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

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

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Speaker 1: can't predict anything presented by first light. Go farther, stay longer, now,

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Speaker 1: pat dir our. Coyotes really killing eating all the deer?

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Speaker 1: Is it as bad as everyone thinks? No, it's not

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Speaker 1: as bad as their bay thinks. Um, why does everyone

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Speaker 1: think it's so bad? Is it more fun to think

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Speaker 1: about coyotes killing deer than other ship killing deer? Yeah?

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Speaker 1: I don't know what it is, but there's something about

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Speaker 1: coyotes and something about wolves that really gets under hunters

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Speaker 1: skin that you know you can you can show them research.

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Speaker 1: It shows like in Wisconsin, and only Wisconsin. About five

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Speaker 1: years ago they wrapped this research and the number one

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Speaker 1: killer of aawns you know, yet one fawns that basically

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Speaker 1: hit the ground in the first three weeks of life

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Speaker 1: are picked off. Go ahead, black bears, exactly exactly. It's

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Speaker 1: anywhere from ten of those fawns are being picked off

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Speaker 1: by black bears, and a few guys will complain about it,

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Speaker 1: but for the most part, they'll always default to the coyote.

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Speaker 1: And you look at the numbers on this particular study,

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Speaker 1: and that's probably a pretty representative study because they have

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Speaker 1: all the major predators in this area. It was six

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Speaker 1: percent of the kills were definitely tied to coyotes six

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Speaker 1: and black bears. Oh, they had at least ten percent,

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Speaker 1: but it's more likely close because as soon as you

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Speaker 1: got about a month out of the finding season, because

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Speaker 1: you know, part of that is he's unknown, they weren't

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Speaker 1: quite sure what got it because everything is basically cleaned up, gone.

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Speaker 1: And but as soon as they got out of that

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Speaker 1: the first month, this is typically when the black bears

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Speaker 1: are hitting them. That just dropped right off. Those unidentifies

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Speaker 1: dropped right off because they can get him up until

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Speaker 1: they're able to get up. Yeah, because the black bears,

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Speaker 1: they probably gonna run very far to chased on a

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Speaker 1: fun and once that phone gets moldering, you know, they

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Speaker 1: let it go. Now, have you ever killed a coyote?

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Speaker 1: Class I like, I'm guessing. I guess is no, because

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Speaker 1: you call him coyotes. I could be here and I

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Speaker 1: found in general, I've found that people who have killed

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Speaker 1: him call him coyotes. Well mine, because I think they

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Speaker 1: don't want it to sound so cute. And people that

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Speaker 1: have not tend to call him coyotes. I called I'm

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Speaker 1: more I guess I'm more formal, you know if but

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Speaker 1: you might. But historian was telling me that I might

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Speaker 1: be right about that about killing him. No, no, no,

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Speaker 1: no he didn't. He didn't. He wasn't interest in that

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Speaker 1: theory at all. But he didn't. He didn't think that

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Speaker 1: was right just to history of calling him coylets and coyotes. Yeah, well,

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Speaker 1: to answer your question, though, I shot one with the

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Speaker 1: bow and arrow, I shot one with the shotgun and

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Speaker 1: didn't get either of them. Both got away from me. Yeah,

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Speaker 1: we're wounding loss basically. Now, why um, why were you

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Speaker 1: shooting at him? That's a good question this man man

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Speaker 1: dislikes well and in both cases is you know, it's

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Speaker 1: it's one of those odd things that I can't really explain.

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Speaker 1: I would never do that to a fox a kyote.

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Speaker 1: I let their all go and I pulled the trigger

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Speaker 1: on the shotgun. And my daughter was with me when

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Speaker 1: I shot the one with the shotgun. Were turkey hunting,

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Speaker 1: and she asked for why did you do that? I

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Speaker 1: couldn't give her a good answer. Control have I have

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Speaker 1: no illusion about that? Yeah, see, I don't. I don't

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Speaker 1: generally like UM I have and the last one I

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Speaker 1: shot at we eight, but I don't shoot at him.

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Speaker 1: The first time I ever came to meet dog during

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Speaker 1: here and we're in and right here and what dirt

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Speaker 1: myth calls Casanova, Wisconsin actually miles south of Casinova, Wisconsin.

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Speaker 1: First time I ever came to visit, I got scolded

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Speaker 1: by Doug because some coyotes come peel them through. I

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Speaker 1: was on We're doing a mooch a drive and some

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Speaker 1: coyotes peeled through and Doug was a little shocked that

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Speaker 1: didn't take a poke at him. I do remember that,

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Speaker 1: and I and your reason for not doing it was

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Speaker 1: not something oh they're just trying to make a living too,

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Speaker 1: or something. I don't know if you were coming right.

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Speaker 1: I don't want to go make and I don't want

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Speaker 1: to go blouching and have the yeah you know, but no,

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Speaker 1: I don't have but but but I have. I don't

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Speaker 1: touch him anymore. I'm kind of the same if I'm

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Speaker 1: kind of interesting, and I know that there are plenty

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Speaker 1: of guys that are hunting him. And then I've listened

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Speaker 1: to uh you talking with Dan Flores and uh and

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Speaker 1: looked into that a little bit more of myself, and

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Speaker 1: it sounds like you shoot them and they're just you

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Speaker 1: shoot one that is being replaced by two. Yeah, that's

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Speaker 1: not even why I don't do my thing about is

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Speaker 1: I just don't like if I if I wanted, if

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Speaker 1: I had need for a kyo hide, right like, if

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Speaker 1: I was gonna if I had some, if my wife

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Speaker 1: wanted something, or I was gonna make something for myself,

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Speaker 1: I would definitely in the winter get a nice one

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Speaker 1: for to use the pelt if I needed to, may

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Speaker 1: have something made. But it's like, I just you know, what,

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Speaker 1: do you walk over there and I eight one. I

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Speaker 1: can tell you they're not like I'm not gonna get

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Speaker 1: them for that reason, so you walk over and like,

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Speaker 1: oh there he is, Yep, got them? Ye. I mean

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Speaker 1: I just like I don't. I don't think you're like

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Speaker 1: really turning the tide on um unless you're like doing

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Speaker 1: it in a very concerted way, like in a very systematic,

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Speaker 1: concerted way. I don't think you're like turning the tide

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Speaker 1: on predation by like randomly now and then you'll never

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Speaker 1: make a dent in him with a rifle, you know,

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Speaker 1: just like like just through right. You can go out

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Speaker 1: and call them, go afterm the gristly as you want.

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Speaker 1: He's saying. You're saying actively from doing. Like Doug has

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Speaker 1: a scrap pile here in the woods where he dumps

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Speaker 1: bones and stuff. You could probably put those all the

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Speaker 1: place and POLLINGDVI couty that comes in and it's still

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Speaker 1: that's not gonna make it make a dent. The guys

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Speaker 1: that are really serious about coyote control, and for deer

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Speaker 1: management reasons, they pretty much are trappers. They're they're getting

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Speaker 1: out there in the spring anton they can get them especially,

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Speaker 1: but spring is a really good time to get him,

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Speaker 1: I guess. And they'll build those trapped the ship coyotes.

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Speaker 1: And then the guy said, as soon as you lay

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Speaker 1: off and come back and call the months, it's like

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Speaker 1: you never did, It's like you never trapped. Yeah, they

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Speaker 1: replace themselves. It's just a guy I know named Creig Harper,

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Speaker 1: Professor dont Tennessee. He he always refers to as weak

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Speaker 1: control trying to pull weeds. You can go out in

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Speaker 1: the garden, pull weeds, pull weeds, get that garden cleaned out,

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Speaker 1: and if you leave it alone for a week, come

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Speaker 1: back it's right back everything up again. And that's pretty

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Speaker 1: much the way coyotes are. You know what, someone here's

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Speaker 1: why I want to get the well, we'll talk about

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Speaker 1: this that we're done talking about now. I saw a

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Speaker 1: new guy who was talking about why you know, and

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Speaker 1: we're in the Midwest time my white tails right now.

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Speaker 1: But with him I was about elk in the west.

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Speaker 1: Why are people pissed about wolves when they know that

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Speaker 1: lions kill more elk calves than wolves? Okay, in the

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Speaker 1: area they were where they were doing work, he said,

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Speaker 1: because lions have always been killing elk calves out here,

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Speaker 1: and we've always had a sense that for every hundred calves, right,

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Speaker 1: we're gonna lose thirty two lions. And that's just been

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Speaker 1: something that's just been woven into the cultural fabric. Right

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Speaker 1: when you're on the woods, you get this sense of

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Speaker 1: seven out of ten cows, right, is packing a calf right,

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Speaker 1: And we kind of know that that's like the rate

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Speaker 1: and our harvest statistics are built around that, right. We

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Speaker 1: just get used to that. But then you have some

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Speaker 1: new additive thing which makes a noticeable change from what

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Speaker 1: you've seen in your lifetime and your father's lifetime. And

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Speaker 1: it's additive, and you focus on that, so you're not

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Speaker 1: focusing on the three out of ten, let's say the

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Speaker 1: three out of ten that lions are killing. You're kind

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Speaker 1: of fixated on the one out of ten or two

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Speaker 1: out of ten, the new things killing, because that's this

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Speaker 1: new thing you need to deal with, and so a

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Speaker 1: lot of blame falls to it. And because kyotes, like

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Speaker 1: in my own lifetime, have come onto the scene in

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Speaker 1: so many states. Like the first cow I ever laid

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Speaker 1: eyes on in my whole life, I didn't even know

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Speaker 1: there were any around at the time, and I caught

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Speaker 1: it in a fox trap. Mhm. Now it's like the

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Speaker 1: fox are gone in that area. It's just coyotes. It's

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Speaker 1: like an everyday thing. If you're like, if you hunt

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Speaker 1: around there, it's an everyday thing to see kyotes and

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Speaker 1: they weren't on around. So then you have like some mortality, right,

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Speaker 1: and all these other causes of mortality have always been around,

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Speaker 1: but no always like this new kid on the block thing,

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Speaker 1: And it does get a lot of attention. Yeah, I

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Speaker 1: can buy that because I know in Wisconsin again and

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Speaker 1: that's my base, people got mapped me when I point

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Speaker 1: this up up and I first started working in this

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Speaker 1: industry in the newspapers back in the eighties. There was

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Speaker 1: no really weren't any wolves to speak of in Noulding, Wisconsin.

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Speaker 1: There's a handful of them. It's just like mid eighties.

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Speaker 1: And I've been covering the outdoors in Wisconsin all that time.

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Speaker 1: I've never I've done other things along the way, but

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Speaker 1: pretty much my beach Wisconsin. And I always remember, back

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Speaker 1: in the eighties, you go to a public hering, grow up,

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Speaker 1: public meeting up about deer, and people north have always

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Speaker 1: complained about not enough deer up north. And back then

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Speaker 1: they always played the Chippawa, the Chippawa Indian tribes. They

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Speaker 1: always because they were on a treaty that allowed them

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Speaker 1: they could hunt off off their reservation territory. So they

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Speaker 1: you were blamed. They weren't registering their deer, they weren't

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Speaker 1: doing this, all sorts of accusations. Well then the wolf

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Speaker 1: builds up in the nineties and hunting back then, right,

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Speaker 1: probably so, but a couple of times, and I'm not

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Speaker 1: I'm not doing it just to be a jerk, but

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Speaker 1: I'm pointing out to people that you know, thirty years ago,

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Speaker 1: you guys always blamed the Chippewa for no deer. Well,

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Speaker 1: now the wolves are up there. Now it's the wolves fault,

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Speaker 1: you know, So that you're letting the Indians off the hook. Now,

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Speaker 1: I guess they weren't just a big problem after all.

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Speaker 1: But then I think my area where I hunting, Billion,

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Speaker 1: Wisconsin is a prime example. You go up there, and

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Speaker 1: the biggest problem with any animal basically is always their habitat.

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Speaker 1: And where I hunt in Milling, Wisconsin is pretty much

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Speaker 1: mature timber. There's not much in there for deer to

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Speaker 1: really live off of. And so I go up there,

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Speaker 1: and I have my common jolker around our camp is

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Speaker 1: that that habitat so pour around us. Even the wolves

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Speaker 1: don't hunt deer there because there's just nothing there the

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Speaker 1: whole deer. And I'm not I don't think, you know,

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Speaker 1: has always been bad. Well, in my in my friends

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Speaker 1: camp back in the fifties when his dad was there

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Speaker 1: with his buddies and forties, was a pretty good, pretty

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Speaker 1: good place, and the forest hadn't been cut over that

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Speaker 1: long before that. And then by the sixties and this

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Speaker 1: guy's uh, he keeps camp journals like he makes. When

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Speaker 1: you got at his camp, you got right in his

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Speaker 1: journal before you leave, and he keeps track of every

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Speaker 1: deer killed that basically back into the sixties, and his

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Speaker 1: area pretty much has been bad, you know for a

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Speaker 1: long time. Yeah, pretty much, you know, since since I'd

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Speaker 1: say the seventies for sure. But um, the thing is

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Speaker 1: too though, I look, I balanced that out somewhat because

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Speaker 1: his friends are mainly bird hunters. They deer hunt, but

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Speaker 1: they're mainly bird hunters until guys like I came along

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Speaker 1: in the late nineties early two thousand's where you really

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Speaker 1: go out and to sit all day and hunt deer

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Speaker 1: the way you know, you almost have to, didn't kill

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Speaker 1: a whole lot, dear, So I'm not sure how represented

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Speaker 1: that is. But then now I've talked to other guys

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Speaker 1: in the area, and that area we happen to hunt

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Speaker 1: has always been a tough spot because it's sloss pruce,

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Speaker 1: which deer don't really make much use of. So's it's

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Speaker 1: I don't think I saw that in common. But then

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Speaker 1: there's our parts in the north you go into and

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Speaker 1: the aspens getting real mature. The gross aren't all that

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Speaker 1: you know, basically, as you know, grass rough gross and

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Speaker 1: deer if they're doing fine. Usually they have good, good

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Speaker 1: young forest regeneration going on. And if you don't have

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Speaker 1: that those young aspens coming up well, especially in the

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Speaker 1: area that yeah, and then then that's northern forest habitat.

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Speaker 1: You have to have that young growth, you know. But

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Speaker 1: then you get down this area too, you can make

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Speaker 1: up for a lot of the shortcomings of that natural

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Speaker 1: habitat with crops and our stuff that can pull them through.

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Speaker 1: But there's even research now in Wisconsins showing that they're

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Speaker 1: even getting winter loss in central Wisconsin, which is farm country,

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Speaker 1: because the woods have been so over browsed and there's

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Speaker 1: really nothing left in there, and you have clean farming

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Speaker 1: practices with nothing left in the fields, have no place

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Speaker 1: to hide, no place to eat basically, And then that's

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Speaker 1: another you're seeing winter starvation in this eastern part of Wisconsin,

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Speaker 1: so I mean central east, central Wisconsin, Central Wisconsin, and

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Speaker 1: even parts of west central Wisconsin's seen some winter loss now,

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Speaker 1: which is never something that they're worried about, you know,

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Speaker 1: twenty years ago, No, Doug, do you practice clean farm?

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Speaker 1: Are you part of the problem part of the solution.

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Speaker 1: I would say that I'm part of the solution for

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Speaker 1: two reasons. One because of our forestry practices and we've

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Speaker 1: got you know, various age classes of of woods. But

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Speaker 1: then our eggland is in CRP and though that's those

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Speaker 1: CRP fields are planted to um clover, alfelf orchard grass,

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Speaker 1: and then some of the edges have additional clover and

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Speaker 1: that sort of thing. So that's great cover for not

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Speaker 1: just deer, but for everything because you can solve because

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Speaker 1: you guys have in this area the deer overpopulation problem,

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Speaker 1: by some definitions, absolutely the lead. The definition in your mind,

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Speaker 1: just to put words in your mouth, the definition in

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Speaker 1: your mind would be that you guys, maybe, um, it

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Speaker 1: may be like like disease transmission issues, there's enough deer

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Speaker 1: where you could have disease transmission issues without getting into

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Speaker 1: all that too much. What I was going to suggest,

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Speaker 1: if you're serious about reducing the deer population, you can

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Speaker 1: just make your farm real shitty, but then you're gonna

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Speaker 1: lose a lot of other wildlife. Well yeah, fair enough,

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Speaker 1: Like you could do clean farming and and and a

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Speaker 1: lot and let everything get overgrown and then there wouldn't

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Speaker 1: be so many deer. You know, it's interesting when I

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Speaker 1: know a fair number of farmers around here and I

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Speaker 1: know those guys are you know, they're it's it's clean farming.

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Speaker 1: It really isn't. Uh. Someone referred to it as a desert,

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Speaker 1: not farmers. Other people that's the desert once they've been

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Speaker 1: out there. But I'm always amazed at the amount of

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Speaker 1: deer that I'll still see in farm fields that it's

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Speaker 1: corn stubble, and if they're stubble there, there's gonna be

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Speaker 1: some something that they'll eat, just like the cattle eat

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Speaker 1: the fodder from the ears and that sort of thing. Um,

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Speaker 1: apparently you know, picking through the bean fields and stuff too,

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Speaker 1: but it's a kind of at different times of the

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Speaker 1: year and then what's exposed, and um, you know, they'll

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Speaker 1: work awful hard at it, or you'll see them if

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Speaker 1: we take take that right up around the and and

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Speaker 1: look at those farm fields. Well, Joe, the guy who

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Speaker 1: farms it up there is the hell of a good farmer. Yet,

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Speaker 1: I mean, there'll be times we'll see seventy five deer

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Speaker 1: up there, you know, working on those fields, and all

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Speaker 1: there are grass strips and then it's corn and beans.

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Speaker 1: So I get that the the clean farm thing, but

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Speaker 1: the clean farming thing. But then I see there that

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Speaker 1: it doesn't seem to be the case, and I wonder

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Speaker 1: if it's just they've also attributed those practices to some

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Speaker 1: of the declines and waterfowl that we saw back in

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Speaker 1: the eighties and things that the people weren't leaving enough

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Speaker 1: that that that we had waterfowl populations that had grown

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Speaker 1: used to all the stubble leftovers, yea, and that the

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Speaker 1: clean farming practices was one of a handful of things

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Speaker 1: that caused a lot of duck species to collapse. I

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Speaker 1: wonder one of the things I noticed around here, and

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Speaker 1: I have to I have to ask Joe about it.

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Speaker 1: It's like he's my farmer reference all the time. They

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Speaker 1: do a lot of spring um grinding of the corn

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Speaker 1: fodder and then bailing it rather than in the fall.

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Speaker 1: And I'm sure it's probably a matter of time and

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Speaker 1: you know, and those sort of things. But um, he's

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Speaker 1: the kind of guy who would leave it because you know,

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Speaker 1: it's good for the wildlife for the you know, through

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Speaker 1: the winter and then in the spring doing it. But um,

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Speaker 1: and then it dries out, you know, great. And and

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Speaker 1: I know there's some rotation as to where they'll do

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Speaker 1: that and where they won't. You know, they won't take

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Speaker 1: the fodder off of each at that field every year,

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Speaker 1: and you know every year because they want to put

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Speaker 1: some of that organic matter back in. But I also

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Speaker 1: think that up there now, and you know, as we

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Speaker 1: start talking about it and thinking about it, that there's

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Speaker 1: a lot of edge there. You know, there's there's brows,

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Speaker 1: there's some other things there. So you know they're probably

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Speaker 1: good working through there and getting a little bit of everything,

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Speaker 1: you know what I mean. Yeah, I'm with you now,

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Speaker 1: pat Um. You're kind of like a dying breed in

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Speaker 1: that you are a like a like a regional one

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Speaker 1: of your jobs, like a regional outdoor columnist. We'll have

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Speaker 1: a new him. All they all died, Yeah, they died

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Speaker 1: in the well. You know. The biggest biggest change is

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Speaker 1: um the way that newspapers went downhill. And when I

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Speaker 1: started off, there was about three or four guys in

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Speaker 1: Wisconsin were full time outdoor writers. Two are at the

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Speaker 1: Milwaukee Journal, always at the Milwaukee Sentinel. There's one in

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Speaker 1: Green Bay. There's one I wa saw. That's when the

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Speaker 1: cross is probably seven of them, I think about it.

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Speaker 1: I had one growing up, the Mosquito Chronicle had I

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Speaker 1: can't remember his name, Bob, I think I had like

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Speaker 1: a dude. Now it seems like other worldly that there

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Speaker 1: would be like the dude whose job it was a

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Speaker 1: right about hunting and fishing opportunities, local wildlife politics, and

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Speaker 1: that was his beat at a newspaper. And this guy

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Speaker 1: had like a desk at a newspaper. Yeah, that was

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Speaker 1: to cover like, hey, the perch are in it's just amazing, man,

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Speaker 1: like big yellow bellies. Last week's meeting at the d

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Speaker 1: n RC office. Well, my my, um, I still get

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Speaker 1: grumpy about when when I see a door writer at

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Speaker 1: a newspaper not taking that beat seriously and just writing

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Speaker 1: about fishing roundups and I'm doing the I think it's

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Speaker 1: not doing the hard report, not doing the hard deper

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Speaker 1: because you know, yeah, but but but I my understanding

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Speaker 1: is is it year well, first sketch out, like how

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Speaker 1: how long have you been um doing? Like how long

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Speaker 1: have you been a What's am I using the right

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Speaker 1: word when I say, like a regional outdoor columns? Like

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Speaker 1: what do you call it? What do you guys call it?

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Speaker 1: I'm I just call myself note door writer. And you're

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Speaker 1: like a syndicated outdoor writer in Wisconsin and you focus Yeah,

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Speaker 1: The focus of my reporting and column writing is Wisconsin,

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Speaker 1: and I've done I've basically my my beat a statewide

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Speaker 1: beca as much as I can. I'm centrally located right

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Speaker 1: in the middle of Wisconsin, so I kind of keep

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Speaker 1: an eye on you try to cover the whole. I try.

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Speaker 1: I try to cover statewide issues and but but I

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Speaker 1: still find there's always those little local guys that do

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Speaker 1: something that's will be a fast daing that I'll do

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Speaker 1: stories and I'll I'll drive down a mass and sometimes

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Speaker 1: for a story whatever it might be. But I am

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Speaker 1: That's why I want to put my job now, because

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Speaker 1: you can't make a living as a freelance guy in newspapers.

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Speaker 1: You can make it, you could, but now you can't.

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Speaker 1: I don't know if you ever could because newspapers have

365
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Speaker 1: never paid freelancers that much. And but you know, as

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Speaker 1: newspapers declined and they started losing revenues, advertising revenues, they

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Speaker 1: just started killing staff like craziest. So I gotta imagine

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Speaker 1: that you had the first guy to go, oh, you

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Speaker 1: would be you'd be one of the very first. Like

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Speaker 1: I know, Um, right now we're down to one full

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Speaker 1: time outdoor writer paid by a newspaper in Wisconsin. That's

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Speaker 1: um Paul Smith at the Milwaukee Journal. Is he barely

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Speaker 1: hanging on? I have no idea. I don't know what. Yeah, yeah, Paul.

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Speaker 1: Paul's a very good outdoor writer. But you know the

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Speaker 1: problem is that he doesn't do like chip shop Penny

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Speaker 1: any He just pretty good stuff. I respect his work

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Speaker 1: and where I where I um where I've made my niche.

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Speaker 1: You know, an outdoor writing I think is covering issues

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Speaker 1: as a columnist where I I like to always think

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Speaker 1: that I give. I give an opinion, but I like

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Speaker 1: to think it's an informed opinion. It's not just off

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Speaker 1: the cuff before I had give an opinion. I've done

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Speaker 1: a lot, done a lot of interviews, done a lot

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Speaker 1: of reading, and I always hate I'm always sensed about

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Speaker 1: the word research because I think I've worked with guys

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Speaker 1: who do scientific research. I know then the research word

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Speaker 1: is a real important word to them. They don't like,

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Speaker 1: you know, to use it just for basically saying he

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Speaker 1: went on Google and typed in, you know, a Google search.

390
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Speaker 1: And so I'm kind of careful how I use that

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Speaker 1: word research. But that's but by learning how do reporting work?

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Speaker 1: The way I did you know. Back in the eighties,

393
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Speaker 1: I started discovering that most outdoor writers working in a

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Speaker 1: national scene on the magazine front and elsewhere, most of

395
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Speaker 1: those guys don't like doing interviews. We call people up

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Speaker 1: or sit through a long day of suminars and take

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Speaker 1: notes to record interviews, transcribe interviews all the world nitty

398
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Speaker 1: gritty work. What those guys do a lot of is

399
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Speaker 1: they'll do a deal or like some company will host, right,

400
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Speaker 1: They'll be like, oh, they'll round up like ten outdoor

401
00:21:56,200 --> 00:22:01,720
Speaker 1: writers and they'll be like, we're going to Texas to asked, uh,

402
00:22:01,720 --> 00:22:06,920
Speaker 1: these new bullets here on on wild Pigs right right,

403
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Speaker 1: And then everyone goes down there and they all shoot

404
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Speaker 1: a wild pig of these new bullets, and they all

405
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Speaker 1: go to their respective publications and they all write an article.

406
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Speaker 1: And you can tell because in there they'll be like

407
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Speaker 1: I was with, I was hunting with. You know, Bob's

408
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Speaker 1: the head of marketing and development at Bob's Bullets. And

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Speaker 1: that is a lot of outdoor writing. Well not I

410
00:22:28,600 --> 00:22:31,200
Speaker 1: don't know if that's so much anymore. I mean, like

411
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Speaker 1: really it really was back in nineties. Well, you know,

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Speaker 1: there are there are the gun writers and Ammo type

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Speaker 1: guys that still do that a lot. But I would

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Speaker 1: I'd never fit into that group. I mean, I know

415
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Speaker 1: it is. I think of it as like gun writers. Yeah,

416
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Speaker 1: gun writers do. I still there's probably still enough work

417
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Speaker 1: there where they get those kind of those kind of

418
00:22:48,080 --> 00:22:50,120
Speaker 1: things that come down. Plus they know what they're doing,

419
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Speaker 1: you know. I like to hunt. I don't really. I've

420
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Speaker 1: got a lot of different dear rifles. I kind of

421
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Speaker 1: like deer rifles, but I don't really know the specs

422
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Speaker 1: on them as far as you know which one you're blissed.

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Speaker 1: The ballistic coy fish and stuff, I don't. I don't

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Speaker 1: know any anything. Yeah, and that kind of stuff. I

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00:23:11,040 --> 00:23:13,959
Speaker 1: like the look of a good wallet stock rifle, and

426
00:23:14,000 --> 00:23:16,040
Speaker 1: I like the old lever action three or weight um

427
00:23:16,080 --> 00:23:19,120
Speaker 1: savage those kind of things. I find that interesting. But

428
00:23:19,400 --> 00:23:21,040
Speaker 1: to go on these um, I think most of his

429
00:23:21,119 --> 00:23:24,240
Speaker 1: companies figure out pretty quickly what your strengths and weaknesses are,

430
00:23:24,680 --> 00:23:26,400
Speaker 1: and they probably have me on one of those kind

431
00:23:26,400 --> 00:23:29,040
Speaker 1: of outings and go I don't ever bring that guy back.

432
00:23:29,119 --> 00:23:31,399
Speaker 1: He's just knocking. He doesn't get this stuff. Yeah, he

433
00:23:31,440 --> 00:23:34,399
Speaker 1: was doing research the whole time because this wasn't it

434
00:23:34,440 --> 00:23:36,919
Speaker 1: wasn't it wasn't up my alley and the magazine I

435
00:23:36,960 --> 00:23:39,640
Speaker 1: used to add that Deer and deeringing magazine. This is back.

436
00:23:39,720 --> 00:23:42,680
Speaker 1: And I got hired there in ninety one, left there

437
00:23:42,680 --> 00:23:44,840
Speaker 1: in two thousand one. So you're the editor in chief

438
00:23:44,880 --> 00:23:47,760
Speaker 1: there for two eleven years. But backup for example, I

439
00:23:47,800 --> 00:23:51,000
Speaker 1: still don't understand. So we like, what was your first

440
00:23:51,040 --> 00:23:55,720
Speaker 1: outdoor writing job. Newspaper? Yeah, and I had a specific newspaper. Yeah,

441
00:23:55,800 --> 00:23:58,040
Speaker 1: but I will study journalism. Oh yeah, yeah, but you

442
00:23:58,080 --> 00:24:01,960
Speaker 1: came out of the Navy. Yeah, I was in the Navy. Nay,

443
00:24:02,600 --> 00:24:06,119
Speaker 1: my dad told me. That's always one of the stories

444
00:24:06,160 --> 00:24:08,720
Speaker 1: I enjoyed talking about. But when I was nineteen years old,

445
00:24:08,720 --> 00:24:11,480
Speaker 1: that said I was going to Navy, and those days

446
00:24:11,480 --> 00:24:13,960
Speaker 1: I decided and I followed my father's footsteps. He was

447
00:24:14,000 --> 00:24:17,000
Speaker 1: a firefighter in the Navy. No, no, in the in

448
00:24:17,040 --> 00:24:20,240
Speaker 1: the Madison, Wisconsin but Dad encouraged me to go to

449
00:24:20,400 --> 00:24:22,480
Speaker 1: the old man hadn't been in the Navy. Now he was.

450
00:24:22,640 --> 00:24:25,080
Speaker 1: He was in the Coast Guard and in the Army,

451
00:24:25,160 --> 00:24:27,000
Speaker 1: but he was in the Coast Guard Reserve and he

452
00:24:27,080 --> 00:24:29,520
Speaker 1: knew enough about the military that knew if you want

453
00:24:29,560 --> 00:24:32,040
Speaker 1: to get firefighting training, you go in the coast Guard

454
00:24:32,080 --> 00:24:34,679
Speaker 1: the Navy because they when a ship's not fire you

455
00:24:34,720 --> 00:24:38,320
Speaker 1: better get that fire off you want to hurt so

456
00:24:38,320 --> 00:24:43,000
Speaker 1: so they really can't run outside. That's one of the

457
00:24:43,000 --> 00:24:45,880
Speaker 1: things I really liked the Navy was how every ship

458
00:24:46,000 --> 00:24:48,240
Speaker 1: was basically its one little city and had to have

459
00:24:48,320 --> 00:24:51,600
Speaker 1: all the all the services. So some of my dad

460
00:24:51,640 --> 00:24:53,919
Speaker 1: when I went in the Navy, he was telling me,

461
00:24:53,960 --> 00:24:56,800
Speaker 1: he's looking at all the recruiting stuff. He says, instead

462
00:24:56,840 --> 00:24:59,040
Speaker 1: of doing this firefighting training, because I was gonna be

463
00:24:59,320 --> 00:25:02,200
Speaker 1: I was what was called done a whole maintenance technician.

464
00:25:02,240 --> 00:25:05,280
Speaker 1: They taught you firefighting, they taught you damage control, welding,

465
00:25:05,280 --> 00:25:07,879
Speaker 1: all these great skills. My dad looked at all this

466
00:25:07,920 --> 00:25:11,520
Speaker 1: stuff and he says, you should take this journalism training

467
00:25:11,560 --> 00:25:16,000
Speaker 1: because they have they trained you to be a journalists

468
00:25:16,040 --> 00:25:18,920
Speaker 1: who because they have people they have They have press

469
00:25:18,960 --> 00:25:21,720
Speaker 1: releases on ships and they have little ship newspapers, and

470
00:25:22,119 --> 00:25:25,359
Speaker 1: especially the bigger ships have regular publications. I don't know

471
00:25:25,400 --> 00:25:27,400
Speaker 1: if they do now, but it's probably on internet now

472
00:25:27,520 --> 00:25:30,879
Speaker 1: or wire based type stuff. But my but I was nineteen.

473
00:25:30,880 --> 00:25:33,119
Speaker 1: I knew everything. So I said, no, I'm gonna go

474
00:25:33,240 --> 00:25:37,199
Speaker 1: off and do this. You know, damage control. Yeah. But

475
00:25:37,240 --> 00:25:39,679
Speaker 1: then by the time I got the Navy, which is

476
00:25:39,720 --> 00:25:44,000
Speaker 1: five years, I realized Dad was right. My strength was

477
00:25:44,000 --> 00:25:46,959
Speaker 1: was writing and editing, and I was a lousy walder.

478
00:25:47,320 --> 00:25:50,480
Speaker 1: I understood damage control, but I realized, God, the skills

479
00:25:50,520 --> 00:25:53,000
Speaker 1: I have, I'm getting bored doing this stuff. You know,

480
00:25:53,840 --> 00:25:55,840
Speaker 1: end up being a locksmith. In my final three years

481
00:25:55,840 --> 00:25:58,159
Speaker 1: in the Navy, got trained to a locksmith, and so

482
00:25:58,240 --> 00:26:00,480
Speaker 1: I was breaking in the says all time for in

483
00:26:00,520 --> 00:26:04,520
Speaker 1: these little wardrooms on Navy ships. And so you're like,

484
00:26:04,760 --> 00:26:09,040
Speaker 1: so the ship has a locks move. Oh yeah, well

485
00:26:09,080 --> 00:26:11,840
Speaker 1: that's a little city, right, yeah, I mean it gets

486
00:26:11,880 --> 00:26:14,560
Speaker 1: locked out of the boat. Well, I was on a

487
00:26:14,920 --> 00:26:17,720
Speaker 1: I was on what's called destroyer tender. It's a big

488
00:26:17,720 --> 00:26:20,879
Speaker 1: repair ship. And so like our job, basically we pulled

489
00:26:20,920 --> 00:26:23,760
Speaker 1: into a port. Then all these destroyers and cruisers would

490
00:26:23,760 --> 00:26:26,520
Speaker 1: pull up alongside of us, and that'd go over there

491
00:26:26,560 --> 00:26:29,680
Speaker 1: and do all the locksmith work. You know, people locked

492
00:26:29,680 --> 00:26:32,000
Speaker 1: all their rooms locked out. I mean my biggest job

493
00:26:32,040 --> 00:26:35,720
Speaker 1: everyone as I spent Christmas Day in seventy eight on

494
00:26:35,760 --> 00:26:38,240
Speaker 1: a submarine all day because the duty officer lost the

495
00:26:38,320 --> 00:26:40,960
Speaker 1: key ring to the to the submarine. Every every key

496
00:26:41,000 --> 00:26:43,720
Speaker 1: that went around that sub So that's been all day

497
00:26:43,720 --> 00:26:46,840
Speaker 1: of replacing all these these keys. But to get back

498
00:26:46,840 --> 00:26:50,520
Speaker 1: to your story, so did you say so it was

499
00:26:50,600 --> 00:26:53,600
Speaker 1: like a war free period I had perfectly. It was

500
00:26:53,680 --> 00:26:56,960
Speaker 1: right after Vietnam and when I was getting out, it

501
00:26:57,160 --> 00:27:00,720
Speaker 1: didn't even have to do Grenada. No, I mess missed that.

502
00:27:01,040 --> 00:27:04,400
Speaker 1: But the closest I came to anything interesting was we evacuated.

503
00:27:04,440 --> 00:27:07,239
Speaker 1: We helped evacuate a bunch of people in Lebanon. You know,

504
00:27:07,280 --> 00:27:10,680
Speaker 1: it's like my my five years and was from eighty

505
00:27:10,800 --> 00:27:13,080
Speaker 1: and when I was getting out was during I ran

506
00:27:13,400 --> 00:27:17,520
Speaker 1: the Ran hostage crisis, and so yeah, a little bit

507
00:27:17,560 --> 00:27:19,520
Speaker 1: of you know, worry about where that would lead, but

508
00:27:19,560 --> 00:27:22,520
Speaker 1: eventually it all calmed down. But I never had to

509
00:27:22,600 --> 00:27:26,119
Speaker 1: do anything interesting. And so I'm I'm always. I'm always

510
00:27:26,160 --> 00:27:28,040
Speaker 1: probably the fact I served the Navy because I really

511
00:27:28,200 --> 00:27:29,879
Speaker 1: I enjoyed it. I don't want to make a care

512
00:27:29,920 --> 00:27:32,600
Speaker 1: out of I enjoyed it. And their friend as their

513
00:27:32,640 --> 00:27:36,080
Speaker 1: friend Rurk says, you you earned your seat at the table. Yeah,

514
00:27:36,160 --> 00:27:39,280
Speaker 1: the table being America. Yeah, and I believe that kind

515
00:27:39,320 --> 00:27:42,080
Speaker 1: of stuff. I like, I believe in public service, all

516
00:27:42,119 --> 00:27:45,240
Speaker 1: those kind of things. I encouraged my daughter, oldest daughter.

517
00:27:45,320 --> 00:27:48,560
Speaker 1: When she um was heading off to college. She asked

518
00:27:48,560 --> 00:27:50,840
Speaker 1: me about navy, and I was told her I said,

519
00:27:50,880 --> 00:27:52,640
Speaker 1: I didn't want to make a care out of this,

520
00:27:53,119 --> 00:27:56,040
Speaker 1: but I liked it. I liked that sense of community,

521
00:27:56,200 --> 00:27:59,359
Speaker 1: that sense of service. She's career, she's been ten years

522
00:27:59,359 --> 00:28:01,879
Speaker 1: now and she is a she's now a doctor in

523
00:28:01,920 --> 00:28:05,520
Speaker 1: the Navy, a nurse midwife, basically the equivalent of a doctor.

524
00:28:06,000 --> 00:28:08,520
Speaker 1: And so I'm real proud of that. And but you know,

525
00:28:08,560 --> 00:28:11,520
Speaker 1: by the time I got the Navy, though, I had

526
00:28:11,560 --> 00:28:13,720
Speaker 1: so many people tell me they'd read my letters. Because

527
00:28:13,720 --> 00:28:15,639
Speaker 1: this is I actually bought typewriter in the Navy, a

528
00:28:15,720 --> 00:28:18,200
Speaker 1: manual typewriter, which I wish I still would have kept,

529
00:28:18,920 --> 00:28:21,679
Speaker 1: and I typed on my letters because I don't know type,

530
00:28:21,680 --> 00:28:24,359
Speaker 1: and I I cranked out letters to everyone, anyone that

531
00:28:24,400 --> 00:28:27,000
Speaker 1: would write to me, I'd write them back. And I

532
00:28:27,080 --> 00:28:31,320
Speaker 1: bought my God. Yeah, and when you started having people

533
00:28:31,320 --> 00:28:33,760
Speaker 1: tell you that when I read your letters, I feel

534
00:28:33,760 --> 00:28:37,240
Speaker 1: like I'm right there. And I thought, well, that means something.

535
00:28:37,240 --> 00:28:40,200
Speaker 1: Well I got when I got out there, I i stuff.

536
00:28:40,200 --> 00:28:43,440
Speaker 1: Following my dad's footsteps, I went off to college and

537
00:28:43,480 --> 00:28:47,360
Speaker 1: got my degree in journalism, and then I but timized Um.

538
00:28:47,440 --> 00:28:49,320
Speaker 1: In my junior year, I started working for the local

539
00:28:49,320 --> 00:28:52,880
Speaker 1: newspaper in ash Goosh, Wisconsin as a local sports writer,

540
00:28:53,320 --> 00:28:55,840
Speaker 1: which was kind of a yeah because it was anyone

541
00:28:55,880 --> 00:28:57,280
Speaker 1: who knew me, and it was a joke that I

542
00:28:57,320 --> 00:28:59,680
Speaker 1: was actually covering high school sports because I un't read

543
00:28:59,680 --> 00:29:02,440
Speaker 1: any Tristan and most of the sports up for the

544
00:29:02,440 --> 00:29:06,440
Speaker 1: Packers and Green Bay Packers I liked. Oh yeah. I

545
00:29:06,480 --> 00:29:07,840
Speaker 1: covered him for two or three years and it was

546
00:29:07,880 --> 00:29:09,960
Speaker 1: a miserable because it was like being a fan. I

547
00:29:09,960 --> 00:29:12,240
Speaker 1: don't like being a you know, working on a beat

548
00:29:12,240 --> 00:29:14,600
Speaker 1: for you're covering in the team, team that you can't

549
00:29:14,640 --> 00:29:17,320
Speaker 1: cheer for, because what do you guys like me? Not

550
00:29:17,480 --> 00:29:21,440
Speaker 1: that I mean like specific like everybody likes their team,

551
00:29:21,480 --> 00:29:23,960
Speaker 1: but why is it that you guys that people Wisconsin

552
00:29:23,960 --> 00:29:25,800
Speaker 1: are so fired u about the Packers. This is win

553
00:29:25,880 --> 00:29:28,280
Speaker 1: the super Bowl or something well they wanted, they wanted

554
00:29:28,360 --> 00:29:31,520
Speaker 1: four times, Steve. Did they win recently? No, not, not

555
00:29:31,600 --> 00:29:35,200
Speaker 1: since two thousand ten. But there always competitive and in

556
00:29:35,200 --> 00:29:38,000
Speaker 1: the last twenty years we've been spoiled. We've had incredible

557
00:29:38,080 --> 00:29:41,520
Speaker 1: quarterback in the last twenty years. But to answer your question,

558
00:29:41,720 --> 00:29:44,320
Speaker 1: Wisconsin dugs yawning, but you don't want to get into

559
00:29:44,320 --> 00:29:46,960
Speaker 1: the Packers because you don't give a not until it

560
00:29:47,000 --> 00:29:49,680
Speaker 1: gets cold and shitty outside and then you know, December,

561
00:29:49,720 --> 00:29:51,880
Speaker 1: I start watching. Well, no, because you guys are telling

562
00:29:51,880 --> 00:29:54,520
Speaker 1: me that that's the perfect day when the Packers are playing,

563
00:29:54,600 --> 00:29:57,959
Speaker 1: that's the day you can hunt everybody else, Like if

564
00:29:58,000 --> 00:29:59,920
Speaker 1: you can. You think we were going to talk about

565
00:30:00,040 --> 00:30:02,600
Speaker 1: been kind of curious about hunting someone else's property, Do

566
00:30:02,600 --> 00:30:04,480
Speaker 1: it while the Packers are playing, because you damn you're

567
00:30:04,480 --> 00:30:06,440
Speaker 1: not gonna run into the guy, and then you can

568
00:30:06,440 --> 00:30:09,640
Speaker 1: go and shoot some deer off his land. Uh, you

569
00:30:09,640 --> 00:30:11,880
Speaker 1: got a question earlier looked like when you're talking about

570
00:30:11,880 --> 00:30:13,760
Speaker 1: the Navy. I'm gonna move on from all this, and

571
00:30:13,840 --> 00:30:16,480
Speaker 1: I don't want you to. We're in Doug's, Doug's farmhouse.

572
00:30:16,480 --> 00:30:18,440
Speaker 1: I don't want to board Doug in his own damn farmhouse.

573
00:30:18,800 --> 00:30:21,520
Speaker 1: Get away from this. I've known Pat for I don't

574
00:30:21,520 --> 00:30:24,280
Speaker 1: know a while, and uh, I don't know ten or

575
00:30:24,320 --> 00:30:26,640
Speaker 1: twelve years or something like that, and uh, we've had

576
00:30:26,680 --> 00:30:29,240
Speaker 1: we've talked about all kinds of things, but I guess

577
00:30:29,280 --> 00:30:32,280
Speaker 1: I've never really heard the whole navy story before. And

578
00:30:32,280 --> 00:30:34,520
Speaker 1: what I'm really curious about with you know, he was

579
00:30:34,560 --> 00:30:36,000
Speaker 1: a locksmith in the name. I didn't know he was

580
00:30:36,040 --> 00:30:38,320
Speaker 1: a locksmith in the Navy. I do about you know, guy,

581
00:30:38,400 --> 00:30:43,760
Speaker 1: your whole life, but I wondered about your father. You here,

582
00:30:43,800 --> 00:30:47,080
Speaker 1: you're telling your father that I'm interested in becoming a

583
00:30:47,120 --> 00:30:50,440
Speaker 1: firefighter and all that, but yet your father's going so

584
00:30:50,520 --> 00:30:53,640
Speaker 1: he discouraged you from He encouraged me to um go

585
00:30:53,680 --> 00:30:56,400
Speaker 1: into firefighting. But I should have finished that story. Yeah,

586
00:30:56,440 --> 00:31:00,200
Speaker 1: that's a good point, Doug. What happened when when um,

587
00:31:00,240 --> 00:31:02,560
Speaker 1: when I came, that became that juncture I had to choose.

588
00:31:03,080 --> 00:31:05,840
Speaker 1: Dad's advice was to go into the journalism school the

589
00:31:05,920 --> 00:31:08,680
Speaker 1: Navy offered, because he said to me, and he was right,

590
00:31:09,000 --> 00:31:12,680
Speaker 1: he said, every the Navy teaches everyone firefighting skills because

591
00:31:12,720 --> 00:31:15,960
Speaker 1: everyone in a fire has to has to respond. And

592
00:31:16,040 --> 00:31:19,120
Speaker 1: Dad had been through the Coast Guards training, and he

593
00:31:19,240 --> 00:31:22,400
Speaker 1: been through prior. He probably been to Navy, actual Navy

594
00:31:22,440 --> 00:31:26,040
Speaker 1: firefighting schools, because the Coast Guard will will help out

595
00:31:26,080 --> 00:31:28,440
Speaker 1: with the Navy stuff and they'll use the Navy facilities.

596
00:31:28,640 --> 00:31:31,200
Speaker 1: So Dad probably knew all that stuff. But again, you know,

597
00:31:31,560 --> 00:31:33,280
Speaker 1: because I was nineteen and thought I thought I was

598
00:31:33,320 --> 00:31:35,240
Speaker 1: smart and that you know, I know what I want

599
00:31:35,280 --> 00:31:39,080
Speaker 1: to do. I just blew off Dad's advice and came

600
00:31:39,120 --> 00:31:43,280
Speaker 1: to realize, you know, like a couple of years a quote,

601
00:31:43,320 --> 00:31:45,840
Speaker 1: you know, the pen is mightier than the sword, The

602
00:31:45,880 --> 00:31:50,680
Speaker 1: pen is mightier than the fire. Hard So I've never

603
00:31:50,720 --> 00:31:53,240
Speaker 1: met I want to move on, Go ahead, let me please.

604
00:31:54,520 --> 00:31:58,200
Speaker 1: So I've never met Pat's dad, but he's a a

605
00:31:58,240 --> 00:32:01,760
Speaker 1: famous character in Madison. He was the fire chief and

606
00:32:01,760 --> 00:32:04,720
Speaker 1: and really interesting guy. So he's like a high level

607
00:32:04,760 --> 00:32:07,440
Speaker 1: fire man. He's the fire chief during the six Oh.

608
00:32:07,440 --> 00:32:11,000
Speaker 1: I I thought he just hated fire, just wanted fire

609
00:32:11,040 --> 00:32:13,640
Speaker 1: to be put out. And I thought, you know, in

610
00:32:13,680 --> 00:32:15,160
Speaker 1: the stories that I've heard about him, he's a bit

611
00:32:15,200 --> 00:32:17,960
Speaker 1: of a character, you know, and I just kind of

612
00:32:17,960 --> 00:32:21,160
Speaker 1: thought that, um, maybe he was just saying sorry, son.

613
00:32:21,520 --> 00:32:24,840
Speaker 1: Now Dad actually told me, and not not making this up.

614
00:32:25,440 --> 00:32:28,160
Speaker 1: Dad actually told me that of his four sons that

615
00:32:28,200 --> 00:32:29,920
Speaker 1: he thought I was the one that was most most

616
00:32:30,560 --> 00:32:36,320
Speaker 1: personality wise, most cut out to be a firefighter. And

617
00:32:36,520 --> 00:32:39,880
Speaker 1: I never quite knew it was true. What is the

618
00:32:39,920 --> 00:32:42,600
Speaker 1: person that Okay, I don't want to talk about it. Well,

619
00:32:43,000 --> 00:32:45,120
Speaker 1: just things like not not being afraid to go up

620
00:32:45,120 --> 00:32:46,640
Speaker 1: the ladder and not being afraid to hang on to

621
00:32:46,720 --> 00:32:50,320
Speaker 1: ship and just you know, yeah, stick your nose in there. Yeah,

622
00:32:50,760 --> 00:32:53,600
Speaker 1: rescuing maidens and distress and whatnot. He thought that, he

623
00:32:53,640 --> 00:32:57,600
Speaker 1: thought you were that guy. So then you Okay, then

624
00:32:58,000 --> 00:33:00,600
Speaker 1: you became so that and I want to skip writing

625
00:33:00,600 --> 00:33:03,520
Speaker 1: about sports because that's not that's not interesting. So you

626
00:33:03,520 --> 00:33:08,480
Speaker 1: wrote about athletics, okay, now then you then then you

627
00:33:08,520 --> 00:33:14,760
Speaker 1: became a professional outdoor writer. Win. Um, where where I

628
00:33:14,760 --> 00:33:17,080
Speaker 1: could construed out full time wasn'tuntil I got the Deer

629
00:33:17,080 --> 00:33:20,600
Speaker 1: and Deer Running magazine. And but but the Nash Cash paper,

630
00:33:21,040 --> 00:33:23,600
Speaker 1: well I did because this is a small, you know,

631
00:33:23,640 --> 00:33:28,080
Speaker 1: like a midsize city in Wisconsin. People and the newspaper

632
00:33:28,200 --> 00:33:31,040
Speaker 1: couldn't staff a full time outdoor writer. But they let

633
00:33:31,080 --> 00:33:33,480
Speaker 1: me basically be a halftime outdoor writer. And I also

634
00:33:33,560 --> 00:33:36,080
Speaker 1: ran the week. I was other of the week on newspapers.

635
00:33:36,400 --> 00:33:38,480
Speaker 1: I also covered the education beat for a while, you

636
00:33:38,520 --> 00:33:41,280
Speaker 1: know that school board, that kind of stuff. But the

637
00:33:41,320 --> 00:33:43,440
Speaker 1: reason I I should just say that real quickly, the

638
00:33:43,440 --> 00:33:46,040
Speaker 1: reason when when in the sports let's get first, was

639
00:33:46,080 --> 00:33:47,640
Speaker 1: because I knew that was the quickest route to the

640
00:33:47,640 --> 00:33:52,120
Speaker 1: outdoor page, because yeah, the sports sections almost always legitimizes

641
00:33:52,160 --> 00:33:55,560
Speaker 1: it my eyes, because it was it was that. That

642
00:33:55,680 --> 00:33:58,720
Speaker 1: was my my ulterior motive was to get into the

643
00:33:58,760 --> 00:34:01,440
Speaker 1: Outdoor page and eventually got control of the Outdoor page.

644
00:34:01,880 --> 00:34:04,480
Speaker 1: And I really worked that beat now because my my

645
00:34:04,600 --> 00:34:08,160
Speaker 1: dream was to use that platform there to get the

646
00:34:08,160 --> 00:34:11,600
Speaker 1: Malwaukee Journal's eye and go to and become the Malaukee

647
00:34:11,640 --> 00:34:14,840
Speaker 1: Journals at door writer. Because you grew up hunting, fishing, Yeah, Yohni,

648
00:34:14,960 --> 00:34:19,600
Speaker 1: what point did you become so bored and making notes

649
00:34:20,080 --> 00:34:28,080
Speaker 1: that's what you're doing? Ok Um, So at that point then,

650
00:34:29,480 --> 00:34:34,040
Speaker 1: because you we're gonna syndicate, can you explain that? Yeah,

651
00:34:34,239 --> 00:34:36,879
Speaker 1: my my syndication. They didn't start to actually started working

652
00:34:36,880 --> 00:34:41,359
Speaker 1: at Deer and Deer running magazine, and Deer and Deer

653
00:34:41,440 --> 00:34:43,360
Speaker 1: Hunting was look E. When I first went there, it

654
00:34:43,440 --> 00:34:45,960
Speaker 1: was it was a neat magazine because it was started

655
00:34:45,960 --> 00:34:48,360
Speaker 1: by local guys up in Appleton, Wisconsin. Is two guys.

656
00:34:48,360 --> 00:34:50,520
Speaker 1: It was yeah, oh yeah, that was started in Appleton,

657
00:34:50,560 --> 00:34:54,040
Speaker 1: Wisconsin and seventies suventy seven by two guys and they

658
00:34:54,280 --> 00:34:56,640
Speaker 1: started off their magazine. It was called they had to

659
00:34:56,719 --> 00:34:59,480
Speaker 1: some traveling road show. Basically they go to high schools

660
00:34:59,480 --> 00:35:02,800
Speaker 1: and civic groups and do presentations of white tail deer

661
00:35:03,160 --> 00:35:04,839
Speaker 1: and they're doing all sorts of crazy stuff that they

662
00:35:04,880 --> 00:35:07,879
Speaker 1: put speakers up in trees and blow noise to see

663
00:35:07,880 --> 00:35:10,279
Speaker 1: how dealer respond to it. And so they're like they're

664
00:35:10,280 --> 00:35:13,399
Speaker 1: like doing their own like shoes stringing their own deer

665
00:35:13,440 --> 00:35:16,480
Speaker 1: research exactly. That that's plus they're the first guys to

666
00:35:16,520 --> 00:35:20,200
Speaker 1: really start actually go on and digging out scientific research

667
00:35:20,280 --> 00:35:22,520
Speaker 1: and putting it to practical use for hunters. And that

668
00:35:22,640 --> 00:35:26,239
Speaker 1: was the tagline the magazinish Yeah yeah, you're there ten

669
00:35:26,320 --> 00:35:29,440
Speaker 1: years yeah, loving years. Yeah. And I really enjoyed it,

670
00:35:29,719 --> 00:35:32,759
Speaker 1: and it gave me opportunities that I never had gotten

671
00:35:32,800 --> 00:35:35,400
Speaker 1: anywhere else because it gave me a one of the

672
00:35:35,400 --> 00:35:36,960
Speaker 1: things I really got out that it was a big

673
00:35:36,960 --> 00:35:39,799
Speaker 1: benefit that made me realize how much I liked, as

674
00:35:39,800 --> 00:35:42,960
Speaker 1: boring as it can be, sitting at these different um

675
00:35:43,000 --> 00:35:47,279
Speaker 1: scientific seminars and waiting for that that little nugget to

676
00:35:47,280 --> 00:35:50,239
Speaker 1: come out of some college kids research on deer that

677
00:35:50,280 --> 00:35:52,160
Speaker 1: they could use in the magazines because they're like, part

678
00:35:52,239 --> 00:35:55,640
Speaker 1: of your job was just to cover all research pertaining

679
00:35:55,640 --> 00:35:58,800
Speaker 1: the white tail deer. Yeah yeah, and especially this stuff.

680
00:35:59,000 --> 00:36:01,799
Speaker 1: The magazine's tag I was and it probably still is

681
00:36:02,160 --> 00:36:06,319
Speaker 1: practical and comprehensive information for white tail deer hunters, and

682
00:36:06,360 --> 00:36:09,520
Speaker 1: that was right up my alley. I like that. I see,

683
00:36:09,560 --> 00:36:13,279
Speaker 1: like I've always found that I love deer hunting, and

684
00:36:13,320 --> 00:36:16,239
Speaker 1: that's the number one thing he's welk in my hollis

685
00:36:16,280 --> 00:36:18,319
Speaker 1: you know, this guy's a deer hunter. That's all all

686
00:36:18,360 --> 00:36:21,440
Speaker 1: he does. But I realized early on that as much

687
00:36:21,440 --> 00:36:24,920
Speaker 1: as I love deer hunting, I'm not a predator to waste.

688
00:36:25,080 --> 00:36:28,279
Speaker 1: I met guys and that up magazine that they are predators.

689
00:36:28,280 --> 00:36:31,600
Speaker 1: They know how to kill deer. They they're good. And

690
00:36:31,640 --> 00:36:34,440
Speaker 1: I that's one thing I really love about what I

691
00:36:34,480 --> 00:36:36,920
Speaker 1: do is I get to meet guys with their hunters

692
00:36:36,920 --> 00:36:39,439
Speaker 1: and fishermen that if you think you're a good hunter

693
00:36:39,480 --> 00:36:41,400
Speaker 1: and fisherman, you're jealous. And these guys you see on

694
00:36:41,440 --> 00:36:44,720
Speaker 1: TV and wherever it might be, I hope there's sometimes

695
00:36:44,719 --> 00:36:47,160
Speaker 1: I really respect the fact that these guys really are

696
00:36:47,160 --> 00:36:49,880
Speaker 1: in many cases better than you are at deer hunting

697
00:36:49,880 --> 00:36:52,200
Speaker 1: and better than you are at bass fishing or walleye fishing.

698
00:36:52,840 --> 00:36:55,960
Speaker 1: And Yeah, but that pisses people because people like always

699
00:36:56,000 --> 00:36:59,200
Speaker 1: be reading magazines and people are goof on. People be like, well,

700
00:36:59,239 --> 00:37:01,959
Speaker 1: goof on, do like me who like like do TV

701
00:37:02,040 --> 00:37:06,239
Speaker 1: about hunting like, oh, he's the moment. Yeah, but not

702
00:37:06,360 --> 00:37:07,839
Speaker 1: many of people get to go out as much as

703
00:37:07,880 --> 00:37:10,879
Speaker 1: we go out. Like if you're in an occupation where

704
00:37:10,880 --> 00:37:15,000
Speaker 1: you're hunting, where you're spending a hundred and fifty plus

705
00:37:15,280 --> 00:37:18,760
Speaker 1: days a year actively out in the woods, hunting and fishing,

706
00:37:18,840 --> 00:37:21,239
Speaker 1: you're probably gonna see some things and learn some things.

707
00:37:21,520 --> 00:37:23,759
Speaker 1: I mean, just you could be the biggest knucklehead in

708
00:37:23,800 --> 00:37:26,719
Speaker 1: the world, but something's gonna rob off on you, and

709
00:37:26,800 --> 00:37:30,239
Speaker 1: that amount expos of exposure, you take that out like

710
00:37:30,440 --> 00:37:32,960
Speaker 1: you attend your career doing that. At the end of that,

711
00:37:33,040 --> 00:37:35,360
Speaker 1: you have seen a ton of ship happened in the woods,

712
00:37:35,800 --> 00:37:37,799
Speaker 1: and a lot of these guys that got good at

713
00:37:37,880 --> 00:37:41,600
Speaker 1: like in my in my my generation, those guys like, um,

714
00:37:41,600 --> 00:37:43,239
Speaker 1: oh he's older than me a little bit, but like

715
00:37:43,320 --> 00:37:46,520
Speaker 1: Miles Color, it was just I'm not sure how he's

716
00:37:46,520 --> 00:37:48,359
Speaker 1: doing these days, but the guy could really go out

717
00:37:48,400 --> 00:37:50,799
Speaker 1: and find he go out in a new area, look

718
00:37:50,840 --> 00:37:53,000
Speaker 1: it over, figure out pretty quickly how to hunt during

719
00:37:53,040 --> 00:37:56,719
Speaker 1: that area. Greg Miller back in the sixties and seventies,

720
00:37:56,719 --> 00:37:59,880
Speaker 1: but was killing really nice deer noldn Wisconsin, and like

721
00:38:00,040 --> 00:38:02,520
Speaker 1: lot of guys didn't know big Bucks existed up there

722
00:38:03,120 --> 00:38:05,840
Speaker 1: and those guys like that, and they always find fascinating

723
00:38:05,840 --> 00:38:07,520
Speaker 1: about of these guys I've met over the year as

724
00:38:07,520 --> 00:38:09,959
Speaker 1: a hunted with They can't tell you a red pine

725
00:38:09,960 --> 00:38:12,560
Speaker 1: from a white pine from a cedar, but they know

726
00:38:12,560 --> 00:38:14,640
Speaker 1: how to kill deer. They know how to line things

727
00:38:14,719 --> 00:38:16,439
Speaker 1: up to figure out what's going on. I've heard people

728
00:38:16,480 --> 00:38:18,839
Speaker 1: others say that the guys say that, like the talking

729
00:38:18,840 --> 00:38:22,080
Speaker 1: about some like white tail expert and being like in

730
00:38:22,200 --> 00:38:24,320
Speaker 1: saying that's some bitch didn't know the kind of tree

731
00:38:24,360 --> 00:38:28,479
Speaker 1: his trees day was in mhm, but he he didn't

732
00:38:28,480 --> 00:38:31,279
Speaker 1: need woodsmanship. He knew how to hunt white tails. Yeah.

733
00:38:31,320 --> 00:38:33,680
Speaker 1: And the point I make because you have all wolves

734
00:38:33,719 --> 00:38:36,239
Speaker 1: don't they can't tell trees of heart either, but they

735
00:38:36,239 --> 00:38:38,160
Speaker 1: probably figure out habitat. And you don't know how they

736
00:38:38,160 --> 00:38:43,160
Speaker 1: conceptualized trees. Well, they probably don't do the Linanean binomial nomenclature,

737
00:38:43,280 --> 00:38:47,719
Speaker 1: but they might conceptualize trees. And someone I want to

738
00:38:47,800 --> 00:38:49,920
Speaker 1: dot one bit. They figure out real quickly when they

739
00:38:49,920 --> 00:38:52,720
Speaker 1: walk into go through a cruise to a section of woods,

740
00:38:53,440 --> 00:38:57,080
Speaker 1: which which ones will bear fruit, which ones productive? And yeah,

741
00:38:57,400 --> 00:39:01,160
Speaker 1: they it's like you've mentioned the past, hunters look at

742
00:39:01,560 --> 00:39:03,759
Speaker 1: treat bottoms a whole lot differently than somebody else going

743
00:39:03,800 --> 00:39:06,480
Speaker 1: buy in the car. You know, it's just it becomes

744
00:39:06,520 --> 00:39:09,040
Speaker 1: part of your you know, they won't live long if

745
00:39:09,040 --> 00:39:11,280
Speaker 1: they can't walk into part of a wood row quickly

746
00:39:11,280 --> 00:39:14,680
Speaker 1: figure out how this thing works. Happened. I couldn't go

747
00:39:14,680 --> 00:39:17,759
Speaker 1: over at Colvert without slowing down or backing up. Yeah,

748
00:39:17,840 --> 00:39:20,560
Speaker 1: I had to expect every bit of water every time.

749
00:39:21,520 --> 00:39:24,120
Speaker 1: And that's that's where I I love meeting those kind

750
00:39:24,120 --> 00:39:27,319
Speaker 1: of people. And I learned real quickly to pay them

751
00:39:27,320 --> 00:39:29,440
Speaker 1: respect for that that. You know, I might know more

752
00:39:29,440 --> 00:39:32,839
Speaker 1: about some guys research project and how it turned out,

753
00:39:32,920 --> 00:39:35,800
Speaker 1: and I might be able to give him law facts.

754
00:39:35,920 --> 00:39:38,080
Speaker 1: They'll they'll blow off, you know, as far as you know,

755
00:39:38,160 --> 00:39:40,759
Speaker 1: like we talked about earlier about coyotes and kind of

756
00:39:41,120 --> 00:39:44,520
Speaker 1: an interesting subject because all this country that they're having

757
00:39:44,520 --> 00:39:47,600
Speaker 1: different impacts on deering, different different levels. You know, there's

758
00:39:47,840 --> 00:39:52,160
Speaker 1: there's areas in northeastern Minnesota, like talking before about um

759
00:39:52,320 --> 00:39:54,880
Speaker 1: the idea that they kind of accept a certain ob

760
00:39:54,960 --> 00:39:57,239
Speaker 1: predation somewhrea because I used to it. Well, you know,

761
00:39:57,280 --> 00:39:58,680
Speaker 1: you go to know the Minnesota and you look at

762
00:39:58,680 --> 00:40:01,120
Speaker 1: the research going back into the six these you know,

763
00:40:01,760 --> 00:40:05,239
Speaker 1: fond survival through that first year, it was like in

764
00:40:05,239 --> 00:40:10,040
Speaker 1: the range often that's regularly because it's our harsh environment,

765
00:40:10,040 --> 00:40:13,480
Speaker 1: winter would kill him off. They come through the summer, okay,

766
00:40:13,719 --> 00:40:16,480
Speaker 1: never make it, never make it out of winter, and

767
00:40:17,400 --> 00:40:20,360
Speaker 1: survival you know, for that first year was not uncommon.

768
00:40:20,880 --> 00:40:25,040
Speaker 1: So what's it around here, Doug? We uh something like

769
00:40:25,120 --> 00:40:29,960
Speaker 1: one point one fawns per do survive because we have

770
00:40:30,040 --> 00:40:32,600
Speaker 1: so many twins, you know, and it's you know, I mean,

771
00:40:32,640 --> 00:40:36,719
Speaker 1: you'll lose a few very good recruitment because there's parts

772
00:40:36,760 --> 00:40:40,360
Speaker 1: of um South Caroline right now where they had like

773
00:40:40,640 --> 00:40:44,400
Speaker 1: point for you know for fawn recruitment one point for

774
00:40:44,719 --> 00:40:47,319
Speaker 1: no no point for like zero point four. What's the

775
00:40:47,360 --> 00:40:50,919
Speaker 1: reason for that? Because right because because right now there's

776
00:40:50,960 --> 00:40:54,960
Speaker 1: areas of the South in South Carolina the other Southeastern

777
00:40:55,000 --> 00:40:58,480
Speaker 1: states then are known counties. Really until recently the deer

778
00:40:59,400 --> 00:41:02,600
Speaker 1: they having figure it out. Those things are going well.

779
00:41:02,960 --> 00:41:04,760
Speaker 1: We have When we kicked off as a little teaser,

780
00:41:04,800 --> 00:41:06,560
Speaker 1: I said, are they really killing all the deer? You said, no,

781
00:41:07,840 --> 00:41:12,480
Speaker 1: I'm some guy in South Carolina's his hair. That's kind

782
00:41:12,480 --> 00:41:14,719
Speaker 1: of why I circle back, because you want to get it,

783
00:41:14,719 --> 00:41:15,680
Speaker 1: but I want to get into it. Two but I

784
00:41:15,760 --> 00:41:17,840
Speaker 1: need to clear something up just for my own understanding,

785
00:41:17,960 --> 00:41:20,480
Speaker 1: because I anestly don't know this yet. I do want

786
00:41:20,520 --> 00:41:21,680
Speaker 1: to talk. I want to talk about a lot of that,

787
00:41:22,719 --> 00:41:25,239
Speaker 1: but I just also understand this. I'm just unders I'm

788
00:41:25,239 --> 00:41:27,840
Speaker 1: still tripped up and and maybe no one else in

789
00:41:27,880 --> 00:41:34,759
Speaker 1: the world is on on the demise of the outdoor columnists.

790
00:41:35,920 --> 00:41:38,520
Speaker 1: And as a way, I wanted to understand that. I

791
00:41:38,560 --> 00:41:41,160
Speaker 1: think it might be helpful. I understand the survival of

792
00:41:41,239 --> 00:41:44,160
Speaker 1: an outdoor columnist. So when you start doing that. So

793
00:41:44,400 --> 00:41:46,600
Speaker 1: so you went to Deer and Deer Hunting and became

794
00:41:46,640 --> 00:41:49,319
Speaker 1: the editor in chief and as a national publication, became

795
00:41:49,360 --> 00:41:52,239
Speaker 1: a national publication. But how did it wind up being

796
00:41:52,280 --> 00:41:56,080
Speaker 1: that you write a article about Wisconsin and it appears

797
00:41:56,120 --> 00:42:00,120
Speaker 1: in a bunch of different newspapers in Wisconsin. Um, the

798
00:42:00,200 --> 00:42:02,600
Speaker 1: way I did it. When I went I went to

799
00:42:02,680 --> 00:42:05,440
Speaker 1: work for Deer and Deer Inn, a magazine. I was

800
00:42:05,520 --> 00:42:08,560
Speaker 1: lucky because back then I still was independently owned, and

801
00:42:08,719 --> 00:42:11,320
Speaker 1: the owners I said to him, you know, I explained

802
00:42:11,360 --> 00:42:13,800
Speaker 1: to them that I really like newspaper work. I like

803
00:42:13,960 --> 00:42:16,920
Speaker 1: newspaper columns. I like writing a weekly column. It's something

804
00:42:16,960 --> 00:42:19,040
Speaker 1: I really took a lot of pride in and I

805
00:42:19,080 --> 00:42:21,880
Speaker 1: asked him, would you mind if I kept writing it.

806
00:42:21,960 --> 00:42:23,920
Speaker 1: I won't do it at work. I'll do it at

807
00:42:23,960 --> 00:42:26,279
Speaker 1: my own time, on the weekends and at night. But

808
00:42:26,360 --> 00:42:28,359
Speaker 1: it is this is important to me? Is this something

809
00:42:28,480 --> 00:42:33,839
Speaker 1: that I like doing? And they agreed, and then I um,

810
00:42:34,400 --> 00:42:38,040
Speaker 1: when the company I bought out the magazine about that

811
00:42:38,120 --> 00:42:39,399
Speaker 1: deer and Deer on me a year and a half

812
00:42:39,440 --> 00:42:41,680
Speaker 1: and get bought out. Well, the company that brought us

813
00:42:41,760 --> 00:42:45,040
Speaker 1: up wanted me to drop the column. Did the guys

814
00:42:45,080 --> 00:42:46,320
Speaker 1: that sold it make a lot of money when I

815
00:42:46,360 --> 00:42:48,759
Speaker 1: sold it? Yeah? I think they did and they count

816
00:42:48,800 --> 00:42:53,160
Speaker 1: pretty good. So but um so like along the way though,

817
00:42:53,200 --> 00:42:55,879
Speaker 1: I started what I did at first as I had

818
00:42:56,320 --> 00:42:59,080
Speaker 1: a woman um who was trying to launch her own

819
00:42:59,120 --> 00:43:02,000
Speaker 1: syndication service. You know, she has based in masks. And

820
00:43:02,000 --> 00:43:03,160
Speaker 1: then she asked me if she could pick up my

821
00:43:03,160 --> 00:43:07,080
Speaker 1: outdoor commas put over her package. So she she pitched

822
00:43:07,120 --> 00:43:09,120
Speaker 1: it to a couple of different newspapers like the Wisconsin

823
00:43:09,200 --> 00:43:13,279
Speaker 1: State Journal and back in those days, We're Seen Were

824
00:43:13,320 --> 00:43:17,120
Speaker 1: Seen newspaper picked it up. Ashcosh picked it up, and

825
00:43:18,239 --> 00:43:21,120
Speaker 1: Waka Shaw and our Tunnel by Milwaukee picked it up.

826
00:43:21,719 --> 00:43:23,799
Speaker 1: And then eventually I had to know Claire, and then

827
00:43:23,840 --> 00:43:26,799
Speaker 1: they dropped it. It's not all sugar and spice either.

828
00:43:27,239 --> 00:43:28,960
Speaker 1: You know, about two or three of them dropped me.

829
00:43:29,400 --> 00:43:31,520
Speaker 1: But then over time, No, my nut game was right now,

830
00:43:31,560 --> 00:43:34,240
Speaker 1: I'm at seventeen newspapers around Wisconsin. I carried my column

831
00:43:34,480 --> 00:43:37,520
Speaker 1: right now, right now, you should I know there were

832
00:43:37,600 --> 00:43:41,680
Speaker 1: seventeen newspapers in Wisconsin. Now when Doc so, when I

833
00:43:41,840 --> 00:43:44,600
Speaker 1: when Doug, I can't remember after before I met you,

834
00:43:45,200 --> 00:43:48,520
Speaker 1: Doug was talking about your work in Wisconsin and how

835
00:43:48,920 --> 00:43:52,160
Speaker 1: people in Wisconsin are so serious about deer and deer hunting.

836
00:43:53,160 --> 00:43:54,960
Speaker 1: Do you know the statistic I can't remember what it is,

837
00:43:55,040 --> 00:44:02,200
Speaker 1: but that like Texas has four times as many deer. God,

838
00:44:02,239 --> 00:44:04,279
Speaker 1: I wish I knew how this went. Texas has four

839
00:44:04,400 --> 00:44:09,080
Speaker 1: times as many deer, twice as many people, but half

840
00:44:09,120 --> 00:44:11,640
Speaker 1: as many hunters or something like that. I'm not sure

841
00:44:11,680 --> 00:44:13,680
Speaker 1: how they're I don't know their numbers in Texas. It

842
00:44:13,760 --> 00:44:17,719
Speaker 1: was just about how do in Wisconsin hunt? Yeah, if

843
00:44:17,760 --> 00:44:21,000
Speaker 1: you look, I think Wisconsin's population is about seven million,

844
00:44:21,560 --> 00:44:26,279
Speaker 1: six six seven millions in places. But it's it's um.

845
00:44:26,680 --> 00:44:28,160
Speaker 1: They give you something to do with what I done

846
00:44:28,920 --> 00:44:31,520
Speaker 1: A really neat piece of research, you know from about ten,

847
00:44:31,719 --> 00:44:34,759
Speaker 1: you know, about twenty years ago. He's not a friend

848
00:44:34,800 --> 00:44:37,759
Speaker 1: of mine. Um Tom Herberline. He made a comment in

849
00:44:37,960 --> 00:44:41,000
Speaker 1: his he was a sociologist and he studied hunting and

850
00:44:41,320 --> 00:44:44,120
Speaker 1: hunting motivations, these kind of things. And you always would

851
00:44:44,120 --> 00:44:48,440
Speaker 1: say of Wisconsin. He said, in Wisconsin, you either are

852
00:44:48,480 --> 00:44:50,480
Speaker 1: a deer hunter or you sleep with a deer hunter.

853
00:44:51,640 --> 00:44:53,960
Speaker 1: And he wasn't and he was an exaggerame he was said,

854
00:44:54,080 --> 00:44:59,640
Speaker 1: he was multitask, you know, and but you have you

855
00:44:59,760 --> 00:45:03,360
Speaker 1: have you look at an average Wisconsin household, it's unusual

856
00:45:03,440 --> 00:45:05,760
Speaker 1: not to have a family or some deer hunter somewhere

857
00:45:05,800 --> 00:45:08,759
Speaker 1: in that family, you know, immediate family. And what Doug

858
00:45:08,880 --> 00:45:11,080
Speaker 1: was talking about when he was telling me that is

859
00:45:11,160 --> 00:45:13,880
Speaker 1: he was saying that, um, not that you get like,

860
00:45:13,920 --> 00:45:15,560
Speaker 1: I don't know if you get actual death threats, but

861
00:45:15,560 --> 00:45:17,560
Speaker 1: I think like as a joke, he was saying, Pat

862
00:45:17,680 --> 00:45:23,440
Speaker 1: Durkin gets like, you know, people mad enough for you,

863
00:45:23,520 --> 00:45:25,920
Speaker 1: they wouldn't be surprised that they would give you a

864
00:45:26,040 --> 00:45:30,279
Speaker 1: death threat over white tailed politics. White tail politics is

865
00:45:30,360 --> 00:45:33,879
Speaker 1: vicious and it's it's it's not it's not always say

866
00:45:33,880 --> 00:45:37,080
Speaker 1: a deer make people stupid. It makes people stupid and

867
00:45:37,160 --> 00:45:41,840
Speaker 1: means sometimes and especially um, if you piss off a

868
00:45:41,880 --> 00:45:44,480
Speaker 1: group of people real fast, it's it's deer hunters that

869
00:45:44,640 --> 00:45:47,200
Speaker 1: they they can be very What would be a thing

870
00:45:47,280 --> 00:45:50,920
Speaker 1: that you found would piss off deer hunters? Um, Basically,

871
00:45:51,040 --> 00:45:54,480
Speaker 1: you write a column about like like, obviously wolves is

872
00:45:54,480 --> 00:45:58,359
Speaker 1: gonna piss piss him off. And if dosease pisses deer

873
00:45:58,440 --> 00:46:02,040
Speaker 1: hunters off, not this, he's somewhat not not as much

874
00:46:02,080 --> 00:46:05,600
Speaker 1: as like baiting. Baiting relates device of divisive issues. Yeah,

875
00:46:05,960 --> 00:46:08,200
Speaker 1: and people like frame for me an article. Let's say

876
00:46:08,239 --> 00:46:11,960
Speaker 1: you said I'm gonna go piss off Wisconsin's deer hunters.

877
00:46:12,880 --> 00:46:15,920
Speaker 1: I will write an article about this subject and frame

878
00:46:16,000 --> 00:46:18,440
Speaker 1: it this way. Well, it will be like the most

879
00:46:18,520 --> 00:46:21,759
Speaker 1: divisive thing you could say. I'll say, I'll try to

880
00:46:21,760 --> 00:46:25,360
Speaker 1: address that question. I will say that I've never written

881
00:46:25,400 --> 00:46:27,160
Speaker 1: a column, and I mean it's from the bottom of

882
00:46:27,160 --> 00:46:29,200
Speaker 1: my heart. I've never written a column with the intent

883
00:46:29,600 --> 00:46:32,160
Speaker 1: of pissing someone off. That's just not how I work.

884
00:46:32,320 --> 00:46:35,800
Speaker 1: I but but will write a You have to have

885
00:46:35,920 --> 00:46:39,880
Speaker 1: done it in anticipation, definitely. You know, if you bring

886
00:46:39,960 --> 00:46:43,000
Speaker 1: this topic up, whether it's some polite society or not,

887
00:46:43,800 --> 00:46:45,560
Speaker 1: people some people are gonna get mad and right and

888
00:46:45,640 --> 00:46:49,600
Speaker 1: write a rotten letter to you and bias. Figure again,

889
00:46:50,080 --> 00:46:52,520
Speaker 1: this is I don't leber. One of my core beliefs

890
00:46:52,680 --> 00:46:55,720
Speaker 1: is that I look at my writing from the newspaper

891
00:46:55,800 --> 00:46:57,520
Speaker 1: as a as something I do as kind of a

892
00:46:57,560 --> 00:47:00,200
Speaker 1: public service. I get paid for it, but I've really

893
00:47:00,280 --> 00:47:03,279
Speaker 1: believe and putting information out there. And if they don't

894
00:47:03,280 --> 00:47:05,279
Speaker 1: want to believe the information, that's up to them. I

895
00:47:05,320 --> 00:47:07,239
Speaker 1: can't change their mind, because you know, people have their

896
00:47:08,440 --> 00:47:11,879
Speaker 1: Once they have an attitude towards something, you're gonna change

897
00:47:11,880 --> 00:47:14,480
Speaker 1: their mind. But I think it's important to find the information.

898
00:47:15,360 --> 00:47:17,640
Speaker 1: And I hate to use word vet because you know,

899
00:47:17,840 --> 00:47:20,320
Speaker 1: on what really how do you go about vetting? Besides

900
00:47:20,440 --> 00:47:22,360
Speaker 1: talked a lot of people and finally get to a

901
00:47:22,360 --> 00:47:25,280
Speaker 1: point where you're saying this, this makes sense, this is factual,

902
00:47:25,560 --> 00:47:28,279
Speaker 1: and put it out there. And yeah, but that's an

903
00:47:28,320 --> 00:47:30,439
Speaker 1: interesting point to bring up right now, because we're sort

904
00:47:30,440 --> 00:47:33,320
Speaker 1: of engaged in this big cultural debate about like what

905
00:47:33,640 --> 00:47:36,560
Speaker 1: you know, this is who? I mean, I don't want

906
00:47:36,560 --> 00:47:39,279
Speaker 1: to say it f A K E News. Okay, So

907
00:47:40,400 --> 00:47:43,359
Speaker 1: we're like really caught up in this well what is right?

908
00:47:45,040 --> 00:47:50,920
Speaker 1: Like can anything be factual or yeah, listen, I think

909
00:47:50,960 --> 00:47:54,160
Speaker 1: on some things there is On some things you can

910
00:47:54,280 --> 00:48:01,240
Speaker 1: you can achieve a scholarly consensus. Okay, on some things

911
00:48:02,320 --> 00:48:06,759
Speaker 1: a scholarly consensus or an academic consensus could be evasive.

912
00:48:07,920 --> 00:48:12,279
Speaker 1: But there's a way to present a contentious argument in

913
00:48:12,360 --> 00:48:19,800
Speaker 1: a way that is transparent about what is known, Like

914
00:48:20,000 --> 00:48:24,120
Speaker 1: explain what is the where does the scholarly consensus end?

915
00:48:25,640 --> 00:48:29,400
Speaker 1: What direction do you feel based on like a reasonable

916
00:48:29,400 --> 00:48:32,080
Speaker 1: amount of work things might be going when you get

917
00:48:32,120 --> 00:48:36,960
Speaker 1: beyond the known facts and not known facts right and

918
00:48:37,080 --> 00:48:40,960
Speaker 1: be open about the things that might prove you to

919
00:48:41,000 --> 00:48:44,560
Speaker 1: be wrong. I'm not ready to give up on this

920
00:48:44,760 --> 00:48:48,800
Speaker 1: idea culturally that there's a way to present information and

921
00:48:48,880 --> 00:48:51,920
Speaker 1: it's like, because we don't know, let's just have it

922
00:48:52,000 --> 00:48:55,400
Speaker 1: be as deceptive in as wrong as possible because we

923
00:48:55,440 --> 00:48:59,680
Speaker 1: don't know. I I really firmly believe and I still

924
00:48:59,760 --> 00:49:03,000
Speaker 1: think most people think this way, that they still want facts.

925
00:49:03,360 --> 00:49:04,920
Speaker 1: I mean, there's there's a lot of people out there

926
00:49:05,000 --> 00:49:08,400
Speaker 1: that when I joke around about science not being an

927
00:49:08,440 --> 00:49:12,239
Speaker 1: alternate facts and that's that's you know, that's b s.

928
00:49:13,920 --> 00:49:17,920
Speaker 1: There's really smart people out there that you can dig

929
00:49:18,000 --> 00:49:21,000
Speaker 1: up their stuff and you can look back in you know,

930
00:49:21,080 --> 00:49:23,239
Speaker 1: thirty or forty years of research and see it. This

931
00:49:23,320 --> 00:49:25,520
Speaker 1: stuff keeps lining up and lining up and lining up.

932
00:49:26,200 --> 00:49:28,360
Speaker 1: We got this, this is this is the way it is.

933
00:49:28,840 --> 00:49:30,520
Speaker 1: You know what. You know, what would frustrate my old

934
00:49:30,520 --> 00:49:34,600
Speaker 1: man about issues of what we would call fact is

935
00:49:34,880 --> 00:49:38,719
Speaker 1: he was frustrated with anything that the that our understanding

936
00:49:38,760 --> 00:49:42,640
Speaker 1: would evolve. Okay, so if under if your understanding of

937
00:49:42,760 --> 00:49:45,680
Speaker 1: something evolves over time, he didn't see it as being

938
00:49:45,719 --> 00:49:49,920
Speaker 1: a natural process. He saw it as the minute a

939
00:49:50,040 --> 00:49:57,000
Speaker 1: position evolved change like our understanding was enhanced. He then thought, well,

940
00:49:57,640 --> 00:50:00,440
Speaker 1: I'm gonna disregard the entire system that he've made. This

941
00:50:00,960 --> 00:50:03,160
Speaker 1: so you can say, like, I mean, take it even

942
00:50:03,239 --> 00:50:06,680
Speaker 1: feels a matter of like human evolution. Okay, so you

943
00:50:06,760 --> 00:50:10,040
Speaker 1: have some idea about human evolution. You know, organisms change

944
00:50:10,040 --> 00:50:13,000
Speaker 1: over time. Corn used to be the size of your pinky.

945
00:50:13,360 --> 00:50:15,680
Speaker 1: Corn is not real big, Like an organism changes over

946
00:50:15,760 --> 00:50:18,960
Speaker 1: time based on certain pressures. But he would get into

947
00:50:19,040 --> 00:50:22,799
Speaker 1: some issue of like like human human evolution is almost

948
00:50:22,840 --> 00:50:25,520
Speaker 1: too controversial to demonstrate my point. Let's they were talking

949
00:50:25,520 --> 00:50:29,560
Speaker 1: about what kills dear fonds. Okay, so we have an

950
00:50:29,640 --> 00:50:35,200
Speaker 1: understanding that that uh, black bears kill deer funds. Then

951
00:50:35,280 --> 00:50:37,560
Speaker 1: someone will come up with a thing that says, well,

952
00:50:37,600 --> 00:50:39,839
Speaker 1: you know, we never looked at bobcats, and I were

953
00:50:39,840 --> 00:50:42,759
Speaker 1: looking at bobcats. Realize the bobcats are significant killer deer fons.

954
00:50:43,000 --> 00:50:45,399
Speaker 1: And he'd be like, but I was told that black

955
00:50:45,480 --> 00:50:48,560
Speaker 1: bears do it now, never mind knowing no ship. Well,

956
00:50:49,120 --> 00:50:51,680
Speaker 1: you know, because like he hated the idea that you

957
00:50:51,680 --> 00:50:54,479
Speaker 1: would have to sort of stay tuned all the time

958
00:50:55,000 --> 00:50:57,799
Speaker 1: as new things came in. And then when new things

959
00:50:57,880 --> 00:50:59,959
Speaker 1: came in, it wasn't that we were dismissing the body

960
00:51:00,040 --> 00:51:03,600
Speaker 1: of knowledges. Were engaged in this activity that is not

961
00:51:03,840 --> 00:51:06,960
Speaker 1: perfect and changes over time, but just trying to maintain

962
00:51:07,120 --> 00:51:09,600
Speaker 1: an understanding of the world that we live in. Yeah,

963
00:51:10,800 --> 00:51:13,320
Speaker 1: this friend of mine, Hybridline, has a great saying about

964
00:51:13,400 --> 00:51:16,960
Speaker 1: research and the whole idea of trying to improve our knowledge,

965
00:51:16,960 --> 00:51:20,560
Speaker 1: improve our understanding things. He makes this comment that he said,

966
00:51:20,560 --> 00:51:25,160
Speaker 1: all all research is either trivial or wrong. Either it

967
00:51:25,280 --> 00:51:29,120
Speaker 1: proves what we already know, which is trivial, or it

968
00:51:29,200 --> 00:51:33,400
Speaker 1: proves what will never believe you know. And and I

969
00:51:33,520 --> 00:51:36,960
Speaker 1: can think in deer hunting it's constant. I mean, but

970
00:51:37,120 --> 00:51:39,719
Speaker 1: you're talking this research earlier about oh yeah, the article

971
00:51:39,719 --> 00:51:41,680
Speaker 1: you would write through is the article that would piss

972
00:51:41,680 --> 00:51:44,080
Speaker 1: everybody off, right, And all you gotta do in many

973
00:51:44,120 --> 00:51:48,000
Speaker 1: cases with a certain crowd is go back and dig

974
00:51:48,120 --> 00:51:52,000
Speaker 1: up the final results of some recent research which everyone

975
00:51:52,120 --> 00:51:54,600
Speaker 1: was clamoring for when it was like this. There was

976
00:51:54,640 --> 00:51:56,680
Speaker 1: a great study that was done by the Wisconsin Digging

977
00:51:56,719 --> 00:52:00,760
Speaker 1: are from about two thousand through about two thousand thirteen

978
00:52:00,960 --> 00:52:04,440
Speaker 1: looked at fawn survival, looked at over winter survival, and

979
00:52:04,560 --> 00:52:07,919
Speaker 1: two different areas went up northwestern Wisconsin, went on north

980
00:52:08,160 --> 00:52:11,960
Speaker 1: eastern Wisconsin, just north of me. And what was really

981
00:52:12,040 --> 00:52:14,600
Speaker 1: interesting in the in the farm country of eastern Wisconsin

982
00:52:14,800 --> 00:52:17,640
Speaker 1: right above me, the number one killer of of the

983
00:52:17,719 --> 00:52:23,759
Speaker 1: fawns was, uh, we're being killed by winter starvation, you know.

984
00:52:24,120 --> 00:52:27,360
Speaker 1: And no one thought they were starving at starvation. And

985
00:52:27,600 --> 00:52:29,759
Speaker 1: in those days, I mean in just recent times, you

986
00:52:29,800 --> 00:52:33,120
Speaker 1: just thought it wasn't happening. And you look at, um,

987
00:52:34,360 --> 00:52:36,279
Speaker 1: what else is killing him? All road kills are but

988
00:52:36,360 --> 00:52:38,759
Speaker 1: getting up four or five percent of them sometimes and

989
00:52:39,080 --> 00:52:41,160
Speaker 1: and but then all these things were done. All it's

990
00:52:41,200 --> 00:52:44,279
Speaker 1: really good information. It was all released. People like me

991
00:52:44,360 --> 00:52:46,479
Speaker 1: wrote about it, people like and then I got people

992
00:52:46,640 --> 00:52:48,719
Speaker 1: right into me saying this, this is all bullshit. You know,

993
00:52:48,800 --> 00:52:50,919
Speaker 1: this is just the d n R spinning their fast

994
00:52:51,000 --> 00:52:54,280
Speaker 1: because the thing they didn't like was because in northwestern Wisconsin,

995
00:52:54,320 --> 00:52:57,359
Speaker 1: where there's wolves, wolves were not found to be much

996
00:52:57,400 --> 00:52:59,880
Speaker 1: of a productor at all for falls. Yeah, they this

997
00:53:00,080 --> 00:53:02,240
Speaker 1: was a cover up. So so they have this research,

998
00:53:02,320 --> 00:53:04,279
Speaker 1: they didn't like the way it turned out, so they disregarded.

999
00:53:04,680 --> 00:53:06,600
Speaker 1: They did the same thing with them they did us.

1000
00:53:07,320 --> 00:53:13,239
Speaker 1: Did I really intense sociological research into public attitudes to

1001
00:53:13,280 --> 00:53:16,080
Speaker 1: our wolves. All the people who don't like don't like wolves,

1002
00:53:16,120 --> 00:53:18,719
Speaker 1: which is a lot of them. We're convinced that when

1003
00:53:18,800 --> 00:53:21,000
Speaker 1: they do this research, we're not find out that Wisconsin

1004
00:53:21,080 --> 00:53:23,839
Speaker 1: I really don't like wolves, even the especially the ones.

1005
00:53:24,480 --> 00:53:26,800
Speaker 1: Um they knew the people down in still in Wisconsin

1006
00:53:26,880 --> 00:53:29,640
Speaker 1: who don't deal with wolves will like them. Those are

1007
00:53:29,640 --> 00:53:33,640
Speaker 1: as people like them the most right and New Jersey can't. Ladies,

1008
00:53:33,719 --> 00:53:36,759
Speaker 1: and the person like the least likely that like you know,

1009
00:53:37,480 --> 00:53:40,480
Speaker 1: and that's that's very true. That I'll get to that though.

1010
00:53:40,800 --> 00:53:42,520
Speaker 1: But you know that the thing they found though is

1011
00:53:42,560 --> 00:53:46,200
Speaker 1: even in wolf country, the majority of people still overall

1012
00:53:46,400 --> 00:53:50,920
Speaker 1: supportive wolves, but define defined like wolves. Well that's that's

1013
00:53:50,960 --> 00:53:53,160
Speaker 1: that's a good question. That's a good good point, you know.

1014
00:53:53,320 --> 00:53:55,280
Speaker 1: And it basically it's the fact that I don't dislike

1015
00:53:55,320 --> 00:53:57,759
Speaker 1: I don't dislike wolves. I love them. I think, I

1016
00:53:57,800 --> 00:54:01,719
Speaker 1: think I like Oh, I like all wildlife, including and

1017
00:54:01,760 --> 00:54:04,720
Speaker 1: I have a special place in my heart for the wolf.

1018
00:54:05,880 --> 00:54:07,920
Speaker 1: Does it mean you like him or like? What does

1019
00:54:07,960 --> 00:54:10,800
Speaker 1: that mean? Well, if I like them, there and I

1020
00:54:11,120 --> 00:54:13,840
Speaker 1: like them to be managed by the state, and I

1021
00:54:14,200 --> 00:54:18,000
Speaker 1: have and I believe, based on consteadable bit of research

1022
00:54:18,200 --> 00:54:21,959
Speaker 1: that we have a sustainable population in the northern Great

1023
00:54:22,040 --> 00:54:24,920
Speaker 1: Lakes that can be managed as a renewable resource. Does

1024
00:54:24,960 --> 00:54:27,239
Speaker 1: that put me in liking or not liking? Put you

1025
00:54:27,239 --> 00:54:29,880
Speaker 1: in the liking like? Like, I've been a liking camp too,

1026
00:54:29,920 --> 00:54:32,280
Speaker 1: because I actually drew a wolf tag in two thousand

1027
00:54:32,280 --> 00:54:34,719
Speaker 1: and twelve and they first issued him, and I found

1028
00:54:34,760 --> 00:54:37,000
Speaker 1: out real quickly I don't know the wolf funding to

1029
00:54:37,080 --> 00:54:40,359
Speaker 1: be very effective at it, but I still be kind

1030
00:54:40,400 --> 00:54:43,080
Speaker 1: as a liker. Oh yeah, definitely. But but I should

1031
00:54:43,120 --> 00:54:45,640
Speaker 1: say that I think I think the way they they

1032
00:54:45,719 --> 00:54:49,319
Speaker 1: worded it in this in this research was basically one

1033
00:54:49,360 --> 00:54:51,239
Speaker 1: of the one of the things was do you want

1034
00:54:51,520 --> 00:54:55,160
Speaker 1: more walls right now? As the wolf wolf numbers we

1035
00:54:55,200 --> 00:54:58,120
Speaker 1: have right now? Is that adequate? Is that inadequate? Is

1036
00:54:58,160 --> 00:55:01,560
Speaker 1: that too many? Too few? And most people, like I

1037
00:55:01,600 --> 00:55:04,439
Speaker 1: think it's like in a six range, things are okay

1038
00:55:04,480 --> 00:55:06,200
Speaker 1: the way they are. They didn't have a problem with

1039
00:55:06,360 --> 00:55:08,400
Speaker 1: with the wolf numbers, whereas a lot of the hunters

1040
00:55:08,440 --> 00:55:11,239
Speaker 1: don't want that many wolves. You know, the hunters would say,

1041
00:55:11,840 --> 00:55:14,040
Speaker 1: you know, the d n R says there's seven d

1042
00:55:14,160 --> 00:55:16,600
Speaker 1: wall as well, there's more like two thousand. So I

1043
00:55:16,880 --> 00:55:19,200
Speaker 1: always asked him, well, where do you get your number?

1044
00:55:20,040 --> 00:55:21,400
Speaker 1: I can tell you how the how the DINR got

1045
00:55:21,440 --> 00:55:23,880
Speaker 1: there in number. I can try the survey, showy that

1046
00:55:24,000 --> 00:55:26,080
Speaker 1: that that field work that was done to get that number.

1047
00:55:26,400 --> 00:55:28,719
Speaker 1: So where do you get this two thousand number? You know?

1048
00:55:29,080 --> 00:55:32,439
Speaker 1: But but hold on a minute. I know we're getting

1049
00:55:32,440 --> 00:55:34,239
Speaker 1: distracted a lot. But they had a we had a

1050
00:55:34,320 --> 00:55:39,200
Speaker 1: guest um right on this year podcast, Frank mcmahnon, right,

1051
00:55:40,320 --> 00:55:45,120
Speaker 1: who runs the U s GS Grizzly Bear program in

1052
00:55:45,160 --> 00:55:48,640
Speaker 1: the Greater Yellstone ecosystem. You ask him how many are there?

1053
00:55:49,920 --> 00:55:54,719
Speaker 1: He'll give you a number and you'll say, but probably more, yeah, yeah,

1054
00:55:55,120 --> 00:55:59,400
Speaker 1: or there's sixty two, but probably more, And like, why

1055
00:55:59,480 --> 00:56:01,880
Speaker 1: did you tell me six two, because that's the model

1056
00:56:01,960 --> 00:56:05,120
Speaker 1: we use, but we know that that model has changed.

1057
00:56:05,280 --> 00:56:07,960
Speaker 1: We have an updated the model. There's almost certainly more.

1058
00:56:08,160 --> 00:56:09,480
Speaker 1: But I said, but if I put a gun to

1059
00:56:09,600 --> 00:56:11,919
Speaker 1: your head and said how many are there, what would

1060
00:56:11,920 --> 00:56:17,440
Speaker 1: you say? Sixty two? But probably more to a to

1061
00:56:17,560 --> 00:56:22,279
Speaker 1: a wide margin more. Well, that's the thing. I'd say,

1062
00:56:22,360 --> 00:56:24,719
Speaker 1: Well what's this wide margin? Because it depends on how

1063
00:56:24,760 --> 00:56:27,440
Speaker 1: you're modeling them, And sometimes you might have a model

1064
00:56:27,520 --> 00:56:29,879
Speaker 1: like like in this case. I hate to go way back,

1065
00:56:29,920 --> 00:56:32,400
Speaker 1: but here's what happened in this case. When they modeled

1066
00:56:32,400 --> 00:56:36,160
Speaker 1: out how many they had, it was based on it

1067
00:56:36,280 --> 00:56:42,160
Speaker 1: was based on the home range of females. Okay, knowing

1068
00:56:42,239 --> 00:56:46,640
Speaker 1: that females had some fidelity to their home range and

1069
00:56:46,760 --> 00:56:51,200
Speaker 1: we're generally intolerant of other breeding age females near them.

1070
00:56:52,120 --> 00:56:54,320
Speaker 1: And that model was drawn up at a time before

1071
00:56:54,800 --> 00:56:56,680
Speaker 1: that model was drawn up at a time when they

1072
00:56:56,760 --> 00:57:01,240
Speaker 1: hadn't really dispersed across suitable habitat. So what they found

1073
00:57:01,360 --> 00:57:04,640
Speaker 1: over time is that they're more comfortable living closer together.

1074
00:57:05,040 --> 00:57:07,319
Speaker 1: They don't quite know how much, though, So when they

1075
00:57:07,440 --> 00:57:09,480
Speaker 1: model it out, they come up with a number. But

1076
00:57:09,640 --> 00:57:12,319
Speaker 1: all the experts like, but they're much more comfortable living

1077
00:57:12,360 --> 00:57:15,279
Speaker 1: closer together. Now we haven't adjusted the model, so I

1078
00:57:15,480 --> 00:57:17,840
Speaker 1: know there are more, but the ants we have to

1079
00:57:17,960 --> 00:57:21,120
Speaker 1: have because this is the model that we put forth

1080
00:57:21,440 --> 00:57:23,840
Speaker 1: tells us this, even though we all know it's probably wrong.

1081
00:57:24,240 --> 00:57:25,720
Speaker 1: So I think that it is like you can go

1082
00:57:25,760 --> 00:57:26,840
Speaker 1: out and do like if you go out and just

1083
00:57:26,880 --> 00:57:29,680
Speaker 1: do account, Okay, you can go out. Let let's see

1084
00:57:29,680 --> 00:57:31,320
Speaker 1: you go out and do a survey where you're flying

1085
00:57:31,400 --> 00:57:34,240
Speaker 1: trans sex out of a helicopter. Count wolves and you

1086
00:57:34,320 --> 00:57:37,320
Speaker 1: can be I can damn sure tell you that there

1087
00:57:37,320 --> 00:57:42,680
Speaker 1: are seven hundred, probably a lot that we missed. I

1088
00:57:42,880 --> 00:57:44,720
Speaker 1: can damn sure tell you their seven hundred. Now you're

1089
00:57:44,720 --> 00:57:48,360
Speaker 1: gonna have two things. The non likers of wolves are

1090
00:57:48,400 --> 00:57:51,440
Speaker 1: gonna pay a lot of attention to the probably more

1091
00:57:52,240 --> 00:57:54,600
Speaker 1: the likers in the case in this way you're sketching on.

1092
00:57:54,960 --> 00:57:57,160
Speaker 1: The lakers are gonna pay a lot of attention to

1093
00:57:57,320 --> 00:57:59,960
Speaker 1: that minimal known number, and that's very important to them

1094
00:58:00,000 --> 00:58:02,440
Speaker 1: because they want to present it as not as numerous,

1095
00:58:02,960 --> 00:58:06,600
Speaker 1: because their goal is to keep them listed. Yeah, and

1096
00:58:06,640 --> 00:58:09,200
Speaker 1: the other people's goal, their tendency is the de list.

1097
00:58:09,280 --> 00:58:11,960
Speaker 1: So they're gonna like that bigger number you find that

1098
00:58:12,040 --> 00:58:13,720
Speaker 1: all the time in this kind of Yeah. And the

1099
00:58:13,960 --> 00:58:16,200
Speaker 1: thing that where I get sick of that this whole

1100
00:58:16,200 --> 00:58:18,959
Speaker 1: discussion is that no one really knows for certain You can't,

1101
00:58:19,000 --> 00:58:21,440
Speaker 1: you can't. Like The point I think we should always

1102
00:58:21,480 --> 00:58:23,320
Speaker 1: make is that you look at our country. We can't

1103
00:58:23,360 --> 00:58:26,120
Speaker 1: even agree how to count people in this country. We

1104
00:58:26,520 --> 00:58:29,760
Speaker 1: have real, honest to God important fights over a census

1105
00:58:29,920 --> 00:58:32,840
Speaker 1: for people. So if you can't count noses on humans,

1106
00:58:33,280 --> 00:58:36,040
Speaker 1: we know, we know our addresses, they pretty much can

1107
00:58:36,240 --> 00:58:37,760
Speaker 1: go into our homes and figure out what we got.

1108
00:58:38,120 --> 00:58:41,640
Speaker 1: Even then you're still arguing about But um, that's the

1109
00:58:41,760 --> 00:58:44,240
Speaker 1: point that it's in the real famous wolf bitlogists make.

1110
00:58:44,280 --> 00:58:47,440
Speaker 1: Whether it's val guys. He's not specifically a wolf biologist,

1111
00:58:47,480 --> 00:58:51,080
Speaker 1: but yeah, he knows his stuff. Though there's a guy

1112
00:58:51,440 --> 00:58:53,400
Speaker 1: I forget his name is over in Italy. He's a

1113
00:58:53,720 --> 00:58:58,240
Speaker 1: Europe's most famous wolf researcher. The point this Italian guy makes,

1114
00:58:58,400 --> 00:59:01,600
Speaker 1: and I think the vale point he says, instead of

1115
00:59:01,840 --> 00:59:05,960
Speaker 1: worrying about individual numbers of wolves, be looking at something

1116
00:59:06,040 --> 00:59:08,080
Speaker 1: that matters. And what matters is how what kind of

1117
00:59:08,160 --> 00:59:12,080
Speaker 1: damage they're doing. Let's let's quantify what's what's the damage.

1118
00:59:12,120 --> 00:59:14,600
Speaker 1: We can quantify that that's much easier to get a

1119
00:59:14,680 --> 00:59:16,880
Speaker 1: handle on than how many wolves are out there now

1120
00:59:16,920 --> 00:59:19,320
Speaker 1: if they're not they're out there and they're not killing livestock,

1121
00:59:19,320 --> 00:59:22,240
Speaker 1: they're not killing uncle its or not, they're not doing this.

1122
00:59:23,600 --> 00:59:25,160
Speaker 1: Who cures me numbers are out there? Do you really

1123
00:59:25,240 --> 00:59:27,320
Speaker 1: need to need to have that number that really Manselow's

1124
00:59:27,320 --> 00:59:30,000
Speaker 1: wolves or do anything? And no, you don't. You know

1125
00:59:30,560 --> 00:59:33,440
Speaker 1: the speech price I think Americans and this is one

1126
00:59:33,480 --> 00:59:36,080
Speaker 1: thing that rest of the wildlife ballance around the world

1127
00:59:36,640 --> 00:59:39,800
Speaker 1: really marvelous. The way we hang up on numbers where

1128
00:59:39,800 --> 00:59:43,000
Speaker 1: there's deer numbers that seems like it's deer and wolves

1129
00:59:43,160 --> 00:59:45,360
Speaker 1: especially that people really worry about, you know what, what's

1130
00:59:45,400 --> 00:59:48,080
Speaker 1: our what's our number? And that in Wisconsins we fight

1131
00:59:48,120 --> 00:59:50,120
Speaker 1: about numbers all the time and we don't know what

1132
00:59:50,120 --> 00:59:53,560
Speaker 1: we're talking about. I mean, it's just And then then

1133
00:59:53,600 --> 00:59:55,000
Speaker 1: you get in the arguments wall as a deer for

1134
00:59:55,080 --> 00:59:58,400
Speaker 1: square mile of habitat and who judges the habitat quality?

1135
00:59:58,480 --> 01:00:03,000
Speaker 1: And you end up these crazy you know where people

1136
01:00:03,080 --> 01:00:06,480
Speaker 1: get mad type of discussions because there's nothing anyone can

1137
01:00:06,520 --> 01:00:08,720
Speaker 1: all agree on. It's like trying to define trophy hunting.

1138
01:00:08,800 --> 01:00:11,240
Speaker 1: You know, they're asking people you're like trophy hunting. Well,

1139
01:00:11,280 --> 01:00:14,280
Speaker 1: you don't even define what that means. But what Doug

1140
01:00:14,400 --> 01:00:16,480
Speaker 1: was giving me a number the r day for here, Okay,

1141
01:00:16,840 --> 01:00:20,560
Speaker 1: fifty deer per square mile of suitable habitat. Oh yeah,

1142
01:00:21,480 --> 01:00:24,480
Speaker 1: and that you can't even believe that. But but then

1143
01:00:24,520 --> 01:00:27,360
Speaker 1: again and then then then that, then that moves around

1144
01:00:27,400 --> 01:00:30,160
Speaker 1: to you know, if you do these aerial surveys they

1145
01:00:30,240 --> 01:00:33,080
Speaker 1: do in the winter, double check it. Typically what they

1146
01:00:33,160 --> 01:00:36,320
Speaker 1: find is that those aerial surveys miss a lot too,

1147
01:00:36,800 --> 01:00:38,720
Speaker 1: even with snow covering the ground, and they still miss

1148
01:00:38,720 --> 01:00:40,520
Speaker 1: a lot of deers. So it's all it's why something

1149
01:00:40,560 --> 01:00:44,160
Speaker 1: to argue about. And there're thing that was interesting though

1150
01:00:44,160 --> 01:00:47,320
Speaker 1: about getting back to wolves, and you talked about all

1151
01:00:47,360 --> 01:00:49,960
Speaker 1: of the people in New Jersey love wolves not constant.

1152
01:00:50,120 --> 01:00:53,080
Speaker 1: The one thing that there's a really cool but munch

1153
01:00:53,120 --> 01:00:56,240
Speaker 1: of research done about fifteen years ago about wolves and

1154
01:00:56,400 --> 01:00:59,040
Speaker 1: people public attitudes trey wolves. And what they found is

1155
01:00:59,080 --> 01:01:04,960
Speaker 1: that the pop larity of wolves really ok that's zenas

1156
01:01:05,400 --> 01:01:08,080
Speaker 1: back in the mid nineteen hundreds when they really weren't

1157
01:01:08,080 --> 01:01:11,560
Speaker 1: many wolves really people really around the world, And this

1158
01:01:11,720 --> 01:01:13,400
Speaker 1: is they went back and they looked at all these

1159
01:01:13,400 --> 01:01:16,280
Speaker 1: different sociological studies on at two story walls from all

1160
01:01:16,280 --> 01:01:19,640
Speaker 1: of the world, you know, Europe, Russia, um, even down

1161
01:01:19,720 --> 01:01:22,160
Speaker 1: into the Middle Eastern countries that you know in the

1162
01:01:22,200 --> 01:01:26,000
Speaker 1: mountains areas, and they looked at the North American continent

1163
01:01:26,400 --> 01:01:29,160
Speaker 1: and they fallen that. Yeah, that peaked around in the

1164
01:01:29,280 --> 01:01:32,280
Speaker 1: night night at Yeah, and as soon I started calm

1165
01:01:32,320 --> 01:01:35,720
Speaker 1: back every place that they looked was the more you

1166
01:01:35,840 --> 01:01:38,440
Speaker 1: dealt with the wolves of less popular they became. Yeah,

1167
01:01:38,520 --> 01:01:42,480
Speaker 1: that's my feeling about the bald eagle. If bald eagles

1168
01:01:42,520 --> 01:01:47,440
Speaker 1: were smart, they would stop reproducing so effectively. Because they

1169
01:01:47,560 --> 01:01:51,200
Speaker 1: had they were extraordinarily popular, and they're still pretty popular,

1170
01:01:51,440 --> 01:01:53,560
Speaker 1: but they're getting so numerous. I feel that they're gonna

1171
01:01:53,640 --> 01:01:56,640
Speaker 1: feel their popularity WANs not that they're a problem animal

1172
01:01:56,640 --> 01:01:58,360
Speaker 1: to anyone, but you know, I mean, but I still

1173
01:01:58,400 --> 01:02:01,480
Speaker 1: read people like, holy, an eagle, you know, but he'd

1174
01:02:01,480 --> 01:02:03,600
Speaker 1: be like, well, the oh, there's they're they're everywhere. Now.

1175
01:02:04,040 --> 01:02:05,800
Speaker 1: It's like it's it's gonna come a time when people

1176
01:02:05,800 --> 01:02:07,400
Speaker 1: are gonna see an eagle. They're gonna think about it

1177
01:02:07,480 --> 01:02:11,360
Speaker 1: like they think when they see a robin. Yeah, because

1178
01:02:11,400 --> 01:02:16,000
Speaker 1: they got so popular in their absence. Well, I mean,

1179
01:02:16,040 --> 01:02:18,920
Speaker 1: it's funny about the bald eagle is that people a

1180
01:02:19,000 --> 01:02:22,200
Speaker 1: lot of people who romanticize them, they're bummed out, they're

1181
01:02:22,240 --> 01:02:24,800
Speaker 1: disappointed when they see a bald eagle feeding out a carcass,

1182
01:02:26,480 --> 01:02:29,479
Speaker 1: even though they're a scavenger. Yeah, I mean it hurts

1183
01:02:29,520 --> 01:02:32,480
Speaker 1: something that that's blue there. It's like finding out your

1184
01:02:32,720 --> 01:02:35,200
Speaker 1: your mother was cheating on your dad or something, you know.

1185
01:02:35,880 --> 01:02:37,680
Speaker 1: You know, when when it was put out that the

1186
01:02:37,760 --> 01:02:40,200
Speaker 1: idea that the bald egil be the national and animal,

1187
01:02:41,240 --> 01:02:47,800
Speaker 1: Franklin criticized it. Ben Franklin, he's he's also mistakenly credited

1188
01:02:47,880 --> 01:02:50,560
Speaker 1: with putting forth the turkey, which he did not do.

1189
01:02:51,440 --> 01:02:53,680
Speaker 1: But they said, okay, the eagle be the national animal

1190
01:02:54,080 --> 01:02:57,919
Speaker 1: or national bird, and Ben Franklin thought, like, why would

1191
01:02:57,960 --> 01:03:05,000
Speaker 1: you have like a carrion eater, lowly garbage eater, And

1192
01:03:05,080 --> 01:03:08,080
Speaker 1: he says, kind of people think he argues, its facetious

1193
01:03:08,080 --> 01:03:09,600
Speaker 1: that I've read what he wrote, and you know, they

1194
01:03:09,680 --> 01:03:12,320
Speaker 1: had a different style, so you can't like read between

1195
01:03:12,400 --> 01:03:14,960
Speaker 1: the lines quite as effectively as you could read between

1196
01:03:14,960 --> 01:03:18,160
Speaker 1: the lines of a contemporary writer and thinker. But he

1197
01:03:18,280 --> 01:03:19,920
Speaker 1: had said, like you might as well do it with

1198
01:03:20,040 --> 01:03:24,320
Speaker 1: the damn turkey, because least he's vain, right, he's silly

1199
01:03:24,360 --> 01:03:26,760
Speaker 1: in vain and he made the point in there I

1200
01:03:26,840 --> 01:03:30,000
Speaker 1: think too about um, he's got he's got guts basically

1201
01:03:30,040 --> 01:03:33,280
Speaker 1: because he'll attack that that red corded British guy if

1202
01:03:33,280 --> 01:03:34,800
Speaker 1: he shows up in your garden. You know, that kind

1203
01:03:34,840 --> 01:03:37,520
Speaker 1: of thing. And so, yeah, he didn't like that you

1204
01:03:37,560 --> 01:03:41,360
Speaker 1: didn't want some garbage eating like well, even question that

1205
01:03:41,440 --> 01:03:43,600
Speaker 1: eagles courage because because the little birds attack it and

1206
01:03:43,680 --> 01:03:46,320
Speaker 1: can drive it away from you know. Yeah. Yeah, So

1207
01:03:46,560 --> 01:03:49,560
Speaker 1: so there's always neat little things that you find about Franklin.

1208
01:03:49,680 --> 01:03:51,840
Speaker 1: He was a ladies man. Oh yeah, definitely was. I

1209
01:03:51,880 --> 01:03:57,480
Speaker 1: don't want to get into that. But so you still

1210
01:03:57,480 --> 01:04:00,480
Speaker 1: haven't answered my question. I'm sorry if you want if

1211
01:04:00,520 --> 01:04:02,920
Speaker 1: you were going to write, okay, the article that was

1212
01:04:03,000 --> 01:04:06,440
Speaker 1: going to be most insulting to Wisconsin deer hunters, like

1213
01:04:06,600 --> 01:04:11,840
Speaker 1: like Doug here, Okay, what would the article be right

1214
01:04:11,880 --> 01:04:14,400
Speaker 1: now in the current climate, I guess if I wanted to,

1215
01:04:15,000 --> 01:04:19,560
Speaker 1: and I actually kind of have written. I just don't want.

1216
01:04:19,720 --> 01:04:23,640
Speaker 1: You know, one thing I try to do people, Um no,

1217
01:04:23,800 --> 01:04:28,960
Speaker 1: I some people will accuse me of obsessing on an issue. Yeah,

1218
01:04:29,160 --> 01:04:32,480
Speaker 1: and well, in this case, the thing I recommended a

1219
01:04:32,520 --> 01:04:34,840
Speaker 1: few years ago, people arise bashed on me about, um,

1220
01:04:35,320 --> 01:04:36,800
Speaker 1: well you don't like what the din I was doing

1221
01:04:36,840 --> 01:04:38,640
Speaker 1: on how they're managing c w ds. What would you

1222
01:04:38,720 --> 01:04:41,440
Speaker 1: do if you were the king? And I said, well,

1223
01:04:41,480 --> 01:04:43,520
Speaker 1: the first thing I do is have just to earn

1224
01:04:43,560 --> 01:04:45,240
Speaker 1: a bucket, have a double ear in a book. You

1225
01:04:45,280 --> 01:04:47,360
Speaker 1: don't shoot a buck until you shoot at least two

1226
01:04:47,360 --> 01:04:52,080
Speaker 1: antless deer. Okay, And that dog thinks that you shouldn't

1227
01:04:52,080 --> 01:04:55,640
Speaker 1: be able to shoot any bucks. Well, I don't think

1228
01:04:55,680 --> 01:04:58,080
Speaker 1: that that's not true. I don't think that doesn't really

1229
01:04:58,120 --> 01:05:00,480
Speaker 1: think that. I was trying to make good point at

1230
01:05:00,520 --> 01:05:06,840
Speaker 1: the County Advisory Committee meeting and because people just don't

1231
01:05:06,880 --> 01:05:08,600
Speaker 1: like to be forced to do something, and I think

1232
01:05:08,680 --> 01:05:12,480
Speaker 1: that's the biggest not go yeah, And that's really just

1233
01:05:12,560 --> 01:05:14,680
Speaker 1: part of our character. We just don't like being told

1234
01:05:14,720 --> 01:05:18,880
Speaker 1: what to do. We want until there are none left.

1235
01:05:21,240 --> 01:05:24,360
Speaker 1: So so that that that thing does that. Every time

1236
01:05:24,400 --> 01:05:27,000
Speaker 1: I write about, um, those kind of things where we

1237
01:05:27,280 --> 01:05:32,160
Speaker 1: should mandate something and make people, they get mad. And

1238
01:05:32,440 --> 01:05:34,800
Speaker 1: even the people who are more reasonable get mad at that.

1239
01:05:34,840 --> 01:05:36,360
Speaker 1: They don't. They don't they don't want to be told

1240
01:05:36,400 --> 01:05:39,560
Speaker 1: what to do. But why why was it that you

1241
01:05:39,680 --> 01:05:42,200
Speaker 1: guys and This isn't This is the opposite. This is

1242
01:05:42,240 --> 01:05:46,240
Speaker 1: not mandating, This is unmandating. This is instead of instead

1243
01:05:46,280 --> 01:05:52,280
Speaker 1: of restricting people's choices, you were expanding people's choices, giving

1244
01:05:52,320 --> 01:05:56,200
Speaker 1: them more opportunity for the exercising of free will. Do

1245
01:05:56,280 --> 01:05:57,960
Speaker 1: you guys want to make it that you could wear

1246
01:05:59,280 --> 01:06:05,160
Speaker 1: pink instead that passed? Do you guys really feel that

1247
01:06:05,280 --> 01:06:07,960
Speaker 1: there were women who were like goad Man, I want

1248
01:06:08,000 --> 01:06:11,480
Speaker 1: to hunt so bad, but I am not going into

1249
01:06:11,480 --> 01:06:15,320
Speaker 1: the woods with that blaze orange. I think it's it's

1250
01:06:15,400 --> 01:06:18,000
Speaker 1: it's a it's a color that, um, some women like

1251
01:06:18,400 --> 01:06:20,920
Speaker 1: and some women don't like it. They always you're patronizing

1252
01:06:20,960 --> 01:06:23,680
Speaker 1: them by saying that women want pink. But um, a

1253
01:06:23,760 --> 01:06:26,920
Speaker 1: friend of mine who's in the garment hunt hunting garment industry,

1254
01:06:27,720 --> 01:06:30,919
Speaker 1: he said, when they start making mixing pink hot pink

1255
01:06:30,960 --> 01:06:34,680
Speaker 1: into their um into the hunting clothing for Wisconsin, you

1256
01:06:34,720 --> 01:06:37,000
Speaker 1: know it's basically a Wisconsin market. Now. I don't know

1257
01:06:37,000 --> 01:06:39,760
Speaker 1: if any other state has that has passed blaze pink

1258
01:06:39,880 --> 01:06:44,480
Speaker 1: as an acceptable color, but in Wisconsin it sells. Apparently

1259
01:06:44,520 --> 01:06:48,800
Speaker 1: it was a special session of kind like that went

1260
01:06:48,920 --> 01:06:51,600
Speaker 1: to law like faster than any other. Well, it was

1261
01:06:51,600 --> 01:06:53,720
Speaker 1: because it was. It's an easy lot of pass It's

1262
01:06:53,800 --> 01:06:57,280
Speaker 1: like like I was talking to the Honest's father today

1263
01:06:57,320 --> 01:06:59,720
Speaker 1: about um a careent proposal. I think it's telling you

1264
01:06:59,760 --> 01:07:02,640
Speaker 1: about to about the guy wanting to make the wild

1265
01:07:02,680 --> 01:07:06,040
Speaker 1: turkey or state game bird. And Janice's father read a

1266
01:07:06,080 --> 01:07:08,240
Speaker 1: waste as well. That's kind of law politicians life because

1267
01:07:08,280 --> 01:07:12,200
Speaker 1: it doesn't doesn't cause me angst. It's easily passed, goes

1268
01:07:12,280 --> 01:07:15,240
Speaker 1: through usually in one session, and it makes him feel

1269
01:07:15,320 --> 01:07:18,320
Speaker 1: good and like. And Wisconsin is famous for these kind

1270
01:07:18,360 --> 01:07:21,520
Speaker 1: of things, designating this thing and that thing as a state.

1271
01:07:21,800 --> 01:07:24,040
Speaker 1: You know, we have a state rock. I don't know

1272
01:07:24,080 --> 01:07:27,520
Speaker 1: what it is, but we have one in Michigan. Okay,

1273
01:07:27,640 --> 01:07:31,200
Speaker 1: thank you, and and uh and then yeah, I think

1274
01:07:31,320 --> 01:07:35,840
Speaker 1: we have a state muffin. You know. I think it's like, yeah,

1275
01:07:37,040 --> 01:07:40,960
Speaker 1: you tell me that I was not I probably was.

1276
01:07:41,400 --> 01:07:49,200
Speaker 1: And and I remember getting back into the state if

1277
01:07:49,360 --> 01:07:54,760
Speaker 1: I always remember um. Charles Curralt, he turned around Wisconsin

1278
01:07:54,840 --> 01:07:58,440
Speaker 1: one time and on his little TV show that he

1279
01:07:58,480 --> 01:08:02,240
Speaker 1: had a great program. He after around Wisconsin one time

1280
01:08:02,320 --> 01:08:06,000
Speaker 1: he noticed that every little town b Wiscont, like where

1281
01:08:06,000 --> 01:08:09,920
Speaker 1: I live, iola bull hunting Capital of the World. Fremont, Wisconsin,

1282
01:08:10,240 --> 01:08:14,400
Speaker 1: while capital of the world. Yeah, and you find Charles

1283
01:08:14,480 --> 01:08:16,599
Speaker 1: kraw when are all these little cities that got their

1284
01:08:16,760 --> 01:08:18,479
Speaker 1: Capital of the world type things, And he said, I

1285
01:08:18,600 --> 01:08:21,479
Speaker 1: decide that Wisconsin is a capital of the capital of

1286
01:08:21,520 --> 01:08:25,320
Speaker 1: the world. And I think Wisconsin, getting back even to

1287
01:08:25,400 --> 01:08:29,960
Speaker 1: your Patrick question, there's something Wisconsins are just very schulvinistic

1288
01:08:30,000 --> 01:08:32,920
Speaker 1: about their state. Yeah, but the Wisconsin Knights. And this

1289
01:08:33,000 --> 01:08:34,439
Speaker 1: has coming from the guy that grew up in Michigan.

1290
01:08:34,520 --> 01:08:36,599
Speaker 1: So I grew up in Michigan. When we went down

1291
01:08:36,640 --> 01:08:40,880
Speaker 1: to the beach, we're looking across at you guys. Uh,

1292
01:08:41,360 --> 01:08:45,400
Speaker 1: Wisconsin Knights on average are higher caliber human than Michigan

1293
01:08:45,479 --> 01:08:49,479
Speaker 1: Nights standard. I'll tell you why. I think that's the case.

1294
01:08:49,880 --> 01:08:53,720
Speaker 1: I think that if you went around Michigan and and

1295
01:08:54,280 --> 01:08:58,200
Speaker 1: and pulled people, but you know what, let's limit us. Okay,

1296
01:08:58,280 --> 01:09:01,720
Speaker 1: you go around Michigan pulling people that hold either a

1297
01:09:01,920 --> 01:09:05,240
Speaker 1: hunting or a fishing license. So you limit your survey

1298
01:09:05,400 --> 01:09:09,640
Speaker 1: to those people, and you ask those people what watershed

1299
01:09:09,960 --> 01:09:13,519
Speaker 1: do you live in? I think Wisconsin Nights would beat

1300
01:09:13,560 --> 01:09:20,200
Speaker 1: them three to one. There is a greater environmental in

1301
01:09:20,560 --> 01:09:27,880
Speaker 1: landscape awareness in Wisconsin. Then Michigan buy a huge margin

1302
01:09:27,960 --> 01:09:29,920
Speaker 1: and it haunts me. I can't figure out why it's true.

1303
01:09:30,280 --> 01:09:32,800
Speaker 1: I mean people Wisconsin. People Wisconsin can usually tell you,

1304
01:09:34,400 --> 01:09:36,240
Speaker 1: like if they were to take a leak on the ground,

1305
01:09:37,920 --> 01:09:41,280
Speaker 1: what river that piss would wind up and how it

1306
01:09:41,320 --> 01:09:44,920
Speaker 1: would make its way, and like just little things like that,

1307
01:09:45,240 --> 01:09:48,120
Speaker 1: Or you'll be talking like a random collection of Wisconsin dudes.

1308
01:09:48,360 --> 01:09:49,840
Speaker 1: More of them would know how to go find a

1309
01:09:49,920 --> 01:09:53,479
Speaker 1: morale than a random collection. I don't know what it is.

1310
01:09:57,160 --> 01:09:59,280
Speaker 1: I think it's the people that you talked to in Wisconsin.

1311
01:10:00,520 --> 01:10:02,920
Speaker 1: You think so, yeah, because they all know, because they

1312
01:10:02,920 --> 01:10:05,240
Speaker 1: all know each and they all like the outdoors a lot. Yeah,

1313
01:10:06,680 --> 01:10:09,240
Speaker 1: I don't know, man, I'd like to do it. I'd

1314
01:10:09,280 --> 01:10:12,919
Speaker 1: like to do it. I'm gonna do that. The researchers

1315
01:10:12,920 --> 01:10:15,519
Speaker 1: would call that what they call that street lamp science,

1316
01:10:16,000 --> 01:10:18,240
Speaker 1: where you look underneath the street lamp at night and

1317
01:10:18,320 --> 01:10:20,400
Speaker 1: whenever was going on there, you can see it, so

1318
01:10:20,520 --> 01:10:23,240
Speaker 1: you make your you can try these conclusions about what's

1319
01:10:23,280 --> 01:10:26,200
Speaker 1: going on underneath that street lamp. Well, outside of the

1320
01:10:26,200 --> 01:10:29,880
Speaker 1: street last much bigger world, and so what you're seeing

1321
01:10:29,920 --> 01:10:32,920
Speaker 1: underneath that street lamp might not be anything close to

1322
01:10:33,000 --> 01:10:36,760
Speaker 1: what's going on around it. And I don't know but

1323
01:10:37,240 --> 01:10:39,040
Speaker 1: I like to think that you're right. I like to

1324
01:10:39,080 --> 01:10:41,920
Speaker 1: think of Wisconsin nates have you know, I think they

1325
01:10:42,000 --> 01:10:45,800
Speaker 1: have an enhanced landscape awareness because and I think that

1326
01:10:45,960 --> 01:10:51,160
Speaker 1: the state pride, I think more like, yeah, I don't know,

1327
01:10:51,160 --> 01:10:52,640
Speaker 1: I could be wrong, probably pisting off a lot of

1328
01:10:52,640 --> 01:10:54,479
Speaker 1: guys my home state. I think they're like a more

1329
01:10:54,720 --> 01:10:59,600
Speaker 1: robust um well state patriotism, so to speak. Like a

1330
01:10:59,680 --> 01:11:02,760
Speaker 1: guy used to know in the hunting industry, he would

1331
01:11:02,800 --> 01:11:05,320
Speaker 1: look at that though, and say, Wisconsin stuffers from a

1332
01:11:05,360 --> 01:11:10,400
Speaker 1: whopping inferiority complex. So maybe you guys have a ship state,

1333
01:11:11,240 --> 01:11:13,479
Speaker 1: But but you make up for it by thinking it's

1334
01:11:13,479 --> 01:11:16,479
Speaker 1: a good state and knowing what creeks or what Maybe

1335
01:11:16,960 --> 01:11:18,800
Speaker 1: you make up for it by knowing what creeks flow

1336
01:11:18,840 --> 01:11:22,439
Speaker 1: into what creeks that flow into what rivers. You look

1337
01:11:22,439 --> 01:11:26,120
Speaker 1: at like, totally incredulous, Doug, you're not buying it. You

1338
01:11:26,280 --> 01:11:28,840
Speaker 1: damn sure know what creeks you're in. Well yeah, and

1339
01:11:29,160 --> 01:11:33,640
Speaker 1: and uh, well you probably have a wider experience of

1340
01:11:34,320 --> 01:11:36,880
Speaker 1: folks in Wisconsin than I do, because you know, I don't.

1341
01:11:37,960 --> 01:11:39,720
Speaker 1: I spent a lot of time the folks that I know.

1342
01:11:41,120 --> 01:11:44,960
Speaker 1: I know those kinds of things, no doubt Uh, but

1343
01:11:45,080 --> 01:11:47,160
Speaker 1: you're saying the hunters and fishers so, and I have

1344
01:11:47,280 --> 01:11:50,479
Speaker 1: no idea in Michigan. What people thinking. I've been all

1345
01:11:50,520 --> 01:11:52,560
Speaker 1: around both places. Yeah, I don't want to dwell on.

1346
01:11:52,640 --> 01:11:54,880
Speaker 1: I want to get back to stuff to pass stuff

1347
01:11:54,920 --> 01:11:57,840
Speaker 1: that I read a Pats. Where was I reading the

1348
01:11:58,000 --> 01:12:00,040
Speaker 1: article that you wrote. That's the one thing I like

1349
01:12:00,120 --> 01:12:04,000
Speaker 1: about knowing you is I stumble into your articles because

1350
01:12:04,000 --> 01:12:05,679
Speaker 1: you're write for all kinds but not I don't stumble

1351
01:12:05,680 --> 01:12:08,040
Speaker 1: into your columns. I stumble into your articles you write

1352
01:12:08,040 --> 01:12:11,880
Speaker 1: in magazines and and I believe at least I've been

1353
01:12:11,920 --> 01:12:18,160
Speaker 1: attributing it to you. Did you write a thing? Were

1354
01:12:18,200 --> 01:12:22,200
Speaker 1: you recovering some research about what bucks do during rut?

1355
01:12:23,520 --> 01:12:26,759
Speaker 1: Do they where? Do they actually? Like? Do they travel?

1356
01:12:26,880 --> 01:12:29,840
Speaker 1: Because I keep saying he wrote this, I've written hold

1357
01:12:29,840 --> 01:12:32,559
Speaker 1: on the editor of Deer and Deer Hunting Bucks during

1358
01:12:32,600 --> 01:12:37,720
Speaker 1: your rut? Probably not no, no, recently recently Yeah, And

1359
01:12:38,000 --> 01:12:45,439
Speaker 1: it was about uh GPS data on do bucks? It

1360
01:12:45,520 --> 01:12:48,280
Speaker 1: was like it was like, do bucks really travel all

1361
01:12:48,360 --> 01:12:52,519
Speaker 1: over Holy Hell during the I've written a couple on that. So,

1362
01:12:52,640 --> 01:12:54,639
Speaker 1: now that I've told people what I think you said,

1363
01:12:54,760 --> 01:12:57,040
Speaker 1: what did you say in that? What? What were you

1364
01:12:57,160 --> 01:13:01,439
Speaker 1: reporting on. Yeah. One thing that I liked about some

1365
01:13:01,520 --> 01:13:03,679
Speaker 1: of this recent research they've been doing with with bucks

1366
01:13:03,880 --> 01:13:08,040
Speaker 1: during the rut and where they go is not using GPS,

1367
01:13:08,120 --> 01:13:09,920
Speaker 1: and can I actually really get a pretty good hand

1368
01:13:10,000 --> 01:13:12,800
Speaker 1: line where they are at numerous times a day. And

1369
01:13:12,920 --> 01:13:14,880
Speaker 1: you know, in the old days, thirty years ago, they

1370
01:13:14,960 --> 01:13:18,160
Speaker 1: do it with radio telemetry years ago, and they don't

1371
01:13:18,280 --> 01:13:20,400
Speaker 1: get a reading every every couple of days or something

1372
01:13:20,439 --> 01:13:23,880
Speaker 1: whenever they happened to go out and put their and

1373
01:13:24,560 --> 01:13:27,519
Speaker 1: it was very difficult, but was what was interesting was that, um,

1374
01:13:27,960 --> 01:13:30,479
Speaker 1: it's this research from the nineties that was done with

1375
01:13:30,560 --> 01:13:33,519
Speaker 1: the old fashioned way. They found even back then that

1376
01:13:33,840 --> 01:13:38,679
Speaker 1: these bucks are really individuals that when you say bucks

1377
01:13:38,680 --> 01:13:41,240
Speaker 1: always do this during the rut, they go they really

1378
01:13:41,280 --> 01:13:44,360
Speaker 1: go ranging all the place. While some do but most

1379
01:13:44,400 --> 01:13:46,559
Speaker 1: of them don't, you know. But but there's still always

1380
01:13:46,600 --> 01:13:49,720
Speaker 1: these exceptions that will some buck will go off and

1381
01:13:50,680 --> 01:13:54,160
Speaker 1: who knows where. But yeah, like did it elk in

1382
01:13:54,560 --> 01:13:59,479
Speaker 1: like the elk or a lion born in South Dakota

1383
01:13:59,560 --> 01:14:04,040
Speaker 1: gets hit car in Connecticut? Yeah, yeah, do they all

1384
01:14:04,080 --> 01:14:08,000
Speaker 1: go to Connecticut because it will be in South Dakota? Right,

1385
01:14:08,520 --> 01:14:12,320
Speaker 1: And and what's um fastening about? A lot of research.

1386
01:14:12,680 --> 01:14:16,920
Speaker 1: What they start kind of ore figuring out what's going on.

1387
01:14:17,120 --> 01:14:20,400
Speaker 1: Is that, um, if a buck early in life scores

1388
01:14:20,760 --> 01:14:23,960
Speaker 1: close to home, all the system works, so he stays

1389
01:14:24,000 --> 01:14:25,600
Speaker 1: close to home for the most part as long as

1390
01:14:25,640 --> 01:14:28,559
Speaker 1: he's alive. You know, you always stum if there's enough

1391
01:14:28,880 --> 01:14:31,720
Speaker 1: dose in the area, and he hangs around and he's

1392
01:14:31,720 --> 01:14:34,320
Speaker 1: a plugger, and he keeps moving around until he gets

1393
01:14:34,400 --> 01:14:37,920
Speaker 1: one that the system works, so he keeps doing it. Well,

1394
01:14:37,920 --> 01:14:41,160
Speaker 1: if a buck not our buckets, let's say, for whatever reason,

1395
01:14:41,240 --> 01:14:45,760
Speaker 1: gets chased out of that little area and can't can't

1396
01:14:45,760 --> 01:14:48,240
Speaker 1: you know, he's just got the hormones going. He can't

1397
01:14:48,240 --> 01:14:52,160
Speaker 1: stop himself. It starts wandering and counter at the doll

1398
01:14:52,680 --> 01:14:54,639
Speaker 1: while that system works for him. So next year he's

1399
01:14:54,640 --> 01:14:57,679
Speaker 1: doing that again. So that it's really individual. It's probably

1400
01:14:58,080 --> 01:15:00,040
Speaker 1: little things that I think it's private. Ray somewhe to

1401
01:15:00,200 --> 01:15:03,120
Speaker 1: just how our guns season works around here some years

1402
01:15:03,560 --> 01:15:06,080
Speaker 1: if you're setting on the same theyvor stand every single

1403
01:15:06,200 --> 01:15:08,760
Speaker 1: year and some guy comes in from a different way

1404
01:15:08,840 --> 01:15:10,720
Speaker 1: one day and a buck runs by you, and you think, well,

1405
01:15:10,760 --> 01:15:12,880
Speaker 1: the systems working pretty good, you know, but you didn't

1406
01:15:12,920 --> 01:15:14,960
Speaker 1: know that's just a flute that this guy chased a

1407
01:15:15,000 --> 01:15:18,160
Speaker 1: buck passed you. And but you know, but the other

1408
01:15:18,280 --> 01:15:20,760
Speaker 1: thing too that's cool of us in this research is

1409
01:15:20,800 --> 01:15:23,479
Speaker 1: that I look at and think, well, you know, based

1410
01:15:23,520 --> 01:15:26,639
Speaker 1: on those GPS data, what val guys was saying about

1411
01:15:26,720 --> 01:15:30,240
Speaker 1: mule there thirty forty years ago holds up, you know,

1412
01:15:30,520 --> 01:15:34,040
Speaker 1: because he well, like Geist and John Ozolga who did

1413
01:15:34,200 --> 01:15:38,080
Speaker 1: whitetailed research up in the up of Michigan, they followed

1414
01:15:38,160 --> 01:15:41,120
Speaker 1: us in these really beautiful bucks. The biggest bucks were

1415
01:15:41,160 --> 01:15:44,599
Speaker 1: what I think I think guys called them shirkers. They

1416
01:15:44,640 --> 01:15:47,439
Speaker 1: would come out and they didn't want to get their

1417
01:15:47,439 --> 01:15:50,720
Speaker 1: ass kicked. So if there was a buck working the doll,

1418
01:15:50,960 --> 01:15:52,960
Speaker 1: rather than engage and try to drive that buck off,

1419
01:15:53,040 --> 01:15:55,640
Speaker 1: you'd shrink back. Now, maybe what happened early in his

1420
01:15:55,800 --> 01:15:57,599
Speaker 1: life was that he got in the middle, He got

1421
01:15:57,640 --> 01:16:00,200
Speaker 1: between a buck and a doll, and the bull buck

1422
01:16:00,360 --> 01:16:02,639
Speaker 1: gored him, beat the crop out of him. He thought,

1423
01:16:02,680 --> 01:16:04,920
Speaker 1: I don't want to go with that again, and so

1424
01:16:05,160 --> 01:16:08,479
Speaker 1: he his system was to say, in a safer area,

1425
01:16:08,800 --> 01:16:10,960
Speaker 1: looked for the one to drop into his lap, and

1426
01:16:11,200 --> 01:16:14,800
Speaker 1: and and now her and live longer. And then but

1427
01:16:14,880 --> 01:16:17,679
Speaker 1: then when that big gut buckets shot or just disappears,

1428
01:16:17,680 --> 01:16:20,760
Speaker 1: from landscape. All of a sudden, you got man gave

1429
01:16:20,800 --> 01:16:22,599
Speaker 1: him out again. He's back out there. He's now he's

1430
01:16:22,640 --> 01:16:25,120
Speaker 1: doing a little bit different behavior. And what was really

1431
01:16:25,200 --> 01:16:27,080
Speaker 1: cool about some of the stuff that was Alla ended

1432
01:16:27,160 --> 01:16:31,200
Speaker 1: up mission that the shirkers sugar Yeah, he called up

1433
01:16:32,520 --> 01:16:36,519
Speaker 1: no shirk you know the shirt that shirt short your

1434
01:16:36,600 --> 01:16:39,760
Speaker 1: Duties s h I r K shirt. I don't use

1435
01:16:39,800 --> 01:16:42,840
Speaker 1: that term, that term, honest, I don't know, but you

1436
01:16:42,880 --> 01:16:46,679
Speaker 1: know the work. Yeah, but I think guys called him shirkers.

1437
01:16:47,160 --> 01:16:50,719
Speaker 1: And um Zoga had a very similar conclusion that there's

1438
01:16:50,800 --> 01:16:53,600
Speaker 1: there's bucks that don't really engage much. And he was

1439
01:16:53,760 --> 01:16:56,160
Speaker 1: he checked some of these bucks and his study pun

1440
01:16:56,320 --> 01:16:59,640
Speaker 1: up in the US like a mile square pen. And

1441
01:16:59,680 --> 01:17:01,920
Speaker 1: when I think he found and there was this buck

1442
01:17:02,040 --> 01:17:05,800
Speaker 1: that was not engaging and not taking part. He he um,

1443
01:17:05,880 --> 01:17:07,800
Speaker 1: they I think they must have they must have had

1444
01:17:07,840 --> 01:17:10,240
Speaker 1: a way to trap them and check their blood. Because

1445
01:17:10,280 --> 01:17:12,679
Speaker 1: he did a blood check on this buck. What turns

1446
01:17:12,680 --> 01:17:15,400
Speaker 1: out this buck had a high level of progesterone, a

1447
01:17:15,439 --> 01:17:19,760
Speaker 1: female the female hormone. Yeah. And then but when that

1448
01:17:20,040 --> 01:17:22,240
Speaker 1: buck got his chance from the other, the bigger buck

1449
01:17:22,320 --> 01:17:25,360
Speaker 1: that was dominating him, you know, that scaring him when

1450
01:17:25,400 --> 01:17:28,080
Speaker 1: that buck disappear from you know, I think he died

1451
01:17:28,080 --> 01:17:29,679
Speaker 1: and they just moved himlet of the pen or something.

1452
01:17:30,000 --> 01:17:32,000
Speaker 1: I think he probably died. Well. As soon as that

1453
01:17:32,120 --> 01:17:37,280
Speaker 1: big buck that not stress inducer was was removed, his

1454
01:17:37,920 --> 01:17:42,559
Speaker 1: progesterone levels dropped. And you think this is cool stuff

1455
01:17:42,560 --> 01:17:46,360
Speaker 1: they're doing back in days before GPS, you know, believes

1456
01:17:47,400 --> 01:17:51,680
Speaker 1: Johannest believes that. I think it's the Honest believes that

1457
01:17:51,920 --> 01:17:57,640
Speaker 1: there are bucks who will go up and hide. This

1458
01:17:57,800 --> 01:18:00,160
Speaker 1: is the same stuff that he's talking about. The guy

1459
01:18:00,240 --> 01:18:03,479
Speaker 1: sort yeah, but I just don't. I've read a fair

1460
01:18:03,520 --> 01:18:05,760
Speaker 1: bit of battle guys. Let's leave it to leave it

1461
01:18:05,800 --> 01:18:09,600
Speaker 1: to Pat. Honest believes, based on a thing that he

1462
01:18:09,760 --> 01:18:15,519
Speaker 1: believes originated with vlarious guys, that there are bucks who

1463
01:18:15,600 --> 01:18:18,599
Speaker 1: will play the very long game, and they'll go up

1464
01:18:18,680 --> 01:18:22,160
Speaker 1: and hide up in some hidi hell hole their whole

1465
01:18:22,200 --> 01:18:27,559
Speaker 1: life until they're just giants. Then one day they'll think

1466
01:18:27,600 --> 01:18:29,920
Speaker 1: to themselves, you know, I'm about as big as I'm

1467
01:18:29,920 --> 01:18:33,880
Speaker 1: gonna get, and then they'll come down. Then they'll walk

1468
01:18:34,040 --> 01:18:40,320
Speaker 1: down and get them all. I have a very difficult

1469
01:18:40,400 --> 01:18:43,160
Speaker 1: time with that. I guess I said with you, because

1470
01:18:43,360 --> 01:18:45,400
Speaker 1: am I saying it right? Well, no, I mean I

1471
01:18:45,479 --> 01:18:49,000
Speaker 1: think you're you're making the exaggerated Steve version of the

1472
01:18:49,479 --> 01:18:53,560
Speaker 1: of the shirker of the shirker that he just explained.

1473
01:18:54,479 --> 01:18:59,559
Speaker 1: Oh yeah, we're just like in times of like when

1474
01:18:59,640 --> 01:19:02,320
Speaker 1: like times are hard and it's like there might be

1475
01:19:02,479 --> 01:19:04,600
Speaker 1: like like you're not feeling that well, there's like a

1476
01:19:04,720 --> 01:19:06,720
Speaker 1: rough winner, you didn't have a great summer. You pull

1477
01:19:06,760 --> 01:19:10,439
Speaker 1: a lot of fat, like they decide to instead of

1478
01:19:10,560 --> 01:19:14,640
Speaker 1: go in and engage and just go crazy. They're like,

1479
01:19:15,040 --> 01:19:18,120
Speaker 1: I'll shirk this year, maybe a couple of years the

1480
01:19:18,240 --> 01:19:23,320
Speaker 1: system is working for me, and then re enter. That's

1481
01:19:23,320 --> 01:19:25,080
Speaker 1: the thin thing is that I would never say that

1482
01:19:25,160 --> 01:19:27,640
Speaker 1: wouldn't happen, because I just gave some examples where what

1483
01:19:27,840 --> 01:19:31,439
Speaker 1: kind of happens and the thing that I'm geist will

1484
01:19:31,479 --> 01:19:33,920
Speaker 1: talk about and deer farmer say the same thing that

1485
01:19:34,240 --> 01:19:36,960
Speaker 1: the bucks that aren't being stressed take real big antlers

1486
01:19:37,120 --> 01:19:39,080
Speaker 1: because they can put so much their energy into those,

1487
01:19:39,160 --> 01:19:42,639
Speaker 1: into their growth. You know these animals that are stressed,

1488
01:19:43,160 --> 01:19:47,519
Speaker 1: they're nervous, they're always looking at their shoulder. Yeah, definitely,

1489
01:19:47,960 --> 01:19:51,160
Speaker 1: definitely stressed stress is a big influence on on antler development.

1490
01:19:51,800 --> 01:19:56,080
Speaker 1: So dudes that are shed hunting and needy snow are

1491
01:19:56,160 --> 01:19:59,439
Speaker 1: making next year's shed is not as big. Well, you

1492
01:19:59,479 --> 01:20:02,160
Speaker 1: can probably the argument. But you know, if you see

1493
01:20:02,400 --> 01:20:06,040
Speaker 1: that makes people man because it comes down to your

1494
01:20:06,080 --> 01:20:08,040
Speaker 1: telling someone he can't do something he wants to do.

1495
01:20:08,439 --> 01:20:10,360
Speaker 1: You're trying to get me a ready calm about that, now, huh?

1496
01:20:11,280 --> 01:20:12,680
Speaker 1: What's just there's a thing because we had like a

1497
01:20:12,720 --> 01:20:14,920
Speaker 1: pretty bad winter in some areas and people started bringing

1498
01:20:15,000 --> 01:20:16,840
Speaker 1: up and shed hunting is more and more. It used

1499
01:20:16,840 --> 01:20:20,920
Speaker 1: to be gone the woods hate sentences beginning. It used

1500
01:20:20,960 --> 01:20:23,240
Speaker 1: to be when I was a boy. When I was

1501
01:20:23,280 --> 01:20:25,840
Speaker 1: a boy, like you went on what you found a

1502
01:20:25,880 --> 01:20:28,080
Speaker 1: dear and like I was dear handler. Right, it wasn't

1503
01:20:28,080 --> 01:20:31,200
Speaker 1: like a thing that like was like it just wasn't

1504
01:20:31,240 --> 01:20:35,320
Speaker 1: as much of a thing to find sheds, Like you

1505
01:20:35,360 --> 01:20:39,280
Speaker 1: didn't have many people who really like self identified as

1506
01:20:39,360 --> 01:20:45,240
Speaker 1: shed hunters who do special trips to go hunting sheds. Right. So,

1507
01:20:45,840 --> 01:20:48,719
Speaker 1: now as it's becoming more and more popular and people

1508
01:20:48,760 --> 01:20:50,880
Speaker 1: are more and more gung hoo to get after him

1509
01:20:52,120 --> 01:20:54,880
Speaker 1: the second they dropped to the point where they watch

1510
01:20:55,479 --> 01:21:00,800
Speaker 1: yarded up deer in deep snow calm, you know, march

1511
01:21:01,400 --> 01:21:05,040
Speaker 1: whatever wherever deer in your area drop that they're watching

1512
01:21:05,080 --> 01:21:07,519
Speaker 1: them yard it up in the minute they start dropping,

1513
01:21:07,720 --> 01:21:09,880
Speaker 1: or that they're chasing them to get them to drop,

1514
01:21:10,880 --> 01:21:12,760
Speaker 1: like a deer will drop one and not the other

1515
01:21:12,880 --> 01:21:14,880
Speaker 1: and then they chase after it to try to get

1516
01:21:14,920 --> 01:21:16,840
Speaker 1: it to jostle free the other antlewers so they can

1517
01:21:16,920 --> 01:21:20,200
Speaker 1: get a matching pair. So some people have pointed out

1518
01:21:20,479 --> 01:21:22,240
Speaker 1: this might be something we need to get out ahead

1519
01:21:22,280 --> 01:21:24,240
Speaker 1: of the same way we got out ahead of. You

1520
01:21:24,280 --> 01:21:26,720
Speaker 1: can't hunt year round as much as you want, and

1521
01:21:26,800 --> 01:21:29,840
Speaker 1: there's seasons for that. They put forward this idea that

1522
01:21:29,920 --> 01:21:32,800
Speaker 1: we would regulate this morning that Pisces people you can't

1523
01:21:32,800 --> 01:21:36,559
Speaker 1: find them more stressful time, probably for now that time

1524
01:21:36,600 --> 01:21:45,000
Speaker 1: of year. So Yanni always says winter weekends, spring kills. Yeah. Well,

1525
01:21:45,040 --> 01:21:48,800
Speaker 1: on that warden that we chatted with in November in Colorado,

1526
01:21:49,040 --> 01:21:53,200
Speaker 1: he was saying the number one uh, you know, impact

1527
01:21:53,320 --> 01:21:57,400
Speaker 1: onto deer populations now he believes is well maybe it

1528
01:21:57,479 --> 01:22:01,439
Speaker 1: was like even now with have a that but the

1529
01:22:01,479 --> 01:22:05,000
Speaker 1: summer recreation that it's just you know, and it's just

1530
01:22:05,120 --> 01:22:07,400
Speaker 1: like there's more people that haven't been in the woods,

1531
01:22:07,800 --> 01:22:10,000
Speaker 1: you know, in the past years, and now there's just

1532
01:22:10,240 --> 01:22:13,360
Speaker 1: hikers and bikers and you know, they've been looking they've

1533
01:22:13,400 --> 01:22:15,120
Speaker 1: been doing a lot of work looking at methods of

1534
01:22:15,240 --> 01:22:19,840
Speaker 1: conveyance and what it tends to do with dispersal away

1535
01:22:19,920 --> 01:22:25,840
Speaker 1: from trails. And there's like some counterintuitive ship oh yeah

1536
01:22:26,280 --> 01:22:30,120
Speaker 1: about what freaks them out and what doesn't freak him out. Yeah. Well,

1537
01:22:30,120 --> 01:22:32,120
Speaker 1: actually go into a lot of these game farms, like

1538
01:22:32,479 --> 01:22:34,799
Speaker 1: a deer farm, especially because deer are really a skittish

1539
01:22:34,800 --> 01:22:38,519
Speaker 1: animal that doesn't do well in confinement. That's why they

1540
01:22:38,560 --> 01:22:41,760
Speaker 1: have all those you'll see um like black drape type

1541
01:22:41,800 --> 01:22:45,360
Speaker 1: material around defenses because if deer see something else outside

1542
01:22:45,400 --> 01:22:48,320
Speaker 1: defense that makes them nervous that you know, they start

1543
01:22:48,360 --> 01:22:51,840
Speaker 1: going nut. So they start running around circles very stress Yeah,

1544
01:22:51,840 --> 01:22:53,280
Speaker 1: and they try to keep them relaxed as much as

1545
01:22:53,280 --> 01:22:55,000
Speaker 1: they can and keep them, you know, isolated from all

1546
01:22:55,040 --> 01:22:58,240
Speaker 1: that kind of all those stressors. And but you know,

1547
01:22:58,320 --> 01:23:01,599
Speaker 1: like it's I always find it interesting that the elk

1548
01:23:01,680 --> 01:23:03,760
Speaker 1: farmers will see some of the elk out in the

1549
01:23:03,760 --> 01:23:06,080
Speaker 1: wild in northern Wisconsin and up in the clam Laker,

1550
01:23:06,240 --> 01:23:08,720
Speaker 1: which isn't very good elk habitat, and there a lot

1551
01:23:08,800 --> 01:23:12,599
Speaker 1: more spindle rack type type bowls that aren't anything real impressed.

1552
01:23:12,640 --> 01:23:15,040
Speaker 1: They aren't like you see out in Arizona or something,

1553
01:23:15,680 --> 01:23:18,040
Speaker 1: and then they'll show some elk they have thing. Well, yeah,

1554
01:23:18,040 --> 01:23:20,040
Speaker 1: but you're controlling the environment in that in that pat

1555
01:23:20,120 --> 01:23:24,040
Speaker 1: and you got all they have their food right, their form,

1556
01:23:24,120 --> 01:23:27,439
Speaker 1: they have everything, all the environments controlled. They're not out

1557
01:23:27,479 --> 01:23:30,680
Speaker 1: there running around chasing running away from wolves or ring

1558
01:23:30,760 --> 01:23:34,799
Speaker 1: about wolves and and all. Anything that's staying constantly alert

1559
01:23:35,200 --> 01:23:37,280
Speaker 1: that takes that takes its toll, you know, on their

1560
01:23:37,320 --> 01:23:39,600
Speaker 1: on their energy and their their overall well being. So

1561
01:23:40,080 --> 01:23:42,040
Speaker 1: I think most people can relate to that. Just when

1562
01:23:42,040 --> 01:23:44,760
Speaker 1: you want to add, Doug, Well, when we're you're talking

1563
01:23:44,800 --> 01:23:48,880
Speaker 1: about different books and you know, and and how they

1564
01:23:48,960 --> 01:23:50,679
Speaker 1: acted on it, it just sounded to me like you're

1565
01:23:50,680 --> 01:23:53,800
Speaker 1: talking about guys you know that. Well, I know guys

1566
01:23:53,880 --> 01:23:58,200
Speaker 1: that are more active or more interested in I've known

1567
01:23:58,320 --> 01:24:00,639
Speaker 1: guys my whole life from we're act of more interested

1568
01:24:00,640 --> 01:24:03,519
Speaker 1: in women, not interested in when you got your shirkers too, Yeah,

1569
01:24:03,560 --> 01:24:07,080
Speaker 1: you got your shirkers. My experience, guys like he's gonna

1570
01:24:07,120 --> 01:24:10,639
Speaker 1: go out to the bar, He's gonna, you know, pounded

1571
01:24:10,680 --> 01:24:13,200
Speaker 1: at the bar. He's gonna put in a long night, Thursday,

1572
01:24:13,320 --> 01:24:15,840
Speaker 1: long night, Friday, long night, Saturday, spend all of his

1573
01:24:15,920 --> 01:24:19,360
Speaker 1: money drinking at the bar, right. Yeah, Well that's what

1574
01:24:19,439 --> 01:24:21,880
Speaker 1: I'm just dying to meet someone. And then you got

1575
01:24:22,000 --> 01:24:25,719
Speaker 1: some shirkar. He's at home, he's yeah, he's got roommates.

1576
01:24:25,760 --> 01:24:28,720
Speaker 1: He's just gonna hang. See what comes snipping around two

1577
01:24:28,760 --> 01:24:32,800
Speaker 1: in the morning. Yeah. My experience with with deer in

1578
01:24:32,880 --> 01:24:36,400
Speaker 1: a very limited area, you know this this farm is

1579
01:24:36,760 --> 01:24:39,479
Speaker 1: the older the deer gets, the less it moves. That's

1580
01:24:39,520 --> 01:24:43,760
Speaker 1: the way it seems to me. I like that. We

1581
01:24:43,840 --> 01:24:45,640
Speaker 1: saw something this year that we've already talked about a

1582
01:24:45,640 --> 01:24:50,200
Speaker 1: bunch of times, but we saw a group of mule deer,

1583
01:24:50,960 --> 01:24:54,400
Speaker 1: a shipload of dolls in a very nice buck in

1584
01:24:54,479 --> 01:24:58,320
Speaker 1: an aspen patch, and Yanni is looking through his knockers

1585
01:24:58,439 --> 01:24:59,960
Speaker 1: and he says, oh, some kyotes are coming down to

1586
01:25:00,040 --> 01:25:04,559
Speaker 1: the asthen patch. Okay, kyles come down, and all these

1587
01:25:04,600 --> 01:25:09,080
Speaker 1: freaking doughs just come out of there, like just spraying

1588
01:25:09,200 --> 01:25:15,080
Speaker 1: out of this aspen patch. Okay. That buck stands there

1589
01:25:15,160 --> 01:25:17,400
Speaker 1: and these are his like he's got him collected up.

1590
01:25:17,479 --> 01:25:23,000
Speaker 1: He's working these doughs. He stands up, assesses the situation,

1591
01:25:23,120 --> 01:25:27,519
Speaker 1: what's going on, looks watches the coyotes. All his doughs

1592
01:25:27,520 --> 01:25:30,360
Speaker 1: are gone, and you see him like running that ship

1593
01:25:30,479 --> 01:25:32,200
Speaker 1: in his head. I swear it looked like and he's like,

1594
01:25:32,479 --> 01:25:36,240
Speaker 1: you know what, I'm just gonna lay back down. I'm

1595
01:25:36,280 --> 01:25:38,599
Speaker 1: not gonna go running out out of this asthma patch

1596
01:25:38,720 --> 01:25:41,360
Speaker 1: getting shot at by some asshole. He's like, I just

1597
01:25:41,479 --> 01:25:45,360
Speaker 1: gonna lay down and this this low sort of it'll

1598
01:25:45,400 --> 01:25:48,640
Speaker 1: sort itself out later. He lays back down, and then

1599
01:25:48,720 --> 01:25:50,960
Speaker 1: over the course of the day all those dolls can

1600
01:25:51,000 --> 01:25:53,280
Speaker 1: trick them back in that asthen patch and think about

1601
01:25:53,280 --> 01:25:56,479
Speaker 1: the calories that he saved by not going on that run.

1602
01:25:56,720 --> 01:25:58,559
Speaker 1: And he's like, you all can run around getting all

1603
01:25:58,640 --> 01:26:01,240
Speaker 1: worked up. I ain't. The thing to do is the

1604
01:26:01,360 --> 01:26:03,840
Speaker 1: whole type. So that's one of the reasons that I

1605
01:26:03,960 --> 01:26:05,439
Speaker 1: try to have a place on the farm that we

1606
01:26:05,479 --> 01:26:08,040
Speaker 1: don't go into and let him have a place that

1607
01:26:08,320 --> 01:26:10,680
Speaker 1: that's the dearest place you know that they can go

1608
01:26:10,800 --> 01:26:13,160
Speaker 1: in there and and and you know that's their saying.

1609
01:26:14,360 --> 01:26:17,479
Speaker 1: It might be too um. Sanctuaries or sanctuaries do they

1610
01:26:17,520 --> 01:26:20,639
Speaker 1: work based on your based on what you hear from

1611
01:26:21,400 --> 01:26:24,400
Speaker 1: some of the guys that relay serious about they believe

1612
01:26:24,400 --> 01:26:27,680
Speaker 1: in it. Because I'm not disrespecting man, I thought I

1613
01:26:27,800 --> 01:26:29,600
Speaker 1: was trying to do your favorite No, no, no, no, no.

1614
01:26:29,960 --> 01:26:32,120
Speaker 1: I think it's I think it's pretty much a lot

1615
01:26:32,160 --> 01:26:34,599
Speaker 1: of folks that follow the quality quality deer management type

1616
01:26:34,640 --> 01:26:37,439
Speaker 1: ideas and sitting up their land and a lot I

1617
01:26:37,600 --> 01:26:39,479
Speaker 1: really believe in the sanctuaries. You know, there's certain areas

1618
01:26:39,479 --> 01:26:43,120
Speaker 1: they'll put off guarden. It's it's reached scholarly consensus. Well,

1619
01:26:43,120 --> 01:26:44,519
Speaker 1: I'm not sure if it's. I don't know off has

1620
01:26:44,560 --> 01:26:47,360
Speaker 1: done that. I really don't. I don't. I haven't. I

1621
01:26:47,439 --> 01:26:49,360
Speaker 1: can't say I have seen anything on that. There might be,

1622
01:26:49,479 --> 01:26:51,160
Speaker 1: but I haven't seen it. You know, I don't else

1623
01:26:51,200 --> 01:26:53,439
Speaker 1: have not mean, I don't mean literally scholarly, but it's

1624
01:26:53,479 --> 01:26:56,880
Speaker 1: reached like professional consensus, right, I mean, I know a

1625
01:26:56,960 --> 01:27:00,120
Speaker 1: number of guys who are deadly serious but keeping a

1626
01:27:00,240 --> 01:27:02,519
Speaker 1: sanctuary intact? Do I time to go in there is

1627
01:27:02,560 --> 01:27:04,679
Speaker 1: to retrieve a dead deer basically, and they really don't

1628
01:27:04,800 --> 01:27:07,960
Speaker 1: violate their own sanctus, right that I have a hard

1629
01:27:08,000 --> 01:27:12,240
Speaker 1: time believe that. You like, right, you got this farm

1630
01:27:12,280 --> 01:27:13,840
Speaker 1: and all you're really doing is, you know, you got

1631
01:27:13,920 --> 01:27:16,840
Speaker 1: all your responsibles, but you want to kill a big deer.

1632
01:27:17,200 --> 01:27:18,479
Speaker 1: You like to grow a big deer, and you want

1633
01:27:18,479 --> 01:27:22,000
Speaker 1: to kill a big deer, and and season is going on,

1634
01:27:22,960 --> 01:27:25,360
Speaker 1: and you know those big giants around and you look

1635
01:27:25,439 --> 01:27:27,320
Speaker 1: in there and you see them all the time in there,

1636
01:27:28,200 --> 01:27:33,040
Speaker 1: and seasons winding down. You got a day left, all

1637
01:27:33,080 --> 01:27:36,360
Speaker 1: the cousins and should have gone home. In the areas

1638
01:27:36,400 --> 01:27:39,760
Speaker 1: in the sanctuary, you're looking in there at him. Well,

1639
01:27:40,200 --> 01:27:42,040
Speaker 1: you're telling me that there are guys out there who

1640
01:27:42,040 --> 01:27:44,760
Speaker 1: would be like, no, I can't do it, won't, I

1641
01:27:45,080 --> 01:27:53,000
Speaker 1: won't do it, sanctuary like that. Well, but and their defense, Steve.

1642
01:27:53,160 --> 01:27:56,040
Speaker 1: What they're saying probably is that my odds are killing

1643
01:27:56,080 --> 01:27:58,560
Speaker 1: that buck are better by waiting out here in this

1644
01:27:58,680 --> 01:28:01,559
Speaker 1: trail that's leading down to felf A Field or whatever.

1645
01:28:01,720 --> 01:28:05,120
Speaker 1: Might be looking at him in the sanctuary, Well I

1646
01:28:05,160 --> 01:28:06,720
Speaker 1: don't they can see and they're probably back in there.

1647
01:28:06,720 --> 01:28:09,000
Speaker 1: And that's the company the sancs where I'm thinking about.

1648
01:28:09,280 --> 01:28:11,840
Speaker 1: There's a little pocket you can look into, the one

1649
01:28:11,920 --> 01:28:14,759
Speaker 1: I'm the one I'm imagining, and he's in that little pocket.

1650
01:28:16,320 --> 01:28:19,040
Speaker 1: No one, no one. Well, if you can see him,

1651
01:28:19,160 --> 01:28:27,600
Speaker 1: no i'ctuary could find But you're walking too close to

1652
01:28:27,680 --> 01:28:30,720
Speaker 1: the things. If you can see him that he's like,

1653
01:28:30,720 --> 01:28:32,439
Speaker 1: I don't want to know what's going on. This is

1654
01:28:32,479 --> 01:28:36,920
Speaker 1: your fantasy um sanctuary that I'm putting out a hypothetical,

1655
01:28:37,000 --> 01:28:39,760
Speaker 1: but I understand, but I would. I would like to

1656
01:28:39,880 --> 01:28:43,080
Speaker 1: think I would. I bet you that you will find it. Most,

1657
01:28:44,000 --> 01:28:50,960
Speaker 1: if not all, sanctuaries get violated by the sanctuary owner.

1658
01:28:51,280 --> 01:28:56,000
Speaker 1: Maybe that is buddies, but I think sanctuaries are made

1659
01:28:56,080 --> 01:29:00,360
Speaker 1: to be unsanctuaried by their owner. It's a way him

1660
01:29:00,439 --> 01:29:04,360
Speaker 1: to say, let's take it easy, see how things play out.

1661
01:29:05,439 --> 01:29:09,080
Speaker 1: There's nothing you cousins and whatnot could do to get

1662
01:29:09,120 --> 01:29:12,760
Speaker 1: in there. I'm gonna wait and see. Yeah. But the

1663
01:29:12,840 --> 01:29:15,360
Speaker 1: thing I think I'm struggling with in all sincerity is

1664
01:29:16,200 --> 01:29:18,600
Speaker 1: you know how hard there's as an individual hunter to

1665
01:29:18,680 --> 01:29:21,679
Speaker 1: go in any patch of cover and get a crack

1666
01:29:21,760 --> 01:29:24,439
Speaker 1: at any of her that's in there. And so why

1667
01:29:24,439 --> 01:29:27,840
Speaker 1: would it gu I intentionally violated his own sanctuary with

1668
01:29:28,040 --> 01:29:30,000
Speaker 1: a very low odds. I've ever seen that bucket that

1669
01:29:30,080 --> 01:29:33,200
Speaker 1: goes creeping in there and puts a stain in there? Yeah,

1670
01:29:33,880 --> 01:29:35,720
Speaker 1: I don't want to dwell. Yeah, Okay, now let me

1671
01:29:35,760 --> 01:29:38,639
Speaker 1: ask you about this, gohead. Well, I want to circle

1672
01:29:38,680 --> 01:29:42,360
Speaker 1: back to Yanni story real quickly. Another possible explanation for

1673
01:29:42,520 --> 01:29:45,160
Speaker 1: why he didn't run out there is that there are

1674
01:29:45,240 --> 01:29:47,679
Speaker 1: cases where they've they've they've documented this, you know, actually

1675
01:29:47,760 --> 01:29:50,439
Speaker 1: photographed it, where a buck will stand down on a

1676
01:29:50,560 --> 01:29:54,720
Speaker 1: couity or stand stand off a wolf just by bracing up,

1677
01:29:55,000 --> 01:29:57,960
Speaker 1: taking it on and looking at basically stirring the animal.

1678
01:29:58,040 --> 01:30:01,000
Speaker 1: Dahna saying you want some of this, come try. Well,

1679
01:30:01,040 --> 01:30:02,680
Speaker 1: you know what's funny about that, Now that you want

1680
01:30:02,720 --> 01:30:05,760
Speaker 1: to dig deep around this, I'll point out that those

1681
01:30:06,040 --> 01:30:08,519
Speaker 1: those coyotes that absolutely no interest in those dear it's

1682
01:30:08,560 --> 01:30:11,000
Speaker 1: not what they're doing. But a couple of days later,

1683
01:30:11,080 --> 01:30:15,280
Speaker 1: another big buck they want up shooting this buck he's with,

1684
01:30:15,360 --> 01:30:17,600
Speaker 1: I don't know seven or eight does a couple of

1685
01:30:17,640 --> 01:30:20,000
Speaker 1: coyotes come through and he's the one that runs away.

1686
01:30:20,479 --> 01:30:22,479
Speaker 1: So they all spill off the back of the hill

1687
01:30:23,960 --> 01:30:27,519
Speaker 1: and then over the next minutes they all trickle back

1688
01:30:27,560 --> 01:30:31,960
Speaker 1: into where they were. He never comes back. He spilled

1689
01:30:32,000 --> 01:30:35,200
Speaker 1: off the back of the hill across the gully and

1690
01:30:35,360 --> 01:30:38,160
Speaker 1: we later found him betted up. So it might have

1691
01:30:38,200 --> 01:30:39,519
Speaker 1: been like he's like, yeah, I was kind of think

1692
01:30:39,520 --> 01:30:42,160
Speaker 1: about going to have a nap. Anyways, it's getting late

1693
01:30:42,200 --> 01:30:44,280
Speaker 1: in the day. It's like I don't like to be

1694
01:30:44,400 --> 01:30:46,200
Speaker 1: out this time of day because I've learned in my

1695
01:30:46,360 --> 01:30:50,240
Speaker 1: general bucknus that it's like you get your morning business

1696
01:30:50,280 --> 01:30:51,880
Speaker 1: taking care of and you go hide. So maybe just

1697
01:30:52,000 --> 01:30:54,920
Speaker 1: like I was gonna leave now anyways, now I'm just

1698
01:30:54,960 --> 01:30:57,960
Speaker 1: gonna leave trying trying to figure out why an animal

1699
01:30:58,080 --> 01:31:04,120
Speaker 1: does something. God you know, good luck individual animal does sometimes. Yeah,

1700
01:31:04,280 --> 01:31:06,639
Speaker 1: And I just I just glassed up a skunk working

1701
01:31:06,720 --> 01:31:08,679
Speaker 1: Doug's hill the middle to day. What was he doing?

1702
01:31:09,560 --> 01:31:13,160
Speaker 1: Doug thinks he smells after birth from the cab. Well,

1703
01:31:16,240 --> 01:31:20,160
Speaker 1: here's what I want to ask about, similar thing. And

1704
01:31:20,280 --> 01:31:23,920
Speaker 1: I've i've I think I've I've talked about my I've

1705
01:31:23,960 --> 01:31:26,439
Speaker 1: talked about what I think he wrote about. What is

1706
01:31:26,520 --> 01:31:30,800
Speaker 1: the latest, what's the what's the the thinking on what

1707
01:31:31,040 --> 01:31:36,160
Speaker 1: that lunar phases? Okay, a fact, dear like people like

1708
01:31:36,680 --> 01:31:41,720
Speaker 1: I'm not even gonna bother hunting full moon, I'm sure

1709
01:31:41,760 --> 01:31:43,800
Speaker 1: that discussion has been going on as lost people have

1710
01:31:43,880 --> 01:31:46,280
Speaker 1: been hunting. One of my one of my guys that

1711
01:31:46,360 --> 01:31:50,679
Speaker 1: I look up to the most as a hunter, Remy

1712
01:31:50,720 --> 01:31:58,080
Speaker 1: Warren Remy. He is a firm believer to the point

1713
01:31:58,120 --> 01:32:03,639
Speaker 1: where he'll book even for Bears spring spot Stock Spring Bears,

1714
01:32:04,120 --> 01:32:11,519
Speaker 1: he'll book his clients around lunar cycles the bless his heart. Yeah.

1715
01:32:12,560 --> 01:32:14,800
Speaker 1: To me, the one one thing I really do believe

1716
01:32:14,880 --> 01:32:17,240
Speaker 1: in is that if you have that kind of confidence

1717
01:32:17,320 --> 01:32:22,200
Speaker 1: and something, chances aren't works. Yeah. But I I but

1718
01:32:22,240 --> 01:32:23,960
Speaker 1: don't don't do the like what works for you. I

1719
01:32:24,080 --> 01:32:27,280
Speaker 1: understand all that. Okay, Okay, I won't, but um, like,

1720
01:32:27,320 --> 01:32:28,880
Speaker 1: because then you're just saying that you're open up. Like

1721
01:32:29,320 --> 01:32:31,080
Speaker 1: like if I if I say, oh, I like h

1722
01:32:31,240 --> 01:32:35,200
Speaker 1: you know blue, like I like to this rappola, and

1723
01:32:35,280 --> 01:32:38,200
Speaker 1: I'd be like, all right, dude, if you've got confidence

1724
01:32:38,240 --> 01:32:39,720
Speaker 1: in it and it works for you. But that's a

1725
01:32:39,800 --> 01:32:44,400
Speaker 1: different conversation than like what works. You're humoring someone when

1726
01:32:44,439 --> 01:32:49,760
Speaker 1: you say that maybe. But um. The research I've seenato

1727
01:32:50,160 --> 01:32:53,160
Speaker 1: is that when they have tried to tie in lunar

1728
01:32:53,200 --> 01:32:56,720
Speaker 1: activity to all these different movements, whether it's UM for

1729
01:32:56,960 --> 01:33:01,320
Speaker 1: breeding purposes, for like um, Charlie Alsheimer has had an

1730
01:33:01,360 --> 01:33:05,080
Speaker 1: interesting theory on on on what triggers. It's a second,

1731
01:33:05,160 --> 01:33:08,320
Speaker 1: it's a harvest moon that kind of sets things in motion. Well,

1732
01:33:08,360 --> 01:33:10,880
Speaker 1: when the researchers go in and actually look at this

1733
01:33:10,960 --> 01:33:16,200
Speaker 1: stuff and back back date, you know, when fawns drop

1734
01:33:16,479 --> 01:33:19,080
Speaker 1: because they I backed it stuff pretty accurately and when yeah,

1735
01:33:19,080 --> 01:33:21,960
Speaker 1: they have a known gestation right exactly, so that they

1736
01:33:22,040 --> 01:33:23,439
Speaker 1: go back and they look at that stuff and they

1737
01:33:23,439 --> 01:33:26,000
Speaker 1: do it year after year, and they they basically always

1738
01:33:26,040 --> 01:33:29,439
Speaker 1: beat up Charlie's um theories on that and they beat

1739
01:33:29,520 --> 01:33:31,040
Speaker 1: up in an inn our theory you see on on

1740
01:33:31,160 --> 01:33:34,040
Speaker 1: lunar cycles. And because what triggers the rud is ten

1741
01:33:34,120 --> 01:33:39,400
Speaker 1: things that you can't untangle them all, Yeah, like photo period,

1742
01:33:39,640 --> 01:33:42,680
Speaker 1: all kinds and see like that wouldn't I would never

1743
01:33:42,880 --> 01:33:46,120
Speaker 1: try to take on a guy like in my generation,

1744
01:33:46,200 --> 01:33:48,240
Speaker 1: the guy that we all looked up to is John Wooters,

1745
01:33:48,360 --> 01:33:51,920
Speaker 1: the old deer Here's the deer expert for Peterson's Hunting

1746
01:33:52,000 --> 01:33:55,040
Speaker 1: magazine back in the seventies, eighties and nineties. And John

1747
01:33:55,120 --> 01:33:58,200
Speaker 1: really belied in the moon he um, Yeah, he really

1748
01:33:58,360 --> 01:34:01,760
Speaker 1: followed the lunar phases and he always talked about I

1749
01:34:01,840 --> 01:34:04,680
Speaker 1: think his his belief was that the full moon was

1750
01:34:04,760 --> 01:34:07,120
Speaker 1: a terrible time to be out there hunt in the daylight.

1751
01:34:07,200 --> 01:34:10,600
Speaker 1: And the thinking is least it's always articulated to me

1752
01:34:10,680 --> 01:34:14,720
Speaker 1: by people who really abide by lunar cycles, is the

1753
01:34:14,840 --> 01:34:19,519
Speaker 1: thinking is that it's extra light out m and deer

1754
01:34:19,600 --> 01:34:23,200
Speaker 1: are getting all their business taken care of at night

1755
01:34:24,479 --> 01:34:27,600
Speaker 1: because deer are like a crepuscular animal, their peak activity

1756
01:34:27,680 --> 01:34:31,280
Speaker 1: is low light, so dawn dusk. But here they're having

1757
01:34:31,400 --> 01:34:38,519
Speaker 1: like a crepuscular like atmosphere all through the night, dark

1758
01:34:38,600 --> 01:34:41,639
Speaker 1: but not dark. Did they get all their business taking

1759
01:34:41,680 --> 01:34:43,400
Speaker 1: care of and then they're all tired out and they

1760
01:34:43,439 --> 01:34:46,280
Speaker 1: just go to bed when it gets daylight up. That's like,

1761
01:34:46,320 --> 01:34:50,519
Speaker 1: that's your understanding, now, Uh, just to throw just throw, uh,

1762
01:34:51,320 --> 01:34:53,360
Speaker 1: you know, just to mix it up a little bit.

1763
01:34:54,120 --> 01:34:57,800
Speaker 1: Down South America where they hunt nocturnal, where they hunt

1764
01:34:57,920 --> 01:35:02,680
Speaker 1: like nocturnal animal. They don't like to hunt at night

1765
01:35:03,680 --> 01:35:07,479
Speaker 1: during a full moon because some nocturnal animals have such

1766
01:35:07,640 --> 01:35:12,000
Speaker 1: fidelity to the darkness that they won't come out on

1767
01:35:12,040 --> 01:35:16,560
Speaker 1: the moon lit night because they're there their defense mechanisms

1768
01:35:16,640 --> 01:35:20,240
Speaker 1: like dark. They won't hunt the way till the moon

1769
01:35:20,400 --> 01:35:23,160
Speaker 1: sets and then go hunt. Certain nocturnal animals like that thing.

1770
01:35:23,320 --> 01:35:25,400
Speaker 1: If it's at all light, that's something bitch does not

1771
01:35:25,479 --> 01:35:27,120
Speaker 1: come out. I'm pretty sure they found the same thing

1772
01:35:27,160 --> 01:35:29,760
Speaker 1: with protul their studies in North America. There's certain um,

1773
01:35:30,479 --> 01:35:33,760
Speaker 1: certain small mammals that won't come out bright moon because

1774
01:35:33,800 --> 01:35:37,080
Speaker 1: they know the owls can see them easy. Yeah, there

1775
01:35:37,320 --> 01:35:41,240
Speaker 1: be killed and and I guess I'm always somewhat skeptical

1776
01:35:41,360 --> 01:35:43,519
Speaker 1: of the all night activity thing. And I think, well,

1777
01:35:44,080 --> 01:35:45,680
Speaker 1: deer have their patterns. They're gonna be up in their

1778
01:35:45,680 --> 01:35:47,760
Speaker 1: feet all night long. And even that's seen deer at

1779
01:35:47,840 --> 01:35:49,960
Speaker 1: night a lot of times. But I find beds out

1780
01:35:50,000 --> 01:35:52,479
Speaker 1: in my back little woods where I live that I

1781
01:35:52,520 --> 01:35:54,080
Speaker 1: know there's no deer in there in the daylight, because

1782
01:35:54,120 --> 01:35:56,439
Speaker 1: that's a little open woods. There's never deer in there

1783
01:35:56,479 --> 01:35:58,639
Speaker 1: in the daylight. They might move through a dawn or dust,

1784
01:35:58,680 --> 01:36:00,560
Speaker 1: but they don't. They don't spend daylight and there's just

1785
01:36:01,120 --> 01:36:03,280
Speaker 1: too small little spot. But where you go back there

1786
01:36:03,280 --> 01:36:06,360
Speaker 1: in the winter, there was always fresh deer beds from overnight,

1787
01:36:06,600 --> 01:36:08,599
Speaker 1: you know, so they're not on their feet all night.

1788
01:36:09,280 --> 01:36:11,160
Speaker 1: I never I never buy that that there's you know,

1789
01:36:11,280 --> 01:36:14,240
Speaker 1: there's on their feet, Like ohm, sweet, I can get

1790
01:36:14,280 --> 01:36:16,040
Speaker 1: everything I was gonna get taken care of, taken care of.

1791
01:36:16,560 --> 01:36:18,160
Speaker 1: They ever have sex with all the deer I was

1792
01:36:18,160 --> 01:36:19,800
Speaker 1: gonna have sex with, eat all the food I was

1793
01:36:19,840 --> 01:36:21,880
Speaker 1: gonna eat up, get all that taken care of. And

1794
01:36:21,960 --> 01:36:23,800
Speaker 1: I don't need to be running around like some more

1795
01:36:23,920 --> 01:36:27,640
Speaker 1: on come Come daybreak another handle deer to also have

1796
01:36:28,040 --> 01:36:32,040
Speaker 1: incredible night vision, that their eyes really are are built

1797
01:36:32,040 --> 01:36:34,080
Speaker 1: for that night time activity. So I don't like they're

1798
01:36:34,160 --> 01:36:37,719
Speaker 1: walking around stumb link to the dark on moonless nights. Yeah,

1799
01:36:38,240 --> 01:36:42,639
Speaker 1: I just but I really don't argue that a hold

1800
01:36:42,680 --> 01:36:45,360
Speaker 1: off a guy has the data and it works for him.

1801
01:36:45,600 --> 01:36:47,200
Speaker 1: The thing I would say, though, to a lot of

1802
01:36:47,240 --> 01:36:49,920
Speaker 1: these guys that say, well, my observations on my trail cameras,

1803
01:36:49,960 --> 01:36:53,759
Speaker 1: I never see any kind of good activity during certain

1804
01:36:53,880 --> 01:36:57,519
Speaker 1: hours on certain days the moon, I think as that

1805
01:36:57,680 --> 01:37:00,800
Speaker 1: realized up the scientific rigors though, you know, I really

1806
01:37:01,200 --> 01:37:04,120
Speaker 1: you have a guy that's a scientifically modeling guy that

1807
01:37:04,160 --> 01:37:07,719
Speaker 1: can put all his data together and really cross check

1808
01:37:08,080 --> 01:37:10,639
Speaker 1: that stuff. As I stood that kind of scientific rigor,

1809
01:37:10,760 --> 01:37:12,920
Speaker 1: I doubt it because most of us aren't sing. You're

1810
01:37:12,960 --> 01:37:14,680
Speaker 1: doubt And so if God came down and put a

1811
01:37:14,760 --> 01:37:18,320
Speaker 1: gun to your head instead, do lunar phases matter or not?

1812
01:37:20,880 --> 01:37:22,720
Speaker 1: And you had to say it has yes or no,

1813
01:37:23,280 --> 01:37:26,960
Speaker 1: I'd say no, I just I just go hunting. I

1814
01:37:27,120 --> 01:37:31,040
Speaker 1: just go hunting and putting them I because well, the

1815
01:37:31,080 --> 01:37:32,760
Speaker 1: thing I have to I have to tell you this

1816
01:37:32,920 --> 01:37:35,360
Speaker 1: is one of Pat's favorite subjects, what phase of the

1817
01:37:35,479 --> 01:37:38,479
Speaker 1: rut we're in? It's inside joke with him and I

1818
01:37:38,640 --> 01:37:42,320
Speaker 1: free here because we have some mutual well a friend

1819
01:37:42,320 --> 01:37:44,280
Speaker 1: of his acquaintance of mine who just I can't get

1820
01:37:44,320 --> 01:37:46,280
Speaker 1: on the same page with these deer and what what

1821
01:37:46,400 --> 01:37:48,599
Speaker 1: phases of the ruddy was? So in the fall I'll

1822
01:37:48,840 --> 01:37:50,639
Speaker 1: contact Pat every once in a while and just ask

1823
01:37:50,720 --> 01:37:52,160
Speaker 1: him what phase of the rut do you think we're in?

1824
01:37:52,360 --> 01:37:55,400
Speaker 1: So moving to moving to anecdotal, what's your take on?

1825
01:37:55,800 --> 01:37:59,639
Speaker 1: What's your take on lunar phases? Dog? Just like rob

1826
01:37:59,720 --> 01:38:03,479
Speaker 1: person observations, don't you ignore what what you like, if

1827
01:38:03,520 --> 01:38:05,280
Speaker 1: anything you read just because you like to pay attention

1828
01:38:05,280 --> 01:38:09,160
Speaker 1: to dear and who's shooting to your wind and what

1829
01:38:09,439 --> 01:38:13,240
Speaker 1: and how? And you know, I really don't even have

1830
01:38:13,320 --> 01:38:16,360
Speaker 1: an opinion about it because I feel the same way

1831
01:38:16,400 --> 01:38:19,320
Speaker 1: I see, Dear, look at me, do a little shining

1832
01:38:19,320 --> 01:38:21,600
Speaker 1: and the fall we'll see. I'll see dear lying in

1833
01:38:21,760 --> 01:38:24,800
Speaker 1: fields you know when when you can shine, you know,

1834
01:38:24,960 --> 01:38:29,519
Speaker 1: before ten o'clock at night. Um, I always think your

1835
01:38:29,560 --> 01:38:31,800
Speaker 1: activities based way more on what the weather. I was

1836
01:38:31,800 --> 01:38:33,800
Speaker 1: just wanna say the same thing. I mean, I know

1837
01:38:33,960 --> 01:38:35,960
Speaker 1: you asked me yes or no? A gun to your head. Question,

1838
01:38:36,040 --> 01:38:39,479
Speaker 1: but God, God with a gun, Well, God would't need

1839
01:38:39,520 --> 01:38:46,320
Speaker 1: a gun. Gotta just be he has it, so you

1840
01:38:46,360 --> 01:38:49,640
Speaker 1: know he's serious. My My big thing comes to the

1841
01:38:49,760 --> 01:38:52,720
Speaker 1: rut is the daytime temperature of the daytime templtures abo

1842
01:38:52,960 --> 01:38:56,080
Speaker 1: above forty five degrees. That's when I get bummed out,

1843
01:38:56,120 --> 01:38:58,120
Speaker 1: Like God, the dear probably be moving as much this

1844
01:38:58,320 --> 01:39:00,760
Speaker 1: this for him to get the heavy quote on. I

1845
01:39:00,840 --> 01:39:02,519
Speaker 1: just think that, well, there's more of a bigger pets.

1846
01:39:02,600 --> 01:39:05,080
Speaker 1: You're you're an air tip man, much more, much more

1847
01:39:05,160 --> 01:39:07,800
Speaker 1: than nooner. Yeah. Now let me ask you one last one.

1848
01:39:09,960 --> 01:39:14,360
Speaker 1: Does cameo matter? And I'm not talking yeah, just like

1849
01:39:15,000 --> 01:39:17,040
Speaker 1: I just want you to give me sort of from

1850
01:39:17,040 --> 01:39:19,639
Speaker 1: because because you stay up on the on the research. Okay,

1851
01:39:20,160 --> 01:39:22,840
Speaker 1: so not not personal experience, but just like from your

1852
01:39:23,000 --> 01:39:28,840
Speaker 1: assessment of the research. Uh, what are dear seeing? Does

1853
01:39:28,920 --> 01:39:31,480
Speaker 1: camel matter? Like? What's kind of like the current fashionable

1854
01:39:31,560 --> 01:39:38,240
Speaker 1: feeling the thing I wrote this recently about camel basically

1855
01:39:38,360 --> 01:39:40,400
Speaker 1: and colors, you know, like if you' getting the whole

1856
01:39:40,400 --> 01:39:43,080
Speaker 1: color vision, what can deer seeing colors? And the biggest

1857
01:39:43,160 --> 01:39:46,519
Speaker 1: thing by far is movement. It doesn't matter what you're

1858
01:39:46,640 --> 01:39:49,040
Speaker 1: if you move make any kind of sudden jerky movement.

1859
01:39:50,120 --> 01:39:54,040
Speaker 1: Deer are just so tuned in to movement and they

1860
01:39:54,120 --> 01:39:55,680
Speaker 1: half but I think it's like a three year and

1861
01:39:55,720 --> 01:39:59,320
Speaker 1: ten degree area they can see that they don't see

1862
01:39:59,360 --> 01:40:01,560
Speaker 1: real right above them, which we most of us know.

1863
01:40:01,880 --> 01:40:03,479
Speaker 1: But that's why, dear, they get bow hunted a lot,

1864
01:40:03,560 --> 01:40:06,760
Speaker 1: walk around looking at what they do. Yeah, but but

1865
01:40:06,920 --> 01:40:09,160
Speaker 1: but because I remember growing up and being like, how's

1866
01:40:09,160 --> 01:40:14,280
Speaker 1: that somebody's going around looking up in the trees. Yeah,

1867
01:40:14,600 --> 01:40:18,680
Speaker 1: but um, what what we do know about camel is

1868
01:40:18,760 --> 01:40:21,320
Speaker 1: that if you're not choose a camel that what I've

1869
01:40:21,360 --> 01:40:25,360
Speaker 1: been reading on this is that dear, dear can see

1870
01:40:25,680 --> 01:40:28,599
Speaker 1: shades of gray, and so the lighter shades are gray

1871
01:40:29,080 --> 01:40:32,280
Speaker 1: and the letters tans. They think they shouldn't be able

1872
01:40:32,280 --> 01:40:35,000
Speaker 1: to ascertn those lot better than can the darker hues.

1873
01:40:35,720 --> 01:40:37,800
Speaker 1: So that the camel that has a lot of a

1874
01:40:37,840 --> 01:40:41,519
Speaker 1: lot of light tanned light grays, I'd avoid those. So

1875
01:40:41,680 --> 01:40:44,160
Speaker 1: that like the cou camel that's meant to look like

1876
01:40:44,240 --> 01:40:48,840
Speaker 1: you're laying on a gravel bar, that's a lot of

1877
01:40:48,960 --> 01:40:51,880
Speaker 1: light grays. Yeah, I guess like where I hunt, I'd

1878
01:40:51,880 --> 01:40:53,760
Speaker 1: probably go with the darker stuff, is what I'm saying,

1879
01:40:54,040 --> 01:40:58,680
Speaker 1: but now there's environments for I would still say if

1880
01:40:58,720 --> 01:41:01,519
Speaker 1: I wasn't giving anybody advice trying to match for we

1881
01:41:01,560 --> 01:41:04,200
Speaker 1: are in a common sense, you know, yeah, you know,

1882
01:41:04,600 --> 01:41:06,400
Speaker 1: and you think that you think that the research bears

1883
01:41:06,479 --> 01:41:09,559
Speaker 1: that out, well, what the research has show, but they're

1884
01:41:09,600 --> 01:41:13,120
Speaker 1: not on some whole other trip seeing some whole other

1885
01:41:13,320 --> 01:41:15,599
Speaker 1: because you know, there's this stuff that came out about birds,

1886
01:41:15,640 --> 01:41:17,759
Speaker 1: like birds have a lot of iridescence in their feathers,

1887
01:41:18,240 --> 01:41:21,799
Speaker 1: and like people start to think that when the birds

1888
01:41:21,840 --> 01:41:24,840
Speaker 1: sees a bird's iridescence, it's on this whole other level

1889
01:41:24,920 --> 01:41:27,280
Speaker 1: that you can't even begin to think about what a

1890
01:41:27,840 --> 01:41:30,040
Speaker 1: turkey looks like to a turkey, or what what a

1891
01:41:30,560 --> 01:41:32,400
Speaker 1: I think this stuff had to do with green parrots

1892
01:41:32,479 --> 01:41:34,439
Speaker 1: or something. Some of the research it's like what he

1893
01:41:34,520 --> 01:41:36,679
Speaker 1: sees when he sees that thing, he's not he doesn't

1894
01:41:36,720 --> 01:41:40,400
Speaker 1: see anything like what you see. It's a completely different

1895
01:41:40,439 --> 01:41:42,519
Speaker 1: experience for him to see that. But see, I remember

1896
01:41:42,640 --> 01:41:44,719
Speaker 1: when they first come up to something really good color

1897
01:41:44,840 --> 01:41:48,599
Speaker 1: vision research back about I think it was the first

1898
01:41:48,680 --> 01:41:50,880
Speaker 1: thing that Dr Carl Miller from the University of Georgia

1899
01:41:50,880 --> 01:41:53,639
Speaker 1: put on the screen. What's a picture of a buck

1900
01:41:54,680 --> 01:41:56,439
Speaker 1: dressed up to the hunter he had. He had a

1901
01:41:56,600 --> 01:41:59,600
Speaker 1: little orange hat on, had some classes on. And the

1902
01:41:59,720 --> 01:42:02,080
Speaker 1: point teammate to start off his talk about what deer

1903
01:42:02,200 --> 01:42:05,720
Speaker 1: see says, until we can somehow tap into that animal's

1904
01:42:05,840 --> 01:42:10,280
Speaker 1: brain and actually see what information is passing through the

1905
01:42:10,360 --> 01:42:12,840
Speaker 1: eye into the brain and how he's perceiving that, we'll

1906
01:42:12,880 --> 01:42:15,760
Speaker 1: never know for certain exactly what they're seeing, because you know,

1907
01:42:16,040 --> 01:42:18,800
Speaker 1: their capabilities are so much different from ours. You know,

1908
01:42:18,800 --> 01:42:22,679
Speaker 1: like you read about a deer's nose for example, being

1909
01:42:23,720 --> 01:42:25,720
Speaker 1: like the human nose. I guess they think we have

1910
01:42:25,800 --> 01:42:28,920
Speaker 1: about five million cent receptors in our nose. That deer

1911
01:42:29,000 --> 01:42:34,920
Speaker 1: has like three million million cent receptors. So sent to

1912
01:42:35,120 --> 01:42:38,160
Speaker 1: us compared to a deers is irrelevant. You imagine when

1913
01:42:38,240 --> 01:42:40,040
Speaker 1: you know that we can't begin to comprehend what that

1914
01:42:40,120 --> 01:42:43,360
Speaker 1: deer's picking off all the error. So and I think

1915
01:42:43,439 --> 01:42:45,920
Speaker 1: there's probably things with their vision to that from what

1916
01:42:46,200 --> 01:42:48,519
Speaker 1: from what we know You get back to your question

1917
01:42:48,600 --> 01:42:51,360
Speaker 1: about what does the research show about the camel, Well,

1918
01:42:51,400 --> 01:42:53,479
Speaker 1: the research can't. I don't think anyone's like going in

1919
01:42:53,520 --> 01:42:55,640
Speaker 1: the research as far as trying to match up how

1920
01:42:55,840 --> 01:42:58,559
Speaker 1: how different cameras work in different environments, because how would

1921
01:42:58,560 --> 01:43:00,760
Speaker 1: you do that? You know, the best they can do

1922
01:43:00,960 --> 01:43:03,760
Speaker 1: is the that's this researcher again at the University of

1923
01:43:03,800 --> 01:43:06,439
Speaker 1: Georgia where they have this this test set up to

1924
01:43:06,640 --> 01:43:11,120
Speaker 1: um show the deer colors on on lighted colors over

1925
01:43:11,240 --> 01:43:13,840
Speaker 1: feed bins. If they choose the wrong color, the feed

1926
01:43:13,880 --> 01:43:17,680
Speaker 1: bin won't feed feed bill, feedbin shuts well. Over time

1927
01:43:17,720 --> 01:43:19,960
Speaker 1: they get these dear train when they can start identifying colors,

1928
01:43:20,040 --> 01:43:23,880
Speaker 1: which which colors they can identify to know that well,

1929
01:43:23,920 --> 01:43:26,000
Speaker 1: ask for the food will be and what they've fallen

1930
01:43:26,000 --> 01:43:30,040
Speaker 1: there was that these lighter, lighter shades of gray and white,

1931
01:43:30,200 --> 01:43:32,800
Speaker 1: those kind of you know, lighter colors, they gets into

1932
01:43:32,840 --> 01:43:36,200
Speaker 1: bility discern lest pretty well. And you're saying, like if

1933
01:43:36,240 --> 01:43:39,000
Speaker 1: there's like blue and purple next to each other, then

1934
01:43:39,240 --> 01:43:41,599
Speaker 1: they can't sign up. But but but deer to there,

1935
01:43:41,680 --> 01:43:44,880
Speaker 1: they're they're blue. Ability to see blue again blows ours

1936
01:43:44,920 --> 01:43:47,280
Speaker 1: out of the water. We can't begin to comprehend how

1937
01:43:47,320 --> 01:43:50,000
Speaker 1: well they see. That's never heard, like I've read two

1938
01:43:50,040 --> 01:43:53,639
Speaker 1: our guys are saying like, like it seems that one

1939
01:43:53,720 --> 01:43:57,640
Speaker 1: thing is certain. Don't wear blue, yeah, yeah, and and

1940
01:43:57,760 --> 01:43:59,760
Speaker 1: but you know again, like banks, what you're saying earlier though,

1941
01:44:00,000 --> 01:44:02,000
Speaker 1: and this is just this is just anecdotal, but it's

1942
01:44:02,000 --> 01:44:06,240
Speaker 1: based off a ton of like a lot of personal experience. Okay,

1943
01:44:06,760 --> 01:44:11,160
Speaker 1: like I said, like Jackass on TV guy Ship, but

1944
01:44:11,439 --> 01:44:15,160
Speaker 1: a lot of first experience that I have had things

1945
01:44:15,320 --> 01:44:21,320
Speaker 1: come up, like when you're not moving, come up and

1946
01:44:21,400 --> 01:44:24,360
Speaker 1: they just can't they just can't comprehend you, or they're

1947
01:44:24,479 --> 01:44:28,880
Speaker 1: looking this is the probably trip me. Now they're looking,

1948
01:44:29,120 --> 01:44:31,000
Speaker 1: they're not putting it together. It's a threat, but they're

1949
01:44:31,080 --> 01:44:35,320
Speaker 1: curious about what they're looking at. So they're like, not

1950
01:44:35,439 --> 01:44:37,280
Speaker 1: that I see it, dear, I just see something I

1951
01:44:37,280 --> 01:44:39,360
Speaker 1: don't or not that I see a person or a threat.

1952
01:44:39,400 --> 01:44:41,840
Speaker 1: I just see something I don't understand. And they're looking

1953
01:44:41,920 --> 01:44:45,320
Speaker 1: at you, but not no fear. There's like they see

1954
01:44:45,400 --> 01:44:48,120
Speaker 1: something they haven't seen well, And then I think they're

1955
01:44:48,160 --> 01:44:50,799
Speaker 1: like seeing it's gotta be they're seeing like a collection

1956
01:44:50,840 --> 01:44:54,120
Speaker 1: of colors or a collection of shapes that's unfamiliar, because

1957
01:44:54,560 --> 01:44:58,120
Speaker 1: even coming toward it, ears perked forward coming at you,

1958
01:44:59,479 --> 01:45:02,080
Speaker 1: just being like hell is that more curious? The same

1959
01:45:02,120 --> 01:45:04,040
Speaker 1: way deer go up to trail games, it's like, yeah,

1960
01:45:04,080 --> 01:45:06,720
Speaker 1: what the hell's that thing? Those four and they go

1961
01:45:06,840 --> 01:45:08,280
Speaker 1: up to it to be like, what is it? You know?

1962
01:45:08,520 --> 01:45:12,120
Speaker 1: And I've seen um. I used to hunt um northwestern

1963
01:45:12,160 --> 01:45:14,920
Speaker 1: Ontario for deer quite often back in the in the

1964
01:45:15,040 --> 01:45:18,400
Speaker 1: nineties and in late nineties, early two thousand's, and it's

1965
01:45:18,479 --> 01:45:22,240
Speaker 1: my place I ever seen this. I the biggest, the

1966
01:45:22,400 --> 01:45:24,200
Speaker 1: buck I'm most proud of as a hunter that I

1967
01:45:24,320 --> 01:45:30,320
Speaker 1: killed was up in Ontario. And that buck I was

1968
01:45:30,400 --> 01:45:32,760
Speaker 1: looking at me for the longest time until I think

1969
01:45:32,800 --> 01:45:34,280
Speaker 1: he's looking at me for a long time before I

1970
01:45:34,280 --> 01:45:36,960
Speaker 1: actually saw him, because I was on this little precipice

1971
01:45:37,439 --> 01:45:40,400
Speaker 1: looking in this valley below me. There's a recent clear

1972
01:45:40,439 --> 01:45:43,120
Speaker 1: cut me a ten year old clear cut. And I

1973
01:45:43,200 --> 01:45:46,120
Speaker 1: looked up into the jackpines across from above yards away

1974
01:45:46,120 --> 01:45:47,519
Speaker 1: and I saw the haunch of a deer. I thought,

1975
01:45:47,560 --> 01:45:49,880
Speaker 1: that's gonna be a deer and I looked, there's only

1976
01:45:49,960 --> 01:45:52,160
Speaker 1: the third deer I saw it in seven days. I

1977
01:45:52,240 --> 01:45:53,640
Speaker 1: got my scope up because I knew it was a

1978
01:45:53,680 --> 01:45:56,760
Speaker 1: deer and it wasn't any thought about that, and I thought,

1979
01:45:57,000 --> 01:45:59,200
Speaker 1: that's a buck. I'm gonna be ready to shoot. I

1980
01:45:59,560 --> 01:46:04,800
Speaker 1: got sorry, yeah, on trigger hand, but I make a

1981
01:46:04,840 --> 01:46:07,599
Speaker 1: long story short, I got I got that scoope up

1982
01:46:08,320 --> 01:46:10,120
Speaker 1: a deer is looking right at me. It looked like

1983
01:46:10,200 --> 01:46:11,559
Speaker 1: the way he was looking at me is like he's

1984
01:46:11,560 --> 01:46:15,240
Speaker 1: probably watched me for a while, curious, curious, like what

1985
01:46:15,360 --> 01:46:16,720
Speaker 1: the hell is that over there? Because I often to

1986
01:46:16,760 --> 01:46:19,920
Speaker 1: see many humans in that particular area. And I killed him,

1987
01:46:20,120 --> 01:46:23,080
Speaker 1: and I bought two years later, similar thing happened to

1988
01:46:23,360 --> 01:46:25,920
Speaker 1: my buddy and I just guy named Bruce Ranta losing

1989
01:46:26,080 --> 01:46:29,360
Speaker 1: in Canora, Ontario. We're moving along this this old granite

1990
01:46:29,400 --> 01:46:34,720
Speaker 1: face looked across these big openings up in top right right.

1991
01:46:35,280 --> 01:46:37,040
Speaker 1: Not just like he rolls out of the ground, which

1992
01:46:37,080 --> 01:46:39,920
Speaker 1: he literally did, this book stands up and this looks

1993
01:46:39,920 --> 01:46:42,400
Speaker 1: at us. Didn't run off to like a typical deer

1994
01:46:42,400 --> 01:46:44,680
Speaker 1: around here would do. Just there looked at us. And

1995
01:46:44,880 --> 01:46:47,320
Speaker 1: I had time where I didn't. It wasn't like I

1996
01:46:47,360 --> 01:46:49,200
Speaker 1: took my time, but I hit the ground and got

1997
01:46:49,240 --> 01:46:52,439
Speaker 1: my rifle up and shut him off the prone position

1998
01:46:53,160 --> 01:46:55,840
Speaker 1: and nailed him and he went down. And so I thought,

1999
01:46:55,840 --> 01:46:58,280
Speaker 1: that's twice I've had bucks in these areas that are

2000
01:46:58,360 --> 01:47:01,600
Speaker 1: hunted very often just looked me over out of curiosity.

2001
01:47:01,720 --> 01:47:03,720
Speaker 1: You know, they don't do They're never curious about what

2002
01:47:03,800 --> 01:47:09,000
Speaker 1: they smell exactly. Yeah, they never questioned their nose. That's

2003
01:47:10,000 --> 01:47:11,840
Speaker 1: I think that you can take that one to the bank. Ye,

2004
01:47:13,320 --> 01:47:17,760
Speaker 1: I don't need no outdoor columns and tell me that, well,

2005
01:47:18,400 --> 01:47:19,960
Speaker 1: can you throw out the stories? I want to know

2006
01:47:20,040 --> 01:47:23,920
Speaker 1: why you're most proud of that, because because because just

2007
01:47:23,960 --> 01:47:27,200
Speaker 1: because that sty conditions. No. Yeah, it was a really

2008
01:47:27,240 --> 01:47:30,840
Speaker 1: tough hunt. It was. I had eight days to hunt it,

2009
01:47:31,760 --> 01:47:34,800
Speaker 1: and I was I was bound, determined not to leave

2010
01:47:34,960 --> 01:47:38,840
Speaker 1: till I put in my full time, and going into

2011
01:47:38,880 --> 01:47:43,200
Speaker 1: that seventh day, I've only seen one deer distance where

2012
01:47:43,560 --> 01:47:46,400
Speaker 1: s Norton and I had one little buck I passed

2013
01:47:46,479 --> 01:47:48,160
Speaker 1: up the first day, which I was not gonna go

2014
01:47:48,200 --> 01:47:49,679
Speaker 1: all the way down Tarry and shoot a four corn,

2015
01:47:49,760 --> 01:47:51,599
Speaker 1: you know, so I let it go. But I got

2016
01:47:51,640 --> 01:47:52,880
Speaker 1: down to where I knew I was done in my

2017
01:47:52,920 --> 01:47:54,639
Speaker 1: final afternoon, I want more and more in the goal.

2018
01:47:55,600 --> 01:47:58,000
Speaker 1: And I another reason I was proud of it, because

2019
01:47:58,040 --> 01:48:00,320
Speaker 1: I remember was a big old fatty. It was a

2020
01:48:00,400 --> 01:48:03,880
Speaker 1: big book. He wied to forty dressed out. I said,

2021
01:48:03,880 --> 01:48:07,080
Speaker 1: a beautiful cathedral type ract. It's a real tight thirteen

2022
01:48:07,520 --> 01:48:11,120
Speaker 1: and a half being spread. Beautiful deer and what was

2023
01:48:11,280 --> 01:48:12,360
Speaker 1: what I was really one of the things I was

2024
01:48:12,400 --> 01:48:15,559
Speaker 1: proud of too, not only the fact I persevered through

2025
01:48:15,600 --> 01:48:19,200
Speaker 1: that kind of tough hunt and I got up on

2026
01:48:19,240 --> 01:48:21,360
Speaker 1: the spot and it's like two o'clock in the afternoon.

2027
01:48:21,600 --> 01:48:24,360
Speaker 1: There's actually one fifty one fifteen the afternoon. Because I

2028
01:48:24,360 --> 01:48:28,240
Speaker 1: looked my watchupter I killed him, and I was looking around,

2029
01:48:28,400 --> 01:48:29,760
Speaker 1: and I thought, this is a cool spot I might

2030
01:48:29,800 --> 01:48:32,439
Speaker 1: come back through tomorrow morning. And I had when these

2031
01:48:32,479 --> 01:48:35,320
Speaker 1: old GPS units, from the original GPS units that Lawrence

2032
01:48:35,400 --> 01:48:39,280
Speaker 1: made it that this tall, and they had these in

2033
01:48:39,320 --> 01:48:41,880
Speaker 1: a big cargo pocket and marred locking that spot in.

2034
01:48:42,880 --> 01:48:45,960
Speaker 1: And then as I snapped a little button number in

2035
01:48:46,040 --> 01:48:47,920
Speaker 1: that little snap, and I thought, God, that was loud.

2036
01:48:48,479 --> 01:48:50,559
Speaker 1: And I thought, and it was a quiet deal like today,

2037
01:48:51,240 --> 01:48:54,640
Speaker 1: I thought, before I budge a bear, look around real

2038
01:48:54,720 --> 01:48:57,880
Speaker 1: carefully before I budget, I thought, I looked around and

2039
01:48:58,200 --> 01:49:00,160
Speaker 1: see that haunch and I killed him. I thought, uh,

2040
01:49:00,680 --> 01:49:02,640
Speaker 1: you know so often you do that kind of thing,

2041
01:49:02,720 --> 01:49:05,040
Speaker 1: you get you down. Couldn't have got it done without

2042
01:49:05,080 --> 01:49:08,960
Speaker 1: my lower ants, yeah, I think. And then and now

2043
01:49:09,040 --> 01:49:11,639
Speaker 1: that's from the beauties. One of the beautiful things about hunting.

2044
01:49:12,120 --> 01:49:15,680
Speaker 1: It's those kind of little odd twist like that. For

2045
01:49:15,800 --> 01:49:18,320
Speaker 1: all I know, just because I stopped long enough what

2046
01:49:18,400 --> 01:49:20,360
Speaker 1: I'm thinking you happened when I'm back, I backtracked that

2047
01:49:20,400 --> 01:49:22,840
Speaker 1: buck in the snow. It it looks like came down

2048
01:49:22,880 --> 01:49:25,439
Speaker 1: off this hill. I betchered about the time I was

2049
01:49:25,600 --> 01:49:28,719
Speaker 1: playing around that GPS unit came up in a little spot,

2050
01:49:28,880 --> 01:49:31,920
Speaker 1: and I think what stopped him was that that snap. Yeah,

2051
01:49:32,000 --> 01:49:34,280
Speaker 1: I snapped, and then he looked across and saw me,

2052
01:49:34,360 --> 01:49:37,519
Speaker 1: and I meanwhile, I'm looking down here scanning the hillside,

2053
01:49:37,560 --> 01:49:40,360
Speaker 1: and there he is. I shoot him. So but I

2054
01:49:40,360 --> 01:49:42,320
Speaker 1: always think, oh, there's little things that we always write

2055
01:49:42,320 --> 01:49:43,960
Speaker 1: off as you know, hunters skills. I think a lot

2056
01:49:44,000 --> 01:49:46,559
Speaker 1: of times just you were you, you got him because

2057
01:49:46,600 --> 01:49:48,800
Speaker 1: you stayed alert, but you also got because a fluke,

2058
01:49:49,000 --> 01:49:52,479
Speaker 1: you know, snapping the button. And I was going to

2059
01:49:52,560 --> 01:49:57,560
Speaker 1: say that hadn't seen a You were speculating that he

2060
01:49:57,560 --> 01:49:59,600
Speaker 1: hadn't seen a human before, and you were on this

2061
01:49:59,720 --> 01:50:02,240
Speaker 1: press spiss that might have been a spot that he

2062
01:50:02,400 --> 01:50:04,479
Speaker 1: was familiar with, and he goes, that doesn't belong there.

2063
01:50:05,320 --> 01:50:07,160
Speaker 1: And so since he didn't feel you were a threat,

2064
01:50:07,240 --> 01:50:10,600
Speaker 1: he's just standing there and I wasn't moving. It's like

2065
01:50:10,720 --> 01:50:17,519
Speaker 1: Steve said, Yeah, I've definitely been like fortunate to hang

2066
01:50:17,600 --> 01:50:22,080
Speaker 1: out in areas where you can safely assume they have

2067
01:50:22,200 --> 01:50:25,479
Speaker 1: never encountered a human and it's just it's a different experience,

2068
01:50:25,880 --> 01:50:30,240
Speaker 1: is they You know, the way that high pressure animals

2069
01:50:30,320 --> 01:50:34,400
Speaker 1: react to humans is a learned behavior. You know, there

2070
01:50:34,400 --> 01:50:36,840
Speaker 1: are a thing that goes into this too. As far

2071
01:50:36,920 --> 01:50:38,360
Speaker 1: as um why it might have been looking at me

2072
01:50:39,200 --> 01:50:44,360
Speaker 1: that long with dom seeing, I think came on headed

2073
01:50:44,439 --> 01:50:47,760
Speaker 1: to a hot pink the um well, because at that

2074
01:50:47,920 --> 01:50:50,200
Speaker 1: this tense that I was probably twenty five yards away

2075
01:50:50,240 --> 01:50:53,800
Speaker 1: and from from the best guests the researchers can make

2076
01:50:53,840 --> 01:50:56,559
Speaker 1: on deer vision, they figured the dearest vision is probably

2077
01:50:56,640 --> 01:51:00,439
Speaker 1: bought the equivalent of our vision. That we don't know

2078
01:51:00,479 --> 01:51:03,879
Speaker 1: what that means if you's like visions, you know, perfect

2079
01:51:04,640 --> 01:51:08,400
Speaker 1: good vision, really good human vision. They figured that there

2080
01:51:08,439 --> 01:51:10,840
Speaker 1: is about twenty one hundred that what we see clear

2081
01:51:11,040 --> 01:51:17,720
Speaker 1: a hundred they see. How's that work? Um, basically I can't.

2082
01:51:17,800 --> 01:51:20,760
Speaker 1: I'm not going to explain this stuff. But it's worse,

2083
01:51:22,400 --> 01:51:25,360
Speaker 1: far worse than ours, And so they probably see kind

2084
01:51:25,360 --> 01:51:28,000
Speaker 1: of a blurry image at that range in a hundred yards,

2085
01:51:28,160 --> 01:51:29,840
Speaker 1: they probably can make it out, but it's not really

2086
01:51:30,000 --> 01:51:32,800
Speaker 1: sharp like our I got out. I was really sharp

2087
01:51:32,920 --> 01:51:35,040
Speaker 1: vision like me wearing glasses at a hundred yards, I

2088
01:51:35,040 --> 01:51:38,840
Speaker 1: can see I can make things out prefine detail, and

2089
01:51:39,000 --> 01:51:41,400
Speaker 1: that the best research they've done now recently. Then, you know,

2090
01:51:41,439 --> 01:51:43,720
Speaker 1: like Carl Miller will say, if I get down to

2091
01:51:43,800 --> 01:51:46,080
Speaker 1: chemo patterns, you could probably do really well as it's

2092
01:51:46,080 --> 01:51:48,760
Speaker 1: a blurry pattern, you know, not not you don't need

2093
01:51:48,800 --> 01:51:51,800
Speaker 1: all these fine details because deer can't see us find

2094
01:51:51,840 --> 01:52:00,360
Speaker 1: details anyway. Alright, anything you want to add, i'd something

2095
01:52:00,360 --> 01:52:03,280
Speaker 1: I want to end there was we were going to

2096
01:52:03,400 --> 01:52:06,840
Speaker 1: talk at possibly about the U League, the movement to

2097
01:52:06,960 --> 01:52:14,960
Speaker 1: league lies sail dear me. Yeah, yeah, because I think

2098
01:52:15,080 --> 01:52:17,200
Speaker 1: I feel like you wrote a thing I didn't. You

2099
01:52:17,280 --> 01:52:19,000
Speaker 1: wrote a thing kind of like, oh yeah, you know,

2100
01:52:19,240 --> 01:52:22,000
Speaker 1: it could be cool. Maybe not. What I did is

2101
01:52:22,080 --> 01:52:23,599
Speaker 1: I might be a little bit pissed at you when

2102
01:52:23,600 --> 01:52:25,400
Speaker 1: I read that. I remember you telling me that, yeah,

2103
01:52:26,920 --> 01:52:30,200
Speaker 1: because Steve, Steve, I remember I was somewhere, I was

2104
01:52:30,280 --> 01:52:33,800
Speaker 1: like out of town somewhere, and I read that and

2105
01:52:34,080 --> 01:52:38,560
Speaker 1: I was like, damn, pant Dirk. And I remember you

2106
01:52:38,680 --> 01:52:40,760
Speaker 1: writing me and said just like just saying no, I

2107
01:52:41,200 --> 01:52:46,920
Speaker 1: totally disagreed with that, and I which I which I

2108
01:52:46,960 --> 01:52:48,880
Speaker 1: don't want to be on that path. But I really,

2109
01:52:48,960 --> 01:52:51,360
Speaker 1: I really like that. I don't mind people disagree with me.

2110
01:52:51,400 --> 01:52:53,080
Speaker 1: I was figuring out, which this is the mode you

2111
01:52:53,200 --> 01:52:55,880
Speaker 1: probably wrote it in the big Hey day when everyone

2112
01:52:55,960 --> 01:52:58,200
Speaker 1: thought that across the country that we're just gonna have

2113
01:52:58,320 --> 01:53:01,200
Speaker 1: more and more and more and more, dear well, which

2114
01:53:01,280 --> 01:53:03,040
Speaker 1: is like like turkeys, So we got a lot of turkeys,

2115
01:53:03,120 --> 01:53:05,960
Speaker 1: let's start shooting hands and killing them year around. And

2116
01:53:06,920 --> 01:53:09,920
Speaker 1: my interest in it was, um, what what triggered my

2117
01:53:09,960 --> 01:53:13,240
Speaker 1: interest in it in all seriousness was I was I

2118
01:53:13,360 --> 01:53:16,760
Speaker 1: was visiting my daughter who was stationed then at the

2119
01:53:17,680 --> 01:53:20,800
Speaker 1: Navy Hospital in Naples, Italy, and we went to we

2120
01:53:20,920 --> 01:53:23,360
Speaker 1: spent UM some time out in Florence. So this is

2121
01:53:23,400 --> 01:53:26,519
Speaker 1: two thousand thirteen. We went into this really neat restaurant

2122
01:53:26,520 --> 01:53:30,160
Speaker 1: in Florence and they're in the menu it says for

2123
01:53:30,439 --> 01:53:34,639
Speaker 1: um is for venison and for pork that these meats

2124
01:53:35,680 --> 01:53:38,760
Speaker 1: during the hunting season are fresh fresh from that day,

2125
01:53:39,320 --> 01:53:41,800
Speaker 1: and the rest of the season they're frozen. I thought,

2126
01:53:41,840 --> 01:53:43,880
Speaker 1: that's kind of cool. You can actually get you know,

2127
01:53:44,840 --> 01:53:48,479
Speaker 1: you know, hunter killed that UM. It's called the European model.

2128
01:53:48,520 --> 01:53:52,240
Speaker 1: Of it's called the European model. And so do I

2129
01:53:52,320 --> 01:53:53,600
Speaker 1: need to I don't need to tell you about all

2130
01:53:53,600 --> 01:53:59,920
Speaker 1: about American history. But well that it got me thinking,

2131
01:54:00,040 --> 01:54:03,880
Speaker 1: know that I just come from Sweden. I've been up

2132
01:54:03,880 --> 01:54:07,320
Speaker 1: in Stockholm and up up in Stockholm in Sweden. Um

2133
01:54:07,800 --> 01:54:12,560
Speaker 1: people up there, it's the thing that they do is

2134
01:54:12,640 --> 01:54:16,240
Speaker 1: they they don't If I want to sell Yanni some

2135
01:54:16,400 --> 01:54:18,800
Speaker 1: meat from last year's dear, I could do that in

2136
01:54:19,760 --> 01:54:23,240
Speaker 1: Stockholm in Sweden, and and but a lot of them don't.

2137
01:54:23,400 --> 01:54:24,960
Speaker 1: I mean they can legally do it, but a lot

2138
01:54:24,960 --> 01:54:26,800
Speaker 1: of them still don't do it. They but a lot

2139
01:54:26,800 --> 01:54:29,160
Speaker 1: of them they'll take meat and just give it to

2140
01:54:29,240 --> 01:54:31,280
Speaker 1: them as a gift, like like we kind of like

2141
01:54:31,360 --> 01:54:34,080
Speaker 1: what we do. But but but I guess my point

2142
01:54:34,120 --> 01:54:37,040
Speaker 1: in that article, the thing I got talking about by

2143
01:54:37,120 --> 01:54:39,640
Speaker 1: interviewing some of the Swedish hunters and some of the

2144
01:54:40,080 --> 01:54:43,560
Speaker 1: different people who have worked in both systems, is that

2145
01:54:45,000 --> 01:54:48,040
Speaker 1: you know, we're we could we could probably do this.

2146
01:54:48,400 --> 01:54:50,600
Speaker 1: But I take a whole lot of rethinking of the

2147
01:54:50,640 --> 01:54:54,160
Speaker 1: American model and how we do things in America. But

2148
01:54:54,320 --> 01:54:56,640
Speaker 1: there are there are certain circumstances which I think was

2149
01:54:56,680 --> 01:54:59,920
Speaker 1: what maybe what piste you off was that there are

2150
01:55:00,000 --> 01:55:02,440
Speaker 1: areas in this country where we really have hard time

2151
01:55:02,640 --> 01:55:06,640
Speaker 1: knocking deer numbers down, and so if you could give

2152
01:55:06,680 --> 01:55:10,680
Speaker 1: guys financial incentive to knock them down in some these

2153
01:55:10,680 --> 01:55:12,840
Speaker 1: suburban areas, whatever it might be, may not be a

2154
01:55:12,880 --> 01:55:14,880
Speaker 1: way to deal with this. And I just think in

2155
01:55:14,960 --> 01:55:17,320
Speaker 1: some cases, well it might be cases where are thinking

2156
01:55:17,360 --> 01:55:19,520
Speaker 1: might have to evolve in that. And I don't know

2157
01:55:19,560 --> 01:55:21,560
Speaker 1: if it's not happened anytime soon, I'll doubt would happen

2158
01:55:21,560 --> 01:55:24,800
Speaker 1: anytime soon. But I guess I'm one thing I liked

2159
01:55:24,800 --> 01:55:27,120
Speaker 1: about that that UM, the work I did in that

2160
01:55:27,360 --> 01:55:31,360
Speaker 1: from my workings UM talking to people on Sweden. One

2161
01:55:31,560 --> 01:55:36,400
Speaker 1: interesting nugget I found was that seventy of Swedes have

2162
01:55:36,600 --> 01:55:40,360
Speaker 1: eaten or eat wild meat every year, seventy percent of them.

2163
01:55:40,800 --> 01:55:43,200
Speaker 1: And I've looked around and I found some information for

2164
01:55:43,360 --> 01:55:45,680
Speaker 1: our country and the best data I can find in

2165
01:55:45,720 --> 01:55:49,840
Speaker 1: our countries about of Americans in a typical year will

2166
01:55:49,880 --> 01:55:55,000
Speaker 1: eat some kind of wild animals. So that than that. Yeah,

2167
01:55:55,040 --> 01:55:59,440
Speaker 1: and so again these all research is perfect. You know,

2168
01:55:59,560 --> 01:56:02,080
Speaker 1: It's like we talked about earlier, with populations, you never

2169
01:56:02,200 --> 01:56:04,919
Speaker 1: know how accurate all that stuff is about falling interesting,

2170
01:56:05,400 --> 01:56:08,400
Speaker 1: how much more those Swedes? And plus for you buy

2171
01:56:08,560 --> 01:56:11,800
Speaker 1: if you buy um hunter killed meat and Sweden, you're

2172
01:56:11,840 --> 01:56:14,440
Speaker 1: paying a real premium price for it. So what that

2173
01:56:14,560 --> 01:56:18,200
Speaker 1: does in their mind is that man, you want wild game,

2174
01:56:18,240 --> 01:56:20,160
Speaker 1: you're gonna pay You're not pay a price for it.

2175
01:56:20,960 --> 01:56:23,080
Speaker 1: And but then then but then they put a value

2176
01:56:23,120 --> 01:56:25,640
Speaker 1: on it, and that's really valuable to them. So when

2177
01:56:25,680 --> 01:56:27,160
Speaker 1: they can get it free, they think, oh, man, I

2178
01:56:27,280 --> 01:56:30,040
Speaker 1: have scored. And so they really have this higher appreciation

2179
01:56:30,160 --> 01:56:32,640
Speaker 1: of wild game that I'm not sure a lot of

2180
01:56:32,680 --> 01:56:36,560
Speaker 1: people in our country share, and which which worries me.

2181
01:56:36,640 --> 01:56:39,040
Speaker 1: And I don't know if I'm tracking I'm tracking you there,

2182
01:56:39,080 --> 01:56:41,960
Speaker 1: and I agree that that is the issue. So so

2183
01:56:42,160 --> 01:56:47,160
Speaker 1: that's the upside some things that when I wrote you

2184
01:56:47,200 --> 01:56:49,080
Speaker 1: that I don't agree with it, it was a couple

2185
01:56:49,080 --> 01:56:52,760
Speaker 1: of things. Um No, you're not like a real vocal

2186
01:56:52,800 --> 01:56:55,440
Speaker 1: advocate of this, you were just exploring the idea exactly.

2187
01:56:56,240 --> 01:57:01,880
Speaker 1: Um One, I think that like places, I mean, if

2188
01:57:01,880 --> 01:57:04,240
Speaker 1: you just look historically, places that now think they have

2189
01:57:04,320 --> 01:57:07,280
Speaker 1: this permanent problem with high deer numbers probably will not

2190
01:57:07,400 --> 01:57:09,280
Speaker 1: prove to have a permanent problem with high deer numbers.

2191
01:57:10,080 --> 01:57:13,600
Speaker 1: These things fluctuate wildly. So to go and like rewrite

2192
01:57:14,600 --> 01:57:18,640
Speaker 1: uh sort of the the to rewrite the underpinnings of

2193
01:57:18,840 --> 01:57:22,720
Speaker 1: our wildlife conservation success, which was the de commodification of

2194
01:57:22,760 --> 01:57:27,160
Speaker 1: wildlife and getting rid of market hunting, which saved American wildlife.

2195
01:57:28,680 --> 01:57:31,680
Speaker 1: To to try to address like a temporary problem that,

2196
01:57:31,800 --> 01:57:35,360
Speaker 1: by some estimates isn't even really a problem um by

2197
01:57:35,800 --> 01:57:43,720
Speaker 1: radically altering how we perceive and manage wildlife in America

2198
01:57:43,880 --> 01:57:45,640
Speaker 1: just seems to me like like a a kind of

2199
01:57:45,680 --> 01:57:52,000
Speaker 1: an overshot right, like way too much? Gun go ahead,

2200
01:57:52,080 --> 01:57:55,360
Speaker 1: du So. I'm in the County Dear Advisory communitee here

2201
01:57:55,360 --> 01:57:57,560
Speaker 1: from Richland County, and one of the things that came

2202
01:57:57,640 --> 01:58:03,120
Speaker 1: up as we've been talking about reducing the dear population was, well,

2203
01:58:03,240 --> 01:58:05,120
Speaker 1: I only use one deer, and you want to give

2204
01:58:05,160 --> 01:58:08,200
Speaker 1: me four tags? What are we going to do with that? In?

2205
01:58:08,240 --> 01:58:10,720
Speaker 1: The donation system doesn't seem to be working that well.

2206
01:58:10,800 --> 01:58:12,800
Speaker 1: And I, you know, I have a handful of people

2207
01:58:12,840 --> 01:58:16,520
Speaker 1: that I give uh that I give venison too. I'll

2208
01:58:16,560 --> 01:58:18,640
Speaker 1: take it to the locker. I mean, I don't generally

2209
01:58:18,680 --> 01:58:20,280
Speaker 1: cut up here for other people. So I'll take it

2210
01:58:20,320 --> 01:58:21,920
Speaker 1: to the locker and they'll pay the fee and they'll

2211
01:58:21,920 --> 01:58:24,880
Speaker 1: go and pick it up. And so at the County

2212
01:58:24,880 --> 01:58:28,240
Speaker 1: Deer Advisory Committee, people were, you know, asking about well,

2213
01:58:28,320 --> 01:58:30,160
Speaker 1: how do you how do you have this list of people?

2214
01:58:30,960 --> 01:58:34,360
Speaker 1: And a young man in his late twenties, I guess,

2215
01:58:34,760 --> 01:58:37,280
Speaker 1: stands up and says, you know what I'll do. I'll

2216
01:58:37,280 --> 01:58:40,280
Speaker 1: put a spreadsheet together of people who are and we

2217
01:58:40,360 --> 01:58:44,160
Speaker 1: can advertise it on social media or whatever, and we'll

2218
01:58:44,160 --> 01:58:48,240
Speaker 1: address that problem by here hunters who or you can

2219
01:58:48,240 --> 01:58:50,040
Speaker 1: sign up and say I'd like to have some venison,

2220
01:58:50,080 --> 01:58:54,120
Speaker 1: but I'm not a hunter, and then we can make

2221
01:58:54,200 --> 01:58:57,000
Speaker 1: that connection rather than like you know, feed the hungry

2222
01:58:57,160 --> 01:58:58,800
Speaker 1: or you know those sort of things, but given to

2223
01:58:58,920 --> 01:59:02,720
Speaker 1: the food pantry or in addition to that. Um. Great,

2224
01:59:03,600 --> 01:59:07,480
Speaker 1: And so there's the answer, sorter to the temporary problem. Use. Yeah,

2225
01:59:07,840 --> 01:59:12,240
Speaker 1: I'm all for a little bit of philanthropy. Um. Another

2226
01:59:12,240 --> 01:59:15,040
Speaker 1: problem I see, whether it is it brings in the commodification. Okay,

2227
01:59:15,080 --> 01:59:18,080
Speaker 1: so the commodification of wildlife, and then you're gonna also

2228
01:59:18,320 --> 01:59:22,880
Speaker 1: further commodify access. So I usually try to look at

2229
01:59:22,960 --> 01:59:28,080
Speaker 1: things like I'll oftentimes ask myself what's better for hunters

2230
01:59:28,920 --> 01:59:32,760
Speaker 1: and fishermen and wildlife. Right, So when I'm looking at issues,

2231
01:59:32,800 --> 01:59:36,440
Speaker 1: and I could just see that of all of a sudden, um,

2232
01:59:37,240 --> 01:59:40,440
Speaker 1: these deer all right, we're going back to the eighteen

2233
01:59:41,000 --> 01:59:43,040
Speaker 1: seventies and eighties all over again, when we shut off

2234
01:59:43,040 --> 01:59:45,280
Speaker 1: all of our wildlife and sold it to Eastern markets,

2235
01:59:45,720 --> 01:59:47,480
Speaker 1: that all of a sudden, the deer on my place

2236
01:59:47,560 --> 01:59:52,040
Speaker 1: are real valuable. I'll be you know, there's no way

2237
01:59:52,760 --> 01:59:56,240
Speaker 1: that the neighbor kid that uh moss my lawn and

2238
01:59:56,320 --> 01:59:58,360
Speaker 1: all my cousins and ship are gonna come over here

2239
01:59:58,440 --> 02:00:01,480
Speaker 1: and hunt like the old days. I'm letting this go

2240
02:00:01,720 --> 02:00:04,480
Speaker 1: on a profit deal, and we're gonna make some money

2241
02:00:04,480 --> 02:00:06,920
Speaker 1: on these deal and it's just gonna be the same

2242
02:00:07,000 --> 02:00:08,600
Speaker 1: thing all over again. Man, So he shouldn't have written

2243
02:00:08,600 --> 02:00:12,680
Speaker 1: that damn article. The other thing I'd say too, that

2244
02:00:12,960 --> 02:00:17,040
Speaker 1: that might prevent what you're describing is that in our

2245
02:00:17,120 --> 02:00:21,320
Speaker 1: country we're really buttoned down, you know, our our way

2246
02:00:21,360 --> 02:00:24,280
Speaker 1: of doing things compared to the way Sweden does it.

2247
02:00:24,320 --> 02:00:26,800
Speaker 1: We're Sweden let people just walk over and sell something

2248
02:00:26,840 --> 02:00:29,920
Speaker 1: and let it go, and our country, chances are we'd

2249
02:00:29,960 --> 02:00:32,920
Speaker 1: probably say before we commercialize this, we gotta get an

2250
02:00:32,960 --> 02:00:35,080
Speaker 1: inspection system, we gotta get this, we gotta do that,

2251
02:00:35,520 --> 02:00:37,800
Speaker 1: and we can't just let people start selling walking up

2252
02:00:37,880 --> 02:00:40,680
Speaker 1: the kasbar up here and selling them vaness and burger,

2253
02:00:41,520 --> 02:00:43,480
Speaker 1: that kind of things. So we'd there'd probably be so

2254
02:00:43,560 --> 02:00:46,680
Speaker 1: many different things because like in Sweden, in Stockholm, from

2255
02:00:46,720 --> 02:00:49,600
Speaker 1: what I understand is they don't have some big inspection

2256
02:00:49,680 --> 02:00:54,280
Speaker 1: system coming in there and checking that guys um saying well,

2257
02:00:54,360 --> 02:00:57,960
Speaker 1: it's you know, a pound or whatever it might be

2258
02:00:58,120 --> 02:01:01,160
Speaker 1: in in Sweden compared to ground beef, which is you know,

2259
02:01:01,280 --> 02:01:04,120
Speaker 1: fifth of that or half of that. I don't think

2260
02:01:04,160 --> 02:01:06,720
Speaker 1: our country would um go along with that. I think

2261
02:01:06,760 --> 02:01:10,920
Speaker 1: they want that's our country likes to have everything so safe,

2262
02:01:11,000 --> 02:01:13,360
Speaker 1: everything is so perfect, to the point where it drives

2263
02:01:13,400 --> 02:01:16,960
Speaker 1: me efficient way anyway. Yeah, so I I just don't

2264
02:01:17,000 --> 02:01:19,400
Speaker 1: think it. I think we're a long ways from having

2265
02:01:19,440 --> 02:01:21,640
Speaker 1: that happened. But I really agree with you that. Um.

2266
02:01:22,400 --> 02:01:24,960
Speaker 1: I guess my worry as I look at deer these days,

2267
02:01:25,040 --> 02:01:27,839
Speaker 1: I think, well, in my lifetime, deer went from virtually

2268
02:01:28,520 --> 02:01:31,160
Speaker 1: low numbers. You know, when I started hunting back in

2269
02:01:31,200 --> 02:01:33,600
Speaker 1: the early seventies, the early weren't many deer in Wisconsin.

2270
02:01:33,720 --> 02:01:35,920
Speaker 1: That point, we need to add some many severe hunt

2271
02:01:36,040 --> 02:01:39,320
Speaker 1: severe winter is really tough hunting statewide. We had seventy

2272
02:01:39,360 --> 02:01:42,200
Speaker 1: one killed in nineteen seventy one. Well, we killed more

2273
02:01:42,240 --> 02:01:44,200
Speaker 1: of that with the bow and air on nowadays, and

2274
02:01:44,600 --> 02:01:47,000
Speaker 1: now we're at this time of super abundance and we

2275
02:01:47,120 --> 02:01:50,600
Speaker 1: have CWD croc waste disease moving through you know, this

2276
02:01:50,760 --> 02:01:53,840
Speaker 1: area we're sitting right now, I really worry about We're

2277
02:01:53,880 --> 02:01:55,960
Speaker 1: gonna be with the white tail deer in in in

2278
02:01:56,000 --> 02:02:00,840
Speaker 1: a couple more decades, you know. Uh. The great conservationist

2279
02:02:00,840 --> 02:02:04,480
Speaker 1: and writer Jim Pozwits says that, uh, you know, we

2280
02:02:04,600 --> 02:02:06,560
Speaker 1: used to have a lot of we used to have

2281
02:02:06,600 --> 02:02:08,920
Speaker 1: a lot of crimes that we would committ against wildlife

2282
02:02:08,960 --> 02:02:13,560
Speaker 1: based on its scarcity. Right. He says, Now we're entering

2283
02:02:13,640 --> 02:02:16,440
Speaker 1: into a new thing where we um we have crimes

2284
02:02:16,480 --> 02:02:20,960
Speaker 1: of abundance, meaning that that the greed comes back in,

2285
02:02:21,840 --> 02:02:28,080
Speaker 1: you know, the greed, the commodification, the restricting of access.

2286
02:02:28,600 --> 02:02:30,200
Speaker 1: You know. He says, these are all things that we're

2287
02:02:30,240 --> 02:02:34,400
Speaker 1: just learning, like as a culture, we're learning how to

2288
02:02:34,520 --> 02:02:37,640
Speaker 1: deal with how good we have it. And sometimes the

2289
02:02:37,760 --> 02:02:41,120
Speaker 1: response is, you know, to just put your arms around it,

2290
02:02:41,320 --> 02:02:46,920
Speaker 1: like mind, mind, mind. So yeah, that was got any

2291
02:02:46,960 --> 02:02:51,640
Speaker 1: anything else? No? That was good. I like that. That

2292
02:02:51,720 --> 02:02:54,840
Speaker 1: was a good conversation. Are you glad you brought that up? No? No,

2293
02:02:55,480 --> 02:03:00,160
Speaker 1: the whole the two hours we just had that, Doug. Um,

2294
02:03:03,160 --> 02:03:05,960
Speaker 1: I've got to sit and listen to you guys talk before.

2295
02:03:06,040 --> 02:03:08,160
Speaker 1: In fact, the first time that you and I met

2296
02:03:08,440 --> 02:03:11,360
Speaker 1: to me and dark and yeah, and the first time

2297
02:03:11,400 --> 02:03:13,560
Speaker 1: that Steve and I met. The first person I called

2298
02:03:13,600 --> 02:03:16,160
Speaker 1: when when Steve came out here was was Pat to say, Hey,

2299
02:03:16,720 --> 02:03:20,760
Speaker 1: had this guy coming writer? I think you guys would

2300
02:03:21,360 --> 02:03:25,480
Speaker 1: uh get along and and uh have some interesting conversations.

2301
02:03:25,520 --> 02:03:28,320
Speaker 1: And as I recall that that cold ass hunt that

2302
02:03:28,400 --> 02:03:31,240
Speaker 1: we had that that first time we did. And so

2303
02:03:31,400 --> 02:03:34,520
Speaker 1: it's uh gratifying for me to sit here and uh,

2304
02:03:36,000 --> 02:03:40,400
Speaker 1: I have the folks who follow the podcast and and

2305
02:03:40,600 --> 02:03:43,160
Speaker 1: and you're show and everything, UM get to be in

2306
02:03:43,240 --> 02:03:45,320
Speaker 1: on one of those conversations because I've been involved with

2307
02:03:45,560 --> 02:03:48,840
Speaker 1: several of these with you guys Spain way back. Yeah,

2308
02:03:48,960 --> 02:03:54,600
Speaker 1: well going back to two or something like that. Pat,

2309
02:03:54,680 --> 02:03:57,440
Speaker 1: you know you'd like to add, Yeah, Um, I think

2310
02:03:57,440 --> 02:04:00,360
Speaker 1: I told you in an email every day I listen

2311
02:04:00,360 --> 02:04:03,040
Speaker 1: to your podcast. I think I've listen to every podcast

2312
02:04:03,120 --> 02:04:07,200
Speaker 1: you guys have produced because I like them, and so

2313
02:04:07,280 --> 02:04:09,240
Speaker 1: I knew not to get caught caught off guard by

2314
02:04:09,400 --> 02:04:11,959
Speaker 1: um coming in with a half asked you know, concluding

2315
02:04:12,040 --> 02:04:15,120
Speaker 1: thought you came you came pre concluding, yeah, because you

2316
02:04:15,480 --> 02:04:17,880
Speaker 1: you always jump on guys who just say all, thanks

2317
02:04:17,960 --> 02:04:20,760
Speaker 1: Jeve for having me on and the thing I was

2318
02:04:21,040 --> 02:04:24,840
Speaker 1: But the thing I um hearkened back to with the

2319
02:04:24,920 --> 02:04:27,720
Speaker 1: time I've known you, is that I really like the

2320
02:04:27,800 --> 02:04:31,040
Speaker 1: fact how you are reaching out to the non hunters

2321
02:04:31,040 --> 02:04:33,800
Speaker 1: of this country. The way you operate just started straightforward.

2322
02:04:34,440 --> 02:04:37,520
Speaker 1: You don't apologize for being a hunter. You invite people

2323
02:04:37,600 --> 02:04:40,920
Speaker 1: into your world and show them what's why this matters

2324
02:04:41,040 --> 02:04:43,000
Speaker 1: and how this matters. You know that the idea that

2325
02:04:43,880 --> 02:04:45,680
Speaker 1: the example you gave me in an article I wrote

2326
02:04:45,680 --> 02:04:47,720
Speaker 1: about seven years ago, was that when you invite people

2327
02:04:47,720 --> 02:04:50,320
Speaker 1: into your home, most people come in and they don't

2328
02:04:50,360 --> 02:04:51,760
Speaker 1: know what to make of antlers, like what we have

2329
02:04:51,840 --> 02:04:54,960
Speaker 1: in this room right now, And I'm as beautiful as

2330
02:04:55,000 --> 02:04:57,560
Speaker 1: they are. Yeah, Like you and I can look around

2331
02:04:57,600 --> 02:05:01,040
Speaker 1: this room and we see the differences the nuances of

2332
02:05:01,080 --> 02:05:03,800
Speaker 1: these different antlers. Oh, my wife, even though she's in

2333
02:05:03,880 --> 02:05:05,800
Speaker 1: the hall, she doesn't really get into that stuff. But

2334
02:05:06,440 --> 02:05:09,640
Speaker 1: when they can start realizing that each one those deer

2335
02:05:09,680 --> 02:05:11,440
Speaker 1: up here has a story, Each one those deer up

2336
02:05:11,480 --> 02:05:14,480
Speaker 1: there has provided a meat that has been consumed the

2337
02:05:14,600 --> 02:05:18,440
Speaker 1: people in this room and outside in their families. They

2338
02:05:18,760 --> 02:05:21,920
Speaker 1: understand that that's hunting is not so bad then, because

2339
02:05:21,960 --> 02:05:26,760
Speaker 1: you come across the likable, normal, personal thinking, intelligent, caring person.

2340
02:05:27,400 --> 02:05:29,800
Speaker 1: And the story I'll always go back to that always

2341
02:05:29,960 --> 02:05:33,680
Speaker 1: was formative for my understanding of non hunters. Is back

2342
02:05:33,760 --> 02:05:36,560
Speaker 1: in the seventies when when it was still popular to hitchhike.

2343
02:05:36,840 --> 02:05:39,960
Speaker 1: Everyone hitchhike. When I was first driving mere picking up

2344
02:05:40,000 --> 02:05:43,600
Speaker 1: a college girl, I was May sixteen years old and

2345
02:05:43,800 --> 02:05:46,400
Speaker 1: I was driving driving a little beater when he picked

2346
02:05:46,440 --> 02:05:49,000
Speaker 1: her out, were you kind of thinking like, who knows? No,

2347
02:05:49,320 --> 02:05:51,400
Speaker 1: she was she's a college girl, so she's older than me.

2348
02:05:51,440 --> 02:05:53,040
Speaker 1: I knew, I didn't never didn't have a chance to wife.

2349
02:05:53,080 --> 02:05:56,240
Speaker 1: And I I was shy as hell as you know teenagers,

2350
02:05:56,240 --> 02:05:58,800
Speaker 1: so I never as I scared the girl's basically, but

2351
02:05:59,520 --> 02:06:03,240
Speaker 1: I remember, um I picked she was hit shaking down

2352
02:06:03,440 --> 02:06:06,000
Speaker 1: on the u W mass and campus. I picked her up,

2353
02:06:06,720 --> 02:06:09,520
Speaker 1: and I just come back from hunting out east of town,

2354
02:06:09,840 --> 02:06:13,040
Speaker 1: and I had two dead rabbits on the console between

2355
02:06:13,240 --> 02:06:16,040
Speaker 1: our bucket seats, and this old g t O. Yeah,

2356
02:06:16,600 --> 02:06:19,960
Speaker 1: and she looks these these two dead rabbits laying there,

2357
02:06:20,680 --> 02:06:24,920
Speaker 1: you know, between our seats, and she says, did you

2358
02:06:24,960 --> 02:06:26,960
Speaker 1: just shoot those? You know, because she she was obviously

2359
02:06:27,000 --> 02:06:28,800
Speaker 1: you know, she knew someone hunting us. And so yeah,

2360
02:06:28,800 --> 02:06:31,040
Speaker 1: I was out hunting up by some prairie and got

2361
02:06:31,320 --> 02:06:33,520
Speaker 1: these rabbits, and she's the first question she asked them

2362
02:06:33,560 --> 02:06:37,720
Speaker 1: was the second question was going to eat them? I said, oh, yeah,

2363
02:06:37,920 --> 02:06:41,800
Speaker 1: I love eating rabbits. She says, okay then, and that's

2364
02:06:41,880 --> 02:06:44,080
Speaker 1: really I think where most people are. If you make

2365
02:06:44,280 --> 02:06:46,720
Speaker 1: us to that animal you kill, they're they're all for it.

2366
02:06:47,400 --> 02:06:51,160
Speaker 1: And I always stuck with me that that um that

2367
02:06:51,280 --> 02:06:54,560
Speaker 1: woman's question, and then knowing I was being judged by

2368
02:06:54,600 --> 02:06:57,120
Speaker 1: how I answered it, luckily I answered it, you know,

2369
02:06:57,200 --> 02:07:00,320
Speaker 1: the way she was hoping i'd answered. I. I didn't

2370
02:07:00,360 --> 02:07:03,840
Speaker 1: kill his rabbits for joy, just for the excitement whatever

2371
02:07:04,000 --> 02:07:11,360
Speaker 1: might notate them our body. The historian Randall Williams um,

2372
02:07:11,440 --> 02:07:13,640
Speaker 1: I've had this conversation with a number of times where

2373
02:07:13,720 --> 02:07:17,160
Speaker 1: he says that, uh. He talks about how hunters have

2374
02:07:17,440 --> 02:07:24,920
Speaker 1: a persecution complex. He says, there are a small minority

2375
02:07:25,440 --> 02:07:32,040
Speaker 1: of Americans hunt, a smaller minority of Americans are vehemently

2376
02:07:32,360 --> 02:07:36,800
Speaker 1: opposed the hunting. The vast majority of Americans are just

2377
02:07:37,520 --> 02:07:42,640
Speaker 1: just in the middle. Yeah, they're not particularly bothered by it,

2378
02:07:43,000 --> 02:07:47,400
Speaker 1: they don't engage in it. That the first time in

2379
02:07:47,480 --> 02:07:49,880
Speaker 1: your head, but in the in your average hunter's head,

2380
02:07:49,920 --> 02:07:56,720
Speaker 1: it's like, yeah, yeah, and that's I'm the first time

2381
02:07:56,720 --> 02:07:58,200
Speaker 1: I've heard in the radio, I think was on Geane

2382
02:07:58,240 --> 02:08:01,440
Speaker 1: Farroca's show on and p Are Maybe is that you

2383
02:08:01,480 --> 02:08:04,200
Speaker 1: remember that? And I didn't know who you were, but

2384
02:08:04,320 --> 02:08:07,240
Speaker 1: my wife was listening one day says, as guy's gonna

2385
02:08:07,240 --> 02:08:10,520
Speaker 1: be talking at on hunting at five o'clock. And my expectation,

2386
02:08:10,840 --> 02:08:14,160
Speaker 1: honestly was that, you know, I've been around talking about

2387
02:08:14,240 --> 02:08:16,880
Speaker 1: hunting for as I putting my job for at that point,

2388
02:08:18,160 --> 02:08:21,280
Speaker 1: almost thirty years already, and I thought, oh god, some

2389
02:08:21,560 --> 02:08:24,320
Speaker 1: some guys that get on national public radio and talked about, well,

2390
02:08:24,320 --> 02:08:27,000
Speaker 1: if you don't hunt the deer they'll get they'll start starving,

2391
02:08:27,040 --> 02:08:31,880
Speaker 1: and they'll get diseases, balat population and all those kind

2392
02:08:31,880 --> 02:08:33,960
Speaker 1: of trite things that people have been saying for years.

2393
02:08:34,000 --> 02:08:37,160
Speaker 1: And I always would always dry me about that was that,

2394
02:08:37,920 --> 02:08:40,560
Speaker 1: But that's not why you hunt. You don't see yourself

2395
02:08:40,600 --> 02:08:42,800
Speaker 1: as a pest control officer. You don't see yourself as

2396
02:08:43,600 --> 02:08:45,960
Speaker 1: some guy who's doing the world of service by being

2397
02:08:46,000 --> 02:08:48,160
Speaker 1: out there. You hunt because it's fun and you're getting

2398
02:08:48,200 --> 02:08:50,800
Speaker 1: something out of it that's worthwhile to you personally. And

2399
02:08:50,920 --> 02:08:53,600
Speaker 1: I and I never feel like I have to explain

2400
02:08:53,680 --> 02:08:56,200
Speaker 1: to people why I hunt, because I think well ship

2401
02:08:56,320 --> 02:08:58,560
Speaker 1: trying to explain to people why I love my wife.

2402
02:08:59,440 --> 02:09:01,440
Speaker 1: That's hard, you know. And you soon started taking all

2403
02:09:01,440 --> 02:09:03,720
Speaker 1: the different things that you love about your wife before

2404
02:09:03,800 --> 02:09:06,600
Speaker 1: long song. It's almost trivial. Guys that just used the

2405
02:09:06,800 --> 02:09:09,960
Speaker 1: like the controlling over a bundt like I need to

2406
02:09:10,000 --> 02:09:12,360
Speaker 1: do it because they're over populated. I'm like if you

2407
02:09:12,440 --> 02:09:14,680
Speaker 1: went out to the farmer's place that you hunted on

2408
02:09:15,800 --> 02:09:18,040
Speaker 1: and said, hey, man, me and my buddies, we're here

2409
02:09:18,120 --> 02:09:21,480
Speaker 1: to help you out, Like I'm real concerned about your

2410
02:09:21,520 --> 02:09:25,520
Speaker 1: agricultural practice. Now, I understand you've got any number of

2411
02:09:25,600 --> 02:09:29,640
Speaker 1: problems out here. I'm here to help you most farmers.

2412
02:09:29,680 --> 02:09:32,440
Speaker 1: And I could be like, son, the thing I need

2413
02:09:32,560 --> 02:09:36,600
Speaker 1: most of you is to go out and hunt them bucks. No,

2414
02:09:36,840 --> 02:09:40,800
Speaker 1: they're gonna be like, grab a shovel. I got. I

2415
02:09:40,880 --> 02:09:43,440
Speaker 1: got just the thing for you, boys, if you're here

2416
02:09:43,480 --> 02:09:46,560
Speaker 1: to help me out. This was this one of those

2417
02:09:46,760 --> 02:09:48,640
Speaker 1: fun things of life that happened once a while, you know,

2418
02:09:49,280 --> 02:09:50,920
Speaker 1: so I listened to radio and and then I get

2419
02:09:51,720 --> 02:09:54,440
Speaker 1: your Your show is done, your interviews done, And I

2420
02:09:54,520 --> 02:09:57,240
Speaker 1: said to my wife, guy's pretty smart. I like that.

2421
02:09:57,800 --> 02:10:00,680
Speaker 1: And then I promptly forgot your name, and I you know,

2422
02:10:00,680 --> 02:10:02,920
Speaker 1: and then then about it couldn't have even been a

2423
02:10:03,000 --> 02:10:05,440
Speaker 1: couple months later, Doug lets me know that you're coming

2424
02:10:05,480 --> 02:10:09,360
Speaker 1: out here, and I I finally started to connect that's

2425
02:10:09,400 --> 02:10:11,320
Speaker 1: the guy I heard on the public radio show that

2426
02:10:11,400 --> 02:10:14,000
Speaker 1: one day. And then I go and I read your books,

2427
02:10:14,680 --> 02:10:16,400
Speaker 1: and I said to my wife, you gotta read this

2428
02:10:16,480 --> 02:10:19,840
Speaker 1: guy's books. So this you'll like this. And my wife, Penny,

2429
02:10:20,000 --> 02:10:24,200
Speaker 1: she's from New Jersey, she'd never she had never heard

2430
02:10:24,280 --> 02:10:27,080
Speaker 1: family Jewish people had never met a hunter in their

2431
02:10:27,160 --> 02:10:30,840
Speaker 1: life to like him into their life. And to your

2432
02:10:31,360 --> 02:10:35,160
Speaker 1: observation about people's attitudes, they didn't have an attitude toward

2433
02:10:35,240 --> 02:10:37,480
Speaker 1: hunters because they didn't they didn't know any hunters. There

2434
02:10:37,600 --> 02:10:39,680
Speaker 1: was a foreign concept of them. Why would they why

2435
02:10:39,680 --> 02:10:42,040
Speaker 1: would you even think about hunters and hunting? And so

2436
02:10:42,400 --> 02:10:44,840
Speaker 1: when they saw this guy coming into the into their world,

2437
02:10:45,360 --> 02:10:47,280
Speaker 1: and they see pictures of their pregnant daughter out in

2438
02:10:47,280 --> 02:10:50,000
Speaker 1: the garage, helped me cut up a deer. I think

2439
02:10:50,000 --> 02:10:53,360
Speaker 1: they thought that was kind of cool. Yeah, so I

2440
02:10:53,840 --> 02:10:56,120
Speaker 1: boring happens every day and then something some guy comes

2441
02:10:56,160 --> 02:10:58,480
Speaker 1: and cuts the deer up. Yeah, and and and and

2442
02:10:58,600 --> 02:11:00,760
Speaker 1: then the and the fun thing too is I think

2443
02:11:00,800 --> 02:11:04,520
Speaker 1: they could relate to it because um Penny's mother good

2444
02:11:04,600 --> 02:11:07,320
Speaker 1: Jewish name like Goldie. She was still in those days

2445
02:11:07,400 --> 02:11:10,320
Speaker 1: going in New York City, going to fish markets, bringing

2446
02:11:10,360 --> 02:11:12,960
Speaker 1: home a whole fish, like bigger than your blue gills

2447
02:11:13,000 --> 02:11:17,000
Speaker 1: out here today, gout gutting them and cleaning them and

2448
02:11:17,560 --> 02:11:19,320
Speaker 1: doing all the things that make them ready because they

2449
02:11:19,400 --> 02:11:22,640
Speaker 1: understood that, you know, this isn't all. Not all food

2450
02:11:23,080 --> 02:11:26,240
Speaker 1: in New York comes in in rappers. You know, you

2451
02:11:26,320 --> 02:11:29,520
Speaker 1: got to yourself. So I thought that was for me

2452
02:11:30,120 --> 02:11:32,960
Speaker 1: another eye opening experience where I got to meet people

2453
02:11:33,000 --> 02:11:36,960
Speaker 1: who didn't hunt, and they didn't If you go after

2454
02:11:37,040 --> 02:11:39,560
Speaker 1: those people and start acting against us, against them, well

2455
02:11:39,600 --> 02:11:42,440
Speaker 1: they're definitely turned off down, you know, I think, I think,

2456
02:11:42,520 --> 02:11:44,760
Speaker 1: what the hell's there at? Like I didn't realize that

2457
02:11:44,920 --> 02:11:47,840
Speaker 1: we were in a fight, but now they were making

2458
02:11:47,880 --> 02:11:52,240
Speaker 1: me aware that we are exactly But and you can't

2459
02:11:52,280 --> 02:11:54,720
Speaker 1: blame them if somebody comes after them, it makes them

2460
02:11:54,720 --> 02:11:59,000
Speaker 1: feel it inadequate for not caring about their particular activity

2461
02:11:59,040 --> 02:12:04,440
Speaker 1: and ever anything, what what kind of bullshit's that? That's

2462
02:12:04,440 --> 02:12:07,240
Speaker 1: a good concluder. Thank you, Um, thank you very much. Now.

2463
02:12:08,360 --> 02:12:11,960
Speaker 1: I often in my old age, I I tell people like, uh,

2464
02:12:12,440 --> 02:12:14,640
Speaker 1: if you like, like generally, if you'd like to read

2465
02:12:14,760 --> 02:12:18,440
Speaker 1: someone's work, you know you don't want to meet him

2466
02:12:18,640 --> 02:12:20,600
Speaker 1: because they're never gonna like you don't live up right.

2467
02:12:20,640 --> 02:12:24,400
Speaker 1: No one lives up to them selves on the page.

2468
02:12:24,440 --> 02:12:27,280
Speaker 1: And I've been fortunate to read to meet a lot

2469
02:12:27,360 --> 02:12:29,600
Speaker 1: of writers that I really admired and uh, and usually

2470
02:12:29,640 --> 02:12:33,680
Speaker 1: walk away from it wishing it hadn't happened. But I

2471
02:12:33,800 --> 02:12:35,880
Speaker 1: like knowing you and having known you as long as

2472
02:12:35,920 --> 02:12:40,919
Speaker 1: I did, because uh, it's fun to have the experience,

2473
02:12:40,960 --> 02:12:44,480
Speaker 1: which happens to me often to be did an article

2474
02:12:44,640 --> 02:12:50,600
Speaker 1: catch my eye? Okay? And um, and I'll be reading it,

2475
02:12:50,640 --> 02:12:52,600
Speaker 1: I'm like, oh, that's interesting. And I'll be reading it

2476
02:12:53,240 --> 02:12:55,640
Speaker 1: and I'm like, oh that's good, right, and I'd be

2477
02:12:55,640 --> 02:13:01,560
Speaker 1: like Funk's pet I love that love. Yeah, the deer

2478
02:13:01,640 --> 02:13:05,800
Speaker 1: selling thing. I didn't put it together right away because

2479
02:13:06,000 --> 02:13:09,720
Speaker 1: like you know, like most yeah, you just don't. Writers

2480
02:13:09,720 --> 02:13:11,400
Speaker 1: get pissed that people don't look at who wrote something.

2481
02:13:11,440 --> 02:13:13,040
Speaker 1: But like when you buy a movie, do you go like, oh,

2482
02:13:13,120 --> 02:13:15,160
Speaker 1: let's produced, what studio prot this movie out? It's like

2483
02:13:15,200 --> 02:13:17,440
Speaker 1: it's like, you know, most people like don't engage things

2484
02:13:17,480 --> 02:13:20,000
Speaker 1: that way. Novels are different, but like just reading when

2485
02:13:20,000 --> 02:13:22,280
Speaker 1: you're reading like a bunch of magazine articles in the magazine,

2486
02:13:22,680 --> 02:13:27,480
Speaker 1: so how oftentimes back check like I'll be impressed substance

2487
02:13:27,760 --> 02:13:31,840
Speaker 1: and execution, and they're like, who wrote this? Yeah, in

2488
02:13:31,960 --> 02:13:34,400
Speaker 1: the same way, I don't. I don't think a personally

2489
02:13:34,440 --> 02:13:38,280
Speaker 1: when something when someone like last week I was I do.

2490
02:13:38,600 --> 02:13:40,760
Speaker 1: I do some running articles too now for the Green

2491
02:13:40,840 --> 02:13:46,240
Speaker 1: Bay newspaper and like running around running down the road. Yeah,

2492
02:13:46,320 --> 02:13:49,440
Speaker 1: I don't know why, but late in life I've just

2493
02:13:49,640 --> 02:13:52,920
Speaker 1: discovered running. And I wrote this article last week about

2494
02:13:53,160 --> 02:13:56,480
Speaker 1: basically the importance of having a strong core, which basically

2495
02:13:56,560 --> 02:13:59,160
Speaker 1: is everything from your crotch up to your neck. You know,

2496
02:13:59,160 --> 02:14:00,920
Speaker 1: if you don't have a good wrong core gets strong.

2497
02:14:01,280 --> 02:14:03,240
Speaker 1: But all those kind of things you can't. You can't

2498
02:14:03,240 --> 02:14:05,000
Speaker 1: be much for a runner. You got get in shape first,

2499
02:14:05,040 --> 02:14:07,800
Speaker 1: be freaking become a decent runner. Well, I wrote this article,

2500
02:14:07,880 --> 02:14:10,400
Speaker 1: I thought it was pretty good, and I paying attention.

2501
02:14:10,880 --> 02:14:16,760
Speaker 1: Well then I but then I what was Doug suffered

2502
02:14:16,800 --> 02:14:21,160
Speaker 1: a sprinting injury yesterday ahead it was fun about those

2503
02:14:21,280 --> 02:14:24,680
Speaker 1: that I about A week goes by and I'm talking

2504
02:14:24,760 --> 02:14:27,040
Speaker 1: to a guy who's uh, I was actually getting my

2505
02:14:27,280 --> 02:14:31,880
Speaker 1: my my um my running stride analyzed by real role

2506
02:14:32,000 --> 02:14:35,320
Speaker 1: um analysis done, not because I was having injury problems about.

2507
02:14:35,560 --> 02:14:37,360
Speaker 1: I mean, I'm gonna and the stuff once for all

2508
02:14:37,400 --> 02:14:39,400
Speaker 1: and stopped being injured. I'm going to figure out what

2509
02:14:39,480 --> 02:14:42,080
Speaker 1: what I'm doing wrong and whatever. And this guy's told

2510
02:14:42,080 --> 02:14:44,120
Speaker 1: me it was great artically read their day. He really

2511
02:14:44,200 --> 02:14:47,600
Speaker 1: liked it important to the core. I said, why I

2512
02:14:47,600 --> 02:14:50,360
Speaker 1: wrote that, God, you're right that this is you you know,

2513
02:14:50,960 --> 02:14:54,160
Speaker 1: excuse my names, and puts the five pararticular, and yeah,

2514
02:14:54,200 --> 02:14:57,320
Speaker 1: it feels great, And I'd be lying, you know, imagine

2515
02:14:57,480 --> 02:14:59,880
Speaker 1: he said, like, you know, there's just so much misinformation

2516
02:15:00,000 --> 02:15:02,360
Speaker 1: out there, pat just a matter of fact, just here

2517
02:15:02,400 --> 02:15:07,560
Speaker 1: day I was reading sometim I've had that happen. So yeah,

2518
02:15:07,640 --> 02:15:12,200
Speaker 1: who late in life jogging jackets exactly goes killing all

2519
02:15:12,360 --> 02:15:14,960
Speaker 1: kinds of innocent deer, which I happen to know. And

2520
02:15:15,320 --> 02:15:19,280
Speaker 1: he's saying, yeah, yeah, so it's good. Yeah, that, more

2521
02:15:19,320 --> 02:15:22,160
Speaker 1: than any other reason is the reason why you should

2522
02:15:22,160 --> 02:15:26,040
Speaker 1: try to do good work. Yeah, m ship, that's that's

2523
02:15:26,080 --> 02:15:28,040
Speaker 1: one thing I always tell you know. I get get

2524
02:15:28,120 --> 02:15:30,040
Speaker 1: invited to speak to college classes once in a while,

2525
02:15:30,120 --> 02:15:33,480
Speaker 1: and my my um my daughters used to involunteer me

2526
02:15:33,520 --> 02:15:35,720
Speaker 1: for various class projects to come and talk to people.

2527
02:15:36,120 --> 02:15:38,800
Speaker 1: And the point I always made about writing, because it's

2528
02:15:38,800 --> 02:15:42,520
Speaker 1: a very visible craft, is that you never know who's

2529
02:15:42,560 --> 02:15:45,640
Speaker 1: reading you, So make everything you write your best effort,

2530
02:15:45,720 --> 02:15:48,280
Speaker 1: don't just do a half passed effort. But I think

2531
02:15:48,320 --> 02:15:51,000
Speaker 1: that applies anyone in any any job. You never know

2532
02:15:51,040 --> 02:15:53,800
Speaker 1: who's watching. And so to me, when I when I

2533
02:15:53,960 --> 02:15:57,600
Speaker 1: when actually right, I always figure at some point someone's

2534
02:15:57,600 --> 02:16:00,360
Speaker 1: gonna pick up that newspaper, pick up that mag zene

2535
02:16:00,800 --> 02:16:02,640
Speaker 1: and read it. And and a lot of times two

2536
02:16:02,680 --> 02:16:06,080
Speaker 1: people don't. You can't expect people to read by lines.

2537
02:16:06,160 --> 02:16:08,280
Speaker 1: There's they're going to straight into the article. If you

2538
02:16:08,280 --> 02:16:10,440
Speaker 1: don't catch him the first couple of paragraphs, they're out

2539
02:16:10,560 --> 02:16:12,400
Speaker 1: and they're on. They never looked to see who wrote it.

2540
02:16:12,440 --> 02:16:15,280
Speaker 1: And let's you see people like yourself and I did

2541
02:16:15,320 --> 02:16:17,800
Speaker 1: the same thing. I'll read the article if it's really good,

2542
02:16:17,840 --> 02:16:19,480
Speaker 1: all look at the name. A lot of times you

2543
02:16:19,520 --> 02:16:21,080
Speaker 1: won't recognize but not if you see that name two

2544
02:16:21,120 --> 02:16:25,200
Speaker 1: or three times, it starts thinking in and so so

2545
02:16:25,320 --> 02:16:27,840
Speaker 1: it has to be not only good one time, but

2546
02:16:27,960 --> 02:16:31,560
Speaker 1: good every time. And then sometimes topics don't interest people,

2547
02:16:31,600 --> 02:16:34,000
Speaker 1: they won't read it, and that's fine. Uh, my wife

2548
02:16:34,040 --> 02:16:39,640
Speaker 1: doesn't read everything I write either. Really well, the worst

2549
02:16:39,680 --> 02:16:42,080
Speaker 1: mistake made my writing career is about thirty years ago.

2550
02:16:42,120 --> 02:16:44,320
Speaker 1: I asked my wife one time what you thought about

2551
02:16:44,320 --> 02:16:50,280
Speaker 1: column I wrote? And her honest response, wash, you've written better. Yeah,

2552
02:16:50,480 --> 02:16:52,560
Speaker 1: and I've never I've never asked her since then what

2553
02:16:52,680 --> 02:16:54,640
Speaker 1: you thought of anything I've written. But you know, a

2554
02:16:54,680 --> 02:16:56,320
Speaker 1: lot of times you'll tell me I like that column

2555
02:16:56,320 --> 02:16:59,520
Speaker 1: today or whatever it might be. But yeah, but like

2556
02:17:00,160 --> 02:17:04,400
Speaker 1: I um that my news newspaper column appears in our

2557
02:17:04,560 --> 02:17:07,280
Speaker 1: local newspaper now, so she sees it, but it gets

2558
02:17:07,280 --> 02:17:10,200
Speaker 1: delivered to the door. Yeah, yeah, every Saturday morning she

2559
02:17:10,280 --> 02:17:15,320
Speaker 1: sees my smiling my smiling gap today. Yeah. Alright, well, Pat,

2560
02:17:15,480 --> 02:17:17,920
Speaker 1: thanks for coming on. Thank you. We'll have to have

2561
02:17:18,040 --> 02:17:21,880
Speaker 1: you back talk more about um. You know, what do

2562
02:17:22,000 --> 02:17:24,720
Speaker 1: you do when this moon when it's mooney out? Well,

2563
02:17:25,000 --> 02:17:27,640
Speaker 1: see if your opinions have changed. Well, I wasn't gonna

2564
02:17:27,640 --> 02:17:29,200
Speaker 1: tell you, though, Steve, I really met when I said

2565
02:17:29,200 --> 02:17:34,120
Speaker 1: about the way you're handling yourself, the final final thought

2566
02:17:34,200 --> 02:17:36,480
Speaker 1: on making that is that you know your final concluding

2567
02:17:36,680 --> 02:17:41,400
Speaker 1: twenty five years ago. I've including Colm twenty five years ago,

2568
02:17:42,240 --> 02:17:44,400
Speaker 1: and it's basically the whole idea that we don't we

2569
02:17:44,480 --> 02:17:48,440
Speaker 1: do not have any hunt results. They're talking on hunting's behalf,

2570
02:17:48,920 --> 02:17:52,240
Speaker 1: who are famous for being hunters, and I think I

2571
02:17:52,280 --> 02:17:54,400
Speaker 1: look around now and I see guys like you by

2572
02:17:54,440 --> 02:17:57,760
Speaker 1: Warren Brandy Newburgh, guys who are making their mark out

2573
02:17:57,840 --> 02:18:02,360
Speaker 1: there because they have gotten to a certain stage in life,

2574
02:18:02,440 --> 02:18:06,160
Speaker 1: stage in their careers were they're recognized as smart hunters

2575
02:18:06,200 --> 02:18:09,199
Speaker 1: who are doing something for not just hunting, but overall

2576
02:18:09,280 --> 02:18:14,240
Speaker 1: conservation efforts. And you guys meet people who can communicate

2577
02:18:14,280 --> 02:18:17,279
Speaker 1: to other people outside our little circles of of hunters.

2578
02:18:17,680 --> 02:18:20,200
Speaker 1: And I look at guys like Joe Rogan and I don't.

2579
02:18:20,200 --> 02:18:22,600
Speaker 1: I don't listen to Joe's podcast as carefully as a

2580
02:18:22,680 --> 02:18:24,280
Speaker 1: listening to yours this because they're so long and I'm

2581
02:18:24,840 --> 02:18:26,920
Speaker 1: I'm always, you know, running from one topic to the next.

2582
02:18:27,040 --> 02:18:29,160
Speaker 1: I think it's because of those kind of contacts you

2583
02:18:29,360 --> 02:18:33,120
Speaker 1: established and you network with and you enjoy they're smart

2584
02:18:33,200 --> 02:18:36,920
Speaker 1: people who can You reached an audience that we as

2585
02:18:37,000 --> 02:18:39,880
Speaker 1: I can't reach, and I think we should appreciate that

2586
02:18:39,920 --> 02:18:41,960
Speaker 1: and thank you guys for doing that. And I really

2587
02:18:42,080 --> 02:18:45,280
Speaker 1: say that with deep sincerity. So thank you man. It's

2588
02:18:45,440 --> 02:18:47,680
Speaker 1: very kind of you. Oh you bet. That's the best

2589
02:18:47,720 --> 02:18:51,600
Speaker 1: including thought. Take a pointer from that, Doug extending to

2590
02:18:51,840 --> 02:18:55,040
Speaker 1: do a concluding thought. Do you like my concluding thought?

2591
02:18:56,320 --> 02:19:01,480
Speaker 1: That's why would have to seriously thank you for coming on, man,

2592
02:19:01,720 --> 02:19:03,760
Speaker 1: thank you. We're gonna have you back to talk more

2593
02:19:03,760 --> 02:19:06,039
Speaker 1: about all this stuff. It's always fun, ladies and gentlemen.

2594
02:19:07,040 --> 02:19:11,160
Speaker 1: Pat dark and find his writing. Just look him up

2595
02:19:11,800 --> 02:19:14,119
Speaker 1: on the internet, right, Oh yeah, you're just having Pat

2596
02:19:14,200 --> 02:19:15,920
Speaker 1: Dirk and outdoors and you'll find a lot of stuff.

2597
02:19:16,320 --> 02:19:18,160
Speaker 1: Or open your eye. If you live in Wisconsin and

2598
02:19:18,200 --> 02:19:20,640
Speaker 1: the newspaper comes banging up against your screen door, open

2599
02:19:20,680 --> 02:19:23,800
Speaker 1: it up and see. Yeah, support local journalism. That's that's

2600
02:19:23,879 --> 02:19:27,760
Speaker 1: my my best witch for people. And if you live

2601
02:19:27,800 --> 02:19:29,840
Speaker 1: in Michigan, go figure out what watershed you live in.

2602
02:19:30,720 --> 02:19:31,400
Speaker 1: All right, take care