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

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

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Speaker 1: can't predict anything presented by first, like creating proven versatile

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Speaker 1: hunting apparel from Marino bass layers to technical outerwear for

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Speaker 1: every hunt. First like go farther, stay longer. All right, everybody,

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Speaker 1: this is a special kind of like a literary It's

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Speaker 1: like a literary and biology special edition. Joined here by

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Speaker 1: Carmen van Bianki, who's here for the third damn time.

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Speaker 1: What episode numbers were you in before? I want to look,

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Speaker 1: I don't know, fifty four and nine, and then you missed,

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Speaker 1: then you missed a hundred in some episodes, and now

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Speaker 1: you're back. But we need to check in with you

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Speaker 1: because I feel like we um I feel like, you know,

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Speaker 1: we get all these questions all the time. People be like,

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Speaker 1: how can I have a job in the outdoors? Or

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Speaker 1: how do you be of this or that? So you're

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Speaker 1: our case study. Okay, well it's not been any sort

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Speaker 1: of traditional path. But you've arrived now, I think you've arrived.

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Speaker 1: Now I don't know if I've arrived. I don't know

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Speaker 1: if I've arrived, but you trap animals for living man. Okay,

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Speaker 1: I'll give you that. Yeah, I have a ton of fun.

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Speaker 1: Do you have a year round position? No, really, we'll

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Speaker 1: get to that. But you're still alive. You're obviously feeding

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Speaker 1: yourself and you're clothed and whatnot. Yeah, markers of success. Yeah,

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Speaker 1: we make it work. Um, but it's a hodgepodge. Although

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Speaker 1: I am starting a new chapter and hopefully this is

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Speaker 1: gonna be a full time the rest of my time. Deal.

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Speaker 1: Have you have you if? If you might, you might

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Speaker 1: have to lie, bec I want just to look positive

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Speaker 1: no matter what. But has have any opportunities, has this

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Speaker 1: has coming on the show to explain your pro professional

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Speaker 1: path opened any doors? Don't lie? I gotta be honest. No,

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Speaker 1: damn it really because I felt like I really like

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Speaker 1: laid it on thick and that was, you know, so

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Speaker 1: sweet of you. But um, I mean I've got I

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Speaker 1: more get my jobs, you know, just based on my

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Speaker 1: my skills, and no one cares about that kind of stuff.

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Speaker 1: Our listenership back probably the last time Karmen was just

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Speaker 1: trying to get those jobs. Yeah, so now you know

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Speaker 1: we have twice listenership. It probably made it worse for

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Speaker 1: Carmen because a bunch of dudes are like, Dude, I'm

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Speaker 1: gonna try to get that job. I'm gonna go into that.

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Speaker 1: I'm gonna go into that line of work. That's good.

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Speaker 1: So everything it's like a meritocracy. It's a meritocracy in

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Speaker 1: your field things. Yeah. And and I've had I've been

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Speaker 1: really fortunate to have some regular, uh field jobs for

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Speaker 1: the last years. I mean, I think since we did

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Speaker 1: the last podcast, I've been working on the same project.

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Speaker 1: And so that's been really nice, just not having to

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Speaker 1: worry every season about what the next thing is going

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Speaker 1: to be and where I'm gonna live. Um. So, so

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Speaker 1: that was really nice. And now that project is just

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Speaker 1: about completely wound up. And um, three of my colleagues

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Speaker 1: and friends from that that project, well two of them,

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Speaker 1: there's three of us, are starting a nonprofit doing independent

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Speaker 1: wildlife research. That's the next chapter. That's good. That's the

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Speaker 1: word right out of my mouth. Also joined by what

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Speaker 1: cows here? Hello, fresh off a babysitting my dog? Um,

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Speaker 1: you honest is here fresh off big huge run this morning?

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Speaker 1: Mm hmm. I was just getting up. I got a

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Speaker 1: picture from a friend of mine who did he did

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Speaker 1: you just run into him up on top of that mountain.

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Speaker 1: We ran up there together, ran up there together. We

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Speaker 1: hiked fast up there together. You guys speed hiked. That's good.

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Speaker 1: We kind of ran down. Phil here, say something for yourself. Phil,

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Speaker 1: you don't sound very thrilled in the room. Get pills here,

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Speaker 1: I guess for some reason. And then, uh, very special guests.

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Speaker 1: Who Kathy Raven whose brand new book is out yesterday. Yes,

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Speaker 1: I heard you guys sold so the books called Fox

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Speaker 1: and I and my exposure to it is your publisher,

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Speaker 1: Cindy Spiegel took um, you know, through me a real she.

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Speaker 1: I don't think she would describe it this way, but

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Speaker 1: through me a real lifeline. Many years ago I bought

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Speaker 1: my second book I published with her imprint at Random

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Speaker 1: House for a long time. They've gone on to now

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Speaker 1: start their own publishing venture. You're I think their first book,

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Speaker 1: their first so Spiegel and Grow. It's with spiegl and Growl.

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Speaker 1: Speagle and Grow used to be an imprint at Random House,

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Speaker 1: but now it's a very exciting new venture. Um, you

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Speaker 1: were their first book. I heard you guys have Uh,

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Speaker 1: you've sold the book to eleven different countries. I haven't

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Speaker 1: kept track because that's not my thing, but it's been

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Speaker 1: a lot of countries. Russia picked it up, and Korea

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Speaker 1: and Italy and Germany and waiting for Japan. So does

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Speaker 1: this if you can put in a plug A lot

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Speaker 1: of good populations in countries, so you hear that, you

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Speaker 1: people in Japan, so it'll be widely translated. Yes, even

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Speaker 1: I'm really happy that even the English folks decided to

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Speaker 1: translate it. And I don't know if the Australians and

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Speaker 1: New Zealands have, but I think that's really helpful because

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Speaker 1: when I watch English, I guess Cindy told you. I

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Speaker 1: don't have a TV or stream or anything like that,

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Speaker 1: but I buy DVDs and mostly the DVDs I buy

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Speaker 1: for entertainment are English ones, and I have to watch

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Speaker 1: them with the you know, the close captioning because I

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Speaker 1: don't understand what they're saying. So I think English people

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Speaker 1: probably don't understand all of my vocabulary and such. So

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Speaker 1: they hired a professional to translate it from American to English,

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Speaker 1: and I'm really happy about that. Do you mean like

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Speaker 1: the print version. Yeah, yeah, that's a good question about

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Speaker 1: the audio. Yeah, the spelling is different, and I think

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Speaker 1: some of the slang. I might have used the word

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Speaker 1: mother country at one point, and I remember they wrote

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Speaker 1: and said, so when you say the mother I was

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Speaker 1: being facetious. When you said the mother country, were you

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Speaker 1: talking about us? I said yeah, And there was something

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Speaker 1: else that. Yes, some minor adjustments. So the folks over there,

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Speaker 1: I hope they didn't cut out all my stuff about

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Speaker 1: fox hunting, but I talked about England and the fox

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Speaker 1: Hunters and Downton Abbey and all that. Yeah, they're trying

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Speaker 1: to wash their hands a little fox The whole Fox

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Speaker 1: Hunt made that look a little nicer. Yeah, that's good.

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Speaker 1: It has been translated to a lot of different languages

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Speaker 1: and different accents. That's great. So we're gonna talk about

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Speaker 1: that book in a little bit too, But first we

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Speaker 1: gotta talk about then our thing. Now. Listen, I don't

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Speaker 1: want you to take this the wrong way. I think

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Speaker 1: everyone should go buy your book. But we're gonna promote

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Speaker 1: like we have to promote a thing of ours. So

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Speaker 1: we talked about a week ago. I don't know when

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Speaker 1: the hell, I don't know a while ago. No, it's

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Speaker 1: out right now. The closest listen. Yeah, if you listen

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Speaker 1: to this show on a regular basis. You heard us,

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Speaker 1: uh um getting all excited and explaining our audio book. Yeah.

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Speaker 1: I heard somebody say that an audio original like an

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Speaker 1: immersive audio experience. It's not available in print. You have

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Speaker 1: to listen to it six hours long. Um, but I

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Speaker 1: just want to give everybody a taste of it. So

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Speaker 1: this is like, this is the story. I heard this story? Um,

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Speaker 1: I heard a version of this story, I think from Callahan.

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Speaker 1: Did you originally tell me the story? YEA, some details wrong,

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Speaker 1: cal That's because I never heard the story. You heard

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Speaker 1: a story about Brody was like, hey, do you hear

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Speaker 1: about And I'm like, oh, yeah, that's this guy. It's like, well,

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Speaker 1: do you have his phone number? I was like, oh no,

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Speaker 1: but he used to work Pheasants forever and I know

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Speaker 1: a bunch of folks in that organization. So I had

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Speaker 1: one email tracked down his cell phone number, and and

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Speaker 1: and and I still haven't heard the story. Yeah, so

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Speaker 1: you still haven't heard the damn story. It's a guy

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Speaker 1: named Sam Lowery. He's a game board in Arizona. Before

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Speaker 1: we we jump into this, you want to do a

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Speaker 1: quick summary of what this is, what the whole project is.

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Speaker 1: In case they missed the last and you brought it up.

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Speaker 1: Are you gonna edit that out or leave that in film?

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Speaker 1: I'm gonna leave it in your little comment there. Yeah,

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Speaker 1: that's called direct fils big time producer. H that's going

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Speaker 1: on with her. I would never take that away because

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Speaker 1: because Karin's out of town. Now, Phil's gonna act like

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Speaker 1: big time Mr Director. All right, Phil, Phil's take him

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Speaker 1: jobs away from the folks who answer listener emails. You

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Speaker 1: know what my dad has a story about He was

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Speaker 1: when he was a little kid, he had a job

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Speaker 1: as a soda jerk, and when he came back from

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Speaker 1: the war, he beat the guy up who had that job. Wow,

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Speaker 1: that's unnecessary. Found out that the guy had the job,

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Speaker 1: the guy didn't want to give it back. My dad

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Speaker 1: beat him up. Do you what's your opinion on that?

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Speaker 1: Do you think your dad had the right to take

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Speaker 1: his job back. He felt that you wouldn't that you

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Speaker 1: would if a veteran was returning got it would very

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Speaker 1: quickly step aside and not make a play to keep

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Speaker 1: the job. What if you were in that new soda

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Speaker 1: jerk's position and some guy came in and said, Hey,

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Speaker 1: I want my job back. I just said, here's the

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Speaker 1: apron that guy wants of vanilla soda. Point Man Krim

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Speaker 1: might come back and beat your ass, Phil, But I'll

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Speaker 1: take that little directing. I'll take that little directing comment

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Speaker 1: and I will Um. It's called meat Eaters, camp fire stories,

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Speaker 1: close calls, and it is about. It's a it's a long,

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Speaker 1: it's a it's a collection of a wide variety of

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Speaker 1: different storytellers from mountaineers, game wardens, hunters, spear fisherman. I

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Speaker 1: don't know who else is in there. My daughter has

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Speaker 1: a cameo. Yeah, that's right, she did a great job.

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Speaker 1: Um about close calls and near death experiences and close

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Speaker 1: calls in the wild, and kind of the way like

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Speaker 1: the sort of the physiology that goes into it, the

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Speaker 1: psychology that goes into close calls, the way close calls

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Speaker 1: tend to live with you and haunt you. Um. And

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Speaker 1: one of them, just to give you a taste, what

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Speaker 1: this is all about, is the story of a game

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Speaker 1: board named Sam Laurie who is operating in Arizona. And

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Speaker 1: we described us before as he has a run in

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Speaker 1: with the sociopathic, suzy wielding elk poacher. So take a listen,

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Speaker 1: and such thing the mud puddle. Over the years, I've

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Speaker 1: had the occasion to speak with several game wardens on

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Speaker 1: the subject of poaching. Among the most interesting of these

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Speaker 1: conversations was my talk with a warden who studied what

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Speaker 1: he called super poachers. Super poachers, he found, almost always

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Speaker 1: exhibit sociopathic tendencies. They commit their crimes very quietly. They

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Speaker 1: don't show off photos or brag about the animals they

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Speaker 1: poached on social media, and they don't tend to poach

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Speaker 1: for material game. The real thrill for them is killing

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Speaker 1: animals illegally and doing so without getting caught. The hunt

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Speaker 1: for one such serial poacher is the focus of this

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Speaker 1: next story from Sam Lowry, a retired game warden. Sam

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Speaker 1: told us that most of the time he was dealing

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Speaker 1: with normal people who might have made a minor honest mistake,

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Speaker 1: along with the occasional poacher who was deliberately flouting the

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Speaker 1: rules for profit. In this case, though, he was playing

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Speaker 1: cat and mouse with a dangerous sociopath. My name is

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Speaker 1: Sam Lowry. I've held different positions with the federal and

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Speaker 1: state wildlife agencies, spanning about a forty year career in wildlife.

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Speaker 1: Back in about three or so, I was a wildlife

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Speaker 1: manager for what they called Unit one and three B

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Speaker 1: in northern Arizona. Closest larger town would be Sholow, Arizona.

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Speaker 1: Most people think Arizona is filled with sorrow cacti and desert,

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Speaker 1: and yet in reality there's there's a beautiful high country

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Speaker 1: element of mixed conifer and aspens. And that was the

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Speaker 1: district that I was responsible for that held a very

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Speaker 1: very healthy elk population. In fact, you know, probably world

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Speaker 1: renowned UH units for pursuing elk in that particular region

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Speaker 1: of the White Mountains. So usually by springtime of every year,

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Speaker 1: we were looking forward to Turkey season with spring Gobbler's

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Speaker 1: goblin everywhere, and all the big game seasons were over

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Speaker 1: in terms of elk and deer and big horn sheep

217
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Speaker 1: and what have you, and things for the most part

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Speaker 1: started to slow down. Um with the exception of one

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Speaker 1: evening I got a call and this would have been

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Speaker 1: about in March, that one of our local outfitters who

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Speaker 1: lives quite a ways out into the Boonies heard some

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Speaker 1: shots and U reported it to Gave and Fish. We

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Speaker 1: had a twenty four hour hotline where they could call,

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Speaker 1: and of course that information came back to me that

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Speaker 1: these shots were fired at night. UM sounded like small

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Speaker 1: caliber and fully automatic, which is very unusual for the

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Speaker 1: area we were in. I knew that the caller, so

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Speaker 1: I contacted him the next day and determined the location

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Speaker 1: he was even referring to, and I went out there

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Speaker 1: and sure enough I found two elk land down. They

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Speaker 1: were both probably within eight hours, had been shot. As normally,

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Speaker 1: you take your metal detector and look the carcasses over.

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Speaker 1: You look for any places where the vehicle, the suspect

234
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Speaker 1: vehicle would have pulled off the road. You want to

235
00:14:51,880 --> 00:14:54,880
Speaker 1: look for any shell casings in the road. You want

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Speaker 1: to look for anything that give you any idea of

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Speaker 1: of evidence to to link whoever shot these elk to

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Speaker 1: a person. Unfortunately, there was nothing. Probably about two weeks

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Speaker 1: later where we received another call shots being fired at

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Speaker 1: night and general location but no specifics. I responded to

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Speaker 1: that one the next day as well and found two

242
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Speaker 1: cow elk. One was alive was still kicking. When a

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00:15:29,240 --> 00:15:33,440
Speaker 1: game warden or a wildlife officer comes in contact with

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Speaker 1: an animal that's been poached, what we rely on is evidence.

245
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Speaker 1: You know a lot of times these violators are out

246
00:15:42,080 --> 00:15:45,440
Speaker 1: there at night party and two and they'll throw beer

247
00:15:45,480 --> 00:15:48,400
Speaker 1: cans out, or pop cans or you know, you look

248
00:15:48,440 --> 00:15:50,880
Speaker 1: for anything that might be able to lead you to

249
00:15:50,960 --> 00:15:53,960
Speaker 1: an individual down the road, and there was never anything

250
00:15:54,000 --> 00:15:57,880
Speaker 1: on the on this particular guy's m O. The evidence

251
00:15:57,960 --> 00:16:02,240
Speaker 1: was always very lacking with this particular case. I was

252
00:16:02,280 --> 00:16:05,280
Speaker 1: getting pretty bothered because if you think you found this

253
00:16:05,320 --> 00:16:08,400
Speaker 1: would have been the fifth elk um. They looked like

254
00:16:08,400 --> 00:16:11,560
Speaker 1: they were being shot with twenty two caliber as the

255
00:16:11,600 --> 00:16:14,120
Speaker 1: projectiles that I was able to carve out of the elk,

256
00:16:15,160 --> 00:16:19,360
Speaker 1: how many did we not find? So my my aggravation

257
00:16:19,480 --> 00:16:22,880
Speaker 1: started to grow. I wanted to catch this guy, so

258
00:16:22,920 --> 00:16:28,120
Speaker 1: I actually made a decision to call a reporter while

259
00:16:28,240 --> 00:16:31,200
Speaker 1: I was going to begin performing the knee crops he's

260
00:16:31,240 --> 00:16:35,600
Speaker 1: on his elk. Told him we were again out looking

261
00:16:35,640 --> 00:16:38,680
Speaker 1: at these elk poachings and hoping that an article in

262
00:16:38,720 --> 00:16:42,440
Speaker 1: the paper would stimulate some folks to maybe step forward

263
00:16:42,480 --> 00:16:45,560
Speaker 1: and put an end to who's doing this. The one

264
00:16:45,600 --> 00:16:48,640
Speaker 1: that was still alive I dispatched, which is, you know,

265
00:16:48,680 --> 00:16:50,960
Speaker 1: one of the duties officers have to do once a while,

266
00:16:51,080 --> 00:16:54,360
Speaker 1: never pleasant, but you put the animal out of its misery.

267
00:16:54,440 --> 00:16:57,600
Speaker 1: And the reporter showed up and walked out to the field.

268
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Speaker 1: I remember he looked down at me. He looked like

269
00:17:01,240 --> 00:17:04,119
Speaker 1: he was going to kind of maybe get sick. And

270
00:17:04,200 --> 00:17:08,000
Speaker 1: not that we're hardened that much, but to him, I

271
00:17:08,000 --> 00:17:12,400
Speaker 1: imagine it was a It was a pretty spectacular nasty scene.

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00:17:13,720 --> 00:17:16,400
Speaker 1: The one that was alive had been kicking all night

273
00:17:16,440 --> 00:17:19,359
Speaker 1: trying to get itself up, so it had had made

274
00:17:19,400 --> 00:17:23,040
Speaker 1: this kind of circle depression of of soil around it.

275
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Speaker 1: And so he's asking me, as I'm carving into these

276
00:17:26,320 --> 00:17:29,399
Speaker 1: things about what I'm looking for, And sure enough I

277
00:17:29,440 --> 00:17:32,120
Speaker 1: was able to locate a couple again, twenty two caliber

278
00:17:32,720 --> 00:17:37,520
Speaker 1: slugs that were mostly fragments. At that point, one might wonder,

279
00:17:37,560 --> 00:17:39,879
Speaker 1: you know, how how did kill an elk? Well, when

280
00:17:39,880 --> 00:17:41,919
Speaker 1: you hit him with two or three of them, and

281
00:17:42,000 --> 00:17:45,040
Speaker 1: a couple of them probably in the spinal cord, it

282
00:17:45,119 --> 00:17:50,639
Speaker 1: can drop them. So it it certainly does. I reached

283
00:17:50,640 --> 00:17:53,600
Speaker 1: down into the the more of the gestive area of

284
00:17:53,640 --> 00:17:59,600
Speaker 1: the cavity, and this again was in March and not

285
00:17:59,720 --> 00:18:01,520
Speaker 1: the do you sing in the world. I reached in

286
00:18:01,600 --> 00:18:05,120
Speaker 1: and grabbed about a jack rabbit sized fetus from one

287
00:18:05,119 --> 00:18:07,959
Speaker 1: of the cow elk, and I lighted up on the

288
00:18:08,119 --> 00:18:10,480
Speaker 1: rib cage and looked him in the eye and said,

289
00:18:10,480 --> 00:18:13,520
Speaker 1: you know, this isn't three elk, this is six elk.

290
00:18:14,600 --> 00:18:17,280
Speaker 1: And that's what really kind of turned him white. And

291
00:18:17,600 --> 00:18:19,640
Speaker 1: by the end of the knee cropsy, I had three,

292
00:18:20,560 --> 00:18:23,000
Speaker 1: uh you know, two ft long fetuses laying on the

293
00:18:23,080 --> 00:18:26,199
Speaker 1: rib cage of this one elk, and I thought, you know,

294
00:18:26,240 --> 00:18:28,920
Speaker 1: if that doesn't stimulate someone to come forward and help

295
00:18:28,960 --> 00:18:31,320
Speaker 1: me nab the guy doing this or guys doing this,

296
00:18:31,960 --> 00:18:34,360
Speaker 1: I don't know what can. And the article did come out,

297
00:18:35,280 --> 00:18:39,600
Speaker 1: and all I got was feedback from the public that

298
00:18:39,640 --> 00:18:42,040
Speaker 1: will do everything we can to help you catch this guy.

299
00:18:42,119 --> 00:18:46,320
Speaker 1: But no information ever led to that from that knee cropsy.

300
00:18:47,480 --> 00:18:51,040
Speaker 1: You know, I can't not tell a little piece of

301
00:18:51,040 --> 00:18:55,680
Speaker 1: a story that comes to mind about this individual poaching

302
00:18:55,720 --> 00:18:58,600
Speaker 1: all these elk and and the first thing you want

303
00:18:58,600 --> 00:19:00,680
Speaker 1: to do is a is a war and has catched

304
00:19:00,720 --> 00:19:06,760
Speaker 1: the guy or guys. And an old mentor of mine,

305
00:19:07,840 --> 00:19:11,040
Speaker 1: a warden, had been around for many, many years. We

306
00:19:11,080 --> 00:19:15,119
Speaker 1: called him the herd bull, and we were referred to

307
00:19:15,320 --> 00:19:20,160
Speaker 1: as satellite bulls. And he used to always tell us

308
00:19:20,200 --> 00:19:24,240
Speaker 1: satellite bulls to walk to the dance and you'll finally

309
00:19:24,280 --> 00:19:29,240
Speaker 1: get to dance. Don't run to the dance. And so

310
00:19:29,400 --> 00:19:32,040
Speaker 1: that message to me always said to me to just

311
00:19:32,359 --> 00:19:35,120
Speaker 1: slow down and eventually the person is going to make

312
00:19:35,160 --> 00:19:39,199
Speaker 1: a mistake. And uh, I kept going back to my

313
00:19:39,200 --> 00:19:44,080
Speaker 1: old mentor, thinking, someday, somewhere this guy is going to

314
00:19:44,240 --> 00:19:48,119
Speaker 1: mess up and I'm going to catch him. So after

315
00:19:48,160 --> 00:19:53,000
Speaker 1: the newspaper article came out, nothing ever turned up. Things

316
00:19:53,480 --> 00:19:56,840
Speaker 1: were cold, and uh. In fact, there is a point

317
00:19:56,880 --> 00:19:59,960
Speaker 1: at which I kind of thought maybe the person moved away,

318
00:20:00,600 --> 00:20:02,520
Speaker 1: which could be a good thing, at least some more elk,

319
00:20:02,560 --> 00:20:06,440
Speaker 1: we're going to get tipped over. My wife and I

320
00:20:06,520 --> 00:20:09,080
Speaker 1: lived in a little town called Vernon, and it was

321
00:20:09,119 --> 00:20:12,160
Speaker 1: about twenty miles from a little larger town called Sholo,

322
00:20:13,040 --> 00:20:15,800
Speaker 1: and every once in a while, this was prior to

323
00:20:15,920 --> 00:20:19,760
Speaker 1: us having any any children, we'd head on into the

324
00:20:19,800 --> 00:20:24,160
Speaker 1: big town for Saturday night. On one particular Saturday night,

325
00:20:24,160 --> 00:20:27,359
Speaker 1: we took off to Bill's Bar, famous little tavern and

326
00:20:27,920 --> 00:20:32,280
Speaker 1: in Sholo, whereas, in fact, I had another story where

327
00:20:32,359 --> 00:20:35,520
Speaker 1: some old codgers back in the sixties backed up to

328
00:20:35,600 --> 00:20:37,960
Speaker 1: the back door of Bill's Bar and let a mountain

329
00:20:38,040 --> 00:20:44,480
Speaker 1: lion loose into a crowd of patrons. And uh, and

330
00:20:44,600 --> 00:20:48,320
Speaker 1: you didn't go in there very often without probably seeing

331
00:20:48,440 --> 00:20:51,720
Speaker 1: some kind of fisticuffs and kirk. So you had to

332
00:20:51,720 --> 00:20:54,600
Speaker 1: be a big, big, broad shouldered burley book aoroo work

333
00:20:54,600 --> 00:20:56,920
Speaker 1: in a wide open wind with wilderness to get in there.

334
00:20:58,560 --> 00:21:02,560
Speaker 1: So my wife I did and we we uh went

335
00:21:02,720 --> 00:21:06,040
Speaker 1: had dinner and went dancing, and luckily that night there

336
00:21:06,080 --> 00:21:09,600
Speaker 1: weren't too many cold beers going down the throat, but

337
00:21:09,760 --> 00:21:12,160
Speaker 1: enough to have a fun night. And we were heading

338
00:21:12,200 --> 00:21:16,760
Speaker 1: home after closing about one o'clock in the morning, about

339
00:21:16,760 --> 00:21:20,359
Speaker 1: a twenty mile drive to our little cabin, and uh

340
00:21:20,760 --> 00:21:23,600
Speaker 1: about five miles from home, I could look up into

341
00:21:23,640 --> 00:21:27,600
Speaker 1: the vicinity of where all the out poachings were and

342
00:21:27,920 --> 00:21:33,000
Speaker 1: my gosh, there was a spotlight being thrown around. Spotlights

343
00:21:33,040 --> 00:21:37,720
Speaker 1: are just very very distincting and being able to say

344
00:21:37,800 --> 00:21:43,000
Speaker 1: that's not your headlights. You headlights when vehicles drive, don't

345
00:21:43,119 --> 00:21:46,879
Speaker 1: sweep across the hillside as if they're searching for something.

346
00:21:46,920 --> 00:21:49,119
Speaker 1: It's kind of like a searchlight, if you will. And

347
00:21:49,160 --> 00:21:53,119
Speaker 1: I could see that spotlight being kind of covering different

348
00:21:53,200 --> 00:21:56,920
Speaker 1: hillsides and no doubt in my mind there was some

349
00:21:57,240 --> 00:22:01,479
Speaker 1: activity going on. So I know my my little bride

350
00:22:01,480 --> 00:22:05,160
Speaker 1: wasn't happy, but I decided to to hurry on home

351
00:22:05,200 --> 00:22:07,720
Speaker 1: and put the uniform on and go out and get

352
00:22:07,760 --> 00:22:11,919
Speaker 1: this guy. Um, I certainly wasn't in any condition that

353
00:22:11,920 --> 00:22:15,280
Speaker 1: would prevent me from from doing that. So I I

354
00:22:15,400 --> 00:22:18,760
Speaker 1: made the decision, I'm gonna go suit up and and

355
00:22:18,800 --> 00:22:22,320
Speaker 1: catch this guy. Too good of an opportunity. Jumped in

356
00:22:22,400 --> 00:22:25,480
Speaker 1: my game and fish truck and notified the dispatch that

357
00:22:25,520 --> 00:22:30,159
Speaker 1: I'd be out attempting to make contact with this potential

358
00:22:30,359 --> 00:22:35,480
Speaker 1: health poacher or spotlighter, and took off. And I had

359
00:22:35,480 --> 00:22:38,080
Speaker 1: about a five mile drive to get to where I

360
00:22:38,080 --> 00:22:42,080
Speaker 1: could see the spotlight working. And in those days, we

361
00:22:42,119 --> 00:22:44,399
Speaker 1: had what you call a blackout light that would go

362
00:22:44,440 --> 00:22:47,720
Speaker 1: to the front bumper your game and fish truck, and

363
00:22:47,840 --> 00:22:51,560
Speaker 1: it would allow you to slowly proceed down a dirt

364
00:22:51,680 --> 00:22:55,240
Speaker 1: road without any other lights on. It was a military

365
00:22:55,280 --> 00:22:58,920
Speaker 1: device that we got for all the officers in the state.

366
00:23:00,200 --> 00:23:02,960
Speaker 1: So I proceeded kind of in the direction of this spotlighter,

367
00:23:03,560 --> 00:23:06,879
Speaker 1: occasionally stopping and listening, and I, you know, it was

368
00:23:07,440 --> 00:23:11,439
Speaker 1: difficult to tell. Sometimes I thought I heard rapid fire

369
00:23:12,200 --> 00:23:15,879
Speaker 1: kind of automatic weapon, if you will, And sometimes it

370
00:23:16,600 --> 00:23:19,199
Speaker 1: was more of a crack cracking noise, like more of

371
00:23:19,240 --> 00:23:22,840
Speaker 1: a report of a rifle but nonetheless, I kept entering

372
00:23:22,880 --> 00:23:25,400
Speaker 1: my way to where I thought this guy was working,

373
00:23:26,040 --> 00:23:30,879
Speaker 1: which is a forest service road home to running in

374
00:23:30,880 --> 00:23:33,479
Speaker 1: and out of that vicinity that time of year. So

375
00:23:33,560 --> 00:23:35,960
Speaker 1: I positioned my game and fish struck at the end

376
00:23:36,000 --> 00:23:38,960
Speaker 1: of that and thought, I'm gonna get him. He's gonna

377
00:23:39,000 --> 00:23:42,160
Speaker 1: come out. And now you start to feel the old

378
00:23:42,200 --> 00:23:47,280
Speaker 1: adrenaline coming. You're going into full blown enforcement mode and

379
00:23:47,280 --> 00:23:49,480
Speaker 1: you're pretty sure you're gonna make a stop on what

380
00:23:50,200 --> 00:23:52,920
Speaker 1: was likely to be the worst poacher I'd ever encountered.

381
00:23:54,119 --> 00:23:56,399
Speaker 1: And then all of a sudden, the lights changed and

382
00:23:56,440 --> 00:23:58,800
Speaker 1: they went they went a different way. They were going

383
00:23:58,920 --> 00:24:02,280
Speaker 1: back the same way, but they then turned west, which

384
00:24:02,840 --> 00:24:05,520
Speaker 1: you know, when you're when you're responsible for these districts,

385
00:24:05,560 --> 00:24:07,760
Speaker 1: you know that country like the back of your hand.

386
00:24:07,880 --> 00:24:11,080
Speaker 1: And and I knew that he turned on what I

387
00:24:11,119 --> 00:24:15,439
Speaker 1: assumed was this little dead end two track road, and

388
00:24:15,520 --> 00:24:19,600
Speaker 1: I need to reposition myself to that road, and now

389
00:24:19,640 --> 00:24:24,159
Speaker 1: I'll haven't blocked in. So I did, and when I

390
00:24:24,200 --> 00:24:27,359
Speaker 1: got to that road, there was a a little dip

391
00:24:27,880 --> 00:24:30,320
Speaker 1: onto this other two track road. There was a dip

392
00:24:31,359 --> 00:24:33,960
Speaker 1: with a mud puddle, and it was probably twelve ft across,

393
00:24:34,640 --> 00:24:39,639
Speaker 1: you know, ten ft wide, maybe eight inches deep, and

394
00:24:39,720 --> 00:24:42,160
Speaker 1: if a vehicle goes through that mud puddle, you can

395
00:24:42,200 --> 00:24:45,560
Speaker 1: tell there's gonna be bubbles in it or wash out

396
00:24:45,640 --> 00:24:48,679
Speaker 1: on the other side where water dripped down from the frame.

397
00:24:50,000 --> 00:24:52,159
Speaker 1: And so I accided my game and fish truck, and

398
00:24:52,200 --> 00:24:56,000
Speaker 1: I grabbed a flashlight and I just slowly approached that

399
00:24:56,119 --> 00:24:58,359
Speaker 1: mud puddle and I got down on my knees and

400
00:24:58,400 --> 00:25:03,280
Speaker 1: I kind of muffled the light. I could see no bubbles,

401
00:25:03,800 --> 00:25:06,359
Speaker 1: and then I I kind of walked over to the

402
00:25:06,359 --> 00:25:09,240
Speaker 1: other side and looked on the where the vehicle would

403
00:25:09,240 --> 00:25:14,040
Speaker 1: have driven through, and there's no tracks, there's no sign

404
00:25:14,080 --> 00:25:17,840
Speaker 1: of any washout. I just was bewildered. I thought this

405
00:25:17,880 --> 00:25:22,280
Speaker 1: guy didn't go down this road. So I was discouraged.

406
00:25:22,320 --> 00:25:24,160
Speaker 1: And you know, this has probably been an hour now

407
00:25:24,160 --> 00:25:26,800
Speaker 1: that I've been pursuing this guy, thinking I'm gonna get him,

408
00:25:26,840 --> 00:25:28,960
Speaker 1: and he gave me the slip. So I got my

409
00:25:29,000 --> 00:25:31,840
Speaker 1: game fish truck and backed out and went back on

410
00:25:31,920 --> 00:25:34,520
Speaker 1: the other side of the two road all the way

411
00:25:34,520 --> 00:25:38,000
Speaker 1: out towards Vernon. Uh. I was done for the night.

412
00:25:38,040 --> 00:25:40,919
Speaker 1: And the only thing I can remember is when I

413
00:25:40,960 --> 00:25:44,359
Speaker 1: got back to the cabin that night, my wife was

414
00:25:44,920 --> 00:25:48,240
Speaker 1: let's just stay happy to see me there, not necessarily

415
00:25:48,280 --> 00:25:51,560
Speaker 1: excited about the fact, and running out to catch a

416
00:25:51,600 --> 00:25:55,840
Speaker 1: bad guy at two in the morning. So after that happened,

417
00:25:55,840 --> 00:25:58,760
Speaker 1: I was again discouraged. I thought, when when am I

418
00:25:58,800 --> 00:26:01,280
Speaker 1: going to get another break? I just don't know. But

419
00:26:01,440 --> 00:26:03,879
Speaker 1: that that night I thought I had him, but he

420
00:26:03,920 --> 00:26:09,040
Speaker 1: slipped away. So following that that evening where I felt

421
00:26:09,080 --> 00:26:15,440
Speaker 1: I was the closest at catching this guy, things continued on.

422
00:26:15,560 --> 00:26:19,359
Speaker 1: We we ended up getting a couple more calls on

423
00:26:19,440 --> 00:26:24,119
Speaker 1: elk that were shot UM No again, no no leads.

424
00:26:24,560 --> 00:26:28,040
Speaker 1: And I do recall the vicinity though it was a

425
00:26:28,160 --> 00:26:33,160
Speaker 1: very localized area, you know, all right around that road

426
00:26:33,200 --> 00:26:37,560
Speaker 1: that I found the spotlighter on um and those elk

427
00:26:37,760 --> 00:26:40,959
Speaker 1: would soon be moving out of their winter range up

428
00:26:41,000 --> 00:26:44,080
Speaker 1: into the north range, up into their their summer country,

429
00:26:44,560 --> 00:26:48,040
Speaker 1: so we kind of felt things would be be slowing down.

430
00:26:48,240 --> 00:26:52,240
Speaker 1: But after an elk or two more, it just stopped.

431
00:26:53,240 --> 00:26:55,240
Speaker 1: And while I thought maybe it had to do with

432
00:26:55,280 --> 00:26:59,240
Speaker 1: that migration to higher country, there was still enough elk

433
00:26:59,320 --> 00:27:02,919
Speaker 1: in that lower range to warrant some shooting at the

434
00:27:02,920 --> 00:27:05,600
Speaker 1: guy was still around, but I felt like it it

435
00:27:05,760 --> 00:27:09,840
Speaker 1: just stopped and pretty much kind of stamped at case

436
00:27:10,080 --> 00:27:14,119
Speaker 1: case unsolved. We couldn't put this one behind us, and

437
00:27:14,160 --> 00:27:15,960
Speaker 1: there was a lot of a lot of people trying

438
00:27:16,000 --> 00:27:20,800
Speaker 1: to to make this case work. Never did, and I

439
00:27:20,920 --> 00:27:23,720
Speaker 1: just felt it was it was. It was on onward

440
00:27:23,760 --> 00:27:26,640
Speaker 1: to the next one then that that's gonna be one

441
00:27:26,760 --> 00:27:32,320
Speaker 1: for the books and other blue. One day, our investigator

442
00:27:33,280 --> 00:27:36,480
Speaker 1: called me and said, hey, we got a weird call

443
00:27:36,600 --> 00:27:41,119
Speaker 1: today from a narcotics agent up in Holbrook, which is

444
00:27:41,160 --> 00:27:45,400
Speaker 1: a town about forty miles north of Vermin, and he said,

445
00:27:45,400 --> 00:27:49,840
Speaker 1: we have a guy in custody that is being held

446
00:27:49,840 --> 00:27:57,320
Speaker 1: on some pretty serious drug trafficking charges and attempted homicide charges,

447
00:27:58,080 --> 00:28:01,080
Speaker 1: most likely going to be moved to Albuquerque, but he's

448
00:28:01,080 --> 00:28:05,800
Speaker 1: in our holding facility and during interviews he mentioned something

449
00:28:05,840 --> 00:28:09,480
Speaker 1: about shooting a bunch of elk in the Vernon area,

450
00:28:10,840 --> 00:28:15,239
Speaker 1: and so this UH narcotics agent asked our investigator if

451
00:28:15,280 --> 00:28:19,399
Speaker 1: we had any interest in interviewing him, and of course

452
00:28:19,720 --> 00:28:23,639
Speaker 1: I jumped at the opportunity. I thought to myself, if

453
00:28:23,680 --> 00:28:26,080
Speaker 1: this is if this is the guy, I can finally

454
00:28:26,119 --> 00:28:28,520
Speaker 1: maybe get some closure to this. And it's not going

455
00:28:28,560 --> 00:28:32,320
Speaker 1: to be a citation for killing fifteen elk this season.

456
00:28:32,400 --> 00:28:35,359
Speaker 1: It's this guy is going away, probably too much, bigger house.

457
00:28:36,160 --> 00:28:37,639
Speaker 1: So yeah, I want to go. I want to go

458
00:28:37,760 --> 00:28:40,080
Speaker 1: visit and I want to go talk to him. And

459
00:28:40,120 --> 00:28:43,560
Speaker 1: an Arconics agent relayed to our investigator that he's a

460
00:28:43,680 --> 00:28:47,760
Speaker 1: pretty strange duck and you might want to bring him

461
00:28:47,760 --> 00:28:52,040
Speaker 1: a Baby Ruth candy bar because he likes candy bars.

462
00:28:53,000 --> 00:28:55,120
Speaker 1: That if you bring him that, he might might be

463
00:28:55,160 --> 00:28:59,160
Speaker 1: willing to talk to you. So we did. I've stopped

464
00:28:59,160 --> 00:29:02,040
Speaker 1: the store, got a Baby Ruth candy bar and or

465
00:29:02,200 --> 00:29:05,880
Speaker 1: civilian clothes, so I didn't intimidate him at all with

466
00:29:05,960 --> 00:29:10,400
Speaker 1: the uniform and drove to Hoolebrook and checked in with

467
00:29:10,440 --> 00:29:13,600
Speaker 1: the officers there and let him know what I was

468
00:29:13,640 --> 00:29:16,600
Speaker 1: there for to to interview the suspect. His name was

469
00:29:16,640 --> 00:29:20,720
Speaker 1: Okay and uh. Other than that, I didn't have any

470
00:29:20,760 --> 00:29:23,000
Speaker 1: more details other than the fact that he was being

471
00:29:23,040 --> 00:29:27,600
Speaker 1: held on pretty serious charges. He was running a little

472
00:29:27,600 --> 00:29:33,280
Speaker 1: met lab and some some involvement in a murder case

473
00:29:33,480 --> 00:29:37,640
Speaker 1: in Alburquerque, something to do with a past girlfriend or

474
00:29:37,760 --> 00:29:40,760
Speaker 1: or something of that nature. But he was being held

475
00:29:40,800 --> 00:29:46,360
Speaker 1: on on both narcotics and homicide charges. So they led

476
00:29:46,400 --> 00:29:48,880
Speaker 1: me down this you know, kind of sterile hallway and

477
00:29:48,960 --> 00:29:53,520
Speaker 1: got me into an interrogation room where I sat, and

478
00:29:53,560 --> 00:29:57,680
Speaker 1: then five minutes or so past and the door opens up,

479
00:29:57,680 --> 00:30:02,200
Speaker 1: and here's this straggly looking character in a orange jump suit.

480
00:30:03,280 --> 00:30:05,960
Speaker 1: He had what we call a transport belt around his

481
00:30:06,040 --> 00:30:10,160
Speaker 1: waist with his handcuffs on attached to that transport belt,

482
00:30:10,200 --> 00:30:13,640
Speaker 1: so you can't swing your arms at all. He's he's

483
00:30:14,120 --> 00:30:17,800
Speaker 1: he's confined, kind of looked at me like, you know,

484
00:30:18,200 --> 00:30:22,960
Speaker 1: absolute careless. He didn't have any regard for you know,

485
00:30:23,000 --> 00:30:26,400
Speaker 1: what I was there for, obviously, But the officer that

486
00:30:26,480 --> 00:30:28,640
Speaker 1: led him into the room explained that, you know, I

487
00:30:28,720 --> 00:30:30,440
Speaker 1: was with game and Fish and I just wanted to

488
00:30:30,440 --> 00:30:33,680
Speaker 1: talk to him about some of the unsolved elk poachings

489
00:30:33,680 --> 00:30:37,960
Speaker 1: we had in the White Mountains. And he reluctantly sat down,

490
00:30:38,000 --> 00:30:40,400
Speaker 1: and he kind of just stared at me like he

491
00:30:40,600 --> 00:30:44,040
Speaker 1: was looking through the back of my skull, and he

492
00:30:44,080 --> 00:30:46,920
Speaker 1: had these kind of dark, steely looking eyes. He just

493
00:30:47,120 --> 00:30:50,400
Speaker 1: you know, which was kind of rang the old socio

494
00:30:50,560 --> 00:30:53,080
Speaker 1: path in my mind that this guy doesn't really care

495
00:30:53,200 --> 00:30:55,480
Speaker 1: much about me or what he's about to tell me.

496
00:30:56,840 --> 00:30:59,440
Speaker 1: So I introduced myself. Okay, I'm Sam Lowry. I'm with

497
00:30:59,480 --> 00:31:02,040
Speaker 1: there as a and Fish and I. I know you're

498
00:31:02,040 --> 00:31:04,720
Speaker 1: in here for things more serious than I want to

499
00:31:04,720 --> 00:31:07,680
Speaker 1: talk to you about, but I really wanted to visit

500
00:31:07,720 --> 00:31:09,640
Speaker 1: with you a little bit about something you told the

501
00:31:09,680 --> 00:31:15,040
Speaker 1: officers about your help poaching in Vernon. And he kind

502
00:31:15,080 --> 00:31:17,880
Speaker 1: of let out a little sigh and sat back in

503
00:31:18,000 --> 00:31:21,760
Speaker 1: his chair, almost almost relax a little more. He looked

504
00:31:21,840 --> 00:31:26,720
Speaker 1: right at me, just again he's cold, shark like eyes

505
00:31:26,880 --> 00:31:29,840
Speaker 1: and yeah, that was me that So what do you

506
00:31:29,880 --> 00:31:32,280
Speaker 1: mean it was you? I mean what I was the

507
00:31:32,280 --> 00:31:35,400
Speaker 1: one I have shot probably thirty elk up there, and

508
00:31:35,440 --> 00:31:39,880
Speaker 1: you guys, you guys can never catch me. And I

509
00:31:39,960 --> 00:31:42,560
Speaker 1: kind of leaned in and I wanted to find out

510
00:31:42,600 --> 00:31:46,720
Speaker 1: why and so what was the cause? And and he

511
00:31:46,840 --> 00:31:49,480
Speaker 1: stopped me and looked and said, I'll tell you one thing, though.

512
00:31:50,720 --> 00:31:55,600
Speaker 1: You got a warden out there with angel wings. And

513
00:31:54,800 --> 00:31:58,920
Speaker 1: I kind of paused myself, and I thought, what do

514
00:31:58,960 --> 00:32:00,920
Speaker 1: you mean they're okay? What what do you mean by that?

515
00:32:02,640 --> 00:32:04,440
Speaker 1: And he said, well, one night, he said one of

516
00:32:04,480 --> 00:32:07,840
Speaker 1: your guys was was after me. He darned here had me.

517
00:32:07,880 --> 00:32:10,120
Speaker 1: And he said they played cat and mouse for a

518
00:32:10,160 --> 00:32:13,600
Speaker 1: little while. And he came down this two track road

519
00:32:13,640 --> 00:32:17,160
Speaker 1: where there was a big mud puddle, and he said,

520
00:32:17,200 --> 00:32:20,920
Speaker 1: I was parked probably fifty yards from that, behind a

521
00:32:20,960 --> 00:32:25,000
Speaker 1: big juniper tree. That dumb bastard got out of his

522
00:32:25,080 --> 00:32:27,680
Speaker 1: truck and walked up to the mud puddle with his

523
00:32:27,720 --> 00:32:31,640
Speaker 1: flashlight like he was some kind of hero. And Uh,

524
00:32:31,840 --> 00:32:34,040
Speaker 1: I had made the decision, if he comes through that

525
00:32:34,160 --> 00:32:39,000
Speaker 1: mud puddle, I'm gonna spray him. Yeah, I had to pause.

526
00:32:39,160 --> 00:32:43,240
Speaker 1: I mean he probably saw my face. I said, spray him?

527
00:32:43,280 --> 00:32:45,560
Speaker 1: What you know? What? What? What do you mean? He said,

528
00:32:45,560 --> 00:32:47,440
Speaker 1: I have a newsy That's what I was shooting those

529
00:32:47,440 --> 00:32:51,080
Speaker 1: elk with. And whether he came across on foot or

530
00:32:51,120 --> 00:32:53,520
Speaker 1: in vehicle, that was going to be his last night.

531
00:32:54,560 --> 00:32:56,680
Speaker 1: But strangely enough, that guy got in his truck and

532
00:32:56,720 --> 00:33:00,120
Speaker 1: turned away. Maybe you knew I was down there, and

533
00:33:00,240 --> 00:33:03,360
Speaker 1: I have chills on my neck telling you guys that story.

534
00:33:03,440 --> 00:33:06,480
Speaker 1: I can remember just walking out of that room that

535
00:33:06,600 --> 00:33:12,200
Speaker 1: day thinking, holy mackerel, that was me. Uh, whatever reasons,

536
00:33:12,800 --> 00:33:14,960
Speaker 1: And I can't explain it to you why it didn't

537
00:33:15,040 --> 00:33:18,000
Speaker 1: look like he had driven through that mud puddle, but

538
00:33:18,120 --> 00:33:21,000
Speaker 1: he had, and he was fifty ft or fifty yards

539
00:33:21,040 --> 00:33:25,600
Speaker 1: from me, ready to take me out. So we had

540
00:33:25,640 --> 00:33:27,840
Speaker 1: talked a little more, you know, I was. I was.

541
00:33:28,040 --> 00:33:31,280
Speaker 1: I was pretty much shot, no pun intended. I thought,

542
00:33:31,320 --> 00:33:33,480
Speaker 1: you know what, I just want to go home and

543
00:33:33,560 --> 00:33:36,600
Speaker 1: hug my wife. But I tried to end the interview.

544
00:33:37,200 --> 00:33:39,840
Speaker 1: There was no doubt in my mind it was him.

545
00:33:40,000 --> 00:33:42,200
Speaker 1: He was on meth. He told me he was cooking

546
00:33:42,240 --> 00:33:45,200
Speaker 1: meth up in a little cabin not far from where

547
00:33:45,240 --> 00:33:48,400
Speaker 1: he was doing all the shooting. He was by himself,

548
00:33:49,200 --> 00:33:51,520
Speaker 1: and he just liked to kill stuff. As he told me,

549
00:33:51,600 --> 00:33:56,760
Speaker 1: I like to kill ship and no remorse, no, no, nothing.

550
00:33:56,920 --> 00:34:01,400
Speaker 1: And I never did recover the coozy to match those

551
00:34:01,560 --> 00:34:06,040
Speaker 1: bullets with, but I'll never forget them, you know. Walking

552
00:34:06,160 --> 00:34:09,080
Speaker 1: him back down the hallway, and he kind of looked

553
00:34:09,640 --> 00:34:12,000
Speaker 1: over his shoulder, looked back at me one more time,

554
00:34:13,239 --> 00:34:17,520
Speaker 1: not knowing that I was at Angel was that game warden?

555
00:34:17,560 --> 00:34:19,520
Speaker 1: It had wings at night. I never let him know

556
00:34:19,600 --> 00:34:22,359
Speaker 1: that anyway. But he walked away and that was never

557
00:34:22,440 --> 00:34:25,840
Speaker 1: to be seen again. Old Loki. Oh he ate the

558
00:34:25,880 --> 00:34:33,480
Speaker 1: candy bar too. Okay, there you haveing ladies and gentlemen.

559
00:34:33,520 --> 00:34:37,279
Speaker 1: That's just one little sampling, one little sampling off of

560
00:34:37,320 --> 00:34:39,439
Speaker 1: the Broader project. Again, like I said, it's five six

561
00:34:39,440 --> 00:34:45,080
Speaker 1: hours long, sixteen stories. There's one of them. They're all good.

562
00:34:46,280 --> 00:34:49,279
Speaker 1: So go out and get that's available now. That's for

563
00:34:49,320 --> 00:34:52,800
Speaker 1: your listening. Cathy Ravens Books for your reading. That's for

564
00:34:52,920 --> 00:34:57,439
Speaker 1: your listening. Yeah, well it's available for pre order right now, tomorrow,

565
00:34:57,719 --> 00:35:02,359
Speaker 1: it's available. How it works, Yeah, it's a pre order

566
00:35:02,480 --> 00:35:07,279
Speaker 1: now and I'll just magically show up mm hm as

567
00:35:07,320 --> 00:35:11,480
Speaker 1: a download as a down one. Um, we're gonna continue.

568
00:35:11,520 --> 00:35:13,600
Speaker 1: So when you hear that story and you go listen

569
00:35:13,600 --> 00:35:16,080
Speaker 1: to the broader story, let us know about your crazy stories.

570
00:35:16,719 --> 00:35:19,080
Speaker 1: Because when you send an email and just send it

571
00:35:19,080 --> 00:35:21,160
Speaker 1: in and says like a crazy ass story as a

572
00:35:21,200 --> 00:35:24,480
Speaker 1: subject line, and we might hunt you down because we

573
00:35:24,640 --> 00:35:27,200
Speaker 1: like that kind of story, like you just heard. Yeah,

574
00:35:27,200 --> 00:35:31,879
Speaker 1: we liked working on this project. That was fun. Yeahs

575
00:35:31,920 --> 00:35:35,360
Speaker 1: tracking people down was great. It makes you think about

576
00:35:35,480 --> 00:35:37,319
Speaker 1: things all the time, though, because a lot of these

577
00:35:37,360 --> 00:35:44,000
Speaker 1: stories involved like very micro like incidents and like just

578
00:35:44,280 --> 00:35:47,479
Speaker 1: small things that happened that you know, make the whole

579
00:35:47,600 --> 00:35:51,279
Speaker 1: day have a much different outcome. And so I know,

580
00:35:51,320 --> 00:35:53,480
Speaker 1: when I'm out in the woods and just taking a

581
00:35:53,520 --> 00:35:57,160
Speaker 1: step on a rock that's might be over a precipice

582
00:35:57,239 --> 00:35:59,239
Speaker 1: or something, it makes me think twice. After hearing some

583
00:35:59,280 --> 00:36:03,040
Speaker 1: of these stories. Yeah, it was Yan Yanni's in the

584
00:36:03,120 --> 00:36:06,040
Speaker 1: Yanni's in the project. Because the people that listen to

585
00:36:06,040 --> 00:36:08,920
Speaker 1: this show are familiar with may be familiar with a

586
00:36:08,920 --> 00:36:10,960
Speaker 1: couple of episodes we had called the Meat Tree Part

587
00:36:11,000 --> 00:36:16,640
Speaker 1: one and part two. We revisit that story and some

588
00:36:16,800 --> 00:36:21,400
Speaker 1: aftermath issues from that story. And if that day hadn't happened,

589
00:36:21,440 --> 00:36:24,439
Speaker 1: if that minute, that minute hadn't happened, where we had

590
00:36:24,880 --> 00:36:27,480
Speaker 1: a very close encounter with a with a brown bear

591
00:36:27,520 --> 00:36:29,440
Speaker 1: that Yanni smacked in the face with a set of

592
00:36:29,440 --> 00:36:34,480
Speaker 1: track and polls um this book, this audio project wouldn't

593
00:36:34,480 --> 00:36:39,480
Speaker 1: exist like that set me down the path of like

594
00:36:39,719 --> 00:36:42,919
Speaker 1: being haunted by that day, set me down the path

595
00:36:43,000 --> 00:36:45,840
Speaker 1: of kind of exploring what close calls due to a

596
00:36:46,200 --> 00:36:48,160
Speaker 1: due to you and how they live in your mind.

597
00:36:49,760 --> 00:36:52,480
Speaker 1: What do you think, Phil, that was great? We're good

598
00:36:52,480 --> 00:36:59,160
Speaker 1: to move on? Where Korean standing? I'd say, yes, do people?

599
00:37:00,040 --> 00:37:03,239
Speaker 1: Oh order this audio prize and feels not cut out

600
00:37:03,280 --> 00:37:09,239
Speaker 1: for this job after all? To get it, you gotta

601
00:37:09,280 --> 00:37:12,640
Speaker 1: go to Audible, You can go to Amazon, or you

602
00:37:12,640 --> 00:37:16,000
Speaker 1: can go to our publisher, Penguin Random Houses website to

603
00:37:16,239 --> 00:37:21,000
Speaker 1: pre order or just order whatever Meat Eat camp Fire Stories,

604
00:37:21,000 --> 00:37:25,640
Speaker 1: Close Calls comes out July, but secure it now again.

605
00:37:26,080 --> 00:37:28,040
Speaker 1: You can find it on Audible, you can find it

606
00:37:28,080 --> 00:37:31,319
Speaker 1: on Amazon, you can find it at Penguin Random House

607
00:37:31,360 --> 00:37:36,280
Speaker 1: website and get it Meat Eater camp Fire Stories. Close

608
00:37:36,360 --> 00:37:42,200
Speaker 1: Calls fully available July twenty, available for pre order at

609
00:37:42,200 --> 00:37:47,040
Speaker 1: any point. All right, Carmen, Um, do you do you

610
00:37:47,040 --> 00:37:48,760
Speaker 1: have any close calls you need to make us aware

611
00:37:48,760 --> 00:37:51,640
Speaker 1: of for our next project. No, I have not had

612
00:37:52,000 --> 00:37:56,040
Speaker 1: any what I would consider close calls. But I do

613
00:37:56,520 --> 00:37:59,279
Speaker 1: sometimes think back on ways that I've done things in

614
00:37:59,320 --> 00:38:02,400
Speaker 1: the field and and know now that that was pretty

615
00:38:02,440 --> 00:38:06,040
Speaker 1: stupid and not not very safety minded. So you mean

616
00:38:06,480 --> 00:38:11,359
Speaker 1: in dealing with animals, Yeah, in dealing with animals, but yeah,

617
00:38:11,480 --> 00:38:13,920
Speaker 1: mostly dealing with just getting around on the landscape. Like

618
00:38:13,960 --> 00:38:19,560
Speaker 1: I think about the first job I had UM where

619
00:38:19,600 --> 00:38:24,800
Speaker 1: we were using four wheelers a lot. It was in Alberta, Canada,

620
00:38:25,400 --> 00:38:30,520
Speaker 1: and um in the Alberta Rockies, so super rugged terrain

621
00:38:30,960 --> 00:38:33,120
Speaker 1: and people just kind of blast all over the place

622
00:38:33,160 --> 00:38:36,200
Speaker 1: on a t V s there and so it kind

623
00:38:36,200 --> 00:38:39,200
Speaker 1: of feels like I can go anywhere. But um, I

624
00:38:39,239 --> 00:38:43,600
Speaker 1: mean I was, you know, flipping a TVs and we

625
00:38:43,600 --> 00:38:47,880
Speaker 1: were doing some really not smart stuff, just just stretching

626
00:38:47,880 --> 00:38:50,360
Speaker 1: when an ATV should be doing with more people on

627
00:38:50,400 --> 00:38:53,120
Speaker 1: it than should be on it. That sort of thing. Um,

628
00:38:53,239 --> 00:38:57,440
Speaker 1: snowmobiling too. I learned a snowmobile in the Northern main

629
00:38:57,520 --> 00:39:01,080
Speaker 1: Woods and winter. So I was working with two guys

630
00:39:01,080 --> 00:39:03,960
Speaker 1: who had been doing it their whole lives and basically

631
00:39:04,040 --> 00:39:09,120
Speaker 1: learning on the fly, you know, blasting around at sixty

632
00:39:09,200 --> 00:39:13,239
Speaker 1: miles an hour and again wrecking and flipping snowmobiles and

633
00:39:13,560 --> 00:39:16,560
Speaker 1: all that. So so so the machinery's more expensive, more

634
00:39:16,640 --> 00:39:23,800
Speaker 1: dangerous than the animals, oh, I would say, so yeah. Yeah.

635
00:39:23,840 --> 00:39:27,239
Speaker 1: My other, my other not smart traveling thing was m

636
00:39:28,160 --> 00:39:32,040
Speaker 1: hitchhiking between our our field camp and town. I look

637
00:39:32,080 --> 00:39:34,080
Speaker 1: back on that, I was like, I think I was

638
00:39:34,480 --> 00:39:36,840
Speaker 1: nineteen or twenty. You're going in town to whoop it

639
00:39:36,960 --> 00:39:41,719
Speaker 1: up ORGI groceries. But yeah, yeah, going into town all

640
00:39:41,719 --> 00:39:44,680
Speaker 1: your days off and we just hitchhike. And um, I

641
00:39:44,680 --> 00:39:46,920
Speaker 1: remember this one guy pulled over. It was me and

642
00:39:47,680 --> 00:39:51,600
Speaker 1: a girl I was working with, and he just one

643
00:39:51,600 --> 00:39:55,640
Speaker 1: of those instant creepy vibes out kind of h come

644
00:39:55,680 --> 00:39:58,759
Speaker 1: out standing on the side of the road and he's

645
00:39:58,760 --> 00:40:00,359
Speaker 1: trying to not think at all. He is a couple

646
00:40:00,400 --> 00:40:04,640
Speaker 1: of biologists going into town against groceries. No older, older fellows.

647
00:40:04,800 --> 00:40:08,200
Speaker 1: Here are some people that want to part. I've never

648
00:40:08,239 --> 00:40:10,560
Speaker 1: told my parents this. I don't know if they'll listen,

649
00:40:10,640 --> 00:40:15,120
Speaker 1: but yep, stopped, pulled over. I started to get into

650
00:40:15,160 --> 00:40:20,799
Speaker 1: the front seat, and there were various things you'd get

651
00:40:20,840 --> 00:40:26,800
Speaker 1: in a truck stop bathroom, like different colored condoms and loops,

652
00:40:26,960 --> 00:40:29,480
Speaker 1: just thrown on the floor and in the backseat as

653
00:40:29,520 --> 00:40:32,799
Speaker 1: my friend was getting oh, I hope knew, I don't.

654
00:40:32,800 --> 00:40:36,280
Speaker 1: I don't remember that still in the package. And then

655
00:40:36,480 --> 00:40:40,520
Speaker 1: as she was getting in, she she said, she told

656
00:40:40,520 --> 00:40:43,000
Speaker 1: me there's a gun on the floor here, and there's

657
00:40:43,040 --> 00:40:45,399
Speaker 1: a pistol in the in this car, on the floor,

658
00:40:45,440 --> 00:40:49,480
Speaker 1: and just that combined with his vibe ready to go,

659
00:40:49,600 --> 00:40:54,600
Speaker 1: ready for ready, yes, ready for any number of directions. Yeah,

660
00:40:54,719 --> 00:41:00,360
Speaker 1: so we um, you know it's Tuesday. Go on anyway

661
00:41:00,400 --> 00:41:03,000
Speaker 1: we did. I refused to get in, and he tried

662
00:41:03,040 --> 00:41:07,600
Speaker 1: to convince us, but we waited for the next car. Um.

663
00:41:07,800 --> 00:41:09,759
Speaker 1: I want to role play for a minute. Hold on,

664
00:41:09,920 --> 00:41:13,040
Speaker 1: now be a good time to uh, let Carmen explain

665
00:41:13,120 --> 00:41:14,919
Speaker 1: what she does. I want to role play real quick,

666
00:41:15,000 --> 00:41:18,160
Speaker 1: too far? Okay, you want to cleanse the root words

667
00:41:18,280 --> 00:41:27,479
Speaker 1: role play. I'm Carmen and she's the trucker. Yes, okay, ready,

668
00:41:28,760 --> 00:41:31,280
Speaker 1: I'm not going to get in. I've changed my mind,

669
00:41:32,239 --> 00:41:37,359
Speaker 1: he says, just get in. Oh okay. So not being

670
00:41:37,440 --> 00:41:39,880
Speaker 1: swab No, no, no, no, no, he was. He was

671
00:41:40,320 --> 00:41:43,239
Speaker 1: strange and creepy. Okay. Yeah, that's all. That's It's just

672
00:41:43,440 --> 00:41:50,000
Speaker 1: very quick roleplay. I appreciate keep it. Thank you. Yeah,

673
00:41:50,120 --> 00:41:52,239
Speaker 1: it was what you I wasn't going to do what

674
00:41:52,320 --> 00:41:57,279
Speaker 1: you worried. What's gonna happen? Okay, fill people in now

675
00:41:57,560 --> 00:42:02,759
Speaker 1: moving on. So, uh way a million years ago when

676
00:42:02,760 --> 00:42:05,239
Speaker 1: you came on the show, you were getting engaged. You

677
00:42:05,239 --> 00:42:09,279
Speaker 1: were not getting engage. You were engaging in a long project.

678
00:42:09,320 --> 00:42:12,359
Speaker 1: I think way back then. Let's see the second time

679
00:42:12,400 --> 00:42:14,239
Speaker 1: I was on, I was I was starting on what

680
00:42:14,360 --> 00:42:18,240
Speaker 1: is the Washington Predator Prey Project. Yeah, okay, break that down. Okay,

681
00:42:18,440 --> 00:42:21,600
Speaker 1: So I am like I said that projects winding up.

682
00:42:21,640 --> 00:42:27,800
Speaker 1: But it was a a project between a cooperation between

683
00:42:27,840 --> 00:42:31,560
Speaker 1: the University of Washington and Washington Apartment of Fishing Wildlife

684
00:42:32,160 --> 00:42:38,600
Speaker 1: UM basically in a nutshell, looking at how re colonizing

685
00:42:38,600 --> 00:42:42,560
Speaker 1: wolves could be affecting a number of other species. Dear

686
00:42:42,680 --> 00:42:47,640
Speaker 1: Elk of course, and then um cougars as well. And

687
00:42:47,640 --> 00:42:50,920
Speaker 1: then the component that I mostly worked on was meso

688
00:42:50,960 --> 00:42:56,360
Speaker 1: carnivores so bobcats and coyotes. Um, with sort of the

689
00:42:56,760 --> 00:43:00,279
Speaker 1: explaining the word meso carnivores medium sized, medium side, what's

690
00:43:00,280 --> 00:43:03,839
Speaker 1: the word for? Like what what's a little teeny one

691
00:43:03,880 --> 00:43:11,360
Speaker 1: called one of the little guys? I don't know, smart cardiores?

692
00:43:11,400 --> 00:43:16,960
Speaker 1: Smart car um? All right, go on, okay, so bobcats

693
00:43:16,960 --> 00:43:20,800
Speaker 1: and coyotes so um. Basically just just looking at the premise,

694
00:43:21,480 --> 00:43:24,160
Speaker 1: uh that with the return of wolves and with other

695
00:43:24,200 --> 00:43:27,719
Speaker 1: any larger predators that are taking down larger prey, they

696
00:43:27,719 --> 00:43:30,439
Speaker 1: could be creating This is kind of the theory behind

697
00:43:30,480 --> 00:43:36,280
Speaker 1: the study. They could be creating um. Either food opportunities

698
00:43:36,320 --> 00:43:40,239
Speaker 1: for meso carnivores because they can scavenge the deer carcasses,

699
00:43:40,400 --> 00:43:44,719
Speaker 1: out carcasses, et cetera, and so that could be a

700
00:43:44,760 --> 00:43:48,680
Speaker 1: benefit to the meusic carnivores. But it could also be

701
00:43:48,880 --> 00:43:51,759
Speaker 1: what they call a fatal attraction because these music carnivores

702
00:43:51,760 --> 00:43:54,960
Speaker 1: could be attracted to these spots and then they themselves

703
00:43:54,960 --> 00:43:59,360
Speaker 1: get get killed by the bigger predator. Yeah. So basically

704
00:43:59,360 --> 00:44:02,719
Speaker 1: it's interesting. Yeah, so is that the true definition of

705
00:44:02,760 --> 00:44:05,680
Speaker 1: fatal attraction is that what that comes from. It's a movie, dude.

706
00:44:07,320 --> 00:44:10,480
Speaker 1: It might just be applied to this, to this ecological

707
00:44:10,840 --> 00:44:15,280
Speaker 1: uh theory. What's that movie about? That was Glenn Close?

708
00:44:15,600 --> 00:44:19,680
Speaker 1: Oh that's my pills here? Come on, Bill laid down?

709
00:44:20,560 --> 00:44:23,400
Speaker 1: I don't know's the sharing stone one? That's basic instinct?

710
00:44:23,719 --> 00:44:28,880
Speaker 1: Thank you? Glenn Close gets very jealous and uh, you

711
00:44:28,920 --> 00:44:31,439
Speaker 1: know it goes out the deep end, got it? That's

712
00:44:31,440 --> 00:44:33,759
Speaker 1: the quick it's not about it's like not like a

713
00:44:33,840 --> 00:44:41,920
Speaker 1: David Atton Burrow Navigate narrated. Um. You know what's interesting

714
00:44:41,920 --> 00:44:46,520
Speaker 1: about the creating more food resources? Uh. We have a

715
00:44:46,560 --> 00:44:50,200
Speaker 1: friend who likes to run his hounds, um, and he

716
00:44:50,600 --> 00:44:55,600
Speaker 1: runs mountain lions mostly, but he also runs bobcats. And

717
00:44:55,800 --> 00:45:00,279
Speaker 1: he was telling me that in December, when the season arts,

718
00:45:00,719 --> 00:45:03,880
Speaker 1: you don't cut a lot of cat tracks, he says,

719
00:45:03,920 --> 00:45:05,840
Speaker 1: because there's too many. There's still all the deer and

720
00:45:05,880 --> 00:45:09,680
Speaker 1: elk carcasses from hunting season on the ground. Interesting, Yeah,

721
00:45:09,760 --> 00:45:11,880
Speaker 1: because you kind of his theory is you kind of

722
00:45:11,880 --> 00:45:15,160
Speaker 1: wait and as those deer and elk carcasses from late

723
00:45:15,239 --> 00:45:20,200
Speaker 1: November get mopped up, then you start seeing cats spreading

724
00:45:20,239 --> 00:45:22,400
Speaker 1: out more and they're not just stuck in one place

725
00:45:22,719 --> 00:45:26,000
Speaker 1: feeding on some you know, carcass and gut pile. Yeah, no,

726
00:45:26,280 --> 00:45:29,920
Speaker 1: I mean that that makes sense doing going to on

727
00:45:29,920 --> 00:45:35,440
Speaker 1: on various other projects. Um, wolf clusters is what we

728
00:45:35,520 --> 00:45:38,120
Speaker 1: call them. It's basically wolves that have had GPS colors on.

729
00:45:38,360 --> 00:45:41,799
Speaker 1: They're taking a fix every two to four hours, and

730
00:45:41,880 --> 00:45:46,600
Speaker 1: so you can then download those those GPS points on

731
00:45:46,719 --> 00:45:51,080
Speaker 1: cheer computer run an algorithm that pulls out spots where

732
00:45:52,360 --> 00:45:56,799
Speaker 1: GPS points have been sort of clumping up within a

733
00:45:56,840 --> 00:45:59,759
Speaker 1: certain you know radius of you know, something like two

734
00:45:59,800 --> 00:46:03,080
Speaker 1: hunters within a certain time frame. So basically the wolves

735
00:46:03,120 --> 00:46:05,320
Speaker 1: were hanging out in this little spot for a while.

736
00:46:05,840 --> 00:46:08,200
Speaker 1: So that's you guys have figured out how to do

737
00:46:08,239 --> 00:46:11,439
Speaker 1: that automatically. Yeah, because it's gotta be every fifteen minutes.

738
00:46:11,440 --> 00:46:14,319
Speaker 1: It's gotta be like an enormous amount of every two

739
00:46:14,480 --> 00:46:18,319
Speaker 1: two to four hours. I mean you can hold did

740
00:46:18,320 --> 00:46:22,479
Speaker 1: I word fifteen minutes come from? I think? So every

741
00:46:22,480 --> 00:46:24,800
Speaker 1: two to four hours, So every two to four hours

742
00:46:24,880 --> 00:46:29,040
Speaker 1: he like makes it drops a pin basically yeah, yeah,

743
00:46:29,200 --> 00:46:31,400
Speaker 1: and you can set that that fixed rate is what

744
00:46:31,440 --> 00:46:33,640
Speaker 1: that's called too. I mean you could do you can

745
00:46:33,800 --> 00:46:36,240
Speaker 1: some projects just depending on what question you're trying to answer.

746
00:46:36,280 --> 00:46:39,600
Speaker 1: You could have a really really fine scaled movement path

747
00:46:39,680 --> 00:46:41,439
Speaker 1: of an animal because it could be getting a fixed

748
00:46:41,520 --> 00:46:44,719
Speaker 1: rate every fifteen or thirty minutes or whatever. But for

749
00:46:45,400 --> 00:46:48,279
Speaker 1: kill sites, they've they've done the stats and every two

750
00:46:48,320 --> 00:46:50,719
Speaker 1: hours is is what you want? Really? And so does

751
00:46:50,800 --> 00:46:54,640
Speaker 1: your does your program or wherever the hell just start

752
00:46:54,920 --> 00:46:58,319
Speaker 1: It just starts spitting out way points where there's a

753
00:46:58,320 --> 00:47:02,160
Speaker 1: cluster of activity. Yea, yeah in the morning. Um, you

754
00:47:02,280 --> 00:47:05,359
Speaker 1: just download the latest batch of data you run. It's

755
00:47:05,400 --> 00:47:10,040
Speaker 1: just a computer algorithm. It pulls out those, um those

756
00:47:10,080 --> 00:47:12,839
Speaker 1: clusters and then you you put them on a map

757
00:47:12,880 --> 00:47:15,000
Speaker 1: and you see, Okay, they spend time there. They spent

758
00:47:15,080 --> 00:47:17,239
Speaker 1: time there, and they spent time there, and so there's

759
00:47:17,239 --> 00:47:20,120
Speaker 1: my day. I'm gonna go out there and investigate these

760
00:47:20,160 --> 00:47:23,200
Speaker 1: and it's this is um yeah they you know us

761
00:47:23,320 --> 00:47:26,200
Speaker 1: this for cougars and and it's a common So how

762
00:47:26,200 --> 00:47:29,239
Speaker 1: many days a week to get to go do that? Well,

763
00:47:29,320 --> 00:47:31,600
Speaker 1: when I've been working on projects where that's been my

764
00:47:32,040 --> 00:47:34,279
Speaker 1: full time job for some projects, it's going to going

765
00:47:34,320 --> 00:47:38,359
Speaker 1: to kill sites just every days. Pretty lucky. That's one

766
00:47:38,400 --> 00:47:41,080
Speaker 1: of my I would trade you jobs in a second

767
00:47:41,080 --> 00:47:45,360
Speaker 1: man I'm not gonna lie. It's do you bring a

768
00:47:45,360 --> 00:47:49,680
Speaker 1: lot of that? John Colem Are you trying? Not supposed to? Um?

769
00:47:49,719 --> 00:47:52,719
Speaker 1: I got a lot of junk in my house. I've

770
00:47:52,800 --> 00:47:55,920
Speaker 1: I've I've definitely reined it in a bit. But I've

771
00:47:55,920 --> 00:47:59,600
Speaker 1: always been like that. I've always been picking up diction. Yeah,

772
00:47:59,640 --> 00:48:03,239
Speaker 1: because all that walking around you probably finding shed antlers

773
00:48:03,239 --> 00:48:07,200
Speaker 1: and deadheads and oh yeah yeah, yeah, lots of cool stuff.

774
00:48:07,280 --> 00:48:08,600
Speaker 1: So what do you when you go to all these

775
00:48:08,680 --> 00:48:10,439
Speaker 1: kill sites? What are you looking for? Where the data

776
00:48:10,440 --> 00:48:12,880
Speaker 1: points you're picking up there? Well, again that sort of

777
00:48:12,920 --> 00:48:16,680
Speaker 1: just depends on the question, but usually if you're going

778
00:48:16,680 --> 00:48:18,200
Speaker 1: to kill site, it's one of the main things you're

779
00:48:18,239 --> 00:48:20,480
Speaker 1: you're trying to figure out, is okay, what happened here? Well,

780
00:48:20,520 --> 00:48:23,960
Speaker 1: let me back up, because one thing is for for wolves.

781
00:48:24,000 --> 00:48:26,240
Speaker 1: I know, I don't remember what the rate is with cougars,

782
00:48:26,280 --> 00:48:31,360
Speaker 1: but with wolves, it's about the clusters that you go

783
00:48:31,480 --> 00:48:33,959
Speaker 1: to have a kill at them. So you might go,

784
00:48:35,280 --> 00:48:37,160
Speaker 1: you know, to lots of clusters and they were just

785
00:48:37,200 --> 00:48:39,759
Speaker 1: taking a nap. I mean, they sleep a ton, So

786
00:48:39,800 --> 00:48:43,200
Speaker 1: you end up going to a lot of betting spots um,

787
00:48:43,280 --> 00:48:45,560
Speaker 1: and so you might have just spent you know, half

788
00:48:45,600 --> 00:48:48,960
Speaker 1: your day getting there, and it's a betting spot. But

789
00:48:48,960 --> 00:48:50,880
Speaker 1: but you start to kind of put together a picture,

790
00:48:50,960 --> 00:48:52,680
Speaker 1: especially if you go in order, and you're like, okay,

791
00:48:53,400 --> 00:48:57,200
Speaker 1: m this this clusters. It's winter and it's up on

792
00:48:57,239 --> 00:49:01,920
Speaker 1: a sunny you know, south racing slope, up up on

793
00:49:02,000 --> 00:49:04,759
Speaker 1: the ridge line. Oh, I bet that's going to be

794
00:49:04,920 --> 00:49:08,640
Speaker 1: a betting area. Sure enough, you go there and it's

795
00:49:08,640 --> 00:49:11,640
Speaker 1: a betting area. Usually then you see a cluster and

796
00:49:11,680 --> 00:49:16,920
Speaker 1: it's down in some gnarly, thick looking uh you know,

797
00:49:17,280 --> 00:49:21,520
Speaker 1: canion a hell whole, and you're like, oh, that's that one.

798
00:49:22,040 --> 00:49:25,800
Speaker 1: I'm exciting about it. Oh yeah, because a lot of

799
00:49:25,840 --> 00:49:28,480
Speaker 1: times I think what happens is the deer elk are

800
00:49:28,480 --> 00:49:31,239
Speaker 1: getting chased and where they get hung up is down

801
00:49:31,239 --> 00:49:35,200
Speaker 1: in these bottoms. So for example, I was um at

802
00:49:35,200 --> 00:49:38,360
Speaker 1: a really cool killsite this winter. It was a really

803
00:49:38,400 --> 00:49:43,000
Speaker 1: deep canyon just um you know, creaked down in the bottom,

804
00:49:43,080 --> 00:49:49,160
Speaker 1: and I could reconstruct what happened just from from tracks

805
00:49:49,160 --> 00:49:52,000
Speaker 1: in the snow. Another sign and there had been a

806
00:49:52,000 --> 00:49:55,200
Speaker 1: moose that was fi on a willow um and kind

807
00:49:55,239 --> 00:49:58,640
Speaker 1: of betting and whatever, and then you could see the

808
00:49:58,640 --> 00:50:03,400
Speaker 1: wolves came down this really steep mountain side, and and

809
00:50:03,440 --> 00:50:06,760
Speaker 1: there was a short sort of chase where all tracks

810
00:50:06,800 --> 00:50:08,640
Speaker 1: came together. You could see where the moose had sort

811
00:50:08,680 --> 00:50:10,759
Speaker 1: of leapt and been up to his belly in the

812
00:50:10,800 --> 00:50:14,840
Speaker 1: snow heading down and it hits towards the bottom. And

813
00:50:14,840 --> 00:50:16,200
Speaker 1: you know how when you're snow shooting in the winter

814
00:50:16,200 --> 00:50:17,640
Speaker 1: and all of a sudden you stepped too close to

815
00:50:17,680 --> 00:50:21,360
Speaker 1: a log and you sunk into your hipped. That's what

816
00:50:21,360 --> 00:50:23,360
Speaker 1: happened to the moose. So there was a blanket of

817
00:50:23,400 --> 00:50:27,120
Speaker 1: snow from the mountain side to or you know, from

818
00:50:27,160 --> 00:50:30,239
Speaker 1: the ground to this big, huge log, and it looked

819
00:50:30,280 --> 00:50:33,440
Speaker 1: like the moose had just stepped in the wrong spot,

820
00:50:33,440 --> 00:50:38,440
Speaker 1: gotten mired, and when the wolves overtook it, and so anyway,

821
00:50:38,719 --> 00:50:42,440
Speaker 1: bloodthirsty killers. Do you think the moose knew at that

822
00:50:42,640 --> 00:50:47,880
Speaker 1: point that the jig was up, like lost a wheel?

823
00:50:48,160 --> 00:50:54,000
Speaker 1: It probably? Yeah. Do you find do you do you

824
00:50:54,080 --> 00:50:58,480
Speaker 1: find um? Do you find where they ever like surplus

825
00:50:58,640 --> 00:51:02,279
Speaker 1: killing events? Do you ever find at near searches? I've no,

826
00:51:02,440 --> 00:51:04,200
Speaker 1: I've never seen that. It's not like when like when

827
00:51:04,239 --> 00:51:06,400
Speaker 1: a mountainin gets into like a sheet pasture and just

828
00:51:09,440 --> 00:51:12,720
Speaker 1: don't know at the bedding sides. Don't you also collect

829
00:51:13,239 --> 00:51:15,279
Speaker 1: you're collecting fecal matter, right, so you can see what

830
00:51:15,320 --> 00:51:18,920
Speaker 1: they've been eating in the percentage of alpha. Right, we

831
00:51:19,040 --> 00:51:22,400
Speaker 1: got to collect on um. Yeah, I mean you can

832
00:51:22,440 --> 00:51:25,120
Speaker 1: get so much information from collecting scot. You can do diet,

833
00:51:25,160 --> 00:51:26,839
Speaker 1: you can do genetics. That's a lot of what we've

834
00:51:26,840 --> 00:51:30,200
Speaker 1: been doing, and the status, the percentage of some high status.

835
00:51:30,280 --> 00:51:33,080
Speaker 1: You can see who's getting the meat and who's well.

836
00:51:33,120 --> 00:51:35,600
Speaker 1: And a cool thing about scott is you can see

837
00:51:36,360 --> 00:51:39,800
Speaker 1: um from the type of scat. So if I'm arriving

838
00:51:39,880 --> 00:51:41,680
Speaker 1: at a place where I think you can't it's not

839
00:51:41,760 --> 00:51:45,120
Speaker 1: always easy, especially at wolf clusters to find the kill,

840
00:51:45,239 --> 00:51:47,840
Speaker 1: especially in the summertime. In the summertime, because the clusters

841
00:51:47,920 --> 00:51:50,200
Speaker 1: is too big, because they kind of go all over

842
00:51:50,200 --> 00:51:51,960
Speaker 1: the place. They'll go and eat for a while and

843
00:51:52,000 --> 00:51:56,320
Speaker 1: then they'll go sometimes the ways off in bed I

844
00:51:56,360 --> 00:51:59,880
Speaker 1: don't know, maybe I mean two. And if you're in

845
00:52:00,280 --> 00:52:03,920
Speaker 1: a thick, broken up terrain, it can be tough. And

846
00:52:04,040 --> 00:52:07,200
Speaker 1: so knowing that there's probably some amount of remains of

847
00:52:07,239 --> 00:52:15,360
Speaker 1: an animal within a wide circle round a lot of

848
00:52:15,520 --> 00:52:18,400
Speaker 1: scrounging and crawling and just looking for any sort of

849
00:52:18,480 --> 00:52:23,160
Speaker 1: sign but um. But when I arrive at one of

850
00:52:23,200 --> 00:52:25,960
Speaker 1: those clusters. And I see, I don't know what. I

851
00:52:26,120 --> 00:52:30,480
Speaker 1: call it a carcass early carcass scat. So when they're

852
00:52:30,600 --> 00:52:34,360
Speaker 1: the um, when they eat the organs first, and the

853
00:52:35,080 --> 00:52:38,400
Speaker 1: breeder male and female usually get to eat the organs

854
00:52:39,000 --> 00:52:43,560
Speaker 1: um because they're higher nutrition, and that then when they

855
00:52:43,600 --> 00:52:46,720
Speaker 1: take a ship, it's really nasty. It's black and running

856
00:52:46,760 --> 00:52:49,399
Speaker 1: because it's not bound together by hair, right, it's black

857
00:52:49,440 --> 00:52:52,080
Speaker 1: and running, and so you know, okay, that's that there's

858
00:52:52,120 --> 00:52:54,439
Speaker 1: a there's a decent chance that that's the breeder male

859
00:52:54,520 --> 00:52:57,040
Speaker 1: or female, and that's they just ate the organs. So

860
00:52:57,080 --> 00:52:59,160
Speaker 1: it's an early carcass scat. So we're getting close. And

861
00:52:59,200 --> 00:53:02,360
Speaker 1: so then I often won't get excited, like a breaking

862
00:53:02,440 --> 00:53:04,120
Speaker 1: car gets here somewhere and we just got to find it,

863
00:53:04,239 --> 00:53:06,440
Speaker 1: like it runs right through them, it goes well. They

864
00:53:06,480 --> 00:53:08,000
Speaker 1: I mean, they're usually there for a while. I don't

865
00:53:08,000 --> 00:53:11,200
Speaker 1: know how lony long enough. Yeah, human babies have similar

866
00:53:11,239 --> 00:53:13,920
Speaker 1: poops the first week of their lives. Yeah, it's even

867
00:53:13,960 --> 00:53:19,600
Speaker 1: got a special name. It's not even called. My pet

868
00:53:19,680 --> 00:53:25,719
Speaker 1: theory about um the organ the organ consumption. My pet

869
00:53:25,800 --> 00:53:28,480
Speaker 1: theory is this is that I understand that there's like

870
00:53:28,480 --> 00:53:31,640
Speaker 1: a nutritional load. Right, But I also liked the idea,

871
00:53:31,680 --> 00:53:36,759
Speaker 1: and I think I maybe invented this. Uh, if you

872
00:53:36,800 --> 00:53:40,080
Speaker 1: can eat it fast and you don't know when you're

873
00:53:40,080 --> 00:53:41,799
Speaker 1: gonna lose it because someone else is going to show

874
00:53:41,840 --> 00:53:44,920
Speaker 1: up and beat your ass, right, I think that's what

875
00:53:45,080 --> 00:53:48,160
Speaker 1: makes so you're like you can just inhale the liver,

876
00:53:48,440 --> 00:53:50,520
Speaker 1: that's correct, and then all of a sudden, then all

877
00:53:50,520 --> 00:53:52,440
Speaker 1: of a sudden, whoever else shows up, here's a grizzly.

878
00:53:52,520 --> 00:53:54,600
Speaker 1: They don't get meat drunk from eating that. That's really

879
00:53:54,719 --> 00:53:56,560
Speaker 1: that's I haven't read that, and you might be the

880
00:53:56,600 --> 00:53:58,600
Speaker 1: first one. That's a good hypothesis. You should write that

881
00:53:58,680 --> 00:54:03,480
Speaker 1: up in the senator. You watch like there's very few

882
00:54:03,560 --> 00:54:08,640
Speaker 1: animals that are comfortable on a carcass, like the amount

883
00:54:08,640 --> 00:54:11,200
Speaker 1: of energy they're expanding, whipping their head around and investigating

884
00:54:11,239 --> 00:54:14,560
Speaker 1: every sound and every smell, like it's not like, okay,

885
00:54:14,680 --> 00:54:18,080
Speaker 1: time to relax and eat. Carmen, do you ever show

886
00:54:18,160 --> 00:54:21,440
Speaker 1: up on the when you when you're on the clusters,

887
00:54:21,600 --> 00:54:23,080
Speaker 1: how often do you show up and bump them out

888
00:54:23,120 --> 00:54:25,840
Speaker 1: of there? Well, we try, really really are not to

889
00:54:25,880 --> 00:54:28,280
Speaker 1: do that, but we don't want to be affecting their behavior.

890
00:54:28,360 --> 00:54:30,839
Speaker 1: Bumping them off a kill and if especially if you're

891
00:54:30,840 --> 00:54:33,320
Speaker 1: doing a kill rate studying, need to be well, you

892
00:54:33,320 --> 00:54:35,160
Speaker 1: always need to be really careful about that. But you

893
00:54:35,200 --> 00:54:39,040
Speaker 1: wouldn't want to accidentally affect their kill rate by following

894
00:54:39,400 --> 00:54:42,239
Speaker 1: them so closely as they go around the woods that

895
00:54:42,320 --> 00:54:45,920
Speaker 1: you're bumping them. So what like when you show up,

896
00:54:46,040 --> 00:54:52,279
Speaker 1: usually how many hours have passed since they've moved on? Days? Yeah,

897
00:54:52,520 --> 00:54:56,960
Speaker 1: for and and there's for different species and states. I

898
00:54:57,000 --> 00:55:00,480
Speaker 1: would imagine there's different rules on how really you can

899
00:55:00,520 --> 00:55:03,040
Speaker 1: go in. It would never be that you'd wake up.

900
00:55:03,080 --> 00:55:04,640
Speaker 1: You would never wake up and see that there was

901
00:55:04,640 --> 00:55:09,000
Speaker 1: a cluster from midnight and run out there. And by design,

902
00:55:09,080 --> 00:55:11,160
Speaker 1: you don't do that, right by the design, it's it's

903
00:55:11,200 --> 00:55:14,680
Speaker 1: always I mean, if we didn't have to worry about

904
00:55:14,719 --> 00:55:18,520
Speaker 1: affecting their behavior, be really nice because very quickly, um

905
00:55:19,080 --> 00:55:21,440
Speaker 1: you know with scavengers and that sort of thing, the

906
00:55:21,600 --> 00:55:26,239
Speaker 1: longer it's been since the the kill event, the harder

907
00:55:26,239 --> 00:55:29,560
Speaker 1: I gets to really accurately assess what's going on, because,

908
00:55:29,960 --> 00:55:33,080
Speaker 1: um it, killside analysis is kind of one of those

909
00:55:33,120 --> 00:55:35,920
Speaker 1: things that, um, it's easy until you start learning more

910
00:55:35,920 --> 00:55:38,960
Speaker 1: and then you realize it's easy, except for when it's

911
00:55:39,000 --> 00:55:44,640
Speaker 1: not because you don't really ever know if they are

912
00:55:44,680 --> 00:55:46,640
Speaker 1: the ones that killed it. No, that's not true. Sometimes

913
00:55:46,680 --> 00:55:49,520
Speaker 1: you're you're really really confident that they killed it, your

914
00:55:49,680 --> 00:55:52,120
Speaker 1: animal of interest killed it. But there's a lot of

915
00:55:52,200 --> 00:55:54,840
Speaker 1: scavenging that goes on out there, and so there's a

916
00:55:54,880 --> 00:55:58,319
Speaker 1: lot of just weird stuff that can happen to any

917
00:55:58,360 --> 00:56:01,560
Speaker 1: animal you know, to die, and so it could always

918
00:56:01,560 --> 00:56:04,080
Speaker 1: be a scavenging of it. When you to get to

919
00:56:04,160 --> 00:56:10,160
Speaker 1: the meso predators, Um, are they often there? Mm hmmm.

920
00:56:11,239 --> 00:56:12,759
Speaker 1: Trying to think if I've ever come up on a

921
00:56:12,840 --> 00:56:19,440
Speaker 1: kill and seen I've heard a cougar once, Um, I've

922
00:56:19,480 --> 00:56:22,799
Speaker 1: seen bears coming up. I don't. I don't think I've

923
00:56:22,840 --> 00:56:24,439
Speaker 1: ever come up on a kill. I mean we're usually

924
00:56:24,520 --> 00:56:26,640
Speaker 1: kind of you know, on a snowmobile or we're crashing

925
00:56:26,719 --> 00:56:28,520
Speaker 1: through the woods stuff like that. We're not we're not

926
00:56:28,680 --> 00:56:32,040
Speaker 1: trying to sneak in especially summertime and bears are out.

927
00:56:32,480 --> 00:56:36,880
Speaker 1: So relate the relate the work though to how to

928
00:56:38,160 --> 00:56:44,520
Speaker 1: how do you then roll in the impacts on Kyle's bobcats. Okay,

929
00:56:44,600 --> 00:56:46,560
Speaker 1: so we have so it's not just so going to

930
00:56:46,640 --> 00:56:51,120
Speaker 1: kill sites for for that question, the um putting up

931
00:56:51,239 --> 00:56:53,520
Speaker 1: cameras was was one of the main goals. So we

932
00:56:53,680 --> 00:56:56,040
Speaker 1: get to a kill and and put up a trail

933
00:56:56,120 --> 00:57:00,400
Speaker 1: camera and um and leave it there at least a

934
00:57:00,480 --> 00:57:06,520
Speaker 1: month trying to capture different different interactions between uh apex

935
00:57:06,719 --> 00:57:11,000
Speaker 1: or large carnivores and music carnivores. You set it on video. No,

936
00:57:11,360 --> 00:57:14,800
Speaker 1: it takes too much battery and memory to do that.

937
00:57:15,000 --> 00:57:17,520
Speaker 1: But um, do you do like the clusters? Three three

938
00:57:17,520 --> 00:57:20,360
Speaker 1: shot clusters shot clusters? So we usually have thousands of

939
00:57:20,400 --> 00:57:23,240
Speaker 1: photos and that's that's always like a little just opening

940
00:57:23,320 --> 00:57:25,440
Speaker 1: up a treasure box. Do you have software that sorts

941
00:57:25,520 --> 00:57:28,880
Speaker 1: you all that? The project is going to use software?

942
00:57:28,960 --> 00:57:32,160
Speaker 1: But um, I mean whenever I collect a camera, I

943
00:57:32,200 --> 00:57:34,200
Speaker 1: certainly go through because I'm excited to see what's on it.

944
00:57:34,360 --> 00:57:36,680
Speaker 1: So can you get in there and look at all

945
00:57:36,760 --> 00:57:40,400
Speaker 1: those images? Yeah? Yeah, And so the other the other

946
00:57:40,480 --> 00:57:42,960
Speaker 1: part of that is that we're trapping and collering. We

947
00:57:43,080 --> 00:57:47,000
Speaker 1: were trapping and callering coyotes and bobcats so that we

948
00:57:47,120 --> 00:57:50,720
Speaker 1: could and then the wolves and cougars are also colored

949
00:57:50,760 --> 00:57:54,720
Speaker 1: in the area, and then um, they can use those

950
00:57:54,760 --> 00:57:57,840
Speaker 1: different movement patterns to see how they might be avoiding

951
00:57:57,880 --> 00:57:59,840
Speaker 1: each other on the landscape or not that sort of thing.

952
00:58:00,560 --> 00:58:04,680
Speaker 1: And then also collecting scats for genetic analysis for some

953
00:58:05,080 --> 00:58:08,200
Speaker 1: different population demographics and that sort of thing. So and

954
00:58:08,360 --> 00:58:12,920
Speaker 1: you were you were involved in putting the collars on them. Yeah, yep,

955
00:58:13,040 --> 00:58:15,720
Speaker 1: so I was in charge of So my job on

956
00:58:15,800 --> 00:58:17,439
Speaker 1: the project. I don't work for the state. I don't

957
00:58:17,480 --> 00:58:20,360
Speaker 1: work well, I work for you dub. There's um some

958
00:58:20,800 --> 00:58:25,880
Speaker 1: wonderful graduate students that are heading each section of the research,

959
00:58:26,000 --> 00:58:30,920
Speaker 1: various research projects that are under the Washington Predator Prey umbrella,

960
00:58:30,960 --> 00:58:33,080
Speaker 1: and you can, you know, look those up online. There's

961
00:58:33,080 --> 00:58:37,040
Speaker 1: a website. But um, I was hired by you dub

962
00:58:37,440 --> 00:58:43,520
Speaker 1: to run the fuel component of the Music Carnivore project. So, um,

963
00:58:45,160 --> 00:58:48,160
Speaker 1: every season, our our our main goal was in the

964
00:58:48,240 --> 00:58:52,520
Speaker 1: winter trapping bobcats and in the summer trapping coyotes. And

965
00:58:52,680 --> 00:58:56,600
Speaker 1: how are you catching the bobcats with cage traps? Yeah?

966
00:58:56,800 --> 00:59:00,600
Speaker 1: So it doesn't fly, No, it doesn't unless they are

967
00:59:00,720 --> 00:59:03,800
Speaker 1: a very desperate kyot. I think the project we've got

968
00:59:03,880 --> 00:59:06,560
Speaker 1: to study areas, and not in my study area, but

969
00:59:06,640 --> 00:59:09,200
Speaker 1: the other one. Um, we were working with some trappers,

970
00:59:09,520 --> 00:59:11,880
Speaker 1: so they caught a bobcat that they didn't want to take,

971
00:59:12,160 --> 00:59:14,680
Speaker 1: they could contact us, we go over there and put

972
00:59:14,680 --> 00:59:17,920
Speaker 1: a collar on it. Well, they contacted us once with

973
00:59:18,000 --> 00:59:22,680
Speaker 1: a kyo that had gone to a have been super hungry.

974
00:59:23,120 --> 00:59:25,240
Speaker 1: And are you guys, when you're rigging up those cage traps,

975
00:59:25,720 --> 00:59:28,520
Speaker 1: are you guys using a like an audio element, like

976
00:59:28,600 --> 00:59:30,960
Speaker 1: you put like a call, like a bird bird squawk

977
00:59:31,040 --> 00:59:33,600
Speaker 1: mechanism or anything like that near it. I have used

978
00:59:33,680 --> 00:59:38,960
Speaker 1: those before. Um, we didn't use those on this project, though.

979
00:59:39,120 --> 00:59:43,240
Speaker 1: We were We were using visual little teddy bears, and

980
00:59:44,040 --> 00:59:46,800
Speaker 1: not little teddy bears, but shiny stuff basically cat toys.

981
00:59:47,040 --> 00:59:50,520
Speaker 1: I mean seriously, I've had cameras on on traps and

982
00:59:50,720 --> 00:59:54,439
Speaker 1: I like to So I set my trap, I cover

983
00:59:54,560 --> 00:59:57,160
Speaker 1: it with branches, get it all tucked in, real nice,

984
00:59:57,320 --> 01:00:01,440
Speaker 1: and then just outside the door, I'll hang just a

985
01:00:01,520 --> 01:00:07,400
Speaker 1: little ball of shiny uh you know monofilm. No, No, sorry, Um,

986
01:00:07,560 --> 01:00:10,720
Speaker 1: what's that called bird tape? Really shiny bird tape? Yeah,

987
01:00:10,760 --> 01:00:13,360
Speaker 1: that sort of thing, basically hanging that from monofilment so

988
01:00:13,400 --> 01:00:14,880
Speaker 1: it can kind of blow in the breeze and hopefully

989
01:00:15,160 --> 01:00:19,920
Speaker 1: catch the moonlight or whatever. And I have pictures and

990
01:00:20,080 --> 01:00:23,959
Speaker 1: videos of cats playing with that, like a damn house

991
01:00:24,000 --> 01:00:26,400
Speaker 1: cat before going into the trap, and what are you

992
01:00:26,480 --> 01:00:29,400
Speaker 1: baiting the trap with order or use any meat? All

993
01:00:29,480 --> 01:00:33,040
Speaker 1: kinds of stuff we use, uh, lots of just you know,

994
01:00:33,520 --> 01:00:36,920
Speaker 1: lures and baits that you can get from fm T

995
01:00:37,080 --> 01:00:40,320
Speaker 1: fur trappers or whatever. But you guys haven't done that

996
01:00:40,360 --> 01:00:41,720
Speaker 1: because you see a lot of guys that use those

997
01:00:41,760 --> 01:00:43,800
Speaker 1: cage traps will take little stuff to animals, but get

998
01:00:43,920 --> 01:00:46,840
Speaker 1: really high quality eyes pull the pull the bad eyes

999
01:00:46,880 --> 01:00:49,800
Speaker 1: off and put good eyes on it and place. Yeah,

1000
01:00:49,880 --> 01:00:52,000
Speaker 1: now I've seen that. Um. And then well in the

1001
01:00:52,040 --> 01:00:54,280
Speaker 1: back of the trap. I usually then hang some feathers

1002
01:00:54,320 --> 01:00:55,880
Speaker 1: to kind of catch the wind too, so I use

1003
01:00:55,920 --> 01:00:59,120
Speaker 1: the visual in the trap as well. And then whatever

1004
01:00:59,200 --> 01:01:03,200
Speaker 1: smelly stuff you know, and then um, what do you

1005
01:01:03,280 --> 01:01:07,640
Speaker 1: doing to mitigate your own scent with cats? Nothing? Yeah,

1006
01:01:07,680 --> 01:01:09,520
Speaker 1: they're not. I mean you can just look at their

1007
01:01:09,560 --> 01:01:12,560
Speaker 1: skull and see they're not. They're not built for super

1008
01:01:13,200 --> 01:01:16,920
Speaker 1: super smelling like a coyotes. That's very judgmental, Yeah that is.

1009
01:01:17,520 --> 01:01:20,280
Speaker 1: But you know what they got squashed faces. You're the

1010
01:01:20,320 --> 01:01:25,280
Speaker 1: type of reads book title knows all about it. It's

1011
01:01:25,320 --> 01:01:28,840
Speaker 1: just physiology. When you're trapping cats, you're setting on signed

1012
01:01:28,960 --> 01:01:31,919
Speaker 1: Is it pretty important? My yeah, because we don't where

1013
01:01:31,960 --> 01:01:35,360
Speaker 1: we're trapping. It's not like there's a Bobcat around every corner.

1014
01:01:35,880 --> 01:01:40,320
Speaker 1: And so you can best case scenario, you see fresh sign,

1015
01:01:40,480 --> 01:01:42,720
Speaker 1: you set a trap, and they're still in the area

1016
01:01:42,760 --> 01:01:44,560
Speaker 1: for the next couple of days and happen. You know,

1017
01:01:45,000 --> 01:01:46,840
Speaker 1: to go buy your trap and detect it and go in.

1018
01:01:47,440 --> 01:01:51,520
Speaker 1: But sometimes you you see sign you set and they're

1019
01:01:51,560 --> 01:01:54,080
Speaker 1: not back for two weeks. They're cycling over in some

1020
01:01:54,200 --> 01:01:56,760
Speaker 1: other area of their their home range. We're fine that

1021
01:01:56,920 --> 01:01:59,880
Speaker 1: the bob cats have really big home ranges and made

1022
01:02:00,240 --> 01:02:05,720
Speaker 1: crazy movements. Um, it's pretty incredible. But yeah, so setting

1023
01:02:05,720 --> 01:02:09,280
Speaker 1: on sign is really important. So basically you just get

1024
01:02:09,320 --> 01:02:13,600
Speaker 1: to go out tracking and when you see something good, Yeah,

1025
01:02:13,760 --> 01:02:15,440
Speaker 1: I get the log a lot of hours out there

1026
01:02:15,480 --> 01:02:19,640
Speaker 1: wanting around. Are you by yourself mostly? Um, depends on

1027
01:02:19,720 --> 01:02:22,439
Speaker 1: the project. There's some some work that I've done where

1028
01:02:22,440 --> 01:02:26,920
Speaker 1: I'm mostly alone, um, and other's where I'm not doing this.

1029
01:02:27,080 --> 01:02:29,920
Speaker 1: We were, we were worked in teams. Yeah, and then um,

1030
01:02:30,720 --> 01:02:32,800
Speaker 1: when you run into people, are people kind of like

1031
01:02:33,360 --> 01:02:35,760
Speaker 1: curious what you're doing? Do you bother to explain it

1032
01:02:35,800 --> 01:02:37,040
Speaker 1: to them? And you try to act with you doing

1033
01:02:37,080 --> 01:02:40,479
Speaker 1: something else? No, I mean I'm yeah, No, I'm always

1034
01:02:40,520 --> 01:02:42,480
Speaker 1: happy to talk to the public if they come up

1035
01:02:42,480 --> 01:02:45,640
Speaker 1: and have questions or or whatever. And people do, and um,

1036
01:02:46,080 --> 01:02:49,560
Speaker 1: sometimes they share their stories and sometimes they're really out there.

1037
01:02:49,640 --> 01:02:52,360
Speaker 1: But I wanted Yeah, no, I definitely talked to whoever.

1038
01:02:53,600 --> 01:02:55,360
Speaker 1: And at the starty you've been working on is there

1039
01:02:56,600 --> 01:03:00,800
Speaker 1: do you feel that there was a um meaningful stuff

1040
01:03:00,840 --> 01:03:02,880
Speaker 1: came out of it Now that it's winding down, like,

1041
01:03:02,960 --> 01:03:08,320
Speaker 1: do you feel that like actionable meaningful. I'm trying to

1042
01:03:08,400 --> 01:03:11,000
Speaker 1: use the word data and my results. I was trying

1043
01:03:11,000 --> 01:03:15,320
Speaker 1: to get data. Data is great, Yeah, data data, but

1044
01:03:15,400 --> 01:03:18,000
Speaker 1: I didn't finish I didn't finish the sentence. I said data.

1045
01:03:18,360 --> 01:03:21,360
Speaker 1: You know I'm talking about that. Yeah, it's getting I

1046
01:03:21,480 --> 01:03:25,040
Speaker 1: think that this this UM, the group of grad students

1047
01:03:25,080 --> 01:03:27,560
Speaker 1: that are and and wdf W employees that are working

1048
01:03:27,600 --> 01:03:31,680
Speaker 1: on this study are I'm really excited to see there.

1049
01:03:31,760 --> 01:03:35,560
Speaker 1: There's still in an analysis phase and um, you know,

1050
01:03:35,640 --> 01:03:39,040
Speaker 1: the results are not mine this year. But I'm just

1051
01:03:39,200 --> 01:03:42,479
Speaker 1: knowing these people. I'm they're going to do a great

1052
01:03:42,560 --> 01:03:46,920
Speaker 1: job thinking about the data that they're getting and being

1053
01:03:46,960 --> 01:03:50,800
Speaker 1: really thoughtful and and throw and and answer me important questions.

1054
01:03:50,840 --> 01:03:53,720
Speaker 1: And we've got a ton of data from this project.

1055
01:03:53,960 --> 01:03:55,920
Speaker 1: So are you doing that science e thing right now

1056
01:03:56,080 --> 01:03:59,760
Speaker 1: where um, you're not saying what happened because you guys

1057
01:03:59,800 --> 01:04:02,600
Speaker 1: got go with your little process and everything. I really

1058
01:04:02,680 --> 01:04:04,919
Speaker 1: don't know. I mean, it's it's hot. You can't really

1059
01:04:05,040 --> 01:04:08,360
Speaker 1: look at first of all, I've been involved heavily and

1060
01:04:08,720 --> 01:04:11,280
Speaker 1: all the other facets of the project for the Meso

1061
01:04:11,360 --> 01:04:15,840
Speaker 1: carnivores stuff. I mean we've just been out there busting

1062
01:04:15,920 --> 01:04:19,280
Speaker 1: it and collecting and collecting data, and so without analyzing

1063
01:04:19,320 --> 01:04:21,480
Speaker 1: it or at least, you know, visualizing that data with

1064
01:04:21,560 --> 01:04:23,360
Speaker 1: graphs and stuff, it's hard to say what kind of

1065
01:04:23,400 --> 01:04:25,880
Speaker 1: trends you might be pulling out. You gotta wait for

1066
01:04:26,000 --> 01:04:29,720
Speaker 1: the paper to come out. I think Steve was trying

1067
01:04:29,760 --> 01:04:31,760
Speaker 1: to ask you, are you doing one of those government

1068
01:04:31,880 --> 01:04:35,680
Speaker 1: science things where they give you the conclusion first and

1069
01:04:35,760 --> 01:04:39,120
Speaker 1: then they hire you to get the data that. Yeah,

1070
01:04:39,200 --> 01:04:44,440
Speaker 1: I've done all that show us that wolves are made

1071
01:04:44,480 --> 01:04:48,960
Speaker 1: of rainbow. Whatever they want, that's what they are you

1072
01:04:49,040 --> 01:04:54,760
Speaker 1: to do. Yeah, no pressure, No, absolutely not. I I've

1073
01:04:55,280 --> 01:04:58,920
Speaker 1: um the integrity of the science that I've worked on,

1074
01:04:59,040 --> 01:05:02,000
Speaker 1: I think is a always been really Yeah, it's just

1075
01:05:03,160 --> 01:05:07,200
Speaker 1: good scientists just out there trying to answer questions that

1076
01:05:07,240 --> 01:05:10,040
Speaker 1: they're interested in do you feel that, um, but do

1077
01:05:10,080 --> 01:05:16,560
Speaker 1: you feel that people are like they want to demonstrate

1078
01:05:18,160 --> 01:05:22,160
Speaker 1: that that wolves will bring us these beautiful trophic cascades,

1079
01:05:23,240 --> 01:05:27,720
Speaker 1: like they want to show that. We recently talked about

1080
01:05:27,720 --> 01:05:30,840
Speaker 1: a paper someone put out that was my goodness. Here's

1081
01:05:30,880 --> 01:05:34,560
Speaker 1: one thing about wolves is they really reduce car dear

1082
01:05:34,880 --> 01:05:40,560
Speaker 1: vehicle collisions. And in reading the paper, you're like you said, man,

1083
01:05:40,720 --> 01:05:43,320
Speaker 1: here's an interesting thing to do. I should show that

1084
01:05:43,400 --> 01:05:48,840
Speaker 1: it reduces car vehicle collisions because that'd be helpful. Yeah,

1085
01:05:49,920 --> 01:05:54,360
Speaker 1: smelled like that. Yeah, I totally get what you're saying

1086
01:05:54,880 --> 01:05:57,560
Speaker 1: and getting it. And I've you know, seen that in

1087
01:05:57,680 --> 01:06:01,560
Speaker 1: papers and stuff, but my my has been I don't know,

1088
01:06:01,920 --> 01:06:07,560
Speaker 1: really solid good projects. So that was very much one

1089
01:06:07,600 --> 01:06:09,520
Speaker 1: I was going in with this assumption when I was

1090
01:06:09,560 --> 01:06:15,800
Speaker 1: reading this paper by this fellow, Jonah Kim, who looked

1091
01:06:15,960 --> 01:06:25,000
Speaker 1: at the advantages uh predators get by traveling um roads,

1092
01:06:26,040 --> 01:06:28,960
Speaker 1: uh you know, clean trails things like that. This is

1093
01:06:29,000 --> 01:06:34,000
Speaker 1: in Canada, so there's all sorts of like oil pipeline

1094
01:06:34,120 --> 01:06:36,560
Speaker 1: roads and and cut line roads and things like that.

1095
01:06:37,200 --> 01:06:41,720
Speaker 1: And so he put together the study where he looked

1096
01:06:41,760 --> 01:06:45,000
Speaker 1: at just the efficiency of travel in these areas and

1097
01:06:45,120 --> 01:06:50,480
Speaker 1: how that impacts the um pray species. And it was

1098
01:06:50,760 --> 01:06:52,640
Speaker 1: all very good stuff, but you kind of had this

1099
01:06:52,800 --> 01:06:56,520
Speaker 1: feeling that he was coming down to, so the solution

1100
01:06:56,840 --> 01:07:01,520
Speaker 1: is not killing wolves. It's make the country harder to travel,

1101
01:07:02,200 --> 01:07:05,080
Speaker 1: like putting up impediments on roads and trails that we

1102
01:07:05,240 --> 01:07:09,360
Speaker 1: make for to make life easier for us UM. And

1103
01:07:09,480 --> 01:07:11,760
Speaker 1: I was like, yeah, well yeah, But then at the

1104
01:07:11,960 --> 01:07:17,120
Speaker 1: end he's like, however, this is not, uh like this

1105
01:07:17,360 --> 01:07:21,200
Speaker 1: golden solution to a complex problem. And he laid out

1106
01:07:21,240 --> 01:07:24,360
Speaker 1: the complexity of the issue and then came down to

1107
01:07:24,520 --> 01:07:27,880
Speaker 1: saying like, and if you're in a scenario where your

1108
01:07:27,880 --> 01:07:34,520
Speaker 1: prey species are so reduced that the predator species population

1109
01:07:35,960 --> 01:07:39,000
Speaker 1: UH has a distinct advantage, this is not the only

1110
01:07:39,080 --> 01:07:41,040
Speaker 1: thing that you can do the like, there will have

1111
01:07:41,240 --> 01:07:44,280
Speaker 1: to be some sort of lethal removal on your predator population.

1112
01:07:44,480 --> 01:07:45,880
Speaker 1: So in the end, it didn't feel like you were

1113
01:07:45,920 --> 01:07:50,560
Speaker 1: reading cancer research sponsored by the tobacco company exactly. So

1114
01:07:50,880 --> 01:07:53,960
Speaker 1: that's a shout out for lead author Jonah Time. I

1115
01:07:54,040 --> 01:07:56,320
Speaker 1: hope I'm saying your name right. That was a good paper.

1116
01:08:06,280 --> 01:08:09,800
Speaker 1: So Carmen, UH, two questions for you. Two more questions

1117
01:08:09,880 --> 01:08:13,880
Speaker 1: for you, UM, talk about catching the coyotes, like how

1118
01:08:13,880 --> 01:08:16,040
Speaker 1: you catching to put a collar on them? And then

1119
01:08:16,320 --> 01:08:18,000
Speaker 1: then I'm then I need to hear what you're doing

1120
01:08:18,040 --> 01:08:22,280
Speaker 1: next now that you're doing this, um, catching coyotes. That's

1121
01:08:23,320 --> 01:08:27,400
Speaker 1: probably my favorite kind of trapping, just because of the challenge.

1122
01:08:28,000 --> 01:08:31,759
Speaker 1: It's also in a lot of ways my least favorite,

1123
01:08:31,880 --> 01:08:34,599
Speaker 1: just because of um, well, it just kind of makes

1124
01:08:34,640 --> 01:08:37,240
Speaker 1: you feel bad on a lot of days. It's like

1125
01:08:37,320 --> 01:08:39,639
Speaker 1: you can't wait to get out there and check your traps,

1126
01:08:39,720 --> 01:08:43,719
Speaker 1: but man, I don't know things can foot Hold trapping

1127
01:08:43,880 --> 01:08:46,400
Speaker 1: is just it's kind of, um, it's a little harsh.

1128
01:08:46,560 --> 01:08:49,559
Speaker 1: It's a little harsh, and so we're we are foot

1129
01:08:49,600 --> 01:08:52,800
Speaker 1: hold trapping for coyotes. It's really the only practical way

1130
01:08:52,880 --> 01:08:56,800
Speaker 1: to catch canan's because they're so smart and they're so

1131
01:08:57,000 --> 01:09:04,640
Speaker 1: wary and um and so in that regard really fascinating

1132
01:09:04,680 --> 01:09:09,240
Speaker 1: because you're just having to, um work really hard to

1133
01:09:09,360 --> 01:09:12,840
Speaker 1: get to know the animals that are in the area

1134
01:09:12,920 --> 01:09:16,519
Speaker 1: that you're trying to trap, and you never really figure

1135
01:09:16,560 --> 01:09:19,840
Speaker 1: it out. They're always, you know, just throwing something new

1136
01:09:19,920 --> 01:09:22,439
Speaker 1: at you. Um. And so it's really interesting in that way,

1137
01:09:22,640 --> 01:09:24,960
Speaker 1: just I mean, from exactly how you set your trap

1138
01:09:25,240 --> 01:09:27,760
Speaker 1: to where you put your trap to what area of

1139
01:09:27,800 --> 01:09:30,160
Speaker 1: the mountain that you're you're trapping on? You gotta there's

1140
01:09:30,240 --> 01:09:32,200
Speaker 1: just so many different variables that you're trying to trying

1141
01:09:32,240 --> 01:09:38,160
Speaker 1: to figure out, and it's so frustrating. Victor's number three

1142
01:09:38,360 --> 01:09:42,120
Speaker 1: for coil, and then we use um they like the

1143
01:09:42,200 --> 01:09:46,000
Speaker 1: laminated jaws. They've got a rubber offset jaw. Yeah, so

1144
01:09:46,240 --> 01:09:50,360
Speaker 1: I mean I could, I've could. You know, I often

1145
01:09:50,439 --> 01:09:52,600
Speaker 1: got my hand stuck in it for whatever reason, just

1146
01:09:52,760 --> 01:09:54,960
Speaker 1: not being careful and stuff, and it didn't you know,

1147
01:09:55,080 --> 01:09:57,000
Speaker 1: it doesn't feel good, that's for sure, But it's not

1148
01:09:57,120 --> 01:09:59,840
Speaker 1: like it's breaking scanner. And then you do you ang

1149
01:10:00,040 --> 01:10:01,920
Speaker 1: kurt with like an earth anchor? Or do you use

1150
01:10:02,000 --> 01:10:06,680
Speaker 1: a steak? Um? We so we'd we'd use well, we

1151
01:10:06,840 --> 01:10:10,080
Speaker 1: used lots of things, um steaks. But in our area

1152
01:10:10,320 --> 01:10:13,479
Speaker 1: it's so rocky, the soil is so bad. It's really hard.

1153
01:10:13,520 --> 01:10:17,040
Speaker 1: You see these YouTube videos of guys catching coyouts and

1154
01:10:17,040 --> 01:10:19,880
Speaker 1: they're out in you know, corn fields where every single

1155
01:10:19,960 --> 01:10:22,439
Speaker 1: rock has been picked and the ground is so soft

1156
01:10:22,520 --> 01:10:25,120
Speaker 1: and loaming, and they're just like punk punk punk, you know,

1157
01:10:25,200 --> 01:10:28,040
Speaker 1: punch in a trap and two minutes we're out there

1158
01:10:28,280 --> 01:10:31,559
Speaker 1: in you know degree whether because we're having to trap

1159
01:10:31,600 --> 01:10:33,240
Speaker 1: in the summer because you can't do it in the

1160
01:10:33,280 --> 01:10:35,080
Speaker 1: winter where we are, so you're trapping in the summer,

1161
01:10:35,520 --> 01:10:39,960
Speaker 1: which is a whole another set of um difficulty because

1162
01:10:41,000 --> 01:10:43,439
Speaker 1: because we are trapping for research and so are our

1163
01:10:43,520 --> 01:10:47,720
Speaker 1: ethical standard for how we're treating these animals is different. Right,

1164
01:10:47,760 --> 01:10:50,760
Speaker 1: We've got this professional turn it out in a healthy condition, right,

1165
01:10:50,840 --> 01:10:54,599
Speaker 1: and so we're trying to do we're trying to especially

1166
01:10:54,680 --> 01:10:57,559
Speaker 1: on this project, I wanted to really raise the bar

1167
01:10:58,000 --> 01:11:02,800
Speaker 1: on our both of our well the capture element, so

1168
01:11:03,240 --> 01:11:08,960
Speaker 1: so making it as humane as we could, which is

1169
01:11:09,000 --> 01:11:12,719
Speaker 1: difficult with foothold trapping, and then also the handling part,

1170
01:11:12,840 --> 01:11:15,160
Speaker 1: so when you actually come up to an animal in

1171
01:11:15,200 --> 01:11:18,720
Speaker 1: the trap and then drug it and and do the handling, Um,

1172
01:11:18,840 --> 01:11:23,640
Speaker 1: those can be pretty rodeo ish and there's been a

1173
01:11:23,680 --> 01:11:28,080
Speaker 1: lot of kind of just um, I don't know, cowboys

1174
01:11:28,360 --> 01:11:31,920
Speaker 1: culture around those handlings traditionally not I mean, that's not

1175
01:11:32,040 --> 01:11:35,439
Speaker 1: across the board by any means. But I think that

1176
01:11:35,680 --> 01:11:41,160
Speaker 1: that um, we're getting better at being really thoughtful about

1177
01:11:41,920 --> 01:11:45,840
Speaker 1: not only just getting our animal to live through that experience,

1178
01:11:46,120 --> 01:11:50,280
Speaker 1: but to um have it be as least stressful and

1179
01:11:50,320 --> 01:11:53,320
Speaker 1: painful for them as possible. So so we've been working

1180
01:11:53,360 --> 01:11:57,400
Speaker 1: really hard to raise the bar there um. But back

1181
01:11:57,439 --> 01:12:00,920
Speaker 1: to the different types of anchors. We so we tried

1182
01:12:01,000 --> 01:12:05,240
Speaker 1: steaks way too rocky, use earth acres, but the main

1183
01:12:05,560 --> 01:12:08,040
Speaker 1: the main thing we use is UM a grapple hook

1184
01:12:08,320 --> 01:12:12,080
Speaker 1: on a long chain which you buried down onto the trap. Yeah,

1185
01:12:12,240 --> 01:12:14,920
Speaker 1: usually or sometimes just kind of bury it in the bushes,

1186
01:12:14,960 --> 01:12:18,559
Speaker 1: under leaves and stuff behind it. But basically, what as

1187
01:12:18,600 --> 01:12:21,280
Speaker 1: you're selecting your exact trap site, there's a lot of

1188
01:12:21,320 --> 01:12:24,160
Speaker 1: things you got to think about. Aside from just is

1189
01:12:24,240 --> 01:12:26,439
Speaker 1: this a good spot to catch kyo? Is there is

1190
01:12:26,479 --> 01:12:29,080
Speaker 1: it a likely spot? You've got to think about is

1191
01:12:29,120 --> 01:12:31,479
Speaker 1: there a drop off somewhere, because they could then you know,

1192
01:12:31,640 --> 01:12:35,680
Speaker 1: drag the grapple, and the grapple could get hung up

1193
01:12:35,920 --> 01:12:39,160
Speaker 1: and then they're off off the you know, cliff dangling

1194
01:12:39,600 --> 01:12:41,400
Speaker 1: from the trap. So you're thinking about that, You're thinking

1195
01:12:41,400 --> 01:12:45,599
Speaker 1: about shade because it's summertime. UM, You're thinking about human traffic,

1196
01:12:45,720 --> 01:12:47,519
Speaker 1: is this road too busy? That sort of thing. So

1197
01:12:47,600 --> 01:12:50,479
Speaker 1: there's a lot of safety variables that have to come together.

1198
01:12:51,000 --> 01:12:53,680
Speaker 1: UM And so most of the time, what what ends

1199
01:12:53,760 --> 01:12:57,680
Speaker 1: up being the preferred um steaking method is to use

1200
01:12:57,680 --> 01:12:59,920
Speaker 1: a grapple, because then they can get off the road,

1201
01:13:00,160 --> 01:13:02,200
Speaker 1: get hung up in some shade, be a little bit

1202
01:13:02,240 --> 01:13:04,800
Speaker 1: away from from the road of people come by, whatever,

1203
01:13:05,120 --> 01:13:07,000
Speaker 1: and then you don't have some motor is freaking out

1204
01:13:07,080 --> 01:13:09,400
Speaker 1: or hurting the thing or calling the cops or whatever

1205
01:13:09,479 --> 01:13:12,280
Speaker 1: the hell exactly. And we're out there super early checking traps,

1206
01:13:12,320 --> 01:13:15,240
Speaker 1: so hopefully before people are there. But yeah, and then

1207
01:13:15,280 --> 01:13:17,200
Speaker 1: you work them up like you tranquilize them, put a

1208
01:13:17,280 --> 01:13:21,760
Speaker 1: collar on them. Yeah, take like biometric data off them. Yeah,

1209
01:13:25,400 --> 01:13:30,400
Speaker 1: take biometric data off so, um, we call it body measurements.

1210
01:13:30,600 --> 01:13:34,000
Speaker 1: But yeah, I went overboard, you went over but that's good,

1211
01:13:34,120 --> 01:13:37,640
Speaker 1: that's good. Um. Yeah, so you come up on the

1212
01:13:38,280 --> 01:13:43,720
Speaker 1: trap and um, with the grapple, it's always even more

1213
01:13:43,800 --> 01:13:46,240
Speaker 1: exciting because you sometimes you get to the trap and

1214
01:13:46,360 --> 01:13:49,720
Speaker 1: you see, oh, it's just not there. It doesn't look

1215
01:13:49,800 --> 01:13:53,360
Speaker 1: quite like I left it. And so then you're looking

1216
01:13:54,120 --> 01:13:56,360
Speaker 1: around in the bushes and it can actually be hard

1217
01:13:56,439 --> 01:13:59,280
Speaker 1: to spot the animals case they've usually just they're usually

1218
01:13:59,320 --> 01:14:02,439
Speaker 1: just frozen with fright and so you're uh, And our

1219
01:14:02,479 --> 01:14:04,320
Speaker 1: traps have a little transmitters on them, so if we

1220
01:14:04,400 --> 01:14:08,400
Speaker 1: have to, we can radio telemetry to find it. But

1221
01:14:09,000 --> 01:14:11,479
Speaker 1: usually if you just sort of follow the sign, you

1222
01:14:11,560 --> 01:14:14,439
Speaker 1: can find the animal pretty quickly and they're tangled up

1223
01:14:14,479 --> 01:14:17,960
Speaker 1: and they're um having the worst day of their life

1224
01:14:18,000 --> 01:14:22,639
Speaker 1: probably yeah. Yeah, And so we we work again really hard,

1225
01:14:22,920 --> 01:14:27,800
Speaker 1: just even with our body language and how we carry ourselves, um,

1226
01:14:28,240 --> 01:14:31,600
Speaker 1: to be as non threatening as we can be, but

1227
01:14:33,200 --> 01:14:37,040
Speaker 1: also confident. You don't want to it sounds kind of

1228
01:14:37,080 --> 01:14:40,120
Speaker 1: out there, but your body language matters in how they're

1229
01:14:40,120 --> 01:14:41,919
Speaker 1: going to perceive you, and so you want to be confident,

1230
01:14:42,040 --> 01:14:46,200
Speaker 1: but calm, you know, no big movements, certainly, no talking

1231
01:14:46,320 --> 01:14:49,240
Speaker 1: that sort of thing. Um, So keeping them as calm

1232
01:14:49,320 --> 01:14:53,519
Speaker 1: as possible, and you just um, we get um are

1233
01:14:53,600 --> 01:14:55,920
Speaker 1: drugs pulled up and we use what's called a syringe

1234
01:14:56,000 --> 01:14:57,880
Speaker 1: pole and so it's basically a syringe on the end

1235
01:14:57,880 --> 01:15:01,720
Speaker 1: of a long pole so that you can uh you know,

1236
01:15:01,840 --> 01:15:04,519
Speaker 1: from a little bit of a distance administer the drug

1237
01:15:06,200 --> 01:15:09,400
Speaker 1: and uh yeah, wait for them to go to sleep,

1238
01:15:09,479 --> 01:15:12,479
Speaker 1: and then remove them from the trap and do a

1239
01:15:12,560 --> 01:15:18,759
Speaker 1: medical check and you know, get there their vitals recording

1240
01:15:18,840 --> 01:15:21,400
Speaker 1: and start putting the collar on. When you guys get

1241
01:15:21,479 --> 01:15:23,640
Speaker 1: by catch doing that like a skunk or whatever, do

1242
01:15:23,680 --> 01:15:25,439
Speaker 1: you do you have a way you release it or

1243
01:15:25,439 --> 01:15:28,600
Speaker 1: do you do you have to drug as well. It

1244
01:15:28,840 --> 01:15:33,320
Speaker 1: depends most bycatch. I try to just release um. Skunks

1245
01:15:33,360 --> 01:15:36,240
Speaker 1: are tricky, but I have found with them again, if

1246
01:15:36,320 --> 01:15:40,880
Speaker 1: you're really slow and calm, we hold up a charp

1247
01:15:41,040 --> 01:15:44,680
Speaker 1: in front of us and just slowly, calmly, if you

1248
01:15:44,760 --> 01:15:47,439
Speaker 1: can't walk up to the skunk. And then at the

1249
01:15:47,560 --> 01:15:50,639
Speaker 1: last second, this is where it gets kind of a rodeo.

1250
01:15:50,720 --> 01:15:53,040
Speaker 1: But you you throw the charp on it and then

1251
01:15:53,080 --> 01:15:55,479
Speaker 1: grab it, and then somebody takes it off and they spray,

1252
01:15:55,760 --> 01:15:57,960
Speaker 1: and if you get any of it on you, it's

1253
01:15:58,000 --> 01:16:01,200
Speaker 1: like getting When you do the throw, he's gonna he's

1254
01:16:01,200 --> 01:16:03,960
Speaker 1: gonna call it. He's gonna yeah, yeah, yeah, yeah, And

1255
01:16:04,160 --> 01:16:07,559
Speaker 1: so you get oh. Man, I always say it smells

1256
01:16:07,760 --> 01:16:11,160
Speaker 1: like getting punched in the face. When it's that much,

1257
01:16:12,680 --> 01:16:14,920
Speaker 1: it's just the rest of your day. You just got

1258
01:16:15,000 --> 01:16:18,120
Speaker 1: a headache. And I stopped smelling it so much after

1259
01:16:18,160 --> 01:16:20,360
Speaker 1: a while, but I know other people could smell it on.

1260
01:16:20,400 --> 01:16:23,720
Speaker 1: It gives you a headache. Yeah, it's powerful. Yeah, it's

1261
01:16:23,760 --> 01:16:27,719
Speaker 1: nothing like the sweet, pleasant smell of a road kill skunk.

1262
01:16:27,840 --> 01:16:30,479
Speaker 1: You just drive by it sixty and you go, oh,

1263
01:16:31,120 --> 01:16:34,280
Speaker 1: a little skunky today. Yeah, I got I got two

1264
01:16:34,320 --> 01:16:37,479
Speaker 1: ounces of it in a jar in my fridge right now.

1265
01:16:38,160 --> 01:16:40,679
Speaker 1: But it's in a jar in a vac sealed bag,

1266
01:16:40,800 --> 01:16:44,400
Speaker 1: which is in a vac sealed bag. Is it pure? Pure?

1267
01:16:45,040 --> 01:16:47,920
Speaker 1: Pulled it out with a syringe. Oh yeah, okay, And

1268
01:16:47,960 --> 01:16:50,000
Speaker 1: so you know, it's like it looks like a cartoon

1269
01:16:50,120 --> 01:16:54,200
Speaker 1: skunk spray. It's like bright green. Yeah, yeah, that's crazy looking. Yeah,

1270
01:16:54,280 --> 01:16:58,760
Speaker 1: well it's yeah, be careful with that. Yeah, I don't know.

1271
01:16:58,800 --> 01:17:01,120
Speaker 1: I'm can use it as a joke on someone. I

1272
01:17:01,200 --> 01:17:03,880
Speaker 1: thought about injecting it into the pholstery of someone's car,

1273
01:17:05,960 --> 01:17:08,120
Speaker 1: but yeah, most like a call, do you know, I

1274
01:17:08,160 --> 01:17:13,000
Speaker 1: don't know. There's a cool uh study done on breaking

1275
01:17:13,040 --> 01:17:17,120
Speaker 1: down skunk smell, like exactly why doesn't snake? And one

1276
01:17:17,160 --> 01:17:22,120
Speaker 1: of the interesting like chemical compounds um as as, like

1277
01:17:22,240 --> 01:17:28,080
Speaker 1: the sulfur um hydrogen bonds breakdown, they actually release more

1278
01:17:28,200 --> 01:17:31,680
Speaker 1: smell and their water soluble. So the harder you try

1279
01:17:31,720 --> 01:17:34,519
Speaker 1: to wash something out, the more intense the smell gets.

1280
01:17:35,600 --> 01:17:39,360
Speaker 1: And the theory is is that is to remind whatever

1281
01:17:39,479 --> 01:17:42,720
Speaker 1: came in contact with the skunk that they do not

1282
01:17:42,880 --> 01:17:45,080
Speaker 1: want to come in contact with another skin's like less

1283
01:17:45,120 --> 01:17:50,200
Speaker 1: you forget ye yep. So it's it's a multiday process

1284
01:17:50,320 --> 01:17:55,240
Speaker 1: for whoever comes in contact. But like eight different chemical

1285
01:17:55,320 --> 01:17:58,640
Speaker 1: compounds and two of which like very very rare on

1286
01:17:58,760 --> 01:18:01,840
Speaker 1: the planet. I want to get this when you when

1287
01:18:01,880 --> 01:18:05,360
Speaker 1: you approach it with the tart, you're you're holding up.

1288
01:18:05,360 --> 01:18:07,240
Speaker 1: So so if he takes a shot at you, Yeah,

1289
01:18:07,720 --> 01:18:09,639
Speaker 1: what's the farthest you've ever had him take a shot

1290
01:18:09,680 --> 01:18:12,519
Speaker 1: at you? Not very far? They don't I don't think

1291
01:18:12,560 --> 01:18:14,720
Speaker 1: they want to waste that that spray. Give it to

1292
01:18:14,760 --> 01:18:18,880
Speaker 1: me like feet, I don't know, maybe ten ft. Yeah,

1293
01:18:19,280 --> 01:18:21,200
Speaker 1: but you've never been in a situation where you've been

1294
01:18:21,200 --> 01:18:23,439
Speaker 1: able to like try to pin his tail down, because

1295
01:18:23,479 --> 01:18:25,880
Speaker 1: that's supposed to work, right, They got to lift their

1296
01:18:25,920 --> 01:18:28,360
Speaker 1: tail to spray, is what everybody says, all the old

1297
01:18:28,439 --> 01:18:31,599
Speaker 1: old man wisdom. I mean, have you talked to anybody

1298
01:18:31,640 --> 01:18:34,280
Speaker 1: that's actually done that, because I don't see you being

1299
01:18:34,280 --> 01:18:36,320
Speaker 1: able to get close enough to pin the tail down.

1300
01:18:36,720 --> 01:18:38,040
Speaker 1: And I mean when we sew the tarp on it,

1301
01:18:38,080 --> 01:18:40,120
Speaker 1: we're trying to it's kind of chaotic because then you

1302
01:18:40,160 --> 01:18:42,320
Speaker 1: can't see it, but you're trying to pin everything down.

1303
01:18:42,520 --> 01:18:44,479
Speaker 1: But it's just it's just kind of it's just gonna

1304
01:18:44,520 --> 01:18:48,639
Speaker 1: go now, and like in fur trapper lore of old,

1305
01:18:49,439 --> 01:18:51,519
Speaker 1: it would be that if you could pull off heart

1306
01:18:51,600 --> 01:18:54,719
Speaker 1: shot with the twenty two, he's not going to spray,

1307
01:18:54,840 --> 01:18:57,760
Speaker 1: but everybody knows a brain shot he's gonna spray. But

1308
01:18:57,920 --> 01:19:00,760
Speaker 1: now guys use those like people use those big long

1309
01:19:00,880 --> 01:19:05,960
Speaker 1: poles and oh yeah, to try even to try to

1310
01:19:06,080 --> 01:19:07,960
Speaker 1: kill it, like damage Like people that are doing like

1311
01:19:08,040 --> 01:19:11,120
Speaker 1: damage control work and stuff, they give it an injection

1312
01:19:11,200 --> 01:19:13,600
Speaker 1: with a big long pole. I haven't seen that or

1313
01:19:13,720 --> 01:19:17,560
Speaker 1: done that. Yeah, it's dicey work, it is. Yeah, you

1314
01:19:17,720 --> 01:19:19,800
Speaker 1: gotta handle those guys with care. And then when you

1315
01:19:19,920 --> 01:19:22,600
Speaker 1: go home, Um, is your husband like you smell like

1316
01:19:22,760 --> 01:19:25,320
Speaker 1: us skunk? Yeah? I say you got you got a

1317
01:19:25,320 --> 01:19:28,960
Speaker 1: skunk today, didn't you. I'm pretty sure I go home

1318
01:19:29,000 --> 01:19:30,840
Speaker 1: smelling like all kinds of stuff because I've been living,

1319
01:19:31,160 --> 01:19:34,760
Speaker 1: you know, using lures and everything all day. So what's

1320
01:19:34,800 --> 01:19:37,479
Speaker 1: the most you ever walked in one day? Oh, I

1321
01:19:37,560 --> 01:19:40,160
Speaker 1: don't know how far. I don't really keep track of that.

1322
01:19:40,240 --> 01:19:45,360
Speaker 1: It's some pretty good tracks. Yeah, for work, Yeah, yeah,

1323
01:19:46,080 --> 01:19:49,160
Speaker 1: I don't know how far, especially doing wolf clusters and

1324
01:19:49,800 --> 01:19:53,920
Speaker 1: cougar clusters. You're hiking all over in the mountains, ma'am.

1325
01:19:54,040 --> 01:19:59,840
Speaker 1: Jealousy job. I like that job. UM. Okay, what's your

1326
01:19:59,840 --> 01:20:05,640
Speaker 1: new thing? Okay, so the new thing is UM is

1327
01:20:05,840 --> 01:20:08,080
Speaker 1: something we could be helpful with by promoting the business.

1328
01:20:08,479 --> 01:20:11,160
Speaker 1: I don't know, I mean we're it's it's I don't

1329
01:20:11,200 --> 01:20:13,519
Speaker 1: want to help you. I just don't know how well.

1330
01:20:13,600 --> 01:20:15,439
Speaker 1: I'll explain it what I'll explain what it is and

1331
01:20:15,479 --> 01:20:18,000
Speaker 1: then you can see. But it's UM. We're calling it

1332
01:20:18,640 --> 01:20:22,400
Speaker 1: Home Range Wildlife Research and it's a nonprofit that uh

1333
01:20:23,080 --> 01:20:27,559
Speaker 1: that we're starting, and it's UM going to be sort

1334
01:20:27,600 --> 01:20:30,560
Speaker 1: of three different prongs. So I'm in charge of the

1335
01:20:30,760 --> 01:20:34,639
Speaker 1: research components. So that will be just doing either research

1336
01:20:34,760 --> 01:20:37,160
Speaker 1: that we feel like it's important and want to do

1337
01:20:38,080 --> 01:20:43,400
Speaker 1: UM and we're really UM driven to do research is

1338
01:20:43,400 --> 01:20:49,479
Speaker 1: going to be applicable and is immediately uh needed, so

1339
01:20:50,520 --> 01:20:54,439
Speaker 1: UM not just sort of what's interesting but UM. So

1340
01:20:54,560 --> 01:20:58,479
Speaker 1: that's one component. Then a workshop component for for young

1341
01:20:58,560 --> 01:21:02,439
Speaker 1: biologists just field skills, because we have found over the years,

1342
01:21:03,240 --> 01:21:06,640
Speaker 1: you know, having UM wildlife texts come, a lot of

1343
01:21:06,720 --> 01:21:09,880
Speaker 1: them are maybe just fresh out of college and and

1344
01:21:10,000 --> 01:21:12,280
Speaker 1: maybe even grew up in the city and don't have

1345
01:21:12,520 --> 01:21:14,840
Speaker 1: those sort of basic technical skills that they need to

1346
01:21:15,439 --> 01:21:19,479
Speaker 1: a feel confident be be focused on collecting good, clean

1347
01:21:19,600 --> 01:21:24,200
Speaker 1: data and see aren't gonna be rolling for four wheelers

1348
01:21:24,240 --> 01:21:30,960
Speaker 1: and costing projects money. Um, So some workshops based around

1349
01:21:31,000 --> 01:21:34,680
Speaker 1: that and doing some you know, hopefully some tracking workshops

1350
01:21:35,479 --> 01:21:38,640
Speaker 1: animal track and sign and just various skills that that

1351
01:21:38,840 --> 01:21:41,760
Speaker 1: people might want before they start heading into the field.

1352
01:21:42,080 --> 01:21:44,840
Speaker 1: And then a community science um field because we live

1353
01:21:44,880 --> 01:21:47,639
Speaker 1: in a place where we feel like if the community

1354
01:21:47,720 --> 01:21:50,200
Speaker 1: is invested in your research, you're going to have better outcomes.

1355
01:21:50,240 --> 01:21:53,240
Speaker 1: But also we have a lot of um, you know,

1356
01:21:54,400 --> 01:21:57,040
Speaker 1: hardcore recreators in the area, and so I say there's

1357
01:21:57,080 --> 01:22:01,040
Speaker 1: somebody going out to um hike in the wilderness or whatever,

1358
01:22:01,520 --> 01:22:03,320
Speaker 1: and where we need a camera out there or something

1359
01:22:03,560 --> 01:22:07,120
Speaker 1: we can be using community science to that kind of

1360
01:22:07,160 --> 01:22:10,639
Speaker 1: community science. Yeah, yeah, yeah, And where were you guys

1361
01:22:10,640 --> 01:22:12,160
Speaker 1: out what's what's the name of the outfit? Going to

1362
01:22:12,200 --> 01:22:15,400
Speaker 1: be again Home Range Wildlife Research. Yeah, and you're going

1363
01:22:15,439 --> 01:22:19,439
Speaker 1: to operate out of where you're currently at Winthrop Winthrop Washington,

1364
01:22:20,400 --> 01:22:25,040
Speaker 1: and you'll start local there and then who knows what'll happen. Yeah,

1365
01:22:25,120 --> 01:22:27,360
Speaker 1: I imagine that will be local for for quite a

1366
01:22:27,439 --> 01:22:29,640
Speaker 1: while where we've all been working on that landscape for

1367
01:22:30,400 --> 01:22:32,600
Speaker 1: for a long time, and we're invested in it, and

1368
01:22:32,720 --> 01:22:34,560
Speaker 1: we've spent so much time in the field there that

1369
01:22:34,880 --> 01:22:39,720
Speaker 1: UM it feels like that's a really good foundation for

1370
01:22:40,400 --> 01:22:43,439
Speaker 1: for our research because UM, I think there's a lot

1371
01:22:43,520 --> 01:22:47,720
Speaker 1: of value in having scientists that are good naturalists and

1372
01:22:47,800 --> 01:22:52,400
Speaker 1: that are out there UM and and noticing changes over

1373
01:22:52,479 --> 01:22:55,640
Speaker 1: time on the landscape and picking up those patterns of

1374
01:22:56,040 --> 01:22:59,479
Speaker 1: what's going on out there. When will you get started? UM?

1375
01:22:59,680 --> 01:23:03,240
Speaker 1: We are. We're still in an early phase of figuring

1376
01:23:03,280 --> 01:23:06,760
Speaker 1: out and and UM pulling together the nonprofits so the

1377
01:23:07,000 --> 01:23:09,360
Speaker 1: just the sort of structure of it UM. But we're

1378
01:23:09,400 --> 01:23:12,840
Speaker 1: all we're starting to write curriculum and write I'm working

1379
01:23:12,840 --> 01:23:18,519
Speaker 1: on a proposal for UM links in and Wildfire project UM.

1380
01:23:18,720 --> 01:23:21,160
Speaker 1: And then we've got a community science project that's going

1381
01:23:21,200 --> 01:23:25,800
Speaker 1: to launch this this summer looking at UM natural food

1382
01:23:25,840 --> 01:23:31,240
Speaker 1: availability for for bears coupled with UH how that the

1383
01:23:31,720 --> 01:23:35,320
Speaker 1: whether there's good natural food ability or not a season,

1384
01:23:35,400 --> 01:23:40,200
Speaker 1: how that affects human bear interactions getting into trash stuff

1385
01:23:40,200 --> 01:23:42,479
Speaker 1: like that. That's cool. Yeah, and then you're gonna do

1386
01:23:42,560 --> 01:23:44,000
Speaker 1: that project I was talking about where you go and

1387
01:23:44,080 --> 01:23:46,640
Speaker 1: see if bobcats like to eat on gut piles and

1388
01:23:46,720 --> 01:23:48,920
Speaker 1: that's why you can't find them in early December, right,

1389
01:23:49,439 --> 01:23:52,080
Speaker 1: the importance of hunters the bobcats. Yeah, I won't test

1390
01:23:52,200 --> 01:23:56,559
Speaker 1: the hypothesis that you got to eat the organs quick. Yeah. Yeah,

1391
01:23:57,439 --> 01:23:59,479
Speaker 1: that's great. So with this new thing, are you gonna

1392
01:23:59,520 --> 01:24:01,439
Speaker 1: have are you to like have like a You'll you'll

1393
01:24:01,439 --> 01:24:03,639
Speaker 1: be a full time Yeah, you'll be a full time

1394
01:24:03,680 --> 01:24:10,479
Speaker 1: salaried person. Yep, that's the plan. Just took ten years. Yeah,

1395
01:24:10,840 --> 01:24:15,600
Speaker 1: here you are, ye arrived, hopefully almost forty and and

1396
01:24:15,680 --> 01:24:19,280
Speaker 1: you have some grant writing in your background. Yeah, yeah,

1397
01:24:19,360 --> 01:24:22,640
Speaker 1: we've all got Yeah, for sure that'll be Yeah. My

1398
01:24:23,000 --> 01:24:25,160
Speaker 1: question when I when I heard about this is how

1399
01:24:25,280 --> 01:24:30,040
Speaker 1: comfortable are you asking people for money? Yeah? Comfortable? No,

1400
01:24:30,360 --> 01:24:33,800
Speaker 1: not me, no, no no, but hopefully our board will

1401
01:24:33,840 --> 01:24:36,240
Speaker 1: be comfortable. You're gonna have a board. Yeah, you legally

1402
01:24:36,280 --> 01:24:39,920
Speaker 1: have to have a board as a nonprofit. Yeah. Yeah

1403
01:24:40,920 --> 01:24:46,280
Speaker 1: that's cool man. Yeah, that's great. Full time job, make

1404
01:24:46,320 --> 01:24:49,559
Speaker 1: your own job. That is the moral of the story,

1405
01:24:49,600 --> 01:24:51,920
Speaker 1: and that is I think what's going to be needing

1406
01:24:52,000 --> 01:24:54,360
Speaker 1: to happen for for wildlife Bilo just more and more

1407
01:24:54,400 --> 01:24:58,720
Speaker 1: because it's just it's the field is really flooded and

1408
01:24:59,280 --> 01:25:02,080
Speaker 1: so it's hard to get jobs, just from a competitive standpoint,

1409
01:25:02,200 --> 01:25:08,120
Speaker 1: and also, um, because there's so many people wanting to

1410
01:25:08,240 --> 01:25:11,439
Speaker 1: do that field work, there's um, well it's hard to

1411
01:25:11,439 --> 01:25:16,160
Speaker 1: get paid. Well, they'll do it for nothing, Yeah, exactly. Yeah,

1412
01:25:16,840 --> 01:25:20,080
Speaker 1: I don't know if I mean, it's just pretty intriguing. Oh.

1413
01:25:20,479 --> 01:25:23,240
Speaker 1: The folks that I worked with on the Grizz study

1414
01:25:23,240 --> 01:25:28,800
Speaker 1: there in Idaho, it was just like they created their

1415
01:25:28,840 --> 01:25:31,479
Speaker 1: own jobs and then had to recreate their lifestyles in

1416
01:25:31,640 --> 01:25:34,760
Speaker 1: order to do those jobs. And it's yeah, it's it's

1417
01:25:34,800 --> 01:25:39,240
Speaker 1: a passion passion deal for sure. It's it's not a

1418
01:25:39,600 --> 01:25:41,280
Speaker 1: it's a tough way to make a living for sure.

1419
01:25:41,439 --> 01:25:44,400
Speaker 1: So it's not a meritocracy exactly. That's just what you

1420
01:25:44,479 --> 01:25:46,800
Speaker 1: said at the beginning. But it's not at all. You

1421
01:25:46,880 --> 01:25:48,639
Speaker 1: have to have you have to come from a family

1422
01:25:48,680 --> 01:25:51,680
Speaker 1: with money, don't you, Yeah, basically, or just oh to

1423
01:25:51,760 --> 01:25:54,400
Speaker 1: be able to be able to that's interesting points can't

1424
01:25:54,439 --> 01:25:57,160
Speaker 1: do that. Yeah, it's it's I think it's being talked

1425
01:25:57,200 --> 01:25:59,920
Speaker 1: about more ever, and it's just your podcast is rich,

1426
01:26:00,040 --> 01:26:05,880
Speaker 1: are they? I'm assuming not. I know a lot of

1427
01:26:05,920 --> 01:26:08,519
Speaker 1: people who's but I mean, you know, my brothers included,

1428
01:26:08,640 --> 01:26:11,719
Speaker 1: I know a lot of people who are. We're certainly

1429
01:26:11,760 --> 01:26:15,479
Speaker 1: not rich who slugged it out and pulled it off.

1430
01:26:16,200 --> 01:26:19,360
Speaker 1: But it's like becoming a writer, you gotta commit yourself

1431
01:26:19,439 --> 01:26:21,679
Speaker 1: to spending a bunch of years living below the pot

1432
01:26:21,720 --> 01:26:24,680
Speaker 1: with like living below the poverty line and not be

1433
01:26:24,800 --> 01:26:28,960
Speaker 1: seducted by a plan B. So yeah, I think that

1434
01:26:29,120 --> 01:26:31,400
Speaker 1: that's a gravy way to do it. I had someone

1435
01:26:31,439 --> 01:26:33,920
Speaker 1: explained to me one time that like to be an

1436
01:26:33,960 --> 01:26:38,960
Speaker 1: Olympic skier. They're saying, it's it's in large measure, it's

1437
01:26:39,000 --> 01:26:42,439
Speaker 1: a function of your family's finances because either can ski

1438
01:26:42,560 --> 01:26:44,720
Speaker 1: six months a year, or you go live in New

1439
01:26:44,800 --> 01:26:46,519
Speaker 1: Zealand and you ski twelve months a year, And the

1440
01:26:46,560 --> 01:26:49,320
Speaker 1: people that can ski twelve months a year have a

1441
01:26:49,439 --> 01:26:50,960
Speaker 1: leg up on the people of the ski six and

1442
01:26:51,040 --> 01:26:53,200
Speaker 1: the people that do that are people from wealthy families.

1443
01:26:54,080 --> 01:26:57,280
Speaker 1: And it's undeniable. But I mean, I don't want to like,

1444
01:26:57,320 --> 01:26:59,920
Speaker 1: I would hate to say that point and then discredit people,

1445
01:27:00,200 --> 01:27:03,400
Speaker 1: many people that I know personally that slugged it out

1446
01:27:04,640 --> 01:27:06,639
Speaker 1: and tell us about your brother. I missed that part.

1447
01:27:06,800 --> 01:27:10,280
Speaker 1: You said something about your brother, just that they most

1448
01:27:10,320 --> 01:27:12,960
Speaker 1: certainly were not coming from a wealthy background, and and

1449
01:27:14,120 --> 01:27:17,479
Speaker 1: did it you know, starting out doing like creal surveys

1450
01:27:18,960 --> 01:27:24,440
Speaker 1: for a dollar an hour whatever. Yeah, and then eventually

1451
01:27:24,680 --> 01:27:30,040
Speaker 1: through like sheer will, sheer force of will got there,

1452
01:27:30,320 --> 01:27:34,200
Speaker 1: but it takes forever. Yeah. Yeah, and so that's that's

1453
01:27:34,240 --> 01:27:36,720
Speaker 1: kind of what is happening in wildlife for sure, And

1454
01:27:36,800 --> 01:27:40,720
Speaker 1: there are definitely people that slug it out, but um

1455
01:27:41,120 --> 01:27:42,920
Speaker 1: it does leave a lot of people out and we're

1456
01:27:42,960 --> 01:27:45,799
Speaker 1: missing out on on attracting the best and the brightest.

1457
01:27:45,960 --> 01:27:48,240
Speaker 1: So do you think you're gonna approach this from a

1458
01:27:48,479 --> 01:27:53,920
Speaker 1: project standpoint or you're just going to try to have

1459
01:27:56,200 --> 01:28:01,400
Speaker 1: a fund that people can apply for grants to. UM.

1460
01:28:03,320 --> 01:28:06,639
Speaker 1: I think we'll do some just general fundraising to start out,

1461
01:28:07,040 --> 01:28:10,000
Speaker 1: especially UM like we need to raise money to UM,

1462
01:28:10,240 --> 01:28:12,519
Speaker 1: you know, just start up costs, that sort of thing.

1463
01:28:13,040 --> 01:28:17,080
Speaker 1: But then definitely for different projects, be applying for different

1464
01:28:17,280 --> 01:28:22,719
Speaker 1: specific grants. Identify a project, try to rally some folks

1465
01:28:22,760 --> 01:28:25,800
Speaker 1: around it. Yeah, and then you guys can use your

1466
01:28:25,960 --> 01:28:29,559
Speaker 1: expertise to say why this is exactly so let project

1467
01:28:29,600 --> 01:28:32,400
Speaker 1: worth preson, right, So just sort of like for the

1468
01:28:32,479 --> 01:28:37,639
Speaker 1: benefit of all mankind, yeah, exactly, and in the wildlife, Yeah,

1469
01:28:38,800 --> 01:28:42,040
Speaker 1: I like it. Yeah, best of luck man, thank you.

1470
01:28:43,240 --> 01:28:45,439
Speaker 1: Let's know, we'd be helpful. I don't know what we

1471
01:28:45,560 --> 01:28:49,880
Speaker 1: do if something comes up. All right, exactly, Okay, we're

1472
01:28:49,920 --> 01:28:54,280
Speaker 1: gonna talk about Foxes for minutes. Everybody talk about Fox, Fox, Foxes, Fox,

1473
01:28:54,360 --> 01:28:57,120
Speaker 1: and I okay, get uh, Kathy, give us you can

1474
01:28:57,160 --> 01:28:59,880
Speaker 1: you give us like a kind of your bio, a

1475
01:29:00,160 --> 01:29:03,920
Speaker 1: quick bio. Sure. I was one of those who tried

1476
01:29:03,960 --> 01:29:06,320
Speaker 1: to leg it out. I guess. I have my undergraduate

1477
01:29:06,360 --> 01:29:11,719
Speaker 1: degrees from Missoula and my doctorate in biology from Montana

1478
01:29:11,800 --> 01:29:14,320
Speaker 1: State University. Here I was a part granger in a

1479
01:29:14,320 --> 01:29:19,400
Speaker 1: wildland firefighter for many many years did firefighting. Yeah, long time,

1480
01:29:20,000 --> 01:29:22,080
Speaker 1: and even after I finished my doctorate, I was on

1481
01:29:22,160 --> 01:29:28,720
Speaker 1: the lines hard to give it up, like like seasonal firefighting. Yes, absolutely,

1482
01:29:29,960 --> 01:29:35,920
Speaker 1: And I was just living by myself, trying to use

1483
01:29:36,040 --> 01:29:39,519
Speaker 1: my PhD, trying to find one of those just piles

1484
01:29:39,560 --> 01:29:42,880
Speaker 1: of job applications to fill out for getting a university position.

1485
01:29:42,960 --> 01:29:45,320
Speaker 1: I had started at the University of Montana, but it

1486
01:29:45,479 --> 01:29:48,040
Speaker 1: was a part time. It was a contract, you know,

1487
01:29:48,120 --> 01:29:49,720
Speaker 1: like a post doc. In fact, it might have been

1488
01:29:49,720 --> 01:29:51,719
Speaker 1: called a post doc, but they called me it should

1489
01:29:51,720 --> 01:29:53,160
Speaker 1: have been called a post doc. I guess they called

1490
01:29:53,160 --> 01:29:57,000
Speaker 1: me an assistant professor. And I was looking for professor ships.

1491
01:29:57,040 --> 01:30:00,280
Speaker 1: And then five did you do graduate work in bald eagles? Yeah?

1492
01:30:00,320 --> 01:30:02,040
Speaker 1: I did. My doctor was in bald egos. That's right.

1493
01:30:02,120 --> 01:30:07,719
Speaker 1: What at looking at? So throughout this term evolutionarily significant units,

1494
01:30:07,880 --> 01:30:11,439
Speaker 1: which is the scientific term for species, what we casually

1495
01:30:11,520 --> 01:30:16,960
Speaker 1: call species, but species is right, it's not a dynamic process.

1496
01:30:17,280 --> 01:30:22,120
Speaker 1: Species are constantly changing, their hybridizing, and they're moving, they're becoming.

1497
01:30:22,760 --> 01:30:24,880
Speaker 1: They're on a pathway, they're on an evolution nine pathway.

1498
01:30:24,920 --> 01:30:28,519
Speaker 1: So technically they're The Endangered Species Act is about the

1499
01:30:28,600 --> 01:30:33,360
Speaker 1: species are defined in that Act as evolutionarily significant units.

1500
01:30:33,439 --> 01:30:36,439
Speaker 1: But nobody wanted to call the Act anything that had

1501
01:30:36,439 --> 01:30:39,880
Speaker 1: the word evolution in it for obvious reasons. Right, all

1502
01:30:40,160 --> 01:30:43,520
Speaker 1: led up, rowled up even today, and also it sounds complicated,

1503
01:30:44,080 --> 01:30:48,960
Speaker 1: but the evolutionary significant unit is how species are defined

1504
01:30:48,960 --> 01:30:52,120
Speaker 1: by scientists. So it's looking at the pathways of the

1505
01:30:52,160 --> 01:30:55,200
Speaker 1: bald eagles and is there just one species of bald

1506
01:30:55,240 --> 01:30:57,560
Speaker 1: eagles in North America? And no, of course there's not.

1507
01:30:57,720 --> 01:31:00,759
Speaker 1: Because they mate according to size, so you can figure

1508
01:31:00,760 --> 01:31:02,640
Speaker 1: and you know that a female won't mate with a

1509
01:31:02,720 --> 01:31:04,960
Speaker 1: larger male. I'm looking at Carmen because she knows this,

1510
01:31:05,080 --> 01:31:08,960
Speaker 1: but maybe you know. I've heard that, but I've never

1511
01:31:09,040 --> 01:31:14,439
Speaker 1: understood the signal males from Alaska, so a female and

1512
01:31:14,640 --> 01:31:19,479
Speaker 1: smaller in the south West like Arizona. So a female

1513
01:31:19,600 --> 01:31:22,400
Speaker 1: from Arizona is not going to be she doesn't have

1514
01:31:22,479 --> 01:31:25,360
Speaker 1: the opportunity to mate everywhere in North America because those

1515
01:31:25,400 --> 01:31:27,400
Speaker 1: boys up north are going to be larger than her,

1516
01:31:27,439 --> 01:31:29,320
Speaker 1: and she will not mate with a larger male. So

1517
01:31:29,479 --> 01:31:31,799
Speaker 1: they are on a separate pathway. Of course, the size,

1518
01:31:31,880 --> 01:31:34,960
Speaker 1: So size does make a difference. You guys already knew that,

1519
01:31:35,120 --> 01:31:37,040
Speaker 1: but we've been telling you it doesn't. But it does.

1520
01:31:37,160 --> 01:31:40,719
Speaker 1: And so females absolutely choose their mates based on size.

1521
01:31:40,760 --> 01:31:45,760
Speaker 1: And if the sizes are separating distinctively, then then yeah,

1522
01:31:45,800 --> 01:31:49,120
Speaker 1: there's a point where they crossed, like a threshold of incompatibility, correct,

1523
01:31:49,320 --> 01:31:52,000
Speaker 1: and then they will they will eventually. Then eventually, if

1524
01:31:52,000 --> 01:31:53,840
Speaker 1: you took one from Arizona, if you took a female

1525
01:31:53,840 --> 01:31:56,240
Speaker 1: from Arizona and put her in Southeast Alaska, she might

1526
01:31:56,320 --> 01:32:00,599
Speaker 1: just she might never reproduce. Yeah, that's right, just Aaron, huh,

1527
01:32:01,040 --> 01:32:03,360
Speaker 1: just because the size differences, she's not gonna make Yep,

1528
01:32:03,479 --> 01:32:05,920
Speaker 1: that's right, that's right, that's right. So she doesn't want to.

1529
01:32:05,960 --> 01:32:08,320
Speaker 1: You notice that's true of all the hawks. You see

1530
01:32:08,360 --> 01:32:09,960
Speaker 1: hawks all the time here. You're probably I don't know,

1531
01:32:10,200 --> 01:32:12,559
Speaker 1: I didn't know, you didn't haven't noticed the size differences.

1532
01:32:12,680 --> 01:32:16,760
Speaker 1: So it's like falcons. You've noticed that the female is

1533
01:32:16,880 --> 01:32:18,479
Speaker 1: much bigger than the male. And then when you start

1534
01:32:18,520 --> 01:32:21,519
Speaker 1: looking at hawks, like red tails of females bigger but

1535
01:32:21,640 --> 01:32:23,599
Speaker 1: not much bigger, and eagles so a little bit closer.

1536
01:32:23,680 --> 01:32:27,200
Speaker 1: But the more ferocious of a hunter they are as

1537
01:32:27,280 --> 01:32:31,879
Speaker 1: a bird of prey, the greater the differences size difference

1538
01:32:31,920 --> 01:32:34,920
Speaker 1: between the sexes. We need your hypothesis on that because

1539
01:32:35,400 --> 01:32:37,679
Speaker 1: scientists don't really know the reason for that, and there's

1540
01:32:37,680 --> 01:32:42,120
Speaker 1: a lot of hypotheses. But eagles are understand that. So

1541
01:32:42,200 --> 01:32:45,320
Speaker 1: eagles are a little bit probably the more ferocious. Certain

1542
01:32:45,520 --> 01:32:48,560
Speaker 1: So what's the most ferocious bird of prey that you

1543
01:32:48,640 --> 01:32:50,960
Speaker 1: can think of? The ones that really go after meat

1544
01:32:51,160 --> 01:32:55,719
Speaker 1: versus just dead stuff on, yes, exactly, the falcons, they're

1545
01:32:55,800 --> 01:32:58,479
Speaker 1: just only going to eat meat, live things, fast things,

1546
01:32:58,600 --> 01:33:03,479
Speaker 1: big things. So golden eagles, falcons, they have a huge

1547
01:33:04,320 --> 01:33:08,200
Speaker 1: size dimorphism diameting two and morph meaning size. So there's

1548
01:33:08,240 --> 01:33:10,200
Speaker 1: two different sizes, one for the males and one for

1549
01:33:10,240 --> 01:33:14,240
Speaker 1: the females. Humans are dimorphic. Males are bigger than females.

1550
01:33:14,920 --> 01:33:18,040
Speaker 1: Because humans, the males are bigger than females, and because

1551
01:33:18,120 --> 01:33:21,000
Speaker 1: scientists tend to be humans. We look at the world

1552
01:33:21,200 --> 01:33:24,400
Speaker 1: human centric, and when animals have the opposite, so that

1553
01:33:24,520 --> 01:33:26,720
Speaker 1: the females are bigger than the males, we call that

1554
01:33:26,920 --> 01:33:32,080
Speaker 1: reverse dimorphism. So the bird of prey have a reverse

1555
01:33:32,520 --> 01:33:36,439
Speaker 1: sexual dimorphism. Females are bigger than the males. In humans,

1556
01:33:36,520 --> 01:33:39,280
Speaker 1: males are beta than Have you ever read that Neanderthals

1557
01:33:39,320 --> 01:33:42,960
Speaker 1: didn't have sexual dimorphs as much sexual dimorphisms as we did,

1558
01:33:43,600 --> 01:33:46,960
Speaker 1: that they were like, oh I didn't. But I am

1559
01:33:47,360 --> 01:33:53,520
Speaker 1: reading and shocked at how much we are prejudiced against Neanderthals.

1560
01:33:53,600 --> 01:33:56,360
Speaker 1: And you know there was a time they were just

1561
01:33:56,920 --> 01:33:59,800
Speaker 1: I mean just data just came out a week ago

1562
01:34:00,080 --> 01:34:02,880
Speaker 1: showing that all those things we said about them not

1563
01:34:03,160 --> 01:34:05,599
Speaker 1: engaging in art and not having a sense of a statics,

1564
01:34:05,680 --> 01:34:08,599
Speaker 1: that's all just crap. I joked, We're gonna someday soon

1565
01:34:08,680 --> 01:34:12,000
Speaker 1: find out that they had laptops. They keep getting like,

1566
01:34:12,360 --> 01:34:14,360
Speaker 1: they keep getting it, they keep getting better and better

1567
01:34:14,479 --> 01:34:18,880
Speaker 1: every every day. It's like out Neanderthals had bicycles. It's

1568
01:34:18,920 --> 01:34:20,760
Speaker 1: like every day. It's like, oh they were into art,

1569
01:34:20,840 --> 01:34:24,000
Speaker 1: Oh they were poets. Yeah right, you are right, but

1570
01:34:24,080 --> 01:34:27,680
Speaker 1: they they hung out in Europe for six hundred thousand years. Man,

1571
01:34:27,800 --> 01:34:31,960
Speaker 1: like everybody's like older dumb. It's like, dude, they had

1572
01:34:32,000 --> 01:34:38,640
Speaker 1: a long run. They were so diverse. Prejudice against off

1573
01:34:38,680 --> 01:34:43,080
Speaker 1: the land in every way imaginable. That's right. So clam

1574
01:34:43,240 --> 01:34:47,599
Speaker 1: diving exactly, the Neanderthals with swimmers here, that's how much

1575
01:34:47,640 --> 01:34:51,600
Speaker 1: time they spent the really advanced. Just because they're extinct

1576
01:34:51,720 --> 01:34:54,200
Speaker 1: doesn't mean I mean, I'm totally with you. I'm glad

1577
01:34:54,280 --> 01:34:56,439
Speaker 1: you think that, because you're right that people thought they

1578
01:34:56,479 --> 01:34:59,120
Speaker 1: were just a dumb mass caveman because they're Neanderthals, and

1579
01:34:59,200 --> 01:35:02,439
Speaker 1: we use it as an insult, but it's really they

1580
01:35:02,760 --> 01:35:07,479
Speaker 1: like European people, but Americans maybe, I know my European

1581
01:35:07,520 --> 01:35:10,519
Speaker 1: graduate students didn't think Neandertal was an insult, especially if

1582
01:35:10,520 --> 01:35:13,760
Speaker 1: they had more respect for him. Well, because they're named

1583
01:35:13,760 --> 01:35:16,080
Speaker 1: after the neander Valley, so that's where the first and

1584
01:35:16,120 --> 01:35:17,920
Speaker 1: they were kicking around in the same round. To them,

1585
01:35:18,000 --> 01:35:21,360
Speaker 1: it was like it was like their ancestors. Yeah, yeah,

1586
01:35:21,600 --> 01:35:24,360
Speaker 1: that's right. To get back to the bird thing a

1587
01:35:24,360 --> 01:35:27,320
Speaker 1: little bit because it's cool. I want your hypothesis Sundays.

1588
01:35:27,360 --> 01:35:31,840
Speaker 1: I have one, but I'll make sure i'm getting it right. Um, Okay,

1589
01:35:32,280 --> 01:35:34,040
Speaker 1: as you go up, So if you go look at

1590
01:35:35,760 --> 01:35:37,800
Speaker 1: what's in't that family? That would be like a like

1591
01:35:37,960 --> 01:35:42,280
Speaker 1: a not for give me a not. Eagles are the

1592
01:35:42,439 --> 01:35:46,120
Speaker 1: least ferocious ones. They can survive just scavenging technical I mean,

1593
01:35:46,200 --> 01:35:48,160
Speaker 1: just hang out at the local look at the look

1594
01:35:48,160 --> 01:35:49,920
Speaker 1: at the salmon that they eat. I mean they're not

1595
01:35:50,000 --> 01:35:52,439
Speaker 1: really fishing like an osprey very much. I mean they're

1596
01:35:52,560 --> 01:35:55,040
Speaker 1: they're getting the salmon that are sort of slow moving

1597
01:35:55,200 --> 01:35:58,479
Speaker 1: dead after they've already spawned their bright red they're on

1598
01:35:58,560 --> 01:36:00,960
Speaker 1: the surface. So they're not for as hunters, so they

1599
01:36:01,040 --> 01:36:06,320
Speaker 1: have less sexual Maybe define like ferocious because it seems

1600
01:36:06,320 --> 01:36:08,880
Speaker 1: like it's it's no no, But define it as like

1601
01:36:09,240 --> 01:36:11,680
Speaker 1: as the way you're using it's kind of coming out

1602
01:36:11,760 --> 01:36:15,360
Speaker 1: like as in the more energy they'll expand to get food. Right, Oh,

1603
01:36:16,360 --> 01:36:19,679
Speaker 1: I don't know about energy, but I mean they're taking

1604
01:36:19,800 --> 01:36:25,560
Speaker 1: the most difficult targets. So peregrine and eagles are real hunters. Technically,

1605
01:36:25,600 --> 01:36:28,360
Speaker 1: a bald eagle as a scavenger, they don't even have

1606
01:36:28,560 --> 01:36:32,640
Speaker 1: to physiologically, they're not obligated by their genetics or by

1607
01:36:32,680 --> 01:36:35,439
Speaker 1: their physiology to hunt. They can just like you did.

1608
01:36:35,479 --> 01:36:37,640
Speaker 1: You say, hang out at the dump. That's right. They

1609
01:36:37,680 --> 01:36:39,839
Speaker 1: can hang out at the sitting next to the stream

1610
01:36:39,880 --> 01:36:43,800
Speaker 1: and eat the dead salmon. That's right. Is going to

1611
01:36:43,880 --> 01:36:46,000
Speaker 1: catch live fish, Yeah, and then they wait till the

1612
01:36:46,040 --> 01:36:48,120
Speaker 1: osprey brings it to its nest, and then the bald

1613
01:36:48,120 --> 01:36:51,040
Speaker 1: eagle steals it from the osprey nest when it's already dead.

1614
01:36:51,200 --> 01:36:54,559
Speaker 1: That's what. Yeah, you know, Ben Franklin didn't like eagles

1615
01:36:55,120 --> 01:36:58,800
Speaker 1: because these guys are really good naturalist. He knew. I

1616
01:36:58,920 --> 01:37:01,720
Speaker 1: read the letter that he wrote to his daughter. I

1617
01:37:01,840 --> 01:37:03,599
Speaker 1: wrote to the museum there and asked him if they

1618
01:37:03,600 --> 01:37:05,080
Speaker 1: would send me a copy of because I was tired

1619
01:37:05,120 --> 01:37:06,840
Speaker 1: of just hearing the rumors about it, and I wanted

1620
01:37:06,880 --> 01:37:10,120
Speaker 1: to read the whole thing, not take it out of context. Yeah.

1621
01:37:10,160 --> 01:37:14,240
Speaker 1: So he was kind of joking, but he was also serious.

1622
01:37:14,360 --> 01:37:16,280
Speaker 1: I mean, he was sort of joking about the turkey,

1623
01:37:16,360 --> 01:37:19,920
Speaker 1: but he he wanted he did believe, and he knew

1624
01:37:21,000 --> 01:37:24,080
Speaker 1: that bald eagle's scavengers. I mean, he knew that although

1625
01:37:24,080 --> 01:37:27,360
Speaker 1: it was beautiful, it was not a bird that was

1626
01:37:27,479 --> 01:37:30,160
Speaker 1: really capable of hunting. It wasn't really a bird that

1627
01:37:30,920 --> 01:37:33,439
Speaker 1: if we wanted to use a symbol of a really

1628
01:37:33,560 --> 01:37:36,800
Speaker 1: fierce nation of people, it was a good symbol if

1629
01:37:36,840 --> 01:37:39,320
Speaker 1: you were going to like head people across to the

1630
01:37:39,479 --> 01:37:42,639
Speaker 1: west Land that you didn't own but belonged to Native

1631
01:37:42,640 --> 01:37:45,639
Speaker 1: American nations and you were going to steal their land,

1632
01:37:46,400 --> 01:37:49,800
Speaker 1: then the bald eagle was a great, great symbol for that.

1633
01:37:50,600 --> 01:37:52,640
Speaker 1: And that's actually what the I sis did, right, So

1634
01:37:52,760 --> 01:37:54,720
Speaker 1: bald eagle ended up being good, but they didn't want

1635
01:37:54,760 --> 01:37:56,360
Speaker 1: it to be that. They thought it was going to

1636
01:37:56,439 --> 01:37:59,880
Speaker 1: be like the big fierce hunter, the noble. It's an

1637
01:38:00,040 --> 01:38:04,400
Speaker 1: real noble. Old eagles are, I guess more noble you've

1638
01:38:04,439 --> 01:38:06,439
Speaker 1: ever tried to mess with one. I think bald eagles

1639
01:38:06,520 --> 01:38:08,720
Speaker 1: got a lot of their most recent cache because they

1640
01:38:08,800 --> 01:38:10,920
Speaker 1: were it was for such a long time, it was

1641
01:38:11,040 --> 01:38:13,840
Speaker 1: rare to see one. And I think that's gonna wear

1642
01:38:13,920 --> 01:38:17,160
Speaker 1: off now. And I think that you know, because growing

1643
01:38:17,240 --> 01:38:20,160
Speaker 1: up and be like you know, so it's so sorry,

1644
01:38:21,280 --> 01:38:25,360
Speaker 1: it's like tree right there every day for the last

1645
01:38:25,479 --> 01:38:27,519
Speaker 1: what ten twenty years? Yeah, I think that it's like

1646
01:38:27,640 --> 01:38:30,920
Speaker 1: it's cache. It's cache will be diminished by its success.

1647
01:38:31,040 --> 01:38:35,360
Speaker 1: There's a bald eagle that lives essentially right here, right

1648
01:38:35,400 --> 01:38:39,280
Speaker 1: here at the office. Like it goes from. We have

1649
01:38:39,400 --> 01:38:42,679
Speaker 1: a little cut hay field here just to the west

1650
01:38:42,760 --> 01:38:45,479
Speaker 1: of US, and there's some power poles right there, and

1651
01:38:45,600 --> 01:38:47,599
Speaker 1: it'll sit on those power poles. And then I'll jump

1652
01:38:47,640 --> 01:38:51,080
Speaker 1: across to the north side of the interstate and sit

1653
01:38:51,240 --> 01:38:56,080
Speaker 1: right there too. Yeah, it's I would assume, yeah, it keeps,

1654
01:38:56,320 --> 01:38:58,560
Speaker 1: but that you know, the speaking of their caches. So

1655
01:38:58,720 --> 01:39:01,479
Speaker 1: in the seventies when they got covered by DDT, the

1656
01:39:01,560 --> 01:39:04,160
Speaker 1: United States and a lot of nonprofits, they spent so

1657
01:39:04,320 --> 01:39:08,720
Speaker 1: much money. They're so trying to help the bird recuperate.

1658
01:39:08,800 --> 01:39:11,360
Speaker 1: There are so many graduate students in this country that

1659
01:39:11,680 --> 01:39:13,800
Speaker 1: you know, we're just like this huge club. We belong

1660
01:39:13,880 --> 01:39:15,840
Speaker 1: to people who got their doctor. It's working on bald

1661
01:39:15,880 --> 01:39:19,720
Speaker 1: eagle because endless a pot of money to work on

1662
01:39:19,920 --> 01:39:23,240
Speaker 1: bald eagles endless, and the osprey got like nothing, and

1663
01:39:23,280 --> 01:39:25,880
Speaker 1: they ended up recovering faster anyway. I mean, the the

1664
01:39:26,000 --> 01:39:29,920
Speaker 1: osprey is just really a well suited bird for this country.

1665
01:39:30,000 --> 01:39:32,400
Speaker 1: I mean, they're amazing fisherman. I mean, they are just

1666
01:39:32,680 --> 01:39:37,719
Speaker 1: amazing fishermen. They're talented birds, and they have really great

1667
01:39:37,800 --> 01:39:40,599
Speaker 1: common sense. I mean they don't waste their time fighting

1668
01:39:41,000 --> 01:39:43,519
Speaker 1: with a big a bird that's much bigger than them.

1669
01:39:43,800 --> 01:39:46,760
Speaker 1: If the bald eago wants the fish, baldigo can get

1670
01:39:46,760 --> 01:39:48,639
Speaker 1: the fish. The ospity just goes and gets another fish.

1671
01:39:48,880 --> 01:39:51,439
Speaker 1: I mean, it's easier to just go there. Just that talented,

1672
01:39:51,720 --> 01:39:54,400
Speaker 1: they'll just go get another fish rather than fight over

1673
01:39:55,120 --> 01:39:57,680
Speaker 1: Like you see all the birds fighting at carcasses, but

1674
01:39:57,800 --> 01:40:00,000
Speaker 1: osprey don't hang out of carcasses. They're like their own

1675
01:40:00,040 --> 01:40:02,120
Speaker 1: the ones that fish that well, So they just fish.

1676
01:40:02,360 --> 01:40:05,080
Speaker 1: They've done really really well in this country, and and

1677
01:40:05,240 --> 01:40:08,800
Speaker 1: they don't eat trash or scavenge like and they have

1678
01:40:09,280 --> 01:40:14,719
Speaker 1: high sexual dimorphism or how Yeah, they have a degree

1679
01:40:14,720 --> 01:40:19,400
Speaker 1: of sexual dimorphism. That's right, but it eagles still will have. Uh.

1680
01:40:20,280 --> 01:40:22,960
Speaker 1: I think eagles have a little bit more. Even osprea

1681
01:40:23,000 --> 01:40:26,400
Speaker 1: are only eating fish of course, and not chasing down mammals.

1682
01:40:26,479 --> 01:40:28,760
Speaker 1: So the ones that are chasing down mammals and big

1683
01:40:28,840 --> 01:40:31,160
Speaker 1: mammals and golden eagle will take a deer. I mean,

1684
01:40:31,200 --> 01:40:34,240
Speaker 1: you've certainly seen them chasing after I've seen them chasing

1685
01:40:34,320 --> 01:40:37,200
Speaker 1: after deer. They chase me, and but I'm not quite

1686
01:40:37,240 --> 01:40:41,160
Speaker 1: as all the time they hate me um, So they

1687
01:40:41,240 --> 01:40:43,439
Speaker 1: have a lot of sexual dimorphism. But you never noticed

1688
01:40:43,479 --> 01:40:46,040
Speaker 1: that the females were always bigger than the males. I've

1689
01:40:46,120 --> 01:40:48,880
Speaker 1: heard that, but no, I haven't noticed. And the first

1690
01:40:49,360 --> 01:40:50,920
Speaker 1: I think, if I was looking at him in a nest,

1691
01:40:50,920 --> 01:40:52,240
Speaker 1: I wouldn't be able to tell you who is who.

1692
01:40:52,920 --> 01:40:55,800
Speaker 1: Probably my problem. But because they don't have they don't

1693
01:40:55,840 --> 01:40:59,760
Speaker 1: have the remarkable differences in coloration that like most birds

1694
01:40:59,760 --> 01:41:01,800
Speaker 1: would you most birds that you know that there's a

1695
01:41:01,840 --> 01:41:04,320
Speaker 1: male and females because they have different colors and they're

1696
01:41:04,320 --> 01:41:06,920
Speaker 1: the same size. So it's good. You're looking at some

1697
01:41:07,040 --> 01:41:10,320
Speaker 1: English sparrow eating your crumbs from your scone underneath the

1698
01:41:10,360 --> 01:41:13,120
Speaker 1: table at the cafe or whatever. He's got a big

1699
01:41:13,160 --> 01:41:16,320
Speaker 1: black throat patch. You're like, that's the male. But but

1700
01:41:16,360 --> 01:41:18,720
Speaker 1: I'm not looking at size, right, because they're just looking

1701
01:41:18,720 --> 01:41:21,280
Speaker 1: at coloration at tweet birds are pretty much like the

1702
01:41:21,360 --> 01:41:24,200
Speaker 1: most extreme version being like a pheasant, right, like everybody

1703
01:41:24,240 --> 01:41:25,840
Speaker 1: on the planet can tell you a male peasant from

1704
01:41:25,920 --> 01:41:29,000
Speaker 1: female peasant, well by coloration. If you're hunting at least,

1705
01:41:29,160 --> 01:41:31,479
Speaker 1: we hope you know that. You know what I'm saying.

1706
01:41:31,520 --> 01:41:34,080
Speaker 1: It's like it's not color. That's true. I hadn't. I've

1707
01:41:34,120 --> 01:41:36,600
Speaker 1: forgotten that because because I don't spend a lot of

1708
01:41:36,640 --> 01:41:39,000
Speaker 1: time looking at tweete birds, because there's so many hawks

1709
01:41:39,040 --> 01:41:40,519
Speaker 1: where I live, and there's not a lot of little

1710
01:41:40,560 --> 01:41:43,040
Speaker 1: birds around very long. But blue birds come in. But

1711
01:41:43,120 --> 01:41:45,519
Speaker 1: then the castrels clean them up boom boom boom instantly,

1712
01:41:45,680 --> 01:41:48,759
Speaker 1: which is so much fun to watch. Oh yeah, incredib

1713
01:41:48,800 --> 01:41:52,200
Speaker 1: castals are so amazing, aren't they. Yeah? Yeah, But I

1714
01:41:52,240 --> 01:41:54,639
Speaker 1: don't put out bird feeders or anything to attract birds

1715
01:41:54,680 --> 01:41:56,360
Speaker 1: to come there, so that because you just learn them

1716
01:41:56,360 --> 01:42:01,479
Speaker 1: into their desks, learn them into their tractions. You know.

1717
01:42:01,760 --> 01:42:06,719
Speaker 1: I gotta email the other week talking about big bird seed,

1718
01:42:07,120 --> 01:42:10,320
Speaker 1: like you know, like big pharma and how big bird

1719
01:42:10,439 --> 01:42:15,240
Speaker 1: seed big the big birds seeds in conjunction with Autobahn

1720
01:42:16,200 --> 01:42:21,000
Speaker 1: to keep the perpetuation of feeding birds out there, even

1721
01:42:21,040 --> 01:42:29,040
Speaker 1: though it's it's providing this endless death cycle. Don't even

1722
01:42:29,760 --> 01:42:32,240
Speaker 1: Bozeman anymore. You must know that even when I was

1723
01:42:32,240 --> 01:42:35,719
Speaker 1: a grad student here we get a great what I'm saying,

1724
01:42:35,800 --> 01:42:37,479
Speaker 1: but I get a lot of value. We have a

1725
01:42:37,520 --> 01:42:39,880
Speaker 1: little bird, We have a modest little bird feeder way

1726
01:42:40,000 --> 01:42:42,640
Speaker 1: high up in the air, so it's not adding to

1727
01:42:42,680 --> 01:42:49,160
Speaker 1: the bear problem. And whatever in My children get a

1728
01:42:49,240 --> 01:42:52,080
Speaker 1: tremendous amount of We get a lot of education opportunities.

1729
01:42:52,240 --> 01:42:55,800
Speaker 1: We keep a running list. We keep a running list

1730
01:42:55,840 --> 01:42:58,240
Speaker 1: that we constantly update of what we see in our yard,

1731
01:42:58,439 --> 01:43:01,519
Speaker 1: see or here from our yard. So there's things on

1732
01:43:01,600 --> 01:43:03,000
Speaker 1: the list that we've never seen what we heard it

1733
01:43:03,040 --> 01:43:05,840
Speaker 1: from the yard. And I'll give up my bird feeder

1734
01:43:05,840 --> 01:43:08,960
Speaker 1: when they pry it for my cold had hands change.

1735
01:43:10,320 --> 01:43:12,920
Speaker 1: So this winter the modest little bird feeder. You look

1736
01:43:12,960 --> 01:43:16,479
Speaker 1: at your modest little bird feeder, and you can tell me,

1737
01:43:16,800 --> 01:43:20,000
Speaker 1: or you can tell Carmen about the hawks that should

1738
01:43:20,080 --> 01:43:22,760
Speaker 1: be in Florida for the winter but decided not to

1739
01:43:22,920 --> 01:43:25,760
Speaker 1: go because they're hanging out at your bird feet. Are

1740
01:43:26,040 --> 01:43:28,160
Speaker 1: they're not at my bird feeder? Are you sure you're

1741
01:43:28,200 --> 01:43:30,280
Speaker 1: not seeing red tails that didn't migrate, Well, they're on

1742
01:43:30,360 --> 01:43:32,280
Speaker 1: my list, but that's not what they're doing. They're riding

1743
01:43:32,320 --> 01:43:34,280
Speaker 1: the thermals on the hill behin they're supposed to have

1744
01:43:34,400 --> 01:43:37,479
Speaker 1: migrated though. Well, I can't tell you that they they're

1745
01:43:37,520 --> 01:43:39,760
Speaker 1: in the winter. I just know around my list. If

1746
01:43:39,760 --> 01:43:42,639
Speaker 1: the list is going to get which will be fun.

1747
01:43:42,680 --> 01:43:44,160
Speaker 1: You want to set up a science study. I got

1748
01:43:44,240 --> 01:43:47,200
Speaker 1: a science study for you. I'll pull my bird feeder

1749
01:43:47,240 --> 01:43:49,439
Speaker 1: down and you tell me that that caused birds the leaf.

1750
01:43:51,880 --> 01:43:54,040
Speaker 1: It's just like, like it's a lot of value. Very modest,

1751
01:43:54,040 --> 01:43:56,400
Speaker 1: little high upbird feeder. Um. I think there's a lot

1752
01:43:56,439 --> 01:43:59,240
Speaker 1: of value for the kids, just as them to the list.

1753
01:43:59,520 --> 01:44:02,400
Speaker 1: I have problem with people feeding birds, But what's funny

1754
01:44:02,600 --> 01:44:05,840
Speaker 1: is that everybody used to feed birds a long time ago,

1755
01:44:06,240 --> 01:44:09,240
Speaker 1: and put a little food out for foxes and things too.

1756
01:44:09,320 --> 01:44:13,880
Speaker 1: It suddenly became like we're not supposed to be feeding animals,

1757
01:44:14,000 --> 01:44:16,200
Speaker 1: and the birds are the last ones, right. I mean,

1758
01:44:16,240 --> 01:44:19,200
Speaker 1: everybody like a fed bear is a dead bear. And yeah,

1759
01:44:19,240 --> 01:44:21,280
Speaker 1: they just say that mostly because it rhymes, but I

1760
01:44:21,400 --> 01:44:23,639
Speaker 1: think maybe they also think you shouldn't be feeding bears.

1761
01:44:24,200 --> 01:44:26,160
Speaker 1: There's a limit to that though. I mean, obviously, if

1762
01:44:26,200 --> 01:44:28,400
Speaker 1: you live in the middle of nowhere and there's not

1763
01:44:28,560 --> 01:44:30,680
Speaker 1: any other houses around you, what different I mean for

1764
01:44:30,720 --> 01:44:32,840
Speaker 1: a hundred miles or bears aren't going to go more

1765
01:44:32,880 --> 01:44:35,519
Speaker 1: than twenty five. Does it really matter if you let

1766
01:44:35,600 --> 01:44:38,120
Speaker 1: bears eat food on your property? Probably not. But if

1767
01:44:38,120 --> 01:44:41,040
Speaker 1: you're in Yellowstone National Park at a campground, you don't

1768
01:44:41,080 --> 01:44:44,679
Speaker 1: want bears coming around where there's food, so you can't

1769
01:44:44,720 --> 01:44:48,200
Speaker 1: really be attracting bears at a campground. It's trouble, but

1770
01:44:48,320 --> 01:44:50,840
Speaker 1: it depends on It's a very individual thing. But you

1771
01:44:50,960 --> 01:44:53,120
Speaker 1: talk to your grandma and I bet that generation they

1772
01:44:53,240 --> 01:44:55,560
Speaker 1: used to feed squirrels and stuff like that and chipmunks.

1773
01:44:55,640 --> 01:44:58,400
Speaker 1: And I think in England you're not even supposed to

1774
01:44:58,439 --> 01:45:00,920
Speaker 1: feed birds anymore. I'm pretty or about that. I think

1775
01:45:00,960 --> 01:45:03,439
Speaker 1: I read that in Hella McDonald's new book Vesper Flights,

1776
01:45:03,479 --> 01:45:07,120
Speaker 1: and so, yeah, they're coming for your bird feeder. They

1777
01:45:07,160 --> 01:45:11,679
Speaker 1: are coming for that. Until they finished meeting my thought.

1778
01:45:11,680 --> 01:45:13,519
Speaker 1: I don't know if you heard. It's modest. It's a modest.

1779
01:45:15,200 --> 01:45:18,720
Speaker 1: It was way up high. Feeding animals is not in

1780
01:45:18,920 --> 01:45:22,439
Speaker 1: vogue for sure, But it seems like the stuff that

1781
01:45:22,560 --> 01:45:26,240
Speaker 1: makes the paper are the folks that have gone that

1782
01:45:26,320 --> 01:45:28,080
Speaker 1: are making up for a lot of their neighbors not

1783
01:45:28,240 --> 01:45:32,120
Speaker 1: feeding right, Like some lady in Florida was getting like

1784
01:45:32,280 --> 01:45:36,200
Speaker 1: truckloads of Costco chickens to feed alligators in her back

1785
01:45:37,200 --> 01:45:41,559
Speaker 1: and stuff and barrels of feed. You know, we recently

1786
01:45:41,600 --> 01:45:43,200
Speaker 1: had on our website. I don't know if you've seen it.

1787
01:45:43,600 --> 01:45:48,160
Speaker 1: Um it's really something. There's a white tail fawn swimming.

1788
01:45:48,960 --> 01:45:51,360
Speaker 1: He's got himself in a lake. Some hunters the sea wall,

1789
01:45:52,320 --> 01:45:54,080
Speaker 1: so it's like the fawns out and you can't get

1790
01:45:54,160 --> 01:45:55,640
Speaker 1: up on the beach because there's a sea wall, and

1791
01:45:55,720 --> 01:45:59,120
Speaker 1: so he's swimming parallel to the sea wall. And a

1792
01:45:59,200 --> 01:46:04,960
Speaker 1: bald eagle combs down and very like, very deliberately, like

1793
01:46:05,200 --> 01:46:07,639
Speaker 1: it's done. It knew what it was doing. It comes

1794
01:46:07,680 --> 01:46:09,680
Speaker 1: down and lands on its head and drowns that thing.

1795
01:46:10,520 --> 01:46:14,880
Speaker 1: I mean, it knew it wasn't sitting there and it

1796
01:46:15,000 --> 01:46:18,000
Speaker 1: happened to drown. It came down and drowned that fat

1797
01:46:18,120 --> 01:46:19,560
Speaker 1: and then drug it up on the beach and ate it.

1798
01:46:20,320 --> 01:46:23,360
Speaker 1: That's interesting. It was really interesting and definitely not saying like, oh,

1799
01:46:23,400 --> 01:46:27,240
Speaker 1: that's very normal, but it was very deliberate in it,

1800
01:46:27,400 --> 01:46:29,639
Speaker 1: kind of like it knew that it was drowning something. Yeah,

1801
01:46:30,120 --> 01:46:31,479
Speaker 1: and I knew you were going to say it sat

1802
01:46:31,520 --> 01:46:33,639
Speaker 1: on its head. So I do think it's pretty expected

1803
01:46:33,680 --> 01:46:36,200
Speaker 1: for a because they're large birds and they throw their

1804
01:46:36,240 --> 01:46:38,840
Speaker 1: weight around. Think about again and think about a pagrine falcon.

1805
01:46:39,040 --> 01:46:42,000
Speaker 1: They're relatively small compared to a bald eagle, and they

1806
01:46:42,080 --> 01:46:45,160
Speaker 1: don't throw their weight around. They have great eyesight, they're talented.

1807
01:46:45,280 --> 01:46:49,680
Speaker 1: They're fast, Prairie falcon, nothing's faster, but throwing the weight

1808
01:46:49,720 --> 01:46:53,639
Speaker 1: around thing fits perfectly with your fierceness. They're not fierce,

1809
01:46:53,760 --> 01:46:57,120
Speaker 1: they're just they're slow. Their eyesight isn't as good as

1810
01:46:57,160 --> 01:47:00,960
Speaker 1: a foul. Yeah, paragan foul guns are fierce. Like that

1811
01:47:01,120 --> 01:47:04,599
Speaker 1: added mass when they do the steep or the stoop,

1812
01:47:04,800 --> 01:47:06,360
Speaker 1: you know where they drop out of this guy on

1813
01:47:06,439 --> 01:47:09,400
Speaker 1: their victim. That's got to be tremendous. And you think

1814
01:47:09,439 --> 01:47:11,600
Speaker 1: about it like hunting, So you hunt if are you

1815
01:47:11,680 --> 01:47:14,040
Speaker 1: going to use are you going to go for knockdown power?

1816
01:47:14,160 --> 01:47:16,439
Speaker 1: If let's say you've got a two seventy, are you

1817
01:47:16,479 --> 01:47:18,320
Speaker 1: going to go for knockdown power and put like one

1818
01:47:18,400 --> 01:47:20,479
Speaker 1: eighty grain white in? Or you're gonna go I'm going

1819
01:47:20,560 --> 01:47:22,479
Speaker 1: to get something. Maybe it's not legal to buy it,

1820
01:47:22,520 --> 01:47:23,840
Speaker 1: but you're going to load your own. And you know

1821
01:47:24,040 --> 01:47:25,639
Speaker 1: that you're a straight shooter, and you know that you're

1822
01:47:25,640 --> 01:47:27,360
Speaker 1: a great shot. You know that it's going to be

1823
01:47:27,439 --> 01:47:30,800
Speaker 1: a long shot, so low down to like one grain

1824
01:47:30,880 --> 01:47:32,360
Speaker 1: weight so it doesn't kick the hell out of you

1825
01:47:32,439 --> 01:47:38,000
Speaker 1: when you shoot. That's what I mean by mass, but weight,

1826
01:47:38,280 --> 01:47:40,760
Speaker 1: like somebody putting in one eighty grain weight in a

1827
01:47:40,840 --> 01:47:43,439
Speaker 1: two seventy because they need knockdown power because they're not

1828
01:47:43,520 --> 01:47:47,760
Speaker 1: going to make a good shot. That's the word, thank you,

1829
01:47:48,760 --> 01:47:54,280
Speaker 1: that's the word. I need it. It's vanesse. Doesn't with

1830
01:47:55,000 --> 01:47:57,599
Speaker 1: like the physics of something dropping out of the sky

1831
01:47:59,040 --> 01:48:04,840
Speaker 1: super fast. Don't know if you know, No, so U

1832
01:48:05,520 --> 01:48:07,600
Speaker 1: Red Tails picked up a skunk on my property the

1833
01:48:07,680 --> 01:48:10,000
Speaker 1: other day and I wasn't really thrilled about it, and

1834
01:48:10,120 --> 01:48:11,560
Speaker 1: she dropped She did come back and get it in

1835
01:48:11,640 --> 01:48:14,040
Speaker 1: case you're a Red Tail fan, but she dropped it right.

1836
01:48:14,160 --> 01:48:18,400
Speaker 1: And it was a baby. It was just a few weeks. Yeah,

1837
01:48:18,479 --> 01:48:20,839
Speaker 1: she killed it though. But I picked up the carcass

1838
01:48:20,880 --> 01:48:22,559
Speaker 1: from the ground because she dropped it on this little

1839
01:48:22,600 --> 01:48:24,760
Speaker 1: trail and I thought that I was going to bring

1840
01:48:24,840 --> 01:48:26,960
Speaker 1: it over by the dan so the mom could see.

1841
01:48:27,439 --> 01:48:29,080
Speaker 1: I wondered how they would react to the baby, the

1842
01:48:29,120 --> 01:48:33,439
Speaker 1: dead baby skunk. But anyway I saw with the I

1843
01:48:33,560 --> 01:48:35,840
Speaker 1: wondered if she would recognize that that was hers orf

1844
01:48:35,840 --> 01:48:37,360
Speaker 1: there would be any kind of reaction, But the Red

1845
01:48:37,400 --> 01:48:39,200
Speaker 1: Tail came and snatched it back from me before I

1846
01:48:39,240 --> 01:48:41,680
Speaker 1: got to do anything. But anyway, the skunk, it was

1847
01:48:41,760 --> 01:48:44,599
Speaker 1: dead right she dropped it. She had managed to get

1848
01:48:44,640 --> 01:48:48,120
Speaker 1: her claws right through its head. I mean that's talent

1849
01:48:48,560 --> 01:48:50,720
Speaker 1: she doesn't. You don't need any weight. If you've got

1850
01:48:50,800 --> 01:48:53,479
Speaker 1: that much finesse, it's dead like that second. If she

1851
01:48:53,520 --> 01:48:56,439
Speaker 1: had tried to grab it from its mass, it wouldn't

1852
01:48:56,439 --> 01:48:59,080
Speaker 1: have been dad. Maybe having extra weight would have helped.

1853
01:48:59,360 --> 01:49:01,560
Speaker 1: But red tails are really good hunters. I mean you

1854
01:49:01,600 --> 01:49:04,560
Speaker 1: see them pick up snakes. They're really good. That's a

1855
01:49:04,600 --> 01:49:07,719
Speaker 1: good point. That can't be easy. So she redtails have finesse,

1856
01:49:07,800 --> 01:49:09,760
Speaker 1: so it doesn't matter how much weight they have. A

1857
01:49:09,840 --> 01:49:12,280
Speaker 1: bald eagle that doesn't have finesse because they're used to

1858
01:49:12,360 --> 01:49:16,320
Speaker 1: killing things that are road kill uses their bulk, their mass.

1859
01:49:16,800 --> 01:49:19,240
Speaker 1: They're the one eighty grain weights in your two sevent

1860
01:49:19,280 --> 01:49:23,800
Speaker 1: day basically excusing their book. I know you guys don't

1861
01:49:23,960 --> 01:49:26,679
Speaker 1: go for knockdown power because that's not what you advertise.

1862
01:49:26,720 --> 01:49:30,400
Speaker 1: Probably I like things that yeah I should big, Yeah,

1863
01:49:30,600 --> 01:49:33,320
Speaker 1: I should, I should what would be regarded as a

1864
01:49:33,360 --> 01:49:37,680
Speaker 1: heavy rifle. Yeah, but it doesn't. Yeah. I used to

1865
01:49:37,760 --> 01:49:39,760
Speaker 1: load my own, and so I would always load down, down, down,

1866
01:49:39,840 --> 01:49:41,559
Speaker 1: lower than what I could buy in the market, because

1867
01:49:41,800 --> 01:49:44,040
Speaker 1: I don't want to if it hurts me more than

1868
01:49:44,080 --> 01:49:46,120
Speaker 1: it hurts what's dead. You don't want to lose your

1869
01:49:47,439 --> 01:49:50,960
Speaker 1: ba thing? Yeah, why hunt? If you're like arms going

1870
01:49:51,000 --> 01:49:53,439
Speaker 1: to fall off? I want to keep Can you take

1871
01:49:53,439 --> 01:49:55,360
Speaker 1: it off? Can you take it up? Offline? Arguing about

1872
01:49:55,360 --> 01:49:58,479
Speaker 1: the birds because I want to keep moving and what

1873
01:49:58,560 --> 01:50:00,599
Speaker 1: am I supposed to do? Saying if you got If

1874
01:50:00,600 --> 01:50:02,519
Speaker 1: you want to argue about birds more, you'll have to

1875
01:50:02,560 --> 01:50:05,120
Speaker 1: call Kathy up later. Oh yeah, no problem, I know

1876
01:50:05,160 --> 01:50:09,560
Speaker 1: where she lives. No, I'm am I arguing I don't know,

1877
01:50:12,720 --> 01:50:18,280
Speaker 1: all right, So, uh that's a big digression. Valuable. No,

1878
01:50:18,600 --> 01:50:20,840
Speaker 1: it's my fault, not my fault. I'm glad I did it.

1879
01:50:21,360 --> 01:50:23,000
Speaker 1: It was prompted by me, But I want to keep

1880
01:50:23,040 --> 01:50:25,599
Speaker 1: moving forward. That was just Cathy's bio. By the way,

1881
01:50:25,640 --> 01:50:30,960
Speaker 1: that now you know who I am? Yeah, um, okay,

1882
01:50:31,080 --> 01:50:33,680
Speaker 1: walk me through and whatever way makes sense, walk me

1883
01:50:33,720 --> 01:50:36,879
Speaker 1: through how we got from that? Here? You are studying

1884
01:50:37,160 --> 01:50:41,320
Speaker 1: bald eagles too. You got a brand new book about

1885
01:50:41,400 --> 01:50:46,559
Speaker 1: about not foxes, but a fox based on a fox.

1886
01:50:46,760 --> 01:50:50,840
Speaker 1: It's really important to distinguish between foxes and a fox.

1887
01:50:51,000 --> 01:50:55,040
Speaker 1: So scientists do research, gather information so that you can

1888
01:50:55,160 --> 01:51:00,479
Speaker 1: enlighten us. Staring up Karmen again about foxes, just like

1889
01:51:00,640 --> 01:51:04,599
Speaker 1: sociologists are studying about humans. But when you write a book,

1890
01:51:04,760 --> 01:51:07,800
Speaker 1: a novel, you're not trying to show us about your

1891
01:51:07,960 --> 01:51:11,679
Speaker 1: You've got a protagonist who's one human. My book isn't

1892
01:51:11,680 --> 01:51:15,920
Speaker 1: about foxes in general. It's not encyclopedic information about a

1893
01:51:16,000 --> 01:51:19,560
Speaker 1: particular species. It's about one particular fox. But it is

1894
01:51:19,680 --> 01:51:23,560
Speaker 1: important for us to start realizing that we shouldn't just generalize.

1895
01:51:23,600 --> 01:51:26,559
Speaker 1: We have tended to generalize animals and put them all

1896
01:51:26,600 --> 01:51:32,560
Speaker 1: in one big clumps, yet it keeps us from empathizing

1897
01:51:32,680 --> 01:51:34,760
Speaker 1: with them. I think you'll feel the same when you

1898
01:51:34,840 --> 01:51:38,439
Speaker 1: think about other groups of people. But when we when

1899
01:51:38,560 --> 01:51:42,400
Speaker 1: we put people or animals in a big group, when

1900
01:51:42,479 --> 01:51:47,000
Speaker 1: we generalize, it keeps us from empathizing. And when we empathize,

1901
01:51:47,080 --> 01:51:50,200
Speaker 1: then we can really understand and accept and respect them

1902
01:51:50,240 --> 01:51:53,400
Speaker 1: and understand that they're a little bit closer to humans

1903
01:51:53,479 --> 01:51:55,960
Speaker 1: than we thought that they were. So my book is

1904
01:51:56,000 --> 01:51:59,120
Speaker 1: about an individual fox, and it is important to understand

1905
01:51:59,160 --> 01:52:03,320
Speaker 1: the difference between the generic generic fox. For I mean,

1906
01:52:03,360 --> 01:52:06,560
Speaker 1: there's lots of things that are true about foxes that

1907
01:52:06,680 --> 01:52:09,920
Speaker 1: I believe are true. I've read them in in in

1908
01:52:10,040 --> 01:52:12,240
Speaker 1: my textbook that I use in my classes, and so

1909
01:52:12,800 --> 01:52:16,200
Speaker 1: Foxes do have an instinct to evade, for example, something

1910
01:52:16,280 --> 01:52:20,439
Speaker 1: flying overhead, like a golden eagle, but my particular fox didn't.

1911
01:52:20,640 --> 01:52:22,360
Speaker 1: I mean I would watch him run down the hill

1912
01:52:22,400 --> 01:52:24,439
Speaker 1: and I've got a bald ego nest on the cliff there,

1913
01:52:24,479 --> 01:52:27,040
Speaker 1: and he just would just be bouncing around and I

1914
01:52:27,080 --> 01:52:31,080
Speaker 1: mean he just you know, animals do have individual personalities

1915
01:52:31,160 --> 01:52:34,559
Speaker 1: like that was a blind spot for that fox. Yeah, exactly. Um,

1916
01:52:35,720 --> 01:52:39,160
Speaker 1: but that's not I'm not trying to change how you

1917
01:52:39,240 --> 01:52:41,599
Speaker 1: feel about all foxes. I don't want you to think that, oh,

1918
01:52:41,760 --> 01:52:44,360
Speaker 1: it's not true that foxes evade. It's what's true of

1919
01:52:44,439 --> 01:52:48,160
Speaker 1: the generic fox. It's important that we have when we

1920
01:52:48,280 --> 01:52:51,400
Speaker 1: get in scientific information. We're talking about, you know, the

1921
01:52:51,520 --> 01:52:54,160
Speaker 1: ones under the high part of the Bell curve, and

1922
01:52:54,280 --> 01:52:57,280
Speaker 1: we assume that people know that there's outliers, but some

1923
01:52:57,439 --> 01:53:01,040
Speaker 1: people forget that their outliers and think that everything is

1924
01:53:01,200 --> 01:53:04,679
Speaker 1: the same. We know that humans have outliers to them

1925
01:53:04,720 --> 01:53:07,080
Speaker 1: in the room with like four outliers or so, so

1926
01:53:07,320 --> 01:53:10,439
Speaker 1: you know, humans are outliers, but we forget that's true

1927
01:53:10,479 --> 01:53:15,120
Speaker 1: of other species as well. Outlines humans like humans are

1928
01:53:17,120 --> 01:53:24,280
Speaker 1: kind of generally monogamous. They generally reproduce. But that's certainly,

1929
01:53:25,439 --> 01:53:29,000
Speaker 1: you know, not the case. I think humans scientifically speaking

1930
01:53:29,040 --> 01:53:31,560
Speaker 1: are hair and harem breeding species, Isn't that right? I

1931
01:53:31,600 --> 01:53:34,840
Speaker 1: mean they're harem breeders, but Mormons are monogamous, maybe, I guess,

1932
01:53:34,920 --> 01:53:38,240
Speaker 1: but not humans in general, we're harem breeders. Signed I

1933
01:53:38,280 --> 01:53:41,640
Speaker 1: mean biologically that I know what you mean. You mean,

1934
01:53:41,840 --> 01:53:45,400
Speaker 1: regress is like a sociological like a sociological overlay, a

1935
01:53:45,479 --> 01:53:49,760
Speaker 1: cultural overlay. Yeah, you should read EO. Wilson's socio Biology

1936
01:53:51,320 --> 01:53:54,120
Speaker 1: another but yeah, but I don't know, man, I was

1937
01:53:54,160 --> 01:53:57,600
Speaker 1: reading this thing about how, um that doesn't apply in

1938
01:53:57,680 --> 01:54:03,840
Speaker 1: your house that human in human females, Um, there's no

1939
01:54:04,280 --> 01:54:08,680
Speaker 1: outward visual. There's no outward visual to tell someone that

1940
01:54:08,840 --> 01:54:12,720
Speaker 1: they're in heat. Okay, if you just if you want

1941
01:54:12,760 --> 01:54:14,800
Speaker 1: to talk like like purely, like a million terms, there's

1942
01:54:14,840 --> 01:54:18,960
Speaker 1: no outward visual and it's not like a seasonal thing.

1943
01:54:20,479 --> 01:54:24,080
Speaker 1: It's not like once a year females. Yeah, like yeah,

1944
01:54:24,200 --> 01:54:27,240
Speaker 1: so viable, like it would be like a human female

1945
01:54:27,280 --> 01:54:32,120
Speaker 1: would be sexually viable twelve times a year, not one

1946
01:54:32,200 --> 01:54:35,200
Speaker 1: time a year like some wild animals. And at higher

1947
01:54:35,280 --> 01:54:40,000
Speaker 1: latitudes and then um, the temperature changes. You know that.

1948
01:54:40,280 --> 01:54:41,960
Speaker 1: But it's not outward I'm just telling you. I'm not

1949
01:54:42,000 --> 01:54:45,120
Speaker 1: telling you my of the vaginal fluids. Can you say

1950
01:54:45,200 --> 01:54:52,160
Speaker 1: that on your radio show outward visual displays? Yeah, but

1951
01:54:52,320 --> 01:54:55,640
Speaker 1: baboons Yeah, But on baboons for instance, there's like an

1952
01:54:55,680 --> 01:54:59,320
Speaker 1: outward visual display. So someone was saying, like I just

1953
01:54:59,400 --> 01:55:03,880
Speaker 1: read this thing time explaining monogamy and and staying at home. Okay,

1954
01:55:04,280 --> 01:55:07,560
Speaker 1: And it would be that you couldn't like a bull Elk.

1955
01:55:07,680 --> 01:55:10,240
Speaker 1: Let's take a bull Elk. Okay, he knows as long

1956
01:55:10,280 --> 01:55:14,760
Speaker 1: as he shows up in September around the cows, he's

1957
01:55:14,800 --> 01:55:17,040
Speaker 1: not missing anything. If he goes off into his own

1958
01:55:17,160 --> 01:55:20,560
Speaker 1: zone in November and stays out there and has no

1959
01:55:20,760 --> 01:55:25,920
Speaker 1: interaction with cows at all, totally antisocial, hides out, antisocial,

1960
01:55:26,240 --> 01:55:28,600
Speaker 1: he's not like he knows, he's not missing out on

1961
01:55:28,680 --> 01:55:32,240
Speaker 1: breeding up. You're right, But with a human it want

1962
01:55:32,280 --> 01:55:35,520
Speaker 1: to be in that that you could be missing out

1963
01:55:35,600 --> 01:55:37,520
Speaker 1: and in your absence there could be things going on

1964
01:55:37,640 --> 01:55:40,680
Speaker 1: that you don't want to know about. So that compelled

1965
01:55:40,800 --> 01:55:45,120
Speaker 1: people to spend their entire time together. Wouldn't that just

1966
01:55:45,200 --> 01:55:49,200
Speaker 1: compel one guy to like Genghis Khan, to have more

1967
01:55:49,360 --> 01:55:53,160
Speaker 1: females around him. When I say that we're harem breeders.

1968
01:55:53,200 --> 01:55:55,200
Speaker 1: I don't mean in the last two or three hundred four.

1969
01:55:56,040 --> 01:55:58,040
Speaker 1: Humans have been on the planet for hundreds of thousands

1970
01:55:58,040 --> 01:56:00,600
Speaker 1: of year, so I mean the history of home sapiens.

1971
01:56:01,120 --> 01:56:02,600
Speaker 1: And I'm not even telling I'm just saying, like a

1972
01:56:02,680 --> 01:56:06,360
Speaker 1: thing I read, the thing I read, So never mind.

1973
01:56:06,400 --> 01:56:09,080
Speaker 1: What was I saying? There's a there's all sorts of

1974
01:56:09,080 --> 01:56:11,040
Speaker 1: fun stuff we can tell. Oh, you're talking about outliers

1975
01:56:11,280 --> 01:56:12,480
Speaker 1: and I was trying to say. I was trying to

1976
01:56:12,520 --> 01:56:16,200
Speaker 1: make like some general things about humans, like, sorry, I forget,

1977
01:56:16,560 --> 01:56:21,560
Speaker 1: sorry forget that there are outliers. There are outliers and humans. Yes, yes, yes,

1978
01:56:21,640 --> 01:56:24,000
Speaker 1: you're right, and sorry about that. So we start talking

1979
01:56:24,000 --> 01:56:26,240
Speaker 1: about monogamy and you were just because you picked a

1980
01:56:26,320 --> 01:56:29,520
Speaker 1: weird thing as to be an outlier, and actually, let

1981
01:56:29,520 --> 01:56:33,640
Speaker 1: should have picked something different. But like marshmallows, Yeah, we

1982
01:56:33,840 --> 01:56:37,560
Speaker 1: generally like marshmallows. People like sweet things, and then there's

1983
01:56:37,600 --> 01:56:42,480
Speaker 1: some people that don't like sweet stuff. That's safer, good shob.

1984
01:56:42,840 --> 01:56:45,160
Speaker 1: People like a certain kinds of food, and then every

1985
01:56:45,200 --> 01:56:46,960
Speaker 1: once in a while you run into people that don't

1986
01:56:47,000 --> 01:56:48,920
Speaker 1: like that kind of food, or people are basically all

1987
01:56:48,960 --> 01:56:51,560
Speaker 1: the same sizes and then there's like some people born

1988
01:56:51,640 --> 01:56:54,240
Speaker 1: that are like seven or eight feet tall, some people

1989
01:56:54,280 --> 01:56:57,120
Speaker 1: that are very short. So are you holding out? I

1990
01:56:57,200 --> 01:56:59,200
Speaker 1: want to I want to help out here? Are you

1991
01:56:59,360 --> 01:57:03,800
Speaker 1: holding out? The fox? And fox? And I could be

1992
01:57:03,920 --> 01:57:08,000
Speaker 1: like a wild outlier? Oh he's yeah, he's an outlier,

1993
01:57:08,120 --> 01:57:10,560
Speaker 1: not super wild outliers. I mean, you know, there's a

1994
01:57:10,600 --> 01:57:12,800
Speaker 1: research that was done in Rush over fifty year period

1995
01:57:12,880 --> 01:57:16,160
Speaker 1: and shows that um Dr Balovs research, and so far

1996
01:57:16,360 --> 01:57:19,400
Speaker 1: it's not a huge outlier. I doubt he's even one

1997
01:57:19,440 --> 01:57:22,240
Speaker 1: in a million. It's just that in my experience, in

1998
01:57:22,360 --> 01:57:25,080
Speaker 1: my very short life, and I've always had foxes on

1999
01:57:25,160 --> 01:57:27,200
Speaker 1: my property for for a long time anyway, I've not

2000
01:57:27,320 --> 01:57:29,720
Speaker 1: been able to get this to work with a relationship

2001
01:57:29,800 --> 01:57:31,440
Speaker 1: like that with another fox. But I haven't seen a

2002
01:57:31,520 --> 01:57:34,040
Speaker 1: million foxes, you know, a couple of dozen. So maybe

2003
01:57:34,120 --> 01:57:36,280
Speaker 1: he's one in a thousand or something like that, but

2004
01:57:36,360 --> 01:57:40,640
Speaker 1: he's not that that kind of personality. Isn't that rare? Yeah,

2005
01:57:40,880 --> 01:57:43,000
Speaker 1: he could be one in twenty four because the research

2006
01:57:43,040 --> 01:57:46,160
Speaker 1: shows that foxes are relatively easy to domesticate, almost as

2007
01:57:46,200 --> 01:57:48,520
Speaker 1: easy as dogs. So Dr Baliot was able to do

2008
01:57:48,560 --> 01:58:00,880
Speaker 1: it with about fifty generations that's pretty quick. Okay, lay

2009
01:58:00,880 --> 01:58:04,040
Speaker 1: out the fox, lay out the scenario. So the scenario

2010
01:58:04,280 --> 01:58:07,640
Speaker 1: is this little fox starts coming around my house like

2011
01:58:07,920 --> 01:58:10,760
Speaker 1: all the time at the same time, and I had

2012
01:58:12,200 --> 01:58:14,680
Speaker 1: right he was it was four fifteen. He was watching

2013
01:58:14,800 --> 01:58:17,800
Speaker 1: the sun. He was. He's really sensitive to the sun

2014
01:58:17,880 --> 01:58:20,400
Speaker 1: and kind of jerry manders whole life routines around like

2015
01:58:20,480 --> 01:58:22,400
Speaker 1: he doesn't like the sun in his eyes, but he

2016
01:58:22,480 --> 01:58:24,680
Speaker 1: does like the sun on his body when he's sun bathing,

2017
01:58:24,760 --> 01:58:26,800
Speaker 1: and um, he doesn't like to walk into it, so

2018
01:58:26,920 --> 01:58:30,080
Speaker 1: he does things according to the sun. First. A little

2019
01:58:30,160 --> 01:58:32,800
Speaker 1: sorry when you say little was was it a young No?

2020
01:58:33,040 --> 01:58:35,720
Speaker 1: But he was certainly a run I'm guessing I was

2021
01:58:35,760 --> 01:58:38,640
Speaker 1: guessing about six pounds, and um, you think he is

2022
01:58:38,680 --> 01:58:41,080
Speaker 1: at a run of a litter? Yeah, absolutely. I mean

2023
01:58:41,120 --> 01:58:42,680
Speaker 1: the fact that he couldn't talk. And then when you

2024
01:58:42,760 --> 01:58:46,200
Speaker 1: see when you go and see like a certain rock

2025
01:58:46,280 --> 01:58:47,920
Speaker 1: that he used to stand on all the time, and

2026
01:58:48,000 --> 01:58:50,400
Speaker 1: I have photos of all four ft on that rock,

2027
01:58:50,720 --> 01:58:52,480
Speaker 1: and then you go and look at how small that

2028
01:58:52,640 --> 01:58:55,000
Speaker 1: rock is, and you just, yeah, yeah, he was a

2029
01:58:55,080 --> 01:58:58,640
Speaker 1: real small fox. Foxes are smaller in the in the Rockies,

2030
01:58:58,760 --> 01:59:00,880
Speaker 1: then they're going to be in England and probably even

2031
01:59:00,960 --> 01:59:04,000
Speaker 1: in a more moderate climate than in in Washington State.

2032
01:59:04,160 --> 01:59:07,160
Speaker 1: Organ they're they're small in the Rockies. Everything smaller here

2033
01:59:07,200 --> 01:59:10,560
Speaker 1: because the growing seasons and they can't is short and

2034
01:59:10,600 --> 01:59:12,800
Speaker 1: they can't eat as much. So he was a small

2035
01:59:12,920 --> 01:59:17,400
Speaker 1: fox for sure. Um and he planned his life around

2036
01:59:17,440 --> 01:59:19,600
Speaker 1: the sun pretty much. But I think that he had

2037
01:59:19,640 --> 01:59:23,440
Speaker 1: decided he wanted me in his life. He wanted a person.

2038
01:59:23,520 --> 01:59:26,400
Speaker 1: There wasn't any other choice around for him besides me,

2039
01:59:27,400 --> 01:59:29,160
Speaker 1: and I didn't really want to have anything to do

2040
01:59:29,280 --> 01:59:33,600
Speaker 1: with him, but he wore me down, and eventually I

2041
01:59:33,880 --> 01:59:36,440
Speaker 1: really believe he became what I would call my best friend.

2042
01:59:36,800 --> 01:59:40,040
Speaker 1: We were together every day every day for years. I

2043
01:59:40,120 --> 01:59:43,320
Speaker 1: mean just I read to him and we walked around together,

2044
01:59:43,560 --> 01:59:46,040
Speaker 1: and then we played games together. But it took a

2045
01:59:46,080 --> 01:59:50,240
Speaker 1: while to get to that. No, but I do keep

2046
01:59:50,600 --> 01:59:55,720
Speaker 1: um egg yokes outside, not very close to my house.

2047
01:59:55,800 --> 01:59:58,160
Speaker 1: But when I was just eating egg whites in the

2048
01:59:58,240 --> 02:00:00,320
Speaker 1: days before you could just buy the whites, I would

2049
02:00:00,320 --> 02:00:02,640
Speaker 1: separate them out so I wasn't eating egg yolks every day.

2050
02:00:02,920 --> 02:00:06,000
Speaker 1: I would put egg yolks out by a tree about

2051
02:00:06,000 --> 02:00:09,240
Speaker 1: three from my house, and so he would eat those

2052
02:00:09,280 --> 02:00:11,480
Speaker 1: once in a while, but not many he would come

2053
02:00:11,480 --> 02:00:15,240
Speaker 1: by and eat like one. The magpies ate most of them,

2054
02:00:15,600 --> 02:00:18,280
Speaker 1: And I don't think that he ever associated those egg

2055
02:00:18,360 --> 02:00:21,360
Speaker 1: yolks with me. Um. So no, then I don't think.

2056
02:00:21,440 --> 02:00:23,240
Speaker 1: I was pretty careful not to put things in my

2057
02:00:23,320 --> 02:00:24,920
Speaker 1: mouth in front of him. Even if I was just

2058
02:00:25,080 --> 02:00:28,320
Speaker 1: drinking tea while I was sitting on the steps with him,

2059
02:00:28,320 --> 02:00:30,160
Speaker 1: I wouldn't even drink it while he was watching. I

2060
02:00:30,200 --> 02:00:32,400
Speaker 1: didn't want him to see me put stuff in my mouth,

2061
02:00:32,840 --> 02:00:35,040
Speaker 1: So there was as food with me. But there was

2062
02:00:35,080 --> 02:00:39,240
Speaker 1: a day, like a day when you first took note,

2063
02:00:39,400 --> 02:00:43,760
Speaker 1: like you first registered his presence, the first time that

2064
02:00:43,920 --> 02:00:46,400
Speaker 1: I realized he was odd and something was going to

2065
02:00:46,480 --> 02:00:48,760
Speaker 1: happen when he wasn't just like some air and animal.

2066
02:00:48,800 --> 02:00:51,360
Speaker 1: I mean, there's always foxes and badgers and skunks around

2067
02:00:51,440 --> 02:00:55,000
Speaker 1: in Deer. That day happened when I was hanging out

2068
02:00:55,080 --> 02:00:59,160
Speaker 1: outside and I have I always have scabby knee, so

2069
02:00:59,240 --> 02:01:02,360
Speaker 1: I have the scab knee, and this huge house fly

2070
02:01:02,960 --> 02:01:05,240
Speaker 1: was playing with my scabs, sucking all this blood and

2071
02:01:05,320 --> 02:01:07,120
Speaker 1: playing with the blood, and I was like blowing it

2072
02:01:07,240 --> 02:01:11,240
Speaker 1: to try to get it off my knee. Falling off

2073
02:01:11,240 --> 02:01:14,920
Speaker 1: the cliffs, climbing up the cliffs. No, no, no, climbing

2074
02:01:14,960 --> 02:01:17,440
Speaker 1: up well, that was from a fall when I was jogging,

2075
02:01:17,520 --> 02:01:19,360
Speaker 1: or I shouldn't have been jogging by myself, and took

2076
02:01:19,360 --> 02:01:21,440
Speaker 1: a little bit of a role. But climbing the cliffs

2077
02:01:21,480 --> 02:01:23,440
Speaker 1: are jogging on trails that I shouldn't be jogging on.

2078
02:01:24,600 --> 02:01:29,120
Speaker 1: So I was playing with that fly and then I

2079
02:01:29,280 --> 02:01:31,360
Speaker 1: just kept playing. The fly wouldn't give up, so he

2080
02:01:31,400 --> 02:01:33,240
Speaker 1: would just get off my knee when I would blow

2081
02:01:33,280 --> 02:01:35,320
Speaker 1: really hard, and then he would take a few reconnaissance

2082
02:01:35,440 --> 02:01:37,520
Speaker 1: laps and then boom right back on my scab again,

2083
02:01:37,880 --> 02:01:41,520
Speaker 1: start pulling up the blood again. This nasty little arms,

2084
02:01:41,560 --> 02:01:43,520
Speaker 1: so to speak. They don't really have arms, I know,

2085
02:01:43,680 --> 02:01:46,320
Speaker 1: you know that. And I just got totally obsessed with

2086
02:01:46,400 --> 02:01:48,320
Speaker 1: his fly and forgot about everything else, and I was

2087
02:01:48,440 --> 02:01:51,600
Speaker 1: just staring at this house fly. Then I looked up

2088
02:01:52,480 --> 02:01:55,200
Speaker 1: and there was a fox like two like arms length

2089
02:01:55,280 --> 02:01:58,280
Speaker 1: away from me. It was him, and he didn't even

2090
02:01:58,320 --> 02:02:01,360
Speaker 1: know I was there. He was like staring at that

2091
02:02:01,520 --> 02:02:04,240
Speaker 1: fly on my knee. He was just obsessed with that fly,

2092
02:02:04,520 --> 02:02:06,840
Speaker 1: and I was obsessed with the fly. And at that

2093
02:02:06,960 --> 02:02:08,640
Speaker 1: point I didn't know what to do because he was

2094
02:02:08,760 --> 02:02:13,320
Speaker 1: so close. So I just said fox and then finally

2095
02:02:13,400 --> 02:02:15,280
Speaker 1: he looked up at me. And when he looked up

2096
02:02:15,360 --> 02:02:18,080
Speaker 1: at me, he turned his nose down, so that you know,

2097
02:02:18,160 --> 02:02:19,680
Speaker 1: the snout will be in the way if you're trying

2098
02:02:19,720 --> 02:02:21,960
Speaker 1: to look eye to eye. He turned down and then

2099
02:02:22,560 --> 02:02:25,440
Speaker 1: we were totally eye to eye. The width of six

2100
02:02:25,520 --> 02:02:28,080
Speaker 1: pound animal. His eyes are just about the same with

2101
02:02:29,040 --> 02:02:32,080
Speaker 1: as ours are. Another reason I don't think it's one

2102
02:02:32,160 --> 02:02:33,920
Speaker 1: in a million for fox in a human type. I

2103
02:02:33,920 --> 02:02:36,160
Speaker 1: mean their eyes. You know, I have a skunk that's

2104
02:02:36,200 --> 02:02:38,800
Speaker 1: almost the same size, hanging around all the time, almost

2105
02:02:38,840 --> 02:02:42,280
Speaker 1: the same size as as that fox. But there are

2106
02:02:42,400 --> 02:02:44,080
Speaker 1: there's no way you'd ever look eye to eye. I

2107
02:02:44,120 --> 02:02:46,080
Speaker 1: mean you can barely even see the eyes on a

2108
02:02:46,120 --> 02:02:48,480
Speaker 1: skunk or so small and their heads so small and there,

2109
02:02:49,200 --> 02:02:52,360
Speaker 1: and their eyes are so close together. So fox, when

2110
02:02:52,400 --> 02:02:58,080
Speaker 1: I'm sitting and he's standing standing on all fours, his

2111
02:02:58,240 --> 02:03:00,240
Speaker 1: eyes are the same height as mine and the same

2112
02:03:00,320 --> 02:03:02,560
Speaker 1: with this mind. So we were just eye to eye

2113
02:03:02,720 --> 02:03:07,080
Speaker 1: for just the longest time. And that moment, that was

2114
02:03:07,200 --> 02:03:10,520
Speaker 1: the moment that I knew there was no going back. Really,

2115
02:03:10,640 --> 02:03:13,000
Speaker 1: I mean I tried, but there was not. When you're

2116
02:03:13,080 --> 02:03:14,880
Speaker 1: that close. I mean, he could have reached out and

2117
02:03:15,240 --> 02:03:17,880
Speaker 1: swatted me. I could have, you know, reached grabbed his

2118
02:03:17,960 --> 02:03:20,920
Speaker 1: little neck and strangled him. But we we were just

2119
02:03:21,080 --> 02:03:23,880
Speaker 1: that close, just staring at each other, and then I

2120
02:03:24,000 --> 02:03:26,120
Speaker 1: locked him in. He locked me, and I think he

2121
02:03:26,200 --> 02:03:28,000
Speaker 1: knew he had me and I had him. At that point,

2122
02:03:28,160 --> 02:03:31,480
Speaker 1: I started taking stuff out of my pockets, tapping them

2123
02:03:31,520 --> 02:03:36,320
Speaker 1: on the woodsteps, like geodes and feathers, every mostly all

2124
02:03:36,440 --> 02:03:39,120
Speaker 1: natural things. I had some brass because I keep I

2125
02:03:39,200 --> 02:03:41,640
Speaker 1: don't just let my brass hang out, so I had

2126
02:03:41,720 --> 02:03:43,600
Speaker 1: some brass in my pocket. I took that out too,

2127
02:03:44,200 --> 02:03:46,760
Speaker 1: told him I didn't use it to shoot the dear,

2128
02:03:46,880 --> 02:03:52,520
Speaker 1: let's hang out the walk. I had that, so I

2129
02:03:52,600 --> 02:03:54,440
Speaker 1: took that out and tapped it. But you know, brass

2130
02:03:54,600 --> 02:03:56,240
Speaker 1: is pretty if you roll it in the sun, so

2131
02:03:56,360 --> 02:03:58,600
Speaker 1: I did that. He liked that, and he liked the rocks.

2132
02:03:58,640 --> 02:04:01,160
Speaker 1: He really liked the feathers that were in my pockets.

2133
02:04:01,280 --> 02:04:03,600
Speaker 1: And then I just moved away and let him did

2134
02:04:03,800 --> 02:04:08,320
Speaker 1: show well he's not He was really curious about them.

2135
02:04:08,360 --> 02:04:10,280
Speaker 1: I eventually moved away a couple of meters and just

2136
02:04:10,440 --> 02:04:12,680
Speaker 1: let him knows everything that was there, and he just

2137
02:04:13,840 --> 02:04:16,400
Speaker 1: I kept him coming back for days, just putting my

2138
02:04:16,520 --> 02:04:19,120
Speaker 1: little trinkets out in front of him and letting him

2139
02:04:19,440 --> 02:04:22,280
Speaker 1: show his interest. Then I worried that, well, it was

2140
02:04:22,280 --> 02:04:25,080
Speaker 1: getting boring for me, and he had a very short

2141
02:04:25,120 --> 02:04:27,400
Speaker 1: attention span, so he would look for a little while

2142
02:04:27,440 --> 02:04:33,360
Speaker 1: and then he put his head up, can themselves yes.

2143
02:04:33,640 --> 02:04:36,240
Speaker 1: So I started reading to him after that, and then

2144
02:04:36,400 --> 02:04:40,560
Speaker 1: he was really good about that. He liked it absolutely,

2145
02:04:40,680 --> 02:04:43,520
Speaker 1: he stayed. I mean I timed him quite a lot,

2146
02:04:43,720 --> 02:04:47,560
Speaker 1: and I he averaged eighteen minutes, so that he didn't

2147
02:04:47,600 --> 02:04:49,160
Speaker 1: like it a lot. I mean he wouldn't sit for

2148
02:04:49,240 --> 02:04:51,080
Speaker 1: a very long period time. At eighteen minutes is pretty

2149
02:04:51,080 --> 02:04:54,040
Speaker 1: long for that's about as long as a person can say, okay,

2150
02:04:54,400 --> 02:04:58,880
Speaker 1: explain like I understand reading to it, but explained it

2151
02:04:59,760 --> 02:05:03,280
Speaker 1: just of that I was making it. So the reason

2152
02:05:03,360 --> 02:05:07,440
Speaker 1: it's noise, I mean, the reason I was reading is

2153
02:05:07,480 --> 02:05:10,360
Speaker 1: because I just wasn't used to talking about just myself

2154
02:05:10,480 --> 02:05:13,160
Speaker 1: telling stories, and that's boring and that's hard to do.

2155
02:05:14,080 --> 02:05:18,000
Speaker 1: So I got something that was easy to read. And

2156
02:05:18,200 --> 02:05:20,120
Speaker 1: then you talk for a certain amount of time and

2157
02:05:20,320 --> 02:05:23,680
Speaker 1: look hold up the pictures so he knows you're trying

2158
02:05:23,720 --> 02:05:26,400
Speaker 1: to communicate, and then you stop and then you look

2159
02:05:26,440 --> 02:05:29,280
Speaker 1: at him. Count to fifteen to yourself so that he

2160
02:05:29,440 --> 02:05:31,800
Speaker 1: realizes that you are trying to communicate. If you just

2161
02:05:31,960 --> 02:05:35,040
Speaker 1: make noise, he thinks you're just ignoring him. That you know,

2162
02:05:35,240 --> 02:05:38,080
Speaker 1: it's just a person who's making noise. I mean you

2163
02:05:38,400 --> 02:05:40,200
Speaker 1: you have to do it in that pattern as if

2164
02:05:40,240 --> 02:05:42,920
Speaker 1: you're trying to communicate. And I kept up that pattern

2165
02:05:43,360 --> 02:05:45,360
Speaker 1: and he got used to that pattern, so he knew

2166
02:05:45,400 --> 02:05:48,240
Speaker 1: I was trying to communicate with him. And he had

2167
02:05:48,280 --> 02:05:52,440
Speaker 1: every reason to want me hanging around him because I

2168
02:05:52,600 --> 02:05:55,440
Speaker 1: have hands and big, bad tools. And he knew I

2169
02:05:55,560 --> 02:05:59,440
Speaker 1: hated feral cats. I mean he watched me chase them away.

2170
02:05:59,800 --> 02:06:01,840
Speaker 1: He didn't know about the bad words I was saying

2171
02:06:01,880 --> 02:06:03,800
Speaker 1: to those cats, but he knew I hated Ferrell cats,

2172
02:06:03,840 --> 02:06:07,800
Speaker 1: and he hated Ferrell And there was protection there, reduced predator.

2173
02:06:08,720 --> 02:06:10,800
Speaker 1: He got to hang out in the sunshine in the

2174
02:06:10,840 --> 02:06:13,920
Speaker 1: middle of the day because I was there. Normally Fox

2175
02:06:13,960 --> 02:06:15,840
Speaker 1: wouldn't be able to just you know, not with dogs

2176
02:06:15,920 --> 02:06:18,800
Speaker 1: and feral cats around and eagles. So he got a

2177
02:06:18,880 --> 02:06:23,720
Speaker 1: huge advantage from being my friend. Huge. Okay, but what

2178
02:06:23,880 --> 02:06:25,960
Speaker 1: is he eating all this time? Oh, he was a

2179
02:06:26,000 --> 02:06:28,320
Speaker 1: great hunter, So he's eating lots and lots and lots

2180
02:06:28,360 --> 02:06:33,840
Speaker 1: of voles, mostly voles. That's I think that's Chapter three

2181
02:06:33,920 --> 02:06:36,040
Speaker 1: of the book is called Vole Forest, and it explains

2182
02:06:36,120 --> 02:06:40,880
Speaker 1: how I accidentally he got a huge forest filled with

2183
02:06:41,000 --> 02:06:42,840
Speaker 1: voles on my property. I didn't mean to, but I

2184
02:06:43,000 --> 02:06:45,440
Speaker 1: was just to make a long story short, I just

2185
02:06:45,560 --> 02:06:49,520
Speaker 1: wasn't paying attention to my property and I had this massive,

2186
02:06:49,800 --> 02:06:52,240
Speaker 1: massive amount of voles. I mean they run over my

2187
02:06:52,360 --> 02:06:54,520
Speaker 1: feet while I was walking. I mean one of them

2188
02:06:54,640 --> 02:06:58,400
Speaker 1: gave birth on my boot while I'm not kidding, just

2189
02:06:58,520 --> 02:07:02,440
Speaker 1: because just because the grassload and there was so it

2190
02:07:02,760 --> 02:07:05,000
Speaker 1: ended up just growing too high with the weeds those

2191
02:07:05,080 --> 02:07:07,200
Speaker 1: kind of woody things, and then it lays down and

2192
02:07:07,280 --> 02:07:09,600
Speaker 1: creates that kind of like that sort of buffer between

2193
02:07:09,640 --> 02:07:14,480
Speaker 1: the ground and the animals that hunt voles from the

2194
02:07:14,600 --> 02:07:17,040
Speaker 1: air aren't going to go in through woody things that

2195
02:07:17,120 --> 02:07:21,040
Speaker 1: are thorny, and animals that take skunks take bowls, foxes

2196
02:07:21,080 --> 02:07:23,680
Speaker 1: take fowls, badgers, animals that come in from the side,

2197
02:07:23,840 --> 02:07:26,680
Speaker 1: especially animals that pounds like a fox, they can't get

2198
02:07:26,720 --> 02:07:29,480
Speaker 1: in either. So the voles just start proliferating and proliferating

2199
02:07:29,520 --> 02:07:32,120
Speaker 1: and proliferating until this is huge amount of them. I mean,

2200
02:07:32,160 --> 02:07:35,560
Speaker 1: they were just everywhere so that really attracted him. But

2201
02:07:35,640 --> 02:07:38,440
Speaker 1: he was a good hunter anyway. Even after I figured

2202
02:07:38,440 --> 02:07:41,400
Speaker 1: out how to kind of limit the vols a little bit,

2203
02:07:41,480 --> 02:07:43,160
Speaker 1: he was a terrific hunter. There were days when he

2204
02:07:43,280 --> 02:07:45,760
Speaker 1: had five bals piled up by my front doorsteps. He

2205
02:07:45,800 --> 02:07:51,120
Speaker 1: would wait, he would hunt. Yeah, I thought that he

2206
02:07:51,320 --> 02:07:54,960
Speaker 1: was giving them to me, But he wasn't. But I

2207
02:07:55,080 --> 02:07:57,200
Speaker 1: thought he was. Was it just the same you feel

2208
02:07:57,240 --> 02:07:58,720
Speaker 1: it was a safe place to portal. It was just

2209
02:07:58,920 --> 02:08:02,120
Speaker 1: because he figured out the only place the magpies wouldn't

2210
02:08:02,240 --> 02:08:04,920
Speaker 1: steal them. Magpies were really aggressive, and they'll come to

2211
02:08:05,040 --> 02:08:07,160
Speaker 1: my steps, but they won't come right to the door.

2212
02:08:07,360 --> 02:08:09,640
Speaker 1: That's like the limit for magpies. So he would put

2213
02:08:09,680 --> 02:08:11,920
Speaker 1: them right up the door so that the magpies wouldn't

2214
02:08:11,920 --> 02:08:14,880
Speaker 1: steal them, and he would keep hunting until he had

2215
02:08:15,000 --> 02:08:17,560
Speaker 1: so men enough to fill his whole mouth. Then he

2216
02:08:17,560 --> 02:08:19,440
Speaker 1: would gather them all up and run them up the

2217
02:08:19,520 --> 02:08:21,640
Speaker 1: hill to where the kids were, because he was helping

2218
02:08:21,720 --> 02:08:23,760
Speaker 1: feed them. But if he had to just run up

2219
02:08:23,760 --> 02:08:25,480
Speaker 1: and down, up and down every time he killed one,

2220
02:08:25,480 --> 02:08:27,800
Speaker 1: it wouldn't be very efficient. So he liked to pile

2221
02:08:27,960 --> 02:08:30,400
Speaker 1: his dead things up and then grab them and then

2222
02:08:30,480 --> 02:08:32,720
Speaker 1: bring them up the hill, so he wasn't giving them

2223
02:08:32,760 --> 02:08:35,440
Speaker 1: to me. He was just he was just leaving them

2224
02:08:35,480 --> 02:08:38,960
Speaker 1: there because magpies wouldn't eat anything on my doorstep. You

2225
02:08:39,080 --> 02:08:42,120
Speaker 1: knew that, but I didn't. Yeah, you mentioned it was

2226
02:08:42,160 --> 02:08:45,480
Speaker 1: how vain I was present from the fox. You mentioned

2227
02:08:47,240 --> 02:08:51,200
Speaker 1: how short lived they are. Yeah, yeah, I was a

2228
02:08:51,240 --> 02:08:53,240
Speaker 1: little bit if I think if you'd I came here

2229
02:08:53,320 --> 02:08:54,320
Speaker 1: with what you said, But it's like it's like a

2230
02:08:54,440 --> 02:08:56,600
Speaker 1: few years, right, Yeah, like about a guess. I don't know,

2231
02:08:56,600 --> 02:08:58,200
Speaker 1: I would have I would have thrown out seven or

2232
02:08:58,240 --> 02:09:00,080
Speaker 1: eight years. I don't know why, probably in his do

2233
02:09:00,560 --> 02:09:03,800
Speaker 1: But they're wild animals don't live very long. Yeah. I

2234
02:09:03,960 --> 02:09:07,480
Speaker 1: think that's probably one reason why their personalities might be

2235
02:09:07,520 --> 02:09:10,040
Speaker 1: a little bit different than human personalities. You think back

2236
02:09:10,080 --> 02:09:11,840
Speaker 1: to what your life was like when you were a

2237
02:09:11,880 --> 02:09:14,000
Speaker 1: twenty year old. You were talking about crazy things that

2238
02:09:14,080 --> 02:09:17,320
Speaker 1: you've done, but and how you think about those near

2239
02:09:17,360 --> 02:09:20,520
Speaker 1: death experiences. But you think about those near death experiences

2240
02:09:20,600 --> 02:09:23,080
Speaker 1: differently based on what decade you are in your life.

2241
02:09:23,440 --> 02:09:26,000
Speaker 1: But they don't have like decades of their life. They

2242
02:09:26,640 --> 02:09:31,280
Speaker 1: it's short lived animals, But for us humans, a twenty

2243
02:09:31,400 --> 02:09:34,120
Speaker 1: year old human has a little bit different person. I mean,

2244
02:09:34,160 --> 02:09:37,000
Speaker 1: you don't change the person's genetics. It's the exact same person,

2245
02:09:37,560 --> 02:09:40,880
Speaker 1: but your personality changes when you're twenty versus when you're eighty.

2246
02:09:41,000 --> 02:09:44,240
Speaker 1: Probably your idea about what a near death experience is,

2247
02:09:44,320 --> 02:09:47,720
Speaker 1: even your idea about the passage of time exactly, exactly exactly.

2248
02:09:47,840 --> 02:09:50,160
Speaker 1: And I read somewhere with someone who was trying to

2249
02:09:50,320 --> 02:09:55,080
Speaker 1: capture when we hear that of whatever, a fly or whatever,

2250
02:09:55,240 --> 02:09:59,240
Speaker 1: some aquatic insect has a day or two days right

2251
02:10:00,000 --> 02:10:04,320
Speaker 1: as it emerges, and and someone's describing, though I can't

2252
02:10:04,320 --> 02:10:06,360
Speaker 1: hear who was talking about this with their talking about

2253
02:10:06,880 --> 02:10:09,960
Speaker 1: when you go to swat a fly, right, So in

2254
02:10:10,040 --> 02:10:13,080
Speaker 1: your mind you're like it's fast like right, but the

2255
02:10:13,120 --> 02:10:16,880
Speaker 1: flies mine. It's like there's this um, there's this thing

2256
02:10:17,000 --> 02:10:22,200
Speaker 1: that's that's coming that I'll eventually but I'll eventually need

2257
02:10:22,320 --> 02:10:26,480
Speaker 1: to take into consideration and avoid. You know, it's just

2258
02:10:26,560 --> 02:10:28,280
Speaker 1: like it's tripped like who you know, who really knows,

2259
02:10:28,320 --> 02:10:31,920
Speaker 1: but like it's it's like it's comprehension of time is

2260
02:10:32,120 --> 02:10:34,560
Speaker 1: thousands of light years away, there's up there, it's going

2261
02:10:34,640 --> 02:10:37,560
Speaker 1: to hit the earth. Yeah, that's right. You look at trees,

2262
02:10:37,600 --> 02:10:39,520
Speaker 1: you know, you look at trees that are hundreds of

2263
02:10:39,560 --> 02:10:42,200
Speaker 1: years old, like is it you know, not that it's

2264
02:10:42,240 --> 02:10:46,880
Speaker 1: regarding time, but just whatever the experience is, isn't you know?

2265
02:10:47,680 --> 02:10:50,200
Speaker 1: We're sort of built in. I think that we're born,

2266
02:10:51,200 --> 02:10:54,400
Speaker 1: and we pretty quickly get a grasp of kind of

2267
02:10:54,480 --> 02:10:56,560
Speaker 1: what a year is. We quickly get to grasp of

2268
02:10:56,680 --> 02:11:00,920
Speaker 1: when people die, and we start to measure because we

2269
02:11:01,040 --> 02:11:03,480
Speaker 1: have a like there's a fair sense like if you're

2270
02:11:03,520 --> 02:11:06,160
Speaker 1: live right now, you know you're going to be around

2271
02:11:06,200 --> 02:11:09,920
Speaker 1: eighty and you start taking that stuff off, man, I know,

2272
02:11:10,160 --> 02:11:13,840
Speaker 1: and then you realize that it's it's unavoidable, and there

2273
02:11:13,960 --> 02:11:17,280
Speaker 1: comes this awareness of things are things going by time

2274
02:11:17,360 --> 02:11:21,520
Speaker 1: going back differently and you're burning a fuse and I

2275
02:11:21,600 --> 02:11:24,280
Speaker 1: don't know what you know? Maybe you know now better,

2276
02:11:24,360 --> 02:11:25,680
Speaker 1: but I don't know what a fox. I don't know

2277
02:11:25,720 --> 02:11:29,000
Speaker 1: if a fox is aware that it's it's taken, I don't,

2278
02:11:29,040 --> 02:11:31,560
Speaker 1: but it seems like it would be innate. I think

2279
02:11:31,640 --> 02:11:35,560
Speaker 1: it's one of the reasons why humans have often set

2280
02:11:35,640 --> 02:11:39,400
Speaker 1: themselves apart from other animals and always forget even your

2281
02:11:39,760 --> 02:11:43,160
Speaker 1: even your students, even your undergraduate students in the middle

2282
02:11:43,200 --> 02:11:46,160
Speaker 1: of a biology class, forget that humans are animals and

2283
02:11:46,280 --> 02:11:49,160
Speaker 1: there's only six kingdom of life, and there's an animal

2284
02:11:49,240 --> 02:11:51,560
Speaker 1: kingdom and where in it, there's not a separate kingdom

2285
02:11:51,680 --> 02:11:55,320
Speaker 1: for humans. So we are animals, but people forget that.

2286
02:11:55,480 --> 02:11:57,600
Speaker 1: But one way that we have been different from most

2287
02:11:57,640 --> 02:12:00,600
Speaker 1: of the animals that are around in modern America is

2288
02:12:00,640 --> 02:12:03,760
Speaker 1: that we're so much longer lived. And that's that's even

2289
02:12:03,880 --> 02:12:06,680
Speaker 1: more drastic because maybe a hundred or two hundred years

2290
02:12:06,720 --> 02:12:09,840
Speaker 1: ago we lived maybe sixty years, and now it's eighty.

2291
02:12:09,920 --> 02:12:11,800
Speaker 1: But maybe it's going to be even longer than that.

2292
02:12:11,880 --> 02:12:14,240
Speaker 1: But the lifespan of the animals hasn't changed, so we

2293
02:12:14,320 --> 02:12:17,480
Speaker 1: are separating ourselves a little bit in terms of our longevity.

2294
02:12:17,520 --> 02:12:22,080
Speaker 1: Bears can live for years, grisly bears, large animals can,

2295
02:12:22,160 --> 02:12:24,960
Speaker 1: But we're wiping out the larger animals because they threaten us.

2296
02:12:25,000 --> 02:12:27,320
Speaker 1: So there aren't a lot of large animals around. But

2297
02:12:27,440 --> 02:12:29,440
Speaker 1: you know, bison our large animals, and they probably don't

2298
02:12:29,440 --> 02:12:32,280
Speaker 1: live more than a sixteen years. So we do live

2299
02:12:32,320 --> 02:12:35,400
Speaker 1: a lot longer. And if the length that you live

2300
02:12:36,440 --> 02:12:39,720
Speaker 1: changes your personality, then it would give you a reason

2301
02:12:39,800 --> 02:12:42,440
Speaker 1: to believe that humans we have a little bit different

2302
02:12:42,440 --> 02:12:46,120
Speaker 1: personality than foxes. It doesn't mean that other animals don't

2303
02:12:46,200 --> 02:12:49,640
Speaker 1: have a personality, and I think that I don't believe

2304
02:12:49,680 --> 02:12:53,120
Speaker 1: that humans are the only animals that have certain personality traits.

2305
02:12:53,200 --> 02:12:58,120
Speaker 1: I think that anthropomorphism is just been mischaracterized and it's

2306
02:12:58,160 --> 02:13:00,600
Speaker 1: based on assumptions that just don't make any ense anymore.

2307
02:13:00,760 --> 02:13:02,520
Speaker 1: I want to talk, Well, you got to define it,

2308
02:13:02,640 --> 02:13:04,560
Speaker 1: but I want to talk about anthropomorphism, but first I

2309
02:13:04,600 --> 02:13:07,960
Speaker 1: want to talk and maybe you answered it. Uh what

2310
02:13:08,120 --> 02:13:11,600
Speaker 1: what's the fox's lifespan? Just a few years? Yeah, So

2311
02:13:11,760 --> 02:13:13,920
Speaker 1: you get into this routine with this thing and it's

2312
02:13:14,000 --> 02:13:17,880
Speaker 1: like you know that it's no, it's won't last, that's right,

2313
02:13:18,240 --> 02:13:21,040
Speaker 1: And I and I thought that was really stupid. I

2314
02:13:21,120 --> 02:13:25,080
Speaker 1: remember I was jogging and thinking to myself, this is

2315
02:13:25,440 --> 02:13:28,920
Speaker 1: really really dumb. Why am I spending all this I

2316
02:13:29,040 --> 02:13:30,680
Speaker 1: was spending a lot of time. I mean, my whole

2317
02:13:30,720 --> 02:13:32,880
Speaker 1: life was pretty much geared around you have to be

2318
02:13:33,040 --> 02:13:38,600
Speaker 1: home at four or fifteen. Um, that's just insane. An

2319
02:13:38,640 --> 02:13:40,440
Speaker 1: animal that's just going to be gone on the blink

2320
02:13:40,480 --> 02:13:43,120
Speaker 1: of an eye. But you know, in Paradise Valley there's

2321
02:13:43,280 --> 02:13:46,600
Speaker 1: all those rainbows out there, and double rainbows are really common.

2322
02:13:46,680 --> 02:13:48,760
Speaker 1: And I was jogging on this trail and suddenly this

2323
02:13:48,920 --> 02:13:52,560
Speaker 1: rainbow came up and then it doubled and you can

2324
02:13:52,640 --> 02:13:55,280
Speaker 1: see end to end. You can still see Ndan from

2325
02:13:55,280 --> 02:13:57,000
Speaker 1: my house, but I could see Undan from where I

2326
02:13:57,080 --> 02:13:59,400
Speaker 1: was jogging because it's so open country out there. And

2327
02:13:59,480 --> 02:14:01,480
Speaker 1: then I really lies that a rainbow, I mean, how

2328
02:14:01,520 --> 02:14:04,560
Speaker 1: long does that last? And I stopped to watch it.

2329
02:14:04,760 --> 02:14:06,480
Speaker 1: I mean I didn't just like, oh, it's I'm not

2330
02:14:06,520 --> 02:14:09,320
Speaker 1: going to waste my time with a rainbow because because

2331
02:14:09,400 --> 02:14:12,640
Speaker 1: it's short lived. And I just and that that made

2332
02:14:12,720 --> 02:14:15,320
Speaker 1: up my mind. I thought, that's so stupid to worry

2333
02:14:15,320 --> 02:14:18,040
Speaker 1: about how long something lives when a rainbow doesn't. And

2334
02:14:18,120 --> 02:14:19,840
Speaker 1: I'm not the only one. When you're up in the

2335
02:14:19,920 --> 02:14:22,200
Speaker 1: mountains and you look down you can see cars, I

2336
02:14:22,240 --> 02:14:25,880
Speaker 1: mean they just stop. People that are like going ninety

2337
02:14:25,920 --> 02:14:27,560
Speaker 1: miles an hour to get to the airport and they're like,

2338
02:14:27,640 --> 02:14:29,760
Speaker 1: at whatever, miss people just stop when they see the

2339
02:14:29,800 --> 02:14:32,000
Speaker 1: double rainbows do that and these you know, people have

2340
02:14:32,120 --> 02:14:37,040
Speaker 1: seen hundreds of rainbows and they just stop. Anyway, it

2341
02:14:37,120 --> 02:14:39,560
Speaker 1: doesn't really matter how long it lives. How does the fox?

2342
02:14:39,680 --> 02:14:41,720
Speaker 1: Can you tell you? Are you afraid of ruining those

2343
02:14:41,720 --> 02:14:44,440
Speaker 1: story if you tell how the fox dies? Yeah? I

2344
02:14:44,560 --> 02:14:49,520
Speaker 1: am glad you asked I'm not telling you how the

2345
02:14:49,560 --> 02:14:52,920
Speaker 1: fox died. Listen, we got real numbers here. And these

2346
02:14:52,960 --> 02:14:56,000
Speaker 1: people is reading the book right now. There you go,

2347
02:14:56,200 --> 02:14:58,640
Speaker 1: thank you. Yeah, Carmen is reading the boat. Do you

2348
02:14:58,720 --> 02:15:03,520
Speaker 1: want to I'll find out. I don't want to know

2349
02:15:03,560 --> 02:15:07,360
Speaker 1: how the thoughts did the talk about anthropomorphism, because that's

2350
02:15:07,360 --> 02:15:09,440
Speaker 1: what everybody's gonna say. That's what a guy like me

2351
02:15:09,480 --> 02:15:12,320
Speaker 1: is going to say. They're gonna say, oh, you're anthropomorphiz Yeah,

2352
02:15:12,400 --> 02:15:15,560
Speaker 1: I know everybody. I mean, I've heard that so many times.

2353
02:15:15,680 --> 02:15:19,120
Speaker 1: I mean, that's your unapologetic of course. I mean as

2354
02:15:19,160 --> 02:15:22,040
Speaker 1: a part grinder, as a professor and you know, students,

2355
02:15:22,120 --> 02:15:24,400
Speaker 1: and that a word is a really it's a ward

2356
02:15:24,480 --> 02:15:26,320
Speaker 1: that a lot of people in the public like to

2357
02:15:26,520 --> 02:15:30,120
Speaker 1: say because they think that it's really pedantic. I think,

2358
02:15:30,200 --> 02:15:33,040
Speaker 1: but it's only just now becoming pedantic. I think people

2359
02:15:33,080 --> 02:15:36,800
Speaker 1: think it makes them sound sophisticated and pro science if

2360
02:15:36,880 --> 02:15:40,040
Speaker 1: they accuse everybody of being anthropomorphic. But I think we

2361
02:15:40,160 --> 02:15:42,640
Speaker 1: need to first, you got it, You first got to identify.

2362
02:15:42,960 --> 02:15:49,120
Speaker 1: You have to if it means that you are crediting

2363
02:15:50,080 --> 02:15:56,840
Speaker 1: human traits to an animal that's not human, so human

2364
02:15:57,160 --> 02:16:00,520
Speaker 1: human trait might be for example, this is. One of

2365
02:16:00,560 --> 02:16:03,560
Speaker 1: my students gave me this. Um. She said that Adam

2366
02:16:03,640 --> 02:16:11,840
Speaker 1: and Eve experienced or exhibited modesty, and she said, that's

2367
02:16:12,040 --> 02:16:16,040
Speaker 1: a trait that we think only humans have. You mean

2368
02:16:16,120 --> 02:16:18,760
Speaker 1: when they covered themselves with leaves. Yeah, I never I

2369
02:16:19,160 --> 02:16:21,120
Speaker 1: needed one of my undergraduates explain that to me. And

2370
02:16:21,120 --> 02:16:23,080
Speaker 1: I really loved that. It was part of it had

2371
02:16:23,120 --> 02:16:24,880
Speaker 1: to do with sort of like Neanderthals. But it's a

2372
02:16:24,960 --> 02:16:27,200
Speaker 1: question that I used to ask. They were introduced to

2373
02:16:27,440 --> 02:16:32,440
Speaker 1: shame Bible person, so maybe it's shame, but um, yeah,

2374
02:16:32,760 --> 02:16:35,360
Speaker 1: they were. They were made to feel shame. Okay, they're

2375
02:16:35,360 --> 02:16:37,840
Speaker 1: made to feel shame, and so that's a human trait.

2376
02:16:38,280 --> 02:16:42,640
Speaker 1: And then if you see two little chipmunks mating, um,

2377
02:16:43,959 --> 02:16:46,280
Speaker 1: you say to yourself, they're just out there mating and

2378
02:16:46,360 --> 02:16:48,160
Speaker 1: they don't care that all these people are standing around

2379
02:16:48,280 --> 02:16:52,480
Speaker 1: watching because they don't. They have no shame. They experience

2380
02:16:52,600 --> 02:16:57,800
Speaker 1: no shame. But really, but that's voyeur. I'm a part

2381
02:16:57,840 --> 02:17:07,440
Speaker 1: of the humansitionism. Apart the voy is you're the voyrus

2382
02:17:07,520 --> 02:17:12,560
Speaker 1: for watching the animals or exhibitionists between the and role

2383
02:17:12,600 --> 02:17:15,080
Speaker 1: play and exhibit. This is the most risk ay episode

2384
02:17:15,080 --> 02:17:17,039
Speaker 1: of the Medior podcast. Will go walk out and protest.

2385
02:17:17,080 --> 02:17:18,400
Speaker 1: He's like, I did sign up for this kind of stuff.

2386
02:17:18,400 --> 02:17:20,760
Speaker 1: I'm a family. Now this is what I want. You

2387
02:17:21,640 --> 02:17:23,720
Speaker 1: all went to the University of Montana, finally going to

2388
02:17:23,800 --> 02:17:25,800
Speaker 1: direction that Phil can get on board with. Yeah, the

2389
02:17:26,120 --> 02:17:30,720
Speaker 1: uh the giant red squirrels that overran the campus on

2390
02:17:30,800 --> 02:17:33,720
Speaker 1: the University of Montana. That exact scene you just described

2391
02:17:33,720 --> 02:17:37,080
Speaker 1: played out many times during my stamped at you m

2392
02:17:38,320 --> 02:17:40,840
Speaker 1: you went to You have m too, writing, you studied

2393
02:17:40,879 --> 02:17:44,760
Speaker 1: writing them good school, you went to them. So now

2394
02:17:47,280 --> 02:17:49,080
Speaker 1: I don't know what that makes. It makes us grizz

2395
02:17:49,240 --> 02:17:52,600
Speaker 1: because you're wrong to the undergraduate school. So even when

2396
02:17:52,640 --> 02:17:56,000
Speaker 1: I'm in my regalia, maybe I shouldn't say this on there,

2397
02:17:57,080 --> 02:18:00,040
Speaker 1: my regalias from the University of Montana, my own to

2398
02:18:00,120 --> 02:18:04,520
Speaker 1: graduate school instead of my PhD. Because I just think

2399
02:18:04,560 --> 02:18:06,880
Speaker 1: you always belonged to under gradgate school, don't you. I don't.

2400
02:18:06,920 --> 02:18:08,600
Speaker 1: I don't know. I never I don't look at those

2401
02:18:08,640 --> 02:18:10,440
Speaker 1: institutions in that way. I felt. I felt it was

2402
02:18:10,560 --> 02:18:14,000
Speaker 1: very transactional and like I don't have any sort of

2403
02:18:14,320 --> 02:18:18,120
Speaker 1: when they call about fundraising, do you just help everybody? No,

2404
02:18:18,360 --> 02:18:20,320
Speaker 1: I just have things I'm dedicated to. But it's like

2405
02:18:20,360 --> 02:18:23,240
Speaker 1: I just viewed it as a transactional relationship. Like I

2406
02:18:24,120 --> 02:18:29,280
Speaker 1: I you know, I go to Whale Entire here in town. Okay, um,

2407
02:18:29,959 --> 02:18:32,960
Speaker 1: Like I don't imagine Whale Entire calling me wanting me

2408
02:18:33,000 --> 02:18:35,640
Speaker 1: to send them extra money. Like we engage in a

2409
02:18:35,720 --> 02:18:39,920
Speaker 1: transaction and the transaction is done. Don't call me later

2410
02:18:39,959 --> 02:18:41,920
Speaker 1: and be like, hey, you know you had your oil

2411
02:18:42,040 --> 02:18:44,400
Speaker 1: change here and bought tires here. How about now just

2412
02:18:44,480 --> 02:18:46,640
Speaker 1: sending us money for nothing? It was I feel it

2413
02:18:46,760 --> 02:18:49,280
Speaker 1: was very transactional. But I want to get back. When

2414
02:18:49,280 --> 02:18:51,520
Speaker 1: I dropped out of the University of Montana, nobody ever

2415
02:18:51,640 --> 02:18:54,840
Speaker 1: called and said, hey, really missed you in class. Did

2416
02:18:54,920 --> 02:18:58,680
Speaker 1: you go back? I never did. No. No, Mom listens

2417
02:18:58,720 --> 02:19:04,320
Speaker 1: to these two and so back. You know. Okay, anthropomorphism,

2418
02:19:04,480 --> 02:19:05,960
Speaker 1: so you know what it means. So you get what

2419
02:19:06,080 --> 02:19:08,119
Speaker 1: it means now where you're sorry, Yeah, I just want

2420
02:19:08,160 --> 02:19:10,240
Speaker 1: to make sure everybody. I want to make sure everybody's tracking.

2421
02:19:10,879 --> 02:19:16,440
Speaker 1: So if you pretend that an animal has a certain quality,

2422
02:19:16,760 --> 02:19:19,720
Speaker 1: a certain personality trait, people think you're pretending that it

2423
02:19:19,920 --> 02:19:23,600
Speaker 1: couldn't possibly Then they say you're being anthropomorphic because it's

2424
02:19:23,640 --> 02:19:29,200
Speaker 1: not possible that an animal could possibly feel loyalty or pain.

2425
02:19:29,440 --> 02:19:31,240
Speaker 1: I mean, I think I give an example. You are

2426
02:19:31,240 --> 02:19:33,480
Speaker 1: at about Buffalo, so you'll know this example from my book.

2427
02:19:33,520 --> 02:19:36,560
Speaker 1: Are you familiar with Dr Hornaday's work? Okay, doky, So

2428
02:19:37,000 --> 02:19:39,800
Speaker 1: I've read Horniday's journals. I love them. That's another plug.

2429
02:19:40,120 --> 02:19:43,960
Speaker 1: Dr Hornaday's journals are fantastic. And so he emerged as

2430
02:19:44,000 --> 02:19:46,400
Speaker 1: a very controversial figure. He did. But you know, his

2431
02:19:46,520 --> 02:19:49,720
Speaker 1: family called me when I finished publishing an article about him.

2432
02:19:50,360 --> 02:19:52,200
Speaker 1: They said it was the best piece they've ever It

2433
02:19:52,200 --> 02:19:53,760
Speaker 1: wasn't just about him, it was about Buffalo, but they

2434
02:19:53,760 --> 02:19:55,440
Speaker 1: said it was the best piece they've ever read about him.

2435
02:19:55,440 --> 02:19:58,680
Speaker 1: And I was not trying to be complimentary. I was

2436
02:19:58,800 --> 02:20:01,080
Speaker 1: very objective. I mean I talked about all his warts.

2437
02:20:01,120 --> 02:20:02,920
Speaker 1: There were many of them. He had a lot of prejudices,

2438
02:20:03,040 --> 02:20:08,320
Speaker 1: but he did a lot of important things. Anyway, Buffalo cows,

2439
02:20:08,440 --> 02:20:11,200
Speaker 1: the females were getting when they were getting shot a

2440
02:20:11,280 --> 02:20:14,959
Speaker 1: lot in the late eighteen hundreds. When one falls from

2441
02:20:15,000 --> 02:20:16,960
Speaker 1: a bullet, then the other ones just all kind of

2442
02:20:17,080 --> 02:20:22,680
Speaker 1: stand around. And Hornaday said, these animals are complicit in

2443
02:20:22,760 --> 02:20:24,640
Speaker 1: their own I mean, he wanted to save them. He

2444
02:20:24,760 --> 02:20:28,160
Speaker 1: was furious, but still he said they're complicit in their

2445
02:20:28,200 --> 02:20:33,240
Speaker 1: own extinction because there. He called them stupid brutes because

2446
02:20:33,320 --> 02:20:36,400
Speaker 1: they just stand around and one's gone down. The hunters,

2447
02:20:36,640 --> 02:20:38,800
Speaker 1: probably on the Tutu train, are just going to keep shooting,

2448
02:20:38,800 --> 02:20:40,640
Speaker 1: and they're going to shoot all of them. Yeah, and

2449
02:20:40,680 --> 02:20:46,240
Speaker 1: the hide hunters would even manipulate that. And so how

2450
02:20:48,000 --> 02:20:50,520
Speaker 1: and why don't you believe some of the stories that

2451
02:20:50,640 --> 02:20:53,880
Speaker 1: say that they simply had loyalty. Now, when that character

2452
02:20:54,120 --> 02:20:59,400
Speaker 1: was his name Custer, when Custer um did his last retreat,

2453
02:21:00,040 --> 02:21:05,360
Speaker 1: unning retreat, everybody tried to turn that into his They

2454
02:21:05,440 --> 02:21:07,120
Speaker 1: call it his stand, even though he was doing a

2455
02:21:07,200 --> 02:21:12,240
Speaker 1: running retreat because it was considered honorable to stand in

2456
02:21:12,320 --> 02:21:16,840
Speaker 1: the face of danger. It makes you loyal and brave

2457
02:21:17,200 --> 02:21:20,360
Speaker 1: because he was a human, and that's a human trait.

2458
02:21:20,480 --> 02:21:25,480
Speaker 1: But if an animal stands with her comrades, she's an idiot.

2459
02:21:25,680 --> 02:21:31,680
Speaker 1: They're foolish, you see. He Hornaday wasn't able to see that.

2460
02:21:31,879 --> 02:21:35,560
Speaker 1: It's possible that buffalo might have other characteristics, that they

2461
02:21:35,640 --> 02:21:40,320
Speaker 1: might just be simply standing with their comrades because they're royal.

2462
02:21:40,840 --> 02:21:43,200
Speaker 1: I don't know the answer, but Hornaday doesn't know the

2463
02:21:43,200 --> 02:21:45,440
Speaker 1: answer either. I mean, both Horniday and I are working

2464
02:21:45,600 --> 02:21:48,959
Speaker 1: from a bias and from very limited data. And there's

2465
02:21:49,000 --> 02:21:51,400
Speaker 1: really no way to know. I mean, sometimes science doesn't

2466
02:21:51,440 --> 02:21:53,160
Speaker 1: have an answer for you. You just have to use

2467
02:21:53,200 --> 02:21:56,200
Speaker 1: your instincts, in your common sense. But neither Horniday nor

2468
02:21:56,320 --> 02:21:59,200
Speaker 1: I know what's going on. Really, we could both be wrong.

2469
02:21:59,680 --> 02:22:01,360
Speaker 1: I don't know, But all I know is that he

2470
02:22:01,480 --> 02:22:03,920
Speaker 1: didn't consider it, and I I just throw that out

2471
02:22:03,959 --> 02:22:06,640
Speaker 1: as a possibility. That's what I mean by anthropomorphism. So

2472
02:22:07,120 --> 02:22:10,960
Speaker 1: if I were to say those buffalo aren't stupid, they're

2473
02:22:11,000 --> 02:22:15,840
Speaker 1: just they're there because they're loyal. They're standing with their

2474
02:22:15,879 --> 02:22:19,520
Speaker 1: comments because they're loyal, then you, if you're pedantic, would

2475
02:22:19,520 --> 02:22:22,280
Speaker 1: say to me, so anthropomorphic, Raven, get the hell out

2476
02:22:22,320 --> 02:22:24,720
Speaker 1: of here. But but couldn't you Also, because we often

2477
02:22:24,760 --> 02:22:28,600
Speaker 1: talk about um and teacher trying to teach our kids that,

2478
02:22:28,879 --> 02:22:32,280
Speaker 1: you know, the animals not being stupid, that's like this

2479
02:22:32,480 --> 02:22:35,200
Speaker 1: human thing we want to we want to attribute to it.

2480
02:22:35,600 --> 02:22:39,119
Speaker 1: It's just being an animal. So is there another version

2481
02:22:40,320 --> 02:22:44,240
Speaker 1: where they're not they're not being anthropomorphic, but they're just

2482
02:22:44,360 --> 02:22:48,680
Speaker 1: being buffalo? Yeah, I think that, Well, go ahead here,

2483
02:22:48,760 --> 02:22:50,880
Speaker 1: But you wrote a wonderful book on buffalo. By the way,

2484
02:22:50,920 --> 02:22:53,120
Speaker 1: that's another plug I want to put in this. One

2485
02:22:53,160 --> 02:22:57,400
Speaker 1: of the books I own it's great. I rebel against Okay, one,

2486
02:22:57,480 --> 02:23:04,040
Speaker 1: I discourage my kids from like outrageous anthropomorphism. I discourage that.

2487
02:23:04,240 --> 02:23:07,920
Speaker 1: I also even more vehemently discourage them from describing animals

2488
02:23:07,959 --> 02:23:11,320
Speaker 1: as stupid. If something doesn't run away, I'm like, well,

2489
02:23:11,360 --> 02:23:15,040
Speaker 1: how is it benefits You're not a risk. Why is

2490
02:23:15,080 --> 02:23:17,520
Speaker 1: it beneficial for it to expend all kinds of energy

2491
02:23:17,920 --> 02:23:20,879
Speaker 1: and put itself in the in the way of potential

2492
02:23:21,000 --> 02:23:23,840
Speaker 1: harm by running headlong into some other area to get

2493
02:23:23,840 --> 02:23:26,080
Speaker 1: away from something that's not risky. So when you say,

2494
02:23:26,120 --> 02:23:29,200
Speaker 1: like the turkeys in our yard are stupid because it

2495
02:23:29,240 --> 02:23:32,640
Speaker 1: does stand there, um, maybe be really stupid for it

2496
02:23:32,720 --> 02:23:34,840
Speaker 1: to run away from something that's not threatening it and

2497
02:23:34,920 --> 02:23:37,240
Speaker 1: then it lands in the neighbor's fence and gets eaten

2498
02:23:37,280 --> 02:23:39,880
Speaker 1: by the neighbor's dog because it's retreating from something that

2499
02:23:39,959 --> 02:23:42,440
Speaker 1: pollses no risk. Anyways, maybe the turkey is really smart

2500
02:23:43,600 --> 02:23:46,480
Speaker 1: and doesn't run away, and that's perfect. I mean, that's

2501
02:23:46,520 --> 02:23:48,920
Speaker 1: the first step that we have to take. And in

2502
02:23:49,080 --> 02:23:53,080
Speaker 1: Hornaday's time, animals were always considered I mean, if they

2503
02:23:53,160 --> 02:23:56,920
Speaker 1: had a personality, even those stupidity is not technically a personality.

2504
02:23:57,240 --> 02:24:00,520
Speaker 1: It was always to negate the ability the animal and

2505
02:24:00,600 --> 02:24:02,720
Speaker 1: to say they're stupid and that they're dumb. And I

2506
02:24:02,840 --> 02:24:04,400
Speaker 1: agree with what both of you guys are saying. We

2507
02:24:04,480 --> 02:24:06,920
Speaker 1: need to get people and kids, especially away from the

2508
02:24:07,000 --> 02:24:10,960
Speaker 1: idea of constantly calling animals dumb when they you see skunks,

2509
02:24:11,160 --> 02:24:13,520
Speaker 1: uh getting run over by cars all the time? They're

2510
02:24:13,560 --> 02:24:16,959
Speaker 1: so dumb? Why are they? Because they can't evolve fast

2511
02:24:17,080 --> 02:24:20,720
Speaker 1: enough to realize that humans used to walk and then

2512
02:24:20,920 --> 02:24:22,960
Speaker 1: drag dogs with them, which are a little faster, and

2513
02:24:23,040 --> 02:24:25,400
Speaker 1: then horses, and in like a hundred years, we now

2514
02:24:25,480 --> 02:24:27,880
Speaker 1: have semi trucks do in a hundred miles an hour

2515
02:24:28,320 --> 02:24:31,040
Speaker 1: on the same trail that humans used to walk on.

2516
02:24:31,200 --> 02:24:36,760
Speaker 1: Skunks can't evolve fast enough. We can't either. It's not

2517
02:24:36,879 --> 02:24:39,840
Speaker 1: that they're stupid, it's just that they haven't evolved with

2518
02:24:40,160 --> 02:24:43,240
Speaker 1: semi trucks coming across the highway like this at these

2519
02:24:43,280 --> 02:24:46,840
Speaker 1: outrageous speeds. But we do have a bad habit of

2520
02:24:46,920 --> 02:24:51,120
Speaker 1: calling animals stupid when um, they do things that we

2521
02:24:51,320 --> 02:24:54,480
Speaker 1: don't Underlike you just explain to your kids why would

2522
02:24:54,480 --> 02:24:56,640
Speaker 1: it make sense? But I mean, how could they possibly

2523
02:24:56,720 --> 02:24:59,960
Speaker 1: know that that's something like a semi truck even exist?

2524
02:25:00,040 --> 02:25:02,120
Speaker 1: How could they possibly know that anything could move that

2525
02:25:02,320 --> 02:25:05,280
Speaker 1: fast on the road, so we should stop calling them stupid.

2526
02:25:05,520 --> 02:25:08,200
Speaker 1: So if you as an academic, like I don't know,

2527
02:25:08,400 --> 02:25:09,960
Speaker 1: what do you do you call yourself an academic? I

2528
02:25:10,000 --> 02:25:12,800
Speaker 1: don't know. Yeah, I've had trence, Sure, I know what

2529
02:25:12,879 --> 02:25:15,720
Speaker 1: you mean. I mean I I don't generally identify myself

2530
02:25:15,760 --> 02:25:19,360
Speaker 1: with labels because I generally prefer to identify myself with

2531
02:25:19,480 --> 02:25:21,880
Speaker 1: verbs rather than nouns. But yes, I teach at the

2532
02:25:21,959 --> 02:25:31,800
Speaker 1: universe the anthropomorphic. The anthropomorphism accusation being that you're training. Um,

2533
02:25:33,400 --> 02:25:37,080
Speaker 1: I don't know, like it's one animal. It's just one animal.

2534
02:25:37,080 --> 02:25:39,080
Speaker 1: I'm not accusing you of going against your training. I'm

2535
02:25:39,120 --> 02:25:44,400
Speaker 1: saying that, well, to do a work like this, no doubt,

2536
02:25:44,760 --> 02:25:49,120
Speaker 1: people from your world, from your professional world, we'll look

2537
02:25:49,160 --> 02:25:51,600
Speaker 1: at a work like this and maybe without reading it,

2538
02:25:52,080 --> 02:25:54,720
Speaker 1: but at the surface examination, it would be that you've

2539
02:25:54,760 --> 02:25:56,959
Speaker 1: gone over to the other side. Of course, of course,

2540
02:25:57,120 --> 02:26:01,200
Speaker 1: do you care that they think that? Um, I just

2541
02:26:01,440 --> 02:26:04,560
Speaker 1: expected it. I knew from that. I mean, I hid

2542
02:26:05,120 --> 02:26:07,560
Speaker 1: my relationship with the fox for ages and ages and ages.

2543
02:26:08,480 --> 02:26:12,960
Speaker 1: And I remember starting conversations with people that worked in

2544
02:26:13,000 --> 02:26:16,080
Speaker 1: the academy with me, and I would say something in

2545
02:26:16,120 --> 02:26:18,320
Speaker 1: the middle of a conversation, I might slip in something

2546
02:26:18,360 --> 02:26:22,120
Speaker 1: like oh and fox and I and then someone that

2547
02:26:22,240 --> 02:26:25,440
Speaker 1: a colleague, a close colleague, would say, just just as

2548
02:26:25,520 --> 02:26:28,040
Speaker 1: long as you're not being anthropomorphic, go ahead with your story.

2549
02:26:28,080 --> 02:26:35,240
Speaker 1: And you're like, gosh, oh, oh, absolutely a dirty secret,

2550
02:26:36,280 --> 02:26:40,000
Speaker 1: secret secret. Absolutely, I mean it's a taboo, it absolutely is.

2551
02:26:40,120 --> 02:26:41,920
Speaker 1: So yeah, I mean, I'm ready for it. But I

2552
02:26:42,920 --> 02:26:45,200
Speaker 1: understand that I've been listening to that complaint for a

2553
02:26:45,240 --> 02:26:47,600
Speaker 1: long time. But you asked if there's a middle ground,

2554
02:26:47,959 --> 02:26:51,080
Speaker 1: and of course there is a middle ground. It's just

2555
02:26:51,240 --> 02:26:55,600
Speaker 1: to say that there's a less of a separation between

2556
02:26:55,720 --> 02:26:59,160
Speaker 1: humans and other animals than we previously believed. I'm not

2557
02:26:59,360 --> 02:27:01,800
Speaker 1: saying that Whoman's and other animals have the exact same

2558
02:27:01,840 --> 02:27:05,440
Speaker 1: personality in the same emotions. There's so many animals. A

2559
02:27:05,560 --> 02:27:07,840
Speaker 1: worm is different than a beetle, is different than a

2560
02:27:07,879 --> 02:27:10,400
Speaker 1: bird in every bird species different. I'm just saying that

2561
02:27:10,560 --> 02:27:13,879
Speaker 1: we have this huge separation. Humans are way over here

2562
02:27:13,959 --> 02:27:16,240
Speaker 1: and all the other animals are there. It can't be

2563
02:27:16,440 --> 02:27:19,920
Speaker 1: possible that with the little differences in DNA that there

2564
02:27:19,959 --> 02:27:22,879
Speaker 1: are between the humans and chimps, it can't be possible

2565
02:27:23,000 --> 02:27:25,920
Speaker 1: that all of these traits that we think only belong

2566
02:27:26,000 --> 02:27:28,920
Speaker 1: to humans, and that chimps just simply eat and sleep

2567
02:27:29,040 --> 02:27:32,640
Speaker 1: and defecate and have sex. I mean, it's just not possible.

2568
02:27:35,120 --> 02:27:38,480
Speaker 1: Some of the things that we believe our only human traits,

2569
02:27:38,840 --> 02:27:41,240
Speaker 1: those have to recruit to other animals as well because

2570
02:27:41,280 --> 02:27:43,879
Speaker 1: our DNA. I mean, we're all related, as Darwin has

2571
02:27:44,360 --> 02:27:46,640
Speaker 1: told us. And if you guys haven't read Darwin yet,

2572
02:27:46,680 --> 02:27:48,400
Speaker 1: I there's a lot of plugs for him in my book.

2573
02:27:48,400 --> 02:27:50,920
Speaker 1: And I do try to explain as it fits in

2574
02:27:51,080 --> 02:27:53,840
Speaker 1: and very gently because the book's not encyclopedic and it's

2575
02:27:53,879 --> 02:27:57,120
Speaker 1: not like lecturing. It's a story. But I do have

2576
02:27:57,320 --> 02:27:59,400
Speaker 1: to mention Darwin once in a while because I have

2577
02:27:59,520 --> 02:28:04,120
Speaker 1: been trained biology and I think Darwin's work is amazing. Uh.

2578
02:28:04,320 --> 02:28:06,520
Speaker 1: One way to describe your book, would you say, like, oh,

2579
02:28:06,560 --> 02:28:11,279
Speaker 1: it's about a woman's relationship with a fox. Okay, okay,

2580
02:28:11,800 --> 02:28:17,400
Speaker 1: what um? What do you like? What did you want

2581
02:28:17,400 --> 02:28:19,440
Speaker 1: to accomplish with it? What would be like the deeper

2582
02:28:19,520 --> 02:28:22,600
Speaker 1: explanation of what the book is. It's really about how

2583
02:28:23,040 --> 02:28:27,480
Speaker 1: humans should fit into nature, how it's part of us

2584
02:28:27,560 --> 02:28:29,480
Speaker 1: and we're part of it, and we should stop using

2585
02:28:29,520 --> 02:28:33,560
Speaker 1: that old fashioned term mother nature as though it's some

2586
02:28:33,760 --> 02:28:39,880
Speaker 1: authoritarian figure. Um, you don't like mother Nature. Nature is

2587
02:28:39,920 --> 02:28:43,120
Speaker 1: a community. It's not an individual that we should revere

2588
02:28:43,959 --> 02:28:48,480
Speaker 1: and be afraid of an honor. We are part of nature.

2589
02:28:48,920 --> 02:28:51,720
Speaker 1: We fit into it, and if we fit into it

2590
02:28:51,800 --> 02:28:55,320
Speaker 1: as a community, of course we have responsibilities, but it's

2591
02:28:55,560 --> 02:28:58,680
Speaker 1: not something that we should revere and hold up over ourselves.

2592
02:28:58,760 --> 02:29:02,279
Speaker 1: It's our birthright. We're animals and we should fit ourselves.

2593
02:29:02,600 --> 02:29:04,320
Speaker 1: Let you run this by I'm working on a new

2594
02:29:04,400 --> 02:29:07,720
Speaker 1: tagline for you know, just my general Brandon what I do.

2595
02:29:08,040 --> 02:29:11,119
Speaker 1: And it goes like this, Mother Nature is my co pilot.

2596
02:29:12,160 --> 02:29:16,959
Speaker 1: That's good? You like that? Or is that too much

2597
02:29:17,160 --> 02:29:22,160
Speaker 1: reverence for Mother Nature? So how about um, how about

2598
02:29:22,520 --> 02:29:27,200
Speaker 1: God isn't my co pilot, He's the pilot. That's what

2599
02:29:27,320 --> 02:29:31,119
Speaker 1: our piloted Voyagers. When I worked at Voyagers National Park.

2600
02:29:31,280 --> 02:29:34,600
Speaker 1: That was that was on the airplane that we We

2601
02:29:34,720 --> 02:29:38,040
Speaker 1: had to take ships everywhere because we had Voyagers and

2602
02:29:38,280 --> 02:29:41,280
Speaker 1: Apostle Islands and Ile Royal So of course that's how

2603
02:29:41,320 --> 02:29:46,320
Speaker 1: you got around. Um, Mother Nature, are you seriously thinking

2604
02:29:46,320 --> 02:29:49,039
Speaker 1: about doing that? It's okay, I just I think Mother

2605
02:29:49,160 --> 02:29:53,200
Speaker 1: Nature kind of scares I mean, so your mother is

2606
02:29:53,240 --> 02:29:56,000
Speaker 1: probably some sweet little old lady. Right, but mother Nature

2607
02:29:56,080 --> 02:29:59,280
Speaker 1: does make it seem like, keep in mind, you're honest,

2608
02:29:59,360 --> 02:30:04,360
Speaker 1: is pagan? Yeah they are. They on the soulstaces. They

2609
02:30:04,840 --> 02:30:07,279
Speaker 1: drag logs around their house and whatnot. What's your business

2610
02:30:08,440 --> 02:30:12,480
Speaker 1: a tagline for what? Oh? Just my brand here within

2611
02:30:12,600 --> 02:30:16,120
Speaker 1: the meat eater, brandy brand, my personal brand. Oh but

2612
02:30:16,240 --> 02:30:20,480
Speaker 1: you're totally within meat eater. Oh yeah, he like yeah,

2613
02:30:20,560 --> 02:30:24,520
Speaker 1: he like, um, mother nature. He's like he makes materials.

2614
02:30:24,640 --> 02:30:28,800
Speaker 1: He's he like content producer, he like produces ideas and materials.

2615
02:30:28,959 --> 02:30:30,920
Speaker 1: You guys use that word mother nature a lot, huh.

2616
02:30:32,520 --> 02:30:38,200
Speaker 1: In the book I'm currently writing, which explores children and

2617
02:30:38,360 --> 02:30:43,000
Speaker 1: nature and how they relate. Um, I spent a lot

2618
02:30:43,080 --> 02:30:47,480
Speaker 1: of time talking about the perils of looking down at nature,

2619
02:30:48,959 --> 02:30:51,240
Speaker 1: and I talked a lot about the perils of looking up.

2620
02:30:52,360 --> 02:30:55,800
Speaker 1: And I tried to explore what I'm not a master

2621
02:30:55,879 --> 02:30:58,440
Speaker 1: at this, but I try to explore ways of how

2622
02:30:58,600 --> 02:31:01,360
Speaker 1: to encourage your children to see it like an idea island.

2623
02:31:01,480 --> 02:31:05,160
Speaker 1: And that's so right, that's the book. I mean, that's

2624
02:31:05,320 --> 02:31:07,640
Speaker 1: a more important part of the book. Are equally important part.

2625
02:31:07,640 --> 02:31:11,199
Speaker 1: I mean, obviously, friendship is really important, friendship in general,

2626
02:31:11,280 --> 02:31:13,480
Speaker 1: and then inner species friendship. But yeah, I want people

2627
02:31:13,520 --> 02:31:16,520
Speaker 1: to feel like they fit in with nature, that it's not.

2628
02:31:16,800 --> 02:31:18,920
Speaker 1: I forgot about the fact that some people look down

2629
02:31:18,959 --> 02:31:20,720
Speaker 1: in nature, and that I don't know very many people

2630
02:31:20,760 --> 02:31:23,160
Speaker 1: that do. But I understand that's so Really that comes

2631
02:31:23,160 --> 02:31:27,560
Speaker 1: from something a little bit. When I described looking down

2632
02:31:27,680 --> 02:31:30,280
Speaker 1: at it, I think that it would be it manifests

2633
02:31:30,360 --> 02:31:33,600
Speaker 1: more is very willing to be dismissive of it, right,

2634
02:31:33,879 --> 02:31:38,120
Speaker 1: and that where the most important species in the world,

2635
02:31:38,600 --> 02:31:41,280
Speaker 1: and we're in charge of everything, and we have dominion

2636
02:31:41,360 --> 02:31:43,640
Speaker 1: over everything. You don't find me people who would say, like,

2637
02:31:43,720 --> 02:31:48,000
Speaker 1: I hate nature. No, but an action and action uh,

2638
02:31:48,200 --> 02:31:53,680
Speaker 1: And an outside observer might look at certain actions and

2639
02:31:53,879 --> 02:31:58,480
Speaker 1: be like, man, that guy is not like nature. Sure,

2640
02:31:58,600 --> 02:32:01,960
Speaker 1: all the development that's going on around um Bozeman and

2641
02:32:02,040 --> 02:32:05,040
Speaker 1: then the valley and all over Montana. Some people, if

2642
02:32:05,120 --> 02:32:07,720
Speaker 1: you say, can we have a little bit of regulation

2643
02:32:07,800 --> 02:32:10,040
Speaker 1: here so that we keep a little bit of open space,

2644
02:32:10,120 --> 02:32:12,200
Speaker 1: so that we don't kill every living thing that's not

2645
02:32:12,480 --> 02:32:14,640
Speaker 1: human or dog or cat, And then people would say,

2646
02:32:15,080 --> 02:32:18,520
Speaker 1: would accuse you of not putting humans first. And so

2647
02:32:18,680 --> 02:32:21,080
Speaker 1: I understand that. I mean there are people and you'd argue,

2648
02:32:21,160 --> 02:32:25,480
Speaker 1: oh no, no, I am I'm thinking about humans right now. Yeah, yeah,

2649
02:32:26,560 --> 02:32:28,560
Speaker 1: that's what you're trying to teach your kids. So that

2650
02:32:28,720 --> 02:32:33,000
Speaker 1: makes is it a kid's book? No, it's it's for

2651
02:32:33,920 --> 02:32:37,360
Speaker 1: growing it's for growing ups. Yeah, but that's right, it's

2652
02:32:37,400 --> 02:32:41,600
Speaker 1: for it's for growing ups who have kids in their lives. Yeah. Yeah,

2653
02:32:41,680 --> 02:32:44,760
Speaker 1: and my book is that doesn't need to be your kids,

2654
02:32:44,800 --> 02:32:48,800
Speaker 1: but like yeah, yeah, yeah, yeah, that's right. That's that

2655
02:32:48,840 --> 02:32:51,720
Speaker 1: would be perfect. I mean, that's that sounds a lot

2656
02:32:51,800 --> 02:32:55,039
Speaker 1: like what I'm what I thought I did with Fox exactly,

2657
02:32:55,520 --> 02:32:59,960
Speaker 1: helping people to realize we're part of it and don't

2658
02:33:00,040 --> 02:33:02,480
Speaker 1: look down don't and definitely don't look up at it either,

2659
02:33:02,640 --> 02:33:05,600
Speaker 1: because I mean I have to revere it. We are it. Okay,

2660
02:33:05,680 --> 02:33:10,480
Speaker 1: give people the big plug, how to find it, how

2661
02:33:10,520 --> 02:33:12,760
Speaker 1: to find more about you? If you don't, do you

2662
02:33:12,800 --> 02:33:15,240
Speaker 1: want any found out about I know you're I know

2663
02:33:15,360 --> 02:33:19,480
Speaker 1: from from Cindy, you're publisher. I know you're very private. Yeah,

2664
02:33:19,600 --> 02:33:21,160
Speaker 1: so you don't even like to do this kind of

2665
02:33:21,200 --> 02:33:24,480
Speaker 1: stuff I have, right, this might be my first pot

2666
02:33:24,560 --> 02:33:27,120
Speaker 1: I think I've done some pods. This is my first

2667
02:33:27,160 --> 02:33:30,920
Speaker 1: big studio thing. Now I have a website, but it

2668
02:33:31,000 --> 02:33:33,280
Speaker 1: doesn't have but it won't help you. I mean, I like,

2669
02:33:33,400 --> 02:33:35,160
Speaker 1: I just paid for the domain name and it just

2670
02:33:35,240 --> 02:33:38,520
Speaker 1: sits there, so there's no point in me giving you that. Um,

2671
02:33:38,760 --> 02:33:43,000
Speaker 1: but you can buy the book at Barnes and Noble

2672
02:33:43,560 --> 02:33:47,800
Speaker 1: if you're in Bozeman Country bookshelf, and if you're not

2673
02:33:47,920 --> 02:33:50,080
Speaker 1: one of those people that wants Jeff Bezos to stay

2674
02:33:50,120 --> 02:33:54,040
Speaker 1: in space, you can get it from Amazon. And I think, um,

2675
02:33:55,800 --> 02:33:57,320
Speaker 1: I do want to say one more thing. You can

2676
02:33:57,400 --> 02:33:59,880
Speaker 1: be really diplomatic. No, I want to say one more thing.

2677
02:34:00,000 --> 02:34:01,959
Speaker 1: There's a way you go what you say anywhere books

2678
02:34:02,000 --> 02:34:05,000
Speaker 1: are sold. Anywhere books are sold. I wanted to say

2679
02:34:05,040 --> 02:34:06,720
Speaker 1: one more thing where you can if you just want

2680
02:34:06,760 --> 02:34:09,640
Speaker 1: to listen to it, you can get that audio. It's

2681
02:34:09,680 --> 02:34:11,600
Speaker 1: called you can get an audio book. And I just

2682
02:34:11,640 --> 02:34:15,200
Speaker 1: found out yesterday you can. Did you do your own read? No?

2683
02:34:15,400 --> 02:34:17,040
Speaker 1: But I listened to the girl who didn't read, and

2684
02:34:17,120 --> 02:34:22,119
Speaker 1: I listened to they did. But I I a few

2685
02:34:22,200 --> 02:34:27,200
Speaker 1: of them. You know, winding wind finally are the same words. Yeah,

2686
02:34:27,240 --> 02:34:28,800
Speaker 1: I know, I listened to it. She got windy and

2687
02:34:28,879 --> 02:34:33,760
Speaker 1: windy mixed up. Don't you're spelled the same? Don't let

2688
02:34:33,879 --> 02:34:38,080
Speaker 1: some person you know I don't. I don't like your

2689
02:34:38,120 --> 02:34:39,880
Speaker 1: publishers a dear friend of mine, and I owe a

2690
02:34:40,000 --> 02:34:41,800
Speaker 1: lot of my I owe a lot of my career

2691
02:34:41,879 --> 02:34:43,880
Speaker 1: in life to her. It was her decision. If it

2692
02:34:44,040 --> 02:34:47,520
Speaker 1: was her decision, I'll fight with her about it. If

2693
02:34:47,600 --> 02:34:49,800
Speaker 1: they should not have loved that, you should that should

2694
02:34:49,840 --> 02:34:51,520
Speaker 1: not have happened. You should read your own damn book.

2695
02:34:51,640 --> 02:34:53,880
Speaker 1: You need a professional studio, though, I thought that was

2696
02:34:53,959 --> 02:34:56,039
Speaker 1: the deal, and so it was the time of COVID

2697
02:34:56,200 --> 02:34:58,560
Speaker 1: that was the problem. It was taped during COVIE. I mean,

2698
02:34:58,600 --> 02:35:00,160
Speaker 1: I don't think that was the only problem. M I

2699
02:35:00,200 --> 02:35:02,840
Speaker 1: think they never considered having me made it, but we

2700
02:35:02,959 --> 02:35:04,800
Speaker 1: did have to hire a guy with it who had

2701
02:35:04,840 --> 02:35:06,560
Speaker 1: a student. You might have needed to practice for a

2702
02:35:06,640 --> 02:35:10,400
Speaker 1: long time and had a studio. No, I know you

2703
02:35:10,520 --> 02:35:12,720
Speaker 1: have to practice because I make videos for my students,

2704
02:35:12,800 --> 02:35:16,840
Speaker 1: and you have to keep going over getting repeating everything

2705
02:35:16,920 --> 02:35:19,400
Speaker 1: over and over because you noticed you said something wrong

2706
02:35:19,480 --> 02:35:21,760
Speaker 1: or there was too much of a pause there and whatever.

2707
02:35:21,920 --> 02:35:25,280
Speaker 1: So it takes a long time. No, wait, one more

2708
02:35:25,400 --> 02:35:29,800
Speaker 1: thing audio and and the download onto the little machines

2709
02:35:29,879 --> 02:35:31,600
Speaker 1: that you can read from. You can do that. I

2710
02:35:31,680 --> 02:35:34,560
Speaker 1: just found that out yesterday. So anywhere books are sold,

2711
02:35:34,720 --> 02:35:44,920
Speaker 1: anywhere books are sold even Amazon, Amazon, And so that's right, No,

2712
02:35:45,160 --> 02:35:47,880
Speaker 1: thanks everybody who buys it for sure. Yeah, I think

2713
02:35:47,920 --> 02:35:53,920
Speaker 1: it's more so, Um, you're becoming uh, all of this

2714
02:35:54,080 --> 02:35:58,040
Speaker 1: is making you become less of a hermit. Well, do

2715
02:35:58,040 --> 02:36:02,000
Speaker 1: you think you're gonna go back into hiding? Not you're hiding.

2716
02:36:02,640 --> 02:36:04,080
Speaker 1: Do you think you're going to become do you do

2717
02:36:04,120 --> 02:36:09,720
Speaker 1: you imagine? Now I'll being more. I just have plug

2718
02:36:09,800 --> 02:36:13,520
Speaker 1: about hermits and such um and you'll read this in

2719
02:36:13,640 --> 02:36:17,760
Speaker 1: my book. Also, people who live away from other people.

2720
02:36:18,959 --> 02:36:23,360
Speaker 1: We're not trying to hide from people. We don't dislike people.

2721
02:36:23,560 --> 02:36:25,840
Speaker 1: We're not trying to get away from people. We just

2722
02:36:26,560 --> 02:36:30,320
Speaker 1: love the things that people get rid of. And that's

2723
02:36:30,360 --> 02:36:32,480
Speaker 1: why I want to live in a place where I

2724
02:36:32,600 --> 02:36:35,120
Speaker 1: can sit outside and watch the badgers and the skunks

2725
02:36:35,160 --> 02:36:37,680
Speaker 1: and the eagles and the foxes, and where it's quiet

2726
02:36:38,080 --> 02:36:40,000
Speaker 1: and I can hear what I want to hear, like

2727
02:36:40,160 --> 02:36:43,760
Speaker 1: the wind, and I don't have to see trucks coming

2728
02:36:43,800 --> 02:36:46,119
Speaker 1: by all day long. It's not because I don't like humans.

2729
02:36:46,160 --> 02:36:48,960
Speaker 1: It's because I love the things that humans get rid of.

2730
02:36:49,560 --> 02:36:52,520
Speaker 1: And if I was really misanthropic, I would live in

2731
02:36:52,560 --> 02:36:57,400
Speaker 1: a city. Because if you really dislike humans, then you

2732
02:36:57,520 --> 02:37:00,200
Speaker 1: want to live where there's a lot of humans so

2733
02:37:00,400 --> 02:37:02,760
Speaker 1: that you can torture them and whatever the hell you

2734
02:37:02,840 --> 02:37:09,520
Speaker 1: do around. Yeah. So the bad guys who don't like

2735
02:37:09,680 --> 02:37:12,959
Speaker 1: people are the ones that live where there's people, right,

2736
02:37:13,240 --> 02:37:16,840
Speaker 1: The people that are really I don't like people, they

2737
02:37:16,959 --> 02:37:20,680
Speaker 1: live in cities like the country. Yeah, that's a seed. Yeah,

2738
02:37:20,840 --> 02:37:22,800
Speaker 1: it needs work, but that's a good seed of an idea.

2739
02:37:22,840 --> 02:37:27,240
Speaker 1: I like that. There's your tagline, n't but I've been

2740
02:37:27,280 --> 02:37:30,360
Speaker 1: working on that idea. There's something there, man, I think

2741
02:37:30,400 --> 02:37:34,199
Speaker 1: there is for sure, don't you know. It's a compelling point.

2742
02:37:34,520 --> 02:37:37,160
Speaker 1: Gonna I'm gonna like land bed and unpack that one. Good.

2743
02:37:37,600 --> 02:37:40,200
Speaker 1: That's a good one. I've never thought about humans getting

2744
02:37:40,320 --> 02:37:44,039
Speaker 1: rid of silence, but it's true, getting rid of silence.

2745
02:37:44,920 --> 02:37:46,960
Speaker 1: It's one of my favorite things about where we live

2746
02:37:47,440 --> 02:37:51,480
Speaker 1: is the silence. And there was like a death metal

2747
02:37:51,560 --> 02:37:55,800
Speaker 1: band that covers the sound of silence, No Sound of

2748
02:37:56,000 --> 02:38:02,520
Speaker 1: Silence Disturbed. The name of the Kathy Raven, the title

2749
02:38:02,600 --> 02:38:05,680
Speaker 1: of the book, Easy to Remember, Box and I, Box

2750
02:38:05,760 --> 02:38:09,560
Speaker 1: and I and then Carmen van Bianci third appearance on

2751
02:38:09,640 --> 02:38:12,680
Speaker 1: the podcast. Her new company will not a company. Her

2752
02:38:12,720 --> 02:38:17,240
Speaker 1: new nonprofit will be called Home Range wildlife research. How

2753
02:38:17,280 --> 02:38:19,200
Speaker 1: do you How do you do you want people going

2754
02:38:19,240 --> 02:38:21,600
Speaker 1: and looking you up on social media and stuff? Or

2755
02:38:21,600 --> 02:38:23,280
Speaker 1: do you hate that kind of stuff? I don't have

2756
02:38:23,400 --> 02:38:28,920
Speaker 1: any of that. Good for you. Let's competition for my account.

2757
02:38:30,080 --> 02:38:33,800
Speaker 1: Um do you care to have people find you? Well? Uh,

2758
02:38:34,200 --> 02:38:36,680
Speaker 1: we do have a website home range dot org and

2759
02:38:36,760 --> 02:38:38,720
Speaker 1: that's the way to go. You don't want them like

2760
02:38:38,800 --> 02:38:41,640
Speaker 1: emailing you and stuff like that. Oh they can email me,

2761
02:38:42,040 --> 02:38:43,600
Speaker 1: and not so badly that you want to give out

2762
02:38:43,640 --> 02:38:46,120
Speaker 1: your email address. I wouldn't do that. Yeah, probably not.

2763
02:38:46,560 --> 02:38:50,200
Speaker 1: There's got to be contact us at home range dot org. True, Yes,

2764
02:38:50,280 --> 02:38:52,400
Speaker 1: I have a home range email. Oh there you go

2765
02:38:53,360 --> 02:38:55,200
Speaker 1: and you check. So someone wants to reach out to

2766
02:38:55,200 --> 02:38:57,360
Speaker 1: you and say, hey, I got a study idea for you. Yeah,

2767
02:38:57,600 --> 02:39:00,400
Speaker 1: I'm a budding young biologist on your job. Yep, I

2768
02:39:00,440 --> 02:39:02,280
Speaker 1: got a wolf story to tell you about. Or I

2769
02:39:02,320 --> 02:39:05,080
Speaker 1: got a good jillion dollars and I'm looking to put

2770
02:39:05,160 --> 02:39:08,720
Speaker 1: it in a nonprofit especially those Ye Yes, home range

2771
02:39:08,800 --> 02:39:13,560
Speaker 1: dot org. Okay, fox and I home range dot org

2772
02:39:13,640 --> 02:39:16,640
Speaker 1: two very different things, but both worthwhile checking out. Thank

2773
02:39:16,680 --> 02:39:17,160
Speaker 1: you everybody,