's

1595
01:31:20,560 --> 01:31:24,000
Speaker 1: so much fervor around this and both on all I

1596
01:31:24,080 --> 01:31:26,240
Speaker 1: think on all sides here, and what I like about

1597
01:31:26,280 --> 01:31:28,040
Speaker 1: American coyoty and what I like about the way that

1598
01:31:28,080 --> 01:31:30,519
Speaker 1: you approach it is here's the history of it, here's

1599
01:31:30,520 --> 01:31:32,760
Speaker 1: where we are, here's where we're going. I think that

1600
01:31:33,000 --> 01:31:34,880
Speaker 1: I think that makes it strikes a chord with me,

1601
01:31:34,960 --> 01:31:36,920
Speaker 1: and I hope strikes chord with anyone who has read

1602
01:31:36,920 --> 01:31:39,120
Speaker 1: it or will go on to read it. But like

1603
01:31:39,560 --> 01:31:43,080
Speaker 1: in creating a balance, because what I we had a

1604
01:31:43,160 --> 01:31:46,080
Speaker 1: gentleman on the podcast a couple episodes ago that was

1605
01:31:46,760 --> 01:31:49,200
Speaker 1: was charging, what we're talking about for hunters, Hey, all

1606
01:31:49,280 --> 01:31:52,040
Speaker 1: hunters hate predators. And my my response was like, I

1607
01:31:52,160 --> 01:31:54,439
Speaker 1: know a lot of hunters and I don't know any

1608
01:31:54,479 --> 01:31:56,719
Speaker 1: of them that hate predators, and and that is true.

1609
01:31:56,960 --> 01:31:59,200
Speaker 1: And I got criticized by a lot of people that said, hey, listen,

1610
01:31:59,200 --> 01:32:02,320
Speaker 1: you're not addressing what's out there, this reality that there

1611
01:32:02,400 --> 01:32:05,160
Speaker 1: are groups of hunters that do feel this way. So

1612
01:32:05,240 --> 01:32:08,320
Speaker 1: I said, okay, that's a fair comparison. So I'm glad

1613
01:32:08,360 --> 01:32:12,120
Speaker 1: we're having this conversation. My point is, as a hunter

1614
01:32:12,160 --> 01:32:14,960
Speaker 1: in the modern sense, wherever in my time that I

1615
01:32:15,080 --> 01:32:18,000
Speaker 1: have to be a hunter, I feel that balance is

1616
01:32:18,040 --> 01:32:20,640
Speaker 1: something that I'm trying to achieve in all of my activities.

1617
01:32:21,000 --> 01:32:23,880
Speaker 1: And I would hope that those that are setting game regulations,

1618
01:32:23,920 --> 01:32:26,439
Speaker 1: are thinking of those same things. I know that they

1619
01:32:26,479 --> 01:32:29,519
Speaker 1: are in most cases, and so thinking of like starting

1620
01:32:29,600 --> 01:32:31,800
Speaker 1: with the core belief of balancing these things because we

1621
01:32:31,920 --> 01:32:34,439
Speaker 1: have to balance them. They're ever changing, right as you said,

1622
01:32:34,439 --> 01:32:36,560
Speaker 1: they're changing all the time. Our generation will deal with

1623
01:32:36,640 --> 01:32:40,600
Speaker 1: coyotes and the prior generation did not have to. And

1624
01:32:40,760 --> 01:32:43,680
Speaker 1: so how do you what's the balance there? Because I

1625
01:32:43,720 --> 01:32:45,280
Speaker 1: don't I don't know that I've ever heard you or

1626
01:32:45,320 --> 01:32:48,040
Speaker 1: read anything where you said like, let's quit hunting predators,

1627
01:32:48,120 --> 01:32:51,280
Speaker 1: or let's quit hunting coyotes, or let's let's not touch him,

1628
01:32:51,840 --> 01:32:54,360
Speaker 1: like there's some version of balance here that kind of

1629
01:32:54,680 --> 01:32:56,800
Speaker 1: sets us in a course for the future. Yeah, well

1630
01:32:56,880 --> 01:33:00,280
Speaker 1: you've never read that, because I've never written that, never

1631
01:33:00,360 --> 01:33:04,400
Speaker 1: said anything like that. Um, I'm not any hunting in

1632
01:33:04,439 --> 01:33:12,040
Speaker 1: any way, including uh, including predators, particularly because of the

1633
01:33:12,120 --> 01:33:15,280
Speaker 1: simple fact that one of the things biology is teaching

1634
01:33:15,360 --> 01:33:18,120
Speaker 1: us about animals like wolves and coyotes, and coyotes are

1635
01:33:18,160 --> 01:33:22,400
Speaker 1: a particular example of this is they're they're extremely individualistic.

1636
01:33:23,240 --> 01:33:27,520
Speaker 1: And the studies that I used in writing Coyote America

1637
01:33:28,680 --> 01:33:34,360
Speaker 1: pretty much indicated that about ninety of the coyote population

1638
01:33:34,840 --> 01:33:37,439
Speaker 1: they're very good citizens. I mean they most of what

1639
01:33:37,600 --> 01:33:39,680
Speaker 1: coyotes do, the great majority of what katies do in

1640
01:33:39,720 --> 01:33:43,000
Speaker 1: the world is beneficially humans in the broad sense, and

1641
01:33:43,160 --> 01:33:47,080
Speaker 1: most of them are very good citizens of the natural world.

1642
01:33:47,240 --> 01:33:52,439
Speaker 1: But there are four or five, uh, sort of about

1643
01:33:52,479 --> 01:33:55,759
Speaker 1: the same percentage of humans that tend to get into trouble,

1644
01:33:56,520 --> 01:34:00,800
Speaker 1: about that percentage of coyotes. Uh. Individual sick as they are,

1645
01:34:01,439 --> 01:34:05,160
Speaker 1: will develop bad habits, they'll get into trouble. Sometimes they'll

1646
01:34:05,400 --> 01:34:08,200
Speaker 1: you know, a coyote will decide that it's going to

1647
01:34:08,320 --> 01:34:11,720
Speaker 1: kill every housecat that it can find. Sometimes a coyote

1648
01:34:11,800 --> 01:34:16,600
Speaker 1: will specialize in killing fononts. And so my thinking about that,

1649
01:34:16,800 --> 01:34:18,400
Speaker 1: and I think this is the way most of the

1650
01:34:18,479 --> 01:34:21,720
Speaker 1: coyote management programs that have been set up in most

1651
01:34:21,840 --> 01:34:25,439
Speaker 1: urban areas where coyotes, of course have become a prominent

1652
01:34:25,520 --> 01:34:28,080
Speaker 1: feature in the last few decades, is based on this

1653
01:34:28,400 --> 01:34:33,240
Speaker 1: principle that what you do is you leave the good

1654
01:34:33,360 --> 01:34:38,000
Speaker 1: citizen animals alone. If there is a problem one, you

1655
01:34:38,520 --> 01:34:40,880
Speaker 1: take care of it. You you remove it from the

1656
01:34:40,960 --> 01:34:43,880
Speaker 1: population in some way, and that's usually by shooting it,

1657
01:34:44,000 --> 01:34:48,160
Speaker 1: by taking it out. But the majority of the animals

1658
01:34:48,280 --> 01:34:51,880
Speaker 1: are not going to get into trouble, and so the

1659
01:34:52,520 --> 01:34:55,639
Speaker 1: you know, I've heard people say, I've had people say

1660
01:34:55,680 --> 01:34:58,839
Speaker 1: to me, Okay, so a coyote. I think a coyote.

1661
01:34:58,880 --> 01:35:02,400
Speaker 1: In fact, I tell a story about a Novajo guy

1662
01:35:03,200 --> 01:35:05,160
Speaker 1: that I met when I was floating down the Grand

1663
01:35:05,240 --> 01:35:07,360
Speaker 1: King and a few years ago, and he told me

1664
01:35:07,479 --> 01:35:11,519
Speaker 1: this coyote story about he lived and lives in Bluff, Utah,

1665
01:35:11,920 --> 01:35:14,960
Speaker 1: and uh, a coyote was getting into town and it

1666
01:35:15,120 --> 01:35:18,120
Speaker 1: was chasing dogs and it was killing sheep, and so

1667
01:35:18,360 --> 01:35:22,960
Speaker 1: the local Novajo chapter leadership told him to ask Marcus

1668
01:35:23,000 --> 01:35:25,080
Speaker 1: if he would take care of this animal, he would

1669
01:35:25,080 --> 01:35:29,560
Speaker 1: take it out. And he puts his rifle in the

1670
01:35:29,640 --> 01:35:32,519
Speaker 1: gun rack in his truck and he's driving around the

1671
01:35:32,680 --> 01:35:36,280
Speaker 1: dirt roads around Bluff one day, and son of a gun,

1672
01:35:36,479 --> 01:35:39,400
Speaker 1: this coyote comes trotting out right in front of his truck,

1673
01:35:40,280 --> 01:35:42,519
Speaker 1: and so he slams on the brakes, and when the

1674
01:35:42,680 --> 01:35:45,639
Speaker 1: dust settles from the truck stopping, the coyote is still

1675
01:35:45,680 --> 01:35:48,519
Speaker 1: standing there right in front of his truck, twenty feet away,

1676
01:35:48,680 --> 01:35:51,200
Speaker 1: looking right at him, and so he's reaching up to

1677
01:35:51,240 --> 01:35:53,880
Speaker 1: get his rifle down. I mean, and I won't go

1678
01:35:54,000 --> 01:35:56,559
Speaker 1: through the whole story that I tell it's a uh

1679
01:35:56,680 --> 01:35:58,200
Speaker 1: and I tell it in the words that he he

1680
01:35:58,960 --> 01:36:03,519
Speaker 1: described it to me as we were floating down the river. Um.

1681
01:36:03,920 --> 01:36:09,320
Speaker 1: But he ultimately ends up not shooting that animal because

1682
01:36:09,600 --> 01:36:13,320
Speaker 1: of two things. First of all, he thought, I'm not

1683
01:36:13,520 --> 01:36:16,960
Speaker 1: sure this is the right one, you know. I mean

1684
01:36:17,120 --> 01:36:21,400
Speaker 1: Indians suffered in their history in America. Some Indian got

1685
01:36:21,439 --> 01:36:25,719
Speaker 1: into trouble. The cavalry goes out, and the nearest Indian

1686
01:36:25,840 --> 01:36:29,000
Speaker 1: village they can find, they right into and shoot everybody

1687
01:36:29,040 --> 01:36:33,520
Speaker 1: in sight, even if they weren't involved in the depredation

1688
01:36:33,600 --> 01:36:37,160
Speaker 1: of the crime. And so Marcus's idea was, I'm not

1689
01:36:37,320 --> 01:36:39,640
Speaker 1: sure this is the right coyote. It may not be,

1690
01:36:40,080 --> 01:36:42,400
Speaker 1: and I don't want to shoot an animal that's that's

1691
01:36:42,479 --> 01:36:45,160
Speaker 1: not the one that's causing trouble. And the other thing

1692
01:36:45,240 --> 01:36:49,840
Speaker 1: he realizes as he's looking at it is that, man,

1693
01:36:50,400 --> 01:36:55,760
Speaker 1: this thing is gorgeous. Look at it. It is completely confident.

1694
01:36:55,840 --> 01:36:58,680
Speaker 1: At one point, it turns towards him and yawns at

1695
01:36:58,760 --> 01:37:02,960
Speaker 1: him and in just sort of nonchalantly walks off the road.

1696
01:37:03,600 --> 01:37:07,320
Speaker 1: And his take on it was, I'm getting to witness

1697
01:37:07,720 --> 01:37:11,759
Speaker 1: something really beautiful and really wonderful in the natural world.

1698
01:37:12,320 --> 01:37:16,880
Speaker 1: And who am I to erase it and take it away.

1699
01:37:18,040 --> 01:37:23,080
Speaker 1: Why not just enjoy the delight of getting to see

1700
01:37:23,680 --> 01:37:28,439
Speaker 1: something really beautiful happening in nature, rather than killing it

1701
01:37:28,680 --> 01:37:33,280
Speaker 1: and draining all the romance out of the world in

1702
01:37:33,680 --> 01:37:36,840
Speaker 1: some single act that, as he said, I may end

1703
01:37:36,920 --> 01:37:40,880
Speaker 1: up regretting if I do. Yeah, And I think that's I.

1704
01:37:41,160 --> 01:37:43,920
Speaker 1: This is only I only speak for me personally. Like

1705
01:37:44,000 --> 01:37:45,840
Speaker 1: I said, there's plenty people out there to have a

1706
01:37:45,880 --> 01:37:47,720
Speaker 1: more hardened view in the cull ups of hunters than

1707
01:37:47,760 --> 01:37:50,360
Speaker 1: I do. I think if I would, if I were

1708
01:37:50,400 --> 01:37:52,800
Speaker 1: to assess my current state of being when it comes

1709
01:37:52,800 --> 01:37:55,640
Speaker 1: to coyotes, it is more of a question than it

1710
01:37:55,760 --> 01:37:59,040
Speaker 1: is a statement. It's like, what is my role right

1711
01:37:59,080 --> 01:38:02,760
Speaker 1: as a hunter? I? Oh, I trust our model. I

1712
01:38:02,840 --> 01:38:06,800
Speaker 1: trust that my role within hunting an elk or hunting

1713
01:38:06,840 --> 01:38:10,680
Speaker 1: a deer, it it's a model that's worked. It's an

1714
01:38:10,680 --> 01:38:14,120
Speaker 1: equation that has an answer, and I kind of know

1715
01:38:14,240 --> 01:38:17,599
Speaker 1: where it's going. So just for me personally, I think

1716
01:38:17,680 --> 01:38:19,320
Speaker 1: right now, my question be like, where do I fit

1717
01:38:19,400 --> 01:38:21,800
Speaker 1: in as a hunter? I have the ability to take

1718
01:38:21,840 --> 01:38:25,280
Speaker 1: out every kio it was within range? What do I

1719
01:38:25,400 --> 01:38:28,880
Speaker 1: do you know? I've I've certainly been on plenty of

1720
01:38:29,360 --> 01:38:33,960
Speaker 1: ranches in Texas or like in Georgia one time where

1721
01:38:33,960 --> 01:38:35,680
Speaker 1: it was like, if you see the lantern when you

1722
01:38:35,720 --> 01:38:37,080
Speaker 1: sit down on the trees, and I said, listen, if

1723
01:38:37,120 --> 01:38:39,559
Speaker 1: you want to hunt deer here, you must shoot every

1724
01:38:39,600 --> 01:38:42,000
Speaker 1: kid you see no questions. I asked. If I find

1725
01:38:42,040 --> 01:38:46,719
Speaker 1: out you didn't, we're gonna have trouble. And so I've

1726
01:38:46,800 --> 01:38:49,639
Speaker 1: been through those kind of situations. I don't feel bad

1727
01:38:49,720 --> 01:38:52,160
Speaker 1: in shooting a kioude if I if i've I've thought

1728
01:38:52,200 --> 01:38:54,080
Speaker 1: it through, just like I've thought anything through when I

1729
01:38:54,200 --> 01:38:57,320
Speaker 1: kill it. And so, but when I think about your

1730
01:38:57,360 --> 01:38:59,920
Speaker 1: book and kind of what you posit, I want to

1731
01:39:00,320 --> 01:39:02,479
Speaker 1: what's my role? And that's like I said, that's just

1732
01:39:02,560 --> 01:39:04,120
Speaker 1: me personally. I think there's plenty of other people that

1733
01:39:04,200 --> 01:39:07,880
Speaker 1: can say, well, yeah, I appreciate you saying that, Ben,

1734
01:39:08,000 --> 01:39:11,000
Speaker 1: And so, I mean, I guess what I would say

1735
01:39:11,720 --> 01:39:19,439
Speaker 1: is that, uh, it's everyone's personal decision. Um. If it's

1736
01:39:19,479 --> 01:39:22,080
Speaker 1: me sitting in the deer stand and a coyote walks by,

1737
01:39:22,760 --> 01:39:28,360
Speaker 1: I'm putting my rifle down and marveling at the animal.

1738
01:39:29,320 --> 01:39:32,880
Speaker 1: Um unless somebody tells me this is a coyote. That's

1739
01:39:32,960 --> 01:39:37,920
Speaker 1: you know, it's somehow developed, you know, a need to

1740
01:39:38,200 --> 01:39:41,439
Speaker 1: kill every ranch dog within twenty miles and it's got

1741
01:39:41,520 --> 01:39:44,880
Speaker 1: a particular marking that you can recognize, then I might,

1742
01:39:45,479 --> 01:39:49,320
Speaker 1: you know, maybe I would do, uh, do the deed

1743
01:39:49,400 --> 01:39:53,040
Speaker 1: and take it out. But um, personally, I'm not going

1744
01:39:53,120 --> 01:39:54,840
Speaker 1: to do anything like that. But I think it's a

1745
01:39:54,920 --> 01:39:58,240
Speaker 1: decision that everybody has to make. I guess what I'm

1746
01:39:58,360 --> 01:40:06,200
Speaker 1: saying is, know something about these animals other than what

1747
01:40:06,720 --> 01:40:13,639
Speaker 1: you've just absorbed by sort of you know, information handed

1748
01:40:13,720 --> 01:40:19,320
Speaker 1: down or sort of street legends or something urban legends.

1749
01:40:20,120 --> 01:40:28,840
Speaker 1: And don't fool yourself that you're doing something that scientifically

1750
01:40:29,120 --> 01:40:35,360
Speaker 1: and ecologically viable by taking out every coyote that you see,

1751
01:40:35,720 --> 01:40:38,679
Speaker 1: I mean, in a place like Georgia, the reason those

1752
01:40:38,720 --> 01:40:41,200
Speaker 1: coyotes are there is because we got rid of all

1753
01:40:41,280 --> 01:40:45,360
Speaker 1: the red wolves. I mean, in the original natural situation

1754
01:40:45,640 --> 01:40:49,400
Speaker 1: in Georgia seventy five or a hundred years ago was

1755
01:40:49,520 --> 01:40:52,000
Speaker 1: that if you went out and hunted whitetail deer, you

1756
01:40:52,120 --> 01:40:54,439
Speaker 1: were hunting deer in a place where there were also

1757
01:40:54,600 --> 01:40:57,799
Speaker 1: wolves that were taking out deer. And that's how nature

1758
01:40:58,040 --> 01:41:01,840
Speaker 1: is supposed to work, when it an entire heaven and

1759
01:41:01,920 --> 01:41:05,800
Speaker 1: an entire earth, is throw said, But when you extract

1760
01:41:05,920 --> 01:41:10,080
Speaker 1: the predator from it and then get used to they're

1761
01:41:10,120 --> 01:41:13,280
Speaker 1: not being a predatory. Point. Yeah, it's hard to kind

1762
01:41:13,280 --> 01:41:16,640
Speaker 1: of bitch about the fact that, well, the predators from

1763
01:41:16,720 --> 01:41:19,760
Speaker 1: the west are going to fill that niche if they

1764
01:41:19,840 --> 01:41:23,840
Speaker 1: have the opportunity. And so when people tell me, well,

1765
01:41:23,960 --> 01:41:26,040
Speaker 1: you know, everywhere in the South, I'm going to kill

1766
01:41:26,120 --> 01:41:30,160
Speaker 1: every coyote, I c uh, it always makes me think, well,

1767
01:41:30,200 --> 01:41:32,240
Speaker 1: you know, a hundred years ago, you'd have had wolves here,

1768
01:41:32,280 --> 01:41:34,760
Speaker 1: and so that's why there wouldn't have been coyotes in

1769
01:41:34,800 --> 01:41:37,960
Speaker 1: the woods. And I think, like, like we said earlier,

1770
01:41:38,000 --> 01:41:40,559
Speaker 1: there was a moment in time which I was kind

1771
01:41:40,600 --> 01:41:42,479
Speaker 1: of a part of where it's like, they're coming in,

1772
01:41:43,040 --> 01:41:46,160
Speaker 1: they're here, Like, what do we do that they're here?

1773
01:41:46,200 --> 01:41:48,320
Speaker 1: Now you know they weren't here before they're here, Now

1774
01:41:48,400 --> 01:41:50,679
Speaker 1: what do we do kill them all if if they're

1775
01:41:50,680 --> 01:41:52,760
Speaker 1: going to have a negative effect, because what are they

1776
01:41:52,800 --> 01:41:55,880
Speaker 1: coming here to do? Not coming here to play sports

1777
01:41:55,960 --> 01:41:58,720
Speaker 1: and go to the library, coming here to kill and

1778
01:41:58,880 --> 01:42:02,639
Speaker 1: pray upon the things that we've worked hard to kind

1779
01:42:02,720 --> 01:42:06,080
Speaker 1: of balance and and grow. So there was that moment.

1780
01:42:06,160 --> 01:42:09,760
Speaker 1: I think it's probably an honest moment to be they're here,

1781
01:42:10,240 --> 01:42:13,280
Speaker 1: we got to figure something out. But now, but now

1782
01:42:13,320 --> 01:42:16,120
Speaker 1: they're everywhere, so that we're past that moment. It I mean,

1783
01:42:16,520 --> 01:42:19,800
Speaker 1: you're right, that was a moment, but that was a

1784
01:42:20,000 --> 01:42:25,000
Speaker 1: moment of a specific couple of generations, because a generation

1785
01:42:25,200 --> 01:42:28,080
Speaker 1: or two back from there, what you would have been

1786
01:42:28,120 --> 01:42:31,439
Speaker 1: seeing was well, fewer and fewer wolves all the time,

1787
01:42:32,000 --> 01:42:34,439
Speaker 1: fewer and fewer wolves. There should be wolves still here.

1788
01:42:34,760 --> 01:42:37,120
Speaker 1: And then finally we reach a period of two or

1789
01:42:37,200 --> 01:42:39,680
Speaker 1: three generations where while there are no wolves at all,

1790
01:42:39,960 --> 01:42:43,040
Speaker 1: and we got used to that, but that's not the

1791
01:42:43,320 --> 01:42:47,680
Speaker 1: natural world of North America. It's just not natural for

1792
01:42:47,880 --> 01:42:51,360
Speaker 1: us to have no predators on the continent. That's what

1793
01:42:51,520 --> 01:42:55,280
Speaker 1: we managed to create for a while, and everybody got

1794
01:42:55,360 --> 01:42:57,559
Speaker 1: pretty used to it, to be sure. And so now

1795
01:42:58,439 --> 01:43:01,240
Speaker 1: having to confront the fact that predators are back, you know,

1796
01:43:01,360 --> 01:43:04,320
Speaker 1: we're kind of that's super interesting, man, to think about

1797
01:43:04,360 --> 01:43:08,280
Speaker 1: it that way, because then in that scenario, the coyote

1798
01:43:08,360 --> 01:43:12,000
Speaker 1: come becomes the symbol of what of like taking it back.

1799
01:43:12,200 --> 01:43:14,880
Speaker 1: It's the rewilding of the East and the South. I

1800
01:43:14,960 --> 01:43:16,680
Speaker 1: never really thought about that way, but it's like it's

1801
01:43:16,840 --> 01:43:19,840
Speaker 1: there's there was always predators. There was always going to

1802
01:43:19,880 --> 01:43:22,000
Speaker 1: be predators. We did a nice job within our manifest

1803
01:43:22,040 --> 01:43:25,280
Speaker 1: destiny time of kind of of changing the way that

1804
01:43:25,800 --> 01:43:28,479
Speaker 1: everything works. But nature has its way of like, hey

1805
01:43:28,800 --> 01:43:30,800
Speaker 1: we have this animal, Oh we know, we know who

1806
01:43:30,840 --> 01:43:34,960
Speaker 1: can do that job. Coyotes go on. It's that line

1807
01:43:35,000 --> 01:43:40,360
Speaker 1: from Jurassic Park. No, that's that's if you're looking at

1808
01:43:40,439 --> 01:43:42,600
Speaker 1: it with an open mind. You have to see that.

1809
01:43:43,240 --> 01:43:46,360
Speaker 1: You have to and and go at it if you

1810
01:43:46,520 --> 01:43:48,839
Speaker 1: if you're approaching it from that angle, then you're approaching

1811
01:43:48,880 --> 01:43:50,560
Speaker 1: it with an open mind like, hey, look, this was

1812
01:43:50,600 --> 01:43:54,720
Speaker 1: always going to happen. What we got used to is not.

1813
01:43:56,040 --> 01:43:58,960
Speaker 1: It's it's natural for us. But we choose like periods

1814
01:43:58,960 --> 01:44:02,280
Speaker 1: of time as native even natural. We're just choosing periods

1815
01:44:02,320 --> 01:44:04,519
Speaker 1: of time here. But when you look at a million years,

1816
01:44:04,640 --> 01:44:07,600
Speaker 1: that's that's the full boat as far as well we

1817
01:44:07,640 --> 01:44:10,599
Speaker 1: can really you know what the context provides. Well, that's

1818
01:44:10,600 --> 01:44:14,080
Speaker 1: exactly right. And I mean that's how I try to

1819
01:44:14,200 --> 01:44:17,479
Speaker 1: when I write about animals in in Coyote America or

1820
01:44:17,560 --> 01:44:19,560
Speaker 1: in the other book that I published a couple of

1821
01:44:19,600 --> 01:44:23,400
Speaker 1: years ago, American Serengetti, which is about you know, these

1822
01:44:23,560 --> 01:44:26,040
Speaker 1: big animals that we had on the American Great Plains

1823
01:44:26,120 --> 01:44:28,120
Speaker 1: that we lost and we don't even have a historical

1824
01:44:28,200 --> 01:44:30,960
Speaker 1: memory in the United States of only a hundred and

1825
01:44:31,000 --> 01:44:34,320
Speaker 1: twenty five years ago we had a beast sheary in

1826
01:44:34,400 --> 01:44:37,440
Speaker 1: the central part of the United States that was comparable

1827
01:44:37,560 --> 01:44:40,800
Speaker 1: to that of Africa, and we don't even remember that

1828
01:44:40,960 --> 01:44:44,080
Speaker 1: it was there. But that was the largest destruction of

1829
01:44:44,200 --> 01:44:47,960
Speaker 1: animal life anywhere in world history that I was able

1830
01:44:48,000 --> 01:44:50,320
Speaker 1: to discover when I was writing that book. I mean,

1831
01:44:50,360 --> 01:44:54,519
Speaker 1: we took out thirty million bison and fifteen million prong horns.

1832
01:44:54,560 --> 01:44:58,400
Speaker 1: I mean it just it's five to six million wild horses,

1833
01:44:58,640 --> 01:45:02,799
Speaker 1: even in order eradicate this beast area from the American

1834
01:45:02,840 --> 01:45:08,040
Speaker 1: Great Plains. But if you understand, you know, being a

1835
01:45:08,200 --> 01:45:11,720
Speaker 1: hunter or being somewhat observing the natural world in the

1836
01:45:11,880 --> 01:45:16,080
Speaker 1: context of a bigger history than just the immediate time

1837
01:45:16,200 --> 01:45:19,320
Speaker 1: frame that you're in, then suddenly all this starts making

1838
01:45:19,479 --> 01:45:21,800
Speaker 1: a kind of a sense that you've you've never thought of,

1839
01:45:21,920 --> 01:45:24,800
Speaker 1: and we tend to think about hunters is being okay,

1840
01:45:24,880 --> 01:45:27,880
Speaker 1: this is a timeless tradition that we've always engaged in.

1841
01:45:28,360 --> 01:45:30,479
Speaker 1: I mean, we came out of Africa as hunters, we

1842
01:45:30,520 --> 01:45:32,679
Speaker 1: spread around the world as hunters. This is something we've

1843
01:45:32,880 --> 01:45:35,840
Speaker 1: always done. Well, we need to think about the animals

1844
01:45:36,080 --> 01:45:40,360
Speaker 1: in the same way. Not just Okay, I'm a hunter.

1845
01:45:40,520 --> 01:45:43,879
Speaker 1: I come from two million years of evolution out of Africa.

1846
01:45:44,560 --> 01:45:47,080
Speaker 1: But all I can think of is this five year

1847
01:45:47,200 --> 01:45:50,120
Speaker 1: or ten year period that I happen to be hunting deering. Yeah,

1848
01:45:50,120 --> 01:45:52,559
Speaker 1: and you'll find our will find ourselves as hunters tradition.

1849
01:45:52,600 --> 01:45:54,120
Speaker 1: I think talking on both sides of her mouth when

1850
01:45:54,160 --> 01:45:56,760
Speaker 1: that's concerned, you know, in defending hunting, it's like, well,

1851
01:45:56,800 --> 01:45:59,200
Speaker 1: we've always done this. This is our blood, it's in

1852
01:45:59,280 --> 01:46:01,960
Speaker 1: our blood, it's in genetics to do this. And at

1853
01:46:02,000 --> 01:46:04,679
Speaker 1: the same time we're like, well, you know we want

1854
01:46:05,240 --> 01:46:07,320
Speaker 1: I want big bucks. Well here's what I gotta do

1855
01:46:07,400 --> 01:46:08,920
Speaker 1: to get that, And so you end up kind of

1856
01:46:10,200 --> 01:46:13,639
Speaker 1: wanting to use the pro side of hunting being really

1857
01:46:13,720 --> 01:46:16,000
Speaker 1: what made us and a lot of sense has made

1858
01:46:16,040 --> 01:46:18,479
Speaker 1: us who we are and what we are in the

1859
01:46:18,560 --> 01:46:22,040
Speaker 1: sense of human evolution. But we can't then just address

1860
01:46:22,640 --> 01:46:26,719
Speaker 1: wildlife in the natural world and conservation in the context

1861
01:46:26,800 --> 01:46:29,200
Speaker 1: of only the time in which we live. That's yeah,

1862
01:46:29,360 --> 01:46:32,360
Speaker 1: that's that's certainly my point. Yeah, I think that's I

1863
01:46:32,439 --> 01:46:35,599
Speaker 1: think it's worth repeating just because it's it should there

1864
01:46:35,600 --> 01:46:38,400
Speaker 1: should be some profundity in it for anybody who really

1865
01:46:38,479 --> 01:46:42,439
Speaker 1: cares about in the ecosystem, past, present, future or whatever,

1866
01:46:42,680 --> 01:46:44,960
Speaker 1: you know, because it's it's a relationship that we all

1867
01:46:45,000 --> 01:46:47,160
Speaker 1: have that's important. Which it was just another part of,

1868
01:46:47,400 --> 01:46:52,800
Speaker 1: you know, of hunting being in nature. Uh what we

1869
01:46:52,960 --> 01:46:56,679
Speaker 1: always think, what we argue when when you defend hunting,

1870
01:46:57,000 --> 01:46:59,920
Speaker 1: one of the things you say is that, Okay, much

1871
01:47:00,000 --> 01:47:03,880
Speaker 1: sch of it is about being outdoors, being engaged with

1872
01:47:04,600 --> 01:47:08,639
Speaker 1: with nature, being engaged with animals, and so it's bigger,

1873
01:47:09,400 --> 01:47:11,719
Speaker 1: a bigger thing. I think it should be a bigger

1874
01:47:11,800 --> 01:47:16,040
Speaker 1: thing than just Okay, I shot an eight point white

1875
01:47:16,080 --> 01:47:20,280
Speaker 1: tail last week. It should be about seeing Jupiter in

1876
01:47:20,360 --> 01:47:25,280
Speaker 1: the sky before the sun came up, and hearing woodpeckers

1877
01:47:26,280 --> 01:47:31,559
Speaker 1: banging on hardwood trees, uh in that twilight, and hearing

1878
01:47:31,640 --> 01:47:35,120
Speaker 1: squirrels chattering, and watching a red tail hawk come over

1879
01:47:35,240 --> 01:47:38,080
Speaker 1: and swoop down on something that you can't quite tell

1880
01:47:38,200 --> 01:47:41,840
Speaker 1: what it is, and and seeing a coyote trot by.

1881
01:47:42,080 --> 01:47:45,120
Speaker 1: And I mean that's all a part of the the

1882
01:47:45,280 --> 01:47:49,479
Speaker 1: whole of being out there. It's not just the act

1883
01:47:49,600 --> 01:47:53,080
Speaker 1: of pulling the trigger and dropping the animals. Ay man, Yeah,

1884
01:47:53,120 --> 01:47:55,400
Speaker 1: I think there was a tern that that's been used

1885
01:47:55,400 --> 01:47:57,720
Speaker 1: around me a bunch lately, and we've been working on

1886
01:47:57,800 --> 01:47:59,400
Speaker 1: what I was telling you about the back forty project

1887
01:47:59,479 --> 01:48:01,920
Speaker 1: we were working on of Michigan. And there's a term

1888
01:48:02,000 --> 01:48:03,960
Speaker 1: we heard from a bunch of people kind of in

1889
01:48:04,040 --> 01:48:08,240
Speaker 1: a confluence ecosystem services, And I used that in the

1890
01:48:08,320 --> 01:48:11,840
Speaker 1: last episode we're talking about snakes. But for whatever reason,

1891
01:48:11,960 --> 01:48:15,040
Speaker 1: that term and the idea around it helps me understand

1892
01:48:15,840 --> 01:48:19,479
Speaker 1: different species. And it's like each thing has a service

1893
01:48:20,000 --> 01:48:23,040
Speaker 1: to the ecosystem and to erase any one of those

1894
01:48:23,080 --> 01:48:25,320
Speaker 1: things is to eliminate that service, you know. And so

1895
01:48:25,479 --> 01:48:28,240
Speaker 1: can we take people through kind of what that is

1896
01:48:28,320 --> 01:48:31,640
Speaker 1: for kyles, Like what do they bring to these ecosystems? Well,

1897
01:48:32,000 --> 01:48:36,519
Speaker 1: are they occupy the niche of the mid size predator,

1898
01:48:36,840 --> 01:48:41,240
Speaker 1: which is present all over the world. Um jackals occupy

1899
01:48:41,439 --> 01:48:44,080
Speaker 1: that niche in Africa, in the Middle East and increasingly

1900
01:48:44,160 --> 01:48:48,000
Speaker 1: Europe because jackals, which are fairly closely related to coyotes,

1901
01:48:48,120 --> 01:48:49,800
Speaker 1: only split from them a little more than a million

1902
01:48:49,880 --> 01:48:52,479
Speaker 1: years ago, especially the golden jackals, And I've seen like

1903
01:48:52,520 --> 01:48:55,160
Speaker 1: golden is very similar, very similar. They look very much

1904
01:48:55,200 --> 01:48:59,879
Speaker 1: like coyotes, and they are expanding through Europe. Uh tasma

1905
01:49:00,000 --> 01:49:04,479
Speaker 1: An and devils in Tasmania occupy the niche of the

1906
01:49:04,800 --> 01:49:08,360
Speaker 1: excuse me, the mid sized predator. Everywhere in the world.

1907
01:49:08,640 --> 01:49:13,439
Speaker 1: Every ecology has developed, uh, a large predator for for

1908
01:49:13,720 --> 01:49:17,400
Speaker 1: large prey, a mid sized predator, and smaller predators like

1909
01:49:17,640 --> 01:49:20,880
Speaker 1: minks for example, and weasels and things like that. But

1910
01:49:21,000 --> 01:49:24,880
Speaker 1: there's always a mid sized predator everywhere that nature has

1911
01:49:25,280 --> 01:49:28,679
Speaker 1: evolved to fill all the normal niches. And so those

1912
01:49:28,720 --> 01:49:33,479
Speaker 1: midsized predators, uh, they keep a balance, for example, in

1913
01:49:33,760 --> 01:49:38,280
Speaker 1: terms of the numbers of skunks and weasels and raccoons

1914
01:49:38,840 --> 01:49:43,000
Speaker 1: remain lower when the mid sized predator niche is filled. Uh.

1915
01:49:43,360 --> 01:49:48,200
Speaker 1: Every place that we've come close to eliminating coyotes, and

1916
01:49:48,479 --> 01:49:50,880
Speaker 1: and the truth is, of course, as people who read

1917
01:49:50,960 --> 01:49:55,080
Speaker 1: my book will understand, it's essentially impossible, as a result

1918
01:49:55,160 --> 01:49:59,880
Speaker 1: of the peculiar evolution of coyotes alongside wolves, to rem

1919
01:50:00,000 --> 01:50:03,400
Speaker 1: move coyotes, which is another part of the shooting them.

1920
01:50:03,560 --> 01:50:06,840
Speaker 1: You may think you're doing good, you're actually even in

1921
01:50:06,960 --> 01:50:10,200
Speaker 1: that sort of practical sense, you're not doing so. But

1922
01:50:10,360 --> 01:50:13,880
Speaker 1: the niche of the mid sized predator is critical in nature,

1923
01:50:14,320 --> 01:50:17,479
Speaker 1: and so uh, as I said, there's kind of nowhere

1924
01:50:17,520 --> 01:50:19,599
Speaker 1: around the world you can find a place where there's

1925
01:50:19,640 --> 01:50:22,400
Speaker 1: not an animal that occupies that niche that the coyote

1926
01:50:22,479 --> 01:50:24,680
Speaker 1: does here. Now, that's a great way to look at it.

1927
01:50:24,680 --> 01:50:26,640
Speaker 1: And what do you think about trophic cascade? Is that

1928
01:50:26,760 --> 01:50:29,200
Speaker 1: something that like I've heard it use and I've heard

1929
01:50:29,240 --> 01:50:32,000
Speaker 1: it decried. I've I've kind of seen that term bounce around.

1930
01:50:32,560 --> 01:50:34,760
Speaker 1: You have a perspective on that, well, I mean one

1931
01:50:34,800 --> 01:50:37,679
Speaker 1: of the ways to to watch it, uh and see

1932
01:50:37,680 --> 01:50:40,080
Speaker 1: it in action. We should explain, I'm sorry, explain what

1933
01:50:40,120 --> 01:50:44,800
Speaker 1: that is first. The trophic cascade is what happens in

1934
01:50:44,960 --> 01:50:48,120
Speaker 1: nature when a species is removed from its niche. And

1935
01:50:48,200 --> 01:50:50,880
Speaker 1: the one that most of us are familiar with these days,

1936
01:50:50,960 --> 01:50:53,320
Speaker 1: because you can, of course go on YouTube and see

1937
01:50:53,360 --> 01:50:56,200
Speaker 1: examples of it, uh, is the removal of the gray

1938
01:50:56,240 --> 01:50:59,280
Speaker 1: wolf in the West and particularly in Yellowstone National Park.

1939
01:50:59,720 --> 01:51:03,200
Speaker 1: So gray wolves the last gray wolves are killed in

1940
01:51:03,280 --> 01:51:07,599
Speaker 1: Yellowstone in nine so there are no wolves in Yellowstone

1941
01:51:07,600 --> 01:51:13,280
Speaker 1: from when we reintroduced them, uh, period of seventy years.

1942
01:51:14,120 --> 01:51:17,320
Speaker 1: It's that's a very useful period, by the way, and

1943
01:51:17,439 --> 01:51:21,320
Speaker 1: I devote some time to it for coyotes in Yellowstone

1944
01:51:22,080 --> 01:51:27,640
Speaker 1: because coyote evolution alongside wolves is what has given them

1945
01:51:27,880 --> 01:51:32,280
Speaker 1: coyotes their wariness, their intelligence, and their ability to survive

1946
01:51:32,680 --> 01:51:36,720
Speaker 1: almost anything that wolves are humans can throw at them

1947
01:51:36,800 --> 01:51:39,559
Speaker 1: to try to diminish their numbers. They evolved a number

1948
01:51:39,760 --> 01:51:43,800
Speaker 1: of adaptations that allowed them to survive wolf harassment that

1949
01:51:44,200 --> 01:51:47,320
Speaker 1: when we started harassing them, they began to employ against

1950
01:51:47,400 --> 01:51:50,760
Speaker 1: our efforts too. But that period of seventy years where

1951
01:51:51,040 --> 01:51:54,960
Speaker 1: there are no wolves in Yellowstone but the coyote population

1952
01:51:55,120 --> 01:51:58,120
Speaker 1: is there, one of the things we realize is that

1953
01:51:58,479 --> 01:52:03,200
Speaker 1: when coyotes are not harassed and not persecuted, their population

1954
01:52:03,320 --> 01:52:06,000
Speaker 1: doesn't just keep growing and growing and growing so that

1955
01:52:06,120 --> 01:52:09,400
Speaker 1: they spill out of Yellowstone and and just run amuck

1956
01:52:09,479 --> 01:52:13,479
Speaker 1: all over the whole West. Coyotes, like most animals, rise

1957
01:52:13,640 --> 01:52:16,720
Speaker 1: to the level of the carrying capacity of the landscape,

1958
01:52:17,200 --> 01:52:21,160
Speaker 1: and their numbers don't really grow beyond that. So one

1959
01:52:21,200 --> 01:52:23,880
Speaker 1: of the things that biologists who were studying coyotes and

1960
01:52:23,960 --> 01:52:28,800
Speaker 1: Yellowstone during this interval when wolves weren't there realized is that, wow,

1961
01:52:29,400 --> 01:52:32,479
Speaker 1: the normal litter size for coyotes is about five to

1962
01:52:32,680 --> 01:52:36,960
Speaker 1: six pups. But in this situation where coyote numbers have

1963
01:52:37,160 --> 01:52:41,080
Speaker 1: risen to the level of the carrying capacity, they're only

1964
01:52:41,160 --> 01:52:43,320
Speaker 1: able to get they may have four or five pups,

1965
01:52:43,400 --> 01:52:46,880
Speaker 1: but they're only able to raise a couple because there's

1966
01:52:46,920 --> 01:52:49,519
Speaker 1: just not the space on the landscape for any more

1967
01:52:49,600 --> 01:52:54,960
Speaker 1: of them. But the trophic realization, the trophic cascade realization

1968
01:52:55,120 --> 01:53:00,439
Speaker 1: comes when we reintroduce wolves back into the park. And

1969
01:53:00,600 --> 01:53:05,400
Speaker 1: when wolves gray wolves get back into Yellowstone, the population

1970
01:53:05,520 --> 01:53:07,839
Speaker 1: of coyotes, and this is sort of the way trophic

1971
01:53:07,960 --> 01:53:12,840
Speaker 1: cascades work all the way down the line. While coyotes

1972
01:53:12,920 --> 01:53:16,080
Speaker 1: were there and wolves were not, we think the numbers

1973
01:53:16,160 --> 01:53:20,840
Speaker 1: of raccoons, skunks, and weasels probably went down, and even

1974
01:53:21,040 --> 01:53:25,320
Speaker 1: foxes probably went down because of the effect of coyotes

1975
01:53:25,520 --> 01:53:29,000
Speaker 1: rising to the level of the carrying capacity. When wolves

1976
01:53:29,120 --> 01:53:33,559
Speaker 1: come in, the number of coyotes drops by nearly fifty

1977
01:53:34,400 --> 01:53:39,240
Speaker 1: in Yellowstone. That allows the number of weasels, minks, skunks,

1978
01:53:39,360 --> 01:53:43,400
Speaker 1: and raccoons to rise. And of course the other effect

1979
01:53:43,520 --> 01:53:51,000
Speaker 1: it has because prey animals, their instinct about predators is

1980
01:53:51,520 --> 01:53:57,759
Speaker 1: unless they have been culturally trained to flee, they don't

1981
01:53:57,840 --> 01:54:02,080
Speaker 1: really flee predators. And we had several generations of elk

1982
01:54:02,520 --> 01:54:06,320
Speaker 1: in Yellowstone National Park that had not learned what to

1983
01:54:06,439 --> 01:54:10,120
Speaker 1: do when wolves come back on the landscape and elk

1984
01:54:10,320 --> 01:54:13,760
Speaker 1: basically stood around and let wolves just run them down

1985
01:54:14,160 --> 01:54:17,320
Speaker 1: and kill them one after another. But when wolves finally

1986
01:54:17,360 --> 01:54:20,400
Speaker 1: did start scaring the crap out of the elk population

1987
01:54:20,760 --> 01:54:23,400
Speaker 1: in Yellowstone and of course lowering their numbers as a

1988
01:54:23,479 --> 01:54:27,519
Speaker 1: result of predation, that began to produce an effect on

1989
01:54:28,479 --> 01:54:32,760
Speaker 1: the plant community, so that suddenly you've got cotton woods

1990
01:54:32,880 --> 01:54:38,840
Speaker 1: and aspens able to grow again when elk herbivory had

1991
01:54:38,920 --> 01:54:43,160
Speaker 1: basically kept those species almost cropped down to the point

1992
01:54:43,200 --> 01:54:47,720
Speaker 1: where they couldn't replace themselves. So the Yellowstone with the

1993
01:54:47,840 --> 01:54:52,360
Speaker 1: wolf recovery has provided this kind of remarkable look at

1994
01:54:53,240 --> 01:54:56,560
Speaker 1: a landscape that when it's complete it looks like this,

1995
01:54:56,840 --> 01:55:00,200
Speaker 1: but when you take one animal out or another animal out,

1996
01:55:00,520 --> 01:55:04,800
Speaker 1: it changes the whole landscape, even down to the plant communities. Yeah,

1997
01:55:05,240 --> 01:55:08,280
Speaker 1: that's so compelling, And and the coyotes like where it

1998
01:55:08,400 --> 01:55:10,720
Speaker 1: sits and all. This whole story kind of to me

1999
01:55:10,920 --> 01:55:13,520
Speaker 1: is painted well both in that but in also like

2000
01:55:14,160 --> 01:55:16,960
Speaker 1: we went through at the turn of the century and

2001
01:55:17,040 --> 01:55:18,520
Speaker 1: on into what we'll call, I guess we could just

2002
01:55:18,560 --> 01:55:21,800
Speaker 1: call like the conservation and recovery period of our hunting

2003
01:55:21,920 --> 01:55:25,520
Speaker 1: history if we can market somehow. It's like we we've

2004
01:55:26,520 --> 01:55:29,600
Speaker 1: we wiped out a lot of things. We established some

2005
01:55:29,680 --> 01:55:33,560
Speaker 1: principles and practices and ideologies that would help us bring

2006
01:55:33,680 --> 01:55:37,240
Speaker 1: those things back more in certain landscapes than others. Right,

2007
01:55:37,280 --> 01:55:39,160
Speaker 1: We've picked yellow stone in other places to kind of

2008
01:55:39,240 --> 01:55:43,840
Speaker 1: have these havens, and now we're kind of there, like

2009
01:55:44,440 --> 01:55:46,120
Speaker 1: in a lot of ways with unclos were in the

2010
01:55:46,400 --> 01:55:48,560
Speaker 1: best of times. You know, there's more white tail deer

2011
01:55:48,600 --> 01:55:51,560
Speaker 1: here than wind. Columbus put a boat down, didn't know

2012
01:55:51,560 --> 01:55:56,920
Speaker 1: where he was. We're so we we've have to kind

2013
01:55:56,960 --> 01:55:59,920
Speaker 1: of I think I've been thinking this lately. We kind

2014
01:56:00,000 --> 01:56:01,600
Speaker 1: of have to start to adjust the way that we

2015
01:56:02,000 --> 01:56:04,520
Speaker 1: we look at things were no longer our model of

2016
01:56:04,600 --> 01:56:07,880
Speaker 1: conservation is no longer helping to recover many of these things.

2017
01:56:08,640 --> 01:56:11,360
Speaker 1: It's looking at like, how do we manage what's here,

2018
01:56:11,920 --> 01:56:15,120
Speaker 1: keep it where it is, provide balance, and then allow

2019
01:56:15,280 --> 01:56:18,080
Speaker 1: some of these things that we've we've extrapated to come

2020
01:56:18,120 --> 01:56:21,480
Speaker 1: back and find a way to be and hopefully, hopefully

2021
01:56:21,600 --> 01:56:24,200
Speaker 1: hunting can can help facilitate that in a way that

2022
01:56:24,320 --> 01:56:27,240
Speaker 1: makes sense. And that's where we get to some of

2023
01:56:27,280 --> 01:56:29,440
Speaker 1: the arguments that we have and we've had over grizzly

2024
01:56:29,520 --> 01:56:32,560
Speaker 1: bears and gray wolves and things like that. So I

2025
01:56:32,640 --> 01:56:34,080
Speaker 1: think if you can maybe come into it with like

2026
01:56:34,240 --> 01:56:36,760
Speaker 1: maybe an honest I don't know if you agree with

2027
01:56:36,840 --> 01:56:39,320
Speaker 1: that kind of characterization of where we are, but like,

2028
01:56:39,440 --> 01:56:41,120
Speaker 1: if we can come to it with sort of an

2029
01:56:41,160 --> 01:56:43,760
Speaker 1: honest look at kind of the current state of being,

2030
01:56:43,800 --> 01:56:45,720
Speaker 1: that maybe we could address it better. Because there certainly

2031
01:56:45,840 --> 01:56:47,600
Speaker 1: is a lot of fervor and a lot of anger

2032
01:56:47,720 --> 01:56:50,600
Speaker 1: around predators and what we do with them and in

2033
01:56:50,680 --> 01:56:54,920
Speaker 1: the roles of of us. Yeah, there is. I think

2034
01:56:55,000 --> 01:56:57,720
Speaker 1: we're getting there though, and I have I have great,

2035
01:56:58,120 --> 01:57:03,400
Speaker 1: great hopes for coming generations because I think the coming

2036
01:57:03,440 --> 01:57:07,720
Speaker 1: generations if they if they read uh, and if they

2037
01:57:08,480 --> 01:57:12,320
Speaker 1: pay attention to good science, uh and read science, and

2038
01:57:13,040 --> 01:57:18,360
Speaker 1: because what science basically is, it's for people who are outdoors.

2039
01:57:18,560 --> 01:57:22,600
Speaker 1: It's woodcraft, it's mountain craft, it's river craft. It's I mean,

2040
01:57:22,960 --> 01:57:25,720
Speaker 1: as I was telling you earlier today we were having lunch.

2041
01:57:25,800 --> 01:57:28,720
Speaker 1: You know, one of the experiences I've I've been getting

2042
01:57:28,760 --> 01:57:32,560
Speaker 1: to enjoy and doing talks around the country about both

2043
01:57:32,600 --> 01:57:38,080
Speaker 1: the Coyote Book and American Serengetti is having uh people

2044
01:57:38,200 --> 01:57:43,040
Speaker 1: who are wilderness guides uh come to these reading events

2045
01:57:43,120 --> 01:57:46,320
Speaker 1: that I've been doing and basically saying man, I've been

2046
01:57:46,440 --> 01:57:50,280
Speaker 1: absorbing the stuff from your books. I heard about you.

2047
01:57:50,440 --> 01:57:54,080
Speaker 1: I learned about you from Joe Rogan podcasts or Stephen

2048
01:57:54,160 --> 01:57:57,440
Speaker 1: Ronella podcasts a Mediator podcast, and I got your books,

2049
01:57:57,440 --> 01:58:00,560
Speaker 1: and I've been absorbing that information because it's giving me

2050
01:58:00,760 --> 01:58:04,720
Speaker 1: additional woodcraft and mountain craft. And so, I mean, that's

2051
01:58:04,840 --> 01:58:09,680
Speaker 1: really kind of what science does. If you absorb it

2052
01:58:09,800 --> 01:58:13,640
Speaker 1: and incorporated, it makes your experience of the world out

2053
01:58:13,680 --> 01:58:18,280
Speaker 1: there that much richer that you suddenly began to understand

2054
01:58:18,360 --> 01:58:21,160
Speaker 1: how it works, how it's worked in the past, how

2055
01:58:21,680 --> 01:58:23,880
Speaker 1: we changed it without I mean, we didn't know what

2056
01:58:23,960 --> 01:58:26,000
Speaker 1: the hell we were doing when we were getting rid

2057
01:58:26,040 --> 01:58:28,760
Speaker 1: of all those predators. We just were employing the European

2058
01:58:29,040 --> 01:58:31,960
Speaker 1: standard of you know, you wipe out the wolves. That's

2059
01:58:32,000 --> 01:58:36,760
Speaker 1: what they did in Europe even years ago. So we

2060
01:58:36,920 --> 01:58:39,440
Speaker 1: just came to North America and did the same thing

2061
01:58:39,600 --> 01:58:42,600
Speaker 1: without really understanding what the consequences were going to be.

2062
01:58:42,840 --> 01:58:46,360
Speaker 1: And now we're getting an opportunity to, you know, to

2063
01:58:46,480 --> 01:58:50,560
Speaker 1: experience the whole enchilata, the entire heaven and entire earth

2064
01:58:51,880 --> 01:58:54,680
Speaker 1: work like yours is. Like it provides some some level

2065
01:58:54,720 --> 01:58:58,520
Speaker 1: of empowerment to someone that's looking to make these informed choices.

2066
01:58:58,840 --> 01:59:01,880
Speaker 1: You know, we've I've had folk on the podcast. Had

2067
01:59:02,080 --> 01:59:04,240
Speaker 1: a friend of mine due Shawn's Mentana on the podcast

2068
01:59:04,320 --> 01:59:07,920
Speaker 1: that was grew up in Czechoslovakia, and he talked about

2069
01:59:09,240 --> 01:59:12,560
Speaker 1: this idea of hunters being this this great source of

2070
01:59:12,720 --> 01:59:15,520
Speaker 1: knowledge because they were the selectors. They were the ones

2071
01:59:15,600 --> 01:59:17,920
Speaker 1: going out into the wilderness and decide like they had

2072
01:59:17,960 --> 01:59:20,360
Speaker 1: to take stock of everything that was in the woods

2073
01:59:20,360 --> 01:59:22,440
Speaker 1: because they had to understand what the selective was not

2074
01:59:22,560 --> 01:59:26,480
Speaker 1: the select and they had this great responsibility within not

2075
01:59:26,680 --> 01:59:29,879
Speaker 1: only like the smaller communities about it, in the greater culture.

2076
01:59:30,960 --> 01:59:34,560
Speaker 1: It's in. We have some of that still, but it's

2077
01:59:34,600 --> 01:59:38,000
Speaker 1: it's it's messy, it's it's it's involved in all the

2078
01:59:38,080 --> 01:59:39,560
Speaker 1: other things we did. Like you said that, we didn't

2079
01:59:39,600 --> 01:59:41,440
Speaker 1: know what we were doing at the time, and so

2080
01:59:41,560 --> 01:59:44,360
Speaker 1: we had a lot of looking back at our you know,

2081
01:59:44,880 --> 01:59:49,600
Speaker 1: our predestined move across this country. Like we fixed a

2082
01:59:49,640 --> 01:59:52,280
Speaker 1: lot of it, but we're not all the way there now,

2083
01:59:52,360 --> 01:59:54,560
Speaker 1: we're not all way there. But you know that's kind

2084
01:59:54,600 --> 01:59:59,280
Speaker 1: of what the big context, the big history is for,

2085
02:00:00,080 --> 02:00:06,560
Speaker 1: is uh, wrapping your head around the long term patterns

2086
02:00:06,880 --> 02:00:12,960
Speaker 1: and trying to understand where along the line of the

2087
02:00:13,120 --> 02:00:18,360
Speaker 1: trajectory we are and how you correct the errors that

2088
02:00:18,680 --> 02:00:21,200
Speaker 1: we've made in the past, and how you try to

2089
02:00:21,640 --> 02:00:25,080
Speaker 1: set up a future that's going to be more equitable

2090
02:00:25,240 --> 02:00:30,000
Speaker 1: for for not just us. It's not all about us,

2091
02:00:30,520 --> 02:00:33,400
Speaker 1: of course, it's about all the rest of the natural

2092
02:00:33,440 --> 02:00:37,040
Speaker 1: world that's out there. And so uh, as I said,

2093
02:00:37,120 --> 02:00:40,520
Speaker 1: I'm I'm I'm optimistic, especially for the you know, the

2094
02:00:40,640 --> 02:00:45,280
Speaker 1: coming generations. I think I think that the generations that

2095
02:00:45,480 --> 02:00:48,200
Speaker 1: are here now and are are you know, on the

2096
02:00:48,360 --> 02:00:53,320
Speaker 1: eve of emerging, uh in sort of manning the tiller

2097
02:00:53,440 --> 02:00:56,520
Speaker 1: of the direction of the country. Uh, They're going to

2098
02:00:56,560 --> 02:01:00,520
Speaker 1: be less influenced by the kind of propagand and like

2099
02:01:00,720 --> 02:01:04,640
Speaker 1: the Bureau of Biological Survey was putting out about predators

2100
02:01:04,720 --> 02:01:07,720
Speaker 1: in the twenties, thirties and forties, Yeah, what what is

2101
02:01:07,760 --> 02:01:09,720
Speaker 1: there to kind of put a bowl on that? What

2102
02:01:10,680 --> 02:01:12,320
Speaker 1: what is there that people can go out and grab?

2103
02:01:12,400 --> 02:01:14,680
Speaker 1: And we've we've covered cloudy America. But when we're looking

2104
02:01:14,720 --> 02:01:16,480
Speaker 1: for data and looking for like what what are the

2105
02:01:16,560 --> 02:01:18,720
Speaker 1: things the key in on is like, hey, this is valuable,

2106
02:01:18,840 --> 02:01:21,360
Speaker 1: this has value. Is there anything that you've in your

2107
02:01:21,680 --> 02:01:23,640
Speaker 1: putting the book together you had to I'm sure calmed

2108
02:01:23,720 --> 02:01:26,400
Speaker 1: through lots and lots of resources. Is there something that

2109
02:01:26,480 --> 02:01:31,440
Speaker 1: you use the tool to maybe to seek out legitimacy. Well,

2110
02:01:31,560 --> 02:01:37,640
Speaker 1: I'm I'm kind of a big advocate of understanding what

2111
02:01:37,960 --> 02:01:41,680
Speaker 1: was here, uh five hundred years ago, a thousand years ago.

2112
02:01:42,160 --> 02:01:44,080
Speaker 1: I mean, you go back twelve thousand years ago. Of

2113
02:01:44,160 --> 02:01:47,240
Speaker 1: course we had obsary that really was an analog of

2114
02:01:47,520 --> 02:01:53,040
Speaker 1: of Africa with mammoths and camels and ground slots and

2115
02:01:53,240 --> 02:01:56,480
Speaker 1: say were tooth cats and and you know, we humans,

2116
02:01:56,560 --> 02:02:01,520
Speaker 1: probably again without knowing what the hell we were doing, uh,

2117
02:02:01,680 --> 02:02:04,520
Speaker 1: probably played a major role in the simplification of that.

2118
02:02:04,640 --> 02:02:07,920
Speaker 1: And be Sherry ten thousand years ago to the eternal

2119
02:02:08,520 --> 02:02:11,280
Speaker 1: regret of all of the rest of us down the timeline.

2120
02:02:11,360 --> 02:02:14,160
Speaker 1: I mean, I'd love to be able to walk outside,

2121
02:02:14,360 --> 02:02:16,840
Speaker 1: uh you know, into the hills around Bozeman and see

2122
02:02:16,880 --> 02:02:19,640
Speaker 1: a herd of mammoths go by, and those things would

2123
02:02:19,680 --> 02:02:21,600
Speaker 1: have been here ten thousand years ago. I mean, we

2124
02:02:21,680 --> 02:02:25,520
Speaker 1: know there are mammoth sites within fifty miles of here. Um,

2125
02:02:26,320 --> 02:02:30,360
Speaker 1: so I I kind of uh, you know, I'm I'm

2126
02:02:30,400 --> 02:02:35,200
Speaker 1: an advocate of the big history thing. Um. You know,

2127
02:02:35,360 --> 02:02:37,839
Speaker 1: I won't say I'm necessarily a mammoth of really our

2128
02:02:37,920 --> 02:02:43,840
Speaker 1: advocate of rewilding with mammoths. Um. But I do think

2129
02:02:44,040 --> 02:02:51,240
Speaker 1: that North America is not too urbanized, not too developed

2130
02:02:51,720 --> 02:02:55,400
Speaker 1: for us to have a good semblance of the wild

2131
02:02:55,480 --> 02:03:02,080
Speaker 1: America that we managed to acquire when uh, when Europeans

2132
02:03:02,120 --> 02:03:05,120
Speaker 1: and native people met one another five hundred years ago.

2133
02:03:05,560 --> 02:03:08,200
Speaker 1: Indian people had managed over the ten thousand years since

2134
02:03:08,240 --> 02:03:10,840
Speaker 1: the plies to saying to keep things. I mean, they

2135
02:03:11,120 --> 02:03:14,920
Speaker 1: did pretty damn well for ten thousand years. And that's

2136
02:03:15,000 --> 02:03:17,640
Speaker 1: kind of the world i'd like to I'd like to see.

2137
02:03:18,320 --> 02:03:22,760
Speaker 1: And uh, it means that animals like coyotes and gray

2138
02:03:22,800 --> 02:03:26,720
Speaker 1: wolves deserve a place there. They're a functioning part of

2139
02:03:26,840 --> 02:03:30,600
Speaker 1: the ecology of this continent for millions of years. And

2140
02:03:31,280 --> 02:03:33,000
Speaker 1: who the hell were we to think that we were

2141
02:03:33,000 --> 02:03:36,120
Speaker 1: gonna walk in here and overnight just take them out

2142
02:03:36,200 --> 02:03:39,280
Speaker 1: without any thought. I think that's I find that in

2143
02:03:39,400 --> 02:03:42,840
Speaker 1: all of and there's very many contentious points, and for

2144
02:03:42,960 --> 02:03:45,360
Speaker 1: whatever reason, I like to run right out of it

2145
02:03:46,200 --> 02:03:49,600
Speaker 1: to do it that way. But I think in general

2146
02:03:49,720 --> 02:03:51,880
Speaker 1: that's a good place, Like that last statement you made

2147
02:03:51,920 --> 02:03:53,680
Speaker 1: is a good place to get into the middle where

2148
02:03:53,760 --> 02:03:55,560
Speaker 1: we can have a conversation, like if we all can

2149
02:03:55,640 --> 02:03:59,880
Speaker 1: agree that this is not only valuable in the present tense,

2150
02:04:00,000 --> 02:04:02,680
Speaker 1: in the past tense, and it's inevitable for the future tense.

2151
02:04:03,760 --> 02:04:06,360
Speaker 1: How when we all value these animals, and then what

2152
02:04:06,440 --> 02:04:08,360
Speaker 1: do we do? We might I think people that are

2153
02:04:09,080 --> 02:04:11,000
Speaker 1: folks we've had in here that are anti hunting on

2154
02:04:11,080 --> 02:04:13,480
Speaker 1: the on the predator side of things, might say, well,

2155
02:04:13,520 --> 02:04:16,080
Speaker 1: we just don't touch them. We let them play their

2156
02:04:16,120 --> 02:04:18,360
Speaker 1: service for the ecosystem. We don't touch them, We allow

2157
02:04:18,440 --> 02:04:20,800
Speaker 1: them to do whatever they want to do. Hunters might

2158
02:04:20,800 --> 02:04:23,280
Speaker 1: say that, but what if we just we just trim

2159
02:04:23,360 --> 02:04:26,040
Speaker 1: around the edges, like we there can be a service

2160
02:04:26,120 --> 02:04:29,720
Speaker 1: that hunters can then provide to Um, there's a conversation

2161
02:04:29,760 --> 02:04:31,560
Speaker 1: we had right there. We can certainly look at the

2162
02:04:31,640 --> 02:04:33,800
Speaker 1: data and look at what you've learned about the history

2163
02:04:33,840 --> 02:04:36,480
Speaker 1: of what might happen and make some sort of sensical

2164
02:04:36,680 --> 02:04:40,120
Speaker 1: like just like have some some pragmatism and go forward.

2165
02:04:40,800 --> 02:04:43,640
Speaker 1: Um will we do that? I don't know, but we

2166
02:04:43,760 --> 02:04:46,360
Speaker 1: can certainly do that in pockets. And I think conversations

2167
02:04:46,400 --> 02:04:48,160
Speaker 1: like this one can help move it. Well, I hope so.

2168
02:04:48,400 --> 02:04:51,160
Speaker 1: I mean one of the things, uh, I kind of realized,

2169
02:04:51,920 --> 02:04:55,640
Speaker 1: uh a few years ago the Cowboy poets and Nevada

2170
02:04:56,120 --> 02:04:59,600
Speaker 1: asked me to do a keynote address for uh there

2171
02:05:00,000 --> 02:05:02,440
Speaker 1: annual meeting. That's something to put on your resume. Yeah,

2172
02:05:04,240 --> 02:05:06,720
Speaker 1: for a cowboy. Everybody wants to be a cowboy Poe

2173
02:05:06,720 --> 02:05:09,440
Speaker 1: at least. And there was a There was a crowd

2174
02:05:09,560 --> 02:05:13,840
Speaker 1: of about eight or nine hundred people, many of whom

2175
02:05:14,160 --> 02:05:17,520
Speaker 1: you know. As a I realized that as a former

2176
02:05:17,720 --> 02:05:22,960
Speaker 1: university professor, I probably didn't necessarily share uh some of

2177
02:05:23,000 --> 02:05:25,640
Speaker 1: the same values with some of the people in the audience.

2178
02:05:26,640 --> 02:05:29,480
Speaker 1: But I realized before I did that talk, and this

2179
02:05:29,640 --> 02:05:31,280
Speaker 1: is kind of the way I pitched it, that the

2180
02:05:31,560 --> 02:05:35,880
Speaker 1: one thing we all had in common that I had

2181
02:05:35,960 --> 02:05:39,480
Speaker 1: in common with them and they had in common with me.

2182
02:05:40,320 --> 02:05:42,760
Speaker 1: And this is how I tried to try to sort

2183
02:05:42,800 --> 02:05:47,240
Speaker 1: of to aim the talk that I did was that

2184
02:05:47,560 --> 02:05:52,920
Speaker 1: we all were in love with the Old West. They

2185
02:05:53,080 --> 02:05:56,760
Speaker 1: love the Old West. I love the Old West. They

2186
02:05:56,920 --> 02:05:59,520
Speaker 1: might have liked the Old West because of horses and

2187
02:05:59,760 --> 02:06:02,920
Speaker 1: cow attle. I like the Old West because of the

2188
02:06:02,960 --> 02:06:06,480
Speaker 1: world Lewis and Clark saw. But we were all in

2189
02:06:06,640 --> 02:06:11,240
Speaker 1: love with that common vision of what the American West

2190
02:06:11,520 --> 02:06:14,680
Speaker 1: once was. And I think in a larger sense, we

2191
02:06:14,880 --> 02:06:16,800
Speaker 1: kind of probably are all kind of in love with

2192
02:06:16,920 --> 02:06:21,040
Speaker 1: what America once was, all of the country, and if

2193
02:06:21,080 --> 02:06:25,520
Speaker 1: we can somehow just start there and use that as

2194
02:06:25,600 --> 02:06:29,000
Speaker 1: a commonality, then maybe we can as we get into

2195
02:06:29,080 --> 02:06:32,200
Speaker 1: all these separate issues and the nuances of it all,

2196
02:06:32,680 --> 02:06:35,240
Speaker 1: we can all keep remembering this is the one thing

2197
02:06:35,480 --> 02:06:38,240
Speaker 1: we all want to see. It almost always comes back

2198
02:06:38,280 --> 02:06:40,240
Speaker 1: to value systems, right, I mean, it always comes back

2199
02:06:40,280 --> 02:06:42,240
Speaker 1: to the thing of the lucky thing we're having all

2200
02:06:42,320 --> 02:06:46,160
Speaker 1: this conversation is that we all value these things like

2201
02:06:46,240 --> 02:06:47,960
Speaker 1: they wouldn't be here if we didn't all agree that

2202
02:06:48,000 --> 02:06:50,560
Speaker 1: they have value. Let's let's all agree. And I think

2203
02:06:50,600 --> 02:06:52,120
Speaker 1: maybe with coyotes, that's the one thing you can just

2204
02:06:52,240 --> 02:06:53,840
Speaker 1: kind of spin back to. Can we just all agree

2205
02:06:53,880 --> 02:06:55,800
Speaker 1: they have value. They wouldn't be here, they wouldn't be

2206
02:06:55,840 --> 02:06:58,520
Speaker 1: so damn adaptable, they wouldn't be what they are if

2207
02:06:58,560 --> 02:07:01,000
Speaker 1: they didn't have value. They just it's impossible to say

2208
02:07:01,040 --> 02:07:05,000
Speaker 1: those things and and have any monica the truth. I mean,

2209
02:07:05,080 --> 02:07:08,000
Speaker 1: they just are. So it's it's nice to through your

2210
02:07:08,080 --> 02:07:10,480
Speaker 1: work and conversations they just just to freaking see it

2211
02:07:10,720 --> 02:07:13,960
Speaker 1: for a minute, stop and see it and think about it,

2212
02:07:14,040 --> 02:07:16,200
Speaker 1: and then go back to the debate about what we

2213
02:07:16,240 --> 02:07:18,200
Speaker 1: want to do with them, you know, when they're eating

2214
02:07:18,240 --> 02:07:22,280
Speaker 1: the fawns and whacking lambs and and bothering our cattle

2215
02:07:22,320 --> 02:07:24,680
Speaker 1: and eating the chickens in downtown l a of the

2216
02:07:25,440 --> 02:07:31,000
Speaker 1: of the of the foe, aristocratic uh you know, tech

2217
02:07:31,520 --> 02:07:33,800
Speaker 1: guy or the or in the case of like Joe

2218
02:07:33,880 --> 02:07:37,360
Speaker 1: Rogan is the famous podcaster whose chickens are getting He's

2219
02:07:37,400 --> 02:07:41,080
Speaker 1: living in Ventura in Hollywood Hills and getting his chickens

2220
02:07:41,120 --> 02:07:43,640
Speaker 1: whacked by coyotes. You know, So it's like there's some

2221
02:07:43,960 --> 02:07:46,600
Speaker 1: some weird do you feel like there's some weird irony

2222
02:07:46,800 --> 02:07:50,920
Speaker 1: and in the current state of like urban coyotes, like

2223
02:07:51,440 --> 02:07:55,360
Speaker 1: they just don't give a shit, Like well they The

2224
02:07:55,480 --> 02:07:58,200
Speaker 1: truth is they've been living among us for you know,

2225
02:07:58,400 --> 02:08:01,160
Speaker 1: ever since we got here fifteen thousand years ago, and

2226
02:08:02,240 --> 02:08:05,800
Speaker 1: uh so they're they're used to being around us. That's

2227
02:08:05,920 --> 02:08:09,160
Speaker 1: one of the reasons. For example, in the nineteen twenties,

2228
02:08:09,240 --> 02:08:12,440
Speaker 1: we were able to pretty effectively get rid of wolves,

2229
02:08:13,040 --> 02:08:15,840
Speaker 1: but we were never able to get rid of coyotes

2230
02:08:15,920 --> 02:08:17,640
Speaker 1: or even come close to it. And one of the

2231
02:08:17,720 --> 02:08:22,080
Speaker 1: reasons is because they have been living amongs and knowing

2232
02:08:22,160 --> 02:08:26,080
Speaker 1: how to interact with us for so very long. And

2233
02:08:26,840 --> 02:08:30,480
Speaker 1: I mean, you know, without going into too much biological detail,

2234
02:08:30,640 --> 02:08:34,640
Speaker 1: they have a particular adaptation called fish and fusion that's

2235
02:08:35,160 --> 02:08:39,120
Speaker 1: very similar to something we do in our evolutionary lives.

2236
02:08:40,080 --> 02:08:41,920
Speaker 1: It's one of the many things that coyotes have in

2237
02:08:42,040 --> 02:08:45,800
Speaker 1: common with humans. Uh learning how to survive through your

2238
02:08:45,880 --> 02:08:48,800
Speaker 1: wits as another one. But this fish and fusion adaptation

2239
02:08:48,920 --> 02:08:56,680
Speaker 1: means that coyotes when they're pressured, they don't exist as

2240
02:08:56,840 --> 02:09:00,800
Speaker 1: packs and in groups in a fusion mode in in

2241
02:09:00,920 --> 02:09:05,320
Speaker 1: our sense as communities, but when they're pressured and harassed

2242
02:09:05,400 --> 02:09:09,360
Speaker 1: and persecuted, they tend to split into singles and pairs

2243
02:09:09,680 --> 02:09:12,240
Speaker 1: and scatter across the landscape. I mean, that's one of

2244
02:09:12,280 --> 02:09:15,400
Speaker 1: the ways we survived great disease epidemics and our our

2245
02:09:15,480 --> 02:09:18,960
Speaker 1: evolutionary history as we did the same thing, and coyotes

2246
02:09:19,000 --> 02:09:23,920
Speaker 1: have that ability. So I mean their ability to survive

2247
02:09:24,440 --> 02:09:28,680
Speaker 1: through their ecological adaptations that are very similar to the

2248
02:09:28,760 --> 02:09:32,080
Speaker 1: ones that we used to survive, and their survival by

2249
02:09:32,120 --> 02:09:35,360
Speaker 1: our by wits, which is of course how we humans

2250
02:09:35,400 --> 02:09:37,680
Speaker 1: have come to be a dominant species on the planet.

2251
02:09:38,600 --> 02:09:41,080
Speaker 1: That's to me one of the reasons we ought, as

2252
02:09:41,280 --> 02:09:44,920
Speaker 1: Indian people did we ought to really appreciate coyotes, because

2253
02:09:45,240 --> 02:09:48,839
Speaker 1: in effect, they're emulating in the world the same success

2254
02:09:49,400 --> 02:09:52,000
Speaker 1: that we've had. I mean, if you look at them

2255
02:09:52,040 --> 02:09:54,640
Speaker 1: that way, other than just you know, there there's the

2256
02:09:54,960 --> 02:09:58,160
Speaker 1: little vermin that's breathing up good air and uh, I

2257
02:09:58,200 --> 02:10:02,920
Speaker 1: should shoot it on site, you start appreciating the natural

2258
02:10:03,000 --> 02:10:06,840
Speaker 1: world and America, North America in a way that maybe

2259
02:10:06,880 --> 02:10:08,840
Speaker 1: you haven't before. I think, and I think we've said

2260
02:10:08,880 --> 02:10:11,440
Speaker 1: this before in this past. Maybe maybe an unpopular thing,

2261
02:10:11,480 --> 02:10:14,240
Speaker 1: but I think true is that we have seen this

2262
02:10:14,360 --> 02:10:17,720
Speaker 1: in the hunting community. And I think maybe in general,

2263
02:10:18,040 --> 02:10:20,040
Speaker 1: I don't know, but certainly in the hunting community were

2264
02:10:21,000 --> 02:10:23,080
Speaker 1: it's almost as if we enjoy when the gloves come

2265
02:10:23,120 --> 02:10:27,000
Speaker 1: off when someone says, hey, listen, ferrell hogs don't care

2266
02:10:27,040 --> 02:10:29,520
Speaker 1: how you kill them, like when we and we very

2267
02:10:29,600 --> 02:10:32,640
Speaker 1: much enjoy when the ethical gloves are removed, like there's

2268
02:10:32,680 --> 02:10:36,040
Speaker 1: a we we there's we revel in it a little

2269
02:10:36,040 --> 02:10:38,880
Speaker 1: bit like oh wow, we can just we can hate

2270
02:10:38,920 --> 02:10:42,400
Speaker 1: these ones, or like we can just that that happens.

2271
02:10:42,440 --> 02:10:45,240
Speaker 1: And it's not I'm not saying that. I'm saying that

2272
02:10:45,280 --> 02:10:48,800
Speaker 1: from experience, like personal experience, like when somebody says, like, oh,

2273
02:10:48,880 --> 02:10:50,720
Speaker 1: there's a group of there's a group of pigs or

2274
02:10:50,720 --> 02:10:52,440
Speaker 1: a group of coyotes, and we don't have to value

2275
02:10:52,520 --> 02:10:55,240
Speaker 1: them like we do the other ones. And here's uh,

2276
02:10:55,600 --> 02:10:57,600
Speaker 1: you know, I our laser night vision goggles and a

2277
02:10:57,640 --> 02:11:00,200
Speaker 1: machine gun and we might eat him. We I know,

2278
02:11:00,320 --> 02:11:03,240
Speaker 1: we don't know, go for it though, like it becomes

2279
02:11:03,920 --> 02:11:06,040
Speaker 1: it's analogous to a video game or something you know,

2280
02:11:06,840 --> 02:11:08,720
Speaker 1: I've seen that I've seen with and see what pigs

2281
02:11:08,840 --> 02:11:11,720
Speaker 1: or other things. And so Yeah, the biologists refer to

2282
02:11:11,840 --> 02:11:16,120
Speaker 1: that as the henhouse syndrome. It's the it's the same

2283
02:11:16,200 --> 02:11:19,200
Speaker 1: thing that I mean, most predators do it, and they

2284
02:11:19,280 --> 02:11:24,480
Speaker 1: tend to do it with prey that's either naive, are

2285
02:11:24,600 --> 02:11:29,280
Speaker 1: not valued and uh. And what it results in is

2286
02:11:29,600 --> 02:11:34,160
Speaker 1: the fox that gets into a henhouse uh and kills

2287
02:11:34,640 --> 02:11:38,960
Speaker 1: fifty or sixty chickens in a night, bites the introls

2288
02:11:39,120 --> 02:11:42,600
Speaker 1: out of four or five as it's leaving, but basically

2289
02:11:42,800 --> 02:11:48,960
Speaker 1: just slaughters the prey and leaves them lying. And predators

2290
02:11:49,040 --> 02:11:52,280
Speaker 1: all over the world have an inclination to occasionally do

2291
02:11:52,440 --> 02:11:55,480
Speaker 1: that surplus killing things like that. Yeah, and human predators

2292
02:11:55,880 --> 02:11:59,320
Speaker 1: do the same thing and sometimes sort of like being

2293
02:11:59,440 --> 02:12:01,720
Speaker 1: freed to able to do it. Yeah, there's like this

2294
02:12:01,920 --> 02:12:04,120
Speaker 1: weird like wow, man, it was stressful trying to pick

2295
02:12:04,160 --> 02:12:06,320
Speaker 1: out the right one of those and make sure there's

2296
02:12:06,400 --> 02:12:07,840
Speaker 1: more of them. And if you just tell me that,

2297
02:12:07,920 --> 02:12:09,840
Speaker 1: I can just oh man, we gotta get rid of

2298
02:12:09,840 --> 02:12:13,520
Speaker 1: all the ease, then perfect. It's the easier situation. Let's cumbersome.

2299
02:12:14,040 --> 02:12:16,520
Speaker 1: We should probably end up here on like some you

2300
02:12:16,600 --> 02:12:20,040
Speaker 1: got some really good, like wit examples of what kyos

2301
02:12:20,120 --> 02:12:24,480
Speaker 1: do that might make us chuckle or make us appreciate. Well,

2302
02:12:24,640 --> 02:12:27,960
Speaker 1: I mean, they're all kinds. I figured that the list

2303
02:12:28,080 --> 02:12:32,080
Speaker 1: is endless. The list is endless. I mean we think

2304
02:12:32,320 --> 02:12:37,840
Speaker 1: that urban life, for example, is probably selecting for uber

2305
02:12:38,000 --> 02:12:43,920
Speaker 1: intelligent coyotes. I mean, the whole you know, literature behind

2306
02:12:44,160 --> 02:12:48,200
Speaker 1: urban coyotes is kind of fascinating because, for one thing,

2307
02:12:48,320 --> 02:12:51,600
Speaker 1: when coyotes get into cities and start living among people,

2308
02:12:52,240 --> 02:12:53,840
Speaker 1: they live a lot longer than they do out in

2309
02:12:53,880 --> 02:12:57,000
Speaker 1: the country because out in the country people are shooting them,

2310
02:12:57,240 --> 02:13:00,080
Speaker 1: poisoning them, trying to run over them with cars. And

2311
02:13:00,160 --> 02:13:02,839
Speaker 1: when they get into in the average lifespan of coyote

2312
02:13:02,840 --> 02:13:05,360
Speaker 1: and the countryside is about three years. When they get

2313
02:13:05,400 --> 02:13:08,960
Speaker 1: into cities, they're living to ten, twelve, thirteen years old,

2314
02:13:09,800 --> 02:13:13,200
Speaker 1: and the result of living that long and sort of

2315
02:13:13,720 --> 02:13:18,400
Speaker 1: learning how you work life in cities means that coyotes

2316
02:13:18,440 --> 02:13:23,280
Speaker 1: are doing things like learning how to cross interstate highways

2317
02:13:23,400 --> 02:13:27,360
Speaker 1: during the rush hour, and they do it by crossing

2318
02:13:27,960 --> 02:13:32,040
Speaker 1: four lanes of traffic and then sitting in the median. Sometimes.

2319
02:13:32,480 --> 02:13:35,280
Speaker 1: A biologists in Chicago is watch coyotes sit in a

2320
02:13:35,360 --> 02:13:39,160
Speaker 1: median sometimes for three minutes, waiting for traffic to clear

2321
02:13:39,480 --> 02:13:45,200
Speaker 1: in the other four lanes before then dashing across. In California,

2322
02:13:46,120 --> 02:13:49,880
Speaker 1: California Highway one has become are not Highway one, but

2323
02:13:49,960 --> 02:13:53,720
Speaker 1: one oh one has of course, carries so much traffic

2324
02:13:54,080 --> 02:13:59,840
Speaker 1: that coyotes are becoming loath to cross it. And one

2325
02:13:59,880 --> 02:14:01,680
Speaker 1: of the things that seems to be happening is that

2326
02:14:01,920 --> 02:14:04,840
Speaker 1: on either side of Highway one oh one, we are

2327
02:14:04,920 --> 02:14:10,840
Speaker 1: starting to get the beginnings of subspecies differentiation between the

2328
02:14:10,960 --> 02:14:15,960
Speaker 1: coyote populations east of one oh one and west of

2329
02:14:16,040 --> 02:14:19,760
Speaker 1: one oh one. Toys and crips were in different bandanas. Absolutely,

2330
02:14:19,800 --> 02:14:23,560
Speaker 1: they're wearing different bandanas and are becoming slightly different from

2331
02:14:23,640 --> 02:14:27,240
Speaker 1: one another because they're not crossing enough to actually exchange

2332
02:14:27,320 --> 02:14:31,160
Speaker 1: genes anymore. I mean, so highways and modern human life

2333
02:14:31,200 --> 02:14:34,600
Speaker 1: are kind of shaping these animals. I'll give you another one,

2334
02:14:35,120 --> 02:14:38,680
Speaker 1: a couple of examples from when I've visited the predator

2335
02:14:38,760 --> 02:14:42,840
Speaker 1: research facility outside Logan, Utah, and talked to the scientists

2336
02:14:42,880 --> 02:14:45,440
Speaker 1: at Wildlife Services of course, who are designing all sorts

2337
02:14:45,480 --> 02:14:52,520
Speaker 1: of ways to control coyotes, both using uh non mortal

2338
02:14:53,240 --> 02:14:57,960
Speaker 1: uh non lethal means and lethal means. They describe for

2339
02:14:58,120 --> 02:15:04,880
Speaker 1: me their studies of coyote individuality, where they would set

2340
02:15:05,000 --> 02:15:10,040
Speaker 1: up a an enclosure with a pot of goodies at

2341
02:15:10,120 --> 02:15:15,800
Speaker 1: one end and would in between the coyote population. They

2342
02:15:15,880 --> 02:15:20,240
Speaker 1: put twenty coyote twenty coyotes in this particular enclosure. They

2343
02:15:20,360 --> 02:15:24,120
Speaker 1: had a whole uh suite of goodies at the far end,

2344
02:15:24,280 --> 02:15:27,240
Speaker 1: maybe a hundred and fifty feet away, and they tried

2345
02:15:27,480 --> 02:15:34,000
Speaker 1: all kinds of various um basically obstacles to the coyotes

2346
02:15:34,080 --> 02:15:37,280
Speaker 1: getting to the goodies. One of the things they discovered

2347
02:15:37,520 --> 02:15:43,160
Speaker 1: was that within a single day, two or three of

2348
02:15:43,200 --> 02:15:48,240
Speaker 1: the coyotes out of the twenty, walked past every blowing

2349
02:15:48,480 --> 02:15:53,840
Speaker 1: suren flashing light, flattery, everything that they put up and

2350
02:15:54,480 --> 02:15:57,960
Speaker 1: got the goodies. They let this experiment go on for

2351
02:15:58,080 --> 02:16:02,520
Speaker 1: a month and out of those any coyotes. Fourteen of

2352
02:16:02,680 --> 02:16:07,839
Speaker 1: them never went to the other end, never once managed

2353
02:16:07,880 --> 02:16:10,760
Speaker 1: to go down and get the lure from the far

2354
02:16:10,960 --> 02:16:13,800
Speaker 1: end of the enclosure. And so what some of the

2355
02:16:13,960 --> 02:16:18,760
Speaker 1: urban biologists are arguing is that it's those bold coyotes

2356
02:16:19,320 --> 02:16:23,320
Speaker 1: that are willing to wade through whatever obstacles you put

2357
02:16:23,440 --> 02:16:27,720
Speaker 1: up in order to realize their goal and survive that

2358
02:16:27,960 --> 02:16:31,640
Speaker 1: are populating most of the cities. Yeah. And you see

2359
02:16:31,640 --> 02:16:33,840
Speaker 1: how you see how an animal evalls and and our

2360
02:16:33,920 --> 02:16:37,520
Speaker 1: effect on it. So that's right, we're shaping the evolution

2361
02:16:37,560 --> 02:16:40,200
Speaker 1: of these animals. Uh, you know, as we're sitting here,

2362
02:16:41,320 --> 02:16:43,960
Speaker 1: it's amazing. Well, thanks for coming all the way to Bozeman. Man.

2363
02:16:45,360 --> 02:16:47,920
Speaker 1: Look and you told me that you're you're looking forward

2364
02:16:47,920 --> 02:16:50,640
Speaker 1: to another appearance on Rogan's podcast. That's pretty exciting. Don't

2365
02:16:50,640 --> 02:16:53,000
Speaker 1: want to break any of that news. Yeah, I will

2366
02:16:53,040 --> 02:16:57,120
Speaker 1: say we're still negotiating it, but yeah, it might might

2367
02:16:57,200 --> 02:16:59,560
Speaker 1: happen here in a few weeks. I look forward to it.

2368
02:16:59,640 --> 02:17:00,880
Speaker 1: The more and the more we can get you out

2369
02:17:00,879 --> 02:17:02,720
Speaker 1: there talking about this stuff, the better in my opinion.

2370
02:17:02,800 --> 02:17:06,520
Speaker 1: And this is it's enlightening and it's damn important subject.

2371
02:17:07,040 --> 02:17:09,879
Speaker 1: Of all the things we touched on just just value.

2372
02:17:09,879 --> 02:17:11,960
Speaker 1: What do we value? What are we into? Why do

2373
02:17:12,040 --> 02:17:13,840
Speaker 1: we think the way we think? Man? I love it.

2374
02:17:14,040 --> 02:17:15,640
Speaker 1: It's been fun to be here. Be I appreciate it,

2375
02:17:15,640 --> 02:17:21,680
Speaker 1: all right, Thanks Dan. Okay, I guess I grew up.

2376
02:17:23,080 --> 02:17:26,080
Speaker 1: That's it. That's all th HC Episode eighty six in

2377
02:17:26,160 --> 02:17:28,600
Speaker 1: the Books. Just want to say a big thank you Phil.

2378
02:17:28,720 --> 02:17:32,960
Speaker 1: What man, that's why, that's what I say. Sorry, sorry,

2379
02:17:33,240 --> 02:17:35,520
Speaker 1: Look what the hell? Man? I didn't know you were here.

2380
02:17:35,560 --> 02:17:40,760
Speaker 1: I thought I get out of the podcast studio. Jesus Christ.

2381
02:17:41,879 --> 02:17:47,280
Speaker 1: Phil's leaving. He's trying to take my outro. Anyway, Yeah,

2382
02:17:47,360 --> 02:17:50,800
Speaker 1: come back, come back. I miss you. Uh anyway, Thanks

2383
02:17:50,879 --> 02:17:55,080
Speaker 1: to Dan Flores and my our Meteator crew for talking

2384
02:17:55,080 --> 02:17:57,240
Speaker 1: about kites with us. It was great. Now I have

2385
02:17:57,360 --> 02:17:59,200
Speaker 1: something that I didn't tell Phil about that I want

2386
02:17:59,240 --> 02:18:01,520
Speaker 1: to surprise him with. Oh yeah, I love this. This

2387
02:18:01,560 --> 02:18:03,600
Speaker 1: has been happening a lot lately. Yeah, this is a

2388
02:18:03,640 --> 02:18:06,520
Speaker 1: good Okay, I want to give well, you know, we

2389
02:18:06,560 --> 02:18:08,879
Speaker 1: do a lot of segments here on the show, right yeah,

2390
02:18:09,280 --> 02:18:11,840
Speaker 1: a lot of different segments. I want to do one

2391
02:18:12,320 --> 02:18:16,320
Speaker 1: called Dr Phil you know, and I'm offering it to

2392
02:18:16,360 --> 02:18:19,080
Speaker 1: you officially right now. Would you like to accept and

2393
02:18:19,480 --> 02:18:22,560
Speaker 1: and I will give you no, there are no parameters.

2394
02:18:22,640 --> 02:18:25,400
Speaker 1: You can do whatever you want. This is dangerous with

2395
02:18:25,640 --> 02:18:29,000
Speaker 1: Dr Phil. I will accept all right, perfect, okay, but

2396
02:18:29,120 --> 02:18:31,920
Speaker 1: before we talked about how it was contingent on whether

2397
02:18:32,040 --> 02:18:35,959
Speaker 1: or not I kept my mustache after Halloween. Yeah, I'd

2398
02:18:36,000 --> 02:18:38,480
Speaker 1: still like you to keep it. But I'll give you

2399
02:18:38,560 --> 02:18:41,440
Speaker 1: this segment either way. Give you a segmentad right now. Okay,

2400
02:18:41,560 --> 02:18:44,360
Speaker 1: you're gonna regret this, well, yeah, well I will. We'll

2401
02:18:44,440 --> 02:18:47,720
Speaker 1: get to exactly what Dr Phil means. But if you

2402
02:18:47,720 --> 02:18:49,760
Speaker 1: want to write into t a C that the meter

2403
02:18:49,959 --> 02:18:53,480
Speaker 1: dot com and suggest what Dr Phil the new th

2404
02:18:53,640 --> 02:18:57,480
Speaker 1: HC segment should be about or should cover, just write

2405
02:18:57,520 --> 02:18:59,520
Speaker 1: it right in, write an email and I'll for that

2406
02:18:59,560 --> 02:19:02,840
Speaker 1: over to Phil. And Um, he's gonna get a little

2407
02:19:02,879 --> 02:19:06,520
Speaker 1: piece of glory, a little piece of podcast, hosting glory

2408
02:19:06,959 --> 02:19:08,720
Speaker 1: the first time in his life. And you never know

2409
02:19:08,800 --> 02:19:11,240
Speaker 1: that this might go. You might get your own podcast.

2410
02:19:11,720 --> 02:19:15,160
Speaker 1: I can't wait. I'm excited. You're excited. Yeah, I'm already

2411
02:19:15,200 --> 02:19:17,840
Speaker 1: racking my brain. It's palpable. So join us next time

2412
02:19:18,520 --> 02:19:23,520
Speaker 1: for Dr Phil Medicine woman there it is just talk

2413
02:19:23,560 --> 02:19:28,720
Speaker 1: about medicine. Today's episode a seat of mening. I like it.

2414
02:19:28,879 --> 02:19:31,560
Speaker 1: Dr Phil Medicine and maybe we'll stick with that. Anyways,

2415
02:19:31,760 --> 02:19:36,040
Speaker 1: we'll see you then bye bye, because I can't go

2416
02:19:36,280 --> 02:20:05,600
Speaker 1: a week without doing right with R. Drinking in. Don't

2417
02:20:05,680 --> 02:20:08,560
Speaker 1: sit in at the bas foold, stop to throw roots.

2418
02:20:08,879 --> 02:20:12,200
Speaker 1: I'm feeling like in all on our barras shoes. All

2419
02:20:12,440 --> 02:20:14,600
Speaker 1: tell me what is it that a shoe