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Speaker 1: This is the me Eater podcast coming in you shirtless,

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

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Speaker 1: You can't predict anything, all right, Carmen, tell me your

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Speaker 1: last name again, Van Biancy, Van Biancy. What do you

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Speaker 1: think about squid jigging? It was great. I hadn't done

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Speaker 1: that in years. We grew up doing that in the

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Speaker 1: Puga sound. It was a it was a birthday party

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Speaker 1: thing in my family. We had a fall birthday. Wheould

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Speaker 1: you go any time here? No, actually descembrate. It was

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Speaker 1: my sister's birthday. And you guys are j squid. Yeah.

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Speaker 1: We sometimes will take a group of girls down on

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Speaker 1: the dock and now, would you guys clean house? Like?

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Speaker 1: Were you guys better at it than than than? Uh

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Speaker 1: than than me? And Yanni are at it? Not much better?

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Speaker 1: I mean, we didn't have our own lights, so we

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Speaker 1: just go onto the ferry dock and just fish wherever

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Speaker 1: the pools of light from the um fairy lights were.

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Speaker 1: And so I don't know, that doesn't seem to bring

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Speaker 1: as many in. We do better some nights where some

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Speaker 1: other nights. Yeah, I'm addicted to it. So now, uh,

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Speaker 1: it's squid season in in the Pacific Northwest. They come

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Speaker 1: in shallow to spawn. They congregate November and December. I

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Speaker 1: read it they spawned between like five and thirty ft

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Speaker 1: of water um and then people show up down on

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Speaker 1: the piers. Like it seems that the squid are kind

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Speaker 1: of drawn to light. I don't know if their prey.

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Speaker 1: I don't know if they're drawn to light because the

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Speaker 1: stuff they're feeding on congregates around light. There's a lot

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Speaker 1: of like things people don't there's a lot of things

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Speaker 1: that people have different opinions on about squid. Now why okay,

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Speaker 1: First off, a squid jig. This looks like a it's

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Speaker 1: like a little celind, like a glow in the dark,

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Speaker 1: little cylinder, and there's no hook on. There's a bunch

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Speaker 1: of wires up facing, upturned wires that impale the squid.

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Speaker 1: You're you're snagging squid? Now why do you feel? And

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Speaker 1: I'm not you're not a squid expert. What's your theory about? Why?

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Speaker 1: What is that squids interaction with the squid jig? So

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Speaker 1: my squid knowledge is based on a national geographic that

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Speaker 1: I owned when I was little and a um my

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Speaker 1: first report I ever did in elementary school which was

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Speaker 1: on octopus and squid, and so my own got started.

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Speaker 1: You got started in biology early, Oh yeah, very early. Um. Anyway,

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Speaker 1: my understanding is that in the absence of doc lights,

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Speaker 1: they're congregating in moonlight, and they're congregating to mate, and

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Speaker 1: so when they see that flashy squid jigs, they try

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Speaker 1: to mate with it, and that's when you get them.

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Speaker 1: That's what you think they're doing, because I I've had

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Speaker 1: people tell me that I think it's like, I think

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Speaker 1: it's like a feeding thing. Okay, I've heard both. I

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Speaker 1: heard a guy saying it's their territorial and he's trying

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Speaker 1: to fight the jig. I've had guys saying they're trying

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Speaker 1: to mate the jig, and I've had guys saying they're

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Speaker 1: trying to feed on the jig. Because people catch a

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Speaker 1: lot of squid all times a year using jigs and

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Speaker 1: outside of the spawning season, like we caught a giant.

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Speaker 1: Uh my friend and colleague Ben O'Brien called a giant

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Speaker 1: a different species. The ones we were getting getting last

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Speaker 1: night are low legal opallescence. Its common name is the

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Speaker 1: market squid. He caught a big fatty. I don't know

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Speaker 1: what it was that's some bitch hit a halibut jig. Now,

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Speaker 1: I don't think he's trying to breed that halibut jig

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Speaker 1: in June. He's got different opinions about it. Seemed to

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Speaker 1: like light. I wrote a whole article about it, and

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Speaker 1: I never I like it was years ago and outside

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Speaker 1: Magas I wrote a piece about squid jigging and Puget

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Speaker 1: Sound and it was partularly interesting to me is that, um,

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Speaker 1: it doesn't look like you're normal fishing, your normal American

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Speaker 1: fishermen down there, because the people like to fish squid

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Speaker 1: in Seattle are generally the immigrant communities from Southeast Asia,

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Speaker 1: particularly from my own conversations with people, a lot of

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Speaker 1: people from Vietnam, a lot of people from Laos, a

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Speaker 1: lot of people from Cambodia, Filipinos, and a lot of

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Speaker 1: these guys that I had interviewed before had fish squid

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Speaker 1: in their in their home countries, even some guys that

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Speaker 1: had come into the seventies towards after after the fall

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Speaker 1: of Saigon. Some guys that come over and they had

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Speaker 1: jigs squid, same deal, have a light and light, but

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Speaker 1: also talked to guys that fish with poison and guys

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Speaker 1: that fish with dynamite. Yeah, that's a long way to

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Speaker 1: get some squen. This guy was telling me years ago.

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Speaker 1: This is this is I wrote this article. I remember

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Speaker 1: it was right after the terrorist attacks because I was

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Speaker 1: I lived in Montana, and I hadn't spent a lot

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Speaker 1: of time around big buildings, and it was right after

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Speaker 1: the terrorist attacks. And remember it was December, the December

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Speaker 1: after the terrorist attacks. And I remember, you know, the

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Speaker 1: around Seattle, there's so many planes criss crossing, and I

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Speaker 1: couldn't watch a plane while in my field of view

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Speaker 1: there was a large building without thinking that it was

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Speaker 1: headed for the building. I remember being like so paranoid

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Speaker 1: where I'd be like half watching my rod tip and

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Speaker 1: half waiting for a plane to burrow into a skyscraper.

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Speaker 1: So I always have it fixed in my head that

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Speaker 1: it was December two thousand one. Um, the hell's I

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Speaker 1: getting net? I don't know about. I don't know who's

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Speaker 1: who's squid jigging on the docks here in the Pacific Northwest. Yeah,

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Speaker 1: that was what it was. And yeah, and very few

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Speaker 1: now you see you see like some you see like

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Speaker 1: a handful of white people around. It was generally people

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Speaker 1: from the from Southeast Asia. Oh I don't. I was

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Speaker 1: gonna get that now, I interviewed a guy. My interview,

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Speaker 1: I mean it's like basically bullshitted with him on the

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Speaker 1: pier while you're squid jigging. Um, he had fish squid

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Speaker 1: in Vietnam, came to the U. S. And Sev had

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Speaker 1: no idea and what would walk along the piers being

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Speaker 1: curious about the area where his flashlight and one day

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Speaker 1: shined a flashlight in the water, saw a squid and

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Speaker 1: started squid jigging. Now he doesn't claim to be the

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Speaker 1: guy that like fathered squid jigging, but he discovered it,

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Speaker 1: not through hearing about it and seeing people. He discovered

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Speaker 1: by walking down and seeing a squid. And that's when

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Speaker 1: he started squid jigging in future sound. Yeah, I don't

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Speaker 1: know the history of it here, but um, ever since

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Speaker 1: I've was little, there's many people out there and yeah,

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Speaker 1: I don't that's because I don't know. Like if I

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Speaker 1: was at my place in Southeast Alaska right now, would

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Speaker 1: I go out on a float and knocked the ship

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Speaker 1: out of squid if I shined a light in the

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Speaker 1: water or is it like peculiar to the area I

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Speaker 1: don't know, Like, I don't know if people fish squid

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Speaker 1: here because there's squid here, or people fish squid here

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Speaker 1: because there's a population of people who are interested in

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Speaker 1: fishing squad because people doing it, so they do it. Yeah,

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Speaker 1: Like I grew up in a place where people go

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Speaker 1: way out of their way to catch yellow perch. Here

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Speaker 1: is the best yellow perch fish in the world. No

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Speaker 1: one fishes them, it's just local culture. Maybe. Yeah, there's

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Speaker 1: no panfish culture in the Pacific Northwest because everybody's got

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Speaker 1: a salmon centric view of the world. What do you

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Speaker 1: think about I think more people would get after it

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Speaker 1: because it seems like figure it out. And kids love it. Yeah. Yeah.

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Speaker 1: We had my two older youngsters out there and they

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Speaker 1: have a good time. I mean they're not like necessarily fishing,

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Speaker 1: but they're just taking it all in. That's what kids,

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Speaker 1: that's how kids fish. At first. I loved it when

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Speaker 1: I was little was it was exciting to get to

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Speaker 1: go out at night and you're bundled up and you

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Speaker 1: have hot chocolate and it's just cool experience to be

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Speaker 1: outside at night. Like most cold weather outdoor activities, just

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Speaker 1: hot chocolate involved. So all the kids are in and

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Speaker 1: like every other worthwhile pursuit, there are some people who

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Speaker 1: are really good at it and a lot of people

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Speaker 1: that suck. I'm in the suck category. And like what

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Speaker 1: we had, we had fifteen yet fifteen maybe, and we

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Speaker 1: watched some boys next us. They probably filled the bucket. Yeah,

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Speaker 1: they caught everyone, Yeah, fishing the exact same ship. They

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Speaker 1: had a bright as Yeah. I think as a little

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Speaker 1: experiment you should get. Greg was dipping over into their light.

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Speaker 1: He wasn't pulling squid out like that, yeah, but he

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Speaker 1: was kind of on the edge of it. I mean,

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Speaker 1: they definitely had some differences in tackle. Longer rods that does.

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Speaker 1: That doesn't account for everything. It doesn't come for everything

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Speaker 1: little every little thing matters. Yes, And the longer rod

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Speaker 1: does a few things. One, you've got more play in

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Speaker 1: the rod. It's a softer rod tip, you know, so

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Speaker 1: who knows. So maybe when you're jerking it with a

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Speaker 1: stiffer rod, maybe they get out of the way, you know,

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Speaker 1: because they're feeling it more. And that softer pull of

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Speaker 1: the longer, softer rod impales them in a different way

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Speaker 1: that you know, they can't get off double jigs to Yeah,

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Speaker 1: I do that too. And the reason I got away

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Speaker 1: from it is have an inexperienced anglers, like when I

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Speaker 1: had my kids or whatever. They lose so many jicks,

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Speaker 1: so then they're losing two at a time, and then

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Speaker 1: if I put two on, then they're like, why don't

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Speaker 1: I get to right? And then you'll be like, well,

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Speaker 1: because you'll lose them, and then it's like you're an asshole,

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Speaker 1: Like you're like, you know what I mean. So that's

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Speaker 1: why if I was if it's just like you, you

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Speaker 1: were out, we would have been running two. But you know,

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Speaker 1: it's just hard to get I think it's hard to make.

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Speaker 1: They're set up as much as possible, and then if

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Speaker 1: still nothing's changing, we're just going to go over and

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Speaker 1: learned Cambodian or the last time. Last time I was out,

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Speaker 1: I was running two and had a nice double. I

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Speaker 1: saw a guy get a triple two on one and

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Speaker 1: one on one a double. He had a double rig

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Speaker 1: triple squid. I know that half of the ones icon

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Speaker 1: were impaled, like in the side, but that's that's just

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Speaker 1: something that happens. That's what I'm saying. It's like having stance.

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Speaker 1: They were swimming by. I impelled him with my jig motion.

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Speaker 1: Most of the ones I saw coming in with the

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Speaker 1: guys next to us looked like the squid was hooked

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Speaker 1: like between the Yeah, no, there's a there's a lot

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Speaker 1: of mystery to it now. One time I was out

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Speaker 1: there my buddy Drolls in two thousand one, and we

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Speaker 1: went down and we had just a regular sixty watt

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Speaker 1: light bulb. We had a battery and an inverter in

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Speaker 1: a sixty watt light bulb, one of those aluminium shrouds

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Speaker 1: you put around a sixty wild light bulb. And we

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Speaker 1: went down there right at dusk and knocked the ship

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Speaker 1: out of them, like we had over half a bucket.

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Speaker 1: So there is stuff like there's a voraciousness I think

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Speaker 1: they get. They get fired up, you know, and hit

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Speaker 1: batter like maybe sometimes it's so good, any idiot, right,

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Speaker 1: sometimes it's so good. Any of these gonna do good.

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Speaker 1: Last night, it was like the men were separated from

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Speaker 1: the boys, the women from the girls last night by

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Speaker 1: those two dudes next to us, because there was probably

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Speaker 1: twenty people on that pier and two guys. We're knocking

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Speaker 1: the ship out of the squid, and it was killing me.

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Speaker 1: Big Ones, Big Ones, I don't think we caught a

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Speaker 1: single squid. As they were falling. The hook them on

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Speaker 1: the face. Man, it's hard to say face because their

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Speaker 1: eyes are at one end and their mouth is at

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Speaker 1: the other. It's because their feet are at that same end. Yeah,

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Speaker 1: they're jacapod. They have ten well, they have like eight

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Speaker 1: two arms and eight legs, but a total of ten.

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Speaker 1: Two of those things are longer than the others and

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Speaker 1: have different cups, like a different suction cup array on them.

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Speaker 1: And they got a beak like a bird. Yeah, a

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Speaker 1: hard black hooked beak like a bird. I got bit

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Speaker 1: by that one. Ben O'Brien called it hurt um. Now, Carmen,

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Speaker 1: tell tell me what's your job description? Well, like, how

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Speaker 1: do you describe? I guess I described myself as a

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Speaker 1: wildlife biologists. I went to school for and I got

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Speaker 1: um wildlife Management and conservation degree from my undergrad Humboldt

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Speaker 1: State University in California, Northern California. Big dope smoking area,

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Speaker 1: big yeah, especially in county. That's what I'm saying. My

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Speaker 1: buddy always pointed like I got a buddy from Humboldt

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Speaker 1: County and um and and uh when he says Humboldt County,

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Speaker 1: a certain segment of the American population, their ears perk

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Speaker 1: up when it's probably less so now, but back in

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Speaker 1: the day, Yeah, like his father ran a hydroponic supply

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Speaker 1: store there, you go, probably did well. Yeah, so that's

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Speaker 1: the first thing that people think of. But it's also

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Speaker 1: a beautiful place that's uh great to learn about wildlife

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Speaker 1: because we were just constantly out in the field learning

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Speaker 1: all the waterfowl. It's a huge waterfowl migration area and

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Speaker 1: birds everywhere. You've got the ocean, you've got redwoods, you've

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Speaker 1: got the mountains. So it's a really good place to

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Speaker 1: go to school for that. But you weren't hunting back then, right, fishing,

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Speaker 1: but you didn't hunt. Uh you know, yeah, I didn't hunt. Um,

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Speaker 1: when I was in college, there were a lot of

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Speaker 1: hunters in the program and I was starting to get

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Speaker 1: really interested in it and knew that I wanted to

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Speaker 1: do it. So then um, when I graduated from there,

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Speaker 1: I uh started actually taking action on it, and I

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Speaker 1: went out and bought a gun not really knowing what

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Speaker 1: I was doing, and took hunter safety and um, I

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Speaker 1: just kind of started putting it together from there. But

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Speaker 1: but anyway. So, yeah, I call myself a wildlife biologist, um,

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Speaker 1: and I concentrate on carnivores. So most of the work

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Speaker 1: I've done has been with carnivores. My master's work was

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Speaker 1: on links um in Washington, and UM, so most of

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Speaker 1: the most of my career has been just working seasonally

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Speaker 1: all over the country different projects. Just yeah, you say,

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Speaker 1: like like you're like a like field biology though, right, Yeah,

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Speaker 1: because you're out there catching and trapping and track and yeah. Yeah,

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Speaker 1: so for example, yeah, mostly, Um, I started out Actually

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Speaker 1: my first job was uh after my second year of school,

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Speaker 1: and it was in Hawaii working with hawks bowl turtles

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Speaker 1: honoring turtles, which, um it was a pretty couch job.

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Speaker 1: We camped on the beach, waited for turtles to come,

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Speaker 1: and then basically put them in a full nelson, which

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Speaker 1: didn't work. The first time I tried to do that,

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Speaker 1: turtle just kept on going like there was nothing on

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Speaker 1: top of her. Yeah. I didn't quite have the body

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Speaker 1: type for that, but hold on, hold on. So I

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Speaker 1: obviously don't know about this turtle that you're you're speaking of, turtle,

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Speaker 1: big turtle, thee in Hawaii there, Well, I think, yeah, yeah,

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Speaker 1: maybe probably I think there's some overlapping size, but I

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Speaker 1: don't know what an average one is. But that's like

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Speaker 1: a wheelbarrow big. It was huge, very very strong. And

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Speaker 1: so this turtle comes up on the beach. We've been

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Speaker 1: told you restrain it by jumping on it, putting it

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Speaker 1: in a full nelson, and then the rest of the

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Speaker 1: crew will tag it while you've got it. So arms

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Speaker 1: under his front feet. So yeah, yep, you're on the

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Speaker 1: turtle shell. Your your front arms are under the front flippers,

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Speaker 1: sort of lifting them up so they can't get any purchase.

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Speaker 1: And then you know, your hands are locked over its neck.

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Speaker 1: So I did that. You can't come around and grab you. Yeah,

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Speaker 1: these are nesting nesting turtles. And just to keep it

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Speaker 1: in one place so that you can put tag on

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Speaker 1: its flippers. That's what they tag them. Uh, because it's

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Speaker 1: easy to just punch through the skin on the flippers.

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Speaker 1: I've caught, like when I've caught tagged soft shells. Here,

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Speaker 1: they clamp it right to the back of the shell.

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Speaker 1: She's like a perfect place to put it. You put it.

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Speaker 1: It's a flipper. Yeah. It was just a little metal

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Speaker 1: tag with a number on it, not like a track

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Speaker 1: and devoy right right right, um, and they will they

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Speaker 1: will try to get you when you're trying to restrain

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Speaker 1: it probably, I mean, yeah, you don't want to put

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Speaker 1: your hands in front of their face and then their

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Speaker 1: flippers are just flying and it can be kind of

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Speaker 1: a rodeo, especially when I did it, because I just

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Speaker 1: didn't have the weight to hold it down, so it

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Speaker 1: just kept going. So we swapped out. We gotta figured

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Speaker 1: out anyway. That was my first job, and that was

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Speaker 1: also my first dially into trapping, because we would trap

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Speaker 1: mongoose around the beach to try and keep those populations

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Speaker 1: down there invasive there, and they just try to control

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Speaker 1: a mongoose from getting the eggs. Yeah, yeah, have a

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Speaker 1: heart catchmen have a hearts, um, and then we just

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Speaker 1: euthanize them with CEO two gas. You just pick up

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Speaker 1: the trap and you put in a plastic bag and

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Speaker 1: you have a tank and you shoot a shot in there.

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Speaker 1: Because you get the same effect by it's closing off

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Speaker 1: the bag. It just takes forever. Right, That might be

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Speaker 1: a Sloan painful sort of deal. So this is fast,

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Speaker 1: and you could check your little trapline and farrell cats

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Speaker 1: and rats too. Yeah, when I've been in Hawaii. Do

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Speaker 1: you see a lot of those freaking mongooses around me? Yeah? Man,

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Speaker 1: it's a problem invasive. You know, the turtles there, what's

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Speaker 1: the other? So there's the hall, but there's the other

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Speaker 1: kind of like a green. Yeah. Now last year we

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Speaker 1: were on a family vacation and I was spearfishing there

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Speaker 1: and I'd go out at night and you dive down

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Speaker 1: under the coral ledges and you bump in face face

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Speaker 1: those turtles. It's like everything underwater scary. Everything underwater at

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Speaker 1: night it's even scarier. And it's like on the beach

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Speaker 1: it's like, oh, it's a big gas turtle underwater and

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Speaker 1: always be like kind of intimidating to roll up on

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Speaker 1: those things. And one time I went down and there

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Speaker 1: was a turtle laying there under underwater under a coral

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Speaker 1: head and there was a collar, you know, like a

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Speaker 1: unicorn fish feeding on the turtles head and it was

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Speaker 1: a big collar, and I didn't want to obviously hit

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Speaker 1: the turtle, and so I corrected so much to try

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Speaker 1: to get the collar but not get the turtle out

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Speaker 1: out missing the fish off the back side of fishcause

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Speaker 1: I was even I was like point blank range I

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Speaker 1: was just paranoid about messing with that turtle, which is

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Speaker 1: like an image stuck in my mind as giants because

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Speaker 1: they don't like attack people. But anything like that just

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Speaker 1: seems kind intimidating underwater man out of your element in

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Speaker 1: the water too, I find I you know, I run

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Speaker 1: around in the woods all the time, and I've worked

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Speaker 1: with predators and I I don't worry about bears, I

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Speaker 1: don't think about cougars. I'm not I'm totally comfortable. But

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Speaker 1: in the water, I just I did some circling when

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Speaker 1: I did that job, and I would just be I

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Speaker 1: couldn't stop thinking about sharks. I just felt so out

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Speaker 1: of my elm went and it's just not you know,

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Speaker 1: just not what you're used to, you know. I guess

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Speaker 1: that's what you're used to that you're comfortable with. But yeah,

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Speaker 1: because I used to I used to have some of

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Speaker 1: that fear of like I used to have more of

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Speaker 1: a fear of grizzlies. But it just gets used up

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Speaker 1: somehow or goes away, you know. Yeah. I mean I

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Speaker 1: think you just get comfortable and you're your perception of

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Speaker 1: what the risk is changes. You start to realize that

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00:19:53,600 --> 00:19:57,879
Speaker 1: it's usually overblown. So what was the next animal you

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Speaker 1: worked on after? After the turtle work, they're trying to

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Speaker 1: find out about the turtles, just mark and recapture, like yeah,

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Speaker 1: it was a monitoring project and then we'd mark the nests.

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Speaker 1: It was also an effort to protect the nests um

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Speaker 1: and then in the fall when they hatch in late summer.

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Speaker 1: I actually wasn't there for that part when the nestlings hatched.

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Speaker 1: They're trying to be there to get as many as

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Speaker 1: possible to the ocean, just to get them over that

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Speaker 1: first hurdle of making it alive. It's like mechanically assisting

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Speaker 1: m yeah, predators away, helping them get back right, Yeah,

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Speaker 1: because that's the that's their vulnerability rights. Yeah. Well and

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Speaker 1: then also in the water. Not many of them make

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Speaker 1: it anyway, but I think the ideas to just give

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Speaker 1: them a little better of a chance to make it

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Speaker 1: because there's because they're struggling a struggling species. Yeah, how

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Speaker 1: many times, but do you know how many times when

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Speaker 1: those females might breed. I don't know. I that was

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Speaker 1: my one and only dally into reptiles. Yeah, that's the

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00:20:55,200 --> 00:20:57,840
Speaker 1: weird thing about what was animal populations like that? Or

365
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Speaker 1: like fish and they're laying foul and eggs. Well, in

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Speaker 1: the case of turtles are laying a dozen or more eggs,

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Speaker 1: they're gonna live for decades. Presube lay eggs dozens of times. Yeah,

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Speaker 1: and then it's like if they can, if they can

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Speaker 1: have two of those eggs, they're successful. If two of

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Speaker 1: those eggs turned into turnley, if that, yeah, like you're successful. Yeah,

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Speaker 1: over the lifetime, not per um. Yeah, So salmon comes

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Speaker 1: up and drops how many hundreds of eggs, it's successful

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Speaker 1: if two or roughly one or two live. Yeah. Yeah,

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Speaker 1: it's common strategy in nature. I mean you even see

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Speaker 1: it in just our our prey populations. You know that

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Speaker 1: you're having way more babies in the lank and support.

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Speaker 1: So yeah. Yeah. We had a guy we interviewed on

378
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Speaker 1: here one time that had a he had a black

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Speaker 1: bear saw that he watched during his research project that

380
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Speaker 1: he watched um rear ten cubs two hundred pound size,

381
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Speaker 1: back to back to back. Quinn is a quintuplet, five

382
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Speaker 1: m back to back quintuplets. That's impressive that she got

383
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Speaker 1: all ten to one hundred pounds at least. And at

384
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Speaker 1: that point there they're rocking successful. Yeah, well we got

385
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Speaker 1: into that. She was onto a lot of crop land.

386
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Speaker 1: It was onto the place where they dumped road killed. Yeah.

387
00:22:34,240 --> 00:22:40,320
Speaker 1: Well yeah. The bear's name is the Wisconsin supersow. So

388
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Speaker 1: you did the turtle thing, then what happened? So, um,

389
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Speaker 1: let's see. I did a couple of bird projects one

390
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Speaker 1: of the smokies. That was fun, doing some misnetting and

391
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Speaker 1: looking for nests. What kind of birds? Um, we were

392
00:22:56,160 --> 00:23:00,479
Speaker 1: looking for junk on nests. They're just a comment. Yeah yeah, sparrow.

393
00:23:00,520 --> 00:23:02,200
Speaker 1: I got those in my yard right now. Yeah yeah yeah.

394
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Speaker 1: And the reason we were looking for those is we

395
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Speaker 1: were collecting eggs, so it needed to be a common bird.

396
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Speaker 1: And I was working for a PhD student who was

397
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Speaker 1: looking at um environmental leeching. So from all the pollution,

398
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Speaker 1: UM wondering, is calcium leaching out of the environment enough

399
00:23:16,359 --> 00:23:19,600
Speaker 1: that it's affecting eggshells? Why is there? Why is there

400
00:23:19,640 --> 00:23:23,000
Speaker 1: calcium in the environment? Just natural calcium in the environment,

401
00:23:23,119 --> 00:23:25,400
Speaker 1: that's the good part that's spread the birds need from

402
00:23:25,400 --> 00:23:29,960
Speaker 1: eating snails and whatever, um, and then needed for making shells.

403
00:23:30,600 --> 00:23:37,040
Speaker 1: So being leached out by pollution by pollution, yeah yeah,

404
00:23:37,359 --> 00:23:40,320
Speaker 1: because when you know what they used to use DDT

405
00:23:41,840 --> 00:23:46,680
Speaker 1: it would cause the birds shells to be too soft.

406
00:23:47,000 --> 00:23:49,919
Speaker 1: So the one the birds incubating. Do you know what

407
00:23:50,000 --> 00:23:52,600
Speaker 1: it was? Was that a calcium issue? I don't know.

408
00:23:52,760 --> 00:23:55,400
Speaker 1: I don't know why it caused their shells to get thin. Yeah,

409
00:23:55,480 --> 00:23:59,040
Speaker 1: I don't know, I don't know. But so that was

410
00:23:59,080 --> 00:24:02,160
Speaker 1: a great job, just basically wandering around the smoky's usually

411
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Speaker 1: by myself, hiking around um looking for the eggs, looking

412
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Speaker 1: for nest. Yeah, how would you find? You just get

413
00:24:09,840 --> 00:24:13,400
Speaker 1: They like to nest on the ground in cut banks

414
00:24:13,440 --> 00:24:16,040
Speaker 1: a lot. So you just hiking trails, You just watch

415
00:24:16,119 --> 00:24:18,640
Speaker 1: for birds flashing, and you just are looking to see

416
00:24:18,680 --> 00:24:21,000
Speaker 1: the little nest tucked in there. Yeah. You know that

417
00:24:21,040 --> 00:24:23,359
Speaker 1: Tom Petty song where he says I can track a stink.

418
00:24:23,760 --> 00:24:27,159
Speaker 1: I can track a single bee to its high That

419
00:24:27,240 --> 00:24:29,320
Speaker 1: saw the people like hunt bee hives and the old days.

420
00:24:29,520 --> 00:24:31,280
Speaker 1: You just sit out in the woods and watch a

421
00:24:31,320 --> 00:24:34,439
Speaker 1: honeybee fly by, Watch it go as far as you

422
00:24:34,480 --> 00:24:39,240
Speaker 1: could see it. Stand there, wait for honeybee to fly by,

423
00:24:40,600 --> 00:24:42,600
Speaker 1: watch until it disappears out of your line of sight.

424
00:24:43,119 --> 00:24:47,560
Speaker 1: Stand there, and over time I got a friend you

425
00:24:47,600 --> 00:24:48,800
Speaker 1: to do it. Sometimes to take him a couple of

426
00:24:48,840 --> 00:24:50,800
Speaker 1: days of just whenever he would have time, and he

427
00:24:50,800 --> 00:24:53,000
Speaker 1: would just go to his last position and wait for

428
00:24:53,000 --> 00:24:57,119
Speaker 1: one to go by, and eventually you'd locate the honey

429
00:24:57,119 --> 00:24:59,119
Speaker 1: bee hole. Yeah. Yeah, so I started the same deal.

430
00:24:59,200 --> 00:25:01,520
Speaker 1: But we wait for them to flash you sometimes. I

431
00:25:01,560 --> 00:25:03,960
Speaker 1: don't know. I don't know the Tom Petty Cannon fact tracks,

432
00:25:05,080 --> 00:25:09,400
Speaker 1: but he made that claim. Yeah, how many would you find?

433
00:25:09,520 --> 00:25:13,280
Speaker 1: Was it a good day a bird? Oh? No, more

434
00:25:13,320 --> 00:25:17,639
Speaker 1: than that. Yeah, you'd be finding there's tons of juncles

435
00:25:17,640 --> 00:25:19,840
Speaker 1: there you'd find. I don't know, I don't remember. Probably

436
00:25:19,920 --> 00:25:22,879
Speaker 1: four or five might be a good day, just working

437
00:25:22,880 --> 00:25:25,840
Speaker 1: by yourself. Yeah, So, how like when you do these

438
00:25:25,920 --> 00:25:29,560
Speaker 1: jobs like we're gonna get to we're gonna talk about

439
00:25:29,560 --> 00:25:30,879
Speaker 1: a bunch of but how many jobs like this? If

440
00:25:30,920 --> 00:25:33,639
Speaker 1: you had coming into work on a research project that

441
00:25:33,760 --> 00:25:37,080
Speaker 1: involved you run around out in the woods, that's what

442
00:25:37,320 --> 00:25:39,240
Speaker 1: they've all been. I don't know how many jobs I've done,

443
00:25:39,359 --> 00:25:47,640
Speaker 1: doesn't Yeah? Maybe almost? How are they described? Um, there's

444
00:25:47,640 --> 00:25:50,879
Speaker 1: a big the Texas A and M has a wildlife

445
00:25:50,880 --> 00:25:53,680
Speaker 1: program and they have just an online job board that's

446
00:25:53,720 --> 00:25:55,520
Speaker 1: kind of the go to for a lot of people.

447
00:25:55,880 --> 00:25:58,400
Speaker 1: You just start cruising the job board and you find

448
00:25:58,400 --> 00:26:00,840
Speaker 1: a job. Then you're like, the that's in a cool place,

449
00:26:01,119 --> 00:26:03,880
Speaker 1: and i'd be doing something cool. I'm interested in that.

450
00:26:03,920 --> 00:26:06,320
Speaker 1: And you apply and and the more you do then

451
00:26:06,320 --> 00:26:09,000
Speaker 1: the better your resume is, right, Yeah, and so I was.

452
00:26:09,320 --> 00:26:11,280
Speaker 1: But as the goal to wind up, like do you

453
00:26:11,320 --> 00:26:13,280
Speaker 1: have a goal you'll do? You want to keep doing this?

454
00:26:13,440 --> 00:26:14,800
Speaker 1: You have a goal you'll wind up like at a

455
00:26:14,800 --> 00:26:19,399
Speaker 1: fixed position. Yeah. See, that's something I agonize over because

456
00:26:19,520 --> 00:26:24,000
Speaker 1: I love being in the field. I love doing what

457
00:26:24,080 --> 00:26:27,719
Speaker 1: I do, and I I would I'm dreading the day

458
00:26:27,760 --> 00:26:32,080
Speaker 1: when that my typical day involves a lot more office work,

459
00:26:32,160 --> 00:26:35,560
Speaker 1: which it will when I some day get a permanent job,

460
00:26:35,600 --> 00:26:39,000
Speaker 1: which is I would only do because you know you're

461
00:26:39,000 --> 00:26:41,320
Speaker 1: going to make more money and it's just more stable.

462
00:26:41,320 --> 00:26:46,520
Speaker 1: And there's certain fields I think that do that. Yeah.

463
00:26:46,560 --> 00:26:48,080
Speaker 1: And the higher up you go in the field, the

464
00:26:48,119 --> 00:26:50,199
Speaker 1: less you're in the field. And I got friends like

465
00:26:50,200 --> 00:26:53,320
Speaker 1: in the military too, man, Like they train up to

466
00:26:53,400 --> 00:26:55,639
Speaker 1: learn how to do all this like badass stuff, and

467
00:26:55,760 --> 00:26:57,960
Speaker 1: like you do well at it, and eventually what that

468
00:26:58,000 --> 00:27:00,359
Speaker 1: means is you stopped doing it because for soon you

469
00:27:00,440 --> 00:27:03,600
Speaker 1: have a desk. Yeah, exactly. I cling to the hope

470
00:27:03,600 --> 00:27:05,639
Speaker 1: that your job is some what you make of it.

471
00:27:05,720 --> 00:27:09,960
Speaker 1: And so, UM, if I can get a job where

472
00:27:10,440 --> 00:27:14,560
Speaker 1: I'm doing some office stuff and maybe you know, getting

473
00:27:14,560 --> 00:27:18,000
Speaker 1: to um think of research projects and actually be managing

474
00:27:18,000 --> 00:27:21,120
Speaker 1: research projects, but balance out with some field work, that'd

475
00:27:21,160 --> 00:27:24,560
Speaker 1: be good. That'd be ideal. UM doing carnivore stuff, that

476
00:27:24,560 --> 00:27:27,760
Speaker 1: would be good. But I've been having a lot of

477
00:27:27,760 --> 00:27:30,199
Speaker 1: fun doing this, and I've been fortunate enough to be

478
00:27:30,280 --> 00:27:33,320
Speaker 1: able to um for a lot of this time before

479
00:27:33,359 --> 00:27:36,159
Speaker 1: I kind of settled down in eastern Washington, to be

480
00:27:36,200 --> 00:27:38,240
Speaker 1: able to just kind of travel all over, which really

481
00:27:38,480 --> 00:27:40,320
Speaker 1: opens up the number of jobs you can apply for

482
00:27:40,359 --> 00:27:43,840
Speaker 1: obviously if you're free to just go and live wherever

483
00:27:43,920 --> 00:27:46,159
Speaker 1: for a season. How many years ago was it that

484
00:27:46,200 --> 00:27:48,440
Speaker 1: you did, like the junk thing in the Hawaii thing.

485
00:27:48,880 --> 00:27:52,440
Speaker 1: Let's see, I started school in two thousand two Hawaii,

486
00:27:52,520 --> 00:27:56,960
Speaker 1: was I guess two thou four? Yeah? Yeah, And then

487
00:27:56,960 --> 00:27:58,760
Speaker 1: what'd you go on to do after? Because you still

488
00:27:58,760 --> 00:28:02,800
Speaker 1: haven't done a carnivore job for tracking year my career. Yeah,

489
00:28:02,960 --> 00:28:07,520
Speaker 1: so like hunting bird eggs, hunting bird eggs, and I, UM,

490
00:28:07,560 --> 00:28:09,399
Speaker 1: I knew I want to do carnivore. I knew I

491
00:28:09,400 --> 00:28:12,040
Speaker 1: want to do wildlife stuff from when I was really little,

492
00:28:12,320 --> 00:28:15,560
Speaker 1: and then I started getting really interested in carnivores and

493
00:28:15,600 --> 00:28:19,399
Speaker 1: knew I wanted to do that, but I couldn't. I

494
00:28:19,400 --> 00:28:22,480
Speaker 1: don't know it didn't. I was applying for carnivore jobs,

495
00:28:22,480 --> 00:28:27,240
Speaker 1: but I think people were hesitant to hire a twentysomething

496
00:28:27,280 --> 00:28:30,760
Speaker 1: You're old girl who's going to go and trap bears.

497
00:28:31,000 --> 00:28:33,159
Speaker 1: I mean, I think I needed to prove myself a

498
00:28:33,200 --> 00:28:35,720
Speaker 1: little bit. So, UM, do you feel like there was

499
00:28:35,720 --> 00:28:39,320
Speaker 1: a you feel like it's an honest bias there. Yes,

500
00:28:39,520 --> 00:28:42,800
Speaker 1: I can constantly say that it's definitely, especially in the

501
00:28:42,800 --> 00:28:46,080
Speaker 1: carnival world, is it's definitely a boys club, and that's

502
00:28:46,280 --> 00:28:50,320
Speaker 1: um something I'm conscious of. But it's also I mean,

503
00:28:50,360 --> 00:28:53,320
Speaker 1: it's not like it's been a problem or something in

504
00:28:53,360 --> 00:28:56,719
Speaker 1: the field where I'm I feel like people are respectful

505
00:28:56,760 --> 00:29:01,200
Speaker 1: of my abilities and stuff. So have you overcome it now,

506
00:29:03,440 --> 00:29:06,440
Speaker 1: Like does your resume override? Like did you or there's

507
00:29:06,440 --> 00:29:08,040
Speaker 1: still some people like I don't care what I see

508
00:29:08,080 --> 00:29:11,880
Speaker 1: on this resume. It's a girl. I don't know if

509
00:29:11,920 --> 00:29:18,360
Speaker 1: people would not hire me because of that. Um, everybody

510
00:29:18,400 --> 00:29:20,320
Speaker 1: I worked with has been great, but there have been

511
00:29:20,360 --> 00:29:25,320
Speaker 1: people where it takes a little longer to gain their respect,

512
00:29:25,440 --> 00:29:28,080
Speaker 1: and I'm I have the feeling. I mean, it happens

513
00:29:28,200 --> 00:29:31,080
Speaker 1: enough and I see them interacting with other men on

514
00:29:31,120 --> 00:29:34,160
Speaker 1: the crew or whatever that I sense that it is

515
00:29:34,800 --> 00:29:41,480
Speaker 1: maybe just even a subconscious biased against what they think

516
00:29:41,560 --> 00:29:44,400
Speaker 1: I could do in the field. I had someone in

517
00:29:44,560 --> 00:29:49,760
Speaker 1: archaeology one time refer to the Bison boys, and I said,

518
00:29:49,760 --> 00:29:52,040
Speaker 1: what are the Bison boys? And she was saying, well,

519
00:29:52,320 --> 00:29:54,840
Speaker 1: in this field, that helps. If you're working on bison

520
00:29:54,960 --> 00:30:00,560
Speaker 1: and your boys. It's all about like, uh that and that,

521
00:30:00,760 --> 00:30:04,080
Speaker 1: Like in New World archaeology on the great you know, plains,

522
00:30:04,240 --> 00:30:07,520
Speaker 1: it's like the bois and boys, the bearer boys. Yeah,

523
00:30:07,600 --> 00:30:11,000
Speaker 1: And I think it's it's common with those field jobs

524
00:30:11,000 --> 00:30:15,280
Speaker 1: that are especially I don't know, more traditionally thought of

525
00:30:15,360 --> 00:30:17,880
Speaker 1: as I don't know if macho is the right word,

526
00:30:17,920 --> 00:30:21,920
Speaker 1: but you know, it involves trucks and knowing how to

527
00:30:21,960 --> 00:30:25,840
Speaker 1: get yourself unstuck when your truck stuff. It involves snowmobiles

528
00:30:25,840 --> 00:30:29,200
Speaker 1: and four wheelers and big animals that you're moving around

529
00:30:29,240 --> 00:30:33,560
Speaker 1: and traps. And I don't I mean, I don't blame

530
00:30:33,560 --> 00:30:37,880
Speaker 1: people because they are an examples out there of women

531
00:30:37,880 --> 00:30:39,880
Speaker 1: doing this a who lot, and so people I think

532
00:30:39,920 --> 00:30:43,160
Speaker 1: just look at me. The first thing they think, it's

533
00:30:43,200 --> 00:30:49,600
Speaker 1: probably not. I don't know, burly trapper biologists girls, you know.

534
00:30:50,400 --> 00:30:54,760
Speaker 1: So I don't know, but I can usually get people

535
00:30:54,800 --> 00:30:59,280
Speaker 1: past that and it works out. So yeah, so bird

536
00:30:59,320 --> 00:31:02,800
Speaker 1: collecting egg gathering. They ate one of those eggs, right, No,

537
00:31:02,920 --> 00:31:05,120
Speaker 1: I didn't. I was watching. I was watching it in

538
00:31:05,160 --> 00:31:08,920
Speaker 1: there with my kids. Man. It was they like to

539
00:31:08,960 --> 00:31:11,160
Speaker 1: watch stuff about the Arctic, and we were watching these

540
00:31:11,880 --> 00:31:15,840
Speaker 1: videos and these boys who just with like old shitty

541
00:31:16,200 --> 00:31:20,840
Speaker 1: three agents, three eights inch line repelled down cliff faces

542
00:31:20,920 --> 00:31:25,880
Speaker 1: to gather eggs. Yeah, they rigg up they got this

543
00:31:26,160 --> 00:31:28,760
Speaker 1: looks like crab hot rope, and they rig up a

544
00:31:28,800 --> 00:31:31,280
Speaker 1: harness and ship and they take the oldest, frailest, older

545
00:31:31,280 --> 00:31:34,080
Speaker 1: guy because he's real life, lower him down over that edge,

546
00:31:34,160 --> 00:31:36,120
Speaker 1: has some bitches garing those eggs up, and they're saying,

547
00:31:36,160 --> 00:31:38,600
Speaker 1: and this the narrators something baha is a common way

548
00:31:38,640 --> 00:31:41,040
Speaker 1: to die. This is in Siberia. I bet have you

549
00:31:41,080 --> 00:31:47,880
Speaker 1: seen that footage of collecting um nest for egg nest

550
00:31:48,040 --> 00:31:52,560
Speaker 1: soup and they're going down these rickety the middle scaffold systems.

551
00:31:53,320 --> 00:31:58,400
Speaker 1: I've tried to do that with. That's a swallow. Yeah,

552
00:31:59,760 --> 00:32:03,720
Speaker 1: one yeah, yeah, what is that family? Like they have

553
00:32:03,760 --> 00:32:07,960
Speaker 1: a saliva and they take stuff in their mouth and

554
00:32:07,960 --> 00:32:10,200
Speaker 1: they cold it with the slive, and the slive is sticky,

555
00:32:10,480 --> 00:32:14,320
Speaker 1: and they build their nests and then um, you boil

556
00:32:14,360 --> 00:32:16,760
Speaker 1: it down and you can extract that sticky saliva and

557
00:32:16,880 --> 00:32:20,960
Speaker 1: used the thicken soups. And I've taken you know those

558
00:32:21,040 --> 00:32:23,920
Speaker 1: kind of swallows that like build them under bridges the

559
00:32:24,040 --> 00:32:27,280
Speaker 1: mud the mud, Yeah, like a barn swallow or something. Yeah,

560
00:32:27,280 --> 00:32:30,200
Speaker 1: I've taken shiploads of those nests and boil them all

561
00:32:30,240 --> 00:32:33,720
Speaker 1: down and then and then skimmed off the you know,

562
00:32:33,760 --> 00:32:36,360
Speaker 1: let the mud settle, and then cooked it down. I've

563
00:32:36,360 --> 00:32:39,000
Speaker 1: never found that ship in there, whatever it is, like,

564
00:32:39,320 --> 00:32:42,040
Speaker 1: I've never isolated what it is that the sticky stuff,

565
00:32:42,040 --> 00:32:44,680
Speaker 1: because I wanted to make some of that soup, and

566
00:32:45,800 --> 00:32:48,360
Speaker 1: I figured that they don't reuse those, you know, those

567
00:32:48,400 --> 00:32:50,760
Speaker 1: dome nests. I figured you could probably break those up

568
00:32:50,760 --> 00:32:52,600
Speaker 1: without breaking any laws and now to get them under

569
00:32:52,680 --> 00:32:55,680
Speaker 1: urban bridges. But I could never get whatever they're after.

570
00:32:56,080 --> 00:32:58,720
Speaker 1: I don't know if it's like whatever they used to

571
00:32:58,760 --> 00:33:01,120
Speaker 1: make that mud sticky, don't know how they extract it

572
00:33:01,160 --> 00:33:04,040
Speaker 1: when they cook it. Well, that maybe the mud they

573
00:33:04,120 --> 00:33:06,200
Speaker 1: use is already sticking. They don't need any of their

574
00:33:06,200 --> 00:33:08,480
Speaker 1: own special I didn't do a whole hell of a

575
00:33:08,480 --> 00:33:10,360
Speaker 1: lot of research. I just I just jumped right into

576
00:33:10,440 --> 00:33:14,960
Speaker 1: it and might be delicious real quick before we get

577
00:33:15,000 --> 00:33:18,120
Speaker 1: off the birds. You called it miss netting. Yeah, eting,

578
00:33:18,240 --> 00:33:22,080
Speaker 1: So that's how you catch birds. Songbirds to put little

579
00:33:22,080 --> 00:33:24,760
Speaker 1: bands on their legs. So you set up these nets

580
00:33:24,840 --> 00:33:27,880
Speaker 1: that are just really fine. You can hardly see them

581
00:33:28,160 --> 00:33:33,720
Speaker 1: missed or miss missed. Oh, I said, yeah, they made

582
00:33:33,760 --> 00:33:35,280
Speaker 1: like missing them. I was like, that doesn't seem like

583
00:33:35,320 --> 00:33:38,560
Speaker 1: an effective way I'd be hit. I'd be hitting no

584
00:33:38,800 --> 00:33:41,040
Speaker 1: missed nets. So you set those up in the morning,

585
00:33:41,120 --> 00:33:43,080
Speaker 1: and they don't they don't, they don't break their bones

586
00:33:43,120 --> 00:33:45,560
Speaker 1: and ship they fly into them and they get tangled,

587
00:33:45,640 --> 00:33:48,280
Speaker 1: and so then you go out there and untangle them,

588
00:33:48,320 --> 00:33:51,400
Speaker 1: and then you can, you know, drop blood and measure things,

589
00:33:51,480 --> 00:33:55,720
Speaker 1: and you gotta have some mortality, right, there is some mortality, yeah,

590
00:33:55,760 --> 00:33:58,200
Speaker 1: but I don't think it's real great. Especially I think

591
00:33:58,240 --> 00:34:01,000
Speaker 1: the most dangerous part is getting them out of the net.

592
00:34:01,120 --> 00:34:02,440
Speaker 1: Is kind of a trick to learn how to do

593
00:34:02,520 --> 00:34:05,760
Speaker 1: that really delicately. But I got a body I don't

594
00:34:05,760 --> 00:34:10,400
Speaker 1: want to say his name. He works with ducks, and

595
00:34:10,560 --> 00:34:13,920
Speaker 1: his PhD advisor said, if you're not killing some ducks,

596
00:34:13,960 --> 00:34:20,400
Speaker 1: you're not working hard, meaning like gets you know, he

597
00:34:20,440 --> 00:34:23,480
Speaker 1: wanted them, he wanted them to get some data and

598
00:34:23,520 --> 00:34:26,080
Speaker 1: like if everything, if you're making all your decisions around

599
00:34:26,120 --> 00:34:29,160
Speaker 1: no mortality, you know. His feeling was, yeah, and that's

600
00:34:29,200 --> 00:34:31,239
Speaker 1: a balance. You work with mallards and things. I mean,

601
00:34:31,239 --> 00:34:32,719
Speaker 1: you work, you're not you know, it's like you're trying

602
00:34:32,760 --> 00:34:39,160
Speaker 1: to catch the last ivory build woodpecker, right yeah, um yeah,

603
00:34:39,239 --> 00:34:44,239
Speaker 1: So after birds, then I, um, I got into carnivores.

604
00:34:44,280 --> 00:34:48,799
Speaker 1: Finally I volunteered. So I spent volunteers. Yeah, I spent right,

605
00:34:48,840 --> 00:34:53,439
Speaker 1: I spent this summer just um trapping bears around where

606
00:34:53,440 --> 00:34:56,719
Speaker 1: I lived, helping out with trapping effort there. And then

607
00:34:57,520 --> 00:35:02,239
Speaker 1: that wasn't humble having bears and cleaning houses in California. Yeah,

608
00:35:02,280 --> 00:35:06,680
Speaker 1: clean the houses and take care of somebody's homestead, doing

609
00:35:06,719 --> 00:35:08,480
Speaker 1: their garden and stuff like that. So I'd cleaned some

610
00:35:08,560 --> 00:35:11,719
Speaker 1: days and then I go trap bears other days and

611
00:35:11,760 --> 00:35:13,360
Speaker 1: how are they what was what was going on with

612
00:35:13,400 --> 00:35:15,759
Speaker 1: the bears? How are they catching foot snares? No? So

613
00:35:15,840 --> 00:35:19,120
Speaker 1: there we were using just colvert traps so it's a bit.

614
00:35:19,280 --> 00:35:22,799
Speaker 1: It's a piece of covert usually blocked off on one end,

615
00:35:23,160 --> 00:35:26,240
Speaker 1: and at that end. For that job, we were using

616
00:35:26,880 --> 00:35:31,959
Speaker 1: um a sock. Stuff it full of dog food, dip

617
00:35:32,000 --> 00:35:37,200
Speaker 1: it in old nasty friar grease um, and then hang

618
00:35:37,320 --> 00:35:39,640
Speaker 1: some fish carcasses. So you hang that in the back.

619
00:35:40,880 --> 00:35:46,320
Speaker 1: I think they were like just salmon carcasses, UM stinky stuff.

620
00:35:46,360 --> 00:35:49,319
Speaker 1: Basically hang that in the back of the trap on

621
00:35:49,360 --> 00:35:52,359
Speaker 1: a chain that's connected to the like a guillotine door.

622
00:35:53,080 --> 00:35:56,480
Speaker 1: They go in, pull on it, door closes. You go

623
00:35:56,560 --> 00:35:59,840
Speaker 1: up to the trap and there's little hatches on the

624
00:36:00,000 --> 00:36:02,439
Speaker 1: sides that you can open up to stick. Jab stick

625
00:36:03,200 --> 00:36:08,040
Speaker 1: UM so lar a long pole with the hypodermic needle

626
00:36:08,080 --> 00:36:10,680
Speaker 1: on the end and instead of the plunger, you've got

627
00:36:10,719 --> 00:36:14,680
Speaker 1: the pole going into the um casing of the needle

628
00:36:15,000 --> 00:36:22,480
Speaker 1: or the um whatever that's called, the two that holds

629
00:36:22,560 --> 00:36:27,839
Speaker 1: the drugs the impact of you exactly. Yeah. So then

630
00:36:28,120 --> 00:36:31,319
Speaker 1: you um, somebody kind of distracts the bear. You're over

631
00:36:31,320 --> 00:36:32,919
Speaker 1: by the hole and you jab it in the butt.

632
00:36:33,719 --> 00:36:35,960
Speaker 1: Go sleep. You open the door and pull it out

633
00:36:36,040 --> 00:36:43,560
Speaker 1: and when you roll up. Usually it depends um, it

634
00:36:43,600 --> 00:36:48,000
Speaker 1: depends on their personality. And it depends on how carefully

635
00:36:48,040 --> 00:36:51,800
Speaker 1: you are about, you know, moving slowly and being quiet.

636
00:36:51,920 --> 00:36:55,960
Speaker 1: I like to, across species try and keep them as

637
00:36:56,200 --> 00:36:59,160
Speaker 1: calm as you can, just react better to the drug

638
00:36:59,239 --> 00:37:03,440
Speaker 1: and you just I mean, it's a stressful, awful experience

639
00:37:03,480 --> 00:37:06,600
Speaker 1: for them. I think, um, even when they're under with

640
00:37:06,640 --> 00:37:09,160
Speaker 1: a lot of the drugs, it's like I've had it

641
00:37:09,239 --> 00:37:13,600
Speaker 1: described as a really bad trip basically depending on the drugs.

642
00:37:13,600 --> 00:37:15,840
Speaker 1: So if you're making a lot of noise and jiggling

643
00:37:15,840 --> 00:37:19,320
Speaker 1: them around and stuff, I don't know, it just sounds awful.

644
00:37:19,560 --> 00:37:22,719
Speaker 1: So um, and there's complications that can happen if they

645
00:37:22,719 --> 00:37:27,360
Speaker 1: start getting stressed out while they're under. So anyway, sometimes

646
00:37:27,360 --> 00:37:32,080
Speaker 1: they're you know, popping their lips and banging around on

647
00:37:32,080 --> 00:37:35,000
Speaker 1: the trap, but sometimes they're calm. I think a lot

648
00:37:35,040 --> 00:37:38,440
Speaker 1: of that is just individual personality. But they gotta get

649
00:37:38,440 --> 00:37:41,480
Speaker 1: trapshy fro those cool word traps. That's funny. That's also

650
00:37:41,560 --> 00:37:46,560
Speaker 1: across species also. That can be kind of uh individual too,

651
00:37:46,560 --> 00:37:52,279
Speaker 1: because sometimes they've had animals get very trapped happy where

652
00:37:52,280 --> 00:37:54,839
Speaker 1: they like it's not that bad. I get to go

653
00:37:54,880 --> 00:37:59,839
Speaker 1: on the trap, I get a meal and then oh yeah,

654
00:38:00,000 --> 00:38:01,799
Speaker 1: because when I used to trap fox. You know, if

655
00:38:01,840 --> 00:38:03,879
Speaker 1: you pinched the toe on a fox and then get them,

656
00:38:04,280 --> 00:38:08,160
Speaker 1: they got mark about that ship. Yeah, canines are a

657
00:38:08,200 --> 00:38:12,200
Speaker 1: little different, and these are um, I mean traps with bait.

658
00:38:12,560 --> 00:38:15,319
Speaker 1: You know, that's where you'd have it happened more so.

659
00:38:15,360 --> 00:38:19,040
Speaker 1: We for example, we had a lynx that was always

660
00:38:19,040 --> 00:38:21,319
Speaker 1: getting in our traps. We'd already put a collar on him.

661
00:38:21,440 --> 00:38:23,600
Speaker 1: He'd always get in our traps and he'd figured out

662
00:38:23,680 --> 00:38:25,680
Speaker 1: that he could just ch a hole through the trap,

663
00:38:25,760 --> 00:38:30,480
Speaker 1: get out, go down the trapline. So for links on

664
00:38:31,960 --> 00:38:33,839
Speaker 1: back up from it. Okay, why are you guys catching

665
00:38:33,840 --> 00:38:35,960
Speaker 1: the bears? What were trying to figure out the bears?

666
00:38:36,080 --> 00:38:38,560
Speaker 1: This is on Timber Company land and they were having

667
00:38:38,600 --> 00:38:42,839
Speaker 1: a lot of problems with bears girdling the trees because

668
00:38:42,840 --> 00:38:45,120
Speaker 1: they eat them. Yeah, and so it kills the people

669
00:38:45,200 --> 00:38:47,799
Speaker 1: here struggle with that, like on the Limited Peninsula talk

670
00:38:47,880 --> 00:38:50,440
Speaker 1: about want doing bear control because of how much they

671
00:38:50,440 --> 00:38:53,040
Speaker 1: girdle and kill trees. Yeah, so they were trying to

672
00:38:53,080 --> 00:38:57,879
Speaker 1: figure out where they were going. We should explain girdling. Oh,

673
00:38:58,000 --> 00:38:59,920
Speaker 1: like you know, in the old days, we went out

674
00:38:59,920 --> 00:39:02,440
Speaker 1: to clear land. Like when you hear about you know,

675
00:39:02,640 --> 00:39:05,120
Speaker 1: pioneer type settlers when they would clear land, they would

676
00:39:05,160 --> 00:39:07,120
Speaker 1: generally go in to get your first crop, and they're

677
00:39:07,120 --> 00:39:10,000
Speaker 1: just going girdle the tree. So you cut through the

678
00:39:10,000 --> 00:39:12,880
Speaker 1: bark and through the cambium layer all the way around

679
00:39:12,880 --> 00:39:16,600
Speaker 1: the tree. Um. Think about like a girdle on someone's leg. Right,

680
00:39:16,600 --> 00:39:19,960
Speaker 1: you're just like cutting a ring around the tree and

681
00:39:20,000 --> 00:39:23,440
Speaker 1: then kill the tree. Yeah, and then you could, so

682
00:39:23,520 --> 00:39:26,279
Speaker 1: you would. You don't need it necessarily to start to

683
00:39:26,440 --> 00:39:29,160
Speaker 1: establish farmland or whatever. You didn't need to necessarily going

684
00:39:29,200 --> 00:39:32,760
Speaker 1: and log the thing off. You can just girdle everything first.

685
00:39:33,360 --> 00:39:35,400
Speaker 1: That lets sunlight through and you can start growing crops,

686
00:39:35,440 --> 00:39:37,799
Speaker 1: and at your leisure you can go in and cut

687
00:39:37,840 --> 00:39:39,719
Speaker 1: the tree down. So people will talk about girdling a

688
00:39:39,719 --> 00:39:41,319
Speaker 1: tree to kill it, just doing that to it. And

689
00:39:41,360 --> 00:39:44,000
Speaker 1: bears are just doing that because they're just eating. Yeah,

690
00:39:44,040 --> 00:39:47,040
Speaker 1: they're eating the cambium land which is right under the bark,

691
00:39:47,480 --> 00:39:50,320
Speaker 1: and so they're eating out. So they're stripping the bark

692
00:39:50,400 --> 00:39:53,080
Speaker 1: up um, and they'll go all the way around the

693
00:39:53,120 --> 00:39:55,080
Speaker 1: tree or probably just strip it far enough up that

694
00:39:55,200 --> 00:40:00,520
Speaker 1: it can kill and damage. Yeah. Yeah, conifers. So they

695
00:40:00,560 --> 00:40:05,920
Speaker 1: were um every time yearly hitting the trees. Oh I

696
00:40:05,960 --> 00:40:09,080
Speaker 1: don't know, but there I think if I remember right,

697
00:40:09,120 --> 00:40:14,000
Speaker 1: I actually did my like senior thesis, uh, using some

698
00:40:14,120 --> 00:40:17,160
Speaker 1: of this information that we learned. But they liked to

699
00:40:17,200 --> 00:40:19,640
Speaker 1: hit the young, fast growing trees. I think if there's

700
00:40:19,680 --> 00:40:24,279
Speaker 1: more Cambium um and so in a you know, unlogging land,

701
00:40:24,280 --> 00:40:27,440
Speaker 1: that's a problem for them. But they were one of

702
00:40:27,480 --> 00:40:30,520
Speaker 1: the things they were hoping they might discover from the

703
00:40:30,600 --> 00:40:35,719
Speaker 1: callers that we were putting on them, um was were

704
00:40:35,760 --> 00:40:42,560
Speaker 1: they migrating in the fall two places for um acorns

705
00:40:43,120 --> 00:40:49,000
Speaker 1: where they could maybe direct hunters, so hopefully, Uh, the

706
00:40:49,040 --> 00:40:52,080
Speaker 1: goal was to maybe figure out how to target the

707
00:40:52,120 --> 00:40:54,680
Speaker 1: bears that were impacting there. So they were like trying

708
00:40:54,680 --> 00:40:59,640
Speaker 1: to do scouting for people. Basically, yeah, that's the kind

709
00:40:59,640 --> 00:41:04,719
Speaker 1: of roof church light. That's well and yeah, and I

710
00:41:04,760 --> 00:41:06,719
Speaker 1: don't know, I actually don't know what became of that.

711
00:41:06,840 --> 00:41:08,440
Speaker 1: They wanted to be like, where are these sons of

712
00:41:08,480 --> 00:41:13,120
Speaker 1: bitches in the fall during hunting season? Yeah, basically, yeah,

713
00:41:13,400 --> 00:41:18,000
Speaker 1: there's also a master there's dirty pool right there. There's

714
00:41:18,320 --> 00:41:22,640
Speaker 1: to get my hands on some of that. There were also, um,

715
00:41:22,680 --> 00:41:24,799
Speaker 1: there's a master's student on that project. I'm not sure

716
00:41:24,840 --> 00:41:27,480
Speaker 1: what she was using the data for. And then I

717
00:41:27,480 --> 00:41:31,480
Speaker 1: did like a habit a little habitat analysis with the

718
00:41:31,560 --> 00:41:34,120
Speaker 1: data that we got. But so then we'd go and um,

719
00:41:34,160 --> 00:41:36,400
Speaker 1: after we trapped, we went out and we do telemetry

720
00:41:36,480 --> 00:41:39,440
Speaker 1: to figure out where they were hanging out. Did you

721
00:41:39,440 --> 00:41:41,120
Speaker 1: ever mess up and get scratched up by a bear

722
00:41:41,160 --> 00:41:43,879
Speaker 1: when you're working a bear? No, I haven't had them

723
00:41:43,880 --> 00:41:47,440
Speaker 1: come up, come back to or something. No. That generally

724
00:41:47,480 --> 00:41:50,239
Speaker 1: happens pretty slowly. So they start lifting their head a

725
00:41:50,280 --> 00:41:52,720
Speaker 1: little and you can just you know, try and calm

726
00:41:52,760 --> 00:41:55,759
Speaker 1: them down. They have a you put a blindfold on

727
00:41:55,800 --> 00:41:58,480
Speaker 1: them to help keep them calm. You heard about that

728
00:41:58,520 --> 00:42:00,759
Speaker 1: story Montane, Right, some guy as are working up at

729
00:42:00,760 --> 00:42:05,000
Speaker 1: Grizzly and they were they're working it up. They were

730
00:42:05,040 --> 00:42:07,600
Speaker 1: relocating it or just working it up, but either way,

731
00:42:07,640 --> 00:42:12,000
Speaker 1: they put some signage out while they're working. Got all done.

732
00:42:12,040 --> 00:42:15,800
Speaker 1: The bear is still comb a toaster be still sedated.

733
00:42:16,560 --> 00:42:21,680
Speaker 1: They took down their signage. Some fellow who lives in

734
00:42:21,680 --> 00:42:23,279
Speaker 1: the area had seen him in there and wonder what

735
00:42:23,360 --> 00:42:26,919
Speaker 1: they were doing. Goes in there, bear wakes up, kills

736
00:42:26,920 --> 00:42:32,320
Speaker 1: that dude. Yeah, super unfortunate. Yeah. Yeah, So we after

737
00:42:32,480 --> 00:42:34,600
Speaker 1: on that project. After we worked up the bear, we'd

738
00:42:34,600 --> 00:42:38,080
Speaker 1: put it back in the trap and let it recover fully. Yeah,

739
00:42:38,120 --> 00:42:40,400
Speaker 1: and then we um could actually tie a rope, so

740
00:42:40,440 --> 00:42:43,319
Speaker 1: you don't put him out when he's vulnerable, right, And

741
00:42:43,360 --> 00:42:46,880
Speaker 1: we didn't want them like, I mean, they're they're drunk

742
00:42:46,880 --> 00:42:49,719
Speaker 1: seeming when they start to stumble off, So we didn't

743
00:42:49,719 --> 00:42:52,239
Speaker 1: want them walking down a logging road and you know,

744
00:42:54,080 --> 00:42:56,480
Speaker 1: get its wits about it. Oh, definitely, because they could

745
00:42:56,840 --> 00:43:00,040
Speaker 1: be killed by another bear or whatever. So yeah, so

746
00:43:00,040 --> 00:43:03,359
Speaker 1: we'd let him recover in the trap and then tie

747
00:43:03,400 --> 00:43:05,000
Speaker 1: a rope to the door, tie that to the truck

748
00:43:05,040 --> 00:43:07,880
Speaker 1: and open the the door that way and let him

749
00:43:07,960 --> 00:43:10,280
Speaker 1: run off. And when they come out, are they usually

750
00:43:10,360 --> 00:43:13,279
Speaker 1: just looking to get out of town. They want to

751
00:43:13,280 --> 00:43:17,120
Speaker 1: get away from probably probably get a little bit um

752
00:43:17,200 --> 00:43:19,920
Speaker 1: imagine like the vast majority of grizzlies are probably the

753
00:43:19,960 --> 00:43:21,680
Speaker 1: same way, But I think they'd be more inclined to

754
00:43:21,760 --> 00:43:25,279
Speaker 1: maybe come out and be like looking to a sign blame. Yeah,

755
00:43:25,440 --> 00:43:27,680
Speaker 1: be a little piste. Yeah, I'd be like, first, I'm

756
00:43:27,680 --> 00:43:30,480
Speaker 1: gonna take care of this. I'm gonna make this thing

757
00:43:30,560 --> 00:43:34,879
Speaker 1: not want to mess with me anymore. And like, yeah,

758
00:43:34,920 --> 00:43:37,239
Speaker 1: we got a friend, We had a friend saved mule

759
00:43:37,239 --> 00:43:39,319
Speaker 1: in your buck who got all hung up in some

760
00:43:39,400 --> 00:43:41,239
Speaker 1: ropes on a fence and once you got it cut

761
00:43:41,280 --> 00:43:48,439
Speaker 1: for you to tack. I have not had that happen yet.

762
00:43:50,360 --> 00:43:55,040
Speaker 1: So all right, what's up with the house cleaning? You're

763
00:43:55,040 --> 00:43:59,000
Speaker 1: working for a service or just running ads at that time,

764
00:43:59,080 --> 00:44:01,879
Speaker 1: and howmelt you could put your name on this just

765
00:44:02,040 --> 00:44:06,120
Speaker 1: kind of like pick up odd jobs sort of thing.

766
00:44:06,920 --> 00:44:09,560
Speaker 1: And so I put myself on that list for house

767
00:44:09,560 --> 00:44:13,360
Speaker 1: cleaning and like yard work and super around the people's houses.

768
00:44:13,760 --> 00:44:21,640
Speaker 1: Oh man, stuff. Yeah, you know their secrets, I imagine, man, Yeah,

769
00:44:22,080 --> 00:44:24,200
Speaker 1: if you probably don't really hide their secrets as well

770
00:44:24,239 --> 00:44:25,799
Speaker 1: as they think they do. Right, it's not all you

771
00:44:25,800 --> 00:44:27,600
Speaker 1: get to do any real snoop and right. And I'm

772
00:44:27,640 --> 00:44:30,239
Speaker 1: an annual cleaner, so I'm like deep cleaning, you know,

773
00:44:30,400 --> 00:44:35,799
Speaker 1: I'm dusting inside the drawers and stuff like that. Yeah. Yeah,

774
00:44:36,040 --> 00:44:39,000
Speaker 1: Actually I think I'm a good cleaner for the same

775
00:44:39,080 --> 00:44:41,960
Speaker 1: reason that uh, I do pretty well in biology. It's

776
00:44:42,000 --> 00:44:45,919
Speaker 1: attention to detail. There's some overlap there. Yeah. So then

777
00:44:46,040 --> 00:44:51,080
Speaker 1: so are you now like professionally as a field biologists.

778
00:44:51,120 --> 00:44:52,880
Speaker 1: Are you now you just can work or do you

779
00:44:52,880 --> 00:44:55,480
Speaker 1: stuck to do side jobs in the off season? Is

780
00:44:55,520 --> 00:44:57,120
Speaker 1: there a sason you call you guys talk about a

781
00:44:57,120 --> 00:44:59,480
Speaker 1: busy season. Why is there a busy season, Well, there's

782
00:44:59,600 --> 00:45:02,360
Speaker 1: I mean in summer, there's usually a lot of jobs

783
00:45:02,400 --> 00:45:05,200
Speaker 1: because that's when people can get out there easily. There

784
00:45:05,200 --> 00:45:07,960
Speaker 1: it's easier to collect data in the summer and then

785
00:45:08,000 --> 00:45:09,799
Speaker 1: but there's always jobs that are going on the winter

786
00:45:09,880 --> 00:45:12,200
Speaker 1: to just usually not as many. A lot of times

787
00:45:12,200 --> 00:45:15,640
Speaker 1: that's when projects take time to you know, do their

788
00:45:15,640 --> 00:45:18,600
Speaker 1: analysis or whatever. So the field portion is often in

789
00:45:18,640 --> 00:45:21,360
Speaker 1: the summer. But then there's jobs that are specific to

790
00:45:21,400 --> 00:45:24,880
Speaker 1: the winter, like snow tracking and trapping some species is

791
00:45:24,920 --> 00:45:26,239
Speaker 1: easier in the winter. Do you still have to do

792
00:45:26,719 --> 00:45:29,320
Speaker 1: odd jobs to fill in? I haven't done odd jobs

793
00:45:29,320 --> 00:45:32,359
Speaker 1: in a while, remember that being when I was when

794
00:45:32,360 --> 00:45:36,520
Speaker 1: I was coming up as a writer. Um, that'd be

795
00:45:36,600 --> 00:45:39,520
Speaker 1: a big moment. Well, I just could do what I

796
00:45:39,560 --> 00:45:42,680
Speaker 1: wanted to do, because I would do like trim trees

797
00:45:42,760 --> 00:45:45,680
Speaker 1: for you know, did arborst work when I finally got

798
00:45:45,760 --> 00:45:47,160
Speaker 1: or I didn't need to do arborist work. Now that

799
00:45:47,200 --> 00:45:50,239
Speaker 1: didn't like doing arborst work. But it was like a mile,

800
00:45:50,280 --> 00:45:52,480
Speaker 1: it was a milestone. It was a milestone, you know

801
00:45:52,480 --> 00:45:56,879
Speaker 1: what I mean, Just like now, it was like a leap, right,

802
00:45:56,960 --> 00:45:58,799
Speaker 1: It was like, now I'm just gonna do I'm just

803
00:45:58,800 --> 00:46:01,520
Speaker 1: gonna do this thing not have to worry about the

804
00:46:01,560 --> 00:46:05,400
Speaker 1: other thing. It feels good, but it's still gonna be

805
00:46:05,440 --> 00:46:06,719
Speaker 1: like it's gonna be hard to make a living, right

806
00:46:06,719 --> 00:46:09,160
Speaker 1: when you're jumping from job job job, and they're not

807
00:46:09,200 --> 00:46:13,120
Speaker 1: paying you know, it's all like entry level. Yeah, yeah,

808
00:46:13,239 --> 00:46:15,040
Speaker 1: that's probably people get out of it as much fun

809
00:46:15,080 --> 00:46:18,919
Speaker 1: as you're having. Eventually you're like I just can't like yeah, yeah,

810
00:46:19,200 --> 00:46:23,000
Speaker 1: dread when I get bills and stuff. Well, and then

811
00:46:23,040 --> 00:46:25,560
Speaker 1: you have that conundrum of like what you're saying, like

812
00:46:25,680 --> 00:46:27,160
Speaker 1: you make the money and all of a sudden you're

813
00:46:27,160 --> 00:46:30,480
Speaker 1: not in the field anymore. Yeah. But yeah, I think

814
00:46:30,520 --> 00:46:33,960
Speaker 1: that that you have people when you're younger, you have

815
00:46:34,000 --> 00:46:40,879
Speaker 1: a tolerance for uncertainty fades if I'm any, If I'm

816
00:46:40,920 --> 00:46:43,560
Speaker 1: any example, like I used to be very comfortable with uncertainty.

817
00:46:43,560 --> 00:46:45,400
Speaker 1: It didn't bollow me at all. It bought me a

818
00:46:45,440 --> 00:46:47,440
Speaker 1: little bit. By me like I kind of like half

819
00:46:47,520 --> 00:46:50,560
Speaker 1: lived in my one brother's basement, half lived in my

820
00:46:50,600 --> 00:46:54,799
Speaker 1: other brother's spare bedroom. Yeah, right, and it is it

821
00:46:54,840 --> 00:46:57,200
Speaker 1: was just like okay, this is how it is. Yeah,

822
00:46:57,320 --> 00:47:01,359
Speaker 1: and I um, I didn't have a whole lot. I mean,

823
00:47:01,360 --> 00:47:02,880
Speaker 1: it's not like I had a bunch of bills. I

824
00:47:02,960 --> 00:47:05,359
Speaker 1: just it felt good to know that I could fit

825
00:47:05,400 --> 00:47:10,399
Speaker 1: everything in my car and go and work wherever. Yeah,

826
00:47:10,440 --> 00:47:12,080
Speaker 1: I went for years and nothing but a cell phone.

827
00:47:12,080 --> 00:47:14,440
Speaker 1: Billy was the only thing my name was. Yeah, I

828
00:47:14,480 --> 00:47:19,080
Speaker 1: didn't even have that for a long time. Um, And

829
00:47:19,120 --> 00:47:21,719
Speaker 1: then I also, yeah I did. I mean I'd do

830
00:47:21,800 --> 00:47:23,719
Speaker 1: some odd jobs if I couldn't find a winner job

831
00:47:23,800 --> 00:47:26,520
Speaker 1: or whatever. I did baking a lot baking. Yeah, I

832
00:47:26,520 --> 00:47:29,040
Speaker 1: had a bakery. I could always go back to come

833
00:47:29,080 --> 00:47:32,959
Speaker 1: crawling back. Yeah, make some cinimon wrong. You know really

834
00:47:32,960 --> 00:47:35,160
Speaker 1: in the annal it makes you just such a whole person,

835
00:47:35,480 --> 00:47:37,000
Speaker 1: you know what I mean. Think about if you hadn't

836
00:47:37,040 --> 00:47:39,880
Speaker 1: done all these odd jobs, you know how different of

837
00:47:39,880 --> 00:47:41,880
Speaker 1: a person you'd be now. But like these skills in

838
00:47:42,000 --> 00:47:47,719
Speaker 1: baking and like, I'm sure you're a very clean organized house. Like, oh,

839
00:47:47,760 --> 00:47:49,960
Speaker 1: it's totally and their thing about it. And I get

840
00:47:49,960 --> 00:47:53,239
Speaker 1: into this all the time with people who, yeah, I

841
00:47:53,239 --> 00:47:55,520
Speaker 1: guess like now that I'm my age or whatever, I've

842
00:47:55,560 --> 00:47:57,759
Speaker 1: come to the weird point in life where I find

843
00:47:57,760 --> 00:48:01,400
Speaker 1: myself getting out depensing. Yeah, like I like give advice

844
00:48:01,440 --> 00:48:02,640
Speaker 1: now you know what I mean. And I have like

845
00:48:02,680 --> 00:48:05,600
Speaker 1: four pieces of advice I give the people, and one

846
00:48:05,640 --> 00:48:09,400
Speaker 1: of them is like, develop your humility, man, do you

847
00:48:09,400 --> 00:48:11,719
Speaker 1: know what I mean? Yeah, because a lot of people

848
00:48:11,719 --> 00:48:14,200
Speaker 1: don't have it, and I feel like, yeah, I could

849
00:48:14,200 --> 00:48:16,319
Speaker 1: say it really old man type thing. Now start talking

850
00:48:16,320 --> 00:48:20,480
Speaker 1: about kids these days, but I'll spare you that. But

851
00:48:20,560 --> 00:48:24,359
Speaker 1: I find the people I admire and the people who

852
00:48:24,680 --> 00:48:27,359
Speaker 1: do something new and find success in something new. We're

853
00:48:27,360 --> 00:48:30,440
Speaker 1: not where they have like family lineage propelling them along,

854
00:48:31,000 --> 00:48:35,319
Speaker 1: you know, but like you're like you know our you know,

855
00:48:35,360 --> 00:48:39,120
Speaker 1: like my like my parents didn't go to college, you know. Um,

856
00:48:39,200 --> 00:48:42,040
Speaker 1: so when we went into professional lives, we're sort of

857
00:48:42,080 --> 00:48:45,000
Speaker 1: going in a new direction. I think. To go and

858
00:48:45,040 --> 00:48:49,279
Speaker 1: do that, you gotta have. You gotta like be able

859
00:48:49,320 --> 00:48:53,719
Speaker 1: to to just like do sucky jobs well, because that's

860
00:48:53,719 --> 00:48:55,759
Speaker 1: the quickest way out. The quickest way out of a

861
00:48:55,800 --> 00:48:58,440
Speaker 1: sucky job is to kick ass at it. If you

862
00:48:58,440 --> 00:49:00,640
Speaker 1: don't kick ass at it, you'll always have sucky jobs.

863
00:49:01,520 --> 00:49:03,359
Speaker 1: Because people were like be like that dude, couldn't even

864
00:49:03,400 --> 00:49:05,719
Speaker 1: do the sucky job. You know. I'm not going to

865
00:49:05,760 --> 00:49:12,759
Speaker 1: give them the important one. But like humility, Yeah, I

866
00:49:12,840 --> 00:49:16,520
Speaker 1: have scrubbed a lot of toilets and that that's a

867
00:49:16,560 --> 00:49:18,440
Speaker 1: quick wait to humility. Yeah. I remember when I was

868
00:49:18,440 --> 00:49:21,160
Speaker 1: in graduate school, I had a job cleaning the bathrooms

869
00:49:21,200 --> 00:49:24,600
Speaker 1: in the l A Building, the Liberal Arts Building, and

870
00:49:24,640 --> 00:49:27,799
Speaker 1: like I was in a very prestigious graduate program, it

871
00:49:27,840 --> 00:49:30,759
Speaker 1: was very difficult to get in. And I would and

872
00:49:30,880 --> 00:49:33,759
Speaker 1: like my classmates would be coming out of writing workshops

873
00:49:33,800 --> 00:49:35,880
Speaker 1: and going to take a leak while I'm in there

874
00:49:35,880 --> 00:49:39,840
Speaker 1: scrubbing the toilets, right, And that ship hurts, man, it hurts,

875
00:49:40,040 --> 00:49:42,680
Speaker 1: but it's like it does something to your head and

876
00:49:42,680 --> 00:49:45,800
Speaker 1: it makes you like different, you know, it gives you something.

877
00:49:47,000 --> 00:49:48,920
Speaker 1: Uh well, it gives you just on top about like

878
00:49:48,960 --> 00:49:53,200
Speaker 1: a level of humility. Yeah, the you know, the familiar

879
00:49:53,280 --> 00:49:57,840
Speaker 1: sting man, you know, gives you a girl and grit.

880
00:49:58,880 --> 00:50:00,759
Speaker 1: I remember sitting there with you on us one day

881
00:50:00,760 --> 00:50:07,080
Speaker 1: in Bozeman and were scrubbing toilets. We're actually pulling off

882
00:50:07,080 --> 00:50:10,600
Speaker 1: a coffee shop and we see a guy like a

883
00:50:10,680 --> 00:50:13,640
Speaker 1: drift boat go buy on a trailer, like very obviously,

884
00:50:13,719 --> 00:50:15,880
Speaker 1: you know, like a young guy driving a boat on

885
00:50:16,000 --> 00:50:19,080
Speaker 1: a morning and like clearly that dude is a guide.

886
00:50:20,160 --> 00:50:22,760
Speaker 1: And Yana said, oh, you know that brings back memories,

887
00:50:22,800 --> 00:50:25,279
Speaker 1: and I thought he was gonna get on nostalgic. It

888
00:50:25,360 --> 00:50:28,879
Speaker 1: was like floating at same fucking stretch of river every day.

889
00:50:31,160 --> 00:50:35,080
Speaker 1: Bo I later found out after we talked with that

890
00:50:35,239 --> 00:50:38,080
Speaker 1: photographer that was with us on that trip, he got it,

891
00:50:38,320 --> 00:50:40,279
Speaker 1: you know, and he said something like, within an hour's drive,

892
00:50:40,280 --> 00:50:43,360
Speaker 1: they have like two hundred miles of floatable river where

893
00:50:43,400 --> 00:50:47,520
Speaker 1: we had I don't know, maybe a quarter of that.

894
00:50:47,680 --> 00:50:53,000
Speaker 1: You know, maybe he didn't have the same beat up

895
00:50:53,000 --> 00:50:57,759
Speaker 1: feelings that I did about it, but yeah, alright, So

896
00:50:57,840 --> 00:51:02,319
Speaker 1: after bears, so after that job, and that was volunteering,

897
00:51:02,840 --> 00:51:05,200
Speaker 1: Oh yeah, that's I mean, you gotta have balls to

898
00:51:05,200 --> 00:51:07,239
Speaker 1: put up a job listing that you're not gonna pay.

899
00:51:07,480 --> 00:51:12,240
Speaker 1: That's a lot of wildlife tech work, especially fun carnivore

900
00:51:12,320 --> 00:51:14,399
Speaker 1: jobs that are super competitive. They're like, people are gonna

901
00:51:14,440 --> 00:51:15,960
Speaker 1: want to do this, People are gonna want to do this.

902
00:51:16,040 --> 00:51:17,600
Speaker 1: People need to get their toe in the door. They

903
00:51:17,640 --> 00:51:21,920
Speaker 1: need to get experience. And our project has no money.

904
00:51:22,040 --> 00:51:26,000
Speaker 1: Let's get volunteers. You probably get w p A volunteers.

905
00:51:27,680 --> 00:51:31,600
Speaker 1: But it's like then he can't even yell at. I'm

906
00:51:31,600 --> 00:51:34,640
Speaker 1: sure you got yelled at as a volunteer, right, you

907
00:51:34,680 --> 00:51:39,640
Speaker 1: know what. Everybody was so appreciative they were Yeah. I

908
00:51:39,680 --> 00:51:44,480
Speaker 1: mean so my next job was right after I graduated,

909
00:51:44,600 --> 00:51:47,800
Speaker 1: and I spent the summer in Alberta in the mountains

910
00:51:47,840 --> 00:51:51,360
Speaker 1: there on a cougar kill site analysis. There you go,

911
00:51:51,600 --> 00:51:55,520
Speaker 1: that's good stuff. Was that paid? Uh? It was very little.

912
00:51:55,760 --> 00:51:57,480
Speaker 1: It was stipe. That's the other thing is a lot

913
00:51:57,480 --> 00:51:59,520
Speaker 1: of these places you get you get a stipend, so

914
00:51:59,600 --> 00:52:02,320
Speaker 1: your basic glee. You're not spending money because you're in

915
00:52:02,360 --> 00:52:07,120
Speaker 1: the middle of nowhere. They give you housing and stipend

916
00:52:08,360 --> 00:52:12,399
Speaker 1: and you're camping out. No, well we had like four

917
00:52:12,440 --> 00:52:15,600
Speaker 1: service housing. Yeah, so bunk house they were. It was

918
00:52:15,680 --> 00:52:21,320
Speaker 1: killside analysis. So this project he um, he was looking

919
00:52:21,440 --> 00:52:24,600
Speaker 1: at pray composition. So what the cougars they were eating

920
00:52:25,120 --> 00:52:28,160
Speaker 1: and kill? Right, so how often they were killing? Um?

921
00:52:28,239 --> 00:52:31,200
Speaker 1: So you got collars on collars on the cougars and

922
00:52:31,280 --> 00:52:34,920
Speaker 1: these were GPS collars, So these collars would take a

923
00:52:34,960 --> 00:52:39,080
Speaker 1: location and store it in the collar. Did he already

924
00:52:39,120 --> 00:52:40,960
Speaker 1: have the collars when you joined up? That was a

925
00:52:41,040 --> 00:52:43,879
Speaker 1: wintertime thing. They use hounds in the winter to call

926
00:52:43,920 --> 00:52:46,279
Speaker 1: it them. Yeah, so run the cougar down on the

927
00:52:46,320 --> 00:52:49,920
Speaker 1: hound darted out of the tree, that's something I wanted

928
00:52:50,480 --> 00:52:52,839
Speaker 1: when you dart. My boy asked this question last night

929
00:52:53,400 --> 00:52:55,279
Speaker 1: after he was talking to you. When you dart the

930
00:52:55,320 --> 00:52:57,200
Speaker 1: cougar up in the tree, how do you keep it

931
00:52:57,200 --> 00:53:01,919
Speaker 1: from getting injured on the fall? I this is how

932
00:53:01,960 --> 00:53:04,120
Speaker 1: he did it and describe it to me, is that

933
00:53:04,200 --> 00:53:07,440
Speaker 1: he would go up there before it was so out

934
00:53:07,520 --> 00:53:10,960
Speaker 1: that it just fell and help help it down. Yeah,

935
00:53:11,320 --> 00:53:13,560
Speaker 1: because it seems like they'd be in some positions where

936
00:53:13,560 --> 00:53:16,320
Speaker 1: you couldn't dart. Him. Boy, that's got to be intimate

937
00:53:16,360 --> 00:53:19,960
Speaker 1: with a big cat, just not quite out and yeah,

938
00:53:20,040 --> 00:53:22,879
Speaker 1: let me help you out of the street. Yeah. Yeah,

939
00:53:22,920 --> 00:53:24,440
Speaker 1: you're kind of stuck. You don't have a lot of

940
00:53:24,800 --> 00:53:27,240
Speaker 1: room to maneuver. Yeah. I'll tell you a horrible story.

941
00:53:27,840 --> 00:53:30,399
Speaker 1: I was working on a magazine article in Nevada one

942
00:53:30,400 --> 00:53:32,720
Speaker 1: time and I got to hanging out with this dude

943
00:53:33,239 --> 00:53:38,160
Speaker 1: who um had been a mule deer and lion guide.

944
00:53:38,239 --> 00:53:42,759
Speaker 1: So he's a he's an outfitter. He had long long

945
00:53:42,800 --> 00:53:46,640
Speaker 1: sinceince he got out of the business. He we could

946
00:53:46,640 --> 00:53:48,680
Speaker 1: looking through photo album and he's got pictures of him

947
00:53:48,719 --> 00:53:52,480
Speaker 1: up in a tree with lions with a jabstick. Okay,

948
00:53:52,520 --> 00:53:55,480
Speaker 1: so the same setup your top boat. He explains me

949
00:53:55,520 --> 00:53:58,520
Speaker 1: that when he was a lion guy, he would find

950
00:53:58,680 --> 00:54:01,880
Speaker 1: the clients only has so much appetite for running lions,

951
00:54:01,920 --> 00:54:09,040
Speaker 1: because it's hard work. He would keep a couple. He

952
00:54:09,080 --> 00:54:13,279
Speaker 1: would go out in the off season trank lions. This

953
00:54:13,640 --> 00:54:15,319
Speaker 1: you're gonna think I'm bullshitting. He took me and showed

954
00:54:15,320 --> 00:54:19,040
Speaker 1: me the cages on his property. He would trank lions.

955
00:54:19,239 --> 00:54:22,800
Speaker 1: Is highly illegal. He would trank lions keeping in cages,

956
00:54:23,000 --> 00:54:25,279
Speaker 1: feed him dear meat. When he had a client that

957
00:54:25,320 --> 00:54:28,080
Speaker 1: couldn't hack it, he'd let one of those out and

958
00:54:28,120 --> 00:54:32,960
Speaker 1: then he run that one. Yeah, you talk about dirty pool. No,

959
00:54:33,040 --> 00:54:35,440
Speaker 1: it's awful. You want to punch the guy in the nose, right,

960
00:54:35,480 --> 00:54:37,160
Speaker 1: But I mean he's talking about like something from way

961
00:54:37,200 --> 00:54:43,520
Speaker 1: back in his mind. You know, clients never knew, I

962
00:54:43,560 --> 00:54:46,560
Speaker 1: mean he should. The weird thing is, yeah, he's got

963
00:54:46,560 --> 00:54:49,600
Speaker 1: a photo albums, like big blown up photos. Just he

964
00:54:49,719 --> 00:54:52,520
Speaker 1: was like he wasn't, you know, hiding and he was

965
00:54:53,040 --> 00:54:55,600
Speaker 1: hiding it from them. But he's like, oh, yeah, here's me,

966
00:54:55,640 --> 00:54:59,040
Speaker 1: and that's where I used to put him. I'm not shipping.

967
00:55:00,360 --> 00:55:02,920
Speaker 1: Just he was an old fellow. I'd be surprised he's

968
00:55:02,920 --> 00:55:05,520
Speaker 1: still alive right now. But you know he's talking about whatever.

969
00:55:05,520 --> 00:55:07,200
Speaker 1: I know if this is something he's doing the fifties

970
00:55:07,280 --> 00:55:11,919
Speaker 1: or sixties. Yeah, but you know, if there's a moral

971
00:55:11,960 --> 00:55:17,320
Speaker 1: to that story, it'sford do your research on your guide. Yeah,

972
00:55:17,560 --> 00:55:21,040
Speaker 1: I mean you'd hope that that stuff is harder to

973
00:55:21,080 --> 00:55:27,680
Speaker 1: get away with. This fellow has some collars on some lives. Yeah, so,

974
00:55:28,120 --> 00:55:33,000
Speaker 1: um so we would. So these GPS collars, they are

975
00:55:33,000 --> 00:55:36,319
Speaker 1: taking locations. Um. I think his were set to every

976
00:55:36,320 --> 00:55:40,399
Speaker 1: two hours. She's getting pretty detailed location data from these

977
00:55:40,440 --> 00:55:44,440
Speaker 1: animals stored on the collar. The collar also has a

978
00:55:44,560 --> 00:55:48,000
Speaker 1: traditional radio transmitter, so it's making the beep if you've

979
00:55:48,000 --> 00:55:51,120
Speaker 1: got your little antenna in case the GPS fails or something. Um,

980
00:55:51,120 --> 00:55:54,080
Speaker 1: just so you can locate them because collars, Yeah, you

981
00:55:54,160 --> 00:55:58,360
Speaker 1: have to find the cat again, get close enough that

982
00:55:58,440 --> 00:56:02,319
Speaker 1: with a special antenna. Uh, you can suck the data

983
00:56:02,360 --> 00:56:08,680
Speaker 1: off the cat's collar. Depending on the topography and everything.

984
00:56:08,800 --> 00:56:13,440
Speaker 1: I don't know, eighty meters maybe close, sometimes further if

985
00:56:13,480 --> 00:56:16,560
Speaker 1: it was a good strong collar. So you gotta find

986
00:56:16,560 --> 00:56:19,640
Speaker 1: the lion all bedded up somewhere. Yeah, hopefully they're not

987
00:56:19,680 --> 00:56:23,080
Speaker 1: moving or you're running to catch up with them. You

988
00:56:23,200 --> 00:56:27,000
Speaker 1: track in on the line yeah, never saw one doing that.

989
00:56:27,040 --> 00:56:28,960
Speaker 1: I heard one, but I never saw one doing that,

990
00:56:30,200 --> 00:56:32,560
Speaker 1: just because it's thick and they're good at hiding and

991
00:56:33,360 --> 00:56:36,160
Speaker 1: the rocks usually you're down the forest. Yeah, it was

992
00:56:36,400 --> 00:56:38,640
Speaker 1: a lot of well, there were some. There was We

993
00:56:38,680 --> 00:56:42,480
Speaker 1: had one, uh, mountain cat. She was way up high.

994
00:56:43,600 --> 00:56:46,120
Speaker 1: She was lying in the mountain. Yeah, lying in the mountains.

995
00:56:46,120 --> 00:56:50,680
Speaker 1: So she lived. Her territory was um way up in

996
00:56:50,880 --> 00:56:53,520
Speaker 1: the Rockies and she was you know, eating mountain goats

997
00:56:53,560 --> 00:56:59,640
Speaker 1: and big horn sheep and stuff. Um, so she was Yeah,

998
00:56:59,680 --> 00:57:02,480
Speaker 1: so she wasn't a lot of open you know, cliffy country.

999
00:57:02,520 --> 00:57:05,040
Speaker 1: But then we had cats that were just down in

1000
00:57:05,080 --> 00:57:08,360
Speaker 1: the in the more boreal forest. So it was really thick.

1001
00:57:08,480 --> 00:57:11,600
Speaker 1: And then there was one kind of town cat that

1002
00:57:11,680 --> 00:57:15,640
Speaker 1: lived sort of near to um Rocky Mountain house, the

1003
00:57:15,719 --> 00:57:19,960
Speaker 1: town that was nearby. And so that cat was you

1004
00:57:20,000 --> 00:57:25,080
Speaker 1: know in farmland. But also timbers at or where would

1005
00:57:25,080 --> 00:57:29,400
Speaker 1: you find it. Just some timber stands all over. I

1006
00:57:29,400 --> 00:57:32,600
Speaker 1: mean they're timber stands, yeah, I mean they I don't

1007
00:57:32,840 --> 00:57:35,120
Speaker 1: I don't know that they'd be betting down in a

1008
00:57:35,160 --> 00:57:37,160
Speaker 1: grassy area. I don't know. We weren't, I mean we weren't.

1009
00:57:37,840 --> 00:57:39,960
Speaker 1: We were going to kill sites. So we just it

1010
00:57:40,000 --> 00:57:41,760
Speaker 1: would be every you would be able to find the

1011
00:57:41,840 --> 00:57:44,520
Speaker 1: kill site without downloading where it had been. Right, but

1012
00:57:44,560 --> 00:57:47,640
Speaker 1: you do that every month or two sort of opportunistically

1013
00:57:47,680 --> 00:57:50,280
Speaker 1: as you heard them, you know, oh I got you. Yeah,

1014
00:57:50,280 --> 00:57:51,960
Speaker 1: so you get a whole pile of data all at

1015
00:57:52,040 --> 00:57:54,800
Speaker 1: once and then so so you'd go find it, download

1016
00:57:54,800 --> 00:57:56,240
Speaker 1: the stuff and you didn't have to do that regularly

1017
00:57:56,480 --> 00:57:59,240
Speaker 1: once and then you'd have all those GPS way points

1018
00:57:59,600 --> 00:58:01,600
Speaker 1: and you analyze those to make sense of where it

1019
00:58:01,640 --> 00:58:03,440
Speaker 1: might have killed something. Yeah. So he how would you

1020
00:58:03,480 --> 00:58:05,360
Speaker 1: know by looking at the way points just it lingered

1021
00:58:05,360 --> 00:58:08,240
Speaker 1: in an area? Yeah, So he had developed an algorithm

1022
00:58:08,240 --> 00:58:13,080
Speaker 1: that would go through the points and um pull out

1023
00:58:13,240 --> 00:58:18,520
Speaker 1: places where the cat had spent enough hours within a

1024
00:58:18,600 --> 00:58:22,560
Speaker 1: small enough radius. So it was like a two intermter.

1025
00:58:22,760 --> 00:58:26,720
Speaker 1: The cat had stayed within a UM you know, two

1026
00:58:26,800 --> 00:58:30,040
Speaker 1: day period, had been had main locations within a two

1027
00:58:30,920 --> 00:58:34,280
Speaker 1: radius or something um for enough hours so they could

1028
00:58:34,320 --> 00:58:36,240
Speaker 1: they could leave. But if they came back, you know,

1029
00:58:36,280 --> 00:58:38,880
Speaker 1: more than two or three times, it would make what

1030
00:58:39,480 --> 00:58:42,240
Speaker 1: they call it cluster well cluster points. So it's basically

1031
00:58:42,280 --> 00:58:46,320
Speaker 1: saying this cat hung out here consistently for you know,

1032
00:58:46,360 --> 00:58:49,880
Speaker 1: more than just a couple of hours. So then our

1033
00:58:49,960 --> 00:58:54,480
Speaker 1: job was to, um, go out to those spots get

1034
00:58:54,520 --> 00:58:57,480
Speaker 1: there however we could. We did a lot of uh formilling,

1035
00:58:58,040 --> 00:59:00,680
Speaker 1: a lot of backpacking in especially for the mound cat,

1036
00:59:01,400 --> 00:59:04,760
Speaker 1: and then you just plug it into your GPS and

1037
00:59:04,840 --> 00:59:07,720
Speaker 1: navigate out there. And then you'd get to the area

1038
00:59:07,720 --> 00:59:10,360
Speaker 1: where the cat had been hanging out and you just

1039
00:59:10,400 --> 00:59:13,360
Speaker 1: start searching and searching and searching to see if there

1040
00:59:13,400 --> 00:59:15,640
Speaker 1: was a kill there. Oftentimes it was just a betting

1041
00:59:15,640 --> 00:59:17,400
Speaker 1: site and you could you know, find a little bed

1042
00:59:17,480 --> 00:59:20,960
Speaker 1: under a tree or whatever, but um, a lot of

1043
00:59:20,960 --> 00:59:23,680
Speaker 1: times it was killed, and so then you'd This is

1044
00:59:23,680 --> 00:59:27,160
Speaker 1: where I started getting really into tracking. I've been interested

1045
00:59:27,200 --> 00:59:29,880
Speaker 1: in tracking before this, and you know, learned a lot

1046
00:59:29,880 --> 00:59:33,320
Speaker 1: in school and just on my own, but um, it's

1047
00:59:33,440 --> 00:59:36,480
Speaker 1: really cool to go to a spot where our predator

1048
00:59:36,520 --> 00:59:39,120
Speaker 1: has been recently and left a lot of sign and

1049
00:59:39,640 --> 00:59:41,560
Speaker 1: you're trying to figure out, you know, sometimes from just

1050
00:59:41,640 --> 00:59:44,040
Speaker 1: tiny bone fragments and hair what it was they ate

1051
00:59:44,720 --> 00:59:47,880
Speaker 1: who else was there, scavenging what went on there, So

1052
00:59:48,160 --> 00:59:51,920
Speaker 1: that that method you would miss all the small stuff

1053
00:59:51,960 --> 00:59:56,080
Speaker 1: the cat killed, right yep. Yeah, So so you're not

1054
00:59:56,120 --> 00:59:59,520
Speaker 1: gonna find like fox turtles. I mean all the garbage

1055
00:59:59,520 --> 01:00:01,200
Speaker 1: they pick up. You're only gonna find a stuff where

1056
01:00:01,200 --> 01:00:04,040
Speaker 1: he had us like a substantial amount of meat underground, right,

1057
01:00:04,160 --> 01:00:07,200
Speaker 1: cats with cats, I feel like we were finding some

1058
01:00:07,360 --> 01:00:10,760
Speaker 1: We were finding some smaller stuff. They'd often when they

1059
01:00:10,800 --> 01:00:14,880
Speaker 1: have a kill, they eat and they stay there. Um,

1060
01:00:14,880 --> 01:00:17,960
Speaker 1: whereas with say wolves, they tend to eat for a

1061
01:00:18,000 --> 01:00:20,760
Speaker 1: little bit and then go bed down or just go

1062
01:00:20,840 --> 01:00:23,160
Speaker 1: on their way if they've eaten it all. So I

1063
01:00:23,200 --> 01:00:26,200
Speaker 1: don't know, it felt it would hang out. Yeah for

1064
01:00:26,280 --> 01:00:28,720
Speaker 1: some I mean mice and little stuff. You're right, you're

1065
01:00:28,760 --> 01:00:31,040
Speaker 1: not catching that stuff, but you're getting the bigger prey.

1066
01:00:31,520 --> 01:00:33,000
Speaker 1: Would you ever go in and find like a bunch

1067
01:00:33,000 --> 01:00:37,000
Speaker 1: of blue grouse feathers? I can think of that happening

1068
01:00:37,040 --> 01:00:38,680
Speaker 1: one time and that was all we found. But that

1069
01:00:39,080 --> 01:00:42,760
Speaker 1: you find blue grouse feathers all the time, you know, Right,

1070
01:00:44,160 --> 01:00:47,160
Speaker 1: So what was the main what were the main things

1071
01:00:47,200 --> 01:00:51,760
Speaker 1: you were You were locating elk dear what elk deer

1072
01:00:52,080 --> 01:00:58,400
Speaker 1: during the during the spring, with a lot of you know, calves, moose, calves, calves, caves. Yeah,

1073
01:00:58,520 --> 01:01:04,600
Speaker 1: so we'd find moose, porcupines, beavers. They love to beavers.

1074
01:01:04,680 --> 01:01:07,320
Speaker 1: They would linger on a beaver carcass. Yeah, we found

1075
01:01:07,320 --> 01:01:08,920
Speaker 1: a lot of beavers, I guess. Yeah, because if you

1076
01:01:09,000 --> 01:01:12,080
Speaker 1: got a cat's hunter pounds and he kills a forty

1077
01:01:12,080 --> 01:01:16,360
Speaker 1: pound beaver, yeah, I mean he's gonna hang out. It's

1078
01:01:16,400 --> 01:01:17,800
Speaker 1: like he's gonna drag it off. I mean, I could

1079
01:01:17,840 --> 01:01:21,400
Speaker 1: drag it too far. Yeah, uh, and then it would

1080
01:01:21,400 --> 01:01:23,600
Speaker 1: be hitting when when they're hitting the beavers, you managed

1081
01:01:23,640 --> 01:01:25,280
Speaker 1: to probably catch them when they're up out of the

1082
01:01:25,280 --> 01:01:29,400
Speaker 1: water working on cutting willows and stuff. Probably. I also

1083
01:01:29,520 --> 01:01:32,640
Speaker 1: imagined because there's I remember in a lot of spots,

1084
01:01:32,640 --> 01:01:35,160
Speaker 1: it would be like a wet meadow with just a

1085
01:01:35,200 --> 01:01:38,280
Speaker 1: deep trench that the beavers have made. But it's it's

1086
01:01:38,360 --> 01:01:41,280
Speaker 1: you know, not the channels, Yeah, plugging them out of there.

1087
01:01:41,400 --> 01:01:43,240
Speaker 1: I mean, I don't know, I never saw that happen

1088
01:01:43,320 --> 01:01:45,120
Speaker 1: or anything, but it's easy to imagine a cat just

1089
01:01:45,160 --> 01:01:47,960
Speaker 1: waiting for one to swim behind. Yeah. You know, you know,

1090
01:01:48,000 --> 01:01:50,960
Speaker 1: I've I've hand grabbed. You can hand grab beavers on

1091
01:01:51,040 --> 01:01:54,560
Speaker 1: dry land. Yeah, you get between them and the water.

1092
01:01:54,640 --> 01:01:56,880
Speaker 1: There's nothing yeah they can do. Yeah. Yeah, you know,

1093
01:01:56,960 --> 01:01:58,840
Speaker 1: we just we've just hurt back when we were of

1094
01:01:58,920 --> 01:02:01,000
Speaker 1: the age that you would her ass animals that you

1095
01:02:01,000 --> 01:02:03,160
Speaker 1: found out in the woods. We would her ask beaver

1096
01:02:03,240 --> 01:02:04,800
Speaker 1: as if we caught them on dry land now and

1097
01:02:04,800 --> 01:02:07,760
Speaker 1: then yeah, yeah, so, yeah, they ate a lot of beavers.

1098
01:02:07,800 --> 01:02:11,200
Speaker 1: There was one that ate porcupines a lot. And then

1099
01:02:12,800 --> 01:02:15,120
Speaker 1: what would you find on the you find? Would would

1100
01:02:15,120 --> 01:02:17,560
Speaker 1: that skin be pretty intact on the porcupine where they

1101
01:02:17,600 --> 01:02:19,360
Speaker 1: kind of pull that porcupine right out of the skin,

1102
01:02:19,440 --> 01:02:21,439
Speaker 1: where they shred that skin and all you'll find maybe

1103
01:02:21,720 --> 01:02:23,240
Speaker 1: a piece of it, but there'd be you know, a

1104
01:02:23,320 --> 01:02:25,840
Speaker 1: pile of quails. Maybe yeah, a piece of the back

1105
01:02:25,920 --> 01:02:27,600
Speaker 1: with clothes on it. Or did you ever get the

1106
01:02:27,600 --> 01:02:29,560
Speaker 1: sense they ate it and then passed the quills or

1107
01:02:29,760 --> 01:02:31,680
Speaker 1: they get the meat out. No, I never had the

1108
01:02:31,720 --> 01:02:34,040
Speaker 1: sense they ate the quills. Yeah, like you go to

1109
01:02:34,080 --> 01:02:37,240
Speaker 1: a griz where a grizzly bear has something, they'll run

1110
01:02:37,280 --> 01:02:41,560
Speaker 1: the whole damn thing through their system, where all the bone,

1111
01:02:41,760 --> 01:02:44,600
Speaker 1: all the hair. Sometimes you'll find all the bone, all

1112
01:02:44,640 --> 01:02:47,800
Speaker 1: the hair and dropping form. Have you found porcupine cliothes? Though?

1113
01:02:48,000 --> 01:02:54,000
Speaker 1: Never Yeah, that might not be good. Yeah, I managed

1114
01:02:54,000 --> 01:02:57,000
Speaker 1: be awful. We found my body. We were hunting in

1115
01:02:57,000 --> 01:03:01,480
Speaker 1: southeast Montana and he shot a mule deer and uh,

1116
01:03:01,800 --> 01:03:03,800
Speaker 1: it was just nasty because she must have the only thing.

1117
01:03:03,840 --> 01:03:07,160
Speaker 1: I think she ran over a porcupine an accident. How

1118
01:03:07,160 --> 01:03:10,120
Speaker 1: does the deer get her entire bottom coded and drills?

1119
01:03:10,160 --> 01:03:11,840
Speaker 1: I feel like she's going along and happened to get

1120
01:03:11,880 --> 01:03:15,480
Speaker 1: over one man. She was full of infections. Also, it

1121
01:03:15,560 --> 01:03:18,760
Speaker 1: was disgusting. Yeah, like messed up, like to the point

1122
01:03:18,760 --> 01:03:21,800
Speaker 1: where it could have like long term fatal Yeah, probably

1123
01:03:21,920 --> 01:03:24,520
Speaker 1: you know from all that just full of quills on

1124
01:03:24,560 --> 01:03:28,600
Speaker 1: her belly and around her memories. Yeah real, all it's green.

1125
01:03:29,080 --> 01:03:30,960
Speaker 1: We cleaned it up, and we cleaned up and got

1126
01:03:30,960 --> 01:03:32,800
Speaker 1: most of meat off it. But I remember thinking it

1127
01:03:32,920 --> 01:03:36,360
Speaker 1: was like a deer killed, like would have become a

1128
01:03:36,440 --> 01:03:41,400
Speaker 1: deer killed by a porcupine. Yeah. So the other fun

1129
01:03:41,440 --> 01:03:45,920
Speaker 1: thing about those kill sites is that on multiple occasions

1130
01:03:46,800 --> 01:03:50,200
Speaker 1: we would find where they had been eating their deer

1131
01:03:50,200 --> 01:03:53,480
Speaker 1: and moose or whatever, and another animal will come along

1132
01:03:53,520 --> 01:03:57,240
Speaker 1: to scavenge, and they just opportunistically swipe that animal and

1133
01:03:57,280 --> 01:04:02,200
Speaker 1: added to them. Really like what I've had a bobcat once,

1134
01:04:02,760 --> 01:04:06,440
Speaker 1: fisher um. I think somebody might have even found a

1135
01:04:06,520 --> 01:04:09,880
Speaker 1: lynx once that he had to kill and it was

1136
01:04:09,920 --> 01:04:13,000
Speaker 1: like sleeping or upen a tree or whatever around comes

1137
01:04:13,040 --> 01:04:14,640
Speaker 1: some other thing to get in there and kills it

1138
01:04:14,640 --> 01:04:17,840
Speaker 1: and then eats it. Yeah, they're opportunistic. We would find

1139
01:04:17,920 --> 01:04:22,760
Speaker 1: double kills two deer in one cash. Yeah. I got

1140
01:04:22,800 --> 01:04:27,280
Speaker 1: a buddy that was running lions, and they had a

1141
01:04:27,360 --> 01:04:29,960
Speaker 1: lion get up in a tree on a rock pile,

1142
01:04:30,920 --> 01:04:32,640
Speaker 1: and it was dark by the time they got there,

1143
01:04:32,720 --> 01:04:35,760
Speaker 1: and they couldn't get up on the rock pile, and

1144
01:04:35,800 --> 01:04:37,880
Speaker 1: there were and there was a dog up on that

1145
01:04:37,960 --> 01:04:42,600
Speaker 1: rock pile. They couldn't get back, so they left and

1146
01:04:42,640 --> 01:04:47,160
Speaker 1: came back at first light. No lion, but it eating dogs. Yeah.

1147
01:04:47,400 --> 01:04:49,160
Speaker 1: The lion came down out of the tree, eighth dog

1148
01:04:49,200 --> 01:04:52,360
Speaker 1: and took off. Yeah. Yeah. From what I've learned about

1149
01:04:52,520 --> 01:04:54,520
Speaker 1: hunting the pounds that you don't want to get your hounds,

1150
01:04:54,520 --> 01:04:57,760
Speaker 1: any of them isolated, because the pack, though, you know,

1151
01:04:57,880 --> 01:05:00,080
Speaker 1: run away from but they know they can take the

1152
01:05:00,160 --> 01:05:03,440
Speaker 1: single The single animal I had have been a satisfying

1153
01:05:03,480 --> 01:05:11,840
Speaker 1: meal a bit. Yeah, No, I got you load. Yeah yeah.

1154
01:05:12,400 --> 01:05:15,000
Speaker 1: Would they would you find the animals that the lions

1155
01:05:15,120 --> 01:05:19,400
Speaker 1: killed tucked up and and buried, like were they bury

1156
01:05:19,440 --> 01:05:21,280
Speaker 1: a beaver or they just eat the beaver, not car

1157
01:05:23,320 --> 01:05:26,840
Speaker 1: they cash a fawn. So sometimes what fighting funds is

1158
01:05:26,960 --> 01:05:29,120
Speaker 1: really hard because a lot of times it's just some

1159
01:05:29,200 --> 01:05:32,400
Speaker 1: tufts of hair and maybe one little hoof or one

1160
01:05:32,440 --> 01:05:35,160
Speaker 1: little bit they scratched the cover up. Yeah, they're real

1161
01:05:35,240 --> 01:05:38,200
Speaker 1: anal about that, so they'll scratch around it. And then

1162
01:05:38,240 --> 01:05:42,120
Speaker 1: with a deer or something especially there it was you know,

1163
01:05:42,520 --> 01:05:45,600
Speaker 1: real mossy if we were in the forested areas, and

1164
01:05:45,640 --> 01:05:49,040
Speaker 1: so they just haul moss from all around and make

1165
01:05:49,080 --> 01:05:52,360
Speaker 1: a huge pile. Oh yeah. Were they pretty fastidious about

1166
01:05:52,400 --> 01:05:56,280
Speaker 1: eating the whole thing or they often leave a lot

1167
01:05:56,320 --> 01:05:58,880
Speaker 1: of meat or what does a cat like like to

1168
01:05:58,920 --> 01:06:04,520
Speaker 1: eat his kill right down a bone? That's something I'm

1169
01:06:04,560 --> 01:06:10,600
Speaker 1: really interested just in general with with predators because I

1170
01:06:10,600 --> 01:06:13,560
Speaker 1: think there's a lot more scavenging than than we think

1171
01:06:13,600 --> 01:06:17,880
Speaker 1: about going on so for um like other stuff, eating

1172
01:06:17,880 --> 01:06:20,840
Speaker 1: those coming in and eating so after the fact, right

1173
01:06:20,880 --> 01:06:23,680
Speaker 1: And with cats, I think it probably happens less because

1174
01:06:23,720 --> 01:06:26,760
Speaker 1: they tend to stick close. Um, but I'm sure they

1175
01:06:26,880 --> 01:06:28,920
Speaker 1: you know, could get chased off of a kill. I

1176
01:06:29,320 --> 01:06:32,080
Speaker 1: definitely went to some that were just like there's a

1177
01:06:32,160 --> 01:06:36,040
Speaker 1: huge rotting maggot pile here for whatever reason, didn't get

1178
01:06:36,080 --> 01:06:41,320
Speaker 1: to finish it. But typically we were finding um, you know,

1179
01:06:41,360 --> 01:06:43,800
Speaker 1: the room and contents they don't like that. They take

1180
01:06:43,840 --> 01:06:47,240
Speaker 1: that out first drag they eat the stomach or the

1181
01:06:47,320 --> 01:06:49,080
Speaker 1: lion not like to eat the stomach. They don't like

1182
01:06:49,120 --> 01:06:51,200
Speaker 1: the room and contents. They'll eat organs and stuffy. But

1183
01:06:51,240 --> 01:06:53,200
Speaker 1: I mean because you always see it looks like someone

1184
01:06:54,000 --> 01:06:56,040
Speaker 1: dumped out a bag of grass clippings out of the

1185
01:06:56,120 --> 01:06:59,280
Speaker 1: lawn more because they eat the actual stomach, but leave

1186
01:06:59,320 --> 01:07:03,080
Speaker 1: that sack as the Yeah. I also sometimes you just

1187
01:07:03,120 --> 01:07:04,720
Speaker 1: find that because they've just kind of taken out the

1188
01:07:04,720 --> 01:07:10,400
Speaker 1: whole thing. Um, so they almost almost yeah yeah, m

1189
01:07:11,960 --> 01:07:16,720
Speaker 1: eat the soft yeah yeah, that's really nutritious stuff that

1190
01:07:16,760 --> 01:07:19,640
Speaker 1: tends to go first with kills. In fact, with wolves,

1191
01:07:19,720 --> 01:07:22,840
Speaker 1: you can tell you can kind of get a timeline

1192
01:07:22,880 --> 01:07:28,000
Speaker 1: from the scats um. So like the early scats from

1193
01:07:28,080 --> 01:07:29,960
Speaker 1: the first feedings on a kill will be these like

1194
01:07:30,160 --> 01:07:35,200
Speaker 1: black nasty I call them organ scats because they've been

1195
01:07:35,200 --> 01:07:37,160
Speaker 1: eating just the organs and pure met And then as

1196
01:07:37,200 --> 01:07:41,560
Speaker 1: they eat those things up and they start eating cracking

1197
01:07:41,560 --> 01:07:43,480
Speaker 1: more bones and eating hair, more of the hair and

1198
01:07:43,560 --> 01:07:46,520
Speaker 1: hide and stuff, you get those more and you can

1199
01:07:46,560 --> 01:07:48,880
Speaker 1: also learn a little bit about who maybe left that

1200
01:07:48,960 --> 01:07:54,560
Speaker 1: scat because the breeding male and female get first pick

1201
01:07:54,640 --> 01:08:01,200
Speaker 1: generally until they're eating the organs' oh wolve that So

1202
01:08:01,280 --> 01:08:05,400
Speaker 1: I'm jumping around side my buddy, uh Rammy just was

1203
01:08:05,440 --> 01:08:07,800
Speaker 1: showing me some photographs. He was out hunting elk and

1204
01:08:08,160 --> 01:08:11,479
Speaker 1: found where some lions. Those two lions had killed. Would

1205
01:08:11,480 --> 01:08:14,400
Speaker 1: you remember they killed? They killed elker deer. I don't

1206
01:08:14,400 --> 01:08:16,320
Speaker 1: remember what it was. And he's got all these pictures

1207
01:08:16,320 --> 01:08:19,160
Speaker 1: of them up in a tree because the wolves rolled

1208
01:08:19,200 --> 01:08:22,400
Speaker 1: in and the lions just ran up on a couple

1209
01:08:22,400 --> 01:08:27,599
Speaker 1: of leaning lean trees. You know, this load took a nap. Yeah,

1210
01:08:28,439 --> 01:08:32,160
Speaker 1: they're like like it now, naps waiting for the wolves

1211
01:08:32,200 --> 01:08:33,760
Speaker 1: to leave because there's nothing they're gonna do about it,

1212
01:08:33,800 --> 01:08:36,000
Speaker 1: you know, stayed up in the tree, right. Yeah. I

1213
01:08:36,040 --> 01:08:40,120
Speaker 1: actually went to a wolf kill site that had It

1214
01:08:40,200 --> 01:08:41,680
Speaker 1: was hard to tell what had happened because it was

1215
01:08:41,720 --> 01:08:44,439
Speaker 1: an old kill site that the wolf I was following

1216
01:08:44,680 --> 01:08:48,439
Speaker 1: had returned to, but it looked to me like she'd

1217
01:08:49,479 --> 01:08:51,840
Speaker 1: they'd killed a deer. I think it's what it was.

1218
01:08:52,840 --> 01:08:56,960
Speaker 1: And then I also found where they had been where

1219
01:08:56,960 --> 01:08:58,960
Speaker 1: they killed a mountain lion and she had gone back

1220
01:08:59,000 --> 01:09:01,639
Speaker 1: and was renowning on those bones. The wolves killed the lion,

1221
01:09:01,880 --> 01:09:04,120
Speaker 1: So I mean, I don't you never know exactly what happened,

1222
01:09:04,160 --> 01:09:07,960
Speaker 1: but but the lion's carcass was close to the deer. Yeah,

1223
01:09:08,080 --> 01:09:10,640
Speaker 1: so they might have rolled up, got a tussle over

1224
01:09:10,720 --> 01:09:13,719
Speaker 1: the deer and killed the lion and eighth the lion. Mhm.

1225
01:09:14,240 --> 01:09:18,519
Speaker 1: It's a good way to get trick analysis. Yeah, that's

1226
01:09:18,560 --> 01:09:22,240
Speaker 1: all that happens. Yeah, So but anyway, just mainly the

1227
01:09:22,320 --> 01:09:26,439
Speaker 1: point there is that when you're looking at predation rates

1228
01:09:27,640 --> 01:09:32,519
Speaker 1: and you know how often predators are killing prey, you

1229
01:09:32,640 --> 01:09:35,680
Speaker 1: gotta kind of think about and remember that it's probably

1230
01:09:35,920 --> 01:09:39,240
Speaker 1: not just that that predator of that prac that pack

1231
01:09:39,400 --> 01:09:41,560
Speaker 1: that's eating it. A lot of times, there's bears coming in,

1232
01:09:41,640 --> 01:09:44,320
Speaker 1: there's you know, food for a lot of stuff. We

1233
01:09:44,400 --> 01:09:46,680
Speaker 1: got a friend, uh fella, we talked to you that

1234
01:09:47,400 --> 01:09:51,160
Speaker 1: he was doing they were doing mortality. They were investigating

1235
01:09:51,240 --> 01:09:57,080
Speaker 1: mortality of collard caribou and they had a caribou wearing

1236
01:09:57,120 --> 01:10:00,720
Speaker 1: a collar. Gotta you know the death you know, the

1237
01:10:01,000 --> 01:10:05,360
Speaker 1: mortality signal had been hit by a car, eaten by wolves,

1238
01:10:05,680 --> 01:10:08,880
Speaker 1: eaten by a bear. Yeah. There's a lot of sharing

1239
01:10:08,960 --> 01:10:12,920
Speaker 1: going yeah, definitely. Yeah, And so that's one of the

1240
01:10:13,000 --> 01:10:15,200
Speaker 1: things that makes kill site analysis fun is it's not

1241
01:10:15,320 --> 01:10:18,600
Speaker 1: always just a straightforward Oh the cat was here, so

1242
01:10:18,920 --> 01:10:20,960
Speaker 1: it ate it all up. You know, you don't know,

1243
01:10:21,320 --> 01:10:24,639
Speaker 1: is this a scavenge situation with the cats? That's less

1244
01:10:24,640 --> 01:10:29,240
Speaker 1: common just because they like fresh meat. But um, like

1245
01:10:29,320 --> 01:10:31,920
Speaker 1: what percent of a wolverine? Like what percent of a

1246
01:10:31,960 --> 01:10:34,360
Speaker 1: wolverines diet? Did he not kill himself? It's got to

1247
01:10:34,400 --> 01:10:36,640
Speaker 1: be enormal. Oh yeah, that's I think one of their

1248
01:10:36,680 --> 01:10:42,920
Speaker 1: main things is scavenging, avalanche slides, other kills. So now

1249
01:10:43,160 --> 01:10:45,200
Speaker 1: the last thing about the lion, that lion job. What

1250
01:10:45,280 --> 01:10:46,800
Speaker 1: were they trying to find out? What are they eating?

1251
01:10:47,320 --> 01:10:49,400
Speaker 1: What are they eating? And what's the kill rate? Yeah,

1252
01:10:49,680 --> 01:10:53,519
Speaker 1: what's that mean? Kills? What do you find or what

1253
01:10:53,720 --> 01:10:56,240
Speaker 1: they find they've I'm not gonna be able to remember

1254
01:10:56,280 --> 01:10:57,600
Speaker 1: off the top of my head. But as far as

1255
01:10:57,680 --> 01:11:00,080
Speaker 1: prayer composition, it's you know, it's very but it all so,

1256
01:11:01,800 --> 01:11:05,479
Speaker 1: I mean, predator populations and eating habitats are eating habits

1257
01:11:07,600 --> 01:11:11,720
Speaker 1: in general are really kind of controlled from the bottom up.

1258
01:11:11,760 --> 01:11:16,880
Speaker 1: So what's available? You know. Um, something that I've come

1259
01:11:16,960 --> 01:11:20,439
Speaker 1: to realize just from being out there and from you know,

1260
01:11:20,560 --> 01:11:25,080
Speaker 1: reading the literature, is that a lot of times it's

1261
01:11:25,080 --> 01:11:28,280
Speaker 1: the reverse of what people think. It's more the the

1262
01:11:28,400 --> 01:11:35,400
Speaker 1: prey population controlling the predator population um, which is kind

1263
01:11:35,439 --> 01:11:38,840
Speaker 1: of relieves some of the fears that people have of

1264
01:11:39,400 --> 01:11:41,240
Speaker 1: you know, these predators are going to come in and

1265
01:11:42,160 --> 01:11:44,800
Speaker 1: you know, decimate this dear population or whatever. That's the thing.

1266
01:11:45,040 --> 01:11:47,640
Speaker 1: That's the thing I struggle explain to people oftentimes when

1267
01:11:47,760 --> 01:11:50,599
Speaker 1: when they're when they're um, when people get a little

1268
01:11:50,600 --> 01:11:55,120
Speaker 1: bit too hysterical about the predator threat, is um. You know,

1269
01:11:55,320 --> 01:12:00,360
Speaker 1: predators have Really it doesn't really make sense mathematically for

1270
01:12:00,520 --> 01:12:06,200
Speaker 1: predator to annihilate its resource because that spells real bad

1271
01:12:06,280 --> 01:12:10,760
Speaker 1: things for the predators. They can something up and then

1272
01:12:10,840 --> 01:12:12,800
Speaker 1: move on to something else, you know, for sure, Like

1273
01:12:12,840 --> 01:12:16,160
Speaker 1: we got our body in Kentucky, was he was saying it.

1274
01:12:16,320 --> 01:12:21,880
Speaker 1: When coyotes came in, He felt that the first thing

1275
01:12:21,920 --> 01:12:26,080
Speaker 1: they did was they worked groundhogs. And he said that

1276
01:12:26,240 --> 01:12:28,679
Speaker 1: was like the one thing you saw that just vanished

1277
01:12:28,720 --> 01:12:32,120
Speaker 1: from the landscape was groundhogs. It was like he said

1278
01:12:32,120 --> 01:12:36,000
Speaker 1: that he felt just anecdotal personal observation, but he felt

1279
01:12:36,160 --> 01:12:39,640
Speaker 1: that they went from having shiploads of groundhogs and then

1280
01:12:39,680 --> 01:12:41,840
Speaker 1: they had no brown hogs, and then they went on

1281
01:12:41,920 --> 01:12:44,720
Speaker 1: to other things and established a viable population. But he

1282
01:12:44,800 --> 01:12:46,439
Speaker 1: felt that that was a case where it was just

1283
01:12:46,560 --> 01:12:50,439
Speaker 1: they were gone, yeah, and then did they did you

1284
01:12:50,479 --> 01:12:52,640
Speaker 1: feel like they switched to something? Yeah, and then now

1285
01:12:52,720 --> 01:12:54,760
Speaker 1: they got you know, shiploads guy oots and he all

1286
01:12:54,800 --> 01:12:56,320
Speaker 1: kinds of stuff. But he felt the one thing that

1287
01:12:56,400 --> 01:12:59,320
Speaker 1: he saw just vanish was it must have been this

1288
01:12:59,439 --> 01:13:01,559
Speaker 1: easy pick kinds and something they really dedicated a lot

1289
01:13:01,560 --> 01:13:04,720
Speaker 1: of time to and and that was what they've done. Yeah.

1290
01:13:05,320 --> 01:13:10,040
Speaker 1: It's the other thing that I've learned is that trying

1291
01:13:10,080 --> 01:13:18,200
Speaker 1: to pinpoint the relationship between prey and predator populations is

1292
01:13:18,479 --> 01:13:25,120
Speaker 1: really complicated. It's um, it's tempting to say, you know,

1293
01:13:25,320 --> 01:13:32,560
Speaker 1: this population of deer is doing really badly because X

1294
01:13:32,640 --> 01:13:37,800
Speaker 1: predator is on the rise, or you know, because they

1295
01:13:37,840 --> 01:13:40,200
Speaker 1: gave out way too many tags or whatever. It's it's

1296
01:13:40,240 --> 01:13:47,919
Speaker 1: easy to try and pinning on one thing, but in reality,

1297
01:13:48,040 --> 01:13:51,200
Speaker 1: there are usually a lot of factors going on and

1298
01:13:51,320 --> 01:13:56,880
Speaker 1: working together. And um, I think the climate is under

1299
01:13:58,320 --> 01:14:03,519
Speaker 1: appreciated for its influence on prey populations, you know, a

1300
01:14:03,560 --> 01:14:07,280
Speaker 1: bad winner or a drought or whatever, and and predators

1301
01:14:07,320 --> 01:14:15,880
Speaker 1: are often um over appreciated for theirs. It's it's hard

1302
01:14:16,000 --> 01:14:21,679
Speaker 1: to find a situation where I mean it happens especially

1303
01:14:21,720 --> 01:14:26,160
Speaker 1: in situations where populations are already not doing well. Um,

1304
01:14:26,520 --> 01:14:31,720
Speaker 1: but it's it's not often that you see this population

1305
01:14:31,800 --> 01:14:37,080
Speaker 1: of prey is doing badly and it's because of this

1306
01:14:37,400 --> 01:14:41,080
Speaker 1: predator population. But yeah, I think that it becomes most

1307
01:14:41,160 --> 01:14:44,840
Speaker 1: pronounced when you get to those vulnerable spots like for instance,

1308
01:14:44,880 --> 01:14:47,519
Speaker 1: the cab the caribou guy we talked with, he's dealing

1309
01:14:47,600 --> 01:14:51,240
Speaker 1: with with a dozen animals, which is a population that

1310
01:14:51,880 --> 01:14:54,160
Speaker 1: is going to have It's a huge deal for us,

1311
01:14:54,680 --> 01:14:57,000
Speaker 1: you know, like losing one new predator is a huge deal.

1312
01:14:57,080 --> 01:14:58,880
Speaker 1: Losing one anything, losing one to get hit by a

1313
01:14:58,920 --> 01:15:04,759
Speaker 1: car vehicle, mortality on white tail deer isn't really making

1314
01:15:04,760 --> 01:15:07,360
Speaker 1: anybody worried. But when you've got a dozen of something,

1315
01:15:07,600 --> 01:15:10,080
Speaker 1: it's a big deal. Or you have a drainage that

1316
01:15:10,200 --> 01:15:16,120
Speaker 1: has a population of maybe six or seven breeding female moose, Yeah,

1317
01:15:16,439 --> 01:15:19,720
Speaker 1: predation becomes an issue because you got six or seven well,

1318
01:15:19,760 --> 01:15:23,519
Speaker 1: and everything becomes into yeah, everything. You can't just point

1319
01:15:23,560 --> 01:15:27,800
Speaker 1: it at the predators and it's habitat and um and

1320
01:15:28,240 --> 01:15:31,840
Speaker 1: climb our they're usually big. It's hard to isolate all

1321
01:15:31,840 --> 01:15:34,559
Speaker 1: those different factors for the research so that you can

1322
01:15:34,680 --> 01:15:37,880
Speaker 1: say if it's another but that's what um our buddy

1323
01:15:37,920 --> 01:15:41,479
Speaker 1: bil Andre is talking about the warden from Colorado. Have

1324
01:15:41,560 --> 01:15:43,639
Speaker 1: you heard about the researcher doing in the Piance Basin

1325
01:15:43,920 --> 01:15:47,680
Speaker 1: in Colorado with the with the predator mule dear relationship.

1326
01:15:48,640 --> 01:15:51,120
Speaker 1: They feel like they've got an isolated enough area and

1327
01:15:51,200 --> 01:15:55,360
Speaker 1: a herd that's not doing well compared to other herds

1328
01:15:55,400 --> 01:15:58,120
Speaker 1: around it, but it's isolated and they know that they've

1329
01:15:58,160 --> 01:16:00,800
Speaker 1: got like what do you say, the habitat they know

1330
01:16:01,040 --> 01:16:04,439
Speaker 1: can support the the fall. Yeah, they're they have they're

1331
01:16:04,479 --> 01:16:11,040
Speaker 1: having great fawn the females, they test their pregnant with twins.

1332
01:16:11,520 --> 01:16:14,000
Speaker 1: The fawns when they test them, the live fonds and

1333
01:16:14,040 --> 01:16:17,920
Speaker 1: they test them are heavier than the last time they

1334
01:16:17,960 --> 01:16:21,240
Speaker 1: are tested in the eighties, so they're well fed. But

1335
01:16:21,360 --> 01:16:25,120
Speaker 1: they have just zero recruitment. So they feel like maybe

1336
01:16:25,640 --> 01:16:28,760
Speaker 1: they're getting some very heavy predation right during that like

1337
01:16:29,240 --> 01:16:33,240
Speaker 1: early stages of growth like in June July, and so

1338
01:16:33,320 --> 01:16:37,160
Speaker 1: they're gonna try predator removable at those keys. You know

1339
01:16:37,400 --> 01:16:39,960
Speaker 1: what they think is But one thing you're saying, too

1340
01:16:40,120 --> 01:16:41,720
Speaker 1: was peculiar about the approach we're taking. As a lot

1341
01:16:41,760 --> 01:16:44,799
Speaker 1: of times people do sort of this like generalized predator control.

1342
01:16:46,000 --> 01:16:48,000
Speaker 1: But they're gonna do a very targeted predator control at

1343
01:16:48,040 --> 01:16:50,960
Speaker 1: a very targeted time. So not like going out in

1344
01:16:51,439 --> 01:16:55,439
Speaker 1: January February to catch cats that may or may not

1345
01:16:55,680 --> 01:17:00,280
Speaker 1: be killing fawns in May and June, but to kill

1346
01:17:00,400 --> 01:17:04,680
Speaker 1: cats in May and June to see if you know,

1347
01:17:04,720 --> 01:17:06,519
Speaker 1: you never know if you're getting like the cat, but

1348
01:17:06,680 --> 01:17:08,680
Speaker 1: like to see if what kind of movement that has

1349
01:17:08,760 --> 01:17:15,000
Speaker 1: on it? Yea. Um but man, Yeah, predator control. It's

1350
01:17:15,040 --> 01:17:18,120
Speaker 1: like such a thorny subject it is, and it's um.

1351
01:17:20,600 --> 01:17:25,960
Speaker 1: I think it's slowly changing a little bit. I think

1352
01:17:26,080 --> 01:17:31,120
Speaker 1: our traditional predator management is has been in the past

1353
01:17:31,280 --> 01:17:35,760
Speaker 1: that there's a problem, we kill the predators. Um. But

1354
01:17:35,880 --> 01:17:41,439
Speaker 1: I think that there are other ways and um that

1355
01:17:41,600 --> 01:17:45,160
Speaker 1: that's slowly starting to be incorporated. Yeah, but I'm afraid

1356
01:17:45,160 --> 01:17:47,360
Speaker 1: they're gonna throw out the baby with the bathwater. I mean,

1357
01:17:47,400 --> 01:17:49,960
Speaker 1: I think the old days of you know, taking a

1358
01:17:50,200 --> 01:17:53,400
Speaker 1: half dead animal and injecting it with strict nine and

1359
01:17:53,479 --> 01:18:01,080
Speaker 1: then having that be your predator control program is you know,

1360
01:18:01,439 --> 01:18:05,160
Speaker 1: those days are beyond us. But I think that also

1361
01:18:05,280 --> 01:18:07,760
Speaker 1: there are times like this thing we're talking about, this

1362
01:18:08,000 --> 01:18:11,000
Speaker 1: this piece of work that they're doing in Colorado or

1363
01:18:11,040 --> 01:18:12,840
Speaker 1: the thing they're doing with mountain like the thing they're

1364
01:18:12,840 --> 01:18:15,000
Speaker 1: not doing active predator control of the Mountain carripe, but

1365
01:18:15,800 --> 01:18:19,719
Speaker 1: were they. It's like in cases, I think it's very valuable,

1366
01:18:20,280 --> 01:18:22,599
Speaker 1: but everybody, you know, people want to be so binary.

1367
01:18:22,680 --> 01:18:27,519
Speaker 1: It's like we had the early model which was used

1368
01:18:27,560 --> 01:18:31,280
Speaker 1: poison to eradicate all predators, and and now to have

1369
01:18:31,439 --> 01:18:35,240
Speaker 1: this like over correction that we're leading to now where

1370
01:18:35,280 --> 01:18:36,880
Speaker 1: we want to be like, oh no, it's you know,

1371
01:18:37,040 --> 01:18:40,800
Speaker 1: it's like this this tool we dacn't use because of

1372
01:18:41,120 --> 01:18:44,680
Speaker 1: the you know, because of the public perception of it

1373
01:18:44,800 --> 01:18:48,000
Speaker 1: and the pr obstacles in the way. It's just like

1374
01:18:48,080 --> 01:18:52,479
Speaker 1: everything else. I think like predator control at times can

1375
01:18:52,520 --> 01:18:54,519
Speaker 1: be a valuable tool. Does that mean I think we

1376
01:18:54,560 --> 01:18:58,439
Speaker 1: should poison carcasses and kill everything that feeds on a

1377
01:18:58,640 --> 01:19:02,880
Speaker 1: on a on a on a dead l No. Yeah,

1378
01:19:03,040 --> 01:19:06,240
Speaker 1: I think that we don't want to limit the tools

1379
01:19:06,320 --> 01:19:09,439
Speaker 1: we've got. But I my I don't know. My feeling

1380
01:19:10,840 --> 01:19:13,760
Speaker 1: and what I've learned from just being around predator management

1381
01:19:14,040 --> 01:19:19,439
Speaker 1: is that, um, we often come at it from look

1382
01:19:19,479 --> 01:19:22,160
Speaker 1: at it with a certain framework of what we've always done,

1383
01:19:22,200 --> 01:19:27,960
Speaker 1: which is there's a problem we control predator populations where um,

1384
01:19:28,960 --> 01:19:32,120
Speaker 1: where I think we're missing in situations, that there are

1385
01:19:34,000 --> 01:19:36,559
Speaker 1: other things that might actually be the problem, a more

1386
01:19:36,640 --> 01:19:42,040
Speaker 1: underlying problem, um, and that there might be other ways

1387
01:19:42,800 --> 01:19:46,360
Speaker 1: to solve it, that this is not a panacea. Yeah,

1388
01:19:46,560 --> 01:19:48,759
Speaker 1: it's like it's like people, some people, some people, especially

1389
01:19:48,760 --> 01:19:49,960
Speaker 1: on our end of things, like a lot of big

1390
01:19:50,000 --> 01:19:51,920
Speaker 1: game huners, want to think that that's like the answer

1391
01:19:51,960 --> 01:19:55,639
Speaker 1: to all problems. Right, Yeah, I think we're where it gaus,

1392
01:19:55,680 --> 01:19:58,240
Speaker 1: we're with predator controls. When people act like it's a um,

1393
01:20:00,439 --> 01:20:02,960
Speaker 1: you know, I think a lot of hunters, especially act

1394
01:20:03,000 --> 01:20:05,160
Speaker 1: like it's like this panacea where they feel like it's

1395
01:20:05,200 --> 01:20:08,160
Speaker 1: solved all problems. The predators are the root of all

1396
01:20:08,240 --> 01:20:13,439
Speaker 1: evil when it comes to diminished game populations. I read

1397
01:20:13,479 --> 01:20:15,599
Speaker 1: this paper not long ago. Was more like an internal

1398
01:20:15,760 --> 01:20:19,639
Speaker 1: letter where a guy was there, there's a biologist news

1399
01:20:19,760 --> 01:20:24,559
Speaker 1: explaining people's perceptions of the impact of wolves on elk

1400
01:20:26,040 --> 01:20:29,640
Speaker 1: and you're saying, how we've always, you know, prior to

1401
01:20:29,720 --> 01:20:35,120
Speaker 1: the re establishment of wolves, we've always lost thirty calves

1402
01:20:36,080 --> 01:20:41,519
Speaker 1: per hundred two lions. And he said the wolves probably

1403
01:20:41,640 --> 01:20:46,439
Speaker 1: added about ten calves per hundreds, but people were just

1404
01:20:46,640 --> 01:20:49,360
Speaker 1: used to thirty. Like people had just become used to

1405
01:20:49,479 --> 01:20:53,360
Speaker 1: the fact that you know, about sevent calves survived, and

1406
01:20:53,439 --> 01:20:55,760
Speaker 1: they got used to like that was how we allocated

1407
01:20:55,840 --> 01:20:59,600
Speaker 1: tags that people are used to seeing. And then you

1408
01:20:59,720 --> 01:21:03,559
Speaker 1: had an additive effect of wolves and it wound up,

1409
01:21:04,920 --> 01:21:07,960
Speaker 1: you know, it upset this sort of long standing system,

1410
01:21:08,040 --> 01:21:10,519
Speaker 1: and it impacted the number of lk impacted the number

1411
01:21:10,520 --> 01:21:12,920
Speaker 1: of tags, and people are like, oh, it's all wolves.

1412
01:21:13,360 --> 01:21:16,559
Speaker 1: It was like, no, in fact, it's mostly lions. Wolves

1413
01:21:16,560 --> 01:21:20,800
Speaker 1: are just a new additive to that. Yeah, you know,

1414
01:21:20,960 --> 01:21:23,200
Speaker 1: but it's like people take a while. I get used

1415
01:21:23,200 --> 01:21:26,559
Speaker 1: to it, but then they then I run into people

1416
01:21:27,160 --> 01:21:30,760
Speaker 1: about wolves who almost want to make you believe that

1417
01:21:30,840 --> 01:21:34,120
Speaker 1: wolves eat grass. By the way, they point out that

1418
01:21:34,280 --> 01:21:37,280
Speaker 1: there's no you know what I mean, that they don't

1419
01:21:37,280 --> 01:21:39,600
Speaker 1: do anything. I was like, well, these seven pounds of

1420
01:21:39,640 --> 01:21:44,080
Speaker 1: me today, so it's coming from somewhere. Yeah. I mean,

1421
01:21:44,160 --> 01:21:51,360
Speaker 1: they they're out there just doing their thing. But in

1422
01:21:51,520 --> 01:21:58,200
Speaker 1: both directions. The the impact that they have I think

1423
01:21:58,320 --> 01:22:02,920
Speaker 1: is overblown a lot. They're not, um, they're not necessarily

1424
01:22:03,520 --> 01:22:09,960
Speaker 1: fixing everything, and um, they're also not ruining everything. I like,

1425
01:22:10,200 --> 01:22:12,439
Speaker 1: I mean, I enjoy them being out there. I like

1426
01:22:12,560 --> 01:22:14,519
Speaker 1: them being out there it's like I think that I

1427
01:22:14,680 --> 01:22:20,880
Speaker 1: probably represent a pretty standard view of UM. I like

1428
01:22:21,120 --> 01:22:25,320
Speaker 1: having all the native species on the ground. I like

1429
01:22:25,520 --> 01:22:31,000
Speaker 1: having like, you know, an intact collection of large predators.

1430
01:22:32,120 --> 01:22:36,479
Speaker 1: And I also like it when those large predators are

1431
01:22:36,520 --> 01:22:40,920
Speaker 1: managed as a renewable resource where you have interest. So

1432
01:22:42,240 --> 01:22:44,120
Speaker 1: that's just my personal take on I'm like the middle

1433
01:22:44,120 --> 01:22:46,679
Speaker 1: of the road or yeah, I'm like, yeah, I would

1434
01:22:46,800 --> 01:22:49,680
Speaker 1: never suggest eradicating them. But I also don't like that

1435
01:22:50,600 --> 01:22:54,719
Speaker 1: the game we play where people have they're like favorite

1436
01:22:54,760 --> 01:22:58,920
Speaker 1: animals and then they um want to act like certain

1437
01:22:58,960 --> 01:23:03,720
Speaker 1: animals are off limits because they're like a calendar worthy species. Yeah. Yeah,

1438
01:23:03,760 --> 01:23:07,400
Speaker 1: and that's all. That's tough thing to talk about two

1439
01:23:07,400 --> 01:23:11,559
Speaker 1: because that hits some people's emotional attachment to different animals

1440
01:23:11,680 --> 01:23:14,479
Speaker 1: and just kind of their own belief system. You know,

1441
01:23:14,520 --> 01:23:18,639
Speaker 1: there's some animals that are just taboo for take you know, UM,

1442
01:23:20,960 --> 01:23:23,280
Speaker 1: but I think we all we all have that that

1443
01:23:23,479 --> 01:23:25,960
Speaker 1: threshold somewhere or you know, a lot of hunters I

1444
01:23:26,040 --> 01:23:28,000
Speaker 1: think of I kind of think of a graph and

1445
01:23:28,200 --> 01:23:32,840
Speaker 1: there's a lineup of animals on the X axis, and

1446
01:23:33,400 --> 01:23:38,479
Speaker 1: like so for me, zero is mosquitoes, and then you know,

1447
01:23:38,920 --> 01:23:43,559
Speaker 1: at the other I know the X axis. There's something

1448
01:23:43,640 --> 01:23:46,679
Speaker 1: I would not want to kill, like my grandma or something,

1449
01:23:47,240 --> 01:23:50,280
Speaker 1: and so and then there's this Yeah, two lines and

1450
01:23:50,400 --> 01:23:57,000
Speaker 1: one is um, your desire to eat it hunted, UM

1451
01:23:58,320 --> 01:24:01,800
Speaker 1: be a predator for some reason. And then there's another line,

1452
01:24:02,600 --> 01:24:07,040
Speaker 1: UM that's just kind of your empathy or whatever. And

1453
01:24:07,120 --> 01:24:09,519
Speaker 1: so you have this line that for me, I want

1454
01:24:09,560 --> 01:24:12,840
Speaker 1: to kill mosquitoes. So I don't have empathy and I

1455
01:24:12,960 --> 01:24:15,880
Speaker 1: have a high want. And then where those lines intersect,

1456
01:24:16,080 --> 01:24:20,360
Speaker 1: where I've got um, the desire to kill something is

1457
01:24:20,720 --> 01:24:28,320
Speaker 1: higher than my empathy, higher than UM, my desire to

1458
01:24:28,400 --> 01:24:32,800
Speaker 1: just know they're there, that individuals there, um. And then

1459
01:24:33,240 --> 01:24:39,080
Speaker 1: but there's also the point where I like knowing they're there,

1460
01:24:39,120 --> 01:24:41,760
Speaker 1: and my empathy is so great that I have no

1461
01:24:41,880 --> 01:24:46,200
Speaker 1: desire to kill them. Where is it fall for you? Um?

1462
01:24:49,200 --> 01:24:54,040
Speaker 1: I I think empathy grows as you interact with animals

1463
01:24:54,080 --> 01:24:56,200
Speaker 1: a lot. So for me, I don't know about that.

1464
01:24:56,360 --> 01:25:00,280
Speaker 1: Well okay, well, okay, here I think bear. This is

1465
01:25:00,320 --> 01:25:04,639
Speaker 1: where things are getting really great. For me, those lines

1466
01:25:04,680 --> 01:25:09,479
Speaker 1: start to get really close. I would have a hard

1467
01:25:09,479 --> 01:25:12,240
Speaker 1: time hunting a bear. I wouldn't I don't have a desire,

1468
01:25:12,720 --> 01:25:17,920
Speaker 1: my desire to to eat it doesn't outweigh my desire

1469
01:25:18,000 --> 01:25:22,400
Speaker 1: to just know they're there. I've also I have interacted

1470
01:25:22,439 --> 01:25:26,200
Speaker 1: with so many bears. I've held their cubs and watched

1471
01:25:26,240 --> 01:25:30,000
Speaker 1: them in their dens, and watched hours of you know,

1472
01:25:30,200 --> 01:25:33,519
Speaker 1: trail camp footage of them, and so I just feel

1473
01:25:33,560 --> 01:25:38,760
Speaker 1: too connected so that myself doesn't explain it. Why not

1474
01:25:39,600 --> 01:25:42,360
Speaker 1: interaction doesn't explain it? Because think about how how much

1475
01:25:42,400 --> 01:25:48,760
Speaker 1: have you interacted with elk? Yeah, thousands of hours held

1476
01:25:48,760 --> 01:25:57,320
Speaker 1: their babies? Okay, but observation studying, right, Yeah, I think

1477
01:25:57,560 --> 01:26:00,400
Speaker 1: in my case, in my case, interaction leads in the

1478
01:26:00,479 --> 01:26:04,400
Speaker 1: other direction. There's some things where I feel like, uh,

1479
01:26:06,080 --> 01:26:10,800
Speaker 1: like recently, we had a wolverine, right, get into a

1480
01:26:10,840 --> 01:26:13,879
Speaker 1: wolf carcass in an area where you're allowed one wolverine

1481
01:26:14,040 --> 01:26:16,519
Speaker 1: year hunting. It was the first wolverna I ever laid

1482
01:26:16,560 --> 01:26:19,160
Speaker 1: eyes on. I was like, I'm not gonna kill the

1483
01:26:19,200 --> 01:26:23,240
Speaker 1: first wolverine I ever laid eyes on. Right, That's the

1484
01:26:23,280 --> 01:26:24,760
Speaker 1: thing that I was thinking about what people go to

1485
01:26:24,800 --> 01:26:26,479
Speaker 1: Africa where it's kind of like, oh, that's what that

1486
01:26:26,560 --> 01:26:31,160
Speaker 1: looks like. It's like I don't have any context with it, right'

1487
01:26:31,240 --> 01:26:34,120
Speaker 1: I shoot the first wolverine I see Now, if I'd

1488
01:26:34,160 --> 01:26:36,400
Speaker 1: been out and I glassed up a dozen wolverines over

1489
01:26:36,439 --> 01:26:38,960
Speaker 1: the course of a couple of years, I start being like, yeah,

1490
01:26:39,080 --> 01:26:42,439
Speaker 1: like I now have sort of earned my place at

1491
01:26:42,479 --> 01:26:46,120
Speaker 1: the table. Ah. Yeah, that's just another measuring stick of like,

1492
01:26:47,000 --> 01:26:48,880
Speaker 1: I don't know, I just feel like everybody's got their

1493
01:26:48,960 --> 01:26:52,560
Speaker 1: own kind of complicated value and ethics around it and

1494
01:26:52,720 --> 01:26:56,160
Speaker 1: that that plays into it. But there's mean, you shoot

1495
01:26:56,160 --> 01:26:59,800
Speaker 1: a panda bear. No, I have no desire to do

1496
01:27:00,400 --> 01:27:03,360
Speaker 1: That's what. Yeah, that's where I draw the line. He's

1497
01:27:03,400 --> 01:27:06,240
Speaker 1: always having to be guiding. It seemed like a round

1498
01:27:06,760 --> 01:27:11,000
Speaker 1: animal number ten of the fall, where like because early

1499
01:27:11,120 --> 01:27:13,600
Speaker 1: on it's just like every client you're just like, I

1500
01:27:13,680 --> 01:27:14,920
Speaker 1: want to kill an elk with you. I want to

1501
01:27:15,000 --> 01:27:16,680
Speaker 1: kill an elk with you. Let's go, let's go, let's go.

1502
01:27:16,920 --> 01:27:19,800
Speaker 1: And then when you've seen about ten of them hit

1503
01:27:19,840 --> 01:27:22,760
Speaker 1: the dirt, all of a sudden, you're just kind of like, oh,

1504
01:27:24,560 --> 01:27:28,040
Speaker 1: killing another one. Yeah, there's something so fresh for the

1505
01:27:28,120 --> 01:27:31,439
Speaker 1: client though, yeah he's not he's not feeling that, you know.

1506
01:27:31,840 --> 01:27:33,960
Speaker 1: I definitely felt like as a guide I would just

1507
01:27:34,040 --> 01:27:37,519
Speaker 1: be like, oh, well, you know, yeah, if you don't

1508
01:27:37,520 --> 01:27:39,560
Speaker 1: want to run after that one, we don't have to,

1509
01:27:39,880 --> 01:27:42,479
Speaker 1: you know. Yeah, Yeah, so that empathy line is starting

1510
01:27:43,640 --> 01:27:46,560
Speaker 1: above your desire to. Yeah, I have with I have

1511
01:27:46,800 --> 01:27:50,400
Speaker 1: with wolves as much as I support UM, as much

1512
01:27:50,400 --> 01:27:54,200
Speaker 1: as I support the right of state fishing game agencies

1513
01:27:54,680 --> 01:27:57,599
Speaker 1: to manage wolves as they see fit, as much as

1514
01:27:57,640 --> 01:28:03,360
Speaker 1: I support UM hunters who operating within the letter of

1515
01:28:03,400 --> 01:28:06,680
Speaker 1: the law. They're like right to hunt as long as

1516
01:28:06,720 --> 01:28:10,280
Speaker 1: their state game agency has determined that the population can

1517
01:28:10,360 --> 01:28:15,200
Speaker 1: support harvest and it's all done within accordance to preserving

1518
01:28:15,240 --> 01:28:18,439
Speaker 1: the long term viability of the species and all that stuff.

1519
01:28:18,479 --> 01:28:24,320
Speaker 1: That's a long caveat right, UM. And I've purchased wolf tags,

1520
01:28:24,960 --> 01:28:30,840
Speaker 1: but when I see a wolf, UM, I just don't, right,

1521
01:28:31,920 --> 01:28:35,600
Speaker 1: don't feel desire. Uh. One time we were out and

1522
01:28:36,240 --> 01:28:39,720
Speaker 1: I'd killed a doll ram and then my buddy got

1523
01:28:39,800 --> 01:28:42,760
Speaker 1: a bear. And that night we had a you know,

1524
01:28:42,960 --> 01:28:45,599
Speaker 1: white wolf come rolling down the river bank where we were,

1525
01:28:47,040 --> 01:28:48,800
Speaker 1: And at that time I just was like, you know,

1526
01:28:48,880 --> 01:28:51,200
Speaker 1: we just got a sheet, we got a bear. Two

1527
01:28:51,320 --> 01:28:55,920
Speaker 1: days later, It's like, you know, that's a lot, But

1528
01:28:56,000 --> 01:28:58,320
Speaker 1: there's always something hard. Time I was just hiking up

1529
01:28:58,320 --> 01:29:02,800
Speaker 1: a river with my rifle. Wolf standing there could have

1530
01:29:03,640 --> 01:29:07,120
Speaker 1: you know, shot the wolf, zero desire. I was staying.

1531
01:29:07,160 --> 01:29:08,600
Speaker 1: I mean, I could have thrown a rock at it.

1532
01:29:09,600 --> 01:29:11,320
Speaker 1: No desire, but in the back of my head, and

1533
01:29:11,400 --> 01:29:13,240
Speaker 1: I was like, yeah at some point. But it's like

1534
01:29:13,320 --> 01:29:17,479
Speaker 1: when it happens, I don't the when I like, you know,

1535
01:29:17,520 --> 01:29:20,880
Speaker 1: you show me something like a doll ram, the minute

1536
01:29:20,920 --> 01:29:23,920
Speaker 1: I see it, my desire to go after it goes

1537
01:29:24,000 --> 01:29:29,400
Speaker 1: through the roof. Yeah. But the minute I see that,

1538
01:29:29,680 --> 01:29:32,400
Speaker 1: you know, lay eyes on wolf, the desire doesn't climb

1539
01:29:32,920 --> 01:29:37,160
Speaker 1: grizzly Bears. It's like a very gradual down like a wolf.

1540
01:29:37,240 --> 01:29:41,080
Speaker 1: It's like the desire is pretty sharp down. Grizzly Bears

1541
01:29:41,160 --> 01:29:44,960
Speaker 1: is a gradual down. Black Bears is a flat line.

1542
01:29:45,680 --> 01:29:48,479
Speaker 1: Mm hmm. I'm like, oh, there he is. I suppose

1543
01:29:48,520 --> 01:29:53,760
Speaker 1: we should go over there and get him. Yeah, come,

1544
01:29:53,920 --> 01:29:56,400
Speaker 1: let's go, let's go. Yeah. There's a lot that goes

1545
01:29:56,520 --> 01:30:01,840
Speaker 1: into how quilthy that empathy threshold is reached, and I

1546
01:30:01,920 --> 01:30:04,679
Speaker 1: think that's I don't know, it's a it's not something

1547
01:30:04,760 --> 01:30:08,519
Speaker 1: that we should never necessarily like strive to push through

1548
01:30:08,600 --> 01:30:12,160
Speaker 1: that or or to you know, not think about it

1549
01:30:12,240 --> 01:30:15,000
Speaker 1: too hard, because it's upsetting to think about, you know,

1550
01:30:15,920 --> 01:30:18,920
Speaker 1: killing this elk. And I think it's okay you can

1551
01:30:19,000 --> 01:30:21,599
Speaker 1: be upset about it a little bit but also want

1552
01:30:21,640 --> 01:30:23,920
Speaker 1: to kill it and go through with it. But and

1553
01:30:24,040 --> 01:30:28,920
Speaker 1: it's okay if you're like, I cannot just make that

1554
01:30:29,080 --> 01:30:34,040
Speaker 1: wolf into um into something I don't have empathy for.

1555
01:30:35,160 --> 01:30:37,320
Speaker 1: You know, if if the if the reasons to kill

1556
01:30:37,400 --> 01:30:42,760
Speaker 1: it don't outweigh the kind of sad feeling it would

1557
01:30:42,760 --> 01:30:44,680
Speaker 1: give you to kill out why why push through that?

1558
01:30:44,800 --> 01:30:46,600
Speaker 1: You know? And there's something I know and and and

1559
01:30:46,720 --> 01:30:49,040
Speaker 1: I'm listening. I think that people. Yeah, I think it's

1560
01:30:49,080 --> 01:30:52,160
Speaker 1: something that it's a valuable thing for people to discuss

1561
01:30:52,600 --> 01:30:56,360
Speaker 1: and talk about. I do think also it's important that

1562
01:30:56,400 --> 01:31:00,799
Speaker 1: people recognize it as pretty arbitrary. Yeah, okay, very personal

1563
01:31:00,960 --> 01:31:03,200
Speaker 1: and very arbitrary. And I only have problems with that

1564
01:31:03,280 --> 01:31:07,519
Speaker 1: when people want to start legislating based on their personal

1565
01:31:07,800 --> 01:31:14,360
Speaker 1: arbitrary perception of it, because I'm like, okay, I talked

1566
01:31:14,400 --> 01:31:15,840
Speaker 1: without serie day with someone like if you go and

1567
01:31:15,960 --> 01:31:19,120
Speaker 1: buy like, if you buy a box at Chicken McNuggets, right,

1568
01:31:19,320 --> 01:31:22,400
Speaker 1: how many chickens are in that box in the way

1569
01:31:22,439 --> 01:31:25,519
Speaker 1: they produce that ship. It's not like one chicken, A

1570
01:31:25,680 --> 01:31:28,680
Speaker 1: dozen damn chickens in there all blend it up in

1571
01:31:28,680 --> 01:31:33,879
Speaker 1: a blender together. So I'm like, oh, just imagine cuddling

1572
01:31:33,920 --> 01:31:37,559
Speaker 1: all those twelve little chicks, right, But it's like you're

1573
01:31:37,560 --> 01:31:40,519
Speaker 1: not invited to think about it. So I think that

1574
01:31:40,640 --> 01:31:43,840
Speaker 1: when some people do run the calculations in their head

1575
01:31:43,920 --> 01:31:45,720
Speaker 1: and they're like and they arrive at this thing where like,

1576
01:31:45,760 --> 01:31:50,840
Speaker 1: I wouldn't want to hunt black bears. Therefore I'm going

1577
01:31:50,880 --> 01:31:52,360
Speaker 1: to really push to make it that no one can

1578
01:31:52,439 --> 01:31:54,720
Speaker 1: hunt black bears because it's upsetting for them to think

1579
01:31:54,720 --> 01:31:57,760
Speaker 1: about it's upsetting for me to think about all those

1580
01:31:57,800 --> 01:32:04,560
Speaker 1: little baby chicks. So it's some people feel like obligated

1581
01:32:04,640 --> 01:32:10,960
Speaker 1: to really pursue pushing their line. Yeah, and that's the

1582
01:32:11,000 --> 01:32:12,680
Speaker 1: only time it starts to be not offensive to me.

1583
01:32:12,760 --> 01:32:14,599
Speaker 1: But it just I started to get a little skittish

1584
01:32:15,840 --> 01:32:18,000
Speaker 1: when when that happens. I think it's always going on.

1585
01:32:18,400 --> 01:32:20,480
Speaker 1: You know, if you if you watch the way initiatives

1586
01:32:20,560 --> 01:32:23,120
Speaker 1: work and in the political cycle, it's always going on

1587
01:32:23,320 --> 01:32:28,320
Speaker 1: that people are like coming up with arbitrarily arriving at

1588
01:32:28,400 --> 01:32:31,839
Speaker 1: their favorites and then and then trying to like legislate

1589
01:32:31,880 --> 01:32:38,240
Speaker 1: their favorites when it's when it is entirely arbitrary. Yeah, Um,

1590
01:32:39,800 --> 01:32:43,200
Speaker 1: that's true. But I think that it's going to be

1591
01:32:43,280 --> 01:32:46,479
Speaker 1: a constant battle all the time between our sort of

1592
01:32:47,160 --> 01:32:54,400
Speaker 1: historic cultural attitude towards wildlife and um are your natural

1593
01:32:54,479 --> 01:32:59,560
Speaker 1: areas in general of this is here for us and

1594
01:33:00,200 --> 01:33:03,599
Speaker 1: we can just take I think that's one extreme end

1595
01:33:03,720 --> 01:33:06,320
Speaker 1: and then there's you know, it can't be touched and

1596
01:33:07,000 --> 01:33:10,240
Speaker 1: let's ignore the fact that that we're predators and have

1597
01:33:10,400 --> 01:33:13,640
Speaker 1: a desire to engage with nature in that way. Um.

1598
01:33:14,600 --> 01:33:16,880
Speaker 1: So if those extremes keep fighting and we keep meaning

1599
01:33:16,920 --> 01:33:19,320
Speaker 1: in the middle, that's you still want to have both

1600
01:33:19,960 --> 01:33:25,960
Speaker 1: both ends, maybe because I feel, um, historically the like

1601
01:33:26,040 --> 01:33:28,960
Speaker 1: when I look at just the historic wildlife, the enemy

1602
01:33:30,200 --> 01:33:35,320
Speaker 1: is uh, the just take right, Like what happened to

1603
01:33:35,439 --> 01:33:38,040
Speaker 1: what happened to American wildlife in the late ag ear

1604
01:33:39,439 --> 01:33:44,880
Speaker 1: was having absolutely no regard for the future, no comprehension

1605
01:33:44,920 --> 01:33:49,920
Speaker 1: of the finiteness of our resources. Further than that Abrahamic

1606
01:33:50,080 --> 01:33:53,160
Speaker 1: you know, like Leopold calls like this Abrahamic concept of

1607
01:33:53,320 --> 01:33:56,840
Speaker 1: land where it somehow everything was like given to your

1608
01:33:57,479 --> 01:33:59,840
Speaker 1: god given right. Yeah, like this you have this like

1609
01:34:00,200 --> 01:34:05,760
Speaker 1: you like this divine right to just destroy and a

1610
01:34:05,880 --> 01:34:13,479
Speaker 1: divine duty to civilize. So that's like the old enemy

1611
01:34:13,680 --> 01:34:17,120
Speaker 1: and that has been largely vanquished in this country. I'm

1612
01:34:17,160 --> 01:34:21,840
Speaker 1: not saying globally, but that attitude has been defeated. Yeah,

1613
01:34:21,880 --> 01:34:23,880
Speaker 1: you know, it's it's rude. Is still there, but but

1614
01:34:24,439 --> 01:34:28,920
Speaker 1: we've arrived at a place where you legally squashed it. Right.

1615
01:34:29,800 --> 01:34:33,080
Speaker 1: The new enemy now, like the new threat now, I feel,

1616
01:34:33,200 --> 01:34:37,320
Speaker 1: is the other side of it, which is the complete

1617
01:34:37,360 --> 01:34:40,720
Speaker 1: dissociation with wildlife. And it's something that we just have

1618
01:34:40,880 --> 01:34:44,600
Speaker 1: to look at out the window of a car and

1619
01:34:44,720 --> 01:34:46,920
Speaker 1: it has nothing to do with our lives anymore. That

1620
01:34:47,040 --> 01:34:49,680
Speaker 1: it's an art, it's a relic of the past, and

1621
01:34:49,760 --> 01:34:55,400
Speaker 1: it's just meant for observation. There's no entanglement. Yeah, I know,

1622
01:34:55,439 --> 01:34:58,000
Speaker 1: what do you think of all? I got a concluding

1623
01:34:58,040 --> 01:35:02,000
Speaker 1: thought just after my bathroom break. You're gonna hit me

1624
01:35:02,080 --> 01:35:08,080
Speaker 1: with that. I'm thinking we need to have Calmon back again,

1625
01:35:08,120 --> 01:35:09,960
Speaker 1: because we took a little break and I got the

1626
01:35:10,040 --> 01:35:13,120
Speaker 1: chatter up about her early hunt experiences and there's a

1627
01:35:13,160 --> 01:35:14,880
Speaker 1: lot to talk about there and we didn't even get

1628
01:35:14,920 --> 01:35:19,640
Speaker 1: to that. Yeah we didn't. How many animals do we

1629
01:35:19,720 --> 01:35:23,240
Speaker 1: miss off? We're just getting started on my resume and

1630
01:35:23,280 --> 01:35:24,720
Speaker 1: I don't even like to know, just like a real

1631
01:35:24,840 --> 01:35:29,600
Speaker 1: quick like how even like how it's done. What the

1632
01:35:30,280 --> 01:35:34,160
Speaker 1: tactic of of traffing wolves? Yeah, when they when they

1633
01:35:34,240 --> 01:35:38,520
Speaker 1: put collars on wolves or catching my foot traps, Ye, paddles,

1634
01:35:38,880 --> 01:35:42,040
Speaker 1: padded jaws, Yeah, put in line springs in them. Um,

1635
01:35:42,920 --> 01:35:45,000
Speaker 1: they're just I mean they're they're no different. They've just

1636
01:35:45,120 --> 01:35:48,600
Speaker 1: got pats. So you look a double coil sprain with

1637
01:35:48,680 --> 01:35:52,479
Speaker 1: pats and then you get one in a trap and

1638
01:35:52,560 --> 01:35:57,479
Speaker 1: you drug it and put a collar on and kind

1639
01:35:57,479 --> 01:36:02,960
Speaker 1: of the standard use urine to lure them, all kinds

1640
01:36:03,000 --> 01:36:09,400
Speaker 1: of stuff, all kinds no, not bait, um, yeah, sin lures.

1641
01:36:10,880 --> 01:36:16,120
Speaker 1: They are so smart and they they they tuned up

1642
01:36:16,160 --> 01:36:20,439
Speaker 1: really fast, and so sink control in the area of

1643
01:36:20,520 --> 01:36:24,200
Speaker 1: your trap is really important. In fact, so the trapper

1644
01:36:24,280 --> 01:36:28,439
Speaker 1: that trapped for this project would have everybody else they're

1645
01:36:28,520 --> 01:36:31,880
Speaker 1: just sitting the back of the truck because you know,

1646
01:36:31,960 --> 01:36:37,160
Speaker 1: I didn't want our foot putt smell around. Um. And

1647
01:36:37,240 --> 01:36:40,479
Speaker 1: then just disguising these traps really well and using different

1648
01:36:41,520 --> 01:36:45,000
Speaker 1: sint lures. And it's not it's not easy because um,

1649
01:36:46,280 --> 01:36:48,920
Speaker 1: they are so smart and the slightest, the little thing

1650
01:36:49,000 --> 01:36:52,240
Speaker 1: wrong is gonna make them skittish. I've had so I've

1651
01:36:52,240 --> 01:36:54,679
Speaker 1: done a lot of trail camera work over the last

1652
01:36:55,200 --> 01:36:58,120
Speaker 1: couple of summers with wolves, and even they're they get

1653
01:36:58,160 --> 01:37:01,000
Speaker 1: wary of those. You know, I have so many videos

1654
01:37:01,040 --> 01:37:04,080
Speaker 1: of them just slinking around my camera. They somehow know

1655
01:37:04,400 --> 01:37:07,240
Speaker 1: that it's there. I've don't like it. They don't like it,

1656
01:37:07,360 --> 01:37:11,760
Speaker 1: and I don't know. I've I've tried, um, putting like

1657
01:37:12,040 --> 01:37:14,960
Speaker 1: fur bowls in my hands and then grabbing the camera

1658
01:37:15,080 --> 01:37:17,639
Speaker 1: with that so I'm not even touching the camera. They've

1659
01:37:17,680 --> 01:37:21,880
Speaker 1: got to and I have. You know, they've got the

1660
01:37:21,960 --> 01:37:24,880
Speaker 1: black light so they supposedly can't see it, and you

1661
01:37:24,960 --> 01:37:27,519
Speaker 1: get pictures of their staring right at it. They know,

1662
01:37:27,680 --> 01:37:30,840
Speaker 1: so they're they're pretty savvy. Yeah, it's a sheen to

1663
01:37:30,960 --> 01:37:35,160
Speaker 1: it or something something or maybe a tiny noise. I

1664
01:37:35,240 --> 01:37:37,960
Speaker 1: don't know. It's hard to figure out. Nice to trap

1665
01:37:38,200 --> 01:37:42,000
Speaker 1: Fox and Kyo would be the UM. All the precautions

1666
01:37:42,040 --> 01:37:44,400
Speaker 1: like you die and why actually traps that storm and

1667
01:37:44,479 --> 01:37:49,040
Speaker 1: boxes full of hay. Only use rubber gloves, clean your

1668
01:37:49,080 --> 01:37:51,559
Speaker 1: rubber gloves any to every time. Only use rubber boots

1669
01:37:51,560 --> 01:37:56,880
Speaker 1: clean every time, disinfect everything and um and then you

1670
01:37:56,920 --> 01:37:58,680
Speaker 1: know when you bed the trap and you cover it,

1671
01:37:59,000 --> 01:38:01,599
Speaker 1: you know, half inch three quarter inches of dirt if

1672
01:38:01,640 --> 01:38:05,800
Speaker 1: that trap had any wobble, and they just it's like,

1673
01:38:05,920 --> 01:38:07,960
Speaker 1: but you're stepping on ship the wobbles all the time.

1674
01:38:08,120 --> 01:38:11,040
Speaker 1: They're walking to the right. But how many times did

1675
01:38:11,080 --> 01:38:15,080
Speaker 1: he place his foot? He places foot thousands of times

1676
01:38:15,120 --> 01:38:17,920
Speaker 1: every day, but like how often is something under just

1677
01:38:18,080 --> 01:38:21,720
Speaker 1: under the soil. It's just different. They're nervous because they're

1678
01:38:21,800 --> 01:38:25,479
Speaker 1: they're nervous because yeah, so you you asked them to

1679
01:38:25,520 --> 01:38:27,599
Speaker 1: come in, and once you pinch one's toe, man, they

1680
01:38:27,680 --> 01:38:30,439
Speaker 1: get very very difficult. You'd even then going like if

1681
01:38:30,439 --> 01:38:31,840
Speaker 1: you had like a dirt hole set or a cent

1682
01:38:31,920 --> 01:38:35,160
Speaker 1: post set, you know, when you got your trap, you know,

1683
01:38:35,360 --> 01:38:39,160
Speaker 1: nine inches back, three inches off center, and then you'd

1684
01:38:39,160 --> 01:38:41,040
Speaker 1: want to bed in a couple of them to three

1685
01:38:41,080 --> 01:38:43,400
Speaker 1: feet back because he's not expecting them to be there,

1686
01:38:43,439 --> 01:38:46,360
Speaker 1: you know. But they it's just like they just there's

1687
01:38:47,479 --> 01:38:50,880
Speaker 1: they're just being so frustrated, just like dread Like when

1688
01:38:50,920 --> 01:38:53,680
Speaker 1: he came out and saw your trap excavated, Like when

1689
01:38:53,680 --> 01:38:56,519
Speaker 1: you dig around the outside jaw and expose the jaw,

1690
01:38:56,680 --> 01:38:59,160
Speaker 1: you're like, I will never catch this thing. Yeah, and

1691
01:38:59,240 --> 01:39:02,000
Speaker 1: he will come and do this every night. That's that's

1692
01:39:02,080 --> 01:39:04,880
Speaker 1: the I think the fun thing about research trapping is

1693
01:39:05,240 --> 01:39:09,639
Speaker 1: there's an added challenge of a you're not always trapping

1694
01:39:09,680 --> 01:39:13,320
Speaker 1: in a place where that animals plentiful. UM. So for example,

1695
01:39:13,400 --> 01:39:15,960
Speaker 1: I first trapped links in Maine where there were many more,

1696
01:39:16,000 --> 01:39:18,960
Speaker 1: and it was it was a lot easier. We call

1697
01:39:19,000 --> 01:39:22,439
Speaker 1: a lot of animals um, although catching females we had

1698
01:39:22,479 --> 01:39:25,000
Speaker 1: to get trickier with because they just it seems like

1699
01:39:25,040 --> 01:39:27,519
Speaker 1: in general across species, a lot of times the females

1700
01:39:27,520 --> 01:39:30,240
Speaker 1: are harder to get and older animals. So if you

1701
01:39:30,320 --> 01:39:33,400
Speaker 1: care about getting a nice slice of the demographic, you know,

1702
01:39:34,000 --> 01:39:39,120
Speaker 1: young adult male female, that that adds the challenge. And

1703
01:39:39,280 --> 01:39:42,599
Speaker 1: then you're trapping somewhere where there aren't many. So trapping

1704
01:39:42,680 --> 01:39:49,439
Speaker 1: links in Washington, Uh, they're threatened here and there's less

1705
01:39:49,479 --> 01:39:54,160
Speaker 1: than fifty probably, and so there's a there's it's a

1706
01:39:54,200 --> 01:39:58,120
Speaker 1: whole winter of trapping. And we caught four. And there's

1707
01:39:58,200 --> 01:40:01,479
Speaker 1: this one female with kittens that we just pulled out

1708
01:40:01,840 --> 01:40:06,880
Speaker 1: every stop for and UM got her into trap once,

1709
01:40:06,960 --> 01:40:08,479
Speaker 1: but she got away before we got there. We're not

1710
01:40:08,560 --> 01:40:11,439
Speaker 1: trying to catch those and leg holds, right, they wouldn't

1711
01:40:11,439 --> 01:40:15,920
Speaker 1: hold up. Probably they can get frost bite. Yeah, so

1712
01:40:16,000 --> 01:40:18,600
Speaker 1: we just used they don't it's just not so it

1713
01:40:18,680 --> 01:40:20,639
Speaker 1: just doesn't seem like a cat's gonna do well enough.

1714
01:40:20,680 --> 01:40:24,200
Speaker 1: Foot trap people use them in the summer, Yeah, yeah,

1715
01:40:24,280 --> 01:40:25,920
Speaker 1: but it's hard to get a permit for that. In

1716
01:40:26,040 --> 01:40:30,880
Speaker 1: Washington for research, she guys using box traps. Box traps'larly

1717
01:40:32,280 --> 01:40:34,800
Speaker 1: trap shy, but they get trap shy about box and

1718
01:40:34,960 --> 01:40:39,120
Speaker 1: that's individual. So um. Some of them would go into

1719
01:40:39,240 --> 01:40:42,120
Speaker 1: traps once they figured out that there was bait in there.

1720
01:40:42,120 --> 01:40:44,840
Speaker 1: They'd go in them every night or so for a while,

1721
01:40:45,360 --> 01:40:48,120
Speaker 1: and then they're like I said, the females though super

1722
01:40:48,200 --> 01:40:50,519
Speaker 1: hard to catch, and this one in particular, I mean

1723
01:40:50,600 --> 01:40:53,880
Speaker 1: we had when we ended up when the time that

1724
01:40:53,960 --> 01:40:56,960
Speaker 1: we did catch her. This is a story that still

1725
01:40:57,040 --> 01:41:00,479
Speaker 1: makes me sick to my stomach because it was so frustrating.

1726
01:41:00,479 --> 01:41:07,360
Speaker 1: We've been targeting her the entire winner, and we'd extended

1727
01:41:07,400 --> 01:41:10,240
Speaker 1: our season because we wanted to get her so bad

1728
01:41:11,760 --> 01:41:14,519
Speaker 1: and on the last day we were out closing our

1729
01:41:14,600 --> 01:41:17,960
Speaker 1: traps and we pull up to this trap who was

1730
01:41:18,000 --> 01:41:20,680
Speaker 1: a We started setting double traps, so we'd have one

1731
01:41:20,800 --> 01:41:25,800
Speaker 1: box trap backed up to another one. We'd cover all

1732
01:41:25,960 --> 01:41:29,679
Speaker 1: sides of it with bows so that if a kitten

1733
01:41:30,479 --> 01:41:33,920
Speaker 1: or one of the links went in one trap, the

1734
01:41:34,040 --> 01:41:38,599
Speaker 1: only way for the kitten's mom or or figure out

1735
01:41:38,600 --> 01:41:40,720
Speaker 1: what's going on, yeah, to get too closer to that

1736
01:41:41,360 --> 01:41:43,240
Speaker 1: to be going the other trap. So we had a

1737
01:41:43,320 --> 01:41:47,080
Speaker 1: double trap set, and we had we'd done away with

1738
01:41:47,160 --> 01:41:53,000
Speaker 1: our whole treadle season or our treadle um trigger system,

1739
01:41:53,720 --> 01:41:58,599
Speaker 1: so we had fishing line. We explained what a treadle.

1740
01:41:59,160 --> 01:42:01,120
Speaker 1: You step on this stick and it triggers the trap

1741
01:42:01,320 --> 01:42:03,280
Speaker 1: you step on, you step step on. It's like a

1742
01:42:03,360 --> 01:42:06,240
Speaker 1: lot a lot of dead fall traps that way, because

1743
01:42:06,240 --> 01:42:08,640
Speaker 1: it's just a trigger system where when it enters, it

1744
01:42:08,720 --> 01:42:12,200
Speaker 1: puts its foot on a basic a like a like

1745
01:42:12,280 --> 01:42:15,360
Speaker 1: a stick, like an inch or two off the ground, right, Yeah,

1746
01:42:15,479 --> 01:42:19,640
Speaker 1: So this was so basically are trap sets were this

1747
01:42:19,840 --> 01:42:24,160
Speaker 1: box trap. You cover the sides with bows so that

1748
01:42:24,320 --> 01:42:28,280
Speaker 1: it's it's a tunnel through and you've got visuals out

1749
01:42:28,320 --> 01:42:29,679
Speaker 1: in front of it. You're trying to get the links

1750
01:42:29,720 --> 01:42:31,640
Speaker 1: in the area. And then you've got bait in the

1751
01:42:31,720 --> 01:42:34,200
Speaker 1: back of the trap, and your hope is that they

1752
01:42:34,240 --> 01:42:38,880
Speaker 1: will feel comfortable enough to walk into the trap to

1753
01:42:38,960 --> 01:42:41,759
Speaker 1: get to the bait, and they'll step on this little

1754
01:42:42,280 --> 01:42:44,639
Speaker 1: paddle that you've done your best to disguise with snow

1755
01:42:44,720 --> 01:42:47,320
Speaker 1: and whatever, and they step on that and that triggers

1756
01:42:47,360 --> 01:42:49,639
Speaker 1: the door. The door falls down reb like Ben Benion's

1757
01:42:50,000 --> 01:42:54,000
Speaker 1: hog traps. Yeah, yeah, where they bumped the wire. Picture

1758
01:42:54,080 --> 01:42:56,960
Speaker 1: that you had anything even like a piece of ply

1759
01:42:57,040 --> 01:43:01,120
Speaker 1: would elevated. Where you put weight on that apply would yeah,

1760
01:43:01,200 --> 01:43:03,880
Speaker 1: tips forward and the dogs. So it's kind of like

1761
01:43:04,000 --> 01:43:06,080
Speaker 1: a like I have a heart trap, but these were

1762
01:43:06,320 --> 01:43:09,320
Speaker 1: homemade and bigger. What kind of weight? Uh, what does

1763
01:43:09,360 --> 01:43:11,479
Speaker 1: it take trigger that trap? You tried to just have

1764
01:43:11,600 --> 01:43:15,519
Speaker 1: him on a hair but it was just weird enough

1765
01:43:15,640 --> 01:43:18,880
Speaker 1: that it was and they'd get bugged up with ice

1766
01:43:18,960 --> 01:43:22,840
Speaker 1: and whatever. So they weren't working well enough that we

1767
01:43:22,920 --> 01:43:25,880
Speaker 1: were catching cats and they were wary of them. So

1768
01:43:26,120 --> 01:43:28,920
Speaker 1: what we did was we took those out and we

1769
01:43:29,080 --> 01:43:31,840
Speaker 1: took um fishing line and we drung it kind of

1770
01:43:32,680 --> 01:43:35,880
Speaker 1: towards the back in a sort of a like a

1771
01:43:36,000 --> 01:43:40,120
Speaker 1: zi these shape, So it came from one side to

1772
01:43:40,280 --> 01:43:44,120
Speaker 1: the other and looped back and then went out the

1773
01:43:44,200 --> 01:43:48,840
Speaker 1: top of the trap. Then we had a a mouse

1774
01:43:48,920 --> 01:43:53,640
Speaker 1: trap mounted on the top of the trap and um

1775
01:43:54,040 --> 01:43:56,800
Speaker 1: that would throw the trigger. They would throw the gate. Yeah,

1776
01:43:56,880 --> 01:43:59,920
Speaker 1: So the fishing line was um tied to the little

1777
01:44:00,040 --> 01:44:03,960
Speaker 1: fake cheese thing, and then we had the door was

1778
01:44:04,040 --> 01:44:06,240
Speaker 1: on a on a little piece of rope and you

1779
01:44:06,400 --> 01:44:13,599
Speaker 1: loop that over the the um the lowell thing, yeah,

1780
01:44:13,680 --> 01:44:17,640
Speaker 1: the bail, so that when the cheese got pulled on

1781
01:44:18,240 --> 01:44:21,560
Speaker 1: even slightly we had birds tripping these things. When it

1782
01:44:21,760 --> 01:44:25,840
Speaker 1: got pulled on even slightly by an animal in the trap,

1783
01:44:26,080 --> 01:44:29,479
Speaker 1: the door would close. So anyway, so we've gone through

1784
01:44:30,000 --> 01:44:33,360
Speaker 1: all this. It's our last day. We're closing traps, and

1785
01:44:33,520 --> 01:44:36,000
Speaker 1: we pull up to the trap and the doors are

1786
01:44:36,640 --> 01:44:40,400
Speaker 1: closed because it's a double trap. We leap off our

1787
01:44:40,439 --> 01:44:45,920
Speaker 1: snowmobiles and the trap is empty, and we could tell

1788
01:44:46,000 --> 01:44:49,920
Speaker 1: from the tracks what had happened was one either the

1789
01:44:49,960 --> 01:44:53,200
Speaker 1: mom or the kitten, had gone in the trap, and

1790
01:44:53,320 --> 01:44:57,760
Speaker 1: the other had obviously been upset about this and was was, um,

1791
01:44:59,120 --> 01:45:00,680
Speaker 1: you know, trying to get at it. And we even

1792
01:45:00,720 --> 01:45:02,400
Speaker 1: sat on top of it and all this stuff. But

1793
01:45:02,520 --> 01:45:04,439
Speaker 1: before it got desperate enough to go into the other

1794
01:45:04,560 --> 01:45:06,720
Speaker 1: trap and we would maybe even have both of them,

1795
01:45:07,720 --> 01:45:10,240
Speaker 1: a little bit of snow build up at the bottom

1796
01:45:10,280 --> 01:45:13,400
Speaker 1: of the door created a tiny gap in the between

1797
01:45:13,479 --> 01:45:15,479
Speaker 1: the door and the top of the trap, and that

1798
01:45:15,640 --> 01:45:21,680
Speaker 1: length squeezed out of there, so we missed. We never

1799
01:45:21,760 --> 01:45:26,080
Speaker 1: caught that female. We came so close but never caught her.

1800
01:45:26,240 --> 01:45:30,240
Speaker 1: So anyway, the point of all that is when you

1801
01:45:30,400 --> 01:45:33,280
Speaker 1: have to catch certain individuals, you don't just get to

1802
01:45:33,320 --> 01:45:37,720
Speaker 1: move on. It makes you get creative and get it's fun.

1803
01:45:38,080 --> 01:45:41,559
Speaker 1: Even with beaver trapping, sometimes there's just that last female

1804
01:45:41,600 --> 01:45:43,960
Speaker 1: that you really want to get out of there because

1805
01:45:43,960 --> 01:45:45,800
Speaker 1: you want the whole family group or whatever, and you

1806
01:45:45,920 --> 01:45:49,559
Speaker 1: just even that could be super tricky. So you found

1807
01:45:49,600 --> 01:45:52,240
Speaker 1: that the females are harder to get the males like,

1808
01:45:52,360 --> 01:45:56,880
Speaker 1: as a generalization, Yeah, yeah, I think just they're less,

1809
01:45:57,640 --> 01:46:02,599
Speaker 1: less risky, more wary. A lot that I'd say in general,

1810
01:46:02,720 --> 01:46:09,080
Speaker 1: the easiest is young males and experienced young males because

1811
01:46:09,120 --> 01:46:15,280
Speaker 1: oftentimes they're finding themselves in strange areas to the more aggressive.

1812
01:46:17,200 --> 01:46:18,840
Speaker 1: All right, man, we're gonna have to have you back

1813
01:46:18,880 --> 01:46:21,599
Speaker 1: on and talk more about all this knocky deer concluding

1814
01:46:21,640 --> 01:46:25,880
Speaker 1: thought yunning. Lots of similarities there between the animal kingdom

1815
01:46:26,000 --> 01:46:29,799
Speaker 1: and in us. You know, the young males get in trouble.

1816
01:46:30,520 --> 01:46:35,360
Speaker 1: Jared Diamond talks about Jared the you know, the physiologists

1817
01:46:35,600 --> 01:46:40,040
Speaker 1: and among many other things. Jared Diamond talks about why

1818
01:46:40,320 --> 01:46:45,679
Speaker 1: reckless behavior in males like how that would become selected

1819
01:46:45,760 --> 01:46:50,840
Speaker 1: for in sexual selection, like why would why would you

1820
01:46:50,920 --> 01:46:55,120
Speaker 1: know the propensity to do like ridiculous crazy ship that

1821
01:46:55,280 --> 01:46:58,880
Speaker 1: will get you hurt? Wi is there? And why is

1822
01:46:58,880 --> 01:47:02,400
Speaker 1: there an advantage there? And he thinks it's like getting

1823
01:47:02,439 --> 01:47:05,839
Speaker 1: really ship faced drunk? Why is there? Why is that advanced?

1824
01:47:05,880 --> 01:47:09,360
Speaker 1: Why is that selected for? And he he talks about,

1825
01:47:09,479 --> 01:47:11,120
Speaker 1: I can't here if he was given this idea of

1826
01:47:11,200 --> 01:47:14,920
Speaker 1: his own or given a summation of someone else's theory,

1827
01:47:15,040 --> 01:47:19,599
Speaker 1: But it was that it's a demonstration of fitness because

1828
01:47:19,680 --> 01:47:24,360
Speaker 1: you're basically saying like I'm so fit, I'm so fit

1829
01:47:25,000 --> 01:47:28,640
Speaker 1: that I can afford to do these very risky behaviors

1830
01:47:30,400 --> 01:47:35,640
Speaker 1: and that has over time had like a sexual advantage

1831
01:47:36,439 --> 01:47:40,440
Speaker 1: and attracting females that you're like, now there's a specimen.

1832
01:47:41,080 --> 01:47:50,040
Speaker 1: He can get that drunk. It'll still be okay because

1833
01:47:50,040 --> 01:47:53,719
Speaker 1: there is something about it. You know why? It wasn't

1834
01:47:53,800 --> 01:47:57,800
Speaker 1: just that sexual selection and adapted advantages wouldn't just make

1835
01:47:57,840 --> 01:48:01,280
Speaker 1: you real timid people won't, you know? They don't want that.

1836
01:48:02,680 --> 01:48:04,920
Speaker 1: They want that bull out that just comes screaming in

1837
01:48:05,160 --> 01:48:08,120
Speaker 1: thrash and brush read it up. The guy hiding out

1838
01:48:08,160 --> 01:48:11,479
Speaker 1: in the black timber. He doesn't he's not getting anywhere. Um,

1839
01:48:12,680 --> 01:48:16,920
Speaker 1: all right, is that your concluding dot? No? Um, I

1840
01:48:17,000 --> 01:48:19,519
Speaker 1: guess thanks for coming on. And I'm so stoked that

1841
01:48:19,560 --> 01:48:23,200
Speaker 1: we have people like Carmen out there doing the good

1842
01:48:23,240 --> 01:48:26,240
Speaker 1: work and getting this research done. And and now that

1843
01:48:26,280 --> 01:48:29,400
Speaker 1: you're a hunter, it's even better, you know. I don't know.

1844
01:48:29,439 --> 01:48:32,400
Speaker 1: We were talking about it off while we weren't recording,

1845
01:48:32,479 --> 01:48:39,600
Speaker 1: but just getting somehow keeping science, um, you know, like

1846
01:48:40,000 --> 01:48:42,720
Speaker 1: in the forefront, to keep you know, people making decisions

1847
01:48:42,800 --> 01:48:45,800
Speaker 1: and not getting you know, the politics involved too much.

1848
01:48:45,920 --> 01:48:51,160
Speaker 1: And um, yeah, I just hope we have more people

1849
01:48:51,200 --> 01:48:54,519
Speaker 1: like Carmen out there doing wildlife research and helping us,

1850
01:48:54,760 --> 01:48:58,000
Speaker 1: help the rest of us make this informed decisions. Yeah,

1851
01:48:58,360 --> 01:49:02,880
Speaker 1: just find out about stuff. Yeah, keep learning. I don't

1852
01:49:02,880 --> 01:49:04,760
Speaker 1: know anything thought. What are your concluding thoughts? Do you

1853
01:49:04,800 --> 01:49:07,160
Speaker 1: had any anything you want to you want to try

1854
01:49:07,240 --> 01:49:12,720
Speaker 1: to get the job or anything, or I would just

1855
01:49:13,360 --> 01:49:16,920
Speaker 1: you don't have anything to gain from this. You're not

1856
01:49:17,040 --> 01:49:20,439
Speaker 1: selling anything? Are you selling it? You know, like you

1857
01:49:20,439 --> 01:49:25,680
Speaker 1: don't have like a T shirt company or anything. I mean,

1858
01:49:25,760 --> 01:49:29,639
Speaker 1: as scientists, I think is important to try and reach

1859
01:49:29,720 --> 01:49:32,920
Speaker 1: a wider audience. You know, you know, we had a

1860
01:49:33,000 --> 01:49:35,479
Speaker 1: long discussion about that. Last we had a researcher on

1861
01:49:36,200 --> 01:49:41,400
Speaker 1: who is a m the sociology research, and we had

1862
01:49:41,400 --> 01:49:45,880
Speaker 1: a long discussion about um what I see as my

1863
01:49:46,000 --> 01:49:50,880
Speaker 1: need for scientists too. As painful as it is for

1864
01:49:51,000 --> 01:49:54,960
Speaker 1: them to translate their work for a popular audience, but

1865
01:49:55,040 --> 01:49:57,800
Speaker 1: a lot of them, it's just a very uncomfortable It's

1866
01:49:57,840 --> 01:50:00,479
Speaker 1: super place to go in because you live in a

1867
01:50:00,560 --> 01:50:05,559
Speaker 1: world of caveats and reservations and not wanting to make

1868
01:50:05,680 --> 01:50:09,559
Speaker 1: generalizations and not wanting to oversimplify things. And you enter

1869
01:50:09,640 --> 01:50:12,479
Speaker 1: into a world where people like, so, what's it all mean? Yeah,

1870
01:50:12,840 --> 01:50:15,880
Speaker 1: and you're like, that's not my job. I don't tell you.

1871
01:50:15,920 --> 01:50:17,519
Speaker 1: I'm not here to tell you what to think about it,

1872
01:50:18,439 --> 01:50:20,479
Speaker 1: to tell you what's there. I can tell you what's

1873
01:50:20,479 --> 01:50:23,559
Speaker 1: going on, but I'm not going to translate it for you. Yeah. Yeah,

1874
01:50:23,680 --> 01:50:26,560
Speaker 1: but scientists need to be able to do that effectively,

1875
01:50:27,120 --> 01:50:29,919
Speaker 1: you know, so that their work isn't just being circulated

1876
01:50:29,960 --> 01:50:32,240
Speaker 1: among other scientists. That's the only I talked about too,

1877
01:50:32,360 --> 01:50:34,760
Speaker 1: is like someone's going to translate it. Why not be

1878
01:50:34,840 --> 01:50:37,479
Speaker 1: in the driver's seat. Why let some Why let some

1879
01:50:37,760 --> 01:50:41,040
Speaker 1: you know, Penny, any journalists read your paper and take

1880
01:50:41,080 --> 01:50:42,479
Speaker 1: a stab at it when you can a little bit

1881
01:50:42,479 --> 01:50:45,679
Speaker 1: try to guide it by getting out there with your messaging.

1882
01:50:45,880 --> 01:50:47,760
Speaker 1: Of course, people can abuse it, and you wind up

1883
01:50:47,800 --> 01:50:51,000
Speaker 1: having scientists who get accused of grandstanding, where everything they

1884
01:50:51,040 --> 01:50:53,439
Speaker 1: do is meant to be outward facing, and they lose

1885
01:50:53,479 --> 01:50:56,960
Speaker 1: their credibility. But I think that yeah, to uh, to

1886
01:50:57,240 --> 01:51:00,280
Speaker 1: enter that uncomfortable space of coming in and to aching

1887
01:51:00,360 --> 01:51:03,360
Speaker 1: something that's like really complicated and you're trying not to

1888
01:51:03,479 --> 01:51:06,160
Speaker 1: make to read into it too much, and you're trying

1889
01:51:06,200 --> 01:51:10,479
Speaker 1: not to be suayed by policy and personal opinion, and

1890
01:51:10,560 --> 01:51:13,479
Speaker 1: then explain to people like, here's what's going on out there.

1891
01:51:14,520 --> 01:51:16,880
Speaker 1: It's tough to distill it down because you can always

1892
01:51:16,920 --> 01:51:20,439
Speaker 1: imagine your colleagues listening and jumping on you. Yeah. Yeah,

1893
01:51:20,640 --> 01:51:22,680
Speaker 1: I mean it's it's definitely a skill. I mean, it

1894
01:51:22,800 --> 01:51:28,000
Speaker 1: was taught in classes that I've taken. You talk about it, oh, definitely.

1895
01:51:28,200 --> 01:51:30,840
Speaker 1: I mean a lot of scientists know, Okay, we've got

1896
01:51:30,920 --> 01:51:34,840
Speaker 1: this problem. We need to figure out how to teach

1897
01:51:34,920 --> 01:51:38,480
Speaker 1: people what we have found in a way that's understandable

1898
01:51:38,840 --> 01:51:42,880
Speaker 1: and yet still accurate and true to what we've found,

1899
01:51:42,960 --> 01:51:45,600
Speaker 1: you know, because it's a balance between making it understandable

1900
01:51:46,920 --> 01:51:51,920
Speaker 1: and also not missing important points of your research or

1901
01:51:52,040 --> 01:51:56,720
Speaker 1: simplifying it too. Whatever. My one of my brothers, you know,

1902
01:51:56,800 --> 01:52:00,599
Speaker 1: he's a researcher, and part of the is it's kind

1903
01:52:00,600 --> 01:52:03,880
Speaker 1: of built into his it's sort of built into his

1904
01:52:04,000 --> 01:52:08,439
Speaker 1: job description and some amount of public facing, some amount

1905
01:52:08,479 --> 01:52:12,280
Speaker 1: of public facing work. Yeah, it's a skill. You don't

1906
01:52:12,320 --> 01:52:15,080
Speaker 1: have a great scientist who gives a talk and nobody

1907
01:52:15,160 --> 01:52:18,519
Speaker 1: can understand or follow it, and so that's that doesn't

1908
01:52:18,520 --> 01:52:22,519
Speaker 1: work either, you know, just as much as oversimplifying it

1909
01:52:22,920 --> 01:52:28,320
Speaker 1: or you know, not explaining enough, it doesn't work. So yeah,

1910
01:52:28,520 --> 01:52:30,320
Speaker 1: it's a skill. Yeah, it's a lot easier just to

1911
01:52:30,439 --> 01:52:32,880
Speaker 1: have every answer be I don't know, it's complicated, Yeah,

1912
01:52:34,680 --> 01:52:37,320
Speaker 1: too complicated. I can't explain. Yeah, all right, well thanks

1913
01:52:37,320 --> 01:52:40,120
Speaker 1: to we have to yeah you have to come back on. Yeah, definitely,

1914
01:52:43,200 --> 01:52:43,479
Speaker 1: thank you.