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Speaker 1: If this is the me Eater podcast coming at you shirtless, severely,

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Speaker 1: bug bitten, and in my case, underwear listeningst you can't

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Speaker 1: predict anything brought to you by first Light. When I'm hunting,

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Speaker 1: I need gear that won't quit. First Light builds, no compromise,

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Speaker 1: gear that keeps me in the field longer, no shortcuts,

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Speaker 1: just gear that works. Check it out at first light

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Speaker 1: dot com. That's f I R S T L I

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Speaker 1: T E dot com for people. Oh no, the show

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Speaker 1: is starting right now with this ring. Can it start

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Speaker 1: with this ring?

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Speaker 2: Yeah?

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Speaker 1: Sounds good dyland Mark Canyon. If he doesn't pick up

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Speaker 1: where we keep it, you think, I see? Oh, Mark,

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Speaker 1: you know who I'm sitting here with. I have no

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Speaker 1: idea you're on you're on the You're not on the air,

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Speaker 1: but you know what I mean, you're being recorded. Okay,

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Speaker 1: Uh it's me Mark.

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Speaker 3: I'm here with doctor Bronson Strickland.

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Speaker 1: Hm hm, great guy. And I'm about ready to start

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Speaker 1: telling him about the last thing you told me about

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Speaker 1: deer in the moon and I and I'm gonna like

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Speaker 1: kind of make you look bad. Then I thought that

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Speaker 1: that it was a very interesting point I was telling

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Speaker 1: you about how you know you and I have argued

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Speaker 1: about whether deer are impacted by lunar phases. Yep, you're

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Speaker 1: very I mean you're you're very aware of this debate.

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Speaker 4: Very aware of it.

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Speaker 1: I'm position is, well, I'll tell you what you said

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Speaker 1: the last time we talked, Mark, and it was a

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Speaker 1: long time ago, and it's stuck in my head, it's

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Speaker 1: stuck in my craw you were you were kind of

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Speaker 1: hinting at that science can't detect the subtle difference. Is

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Speaker 1: that could the subtle, subtle things that could make a

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Speaker 1: difference between your success and your failure where you're like,

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Speaker 1: if that buck steps out of the woods a minute earlier,

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Speaker 1: that could be the difference and science can't find that. Yes,

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Speaker 1: So when I say about how you think that, you

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Speaker 1: still think that, well, that has been not my position,

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Speaker 1: but my.

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Speaker 3: No, you didn't put it to me like a question.

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Speaker 5: So I've always said that that is the question that

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Speaker 5: I feel like science has yet was like, there's all

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Speaker 5: these studies that show that cold fronts don't impact movement

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Speaker 5: in a statistically significant way, or the moon in many

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Speaker 5: different ways has not shown yet to make a statistics

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Speaker 5: that's a difference. So I've always been curious though, because

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Speaker 5: on when we see that in all the studies. On

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Speaker 5: the other hand, you have all these other hunters with

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Speaker 5: anecdotal evidence that you.

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Speaker 2: Know that says that's not the case.

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Speaker 5: And so my question has always been, maybe maybe we're

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Speaker 5: just not measuring in the same way or in quite

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Speaker 5: the right way to us these tiny.

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Speaker 3: Little possible edges that you could get.

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Speaker 5: So I'm still like very much on the fence. So

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Speaker 5: Steel like, I'm just curious. I'm Moon curious.

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Speaker 1: That's how I've always described myself.

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Speaker 3: We already talked about you being Moon curious.

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Speaker 1: I'm Mark.

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Speaker 3: I'm Mark curious.

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Speaker 1: Ye know.

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Speaker 5: And Bronson has done a really good job of a

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Speaker 5: lot of this stuff. So I'm glad you're talking to

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Speaker 5: him because he's someone who I listened to a lot

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Speaker 5: and uh, and he certainly knows better than I.

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Speaker 2: I'm simply a guy with questions.

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Speaker 1: Yeah. Remember how I said you're on the air, Mark, Yeah,

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Speaker 1: Well you know what I found all was interested ther

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Speaker 1: day after the after learning at the other day where

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Speaker 1: the FCC start like threatening people for say and stuff

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Speaker 1: they didn't like. Yeah, I was like, the FCC has

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Speaker 1: nothing to do with podcasts. But then I was like,

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Speaker 1: do they the FCC has nothing to do with podcasts?

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Speaker 1: Is that a question of statement.

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Speaker 3: No, I'm telling you it's true because you're not on

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Speaker 3: the air.

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Speaker 1: You're not on the air, you're not we're not using

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Speaker 1: the air, so we can say like things and the

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Speaker 1: FCC won't threaten us and take the show off the air.

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Speaker 1: So if they get mad about this lunar phase stuff,

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Speaker 1: there's nothing to do about it.

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Speaker 5: Saying a lot of crazy stuff about the moon over

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Speaker 5: all these years, I would hate to be brought to

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Speaker 5: court almose past.

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Speaker 1: You can do this the hardware of the easy way mark.

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Speaker 1: That's what they say. All right, man, we'll talk to

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Speaker 1: you later. Thank you. When the episode comes out, why

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Speaker 1: don't you listen and we'll try to find out if

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Speaker 1: what you're saying is a thing or not.

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Speaker 2: I'm looking forward to.

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Speaker 1: As we just said, day goodbye to him. Oh, I

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Speaker 1: don't really do that.

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Speaker 6: Never, No, not even if it's your wife.

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Speaker 1: Definitely not.

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Speaker 2: No, that is a of Steve's is it's a it's

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Speaker 2: in the name of efficiency that please, thank you, hello, goodbye.

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Speaker 2: Once you achieve a certain intimacy with Steve follow in

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Speaker 2: this category as well. That those pleasant trees are out

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Speaker 2: the window.

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Speaker 6: I think, I think that happens to me too, But

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Speaker 6: and then I watch it happen to someone else.

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Speaker 4: If you really want to.

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Speaker 1: If you really want to dig it, I'll take a

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Speaker 1: quick break to take this for you. I like there's

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Speaker 1: people I talk to. I like the main people in

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Speaker 1: my life. I like I talked to him. I like

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Speaker 1: to talk to him a lot, so that anytime we

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Speaker 1: talk it's only about what we have to talk about.

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Speaker 1: The minute I go too long and I haven't talked

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Speaker 1: to somebody, then I dread talking to him because we've

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Speaker 1: got to do all the parts of talking that I don't.

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Speaker 3: Want to do.

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Speaker 6: You know what I mean, how's the family?

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Speaker 1: So if I keep up like a cadence, like if

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Speaker 1: I call it Yanni, I don't need to get into like,

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Speaker 1: oh geez, how you been? Is the householding up? Ye know?

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Speaker 1: I mean, you know, and like wind up in something

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Speaker 1: like that. Yeah.

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Speaker 6: I come to expect no small talk.

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Speaker 1: So I just like if I call you on and

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Speaker 1: like hey blank blank, and he's like blank blank, and

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Speaker 1: then we just hang up because we like kept up

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Speaker 1: on it and we don't have to do like whatever

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Speaker 1: did happen? To your cousin you know I mean or whatever?

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Speaker 1: You know what I mean? Like, it's just better that way.

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Speaker 1: So I just like to. But I tell my wife

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Speaker 1: I love her, and I can always tell how I

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Speaker 1: stand with her because I'll do it because I'm just

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Speaker 1: trying to find out if she's mad at me about

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Speaker 1: something so big I love you and she says I

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Speaker 1: love you, then we're cool. If I go I love

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Speaker 1: you and she just hangs up the I'm like, oh

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Speaker 1: my god, now what now? Okay, you know what I mean.

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Speaker 1: So that's how I find out if I got it, like,

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Speaker 1: if I'm That's how I find out if I'm like

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Speaker 1: cool or not. When I go home.

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Speaker 3: The longer I've been gone, the less likely I am

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Speaker 3: to get the return.

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Speaker 1: You know, things get frosty at home. Join Today by

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Speaker 1: Doctor Brownson Strickland of University of Mississippi.

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Speaker 4: Mississippi State University.

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Speaker 1: Is that a big mistake?

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Speaker 4: That's a pretty yeah.

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Speaker 6: It's not on to make up for say, hot Toddy,

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Speaker 6: it's right.

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Speaker 3: Where do I see it on?

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Speaker 7: Here?

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Speaker 6: The bigger?

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Speaker 1: Doctor Brownson is the Saint John Family Professor of Wildlife

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Speaker 1: Management and the Extension Wildlife Specialist for Mississippi State University.

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Speaker 1: And what do you say when you.

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Speaker 6: Say that that that's that's another mess up. You've offended

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Speaker 6: more Mississippi State folks.

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Speaker 1: Yeah, what does it mean? Hot?

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Speaker 3: Hot like Christmas drinks?

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Speaker 6: I do think hatty toddy means anything. It's a different school.

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Speaker 4: Yeah, that's old. Miss we booze it up.

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Speaker 1: Mississippi State University. Did his did his BS degree in

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Speaker 1: forest resources in the University of Georgia. Did a master's

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Speaker 1: degree Texas A and m Kingsville PhD from Mississippi State University.

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Speaker 1: Bronson is the co director of the ms Here's where

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Speaker 1: things get interesting. He's a co director of the MSU

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Speaker 1: Deer Lab, a certified wild wildlife biologist, and professional member

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Speaker 1: of the Boone and Crockett Club. We're this is We're

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Speaker 1: here to make this is the most important podcast ever

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Speaker 1: ever done. I would say, because this is going to

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Speaker 1: be the final answer. This is gonna be we hope. Yeah.

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Speaker 1: Dudes out there that are like are they argue about

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Speaker 1: like the moon phase? And if I'm talking to Jay Scott,

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Speaker 1: We're going to go down to Mexico for Ko's Deer

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Speaker 1: And he's talking about what dates to go and he's

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Speaker 1: talking about what the moon's doing on those dates. Is

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Speaker 1: all of that true or not true? Every old man,

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Speaker 1: young man, not even old man, every hunter has an

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Speaker 1: opinion about what is the moon doing and how does

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Speaker 1: it effect dear movements.

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Speaker 6: Jay Scott is one of those guys.

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Speaker 3: I don't know where he stands now. Everybody changes.

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Speaker 1: I used to just believe it too, because I like, well,

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Speaker 1: I used to believe that squirrels, that red squirrels bit

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Speaker 1: the nuts off gray squirrels. That's what I was told.

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Speaker 2: He will definitely push us one way or another in

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Speaker 2: January according to what the Moon's going to be doing.

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Speaker 1: When you know, so, I have a lot of I

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Speaker 1: have a lot of friends that are lunar guys, moon guys,

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Speaker 1: and like, here's the deal. And when we started playing

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Speaker 1: It's out, I had a conversation with Krint about it,

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Speaker 1: and I'm like, it's not ridiculous, Okay, I mean, what's

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Speaker 1: not ridiculous about is look at all the wildlife that

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Speaker 1: that absolutely one hundred percent is driven by moonface. Okay,

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Speaker 1: Like turtle nesting, like when turtles hatch turtles, like like

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Speaker 1: shore nesting turtles that lay eggs, their eggs hatch on

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Speaker 1: a new moon. Some species hatch where it's real dark. Okay,

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Speaker 1: what are the kind of examples we have? I mean

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Speaker 1: there's tons of things, man, fish, tides and fish. Yeah,

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Speaker 1: think about it's huge. Well, here here's another one for you.

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Speaker 1: I remember they You ever hear the writer Barbara King Salver.

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Speaker 1: She had a book called High Tide and Tucson, and

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Speaker 1: it was a book of like science writing. Was it

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Speaker 1: King Salver? Was it? They took these mollufs and brought

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Speaker 1: them to Tucson to a university what what universities in Tucson?

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Speaker 1: Camera They took these clams whatever the hell it is asu.

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Speaker 1: I believe it was clams. I'm sure it was clams.

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Speaker 1: They had these clams in an aquarium and Tucson, and

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Speaker 1: they didn't need the ocean to tell them what the

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Speaker 1: tide was doing. Their whole groove became tied to their

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Speaker 1: whole feeding groove became tied to the moon. And it's

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Speaker 1: not even enough, like it's an imperceptible Like the effect

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Speaker 1: on an aquarium is like imperceptible, right, But those suckers

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Speaker 1: tuned in and stayed on a lunar. They stayed on

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Speaker 1: a lunar cycle without even being where there's a giant

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Speaker 1: tide swing. Right, they just knew. So it stands the

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Speaker 1: reason with all these different creatures migratory birds, right, it

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Speaker 1: stands the reason, Like, yeah, the moon impacts stuff. So

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Speaker 1: for someone to say that the moon impacts how bucks move,

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Speaker 1: it's not crazy.

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Speaker 4: It's not like dumb, it's not so Yeah, there is

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Speaker 4: a lot of evidence for some species. And I think

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Speaker 4: the species you mentioned that does make sense. The gravitational

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Speaker 4: pull affecting the tide or moonlight affecting visibility, all that stuff,

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Speaker 4: to me makes perfect sense. And I think there's a

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Speaker 4: lot of examples in the literature for that and it

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Speaker 4: being useful. But what I come back to is, but

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Speaker 4: what made it that way? How did the story begin

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Speaker 4: for white tail deer? Where has there ever been evidence

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Speaker 4: that its influencing whitetail deer except for Paul Paul the

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Speaker 4: stories that are passed down from grandfather today, you know,

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Speaker 4: and it just becomes part of the story, and it

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Speaker 4: makes it fun and it makes it interesting. And humans

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Speaker 4: are always looking for patterns, and we're really good at

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Speaker 4: looking for patterns even when they don't exist, and so

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Speaker 4: it adds I think this element to making it more

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Speaker 4: interesting when the bottom line is, in my opinion, I

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Speaker 4: think the evidence is very strong they're not influenced by

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Speaker 4: the moon whatsoever. And then you think about the natural

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Speaker 4: history of deer and you start asking your question, why

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Speaker 4: would they be.

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Speaker 3: Uh, something to do with visibility.

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Speaker 1: Well, like in reading like historic texts, you'll often find

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Speaker 1: people pre flashlight and stuff, people traveling by horse. You

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Speaker 1: read historic text you'll often find people planning trips to

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Speaker 1: have their trip coincide with a full moon for better

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Speaker 1: nighttime travel.

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Speaker 3: So I used to think I'm the deer thing.

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Speaker 1: I'm like, maybe just historically, when it's a full moon

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Speaker 1: and you're out at night, because there's more light, you

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Speaker 1: become aware of deer around you, so you can see

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Speaker 1: you can see them, and so you think in your head,

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Speaker 1: maybe you wind up thinking. Maybe people wind up thinking

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Speaker 1: when there's a full moon, the deer out.

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Speaker 4: They're always out just because you seeing them.

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Speaker 1: And so you're like, I'm out because I'm out traveling

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Speaker 1: at night because it's a full moon, I can see

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Speaker 1: I see deer because it's a full moon, and therefore

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Speaker 1: I don't know. People land on on that idea that

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Speaker 1: that's a wild I'm like, I'm grasping at straws big,

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Speaker 1: where did that come from? But but I like, like

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Speaker 1: probably the other guys in the room you can like,

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Speaker 1: I'd love to hear Yanni and Spencer like, how if

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Speaker 1: you can remember where it come from, where your idea

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Speaker 1: about this came from? And then and then and then

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Speaker 1: doctor Stricklan, I'd love to hear when you guys did

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Speaker 1: the survey, if you could talk about how eighty three

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Speaker 1: eighty three percent of hunter of surveyed hunters, eighty three

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Speaker 1: percent agree it affects moon, the moon affects deer movement.

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Speaker 1: What they don't agree on is why and how right right,

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Speaker 1: They don't agree on like what it does, how it

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Speaker 1: does it, but they believe it does something. But do

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Speaker 1: you remember, Yanni?

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Speaker 2: Sure, I would say for me it didn't really come

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Speaker 2: down generationally it wasn't because basically for me growing up

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Speaker 2: before I came out West and started hunting professional, really

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Speaker 2: it was maybe five to ten days of archery in Michigan,

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Speaker 2: two or three days of shotgun, and then I'd get

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Speaker 2: three days of rifle in Wisconsin. That was like my

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Speaker 2: entire big game hunting year. So we're gonna be hunting

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Speaker 2: no matter what. Those days you know.

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Speaker 1: You never got I'll take an opening day off this year.

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Speaker 1: I'm not hunting the opener because the looter phase just

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Speaker 1: no way, right.

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Speaker 2: Yeah, exactly. And my dad just never got into it

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Speaker 2: to that level either, which is where I would have

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Speaker 2: got it. So I just started learning about it once

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Speaker 2: I started reading hunting magazines.

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Speaker 1: And doing research on my own, and you would encounter it,

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Speaker 1: yeah as fat Yeah, I would say that.

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Speaker 5: Uh.

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Speaker 2: Where I felt like it actually played a part in

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Speaker 2: my hunting was that when I was an elkhunting guy

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Speaker 2: in Colorado, usually the second rifle season would coincide with

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Speaker 2: the pretty big moon. It would also coincide a lot

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Speaker 2: of times with some warmer weather, extreme amount of hunting pressure,

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Speaker 2: and it was always our hardest week of hunting. Would

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Speaker 2: still kill some olt, but man, it was always our

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Speaker 2: hardest week. So a lot a lot of factors that

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Speaker 2: play there, but it always would seem like that week

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Speaker 2: would also have a big moon, And in my mind

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Speaker 2: it was like, of course, they're just up all night

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Speaker 2: feeding and by the time we get to the meadow

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Speaker 2: half an hour before daylight, they're long gone.

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Speaker 1: They're you know in bed. That's the version I was

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Speaker 1: raised on. Yeah, I was raised on, but again I

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Speaker 1: was raised on a full moon. They feed all night,

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Speaker 1: so they don't need to feed in the daylight hours.

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Speaker 1: But it had zero It was just an observation. It

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Speaker 1: was an observation, but it did not dictate your dictate

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Speaker 1: your habits. Right. It was like you had a two

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Speaker 1: week gun season, you were gonna hunt, you know whatever.

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Speaker 1: We weren't like going out or not going out based

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Speaker 1: on it, But it was just like you'd be like, oh,

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Speaker 1: it's too bad that there's a full moon on the opener.

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Speaker 1: They'll be out.

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Speaker 6: Less because they convenient excuse, or if you're successful, you

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Speaker 6: did it in spite of a full moon, Like damn?

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Speaker 1: Was that your awareness of what the moon was doing.

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Speaker 6: I think when I was a kid, there was a

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Speaker 6: communal anti full moon take from like the deer hunters

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Speaker 6: in my area, and it was just a very rudimentary

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Speaker 6: understanding of like what moon, what moon phase would do

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Speaker 6: to deer movement. And it was like today and I

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Speaker 6: feel like in the last twenty years, there will be

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Speaker 6: very like hyper specific moments of the moon that are

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Speaker 6: good or bad for deer movement. It's like if a

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Speaker 6: new moon is rising under in the morning, Like that's

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Speaker 6: a thing people will say when I was a kid

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Speaker 6: that it was just like full moon bad, and it was.

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Speaker 6: It was not that they were up feeding all night.

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Speaker 6: It was that they were chasing tail all night. So

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Speaker 6: they were tired. They were like exhausted come first light.

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Speaker 6: And so now you're actually going to get some movements

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Speaker 6: like late morning, early afternoon, and so that is like

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Speaker 6: a stronger time to be in the woods, or it's

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Speaker 6: now as good as the morning or the evening. That's

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Speaker 6: like a take.

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Speaker 1: Can you hit me that again?

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Speaker 6: If if it's a full.

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Speaker 1: Moon, since he's been chasing does all chasing does.

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Speaker 6: All night, he can see things so well, it's like

339
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Speaker 6: it's not that no one even turned the lights off tonight,

340
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Speaker 6: you know they can. They can chase them all through

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Speaker 6: the hardwoods, all out in the cornfields. So now they're

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Speaker 6: tired come sunrise at seven thirty am, so they're just

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Speaker 6: bedded down somewhere already got it. But now they're getting

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Speaker 6: a little restless come like eleven am, and so they're

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Speaker 6: gonna be on their feet a little more from that

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Speaker 6: eleven am to one pm. Period kind of unorthodox. It's

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Speaker 6: been so long, yes, yep, and then you know, now

348
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Speaker 6: it's really thrown off his schedule, and that that like movement,

349
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Speaker 6: it's probably not going to be as good for like

350
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Speaker 6: that last you know, thirty minutes of shooting light either,

351
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Speaker 6: because his whole schedule's just off at this point.

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Speaker 2: You know, what's coming coming to my mind is like that.

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Speaker 2: We always think about how the full moon would be

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Speaker 2: beneficial to these animals, right, like they can chase mortel

355
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Speaker 2: or they can feed better all night long. Right, but

356
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Speaker 2: they're prey animals, so like really the wolves can see

357
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Speaker 2: them better, the coyotes can see them better.

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Speaker 1: Let's hear from the experts. Okay, let's start out. Tell

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Speaker 1: us about your survey. We just we just gave you

360
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Speaker 1: three really read Yeah, we just gave you two of

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Speaker 1: the things that are floating around out there. But tell

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Speaker 1: tell us about the survey he did.

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Speaker 4: Okay, So before I get tops, so we did a

364
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Speaker 4: a buck movement project for a complete dealy different reason.

365
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Speaker 4: And so seven or eight years ago, I thought, uh, well,

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Speaker 4: this is going to be a great opportunity. We have

367
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Speaker 4: all these daily movement rates, and so I'm going to

368
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Speaker 4: tinker with this, real simple analyses. I'm gonna take these

369
00:20:14,680 --> 00:20:18,800
Speaker 4: daily movement rates averaged for the population day by day

370
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Speaker 4: by day and daytime movements nighttime movements, and it was

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Speaker 4: very apparent that when you plotted that from September all

372
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Speaker 4: the way to six weeks, two months or a month

373
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Speaker 4: plus post rut, all the variation in movement was apparent.

374
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Speaker 4: Is the rut, there is the right difference in daytime

375
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Speaker 4: movement nighttime movement. So so here we go. I'm gonna

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Speaker 4: put this on Facebook. So on top of that movement graph,

377
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Speaker 4: I plotted the oscillation of full moon, new moon, full

378
00:20:55,359 --> 00:20:59,560
Speaker 4: moon new and had those superimposed on each other. And

379
00:20:59,640 --> 00:21:03,040
Speaker 4: so you can see that from from the phase of

380
00:21:03,080 --> 00:21:07,040
Speaker 4: the moon from new to full in that period there's

381
00:21:07,080 --> 00:21:12,479
Speaker 4: a little there's no variation in deer movement whatsoever. And

382
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Speaker 4: so I put it out there on Facebook. Appears to me,

383
00:21:15,840 --> 00:21:19,200
Speaker 4: you know, the biology and and the science is very

384
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Speaker 4: clear that that there's nothing going on with the moon phase.

385
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Speaker 4: What state Mississippi?

386
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Speaker 3: Yeah, come on.

387
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Speaker 2: This is the thing, people, this is a.

388
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Speaker 6: Thing you will yeah, okay, they will to be like,

389
00:21:32,240 --> 00:21:34,240
Speaker 6: well you didn't study the deer in Wisconsin.

390
00:21:35,160 --> 00:21:37,919
Speaker 1: Well, what the typical things you can't win. You can't win.

391
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Speaker 4: They won't even say in my state it will be

392
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Speaker 4: but my deer, yes.

393
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Speaker 1: And so the fact I got I got it because

394
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Speaker 1: one thing that you got I never encountered it before.

395
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Speaker 1: So when you're talking about that, you're graphic movement. Can

396
00:21:57,560 --> 00:22:01,480
Speaker 1: you is this the yards per hour? Which great? M okay,

397
00:22:01,560 --> 00:22:03,879
Speaker 1: keep explaining that to people, like when you say, like

398
00:22:03,880 --> 00:22:06,440
Speaker 1: you're measuring movement, like, what what does that mean?

399
00:22:06,920 --> 00:22:10,320
Speaker 4: What's the metric? Yeah, yeah, we typically do yards per

400
00:22:10,440 --> 00:22:13,879
Speaker 4: day or yards per hour. That that's the measurement, and

401
00:22:13,920 --> 00:22:17,399
Speaker 4: that's from the sequential GPS locations, So we're getting a

402
00:22:17,400 --> 00:22:20,320
Speaker 4: location from them every fifteen minutes and so it's just

403
00:22:20,320 --> 00:22:22,159
Speaker 4: the sum of that over whatever period of time and

404
00:22:22,200 --> 00:22:24,199
Speaker 4: you come up with a rate of movement from that.

405
00:22:24,800 --> 00:22:26,600
Speaker 4: So put that out there and a couple of people

406
00:22:26,680 --> 00:22:29,240
Speaker 4: where yeah, I knew nothing was going on with this.

407
00:22:29,440 --> 00:22:34,840
Speaker 4: What's but the overwhelming response was this guy's an idiot?

408
00:22:35,320 --> 00:22:36,600
Speaker 1: Me this guy sure?

409
00:22:37,080 --> 00:22:40,400
Speaker 4: And that has nothing to do with the moon phase.

410
00:22:40,800 --> 00:22:44,800
Speaker 4: That's what Grandpa talked about. What was moon phase. It's

411
00:22:44,920 --> 00:22:50,200
Speaker 4: moon position. It's the so lunar aspect of it. That

412
00:22:50,200 --> 00:22:53,280
Speaker 4: that's what's driving it. So it's what time of the

413
00:22:53,359 --> 00:22:59,240
Speaker 4: day is the moon overhead underfoot? Setting things like that,

414
00:22:59,400 --> 00:23:02,920
Speaker 4: where is the moon on the horizon, and the supposed

415
00:23:03,800 --> 00:23:08,119
Speaker 4: gravitational pull and how that might be impacting. That is

416
00:23:08,160 --> 00:23:11,280
Speaker 4: what got people interested in that. So that was all

417
00:23:11,320 --> 00:23:13,480
Speaker 4: the deal. And I didn't have any data at that

418
00:23:13,560 --> 00:23:16,680
Speaker 4: point to refute it, so I just tucked that away

419
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Speaker 4: like this just.

420
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Speaker 1: Another eggheaded college guy about the mood.

421
00:23:21,760 --> 00:23:26,000
Speaker 4: Yeah, a lot worse than that, but yeah. And so

422
00:23:26,080 --> 00:23:29,840
Speaker 4: that data set sat there and we you know, I

423
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Speaker 4: was holding that we got to do this, We've got

424
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Speaker 4: to do something more sophisticated. And I was very lucky

425
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Speaker 4: to have a coworker, a research analyst at POSTOCU named

426
00:23:41,080 --> 00:23:47,200
Speaker 4: Natasha Ellison. She has a PhD in mathematics, so undergraduate

427
00:23:47,400 --> 00:23:52,520
Speaker 4: masters PhD and mathematics with the application to biology and

428
00:23:52,720 --> 00:23:56,520
Speaker 4: movement ecology, and she actually tinkered with quantum mechanics for

429
00:23:56,600 --> 00:24:00,520
Speaker 4: her master's degree. One of her famous statements is the

430
00:24:00,560 --> 00:24:04,359
Speaker 4: math really wasn't that challenging for physics and quantum mechanics

431
00:24:04,359 --> 00:24:07,480
Speaker 4: with their master's degree. So she's at the tip of

432
00:24:07,520 --> 00:24:12,320
Speaker 4: the spear and understanding how to disentangle all this and uh,

433
00:24:12,560 --> 00:24:14,919
Speaker 4: I'm sure she chuckled and rolled her eyes when I

434
00:24:14,960 --> 00:24:16,719
Speaker 4: told her, it's like, Natasha.

435
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Speaker 3: We got a problem with Bucks.

436
00:24:18,240 --> 00:24:21,239
Speaker 4: We gotta we gotta do. We've got an opportunity and

437
00:24:21,280 --> 00:24:23,840
Speaker 4: this is going to be something No other academic is

438
00:24:23,920 --> 00:24:27,920
Speaker 4: going to spend this amount of time and emotion going

439
00:24:27,920 --> 00:24:29,760
Speaker 4: into this life. But we've got a real opportunity to do,

440
00:24:29,800 --> 00:24:34,119
Speaker 4: hopefully to do something special. And so she analyzed it

441
00:24:34,359 --> 00:24:39,320
Speaker 4: at a way a level of detail that had never

442
00:24:39,400 --> 00:24:44,600
Speaker 4: been done before. And so, but when we were digging

443
00:24:44,640 --> 00:24:48,240
Speaker 4: into that, and when we were trying to figure out

444
00:24:48,320 --> 00:24:49,920
Speaker 4: what we're gonna do, how we're gonna do it, et cetera,

445
00:24:50,160 --> 00:24:52,960
Speaker 4: we thought, you know, what, we need to do a survey.

446
00:24:53,560 --> 00:24:56,440
Speaker 4: We need to we need to figure out what what

447
00:24:56,560 --> 00:25:01,359
Speaker 4: people think and what are their expectations from If there

448
00:25:01,640 --> 00:25:05,520
Speaker 4: is a moon effect, how big is it? And so

449
00:25:05,840 --> 00:25:08,919
Speaker 4: we use the term in science called effect size, and

450
00:25:08,960 --> 00:25:12,480
Speaker 4: so is something statistically significant or not? That's what people

451
00:25:12,560 --> 00:25:15,840
Speaker 4: hear all the time. So it's really not as important

452
00:25:16,320 --> 00:25:20,399
Speaker 4: as effect size. Effect size just means the difference between

453
00:25:20,400 --> 00:25:23,560
Speaker 4: the treatment and the control. You get a one percent increase,

454
00:25:23,640 --> 00:25:27,280
Speaker 4: fifty percent increase, one hundred percent increase. That is what's

455
00:25:27,840 --> 00:25:32,200
Speaker 4: the most important people. So we did survey and got

456
00:25:32,240 --> 00:25:38,840
Speaker 4: to say this, this was not a sociology sanctioned, sophisticated

457
00:25:38,960 --> 00:25:42,919
Speaker 4: survey and that department. This was the MSU dear lab

458
00:25:43,560 --> 00:25:48,520
Speaker 4: us doing social media survey and just saying, hey, all

459
00:25:48,600 --> 00:25:50,920
Speaker 4: you people out there, what do you think about this?

460
00:25:51,040 --> 00:25:55,960
Speaker 4: So what came back was yet eighty three percent eighty

461
00:25:56,000 --> 00:25:59,359
Speaker 4: three percent of the people that responded thought the moon

462
00:25:59,640 --> 00:26:03,520
Speaker 4: is affecting deer movement in some way. And then a

463
00:26:03,680 --> 00:26:07,840
Speaker 4: subset of that, which was always more than half. You say, okay,

464
00:26:08,080 --> 00:26:12,200
Speaker 4: if it is affecting deer movement by how much and

465
00:26:12,880 --> 00:26:16,760
Speaker 4: the effect size they reported or the differences they reported

466
00:26:17,119 --> 00:26:20,600
Speaker 4: for something like betting, the difference in bedding was at

467
00:26:20,640 --> 00:26:25,199
Speaker 4: a minimum, they're on their feet thirty minutes earlier, or

468
00:26:25,240 --> 00:26:29,359
Speaker 4: they're on their feet up to two hours earlier. The

469
00:26:29,359 --> 00:26:32,600
Speaker 4: moon is stimulating them to get up out of their

470
00:26:32,600 --> 00:26:37,880
Speaker 4: bed two hours earlier. The distance that they were moving

471
00:26:37,960 --> 00:26:42,000
Speaker 4: in terms of velocity was always at least fifty yards

472
00:26:42,040 --> 00:26:46,720
Speaker 4: per hour, two greater than two hundred yards per hour.

473
00:26:47,320 --> 00:26:52,840
Speaker 4: So these people that are believing the moon is stimulating movement,

474
00:26:53,560 --> 00:26:58,520
Speaker 4: they're all in God, Yeah, they're different animals under a

475
00:26:58,560 --> 00:27:00,240
Speaker 4: specified moon condition.

476
00:27:00,240 --> 00:27:04,000
Speaker 2: Ronson Were those respondents were they all from that general

477
00:27:04,040 --> 00:27:06,480
Speaker 2: area in Mississippi or were they nationwide?

478
00:27:06,880 --> 00:27:07,480
Speaker 4: Nationwide?

479
00:27:08,000 --> 00:27:08,200
Speaker 1: Yeah?

480
00:27:08,280 --> 00:27:08,960
Speaker 4: Nationwide?

481
00:27:09,000 --> 00:27:09,440
Speaker 1: Certainly.

482
00:27:09,840 --> 00:27:14,679
Speaker 7: Was there a specific concentration among you know, was twenty

483
00:27:14,760 --> 00:27:18,639
Speaker 7: five percent although nationwide twenty five percent respondents from like

484
00:27:18,960 --> 00:27:19,600
Speaker 7: Texas or.

485
00:27:19,600 --> 00:27:23,199
Speaker 4: So difficult for us to tell because that was I

486
00:27:23,200 --> 00:27:26,360
Speaker 4: can't remember it was Facebook or Instagram and you might

487
00:27:26,359 --> 00:27:29,840
Speaker 4: be able to disentangle that. I can't.

488
00:27:32,480 --> 00:27:35,040
Speaker 1: When they did the survey and you had eighty three

489
00:27:35,080 --> 00:27:39,359
Speaker 1: percent say that it did something, was it did you

490
00:27:39,440 --> 00:27:41,920
Speaker 1: find that there was a lot of that they had

491
00:27:41,960 --> 00:27:47,560
Speaker 1: contradictory opinions, meaning some people thought they moved earlier, people

492
00:27:47,600 --> 00:27:49,800
Speaker 1: thought they moved later, or did you find like was

493
00:27:50,520 --> 00:27:52,200
Speaker 1: let me put it a different way instead of exploring

494
00:27:52,240 --> 00:27:55,560
Speaker 1: all the exceptions, what if you had to synthesize it

495
00:27:55,560 --> 00:28:00,199
Speaker 1: and make it that like the general impression was what

496
00:28:00,480 --> 00:28:01,520
Speaker 1: among survey people?

497
00:28:02,119 --> 00:28:06,280
Speaker 4: So during the day they betted less, meaning they're on

498
00:28:06,320 --> 00:28:10,320
Speaker 4: their feet more. They are on their feet if you're

499
00:28:10,320 --> 00:28:14,360
Speaker 4: thinking about an afternoon movement, about they're on their feet earlier,

500
00:28:14,920 --> 00:28:17,679
Speaker 4: and when they are moving they are moving at a

501
00:28:17,720 --> 00:28:21,680
Speaker 4: greater rate of speed. All of that which would result

502
00:28:21,720 --> 00:28:23,480
Speaker 4: in greater observability.

503
00:28:23,720 --> 00:28:25,600
Speaker 3: When there's what happening with the moon.

504
00:28:26,560 --> 00:28:27,000
Speaker 4: Name it.

505
00:28:28,280 --> 00:28:33,040
Speaker 1: Oh, okay, so it's an idea that there's more movement,

506
00:28:34,720 --> 00:28:39,400
Speaker 1: but there's But like the general conception is, the general

507
00:28:39,400 --> 00:28:43,920
Speaker 1: perception is that what depending on what the moon is doing,

508
00:28:44,240 --> 00:28:46,800
Speaker 1: it drives more movement. But there's not a lot of

509
00:28:46,840 --> 00:28:49,520
Speaker 1: a there's not a lot of agreement about what the

510
00:28:49,560 --> 00:28:53,640
Speaker 1: moon needs to be doing to drive more movement. Yeah,

511
00:28:53,720 --> 00:28:56,560
Speaker 1: it's not like a it's not like a full.

512
00:28:56,360 --> 00:28:58,240
Speaker 3: Moon gives more dear movement.

513
00:28:58,520 --> 00:29:01,760
Speaker 1: People might disagree about the detail, but something happens and

514
00:29:01,800 --> 00:29:04,640
Speaker 1: there's more movement based on the moon. I'm not doing

515
00:29:04,640 --> 00:29:05,680
Speaker 1: a very good job of articulate.

516
00:29:06,120 --> 00:29:11,000
Speaker 4: There is a moon situation for every person and their

517
00:29:11,080 --> 00:29:14,520
Speaker 4: pet hypothesis for when I want to go hunt. Okay,

518
00:29:14,600 --> 00:29:16,480
Speaker 4: it's either I'm going to go with the moon overhead

519
00:29:16,600 --> 00:29:19,280
Speaker 4: or the moon underfoot, or the moon is setting or rising,

520
00:29:19,640 --> 00:29:22,440
Speaker 4: or it's a full moon, or we're in the perigy

521
00:29:22,640 --> 00:29:25,840
Speaker 4: or apogee because of the gravitation, it's closer or it's

522
00:29:25,880 --> 00:29:28,960
Speaker 4: further away. Every single day you can pull out a

523
00:29:29,040 --> 00:29:30,840
Speaker 4: scenario of what the moon is doing.

524
00:29:31,000 --> 00:29:31,360
Speaker 1: Got it?

525
00:29:31,720 --> 00:29:36,440
Speaker 3: And but whatever that is, it's driving movement. No, it's

526
00:29:36,480 --> 00:29:37,360
Speaker 3: not you know what I'm saying.

527
00:29:37,440 --> 00:29:40,960
Speaker 1: No, No, in their mind, yeah, and they're sold and

528
00:29:41,000 --> 00:29:43,880
Speaker 1: then and then in their mind yeah, in the mind

529
00:29:43,880 --> 00:29:45,520
Speaker 1: of a And I'm not trying to dog on them

530
00:29:45,880 --> 00:29:47,440
Speaker 1: like in the mind of because, like I said, I

531
00:29:47,480 --> 00:29:50,040
Speaker 1: used to I used to think there was something to it.

532
00:29:50,080 --> 00:29:52,440
Speaker 1: Is it fair to say that that people that believe

533
00:29:52,520 --> 00:29:56,560
Speaker 1: it also believe that there's like the opposite effect. Meaning

534
00:29:57,880 --> 00:29:59,600
Speaker 1: let's say you're a full moon or like you're a

535
00:29:59,600 --> 00:30:03,400
Speaker 1: full moon guy, You're a full moon guy, Like I

536
00:30:03,440 --> 00:30:07,000
Speaker 1: see more deer movement at a full moon? Do they do?

537
00:30:07,080 --> 00:30:08,720
Speaker 3: They usually then believe.

538
00:30:08,680 --> 00:30:12,280
Speaker 1: That there is a opposite effect, So a new moon

539
00:30:13,080 --> 00:30:17,920
Speaker 1: equals yes, an extreme on the other example, like much

540
00:30:18,000 --> 00:30:18,560
Speaker 1: less movement.

541
00:30:18,640 --> 00:30:21,160
Speaker 4: Yeah, that's the reason the deer weren't moving today.

542
00:30:21,240 --> 00:30:23,600
Speaker 1: Yeah, because of the opposite gotcha. So it's not just

543
00:30:23,680 --> 00:30:25,920
Speaker 1: it creates a spike, but it's sort of this like

544
00:30:26,560 --> 00:30:27,920
Speaker 1: trend that moves in and out.

545
00:30:28,120 --> 00:30:30,080
Speaker 4: Yeah, and it has a top and bottom. Ya, a

546
00:30:30,080 --> 00:30:33,760
Speaker 4: spike and then a suppression. Yeah, God during daylight hours.

547
00:30:33,760 --> 00:30:35,880
Speaker 4: And that's what we focused on. What hunters are going

548
00:30:35,960 --> 00:30:36,960
Speaker 4: to see?

549
00:30:37,640 --> 00:30:40,800
Speaker 6: What did your study find that did impact deer movement

550
00:30:41,360 --> 00:30:42,440
Speaker 6: just the rut.

551
00:30:43,320 --> 00:30:51,160
Speaker 4: Yeah, so crepuscular periods. So nothing supersedes this, Nothing comes

552
00:30:51,240 --> 00:30:57,120
Speaker 4: even close to superseding sun up and sundown and the rut.

553
00:30:58,360 --> 00:31:02,440
Speaker 4: There is a subtle, subtle effect of temperature, and that

554
00:31:02,600 --> 00:31:07,040
Speaker 4: is what Natasha, It's really complicated in this multivariate all

555
00:31:07,080 --> 00:31:10,840
Speaker 4: these variables are interacting, but there is a subtle effect

556
00:31:11,040 --> 00:31:14,480
Speaker 4: of temperature. Meaning in our neck of the woods it

557
00:31:14,520 --> 00:31:16,600
Speaker 4: would be different up Nora, uh huh, and our neck

558
00:31:16,640 --> 00:31:19,560
Speaker 4: of the woods, when you start getting sub forty degrees,

559
00:31:20,240 --> 00:31:23,520
Speaker 4: we will see a little bit more higher of a

560
00:31:23,560 --> 00:31:25,880
Speaker 4: movement rate during daylight hours.

561
00:31:25,920 --> 00:31:28,960
Speaker 6: I feel like you're saying that is like the hottest

562
00:31:28,960 --> 00:31:33,040
Speaker 6: take a dear biologist has ever had on deer temperature movement.

563
00:31:33,280 --> 00:31:35,800
Speaker 6: And yeah, yeah, deer movement based on tempera.

564
00:31:35,920 --> 00:31:38,400
Speaker 4: Well, this is the guy right here that said for

565
00:31:38,720 --> 00:31:41,320
Speaker 4: more than a decade, it had nothing to do. We

566
00:31:41,360 --> 00:31:46,480
Speaker 4: do not see any signature whatsoever of temperature. But it

567
00:31:46,600 --> 00:31:49,400
Speaker 4: took more data, and it took the right type of

568
00:31:49,440 --> 00:31:55,000
Speaker 4: person analytically to tease apart very very subtle differences, a

569
00:31:55,040 --> 00:31:56,280
Speaker 4: skill set that I didn't have.

570
00:31:56,600 --> 00:32:02,040
Speaker 1: Yeah, can you lay out you do the survey, and

571
00:32:02,080 --> 00:32:06,800
Speaker 1: then you got to start pulling data, like the surveys

572
00:32:06,840 --> 00:32:07,280
Speaker 1: just kind of a.

573
00:32:07,240 --> 00:32:08,640
Speaker 3: Side project to see where you're at.

574
00:32:08,760 --> 00:32:12,479
Speaker 1: Yeah, so to go get a definitive picture of this.

575
00:32:13,880 --> 00:32:16,240
Speaker 1: What are you doing? Like how many deer are you monitoring?

576
00:32:16,320 --> 00:32:18,560
Speaker 1: How do you monitor the deer? Like what is the

577
00:32:18,640 --> 00:32:20,240
Speaker 1: sort of scale of the project?

578
00:32:20,560 --> 00:32:24,120
Speaker 4: Yeah, so, yeah, this is one thing we wanted to

579
00:32:24,120 --> 00:32:27,200
Speaker 4: do different and probably one of the issues in the past,

580
00:32:27,280 --> 00:32:30,320
Speaker 4: including the stuff I did in the past, is treating

581
00:32:30,360 --> 00:32:33,920
Speaker 4: the population as the population and not looking at individuals.

582
00:32:34,120 --> 00:32:39,080
Speaker 4: There's a lot of individual variation and buck movements. Some

583
00:32:39,160 --> 00:32:42,680
Speaker 4: of them are homebodies, some of them have very disjointed

584
00:32:43,160 --> 00:32:46,840
Speaker 4: home ranges that we call a mobile buck personality home range.

585
00:32:46,960 --> 00:32:48,800
Speaker 4: Some of them move a whole bunch, some of them

586
00:32:48,840 --> 00:32:51,000
Speaker 4: don't move a lot. So we don't want to just

587
00:32:51,400 --> 00:32:54,480
Speaker 4: put all of that together and come up with an average.

588
00:32:55,040 --> 00:32:58,240
Speaker 4: We want to be able to look at every single

589
00:32:58,280 --> 00:33:02,840
Speaker 4: buck and what is his movement profile, and then look

590
00:33:02,880 --> 00:33:07,360
Speaker 4: at when you evaluate all these different moon conditions, is

591
00:33:07,400 --> 00:33:12,280
Speaker 4: the buck's behavior movement behavior deviating from the norm that buck.

592
00:33:12,720 --> 00:33:15,200
Speaker 1: Yeah, you're looking at I see like what is he?

593
00:33:15,400 --> 00:33:18,400
Speaker 1: What is it buck a or buck.

594
00:33:18,200 --> 00:33:19,760
Speaker 3: One twenty one?

595
00:33:19,920 --> 00:33:22,840
Speaker 1: What is buck one? Twenty one's normal groove. That's right,

596
00:33:23,520 --> 00:33:26,520
Speaker 1: and then how does Buck one twenty one's groove switch

597
00:33:26,520 --> 00:33:26,960
Speaker 1: at the moon?

598
00:33:27,080 --> 00:33:27,560
Speaker 4: That's right?

599
00:33:27,920 --> 00:33:31,400
Speaker 1: And then Buck one twenty eight, same thing. And one

600
00:33:31,400 --> 00:33:33,080
Speaker 1: of those bucks might be like a dude who likes

601
00:33:33,080 --> 00:33:34,560
Speaker 1: to cruise, and one of those bucks might be a

602
00:33:34,640 --> 00:33:35,600
Speaker 1: dude who likes to stay home.

603
00:33:35,680 --> 00:33:37,920
Speaker 4: Yeah, So the guy that cruises, does he cruise more?

604
00:33:38,120 --> 00:33:38,320
Speaker 1: You know?

605
00:33:38,360 --> 00:33:39,840
Speaker 3: There is a stay of home guy cruse more?

606
00:33:39,920 --> 00:33:40,400
Speaker 1: Yeah? Yeah.

607
00:33:41,280 --> 00:33:46,640
Speaker 4: And so Natasha went through and so for every single buck,

608
00:33:46,800 --> 00:33:50,080
Speaker 4: she created a fourteen day window. So this is a

609
00:33:50,160 --> 00:33:54,440
Speaker 4: moving window. And so for every fourteen days, she looked

610
00:33:54,440 --> 00:33:59,280
Speaker 4: at the seven days prior seven days and it uh

611
00:34:00,080 --> 00:34:04,960
Speaker 4: behind and calculated for every single hour of the day.

612
00:34:05,960 --> 00:34:09,960
Speaker 4: So for this buck at ten am, she has a

613
00:34:10,000 --> 00:34:13,760
Speaker 4: movement profile of what the average response for that buck

614
00:34:14,320 --> 00:34:19,400
Speaker 4: will be at ten am, calibrated for the prior seven

615
00:34:19,480 --> 00:34:22,840
Speaker 4: days and the future seven days. And so when we

616
00:34:22,920 --> 00:34:26,920
Speaker 4: have some moon alignment or phase or whatever, we then

617
00:34:27,040 --> 00:34:32,040
Speaker 4: look at does that buck's ten am movement pattern deviate

618
00:34:32,640 --> 00:34:35,879
Speaker 4: because of the moon. And so then you do the

619
00:34:35,920 --> 00:34:40,640
Speaker 4: sum of those deviations for every single buck that is

620
00:34:40,680 --> 00:34:44,239
Speaker 4: in the population to come up with a mean response

621
00:34:45,120 --> 00:34:50,360
Speaker 4: and that's how we are able to work through A

622
00:34:50,520 --> 00:34:54,640
Speaker 4: Saturday occurred, big hunting day, a Saturday, the rut occurred.

623
00:34:54,960 --> 00:34:57,160
Speaker 4: It was a really warm period, we had a really

624
00:34:57,200 --> 00:35:00,720
Speaker 4: a cold front. By doing that and having a moving

625
00:35:00,840 --> 00:35:04,000
Speaker 4: average for every single buck, you account for all the

626
00:35:04,120 --> 00:35:06,960
Speaker 4: extraneous noise. Sure that can be going on.

627
00:35:07,320 --> 00:35:11,279
Speaker 1: Huh okay, off the moon because now just you brought

628
00:35:11,280 --> 00:35:14,759
Speaker 1: it up a Saturday, a lot of guys hunting. You

629
00:35:14,840 --> 00:35:21,400
Speaker 1: mentioned it crepuscular period. So sunrise, sunset impacts, the rot impacts,

630
00:35:21,719 --> 00:35:23,279
Speaker 1: temperature impacts.

631
00:35:24,280 --> 00:35:26,320
Speaker 3: Pressure's got to make them not move, right, sure?

632
00:35:26,400 --> 00:35:30,280
Speaker 1: Okay, yeah, so that's true.

633
00:35:31,040 --> 00:35:35,240
Speaker 4: I think it's less about it's not that they're not moving,

634
00:35:35,600 --> 00:35:40,160
Speaker 4: it is where they choose to move based on hunting pressure.

635
00:35:40,880 --> 00:35:45,480
Speaker 4: And so in another study that we did conducted in Oklahoma,

636
00:35:46,160 --> 00:35:48,360
Speaker 4: we and that was set up differently. So that was

637
00:35:48,400 --> 00:35:53,240
Speaker 4: a treatment area where there was hunting pressure and treatment

638
00:35:53,280 --> 00:35:57,480
Speaker 4: area too heavy hunting pressure, and a control area. And

639
00:35:57,520 --> 00:36:00,560
Speaker 4: in those places the deer were collared, the hunters were

640
00:36:00,560 --> 00:36:05,440
Speaker 4: collared carrying a GPSHW and so could we could monitor

641
00:36:05,480 --> 00:36:07,400
Speaker 4: where they were going on the landscape and so forth.

642
00:36:07,400 --> 00:36:11,200
Speaker 4: Then we're watching the bucks be able to move around them,

643
00:36:11,800 --> 00:36:15,440
Speaker 4: and it literally took three to four days, and three

644
00:36:15,480 --> 00:36:18,879
Speaker 4: to four days of there are hunters on the landscape,

645
00:36:18,920 --> 00:36:24,440
Speaker 4: it changed. Something is different. Their the bucks movement behavior changed,

646
00:36:25,080 --> 00:36:28,839
Speaker 4: not as much as total distance moved during the day,

647
00:36:29,440 --> 00:36:34,719
Speaker 4: but where they went on the landscape. And the academic

648
00:36:35,160 --> 00:36:39,919
Speaker 4: term is called their tortuosity, meaning the complexity of their

649
00:36:40,040 --> 00:36:45,120
Speaker 4: movement path changed. That we think was because they had

650
00:36:45,160 --> 00:36:48,840
Speaker 4: to avoid all these different places on the landscape that

651
00:36:48,920 --> 00:36:51,440
Speaker 4: they had three to four days of info was going

652
00:36:51,520 --> 00:36:53,200
Speaker 4: to be associated with hunting in danger.

653
00:36:55,560 --> 00:36:59,879
Speaker 1: Oh but his yards per hour, his his yards per

654
00:37:00,520 --> 00:37:02,840
Speaker 1: stay up, stay consistent.

655
00:37:02,920 --> 00:37:07,800
Speaker 4: In that experiment. Yeah. Yeah, their movement behavior really didn't

656
00:37:07,920 --> 00:37:12,480
Speaker 4: change other than the tortuosity and where they went. So quote,

657
00:37:12,640 --> 00:37:16,200
Speaker 4: they did not go nocturnal. They were still on their

658
00:37:16,239 --> 00:37:19,400
Speaker 4: feet because they got eat They're on their feet, they're forging.

659
00:37:19,719 --> 00:37:23,600
Speaker 4: They're just going to areas where they determine there's not

660
00:37:23,680 --> 00:37:27,440
Speaker 4: going to be hunting pressure, no evidence, no memory of

661
00:37:27,640 --> 00:37:28,440
Speaker 4: human activity.

662
00:37:28,560 --> 00:37:31,799
Speaker 1: Yeah. Old Lady Thompson's house, you know, doesn't let anybody hunt.

663
00:37:32,840 --> 00:37:35,360
Speaker 2: Oh yeah, I was just telling my buddy Seth. We

664
00:37:35,440 --> 00:37:37,719
Speaker 2: came out of the woods after we killed the bull.

665
00:37:37,760 --> 00:37:41,440
Speaker 2: I was telling you about earlier. The next night dead,

666
00:37:42,080 --> 00:37:43,880
Speaker 2: not that it was on fire the night before. I've

667
00:37:43,920 --> 00:37:46,720
Speaker 2: only heard like four or five bugles before that bull died.

668
00:37:47,040 --> 00:37:50,080
Speaker 2: But the next evening we hear like a bugle. It's

669
00:37:50,120 --> 00:37:53,920
Speaker 2: just just dead, still quiet. And I'm remarking to my

670
00:37:53,960 --> 00:37:56,280
Speaker 2: buddy's seth. I'm like, yeah, it was kind of hot,

671
00:37:56,440 --> 00:38:00,080
Speaker 2: no wind. You know, it's just like, you know, they

672
00:38:00,120 --> 00:38:02,200
Speaker 2: don't want to run when they got that big winter codeon.

673
00:38:02,480 --> 00:38:06,279
Speaker 2: He goes, well, where I was at yesterday, We're the

674
00:38:06,480 --> 00:38:09,480
Speaker 2: lasting a big herd out in a private hayfield and

675
00:38:09,520 --> 00:38:13,200
Speaker 2: at four thirty they are ripping. Yeah, you know.

676
00:38:13,280 --> 00:38:16,440
Speaker 1: So it's like, yeah, they found a good place to

677
00:38:16,480 --> 00:38:20,520
Speaker 1: go exactly. Yeah, they're going to do their thing. Huh.

678
00:38:20,560 --> 00:38:24,520
Speaker 1: So the going nocturnal from pressure, they just go do

679
00:38:24,560 --> 00:38:24,960
Speaker 1: what they.

680
00:38:24,800 --> 00:38:25,799
Speaker 3: Want to do somewhere else.

681
00:38:25,920 --> 00:38:28,880
Speaker 4: Yeah, yeah, they just changed their behavior on where they

682
00:38:28,920 --> 00:38:32,839
Speaker 4: spend time. Now, I will say this, there have been

683
00:38:32,960 --> 00:38:36,359
Speaker 4: cases at the deer conference we go to, you know

684
00:38:36,480 --> 00:38:40,800
Speaker 4: every year, there have act there have been some cases

685
00:38:40,960 --> 00:38:46,640
Speaker 4: with GPS or VHF collared bucks where in heavily heavily

686
00:38:46,760 --> 00:38:53,360
Speaker 4: hunted places, a buckbedded all day long. But I literally, Steve,

687
00:38:53,520 --> 00:38:57,279
Speaker 4: I remember that one time. In the thirty years i've

688
00:38:57,320 --> 00:38:59,480
Speaker 4: been going and learning about deer and thinking, I've heard

689
00:38:59,520 --> 00:39:03,440
Speaker 4: of one instance where objectively a buck had a mark,

690
00:39:03,760 --> 00:39:06,560
Speaker 4: a radio caller on it or a GPS collar, and

691
00:39:06,719 --> 00:39:10,840
Speaker 4: it did not move during daylight hours because hunting pressure

692
00:39:10,920 --> 00:39:14,680
Speaker 4: was all around God and all these other instances. They're

693
00:39:14,800 --> 00:39:17,440
Speaker 4: up on their feet and moving. Now they may not be.

694
00:39:17,560 --> 00:39:21,200
Speaker 4: You have to look at what's called the step length,

695
00:39:21,719 --> 00:39:25,480
Speaker 4: the movement path. So step length is a surrogate for velocity.

696
00:39:25,920 --> 00:39:28,160
Speaker 4: So if you're getting a ping from that collar every

697
00:39:28,200 --> 00:39:32,080
Speaker 4: fifteen minutes, if he's got a really high rate of speed,

698
00:39:32,120 --> 00:39:35,759
Speaker 4: you're going to cover more distance in fifteen minutes. And

699
00:39:35,800 --> 00:39:39,279
Speaker 4: so what you will see is that their yards per

700
00:39:39,320 --> 00:39:43,320
Speaker 4: hour can slow down, but they're still on their feet

701
00:39:43,400 --> 00:39:44,720
Speaker 4: and they're foraging and moving.

702
00:39:46,400 --> 00:39:49,600
Speaker 3: The other day, we were watching a bull moose.

703
00:39:50,840 --> 00:39:55,080
Speaker 1: Doing his like rut wander, and he was going through

704
00:39:55,080 --> 00:39:59,680
Speaker 1: this big alpine area and we watched them, I mean,

705
00:40:00,320 --> 00:40:06,040
Speaker 1: we watched him go a couple miles fast, and we're

706
00:40:06,080 --> 00:40:08,399
Speaker 1: waiting for him to stop. He was so far away

707
00:40:08,400 --> 00:40:10,160
Speaker 1: where like, well, when he stops, we'll try to call

708
00:40:10,200 --> 00:40:13,520
Speaker 1: and see if he registers the noise at all. We

709
00:40:13,560 --> 00:40:18,080
Speaker 1: watched him go a couple of miles and never stopped once,

710
00:40:18,600 --> 00:40:24,200
Speaker 1: just moving, just cruising, and you're like, where what you know,

711
00:40:24,320 --> 00:40:27,200
Speaker 1: what is his concept of where he's going? But just

712
00:40:28,640 --> 00:40:33,680
Speaker 1: moving and yeah, he's not afraid of anything. Yeah, I'm

713
00:40:33,680 --> 00:40:34,600
Speaker 1: not afraid of anything.

714
00:40:34,960 --> 00:40:39,680
Speaker 6: Yeah. Whitetail hunters have this time period between October ten

715
00:40:39,800 --> 00:40:43,120
Speaker 6: October twenty they refer to as the October Law. And

716
00:40:43,200 --> 00:40:45,080
Speaker 6: if you were to if you lived in a state

717
00:40:45,120 --> 00:40:48,240
Speaker 6: where the deer season is September one to December thirty,

718
00:40:48,280 --> 00:40:51,040
Speaker 6: first they would tell you that is the hardest ten

719
00:40:51,120 --> 00:40:54,399
Speaker 6: day stretch to kill a buck because they're nocturnal. What

720
00:40:54,440 --> 00:40:57,680
Speaker 6: are your movement studies say about that?

721
00:40:57,760 --> 00:41:01,000
Speaker 4: There is no lull that that does does not exist.

722
00:41:01,200 --> 00:41:03,879
Speaker 6: Not in any form. Like they're not only are they

723
00:41:03,920 --> 00:41:07,040
Speaker 6: not nocturnal during that period, but they're also like they're

724
00:41:07,080 --> 00:41:09,799
Speaker 6: moving more in that period than they were October one

725
00:41:09,840 --> 00:41:10,640
Speaker 6: to October Tenen.

726
00:41:11,000 --> 00:41:14,040
Speaker 4: I can't say they're moving more, but they're moving. And

727
00:41:14,280 --> 00:41:16,560
Speaker 4: this is just sit in the Mississippi State data here.

728
00:41:16,680 --> 00:41:20,239
Speaker 4: This is over and over again that there is no law.

729
00:41:20,600 --> 00:41:24,239
Speaker 4: But what can be going on at that time is

730
00:41:25,040 --> 00:41:28,920
Speaker 4: you have got a shuffling, so to speak. It's a

731
00:41:29,000 --> 00:41:32,400
Speaker 4: little bit late in October. So think about bachelor groups

732
00:41:32,800 --> 00:41:37,120
Speaker 4: during the summer box low testosterone velvet, and then we

733
00:41:37,160 --> 00:41:41,560
Speaker 4: get into September October, testosterone is surging through their body again.

734
00:41:41,640 --> 00:41:44,480
Speaker 4: They start getting into hard antler and then they start

735
00:41:44,520 --> 00:41:49,040
Speaker 4: shifting and moving around and setting up their fall winter

736
00:41:49,480 --> 00:41:52,759
Speaker 4: rut home ranges. So I think what's going on a

737
00:41:52,800 --> 00:41:55,840
Speaker 4: lot there is you've had a couple months or a

738
00:41:55,840 --> 00:42:00,560
Speaker 4: couple weeks of seeing the deer that you're normally seeing,

739
00:42:01,200 --> 00:42:03,560
Speaker 4: and then you get into that period in October where

740
00:42:03,560 --> 00:42:07,160
Speaker 4: a shuffle is coming and so they're moving in different

741
00:42:07,200 --> 00:42:09,720
Speaker 4: areas or they have left your area where your trail

742
00:42:09,760 --> 00:42:12,600
Speaker 4: camera is at, but they're still moving.

743
00:42:13,160 --> 00:42:13,359
Speaker 1: Yeah.

744
00:42:13,360 --> 00:42:16,640
Speaker 6: I think like if I was speaking to hunters in

745
00:42:16,680 --> 00:42:19,000
Speaker 6: eastern South Dakota where I grew up, I bet they

746
00:42:19,000 --> 00:42:22,360
Speaker 6: are seeing less movement in that period. But it's because

747
00:42:22,360 --> 00:42:24,880
Speaker 6: now there's combines in the fields. It's because there are

748
00:42:24,920 --> 00:42:27,960
Speaker 6: acorns on the ground. It's because pheasant season just opened

749
00:42:28,040 --> 00:42:30,280
Speaker 6: and that's kicked deer out of some beds. In CRP

750
00:42:30,760 --> 00:42:34,480
Speaker 6: like that, there is a lull happening that's very specific

751
00:42:34,520 --> 00:42:37,360
Speaker 6: to them, but it's not because the buck is now nocturnal.

752
00:42:37,560 --> 00:42:39,719
Speaker 6: It's because he's just moving in a different way in

753
00:42:39,719 --> 00:42:40,360
Speaker 6: a different place.

754
00:42:40,520 --> 00:42:42,319
Speaker 3: You're in a strategic.

755
00:42:41,840 --> 00:42:45,920
Speaker 1: Low, yes, where like all summer, these five bucks come

756
00:42:45,920 --> 00:42:48,640
Speaker 1: into that beanfield and all of a sudden they're not

757
00:42:48,719 --> 00:42:49,200
Speaker 1: there anymore.

758
00:42:49,320 --> 00:42:51,160
Speaker 6: Yeah, And I think it can be true that that's

759
00:42:51,239 --> 00:42:53,560
Speaker 6: like maybe the hardest ten day window to kill a

760
00:42:53,560 --> 00:42:56,640
Speaker 6: mature buck. But it's not because he's unkillable.

761
00:42:57,880 --> 00:43:01,239
Speaker 4: Yeah, he's just in a different place. Yeah, you got

762
00:43:01,239 --> 00:43:05,160
Speaker 4: to go look for him. Now Here's us really interesting

763
00:43:05,400 --> 00:43:10,279
Speaker 4: to me is we we looked at So we had

764
00:43:10,320 --> 00:43:12,600
Speaker 4: to have deer where we had to have two years

765
00:43:12,960 --> 00:43:15,400
Speaker 4: of them being collared. So we had a lot of

766
00:43:15,440 --> 00:43:17,600
Speaker 4: deer come and go, you know, why is.

767
00:43:17,560 --> 00:43:21,120
Speaker 3: That that you had Why two years? What's the significance.

768
00:43:21,040 --> 00:43:26,440
Speaker 4: Because the question, like Spencer was alluding to, is do

769
00:43:26,480 --> 00:43:31,120
Speaker 4: they have fidelity for a site the following year? So

770
00:43:31,400 --> 00:43:34,640
Speaker 4: if you see it in a particular place this October,

771
00:43:35,120 --> 00:43:37,319
Speaker 4: what are the odds you're going to see it next year?

772
00:43:37,800 --> 00:43:40,520
Speaker 4: So we had to limit our data just to bucks

773
00:43:40,800 --> 00:43:42,799
Speaker 4: that so it's a subset of that that we had

774
00:43:42,920 --> 00:43:47,840
Speaker 4: two years of data and it was really amazing. Is

775
00:43:47,880 --> 00:43:51,879
Speaker 4: that on the average when you got to after that

776
00:43:52,200 --> 00:43:55,239
Speaker 4: October kind of break up and shuffling, and when they

777
00:43:55,280 --> 00:44:00,279
Speaker 4: went back and started settling into that area, the average

778
00:44:00,360 --> 00:44:05,200
Speaker 4: distance on a daily scale. And so what we did is,

779
00:44:05,640 --> 00:44:09,960
Speaker 4: where is this buck at five pm October ninth, twenty

780
00:44:10,000 --> 00:44:13,800
Speaker 4: twenty four. Where is it at October ninth, five pm,

781
00:44:13,880 --> 00:44:16,760
Speaker 4: twenty twenty five? About a thousand yards apart?

782
00:44:17,719 --> 00:44:18,239
Speaker 1: Is that right?

783
00:44:19,800 --> 00:44:21,200
Speaker 4: About a thousand yards apart?

784
00:44:21,600 --> 00:44:24,279
Speaker 1: See, if you're hunting ten ac or parcels, that's a lot.

785
00:44:26,000 --> 00:44:28,879
Speaker 4: And that could absolutely be off property and you may

786
00:44:28,920 --> 00:44:32,760
Speaker 4: never see it again. But he's in the neighborhood. If

787
00:44:32,800 --> 00:44:34,400
Speaker 4: he's alive, he's in the neighborhood.

788
00:44:34,520 --> 00:44:35,160
Speaker 1: Yeah. God.

789
00:44:36,800 --> 00:44:39,080
Speaker 6: I used to work with a lot of fish biologists,

790
00:44:39,120 --> 00:44:41,720
Speaker 6: and I found that there were equal number of fish

791
00:44:41,719 --> 00:44:45,759
Speaker 6: biologists who were hardcore anglers as there were guys who

792
00:44:45,840 --> 00:44:48,600
Speaker 6: never fished a day a year, like they just literally

793
00:44:48,719 --> 00:44:51,440
Speaker 6: never wed a line. And I found that they would

794
00:44:51,800 --> 00:44:54,480
Speaker 6: ask very different questions when it came to what they

795
00:44:54,520 --> 00:44:57,840
Speaker 6: were studying. What do you notice for what percentage of

796
00:44:57,880 --> 00:45:01,200
Speaker 6: dear biologists are hardcore hunters? These guys who just like

797
00:45:01,400 --> 00:45:02,160
Speaker 6: never fill a tag?

798
00:45:04,600 --> 00:45:06,640
Speaker 1: Good question, are.

799
00:45:06,880 --> 00:45:07,600
Speaker 6: You a big hunter?

800
00:45:08,120 --> 00:45:09,359
Speaker 4: I am? I am?

801
00:45:09,560 --> 00:45:10,920
Speaker 6: Which do you think that's normal.

802
00:45:12,320 --> 00:45:16,440
Speaker 4: Yeah, yeah, I do. I guess hardcore is a scale,

803
00:45:16,880 --> 00:45:22,000
Speaker 4: you know, I would say probably seventy five percent. There

804
00:45:22,000 --> 00:45:25,799
Speaker 4: are absolutely some that love deer and just ungulates, you know,

805
00:45:26,000 --> 00:45:28,280
Speaker 4: and study that type of stuff, that aren't big hunters.

806
00:45:28,640 --> 00:45:30,319
Speaker 4: But I would say on the white tail side, at

807
00:45:30,360 --> 00:45:32,040
Speaker 4: least the ones I'm thinking about off the top of

808
00:45:32,080 --> 00:45:33,279
Speaker 4: my head, they all hunt.

809
00:45:33,320 --> 00:45:35,399
Speaker 6: Until like that twenty five percent. You don't think those

810
00:45:35,440 --> 00:45:36,520
Speaker 6: folks hunt at all?

811
00:45:38,480 --> 00:45:42,200
Speaker 4: Probably not, okay. I think they're enamored with the deer

812
00:45:42,480 --> 00:45:47,000
Speaker 4: and ecology of it. The system really excites them. Yeah,

813
00:45:47,040 --> 00:45:49,040
Speaker 4: But then picking up our bow or rifle just in

814
00:45:49,200 --> 00:45:49,760
Speaker 4: their things.

815
00:45:49,600 --> 00:45:52,520
Speaker 6: And do you notice anything different with like those biologies? Yeah,

816
00:45:52,560 --> 00:45:54,080
Speaker 6: the questions okay.

817
00:45:53,840 --> 00:45:57,040
Speaker 4: The questions I asked typically that type of part and

818
00:45:57,080 --> 00:45:58,640
Speaker 4: this isn't good or bad, it's just different.

819
00:45:59,120 --> 00:46:01,799
Speaker 6: But I think it needs both, like the field needs

820
00:46:01,800 --> 00:46:02,239
Speaker 6: both of those.

821
00:46:02,320 --> 00:46:06,960
Speaker 4: Yeah, yeah, right. I would say they're more the theory

822
00:46:07,800 --> 00:46:11,720
Speaker 4: type of stuff, which is really important ecological grounding in theory.

823
00:46:12,280 --> 00:46:15,279
Speaker 4: And then people like me is more about the application,

824
00:46:16,200 --> 00:46:19,280
Speaker 4: and you know, my roles extension. So then what's the application?

825
00:46:19,400 --> 00:46:21,279
Speaker 4: How do I tell people about it? What does it

826
00:46:21,320 --> 00:46:24,040
Speaker 4: mean to you for hunting? Your land or managing your land.

827
00:46:24,600 --> 00:46:27,520
Speaker 1: Yeah, I want to hit you with a bunch of

828
00:46:29,719 --> 00:46:31,680
Speaker 1: once we cover off on them. We sold this pretty

829
00:46:31,680 --> 00:46:34,560
Speaker 1: heavy on the moon thing. But let's let's put the

830
00:46:34,600 --> 00:46:36,399
Speaker 1: moon thing to bed. So I want to get into

831
00:46:36,440 --> 00:46:38,319
Speaker 1: other things that drive I want to get into other

832
00:46:38,360 --> 00:46:41,360
Speaker 1: things that drive changes of movement and other things about

833
00:46:42,200 --> 00:46:44,520
Speaker 1: Like you mentioned that different deer have different personalities. I'd

834
00:46:44,520 --> 00:46:46,640
Speaker 1: love to hear more about that. Let's close out on

835
00:46:46,680 --> 00:46:52,520
Speaker 1: this moon thing for a little bit out put some

836
00:46:52,640 --> 00:46:58,279
Speaker 1: numbers to us, or put some way of expressing the

837
00:46:59,600 --> 00:47:03,040
Speaker 1: how much which you can rule out and how much

838
00:47:03,080 --> 00:47:06,600
Speaker 1: could still be up for grabs. Meaning Mark thing is like, hey, listen,

839
00:47:07,640 --> 00:47:10,319
Speaker 1: if a buck comes out. If I'm watching a buck

840
00:47:10,680 --> 00:47:12,400
Speaker 1: and I can't catch him out in the daylight and

841
00:47:12,440 --> 00:47:15,640
Speaker 1: he comes out five minutes early because of the moonface,

842
00:47:15,760 --> 00:47:16,719
Speaker 1: that's a big deal to me.

843
00:47:17,440 --> 00:47:19,000
Speaker 3: Are they catching that in the research?

844
00:47:19,040 --> 00:47:21,600
Speaker 1: You know? That was his question, right, like, when they're

845
00:47:21,640 --> 00:47:25,680
Speaker 1: looking at these general things, like they generally don't change

846
00:47:25,680 --> 00:47:27,560
Speaker 1: their behavior. But he says, but let's say it's just

847
00:47:27,600 --> 00:47:33,080
Speaker 1: five minutes, right, That to me matters, Like when you

848
00:47:33,120 --> 00:47:35,480
Speaker 1: look at it, how like what degree of certainty are

849
00:47:35,480 --> 00:47:40,080
Speaker 1: you comfortable putting on that there is there isn't any

850
00:47:40,080 --> 00:47:41,920
Speaker 1: impact because you're always going to have guys that are like,

851
00:47:41,920 --> 00:47:44,400
Speaker 1: he doesn't know what he's talking about, yeah, yeah, or

852
00:47:44,440 --> 00:47:47,719
Speaker 1: he's not detecting what I'm seeing because I'm seeing things

853
00:47:47,719 --> 00:47:50,000
Speaker 1: at a micro scale and he's looking to macro.

854
00:47:50,719 --> 00:47:55,279
Speaker 4: And I don't ever think we can produce anything that's

855
00:47:55,320 --> 00:47:59,160
Speaker 4: going to affect that person. So when you get in

856
00:47:59,680 --> 00:48:01,880
Speaker 4: got feedback from people, and this was part when we

857
00:48:01,920 --> 00:48:05,680
Speaker 4: when we reached out initially doing this survey. We had

858
00:48:06,080 --> 00:48:08,880
Speaker 4: and I would call them the saddle bow hunter. I

859
00:48:08,920 --> 00:48:11,759
Speaker 4: mean they are just locked in. They they're trying to

860
00:48:11,840 --> 00:48:15,840
Speaker 4: hunt close to cover. And so if if that buck

861
00:48:15,960 --> 00:48:20,080
Speaker 4: is walking out thirty seconds earlier and five more steps,

862
00:48:20,120 --> 00:48:20,920
Speaker 4: I got a shot.

863
00:48:21,040 --> 00:48:21,320
Speaker 1: Yep.

864
00:48:22,960 --> 00:48:26,319
Speaker 4: So what we looked at is, of course, like we

865
00:48:26,400 --> 00:48:31,440
Speaker 4: explained earlier deviation from normal. We did eighty five different analyzes,

866
00:48:32,120 --> 00:48:35,840
Speaker 4: so we we made eighty five different comparisons of all

867
00:48:35,920 --> 00:48:39,960
Speaker 4: the different moon stuff you can put together. And the

868
00:48:39,960 --> 00:48:47,680
Speaker 4: the average response for bedding time deviations were less than

869
00:48:47,719 --> 00:48:50,840
Speaker 4: a minute. A couple of them were two or three minutes.

870
00:48:52,120 --> 00:48:55,399
Speaker 4: But and not to get too deep in the stats here,

871
00:48:56,040 --> 00:48:59,839
Speaker 4: when you run that many analyzes you're gonna you're gonna

872
00:48:59,880 --> 00:49:02,840
Speaker 4: hear your results are gonna follow a bell shaped curve.

873
00:49:04,200 --> 00:49:07,080
Speaker 4: You're gonna get some results that were positive. You're gonna

874
00:49:07,080 --> 00:49:11,200
Speaker 4: get some results that were negative. And so when you

875
00:49:11,280 --> 00:49:14,640
Speaker 4: look at the body of everything that we did, we

876
00:49:14,680 --> 00:49:17,319
Speaker 4: had a couple instances where the deer were on their

877
00:49:17,320 --> 00:49:22,000
Speaker 4: feet a few seconds earlier, maybe a minute earlier. We

878
00:49:22,080 --> 00:49:24,680
Speaker 4: had some results where they stayed in their bed a

879
00:49:24,719 --> 00:49:28,280
Speaker 4: few seconds or a minute longer. We had some results

880
00:49:28,360 --> 00:49:31,480
Speaker 4: where the yard per hour and so think about that.

881
00:49:31,560 --> 00:49:35,680
Speaker 4: Put that in your terms. My pace, one of my steps.

882
00:49:35,320 --> 00:49:35,840
Speaker 1: Is a yard.

883
00:49:37,200 --> 00:49:39,560
Speaker 4: And so when you talk about, yeah, we found a

884
00:49:39,560 --> 00:49:42,040
Speaker 4: big result on such and such a moon condition, they

885
00:49:42,040 --> 00:49:46,360
Speaker 4: were moving three yards per hour more. That's three steps

886
00:49:47,160 --> 00:49:52,359
Speaker 4: and one hour three steps. Now, if that motivates you,

887
00:49:52,480 --> 00:49:55,040
Speaker 4: and that does get back when I'm given this as

888
00:49:55,040 --> 00:49:57,360
Speaker 4: a seminar and people are ready to throw beer cans

889
00:49:57,360 --> 00:50:00,399
Speaker 4: and rotten tomatoes and all that stuff at me. If

890
00:50:00,400 --> 00:50:02,440
Speaker 4: it makes you feel good, man, if this is your

891
00:50:02,480 --> 00:50:08,240
Speaker 4: placebo effect, yeah, roll with it. If it instills more

892
00:50:08,360 --> 00:50:11,440
Speaker 4: confidence in you, that's such and such moon condition, and

893
00:50:11,480 --> 00:50:14,719
Speaker 4: I'm gonna be more alert and I'm gonna get to

894
00:50:14,760 --> 00:50:17,200
Speaker 4: the stand thirty minutes earlier, because this is a red

895
00:50:17,239 --> 00:50:20,600
Speaker 4: moon day. You know, then, by God, keep doing it

896
00:50:21,360 --> 00:50:23,880
Speaker 4: if it makes you happy, but the evidence does not

897
00:50:23,960 --> 00:50:24,480
Speaker 4: support it.

898
00:50:24,880 --> 00:50:28,240
Speaker 6: In college, I would get the field in Stream magazine

899
00:50:28,280 --> 00:50:30,279
Speaker 6: and they would always predict the rut, the best days

900
00:50:30,280 --> 00:50:32,200
Speaker 6: of the rut. And I think it was maybe a

901
00:50:32,280 --> 00:50:36,080
Speaker 6: sophomore and I had saw that, like, the best day

902
00:50:36,120 --> 00:50:37,920
Speaker 6: of the rut this year was on a Saturday. I

903
00:50:38,000 --> 00:50:41,520
Speaker 6: was available, So I did what you're talking about. I

904
00:50:41,600 --> 00:50:43,640
Speaker 6: sat in my best stand that day that I had

905
00:50:43,680 --> 00:50:45,800
Speaker 6: saved for a week leading up to it because I

906
00:50:46,120 --> 00:50:47,799
Speaker 6: knew it was the best day of the rut. I

907
00:50:47,840 --> 00:50:50,399
Speaker 6: got there earlier, I packed lunch to be there all day.

908
00:50:50,480 --> 00:50:52,479
Speaker 6: I was more alert because I was like, it's going

909
00:50:52,560 --> 00:50:54,840
Speaker 6: to happen. And then a buck showed up and the

910
00:50:55,000 --> 00:50:57,360
Speaker 6: killed him, and so I was just more confidence and

911
00:50:57,400 --> 00:51:00,320
Speaker 6: I was a better hunter. That day was going to

912
00:51:01,400 --> 00:51:05,120
Speaker 6: optimistic and so that that I think that that can

913
00:51:05,160 --> 00:51:05,840
Speaker 6: work for people.

914
00:51:05,840 --> 00:51:08,799
Speaker 4: That can be a thing, and keep doing it. If

915
00:51:08,840 --> 00:51:12,080
Speaker 4: it keeps working for you, keep doing it, keep taking

916
00:51:12,120 --> 00:51:16,120
Speaker 4: the placebo. Placebo effect is really really powerful. There's some

917
00:51:16,160 --> 00:51:19,160
Speaker 4: cool science behind that as well. Sure, but yeah, you

918
00:51:19,160 --> 00:51:21,440
Speaker 4: took the words out of my mouth. But I wonder

919
00:51:21,560 --> 00:51:25,080
Speaker 4: if you had gone five additional times under those exact

920
00:51:25,080 --> 00:51:27,520
Speaker 4: same conditions and you didn't have a good day.

921
00:51:27,520 --> 00:51:30,360
Speaker 6: Totally, if you remember the good ones, then I was like,

922
00:51:30,440 --> 00:51:32,399
Speaker 6: it was because this was the best day of the rut,

923
00:51:32,400 --> 00:51:35,760
Speaker 6: as Field and Stream had deemed it. You know, looking

924
00:51:35,800 --> 00:51:38,160
Speaker 6: back now and since I've like formed my own white

925
00:51:38,160 --> 00:51:41,800
Speaker 6: tail opinions, I recognized I was just very confident that day.

926
00:51:41,760 --> 00:51:43,520
Speaker 4: And Field and that was throughout the range of the

927
00:51:43,560 --> 00:51:44,279
Speaker 4: white tailed deer.

928
00:51:44,440 --> 00:51:45,920
Speaker 1: Yeah, but this was going to be the day.

929
00:51:46,080 --> 00:51:52,359
Speaker 6: Yeah, yep, yeah, so that should totally. I got one

930
00:51:52,360 --> 00:51:55,080
Speaker 6: more moon question before we move on. Charles Allsheimer he

931
00:51:55,200 --> 00:51:58,840
Speaker 6: had developed like the rutting moon theory in the nineties

932
00:51:58,840 --> 00:52:00,480
Speaker 6: that caught on with a lot of guys, and the

933
00:52:00,560 --> 00:52:04,040
Speaker 6: running moon theory is that the second full moon after

934
00:52:04,080 --> 00:52:07,560
Speaker 6: the autumn equinox is what triggers the white tail rut.

935
00:52:07,680 --> 00:52:10,759
Speaker 6: That's like, this is the beginning of it. And in

936
00:52:10,800 --> 00:52:13,200
Speaker 6: his theory he had determined there are three types of

937
00:52:13,239 --> 00:52:15,160
Speaker 6: white tail ruts. You could have it a given year

938
00:52:15,239 --> 00:52:16,880
Speaker 6: based on when that second.

939
00:52:16,640 --> 00:52:18,640
Speaker 1: Moon fo Okay, bag, I want to make sure I'm

940
00:52:18,680 --> 00:52:21,880
Speaker 1: tracking autumn equin second full.

941
00:52:21,719 --> 00:52:23,879
Speaker 6: Moon, right, not the first one, the second one.

942
00:52:24,000 --> 00:52:25,879
Speaker 1: When I got that part, but then you said another

943
00:52:25,960 --> 00:52:26,799
Speaker 1: thing that threw me off.

944
00:52:26,840 --> 00:52:29,839
Speaker 6: So that that second full moon could land in late October,

945
00:52:29,960 --> 00:52:32,959
Speaker 6: it could land in mid November, okay, based on when

946
00:52:33,000 --> 00:52:36,200
Speaker 6: that would fall. You could have one of three ruts.

947
00:52:36,440 --> 00:52:39,440
Speaker 6: You could have a synchronized rut, which is if it's

948
00:52:39,480 --> 00:52:43,359
Speaker 6: between like October thirty one and November five. You could

949
00:52:43,360 --> 00:52:47,200
Speaker 6: have a classic rut, which is like November six to thirteen,

950
00:52:47,719 --> 00:52:50,560
Speaker 6: or you could have a trickle rut, which is November

951
00:52:50,600 --> 00:52:51,200
Speaker 6: thirteen on.

952
00:52:51,520 --> 00:52:51,800
Speaker 1: Huh.

953
00:52:51,960 --> 00:52:55,680
Speaker 6: And it's it's basically saying that like some years, if

954
00:52:55,719 --> 00:52:58,919
Speaker 6: you have a trickle rut, for example, maybe that Bell

955
00:52:59,000 --> 00:53:01,560
Speaker 6: curve you're talking about is flat at the top and

956
00:53:01,600 --> 00:53:05,760
Speaker 6: it's just wider, Whereas if you have a synchronized rut

957
00:53:06,120 --> 00:53:09,480
Speaker 6: where you get that full moon on November third, now

958
00:53:09,480 --> 00:53:11,879
Speaker 6: the Bell curve has a really tall peak in it,

959
00:53:12,000 --> 00:53:15,000
Speaker 6: and it's skinnier. Is that anything you've ever seen that

960
00:53:15,160 --> 00:53:17,960
Speaker 6: some years the rut was longer or shorter.

961
00:53:18,680 --> 00:53:24,640
Speaker 1: No, no, no, never even outside of the moon, like

962
00:53:24,800 --> 00:53:25,600
Speaker 1: never mind the moon.

963
00:53:26,200 --> 00:53:29,880
Speaker 4: Yeah, not from from year to year in a place.

964
00:53:30,040 --> 00:53:33,800
Speaker 4: And so when you talk about a you know, a

965
00:53:33,840 --> 00:53:37,360
Speaker 4: protracted rut or a trickle rut. All that stuff is

966
00:53:37,680 --> 00:53:41,080
Speaker 4: related to sex ratio of the population, so we can

967
00:53:41,200 --> 00:53:45,200
Speaker 4: manipulate that with management. Here it has nothing to do

968
00:53:45,520 --> 00:53:50,040
Speaker 4: with the moon. It is about the availability of dozen

969
00:53:50,280 --> 00:53:54,200
Speaker 4: estres and enough box to serve them when they are

970
00:53:54,200 --> 00:53:58,160
Speaker 4: in standing heat. If your sex ratio becomes so biased

971
00:53:58,200 --> 00:54:01,080
Speaker 4: that the dozen estres there is not a buck to

972
00:54:01,640 --> 00:54:05,520
Speaker 4: copulate twenty eight later days later, she's going to cycle

973
00:54:05,600 --> 00:54:08,360
Speaker 4: and come into heat again, and there is your trickle

974
00:54:08,480 --> 00:54:13,000
Speaker 4: or your extended rut. Or if you have dough fawns,

975
00:54:13,360 --> 00:54:16,560
Speaker 4: dough fawnts will typically the proportion of them that do

976
00:54:16,640 --> 00:54:19,080
Speaker 4: come into estres are going to come in a little

977
00:54:19,080 --> 00:54:19,640
Speaker 4: bit later.

978
00:54:20,200 --> 00:54:25,360
Speaker 1: So adult adult that has a faun with her and

979
00:54:25,360 --> 00:54:27,080
Speaker 1: she's trying to get rid of it in the fall,

980
00:54:27,680 --> 00:54:30,640
Speaker 1: she'll come into estris later than adult that did that

981
00:54:30,719 --> 00:54:32,000
Speaker 1: didn't was not carrying a faun.

982
00:54:32,320 --> 00:54:36,600
Speaker 4: I'm sorry, I misspoke, though, uh not everywhere. This varies

983
00:54:36,760 --> 00:54:39,560
Speaker 4: depending on where you're at in the US. In Mississippi,

984
00:54:39,560 --> 00:54:43,560
Speaker 4: for example, ten to fifteen percent of dough faunds or

985
00:54:43,680 --> 00:54:47,040
Speaker 4: do funds will reach sufficient body size and condition to

986
00:54:47,200 --> 00:54:49,680
Speaker 4: come into heat. They're never going to come in at

987
00:54:49,680 --> 00:54:52,880
Speaker 4: the peak of the rut, it'll be two three weeks

988
00:54:52,920 --> 00:54:56,960
Speaker 4: a month later by the time they've reached physiological condition

989
00:54:57,000 --> 00:54:58,320
Speaker 4: where they can come into estras.

990
00:54:58,320 --> 00:55:00,239
Speaker 1: Got it, so that we'll be part of it, and

991
00:55:00,280 --> 00:55:02,280
Speaker 1: that can drive a little late rut action.

992
00:55:02,480 --> 00:55:03,240
Speaker 4: That's your trickle.

993
00:55:03,680 --> 00:55:06,560
Speaker 6: If you do believe in the rutting moon. This year

994
00:55:06,640 --> 00:55:09,799
Speaker 6: twenty twenty five, it is November fifth, so you're you're

995
00:55:09,920 --> 00:55:14,200
Speaker 6: like straddling a synchronized rut and a classic rut, meaning

996
00:55:14,239 --> 00:55:15,759
Speaker 6: that like November five to ten.

997
00:55:15,880 --> 00:55:16,480
Speaker 2: Period.

998
00:55:16,480 --> 00:55:20,920
Speaker 4: Wow, it's gonna be November five to ten. All right,

999
00:55:20,960 --> 00:55:22,000
Speaker 4: let's back it up like those.

1000
00:55:23,280 --> 00:55:24,880
Speaker 6: To be clear, I don't believe in this either. I

1001
00:55:24,920 --> 00:55:27,960
Speaker 6: just love that, but I throw out this thing because

1002
00:55:27,960 --> 00:55:28,440
Speaker 6: some people do.

1003
00:55:28,520 --> 00:55:31,200
Speaker 1: But then he and then he, he says that's not right,

1004
00:55:31,239 --> 00:55:33,200
Speaker 1: and then you alert everybody what day.

1005
00:55:33,080 --> 00:55:36,480
Speaker 6: To be Because because I love that people do believe it.

1006
00:55:36,520 --> 00:55:39,040
Speaker 6: I really appreciate that those folks have taken the time

1007
00:55:39,120 --> 00:55:42,480
Speaker 6: to develop a theory and to spread that theory around.

1008
00:55:42,719 --> 00:55:45,480
Speaker 2: Reason you have bigfoot experts on radio the other day.

1009
00:55:45,480 --> 00:55:49,880
Speaker 7: Exactly, we need a new believer hat it's not just

1010
00:55:49,920 --> 00:55:51,120
Speaker 7: the black bucket of moon.

1011
00:55:51,280 --> 00:55:53,240
Speaker 1: Yeah, exactly, that's great idea.

1012
00:55:53,400 --> 00:55:56,560
Speaker 3: Oh, core full moon buck, That says believer.

1013
00:55:58,680 --> 00:56:04,520
Speaker 4: What's the purpose of the timing of the ruts when

1014
00:56:04,640 --> 00:56:08,160
Speaker 4: the fawns will hit the ground in spring? Yeah? Yeah,

1015
00:56:08,880 --> 00:56:13,640
Speaker 4: Why would mother nature? Why would evolution have that affected

1016
00:56:13,719 --> 00:56:18,960
Speaker 4: by some moon. So the most reliable clock, of course,

1017
00:56:19,120 --> 00:56:23,239
Speaker 4: is photo period. They can be calibrated so well, and

1018
00:56:23,280 --> 00:56:27,359
Speaker 4: so it's so important over time of when the dough

1019
00:56:27,400 --> 00:56:29,879
Speaker 4: needs to be bred seven months later, when that fawn

1020
00:56:30,000 --> 00:56:30,359
Speaker 4: is going.

1021
00:56:30,280 --> 00:56:30,920
Speaker 2: To be dropped.

1022
00:56:32,000 --> 00:56:35,520
Speaker 4: Why would evolution fold in any of the moon stuff

1023
00:56:35,560 --> 00:56:39,399
Speaker 4: to tinker with that at all, I mean, biologically or ecologically.

1024
00:56:39,400 --> 00:56:44,439
Speaker 4: That just doesn't make sense. However, we did test this,

1025
00:56:45,480 --> 00:56:47,120
Speaker 4: and so we did it two ways. We did it

1026
00:56:47,160 --> 00:56:49,560
Speaker 4: at an individual scale and we did it at a

1027
00:56:49,600 --> 00:56:55,080
Speaker 4: population scale, individual scale with our captive deer herd. We

1028
00:56:55,200 --> 00:57:00,920
Speaker 4: looked at records of estrus and copulation for all of

1029
00:57:00,960 --> 00:57:04,280
Speaker 4: our does so population of doze over many, many, many years,

1030
00:57:04,320 --> 00:57:06,800
Speaker 4: and so we know when they were coming into heat,

1031
00:57:07,080 --> 00:57:08,680
Speaker 4: and we knew when they were bred. So we have

1032
00:57:08,760 --> 00:57:13,759
Speaker 4: those records. We then line that up with this rutting moon.

1033
00:57:14,440 --> 00:57:16,840
Speaker 4: And so every year you know that rutting moon is

1034
00:57:16,960 --> 00:57:19,840
Speaker 4: moving back and forth a week or fifteen days or whatever.

1035
00:57:20,240 --> 00:57:23,320
Speaker 4: And so we should have seen if it was influencing

1036
00:57:23,400 --> 00:57:25,800
Speaker 4: when they are coming into estrus, we should have seen

1037
00:57:25,840 --> 00:57:28,520
Speaker 4: them moving towards that or moving back.

1038
00:57:29,320 --> 00:57:30,680
Speaker 6: Zero.

1039
00:57:30,960 --> 00:57:34,640
Speaker 4: We then go to let's go to wild populations, and

1040
00:57:34,720 --> 00:57:37,920
Speaker 4: we looked at wildlife management areas and our state Wildlife

1041
00:57:37,960 --> 00:57:41,280
Speaker 4: Agency is very good at doing what is called spring

1042
00:57:41,440 --> 00:57:45,960
Speaker 4: health checks. What that does is they harvest doze post

1043
00:57:46,000 --> 00:57:49,360
Speaker 4: deer season, typically March, and they will look at the

1044
00:57:49,400 --> 00:57:52,880
Speaker 4: condition of dose and then also look at the number

1045
00:57:52,880 --> 00:57:55,880
Speaker 4: of fetuses that they are carrying. So along with all

1046
00:57:55,960 --> 00:57:58,760
Speaker 4: the general hunter harvest data, that is a way for

1047
00:57:58,800 --> 00:58:02,520
Speaker 4: them to look at what's the condition of this population statewide,

1048
00:58:02,600 --> 00:58:05,080
Speaker 4: so forth. So we know where the rut is in

1049
00:58:05,200 --> 00:58:07,120
Speaker 4: all these places, we know where the peak of the

1050
00:58:07,200 --> 00:58:09,960
Speaker 4: rut is, and so we then line that up with

1051
00:58:10,480 --> 00:58:16,960
Speaker 4: the rutting moon zero no effect whatsoever. So individually population

1052
00:58:17,120 --> 00:58:20,680
Speaker 4: wise logic, Yeah, doesn't make sense to.

1053
00:58:20,640 --> 00:58:22,479
Speaker 6: Me because of the Mississippi deer.

1054
00:58:23,160 --> 00:58:26,520
Speaker 4: That's why maybe it's just those Mississippi deer.

1055
00:58:27,440 --> 00:58:31,440
Speaker 2: Would it be worth just taking five minutes to tabrons

1056
00:58:31,440 --> 00:58:35,160
Speaker 2: and explain what confirmation bias is and how that shows

1057
00:58:35,280 --> 00:58:37,200
Speaker 2: up in hunters?

1058
00:58:38,480 --> 00:58:38,760
Speaker 1: Sure?

1059
00:58:39,320 --> 00:58:39,800
Speaker 2: I think so?

1060
00:58:40,160 --> 00:58:44,320
Speaker 1: Yeah. My favorite analogy about this is you go, I

1061
00:58:44,360 --> 00:58:46,400
Speaker 1: don't know, surprise analogy, Like you go out and you

1062
00:58:46,480 --> 00:58:49,920
Speaker 1: fishing small mouths and you're throwing shar troops and you

1063
00:58:49,920 --> 00:58:52,560
Speaker 1: get a bunch, You're hitting them real good. Then at

1064
00:58:52,600 --> 00:58:55,560
Speaker 1: one minute you throw on a pumpkin colored jig and

1065
00:58:55,560 --> 00:58:57,320
Speaker 1: you're fishing for a couple of seconds, you don't get

1066
00:58:57,320 --> 00:59:00,280
Speaker 1: a hit. You put shar truce back on lo and

1067
00:59:00,280 --> 00:59:02,840
Speaker 1: behold throughout the day you keep catching fish. They were

1068
00:59:02,840 --> 00:59:06,360
Speaker 1: coming on hartreuse. Yeah, yeah, yeah, And like there's something

1069
00:59:06,400 --> 00:59:09,600
Speaker 1: to that, because you know, ain't shartruths. It ain't no use.

1070
00:59:09,680 --> 00:59:12,120
Speaker 1: But I'm saying like you do have a way of

1071
00:59:12,360 --> 00:59:14,680
Speaker 1: you know, like if you were going to go design

1072
00:59:14,760 --> 00:59:18,160
Speaker 1: a study about what color small mouth bass are hitting

1073
00:59:18,160 --> 00:59:19,960
Speaker 1: on in some given day, it wouldn't be like that,

1074
00:59:21,120 --> 00:59:24,680
Speaker 1: you know. Yeah. So I think that you find part

1075
00:59:24,720 --> 00:59:27,760
Speaker 1: of the fun. You find patterns and things, and and

1076
00:59:28,640 --> 00:59:33,160
Speaker 1: you know that works for me. Therefore that's what that's

1077
00:59:33,200 --> 00:59:34,080
Speaker 1: dictated by.

1078
00:59:34,000 --> 00:59:39,000
Speaker 4: Nature, right, Yeah, Well that's a that's a deeper question.

1079
00:59:39,080 --> 00:59:41,439
Speaker 4: I mean, that would be a psychologist to get into

1080
00:59:41,480 --> 00:59:44,040
Speaker 4: all the logical fallacies and how the brain works with that.

1081
00:59:44,160 --> 00:59:46,360
Speaker 4: But I guess the way I think about it, is

1082
00:59:47,560 --> 00:59:50,560
Speaker 4: we're we're really good as human beings. We want to

1083
00:59:50,560 --> 00:59:53,840
Speaker 4: find patterns, so we're trying to find the shortcut. We're

1084
00:59:53,880 --> 00:59:57,280
Speaker 4: really good that that's helped us, that's helped human beings

1085
00:59:57,600 --> 00:59:59,640
Speaker 4: to be able to link those things together, and that's

1086
00:59:59,680 --> 01:00:03,920
Speaker 4: the path. Let's capitalize on it. But the problem that

1087
01:00:04,120 --> 01:00:08,560
Speaker 4: we have is we become enamored with this linkage that

1088
01:00:08,600 --> 01:00:13,040
Speaker 4: we have made between these two things. A leads to B,

1089
01:00:13,040 --> 01:00:18,440
Speaker 4: B leads to C, and we will start ignoring contrary evidence.

1090
01:00:18,480 --> 01:00:23,840
Speaker 4: So it's like we become bought in and emotionally invested

1091
01:00:23,920 --> 01:00:26,760
Speaker 4: in our and hey, in science, it's it's called the

1092
01:00:26,800 --> 01:00:30,400
Speaker 4: pet hypothesis. That's why we have to get outside peer review.

1093
01:00:30,440 --> 01:00:32,440
Speaker 4: That's why you got to talk to a buddy, help me,

1094
01:00:32,680 --> 01:00:36,120
Speaker 4: help me think about this. I'm really locked in confirmation

1095
01:00:36,280 --> 01:00:40,040
Speaker 4: bias could be bothering me here. But but I think

1096
01:00:40,080 --> 01:00:43,680
Speaker 4: that is always going on. Is we we never remember

1097
01:00:43,760 --> 01:00:49,080
Speaker 4: the times we were unsuccessful. We disproportionately remember the times

1098
01:00:49,120 --> 01:00:50,520
Speaker 4: that we were mm hm.

1099
01:00:53,000 --> 01:00:56,040
Speaker 2: And I think if we if you are a moon believer,

1100
01:00:57,280 --> 01:01:00,960
Speaker 2: you only go hunt in those conditions where you mostly

1101
01:01:01,040 --> 01:01:04,720
Speaker 2: hunt those conditions that you think are you know, positively

1102
01:01:04,760 --> 01:01:07,560
Speaker 2: affect your deer hunting. You're not hunting the other days,

1103
01:01:08,160 --> 01:01:12,040
Speaker 2: and so you only have a data set from those days. Yeah,

1104
01:01:12,280 --> 01:01:14,200
Speaker 2: and it could be exactly the same from the days

1105
01:01:14,200 --> 01:01:16,120
Speaker 2: that the moon is doing something completely different.

1106
01:01:16,600 --> 01:01:19,760
Speaker 4: Yeah. And you may be a good enough hunter, and

1107
01:01:19,800 --> 01:01:22,360
Speaker 4: you may be hunting in a enough of a target

1108
01:01:22,440 --> 01:01:25,280
Speaker 4: rich environment where every day you go, you were going

1109
01:01:25,360 --> 01:01:28,280
Speaker 4: to see deer if that's your metric for success, but

1110
01:01:28,320 --> 01:01:30,720
Speaker 4: you're only going to go on those special days, and

1111
01:01:30,760 --> 01:01:35,360
Speaker 4: then that just keeps reinforcing that this moon condition or

1112
01:01:35,360 --> 01:01:39,120
Speaker 4: weather condition or whatever was the reason for my success.

1113
01:01:39,760 --> 01:01:42,720
Speaker 4: When the way to do it would be, and nobody's

1114
01:01:42,720 --> 01:01:45,960
Speaker 4: gonna do this. I'm going to get a random number generator,

1115
01:01:46,040 --> 01:01:47,920
Speaker 4: and I'm going to get a calendar, and I'm going

1116
01:01:47,960 --> 01:01:51,040
Speaker 4: to pick out these particular days and I'm gonna go hunt.

1117
01:01:51,400 --> 01:01:52,360
Speaker 6: That's a fun study.

1118
01:01:52,600 --> 01:01:58,160
Speaker 4: And or look at camera data. Yeah, that'd be another way.

1119
01:01:58,400 --> 01:02:00,800
Speaker 4: Just record camera data all the time and go back

1120
01:02:00,800 --> 01:02:03,439
Speaker 4: and look at it.

1121
01:02:03,520 --> 01:02:04,200
Speaker 1: This is about the moon.

1122
01:02:04,720 --> 01:02:09,200
Speaker 6: It's it's sort of Bloomberg had an article that bigfoot

1123
01:02:09,240 --> 01:02:12,160
Speaker 6: sightings have decreased in the last decade. They peaked around

1124
01:02:12,240 --> 01:02:14,640
Speaker 6: like two thousand and four or so, and they've been

1125
01:02:14,680 --> 01:02:19,680
Speaker 6: going down ever since. If deer hunters were like very

1126
01:02:19,720 --> 01:02:23,120
Speaker 6: conscious of what their trail cameras are telling them. Now

1127
01:02:23,120 --> 01:02:26,120
Speaker 6: that trail cameras are so effective and so cheap and

1128
01:02:26,480 --> 01:02:30,600
Speaker 6: sell cams are very available, I feel like the same

1129
01:02:30,640 --> 01:02:33,440
Speaker 6: thing would happen that if you pulled deer hunters in

1130
01:02:33,480 --> 01:02:36,400
Speaker 6: twenty years from now, it wouldn't be eighty three percent anymore.

1131
01:02:36,600 --> 01:02:37,520
Speaker 1: Yeah, it would be.

1132
01:02:37,480 --> 01:02:41,000
Speaker 6: Lower because they if they were trying to like really

1133
01:02:41,000 --> 01:02:43,280
Speaker 6: pay attention, they would maybe notice it. Oh yeah, the

1134
01:02:43,280 --> 01:02:46,440
Speaker 6: moon isn't saying that that the deer movement is different

1135
01:02:46,800 --> 01:02:48,080
Speaker 6: based on what the moon is doing.

1136
01:02:48,640 --> 01:02:51,720
Speaker 4: Yeah, I agree. I just think it's gonna take a

1137
01:02:51,800 --> 01:02:56,479
Speaker 4: long time because it's really difficult to let go right

1138
01:02:56,800 --> 01:03:01,720
Speaker 4: with that belief, especially if within your little group, you're

1139
01:03:01,760 --> 01:03:06,360
Speaker 4: you're the older, wiser, you're the influencer. The single most

1140
01:03:06,360 --> 01:03:10,240
Speaker 4: difficult thing for a human being to say publicly, I

1141
01:03:10,360 --> 01:03:10,760
Speaker 4: was wrong.

1142
01:03:11,600 --> 01:03:12,000
Speaker 1: Mm hmm.

1143
01:03:12,200 --> 01:03:15,240
Speaker 4: I mean, that's that's real. That's very powerful. It's so

1144
01:03:15,360 --> 01:03:18,080
Speaker 4: difficult to stand up and go forgive me, I was wrong.

1145
01:03:18,120 --> 01:03:21,360
Speaker 4: I made a big mistake. People are very reluctant.

1146
01:03:20,920 --> 01:03:22,960
Speaker 1: To do that. I'm going to hit you with a

1147
01:03:23,000 --> 01:03:25,439
Speaker 1: real I want to bring something up, but I don't

1148
01:03:25,440 --> 01:03:30,760
Speaker 1: want to dwell on it. What's your take on? How

1149
01:03:30,760 --> 01:03:35,000
Speaker 1: do I even ask this man? I'm trying to figure out.

1150
01:03:34,040 --> 01:03:35,840
Speaker 2: He's just saying he wants a real concise ance.

1151
01:03:35,880 --> 01:03:37,520
Speaker 1: I don't want to get into it. I'm just curious

1152
01:03:37,560 --> 01:03:40,240
Speaker 1: because you're a big deer guy. Do your hunter deer researcher,

1153
01:03:41,480 --> 01:03:44,200
Speaker 1: give me, give me your basic like one sentence, what's

1154
01:03:44,240 --> 01:03:45,640
Speaker 1: your basic take on CWD?

1155
01:03:46,400 --> 01:03:55,440
Speaker 4: It's it's real, it's it's the single biggest challenge I

1156
01:03:55,520 --> 01:04:00,480
Speaker 4: believe to deer management and the application of science ants

1157
01:04:01,000 --> 01:04:08,000
Speaker 4: while simultaneously keeping hunters engaged and believing in science. That

1158
01:04:08,120 --> 01:04:12,040
Speaker 4: wasn't very concise, but that's that's the way. It's the

1159
01:04:12,160 --> 01:04:13,400
Speaker 4: challenge of our time.

1160
01:04:13,520 --> 01:04:16,680
Speaker 3: You think it's you believe it's a legitimate threat at.

1161
01:04:16,560 --> 01:04:17,440
Speaker 1: A herd level.

1162
01:04:17,640 --> 01:04:20,160
Speaker 4: Yes, yes, yes I do.

1163
01:04:21,840 --> 01:04:25,880
Speaker 3: Earlier you mentioned different buck personalities?

1164
01:04:26,600 --> 01:04:29,840
Speaker 1: Are there? Is it? Is it possible to give like

1165
01:04:29,880 --> 01:04:32,240
Speaker 1: a handful of buck personality types?

1166
01:04:33,480 --> 01:04:34,720
Speaker 4: Yeah?

1167
01:04:35,400 --> 01:04:37,000
Speaker 1: And have you heard of a shirker buck?

1168
01:04:38,480 --> 01:04:38,960
Speaker 4: I have not.

1169
01:04:39,840 --> 01:04:42,040
Speaker 1: Okay, go on, okay, different.

1170
01:04:41,680 --> 01:04:44,600
Speaker 2: Buck we'll come back to We'll come back to that.

1171
01:04:46,600 --> 01:04:51,800
Speaker 4: You never heard of a shirker I'm not recalling val geist, Oh,

1172
01:04:51,880 --> 01:04:56,720
Speaker 4: val Geist I have heard of that word, but man,

1173
01:04:56,840 --> 01:04:59,000
Speaker 4: I'm drawing a blank on.

1174
01:04:58,600 --> 01:05:00,000
Speaker 3: We'll come around to it.

1175
01:05:00,240 --> 01:05:02,360
Speaker 1: Do give me some buck personality types.

1176
01:05:02,120 --> 01:05:07,320
Speaker 4: Buck personalities, Well, it's just two from what we categorize.

1177
01:05:07,600 --> 01:05:11,440
Speaker 4: This is just relative. We call it buck movement behavior.

1178
01:05:11,520 --> 01:05:12,600
Speaker 3: Yeah, that's what I'm getting at.

1179
01:05:12,640 --> 01:05:14,080
Speaker 1: Yeah, I don't mean like what they're thinking about. I

1180
01:05:14,080 --> 01:05:17,200
Speaker 1: mean what they're like personality types in a way that

1181
01:05:17,240 --> 01:05:19,000
Speaker 1: would impact the hunter's experience.

1182
01:05:19,080 --> 01:05:23,920
Speaker 4: Yeah, so that we call it a sedentary type that's

1183
01:05:23,920 --> 01:05:28,120
Speaker 4: gonna be your introvert, and then your mobile personality type

1184
01:05:28,160 --> 01:05:31,520
Speaker 4: that's gonna be your extrovert. Uh. The what people thought

1185
01:05:31,560 --> 01:05:33,680
Speaker 4: for the longest time, until we had the type of

1186
01:05:33,680 --> 01:05:37,360
Speaker 4: instrumentation to be able to see this, was that after

1187
01:05:37,520 --> 01:05:39,960
Speaker 4: yearling buck dispersal, a buck is going to go set

1188
01:05:40,040 --> 01:05:42,919
Speaker 4: up and have his home range, and that is where

1189
01:05:42,960 --> 01:05:44,640
Speaker 4: it's going to be. Now, the size of that home

1190
01:05:44,760 --> 01:05:48,240
Speaker 4: range can vary by resources. He may be a five

1191
01:05:48,360 --> 01:05:51,040
Speaker 4: hundred acre home range guy, he may be a fifteen

1192
01:05:51,160 --> 01:05:54,280
Speaker 4: hundred acre home range guy. But that is where he

1193
01:05:54,440 --> 01:05:58,400
Speaker 4: is essentially going to live and die is in that

1194
01:05:58,400 --> 01:06:03,040
Speaker 4: that fixed home range. What we found is that about

1195
01:06:03,080 --> 01:06:10,280
Speaker 4: thirty percent of our bucks have completely disconnected and disjointed

1196
01:06:10,800 --> 01:06:14,919
Speaker 4: home ranges, and so they will spend six, seven, eight

1197
01:06:15,000 --> 01:06:18,720
Speaker 4: months and one location, and then they will get up

1198
01:06:18,760 --> 01:06:21,960
Speaker 4: and move to a completely different location.

1199
01:06:21,800 --> 01:06:23,080
Speaker 3: Just forget about the old spot.

1200
01:06:23,800 --> 01:06:24,280
Speaker 4: That's right.

1201
01:06:24,680 --> 01:06:25,160
Speaker 1: That's right.

1202
01:06:25,760 --> 01:06:29,960
Speaker 4: The most sensational example, just to show you that intrinsically

1203
01:06:30,080 --> 01:06:33,120
Speaker 4: in some deer, this is in them that they are

1204
01:06:33,320 --> 01:06:37,360
Speaker 4: going to do it. We call her a buck. In

1205
01:06:37,440 --> 01:06:43,439
Speaker 4: Mississippi fall winter, and we started noticing really strange long

1206
01:06:43,480 --> 01:06:47,040
Speaker 4: distance behavior about February so in Mississippi, so we're on

1207
01:06:47,080 --> 01:06:49,720
Speaker 4: the east side of the Mississippi River. He goes all

1208
01:06:49,800 --> 01:06:53,000
Speaker 4: the way to the Mississippi River miles and miles of miles,

1209
01:06:53,760 --> 01:06:56,880
Speaker 4: and then paces up and down the river for a

1210
01:06:56,960 --> 01:07:00,880
Speaker 4: few days, and then crosses the river and then sets

1211
01:07:00,920 --> 01:07:07,600
Speaker 4: up camp in Louisiana for essentially all summer. August rolls around.

1212
01:07:07,880 --> 01:07:10,960
Speaker 4: He does the same thing. On the Louisiana side. He

1213
01:07:11,040 --> 01:07:13,440
Speaker 4: goes stages by the river a day or two, getting

1214
01:07:13,480 --> 01:07:17,040
Speaker 4: up his nerve, maybe swims the river, comes back to

1215
01:07:17,040 --> 01:07:20,400
Speaker 4: Mississippi to that exact same home range he was the

1216
01:07:20,480 --> 01:07:23,880
Speaker 4: year before. Did that two years in a row, so

1217
01:07:23,960 --> 01:07:28,240
Speaker 4: we had four instances of him taking that long distance

1218
01:07:28,360 --> 01:07:33,600
Speaker 4: movement and crossing the Mississippi River. So that's an extreme

1219
01:07:33,680 --> 01:07:38,040
Speaker 4: example of a mobile personality. And just the way the

1220
01:07:38,200 --> 01:07:41,840
Speaker 4: crow flies distance it was just shy twenty miles wow,

1221
01:07:41,880 --> 01:07:44,200
Speaker 4: so his route was a lot more than that.

1222
01:07:44,400 --> 01:07:46,439
Speaker 1: Yeah, And it's like you could see him doing it once, right,

1223
01:07:47,240 --> 01:07:49,240
Speaker 1: and then he has a good experience or doesn't have

1224
01:07:49,240 --> 01:07:52,840
Speaker 1: a good experience, but the fact that he he goes

1225
01:07:52,880 --> 01:07:55,480
Speaker 1: back to Mississippi. Then a while later he wants to

1226
01:07:56,400 --> 01:08:00,000
Speaker 1: you know what I mean, yeah, like repeat it where yeah,

1227
01:08:00,280 --> 01:08:03,440
Speaker 1: just felt or we wind up thinking that it's a

1228
01:08:03,440 --> 01:08:07,520
Speaker 1: bigger deal, that that swim is a bigger deal than

1229
01:08:07,520 --> 01:08:10,120
Speaker 1: he regards it as. Right, I was reading this thing

1230
01:08:10,160 --> 01:08:11,760
Speaker 1: like these guys were looking at it. There used to

1231
01:08:11,760 --> 01:08:13,400
Speaker 1: be this thing that links. They used to think that

1232
01:08:13,440 --> 01:08:15,640
Speaker 1: links didn't like cross big rivers, and they thought these

1233
01:08:15,680 --> 01:08:19,000
Speaker 1: big rivers were boxed in links home ranges. So they

1234
01:08:19,080 --> 01:08:21,600
Speaker 1: had these links with collars were swimming the tan and

1235
01:08:21,680 --> 01:08:25,960
Speaker 1: awe swimming the Yukon, you know, mm hmm. And people

1236
01:08:26,000 --> 01:08:28,200
Speaker 1: always saw it just they had just figured that that's

1237
01:08:28,240 --> 01:08:31,760
Speaker 1: a border to a lynx's habitat. That's some bit just yeah,

1238
01:08:31,840 --> 01:08:33,760
Speaker 1: right across it, shoot across. You don't even think about it,

1239
01:08:33,760 --> 01:08:36,000
Speaker 1: and in the human mind, you're like, oh, that would

1240
01:08:36,040 --> 01:08:38,280
Speaker 1: be a he can't get across that. He wouldn't want

1241
01:08:38,280 --> 01:08:39,720
Speaker 1: to cross that a cat, you know.

1242
01:08:40,200 --> 01:08:42,960
Speaker 4: And yet we had some bucks that, uh in this

1243
01:08:43,040 --> 01:08:45,920
Speaker 4: one in the Mississippi River. We're talking about a normal river,

1244
01:08:46,040 --> 01:08:49,639
Speaker 4: so think think a river that's fifty yards across or something.

1245
01:08:50,320 --> 01:08:52,960
Speaker 4: We had some bucks that would go across that every

1246
01:08:53,040 --> 01:08:56,920
Speaker 4: single day. Was not an impediment to them whatsoever. We

1247
01:08:56,960 --> 01:08:59,639
Speaker 4: had some bucks that would never cross that river. When

1248
01:08:59,680 --> 01:09:02,839
Speaker 4: you look at their home range and all of their points,

1249
01:09:03,120 --> 01:09:06,800
Speaker 4: it is directly adjacent to that river. They would not

1250
01:09:07,160 --> 01:09:11,080
Speaker 4: do it. Really, So there's just so much variation in

1251
01:09:11,520 --> 01:09:13,839
Speaker 4: their personality and what they're willing to accept.

1252
01:09:13,920 --> 01:09:18,080
Speaker 1: You can't I guess you probably can't say this is

1253
01:09:18,120 --> 01:09:20,840
Speaker 1: one of those strategies better for longevity. Like do you

1254
01:09:20,880 --> 01:09:24,320
Speaker 1: find that like super tight stay at home box, super

1255
01:09:24,360 --> 01:09:28,760
Speaker 1: small home ranges, they have a greater survival rate or

1256
01:09:28,800 --> 01:09:31,400
Speaker 1: is it that not or is that not fair to say.

1257
01:09:31,400 --> 01:09:34,760
Speaker 4: Yeah, we didn't have enough of a sample size to

1258
01:09:34,800 --> 01:09:37,400
Speaker 4: tease that apart, because again, only a third of them

1259
01:09:37,640 --> 01:09:42,720
Speaker 4: were had this mobile personality. But that makes sense to me.

1260
01:09:42,800 --> 01:09:46,360
Speaker 4: I think that's reasonable. I also think of it. This

1261
01:09:46,600 --> 01:09:50,040
Speaker 4: may be a bad analogy here, but I think it's

1262
01:09:50,120 --> 01:09:55,400
Speaker 4: just like embedded within some species and some individuals. There's explorers,

1263
01:09:55,960 --> 01:09:59,640
Speaker 4: there's colonizers, there's individuals that are willing to take a

1264
01:09:59,720 --> 01:10:02,800
Speaker 4: rip and go somewhere else. And you know, I think

1265
01:10:02,800 --> 01:10:05,840
Speaker 4: when you just go way way way back in time,

1266
01:10:06,240 --> 01:10:08,800
Speaker 4: you know, hundreds and hundreds of years ago, and you

1267
01:10:08,840 --> 01:10:14,320
Speaker 4: think about the landscape and that deer. We're always having

1268
01:10:14,360 --> 01:10:19,080
Speaker 4: to colonize different areas based on buffalo going through, based

1269
01:10:19,120 --> 01:10:23,559
Speaker 4: on wildfire, and so I just want to think any

1270
01:10:23,640 --> 01:10:28,360
Speaker 4: way that that tendency is embedded within some individuals that

1271
01:10:28,720 --> 01:10:30,719
Speaker 4: I'm going to go look, I'm going to go explore

1272
01:10:30,760 --> 01:10:33,960
Speaker 4: and I'm going to capitalize on some resources unbeknownst to me.

1273
01:10:34,400 --> 01:10:36,960
Speaker 1: Yeah right here. Oh yeah, because if not you because

1274
01:10:37,040 --> 01:10:41,479
Speaker 1: as as environments and landscapes change, if everybody was a

1275
01:10:41,520 --> 01:10:44,160
Speaker 1: super home body, you'd have awesome pieces of habitat open

1276
01:10:44,240 --> 01:10:51,320
Speaker 1: up and like we're never found. Word doesn't get out. Yeah,

1277
01:10:51,760 --> 01:10:56,320
Speaker 1: with the with the idea that like I've heard this

1278
01:10:56,360 --> 01:10:59,840
Speaker 1: express two ways, maybe it's not this clean that during

1279
01:10:59,880 --> 01:11:02,320
Speaker 1: the rut bucks move more. Okay.

1280
01:11:04,000 --> 01:11:06,080
Speaker 3: I remember someone pointing.

1281
01:11:05,720 --> 01:11:10,240
Speaker 1: Out, like they move more but they don't move to

1282
01:11:10,400 --> 01:11:14,559
Speaker 1: new places more. They just move more in the places

1283
01:11:14,600 --> 01:11:15,519
Speaker 1: that they already move.

1284
01:11:15,479 --> 01:11:17,880
Speaker 3: Anyways, is that fair.

1285
01:11:18,160 --> 01:11:19,080
Speaker 4: That's not think that's fair.

1286
01:11:19,160 --> 01:11:22,360
Speaker 1: That's not fair. Yeah, okay, So what.

1287
01:11:22,720 --> 01:11:24,680
Speaker 4: We were able to do is, of course we did

1288
01:11:24,680 --> 01:11:29,360
Speaker 4: all the annual home range stuff, but we also looked

1289
01:11:29,360 --> 01:11:35,240
Speaker 4: at two week home ranges, daily home ranges, and a

1290
01:11:35,360 --> 01:11:39,920
Speaker 4: term called net distance or net displacement. And the bottom

1291
01:11:39,960 --> 01:11:43,400
Speaker 4: line is you will see the greatest home range if

1292
01:11:43,400 --> 01:11:45,720
Speaker 4: you look at it in two week periods during the

1293
01:11:45,760 --> 01:11:48,680
Speaker 4: peak of the rut and during the late rut or

1294
01:11:48,720 --> 01:11:53,599
Speaker 4: immediately after the peak of the rut. But the amount

1295
01:11:53,680 --> 01:11:57,040
Speaker 4: of area that a buck is spending each day, it

1296
01:11:57,080 --> 01:11:59,800
Speaker 4: did not matter if it was pre rut, no rut,

1297
01:12:00,280 --> 01:12:05,920
Speaker 4: after the rut. Two hundred acres per day independent okay,

1298
01:12:06,320 --> 01:12:10,120
Speaker 4: on a daily scale, independent on the time of year,

1299
01:12:10,479 --> 01:12:14,240
Speaker 4: rut phase or not peak of the rut, post rut,

1300
01:12:14,360 --> 01:12:18,559
Speaker 4: pre rut, et cetera. Did not matter. Even though there

1301
01:12:18,960 --> 01:12:26,040
Speaker 4: they're daily ground they were covering could be greater. During

1302
01:12:26,080 --> 01:12:29,360
Speaker 4: the rut, the amount of area that they were covered

1303
01:12:29,720 --> 01:12:34,040
Speaker 4: was two hundred acres per day, But when you look

1304
01:12:34,080 --> 01:12:37,240
Speaker 4: at the very next day where they're at, it will

1305
01:12:37,280 --> 01:12:42,040
Speaker 4: be further apart, meaning a buck is spending covering ground

1306
01:12:42,080 --> 01:12:45,840
Speaker 4: about two hundred acres of ground per day, but during

1307
01:12:45,920 --> 01:12:48,479
Speaker 4: the peak of the rut in late rut, those daily

1308
01:12:48,760 --> 01:12:57,320
Speaker 4: areas or places are further apart. Really, maybe you make.

1309
01:12:57,439 --> 01:13:00,320
Speaker 2: A single move and then do the two hundred yard

1310
01:13:00,360 --> 01:13:02,800
Speaker 2: circuit and then makes a single move into another two

1311
01:13:02,840 --> 01:13:04,479
Speaker 2: hundred yard circuit. Is that what you're saying?

1312
01:13:05,240 --> 01:13:09,400
Speaker 4: Yeah, so maybe think of it like this. When you

1313
01:13:09,479 --> 01:13:13,519
Speaker 4: get into a non rut and early pre rut, every

1314
01:13:13,600 --> 01:13:17,360
Speaker 4: single day there is a great deal of overlap in

1315
01:13:17,400 --> 01:13:21,160
Speaker 4: the area of buckets covering. He might have an overlap

1316
01:13:21,160 --> 01:13:23,960
Speaker 4: of eighty percent of the area he covered the day before,

1317
01:13:24,160 --> 01:13:27,960
Speaker 4: he's in this area. But when you get to later

1318
01:13:28,080 --> 01:13:31,200
Speaker 4: in the rut, because now they're seeking, they're chasing, they're looking.

1319
01:13:31,640 --> 01:13:34,559
Speaker 4: Now we're spending two hundred acres away over here, fifteen

1320
01:13:34,600 --> 01:13:37,519
Speaker 4: hundred yards away, he's in a completely different area. He's

1321
01:13:37,560 --> 01:13:40,680
Speaker 4: covering the same amount of area in a twenty four

1322
01:13:40,720 --> 01:13:44,479
Speaker 4: hour time frame, but the distance away from the dates

1323
01:13:44,720 --> 01:13:46,080
Speaker 4: he's exploring new spots.

1324
01:13:46,400 --> 01:13:48,360
Speaker 1: Yeah.

1325
01:13:49,000 --> 01:13:51,880
Speaker 2: Really, so do you really as a hunter then are

1326
01:13:51,880 --> 01:13:57,360
Speaker 2: we trying to capitalize on that move between the two spots?

1327
01:13:58,600 --> 01:14:02,200
Speaker 4: If you can. I mean, if if you can find out.

1328
01:14:02,120 --> 01:14:07,760
Speaker 2: I rut funnel, it would be a good place to sit, right, Okay.

1329
01:14:07,640 --> 01:14:10,360
Speaker 4: I think you got to frame it like this. If

1330
01:14:10,640 --> 01:14:13,120
Speaker 4: if you've got a lot of intel on a buck,

1331
01:14:13,200 --> 01:14:16,040
Speaker 4: I mean, I know from camera data observation, I know

1332
01:14:16,439 --> 01:14:19,759
Speaker 4: kind of where he's going to be. The best chance

1333
01:14:19,840 --> 01:14:24,000
Speaker 4: for that is pre rut. But if you want to

1334
01:14:24,040 --> 01:14:26,160
Speaker 4: go out, I'm going to go to the woods and

1335
01:14:26,200 --> 01:14:29,920
Speaker 4: what are my greatest odds of seeing a buck? A

1336
01:14:29,960 --> 01:14:34,120
Speaker 4: good buck? Then because of that movement behavior that is

1337
01:14:34,240 --> 01:14:34,840
Speaker 4: absolutely so.

1338
01:14:34,880 --> 01:14:38,080
Speaker 1: The one that hides out of old Lady Thompson's might

1339
01:14:38,080 --> 01:14:39,240
Speaker 1: be off on your spot.

1340
01:14:39,560 --> 01:14:42,920
Speaker 4: That's right, that's right, he's gonna shift, he's gonna move.

1341
01:14:43,400 --> 01:14:43,839
Speaker 1: Yeah.

1342
01:14:45,320 --> 01:14:49,320
Speaker 4: Really mm hmm. I can show you the show the data.

1343
01:14:49,439 --> 01:14:51,240
Speaker 1: Yeah, oh, let me, I'll hit you know, and then

1344
01:14:51,280 --> 01:14:52,760
Speaker 1: these guys can hit you with whatever they want.

1345
01:14:53,640 --> 01:14:55,479
Speaker 3: Do you this might not be something you can tell

1346
01:14:55,520 --> 01:14:56,160
Speaker 3: from your data.

1347
01:14:56,920 --> 01:15:01,759
Speaker 1: Do you think it's true that bucks play the wind

1348
01:15:02,520 --> 01:15:05,320
Speaker 1: and cruise for does by coming on the down wind

1349
01:15:05,360 --> 01:15:06,240
Speaker 1: side of betting cover?

1350
01:15:09,040 --> 01:15:12,000
Speaker 4: I think probably fifty percent of the time they do.

1351
01:15:12,479 --> 01:15:18,920
Speaker 1: Okay, so they're not visually looking for them. They do,

1352
01:15:19,000 --> 01:15:22,280
Speaker 1: but they in addition to visually looking, they're cruising to

1353
01:15:22,320 --> 01:15:22,880
Speaker 1: smell them.

1354
01:15:23,240 --> 01:15:27,599
Speaker 4: Yeah, what we generally think of right now, and this

1355
01:15:27,640 --> 01:15:30,559
Speaker 4: could have a lot to do with those two hundred

1356
01:15:30,560 --> 01:15:35,559
Speaker 4: acre daily areas being so far apart and disjointed. What

1357
01:15:35,600 --> 01:15:39,720
Speaker 4: we think is that bucks are cruising to find what

1358
01:15:39,840 --> 01:15:44,519
Speaker 4: are called dough focal areas. So think about the social

1359
01:15:44,760 --> 01:15:49,519
Speaker 4: behavior of your dough population, those matrilineal groups. And so

1360
01:15:49,880 --> 01:15:52,120
Speaker 4: here's a group of dose here, here's a group of

1361
01:15:52,160 --> 01:15:55,479
Speaker 4: dose over here. We think of it as a circuit.

1362
01:15:56,439 --> 01:15:59,120
Speaker 4: And so a buck is going to go into this area.

1363
01:15:59,200 --> 01:16:03,559
Speaker 4: He knows who all's there, you know, via signposts sent

1364
01:16:03,720 --> 01:16:06,760
Speaker 4: so forth. He's gonna check it. Since check it, who's

1365
01:16:06,840 --> 01:16:09,639
Speaker 4: good or bad? Anybody close coming into heat? Maybe she's

1366
01:16:09,640 --> 01:16:13,479
Speaker 4: already into heat but occupied. He's gonna go to another area,

1367
01:16:14,439 --> 01:16:17,479
Speaker 4: part of that circuit and look for adoin estris there.

1368
01:16:18,240 --> 01:16:20,519
Speaker 1: Okay, I light, I got one more question than he's

1369
01:16:20,520 --> 01:16:21,200
Speaker 1: Guys can hit some.

1370
01:16:23,080 --> 01:16:25,000
Speaker 3: I asked this earlier, but I kind of screwed it up.

1371
01:16:27,240 --> 01:16:32,680
Speaker 1: During peak rut? Is there like a high Is there

1372
01:16:33,120 --> 01:16:35,719
Speaker 1: a strong likelihood or however you want to put it,

1373
01:16:35,760 --> 01:16:39,280
Speaker 1: Is there a strong likelihood that a buck will go

1374
01:16:39,400 --> 01:16:42,080
Speaker 1: somewhere during peak rut that he has never before been

1375
01:16:42,160 --> 01:16:45,000
Speaker 1: in his life, or is he usually at some point

1376
01:16:45,000 --> 01:16:47,120
Speaker 1: in his life been to all the places he's gonna go.

1377
01:16:47,280 --> 01:16:50,439
Speaker 1: So he's visiting places he knows about, or is he

1378
01:16:50,600 --> 01:16:53,559
Speaker 1: legit like going spots he's never seen before.

1379
01:16:55,720 --> 01:16:59,080
Speaker 4: I think the answer is yes, But I don't think

1380
01:16:59,120 --> 01:17:01,920
Speaker 4: that is just during the rut. So the way we

1381
01:17:01,960 --> 01:17:05,800
Speaker 4: would define that would be called an excursion, and so

1382
01:17:05,920 --> 01:17:08,960
Speaker 4: that would be different from a mobile personality like we

1383
01:17:09,000 --> 01:17:11,320
Speaker 4: talked about earlier, because that is where you set up

1384
01:17:11,360 --> 01:17:14,440
Speaker 4: a new home range and you have affinity for that area,

1385
01:17:14,520 --> 01:17:17,240
Speaker 4: and excursion is I'm in my existing home range and

1386
01:17:17,240 --> 01:17:19,240
Speaker 4: I'm gonna take a trip yep, a two to three

1387
01:17:19,320 --> 01:17:21,320
Speaker 4: day I'm will cut a loop and go here and

1388
01:17:21,360 --> 01:17:25,559
Speaker 4: go here. We see those start to occur during the

1389
01:17:25,600 --> 01:17:29,479
Speaker 4: pre rut, and it really escalates during the rut. But

1390
01:17:29,600 --> 01:17:33,559
Speaker 4: with our data during our study, we saw the greatest

1391
01:17:33,560 --> 01:17:36,200
Speaker 4: amount of excursions in the in the post rut, so

1392
01:17:36,400 --> 01:17:37,439
Speaker 4: after the rut.

1393
01:17:37,520 --> 01:17:41,920
Speaker 1: But excursions being that he again like he's going to

1394
01:17:42,520 --> 01:17:43,720
Speaker 1: it might be hard to do it because you can't

1395
01:17:43,760 --> 01:17:46,519
Speaker 1: track him his whole life. He's going to places he's

1396
01:17:46,640 --> 01:17:51,920
Speaker 1: never been. I can't answer that because you don't know

1397
01:17:51,960 --> 01:17:53,880
Speaker 1: where he's because you can't you don't know his whole life.

1398
01:17:53,880 --> 01:17:56,240
Speaker 1: I don't have his whole life history, got it.

1399
01:17:56,360 --> 01:18:00,639
Speaker 4: Yeah, Yeah, but we we definitely saw the the bucks

1400
01:18:00,680 --> 01:18:04,320
Speaker 4: going to novel areas within the limited time frame we

1401
01:18:04,360 --> 01:18:05,120
Speaker 4: had them studied.

1402
01:18:05,240 --> 01:18:05,479
Speaker 1: We did.

1403
01:18:05,479 --> 01:18:07,680
Speaker 4: In other words, we didn't see the exact same excursion

1404
01:18:07,760 --> 01:18:10,720
Speaker 4: loop every time they would go different areas. Yeah, and

1405
01:18:10,760 --> 01:18:14,200
Speaker 4: so yeah, we think they are looking prospecting, whether it

1406
01:18:14,280 --> 01:18:16,120
Speaker 4: be those food resources whatever.

1407
01:18:16,479 --> 01:18:19,519
Speaker 1: That's when you get like really vulnerable. Man, Like you

1408
01:18:19,560 --> 01:18:21,840
Speaker 1: get really vulnerable to something bad happen to you when

1409
01:18:21,880 --> 01:18:25,600
Speaker 1: you're in places you've never been, Like you're on some

1410
01:18:26,200 --> 01:18:27,360
Speaker 1: do you know what I mean? You have no idea

1411
01:18:27,400 --> 01:18:31,680
Speaker 1: what's going on? And like that to me feels like

1412
01:18:31,720 --> 01:18:33,960
Speaker 1: a that to me feels like a buck would get light. Dude,

1413
01:18:34,000 --> 01:18:36,439
Speaker 1: I'm not doing that. Yeah, do you know what I mean? Like,

1414
01:18:36,479 --> 01:18:38,400
Speaker 1: I'm not like, I've never been there, I have no

1415
01:18:38,439 --> 01:18:41,400
Speaker 1: idea what's happening. It seems like they'd feel so vulnerable.

1416
01:18:41,680 --> 01:18:44,160
Speaker 4: And from a deer management perspective, I mean, if you

1417
01:18:44,439 --> 01:18:46,519
Speaker 4: do the kind of stuff we were gone with, you

1418
01:18:46,560 --> 01:18:49,120
Speaker 4: know your you're managing for antlers and older bucks and

1419
01:18:49,120 --> 01:18:52,320
Speaker 4: so forth. That is where even with a large area,

1420
01:18:52,400 --> 01:18:54,519
Speaker 4: so you may have a five to ten thousand acre

1421
01:18:54,640 --> 01:18:58,320
Speaker 4: tract and you were primarily controlling the harvest within that

1422
01:18:58,360 --> 01:19:02,800
Speaker 4: population except for the excursion, and so that is where

1423
01:19:02,840 --> 01:19:04,960
Speaker 4: you will see some of those target bucks are gonna

1424
01:19:04,960 --> 01:19:07,160
Speaker 4: go off and man, they get hammered.

1425
01:19:07,400 --> 01:19:09,680
Speaker 1: Yeah. Yeah, you go over to the place where the

1426
01:19:09,920 --> 01:19:12,000
Speaker 1: you know, brown it's down property.

1427
01:19:11,600 --> 01:19:15,800
Speaker 4: I get shot. And that is so frustrating because you've

1428
01:19:15,840 --> 01:19:19,120
Speaker 4: done everything all year long for years and years and years,

1429
01:19:19,400 --> 01:19:21,840
Speaker 4: and you have that weekend where he decides to take

1430
01:19:21,880 --> 01:19:22,640
Speaker 4: a trip.

1431
01:19:22,560 --> 01:19:24,040
Speaker 3: Do What's funny is uh?

1432
01:19:24,439 --> 01:19:27,720
Speaker 1: I know these guys and they have a big no

1433
01:19:27,840 --> 01:19:32,400
Speaker 1: fence operation in Texas, but they wound up doing one fence.

1434
01:19:33,160 --> 01:19:36,200
Speaker 1: They fenced one property line because they have some brown

1435
01:19:36,240 --> 01:19:40,479
Speaker 1: it's down neighbors and so they just tried to like

1436
01:19:40,560 --> 01:19:43,559
Speaker 1: control it a little bit by blocking that spot right

1437
01:19:44,120 --> 01:19:47,040
Speaker 1: you know, the other three sides or do whatever they want. Yeah.

1438
01:19:47,520 --> 01:19:50,679
Speaker 4: I got a couple of places like that too. It's

1439
01:19:50,760 --> 01:19:53,120
Speaker 4: that pinch point, that corridor of where they're going to

1440
01:19:53,200 --> 01:19:55,280
Speaker 4: go on to that other property and we're gonna block.

1441
01:19:55,040 --> 01:19:56,640
Speaker 3: That up, and these dudes stands.

1442
01:19:56,800 --> 01:19:59,439
Speaker 1: It's so funny is these dudes stands are all we're

1443
01:19:59,479 --> 01:20:04,400
Speaker 1: all that property life. Oh yeah, oh just waiting, you know, Yeah,

1444
01:20:05,320 --> 01:20:06,160
Speaker 1: all right, I'm done.

1445
01:20:08,560 --> 01:20:12,160
Speaker 6: The October Boogeyman is the October law for hunters. The

1446
01:20:12,200 --> 01:20:16,479
Speaker 6: November version of that is lockdown, where there's an idea

1447
01:20:16,640 --> 01:20:18,760
Speaker 6: that there is a phase of the rut for like

1448
01:20:18,840 --> 01:20:22,439
Speaker 6: two to four days where a buck gets a hot

1449
01:20:22,479 --> 01:20:26,120
Speaker 6: dough around like November sixteenth, and they bed down and

1450
01:20:26,160 --> 01:20:29,800
Speaker 6: they breed and they just become less visible and they

1451
01:20:29,880 --> 01:20:34,479
Speaker 6: just become very dedicated to that spot and like running

1452
01:20:34,720 --> 01:20:35,360
Speaker 6: with each other.

1453
01:20:35,960 --> 01:20:37,400
Speaker 3: I don't care what he says, this is true?

1454
01:20:37,560 --> 01:20:38,080
Speaker 1: Is that a thing?

1455
01:20:38,280 --> 01:20:41,160
Speaker 6: Do the deer movement studies show thing.

1456
01:20:41,760 --> 01:20:44,719
Speaker 1: Yeah, they just stand there like the does are feeding,

1457
01:20:44,680 --> 01:20:46,280
Speaker 1: and he just stands there. He doesn't lay down, he

1458
01:20:46,320 --> 01:20:47,960
Speaker 1: doesn't eat, he just stands there.

1459
01:20:48,240 --> 01:20:49,559
Speaker 4: Yeah, that's legit.

1460
01:20:49,840 --> 01:20:52,920
Speaker 1: Oh it is okay, Yeah, because everything else you're like, no,

1461
01:20:53,000 --> 01:20:55,800
Speaker 1: that's not true. That's legit.

1462
01:20:55,880 --> 01:20:57,360
Speaker 4: So you get like in the peak of the rut,

1463
01:20:58,000 --> 01:21:01,679
Speaker 4: this is going to occur all all the time. When

1464
01:21:01,720 --> 01:21:05,920
Speaker 4: there is a dough an estras it becomes a population

1465
01:21:06,120 --> 01:21:09,479
Speaker 4: a level of fact, or it becomes noticeable when a

1466
01:21:09,560 --> 01:21:13,240
Speaker 4: greater proportion of the does are in standing heat and

1467
01:21:13,320 --> 01:21:17,000
Speaker 4: bucks are tending them. So you're gonna have less bucks

1468
01:21:17,040 --> 01:21:19,800
Speaker 4: available roaming the landscape because they're locked in.

1469
01:21:19,960 --> 01:21:24,000
Speaker 6: If there are too many dos, that happens.

1470
01:21:24,040 --> 01:21:26,960
Speaker 4: You're saying no, I'm saying that if you had an

1471
01:21:27,000 --> 01:21:28,479
Speaker 4: appropriate number of doughs.

1472
01:21:28,760 --> 01:21:32,519
Speaker 1: Okay, that's kind of like some magical world every dough,

1473
01:21:32,880 --> 01:21:35,200
Speaker 1: like you have some thing where it lists every dough

1474
01:21:35,200 --> 01:21:39,120
Speaker 1: in a population all came into heat on November seventh.

1475
01:21:39,280 --> 01:21:42,240
Speaker 1: It would be reasonable to assume that on November seventh,

1476
01:21:43,240 --> 01:21:46,240
Speaker 1: no bucks are running around doing crazy stuff, right because

1477
01:21:46,240 --> 01:21:47,839
Speaker 1: they're standing there with all these doughs.

1478
01:21:47,640 --> 01:21:51,800
Speaker 4: That are exactly And then twenty eight days later you're

1479
01:21:51,800 --> 01:21:54,719
Speaker 4: gonna have the leftovers because the sex ratio, there's always

1480
01:21:54,720 --> 01:21:57,960
Speaker 4: more doughs than bucks, and so some of them may

1481
01:21:58,000 --> 01:22:01,559
Speaker 4: not get bred, and so then that would follow again

1482
01:22:01,720 --> 01:22:02,760
Speaker 4: twenty eight days later.

1483
01:22:03,280 --> 01:22:06,040
Speaker 6: How impactful, though, do you think lockdown is? Is it

1484
01:22:06,080 --> 01:22:08,000
Speaker 6: a thing where like hunters are going to have a

1485
01:22:08,000 --> 01:22:09,439
Speaker 6: worse experience in the woods.

1486
01:22:11,160 --> 01:22:14,519
Speaker 4: I would still go because it's it's the rut. I

1487
01:22:14,520 --> 01:22:18,040
Speaker 4: would look at it as the frequency of just seeing

1488
01:22:18,560 --> 01:22:22,200
Speaker 4: more bucks during that time frame is gonna be less

1489
01:22:22,360 --> 01:22:25,200
Speaker 4: because some of them are locked in with does, but

1490
01:22:25,400 --> 01:22:27,599
Speaker 4: you also have the odd man out or the odd

1491
01:22:27,680 --> 01:22:30,040
Speaker 4: buck out, and he's gonna be going around looking for

1492
01:22:30,160 --> 01:22:34,280
Speaker 4: another dough and estress, so that there's still gonna be

1493
01:22:34,400 --> 01:22:37,439
Speaker 4: general buck movement. You're just gonna have a greater number

1494
01:22:37,600 --> 01:22:39,679
Speaker 4: of them that is occupying a dough.

1495
01:22:39,600 --> 01:22:41,960
Speaker 6: And there's no crater though in the bell curve. When

1496
01:22:42,000 --> 01:22:46,799
Speaker 6: that happens, don't see it, Okay, Yeah, man, I wonder.

1497
01:22:46,640 --> 01:22:49,479
Speaker 2: If you do, you could tell me what days not

1498
01:22:49,600 --> 01:22:50,280
Speaker 2: to hunt.

1499
01:22:50,800 --> 01:22:53,200
Speaker 1: What I'm thinking is this man picture you got like

1500
01:22:53,280 --> 01:22:56,360
Speaker 1: some kind of weird deal where you can it's illegal,

1501
01:22:58,640 --> 01:23:01,679
Speaker 1: like you put out some kind of a birth control

1502
01:23:01,760 --> 01:23:04,680
Speaker 1: thing or something where none of the dos ever come in.

1503
01:23:04,840 --> 01:23:07,479
Speaker 6: Oh, Bucks, just crazy everywhere.

1504
01:23:08,520 --> 01:23:11,639
Speaker 1: It's a short term play. Yeah, it's not a good lie.

1505
01:23:11,720 --> 01:23:13,920
Speaker 4: That'd be some some evil science there.

1506
01:23:14,600 --> 01:23:17,439
Speaker 1: It's a bad long term play. You're going to see

1507
01:23:17,479 --> 01:23:18,639
Speaker 1: a plumbing deer population.

1508
01:23:19,040 --> 01:23:22,960
Speaker 2: We're in Wisconsin. Uh you know, cwd's big there, big deer.

1509
01:23:23,000 --> 01:23:26,679
Speaker 2: Heard a lot of our neighbors have started shooting more does.

1510
01:23:28,240 --> 01:23:31,120
Speaker 2: Since they've started doing that, they claim to have a

1511
01:23:31,280 --> 01:23:36,920
Speaker 2: better rut because less does mean more bucks moving around,

1512
01:23:37,000 --> 01:23:40,320
Speaker 2: more bucks reacting to calls does that make sense.

1513
01:23:40,880 --> 01:23:44,920
Speaker 4: It makes perfect sense. I do not know of a

1514
01:23:45,280 --> 01:23:49,519
Speaker 4: study that has specifically evaluated that, but I think that

1515
01:23:49,640 --> 01:23:54,360
Speaker 4: is entirely logical because you've increased competition. You know, they're

1516
01:23:54,600 --> 01:23:57,439
Speaker 4: less does per male and so they have to compete more,

1517
01:23:57,560 --> 01:23:59,679
Speaker 4: look more, search more, et cetera.

1518
01:24:01,479 --> 01:24:02,120
Speaker 1: It's my turn.

1519
01:24:02,479 --> 01:24:04,439
Speaker 2: We're just going said you were done.

1520
01:24:04,560 --> 01:24:08,160
Speaker 1: I was for my turn when this turn, This turn

1521
01:24:08,160 --> 01:24:09,240
Speaker 1: is gonna be one question turned.

1522
01:24:10,680 --> 01:24:11,360
Speaker 4: Uh.

1523
01:24:11,760 --> 01:24:14,439
Speaker 1: We have a buddy who has a really great property

1524
01:24:14,479 --> 01:24:21,960
Speaker 1: in Texas whereabouts Way South Texas, Brownsville, Way South Texas.

1525
01:24:22,920 --> 01:24:27,360
Speaker 1: Like when you're cruising around, you see I mean, you

1526
01:24:27,360 --> 01:24:30,559
Speaker 1: see way more Bucks and does anyhow, we go down

1527
01:24:30,600 --> 01:24:32,360
Speaker 1: there a couple times. We've gone down to Rattle Bucks,

1528
01:24:32,360 --> 01:24:33,800
Speaker 1: which is the funnest thing in the world because it's

1529
01:24:33,880 --> 01:24:39,080
Speaker 1: very effective there. I developed this little theory that the

1530
01:24:39,120 --> 01:24:42,439
Speaker 1: most effective time to rattle them is during the middle

1531
01:24:42,439 --> 01:24:45,080
Speaker 1: of the day. In my thinking, the dolls are all

1532
01:24:45,160 --> 01:24:48,799
Speaker 1: laying down on their board and they're just more inclined

1533
01:24:48,800 --> 01:24:51,360
Speaker 1: to wonder what's up when the doors are up on

1534
01:24:51,439 --> 01:24:53,200
Speaker 1: their feet. They're like, yeah, yeah, I hear it, but

1535
01:24:53,240 --> 01:24:57,120
Speaker 1: I'm like following my dough around. Then midday he gets bored.

1536
01:24:57,760 --> 01:24:59,920
Speaker 1: He hears the rattle, He's got nothing else going on,

1537
01:25:00,120 --> 01:25:02,439
Speaker 1: and so he runs over. Yeah, what do you think

1538
01:25:02,479 --> 01:25:03,000
Speaker 1: about that?

1539
01:25:03,080 --> 01:25:10,360
Speaker 4: There's a merit to that, Steve, but it's wrong. We

1540
01:25:10,400 --> 01:25:15,040
Speaker 4: did a study on that. Now I was a tech,

1541
01:25:15,200 --> 01:25:17,760
Speaker 4: I was a participant as a buddy of mine. So

1542
01:25:17,840 --> 01:25:20,680
Speaker 4: again my master's degree was in South Texas, so I

1543
01:25:20,720 --> 01:25:23,840
Speaker 4: spent a lot of time down there, and so we

1544
01:25:23,880 --> 01:25:27,439
Speaker 4: did a rattling experiment. To my knowledge, it is the

1545
01:25:27,520 --> 01:25:31,000
Speaker 4: only peer reviewed experiment ever done on rattling antlers and

1546
01:25:31,439 --> 01:25:36,599
Speaker 4: and dough response. And what we found, very generally was

1547
01:25:36,800 --> 01:25:43,200
Speaker 4: we we varied the how loud the rattling was, the

1548
01:25:43,400 --> 01:25:49,439
Speaker 4: duration of rattling, the time of day of rattling, and

1549
01:25:49,479 --> 01:25:53,160
Speaker 4: then the time of year relative to the rut for

1550
01:25:53,240 --> 01:25:57,080
Speaker 4: the rattling. And so the clear winner for time of

1551
01:25:57,200 --> 01:26:04,160
Speaker 4: day was crepuscular. No, here's why, because the real winner

1552
01:26:04,320 --> 01:26:07,400
Speaker 4: on the rattling technique. And remember back then, so this

1553
01:26:07,439 --> 01:26:10,680
Speaker 4: would have been this has been mid nineties, and so

1554
01:26:10,760 --> 01:26:13,559
Speaker 4: this is your You're reading the magazine and how do

1555
01:26:13,600 --> 01:26:17,280
Speaker 4: you set up your rattling sequence? And so you got

1556
01:26:17,280 --> 01:26:19,640
Speaker 4: to get there, and you gotta get crouch and you

1557
01:26:19,720 --> 01:26:23,000
Speaker 4: got to scrape the brush and you gotta kick and

1558
01:26:23,000 --> 01:26:25,719
Speaker 4: you gotta rattle, and you got to remember that, remember

1559
01:26:25,840 --> 01:26:27,519
Speaker 4: all that.

1560
01:26:28,200 --> 01:26:30,040
Speaker 3: But anyways, gone, okay, Well.

1561
01:26:30,200 --> 01:26:31,479
Speaker 4: It was a thing back in the day.

1562
01:26:32,680 --> 01:26:35,320
Speaker 1: And what we found, you're you're painting the whole picture,

1563
01:26:35,439 --> 01:26:38,240
Speaker 1: like the deer. You're kind of like you're you're sort

1564
01:26:38,240 --> 01:26:40,400
Speaker 1: of creating the entire encounter.

1565
01:26:40,520 --> 01:26:43,599
Speaker 4: You're trying to mimic reality. Yeah, where they're bumping into

1566
01:26:43,600 --> 01:26:46,520
Speaker 4: the brush and all that, sort of making it more realistic.

1567
01:26:46,840 --> 01:26:50,760
Speaker 4: But the bottom it was just very very clear, how

1568
01:26:50,880 --> 01:26:55,200
Speaker 4: loud you are. Number One, the louder you make it,

1569
01:26:55,360 --> 01:26:58,720
Speaker 4: you increase the probability that more bucks will hear it.

1570
01:26:59,200 --> 01:27:02,200
Speaker 4: More bucks will hear it when more bucks are circulating

1571
01:27:02,320 --> 01:27:05,160
Speaker 4: during the crepuscular period, more bucks are going to be

1572
01:27:05,240 --> 01:27:09,960
Speaker 4: up and about circulating during the pre rut. So make

1573
01:27:10,000 --> 01:27:14,360
Speaker 4: it as loud as you can. And the sequence that

1574
01:27:14,400 --> 01:27:18,040
Speaker 4: we were doing, we had a we had four different sequences,

1575
01:27:18,120 --> 01:27:21,360
Speaker 4: but the one that always worked the best was called

1576
01:27:21,760 --> 01:27:26,040
Speaker 4: long and Loud. I still remember it. It's still etched

1577
01:27:26,080 --> 01:27:28,800
Speaker 4: in here. Long and Loud was you got to go

1578
01:27:28,920 --> 01:27:32,120
Speaker 4: for three minutes. Three minutes. That doesn't sound like a

1579
01:27:32,160 --> 01:27:36,559
Speaker 4: lot with those things. As hard as you can possibly go.

1580
01:27:36,720 --> 01:27:39,160
Speaker 4: Your arms will be tired, they're spaghetti. Yeah, I mean

1581
01:27:39,160 --> 01:27:42,840
Speaker 4: you're you're just done by that. But that was the

1582
01:27:42,880 --> 01:27:46,160
Speaker 4: clear winter, and so just the obvious thing is they

1583
01:27:46,160 --> 01:27:48,960
Speaker 4: could hear it better. And so I and I even

1584
01:27:49,040 --> 01:27:51,559
Speaker 4: had chances where a sweat somebody on the ground.

1585
01:27:52,120 --> 01:27:52,519
Speaker 1: This was that.

1586
01:27:52,760 --> 01:27:55,400
Speaker 4: Do youn't know where the Welder Wildlife Refuge is?

1587
01:27:55,439 --> 01:27:55,599
Speaker 7: Aid?

1588
01:27:55,640 --> 01:27:59,400
Speaker 4: Did you go past it? Going south? Unhunted population tens

1589
01:27:59,439 --> 01:28:02,360
Speaker 4: of thousands of They have all these observation towers. So

1590
01:28:02,360 --> 01:28:05,960
Speaker 4: we got an observers up top fifteen twenty foot above

1591
01:28:05,960 --> 01:28:09,679
Speaker 4: the brush, and somebody down below, and you could literally

1592
01:28:09,760 --> 01:28:13,559
Speaker 4: even see I saw this to where the guy below

1593
01:28:13,640 --> 01:28:16,320
Speaker 4: starts rattling. He's doing a long and loud or something

1594
01:28:16,400 --> 01:28:19,280
Speaker 4: like that, and the buck is four hundred yards away,

1595
01:28:19,680 --> 01:28:22,639
Speaker 4: and he hears it and he starts coming, coming, coming,

1596
01:28:22,680 --> 01:28:25,840
Speaker 4: He's not running, but he's coming. He's obviously moving that way,

1597
01:28:26,240 --> 01:28:32,320
Speaker 4: stopped rattling. He was back to browsing around. And then

1598
01:28:32,360 --> 01:28:34,320
Speaker 4: it was over a thirty minute period, and so then

1599
01:28:34,360 --> 01:28:36,439
Speaker 4: we had an elapsed time and you do another rattle,

1600
01:28:36,479 --> 01:28:39,400
Speaker 4: and then another rattle, and do you rattle bring him in,

1601
01:28:39,600 --> 01:28:44,160
Speaker 4: keep coming, stop rattling. He stopped rattled him again, finally

1602
01:28:44,479 --> 01:28:50,120
Speaker 4: closed the distance and brought him in the volume and

1603
01:28:50,280 --> 01:28:54,760
Speaker 4: increasing the probability that a buck is within distance of

1604
01:28:54,840 --> 01:28:57,280
Speaker 4: hearing you. That was the secret sauce.

1605
01:28:58,120 --> 01:29:00,680
Speaker 6: I like your strategy, though, Steve, because as if I'm

1606
01:29:00,720 --> 01:29:04,679
Speaker 6: thinking about rattling, if it's donn or dusk, in my head,

1607
01:29:04,760 --> 01:29:06,800
Speaker 6: deer movement is already like a nine out of ten.

1608
01:29:07,040 --> 01:29:09,559
Speaker 6: I don't need to help the deer movement anymore right now.

1609
01:29:09,800 --> 01:29:12,000
Speaker 6: At midday, though, maybe it's like a four out of ten,

1610
01:29:12,479 --> 01:29:13,960
Speaker 6: and so I could rattle and bring it up to

1611
01:29:13,960 --> 01:29:16,439
Speaker 6: a seven out of ten. And so I'm just like

1612
01:29:16,680 --> 01:29:19,840
Speaker 6: I'm raising the floor of my hunt at that point.

1613
01:29:20,040 --> 01:29:24,320
Speaker 1: Yeah, we were not viewing it as making We were

1614
01:29:24,360 --> 01:29:26,280
Speaker 1: not viewing it as hey, there's nothing else to do.

1615
01:29:27,120 --> 01:29:30,000
Speaker 1: We're viewing it as going out in the morning. There's

1616
01:29:30,040 --> 01:29:32,679
Speaker 1: like deer round and you do a few rattle sessions,

1617
01:29:32,800 --> 01:29:35,160
Speaker 1: nothing happened, gets to be eleven am, and all of

1618
01:29:35,160 --> 01:29:39,440
Speaker 1: a sudden, buck buck buck. So I had this whole boredom.

1619
01:29:39,560 --> 01:29:42,240
Speaker 1: There you go, hypothesis, But it could be other factors

1620
01:29:42,240 --> 01:29:42,880
Speaker 1: in there. Well.

1621
01:29:43,080 --> 01:29:46,000
Speaker 6: Ask a question, what do your movement studies say about age?

1622
01:29:46,040 --> 01:29:47,920
Speaker 6: I assume it's just real simple that like a one

1623
01:29:48,000 --> 01:29:50,360
Speaker 6: and a half year old moves more and he's more

1624
01:29:50,360 --> 01:29:52,120
Speaker 6: reckless than a five and a half year old. Is

1625
01:29:52,160 --> 01:29:53,240
Speaker 6: that Is that what you've seen?

1626
01:29:54,120 --> 01:29:57,559
Speaker 4: Yeah, it's very subtle. You know. There's a lot of

1627
01:29:57,680 --> 01:30:00,880
Speaker 4: people will say, and maybe we didn't not have enough

1628
01:30:01,160 --> 01:30:04,280
Speaker 4: really really old bucks. We had several five and six

1629
01:30:04,400 --> 01:30:09,000
Speaker 4: year olds, but we saw a general decline, a general

1630
01:30:09,400 --> 01:30:14,799
Speaker 4: contraction in home range. But it was not overwhelming. Okay,

1631
01:30:14,920 --> 01:30:18,200
Speaker 4: but yes it did. You know after the yearling dispersal event,

1632
01:30:18,320 --> 01:30:20,880
Speaker 4: they're typically going to have a larger one and then

1633
01:30:20,920 --> 01:30:23,599
Speaker 4: it's like they keep figuring out, you know, year after

1634
01:30:23,680 --> 01:30:24,920
Speaker 4: year it gets a little bit small.

1635
01:30:25,160 --> 01:30:29,280
Speaker 6: Huh, I feel like hard oh Whitetail hunters will also

1636
01:30:29,400 --> 01:30:32,639
Speaker 6: say that you talked about how there's more movement after

1637
01:30:32,680 --> 01:30:36,000
Speaker 6: the peak of the rut, and usually those are the

1638
01:30:36,000 --> 01:30:38,880
Speaker 6: mature bucks. They're the wise ones who know that not

1639
01:30:39,000 --> 01:30:41,040
Speaker 6: every dough has been bred yet, so they're playing the

1640
01:30:41,080 --> 01:30:42,680
Speaker 6: long game. That's when they're going to get up and

1641
01:30:43,640 --> 01:30:46,720
Speaker 6: be a little more reckless. Is if you think the

1642
01:30:46,880 --> 01:30:50,200
Speaker 6: peak of the rut is like November fourteen, those old

1643
01:30:50,240 --> 01:30:53,960
Speaker 6: mature bucks, five six year olds, they are really participating

1644
01:30:54,000 --> 01:30:56,880
Speaker 6: in the rut more in that like fifteenth to twenty

1645
01:30:56,920 --> 01:30:59,280
Speaker 6: fifth time period than a two and a half year old?

1646
01:30:59,320 --> 01:31:03,800
Speaker 6: Is that? Is that like putting too much stock in

1647
01:31:04,200 --> 01:31:04,919
Speaker 6: those ideas.

1648
01:31:05,280 --> 01:31:09,800
Speaker 4: I think a buck is gonna participate whenever he can, huh,

1649
01:31:09,800 --> 01:31:12,839
Speaker 4: and whenever he detects there is a dough an estress,

1650
01:31:13,040 --> 01:31:17,040
Speaker 4: he's gonna participate. Okay, if that answers your question.

1651
01:31:17,160 --> 01:31:19,000
Speaker 6: Yeah, Like I said, a white tail hunter would say,

1652
01:31:19,000 --> 01:31:20,519
Speaker 6: that is the time period of the rut for the

1653
01:31:20,560 --> 01:31:23,240
Speaker 6: old bucks. That's like when they are vulnerable.

1654
01:31:24,040 --> 01:31:27,439
Speaker 4: Well, yeah, they would be exposed more during that time,

1655
01:31:27,479 --> 01:31:29,479
Speaker 4: but not more than a two and a half year old,

1656
01:31:29,560 --> 01:31:31,479
Speaker 4: is I wouldn't think?

1657
01:31:31,479 --> 01:31:33,600
Speaker 1: So? Okay, Yeah, I'm gonna go out of order and

1658
01:31:33,600 --> 01:31:36,679
Speaker 1: ask my next question. Then Yanni, and then Spencer.

1659
01:31:37,560 --> 01:31:40,080
Speaker 2: We have a couple left time.

1660
01:31:40,120 --> 01:31:41,000
Speaker 1: Why ask your question?

1661
01:31:41,840 --> 01:31:43,240
Speaker 3: I was afraid I don't forget you.

1662
01:31:43,360 --> 01:31:45,120
Speaker 2: No, go ahead, I won't forget mine because it's sitting

1663
01:31:45,160 --> 01:31:45,680
Speaker 2: right in front of me.

1664
01:31:45,800 --> 01:31:49,720
Speaker 1: How far away you think? How far away you think

1665
01:31:49,760 --> 01:31:53,680
Speaker 1: a buck can smell it a dough? That's an astress?

1666
01:31:57,200 --> 01:32:01,240
Speaker 4: Great question, I would say, Uh, I haven't said it

1667
01:32:01,280 --> 01:32:04,320
Speaker 4: depends yet, but I think it's going to depend so

1668
01:32:04,439 --> 01:32:06,920
Speaker 4: much on wind condition, you know, and.

1669
01:32:06,920 --> 01:32:10,519
Speaker 1: So wild ass like, like perfect conditions.

1670
01:32:10,320 --> 01:32:11,439
Speaker 4: Hundreds of yards?

1671
01:32:12,640 --> 01:32:16,120
Speaker 2: Are you asking about the doe herself or just the

1672
01:32:16,160 --> 01:32:17,679
Speaker 2: scent that maybe she left behind?

1673
01:32:18,920 --> 01:32:24,000
Speaker 1: Just detect the presence of a doe that's in heat. Yeah,

1674
01:32:24,040 --> 01:32:26,799
Speaker 1: in perfect conditions, it wouldn't be it wouldn't be crazy

1675
01:32:26,840 --> 01:32:28,000
Speaker 1: to say hundreds of yards.

1676
01:32:28,680 --> 01:32:30,360
Speaker 4: I don't think so, not at all.

1677
01:32:30,960 --> 01:32:33,559
Speaker 1: Yeah, their sense of smells that good.

1678
01:32:34,080 --> 01:32:36,400
Speaker 4: Yeah, yeah, I think so. I don't know if it's

1679
01:32:36,439 --> 01:32:41,200
Speaker 4: five hundred yards to me, I think about diffusion, and so,

1680
01:32:41,240 --> 01:32:43,240
Speaker 4: you know, the further and further you're getting away, the

1681
01:32:43,280 --> 01:32:47,559
Speaker 4: more those molecules are, you know, being distributed within the air,

1682
01:32:47,600 --> 01:32:51,040
Speaker 4: and can they pick up enough of a concentration to

1683
01:32:51,080 --> 01:32:53,600
Speaker 4: cause a response. But certainly hundreds.

1684
01:32:53,200 --> 01:32:54,040
Speaker 1: Of yards.

1685
01:32:56,680 --> 01:32:58,960
Speaker 2: Bronson, why did you bring that antler all the way

1686
01:32:58,960 --> 01:33:00,479
Speaker 2: from here?

1687
01:33:01,360 --> 01:33:02,759
Speaker 4: Yeah?

1688
01:33:03,120 --> 01:33:05,880
Speaker 2: And if you're just listening, you're just later gonna have

1689
01:33:05,920 --> 01:33:07,880
Speaker 2: to go to YouTube and watch to see what we're

1690
01:33:07,920 --> 01:33:08,360
Speaker 2: gonna tell you.

1691
01:33:08,439 --> 01:33:10,280
Speaker 1: He's got a big old he's got a big old

1692
01:33:10,280 --> 01:33:13,200
Speaker 1: buck antler. It's a Michigan tan with the browtie and

1693
01:33:13,240 --> 01:33:17,080
Speaker 1: saw it off's got one. He's got an a luinum contraption.

1694
01:33:19,040 --> 01:33:21,439
Speaker 1: He's got an a lunum contraption glued to the end

1695
01:33:21,439 --> 01:33:21,680
Speaker 1: of it.

1696
01:33:21,840 --> 01:33:23,840
Speaker 6: Squirrels have been chewing on the times.

1697
01:33:24,520 --> 01:33:26,760
Speaker 4: That was actually damage during velvet.

1698
01:33:27,000 --> 01:33:28,800
Speaker 1: Oh, I just thought.

1699
01:33:31,040 --> 01:33:36,000
Speaker 4: This is a this is an example from or this

1700
01:33:36,080 --> 01:33:40,000
Speaker 4: is a specimen from an experiment we did about ten

1701
01:33:40,080 --> 01:33:44,120
Speaker 4: years ago now. And the question was, let me, let

1702
01:33:44,120 --> 01:33:46,160
Speaker 4: me back up. We always at Mississippi State with the

1703
01:33:46,200 --> 01:33:48,720
Speaker 4: Deer Lab, we tried to do every single thing we

1704
01:33:48,800 --> 01:33:52,000
Speaker 4: do has a purpose for the end user. It's gonna

1705
01:33:52,000 --> 01:33:54,519
Speaker 4: affect hunting, it's going to affect management, help you manage

1706
01:33:54,560 --> 01:33:58,000
Speaker 4: your property. Except this. This has nothing to do at

1707
01:33:58,000 --> 01:34:01,519
Speaker 4: all with man. This is straight up deer biology. Me

1708
01:34:01,760 --> 01:34:06,200
Speaker 4: and Steve Demris, the other co director of the Deer Lab,

1709
01:34:06,280 --> 01:34:08,519
Speaker 4: we have this debate going on for years and years

1710
01:34:08,920 --> 01:34:14,599
Speaker 4: about female choice. Do female white tailed deer can they

1711
01:34:14,680 --> 01:34:19,600
Speaker 4: do they have any type of choice whatsoever? Now? Behaviorally,

1712
01:34:20,439 --> 01:34:22,439
Speaker 4: we don't know if she does, because when she comes

1713
01:34:22,439 --> 01:34:26,080
Speaker 4: into standing heat, she's she's going to breed, you know,

1714
01:34:26,120 --> 01:34:28,120
Speaker 4: if there is a If she's in standing heat and

1715
01:34:28,240 --> 01:34:30,519
Speaker 4: a buck is behind her, she's gonna breed.

1716
01:34:30,479 --> 01:34:34,720
Speaker 3: Doesn't matter if it's a spiky or no big old

1717
01:34:34,800 --> 01:34:35,439
Speaker 3: rope dragger.

1718
01:34:35,640 --> 01:34:39,080
Speaker 4: So I think she has to assume whom I guess

1719
01:34:39,160 --> 01:34:41,920
Speaker 4: that's the right word, assume that that's going to sort

1720
01:34:42,040 --> 01:34:47,160
Speaker 4: itself out, that that hopefully, through a dominance hierarchy, she's

1721
01:34:47,240 --> 01:34:50,960
Speaker 4: getting the better buck. But during the peak of the rut,

1722
01:34:51,000 --> 01:34:53,280
Speaker 4: that may not always be the case because the quote

1723
01:34:53,320 --> 01:34:56,000
Speaker 4: dominant older buck, he may be occupied on a you know,

1724
01:34:56,080 --> 01:34:58,720
Speaker 4: way over here with another though, you know, And we

1725
01:34:58,760 --> 01:35:05,360
Speaker 4: see multi paternity, and so in twenty five percent of doze,

1726
01:35:06,280 --> 01:35:09,519
Speaker 4: the twin faunds, twenty five percent of those will have

1727
01:35:09,520 --> 01:35:13,759
Speaker 4: two different fathers, got it, So it's going on multiple

1728
01:35:13,800 --> 01:35:17,800
Speaker 4: bucks of breeding. So I had just always thought that

1729
01:35:18,680 --> 01:35:22,559
Speaker 4: she has to care. She has to care. Now whether

1730
01:35:22,600 --> 01:35:24,120
Speaker 4: she can do anything about it or not, it's a

1731
01:35:24,120 --> 01:35:26,920
Speaker 4: different question, but she has to care that if what

1732
01:35:27,080 --> 01:35:29,439
Speaker 4: is behind me and about to breed me, is it

1733
01:35:29,479 --> 01:35:32,280
Speaker 4: a year old spike or would it be a three,

1734
01:35:32,400 --> 01:35:35,160
Speaker 4: four or five year old with larger antlers and a

1735
01:35:35,160 --> 01:35:39,720
Speaker 4: big body who has clearly demonstrated I'm a survivor. I

1736
01:35:39,760 --> 01:35:42,720
Speaker 4: can make it. You know, she's got all the investment,

1737
01:35:42,760 --> 01:35:44,840
Speaker 4: she's going to have the gestation for seven months, is

1738
01:35:44,880 --> 01:35:48,280
Speaker 4: all her resources. She ought to care who's behind hers? Like, well,

1739
01:35:48,360 --> 01:35:50,720
Speaker 4: how do we do this? So we ended up we

1740
01:35:50,760 --> 01:35:53,760
Speaker 4: had another project going on and we had a way

1741
01:35:53,840 --> 01:35:56,760
Speaker 4: we could set this up. So we took all of

1742
01:35:56,800 --> 01:35:59,680
Speaker 4: our bucks and we standardized them. We came up with

1743
01:35:59,760 --> 01:36:03,479
Speaker 4: p We paired them by age. We paired them by

1744
01:36:03,560 --> 01:36:08,160
Speaker 4: body size, so a doe looking at a buck couldn't say, well,

1745
01:36:08,200 --> 01:36:10,920
Speaker 4: that buck is clearly four year four years old, that

1746
01:36:10,960 --> 01:36:14,160
Speaker 4: one is clearly a yearling and choose one of them.

1747
01:36:14,320 --> 01:36:14,519
Speaker 1: Yep.

1748
01:36:15,720 --> 01:36:18,760
Speaker 4: So we standardized by body size and age. And then

1749
01:36:18,800 --> 01:36:21,759
Speaker 4: we got with our egg engineering people and we developed

1750
01:36:21,760 --> 01:36:26,640
Speaker 4: a contraption to where we could manipulate antlers.

1751
01:36:26,200 --> 01:36:28,160
Speaker 1: Could make him look like a toad even when he wasn't.

1752
01:36:28,200 --> 01:36:32,360
Speaker 4: That's exactly right. So we challenged these does with.

1753
01:36:32,640 --> 01:36:34,400
Speaker 2: Well, hold on, you gotta explain how you did that.

1754
01:36:35,360 --> 01:36:38,000
Speaker 1: Take a little spike and put that antler on his ass.

1755
01:36:39,560 --> 01:36:40,559
Speaker 2: Yeah he's alive.

1756
01:36:41,200 --> 01:36:43,760
Speaker 4: Yeah, Well we sedate him. Yeah we sedatum.

1757
01:36:43,880 --> 01:36:44,080
Speaker 1: Yeah.

1758
01:36:44,720 --> 01:36:51,120
Speaker 2: Looking so they all had the base part somehow attached

1759
01:36:51,120 --> 01:36:51,679
Speaker 2: to their.

1760
01:36:51,880 --> 01:36:55,120
Speaker 4: Pedical Yeah yeah, So all the all the bucks that

1761
01:36:55,120 --> 01:36:57,680
Speaker 4: are they're in the study. They're going to be sedated

1762
01:36:58,040 --> 01:37:00,799
Speaker 4: and then we're gonna cut their antlers off. We're gonna

1763
01:37:01,080 --> 01:37:04,519
Speaker 4: fix that part, the coupling, a fix to the antler

1764
01:37:04,920 --> 01:37:07,200
Speaker 4: and then the pedicle. They're going to get a receiver

1765
01:37:07,840 --> 01:37:12,800
Speaker 4: coupling there, and so this is incredible, and so then

1766
01:37:13,320 --> 01:37:15,839
Speaker 4: we will challenge a dough. So then we had someone

1767
01:37:15,920 --> 01:37:21,439
Speaker 4: from that school reproductive physiologist. They can induce estress, you know,

1768
01:37:21,479 --> 01:37:24,080
Speaker 4: with the progesterone treatment or something. So now we know

1769
01:37:24,120 --> 01:37:26,920
Speaker 4: where that dough is coming into heat. And so now

1770
01:37:26,960 --> 01:37:30,200
Speaker 4: she's behaviorally, she's demonstrating that she's an estress. So we

1771
01:37:30,280 --> 01:37:32,920
Speaker 4: send her down an alleyway and she's got a pen,

1772
01:37:33,400 --> 01:37:35,519
Speaker 4: and then to her left and her to her right

1773
01:37:35,680 --> 01:37:41,880
Speaker 4: are too equally aged or equally body sized bucks. One

1774
01:37:41,920 --> 01:37:43,880
Speaker 4: of them is carrying a one sixty, one of them

1775
01:37:43,920 --> 01:37:48,360
Speaker 4: is carrying a ninety, and then we monitored her behavior

1776
01:37:48,520 --> 01:37:52,080
Speaker 4: to see which one she would prefer. Now, we could

1777
01:37:52,080 --> 01:37:54,680
Speaker 4: not allow them to breed just the way it was

1778
01:37:54,720 --> 01:37:57,280
Speaker 4: set up the logistics, but then we looked at all

1779
01:37:57,400 --> 01:38:01,120
Speaker 4: the behavioral signs of if we pull the fence up,

1780
01:38:01,439 --> 01:38:04,559
Speaker 4: which which one would she go to? And it was

1781
01:38:04,680 --> 01:38:08,880
Speaker 4: over eighty percent of the time she always went for

1782
01:38:09,520 --> 01:38:12,800
Speaker 4: the antlers. Wow, even a younger official.

1783
01:38:12,479 --> 01:38:16,559
Speaker 1: Dude, good for her, superficial man, hey man, But there's

1784
01:38:16,560 --> 01:38:21,760
Speaker 1: that twenty interest in personality, it's like totally suficial.

1785
01:38:21,840 --> 01:38:24,000
Speaker 4: But it wasn't one hundred percent. It was you know,

1786
01:38:24,160 --> 01:38:26,599
Speaker 4: twenty percent didn't fall for the for the big antlers.

1787
01:38:27,000 --> 01:38:30,160
Speaker 1: So there's some selection going on. Well, but but like

1788
01:38:30,200 --> 01:38:33,559
Speaker 1: you're saying whether or not it, I get what you're saying,

1789
01:38:33,720 --> 01:38:36,759
Speaker 1: Like in that environment, there's selection going on. But however

1790
01:38:36,800 --> 01:38:38,880
Speaker 1: that's occurring in the real world scenario, it.

1791
01:38:38,880 --> 01:38:43,200
Speaker 4: Is hard to determine exactly right, Yeah, can that even happen?

1792
01:38:43,280 --> 01:38:45,000
Speaker 4: You know? The only the only thing we can say

1793
01:38:45,000 --> 01:38:47,439
Speaker 4: in the wild of does she have any choice at all?

1794
01:38:47,640 --> 01:38:51,240
Speaker 4: Is when she since the sensing she's coming into estras,

1795
01:38:51,600 --> 01:38:55,160
Speaker 4: might she go to an area where she knows this

1796
01:38:55,439 --> 01:38:59,280
Speaker 4: knows this guy occupies and just make herself available. Yeah,

1797
01:38:59,320 --> 01:39:02,439
Speaker 4: but yeah, she can't be very proactive in this thing.

1798
01:39:02,680 --> 01:39:05,280
Speaker 4: But when you standardize all that and controlled for it,

1799
01:39:06,080 --> 01:39:11,040
Speaker 4: that's what she preferred. So it does follow the ecological

1800
01:39:11,120 --> 01:39:14,639
Speaker 4: theory about antlers or an honest signal of quality.

1801
01:39:14,760 --> 01:39:16,519
Speaker 3: Yeah, yeah, I think I've wondered.

1802
01:39:18,280 --> 01:39:20,560
Speaker 1: I'm especially thinking about this as you're explaining this is

1803
01:39:20,600 --> 01:39:23,160
Speaker 1: when you're watching a buck work a group of does

1804
01:39:24,400 --> 01:39:27,519
Speaker 1: and you see like he's particularly interested, like he sort

1805
01:39:27,560 --> 01:39:30,160
Speaker 1: of singled out a dough. He's very interested in his dough.

1806
01:39:30,200 --> 01:39:32,599
Speaker 1: He's singled out. But you see her every time he approaches.

1807
01:39:32,640 --> 01:39:33,080
Speaker 1: She runs.

1808
01:39:33,120 --> 01:39:35,200
Speaker 3: Every time he approaches, she runs, And you.

1809
01:39:35,240 --> 01:39:38,599
Speaker 1: Wonder, like, well, if it was a different buck, would

1810
01:39:38,640 --> 01:39:41,360
Speaker 1: she run every time? Like? Is she running because she's

1811
01:39:41,400 --> 01:39:43,200
Speaker 1: just not ready? Or is she running because she doesn't?

1812
01:39:43,320 --> 01:39:47,080
Speaker 1: Like she doesn't want that buck buyer? Because from whatever

1813
01:39:47,120 --> 01:39:50,160
Speaker 1: in his perspective, there's something very particular.

1814
01:39:49,600 --> 01:39:50,880
Speaker 3: About that dough.

1815
01:39:50,960 --> 01:39:54,880
Speaker 1: He's like hounding that dough, so he knows something's going on.

1816
01:39:55,120 --> 01:39:56,280
Speaker 3: But she's not receptive.

1817
01:39:58,439 --> 01:40:02,160
Speaker 4: I just don't think she's ready. She's just not She's close.

1818
01:40:02,360 --> 01:40:06,000
Speaker 1: Yeah, he knows she's close, but she's not that ready yet, right, yeh,

1819
01:40:06,280 --> 01:40:08,240
Speaker 1: got it? So she might not be making like a

1820
01:40:08,360 --> 01:40:11,479
Speaker 1: not you not you wait, I'm waiting for Dave or whatever.

1821
01:40:11,960 --> 01:40:16,759
Speaker 4: Yeah, I think she's just waiting to be receptive. Physiologically, yeah.

1822
01:40:18,160 --> 01:40:18,240
Speaker 1: Uh.

1823
01:40:18,360 --> 01:40:22,240
Speaker 6: There's a theory among whitetail hunters that if you have

1824
01:40:22,439 --> 01:40:24,519
Speaker 6: an old dominant buck, like a six and a half

1825
01:40:24,640 --> 01:40:28,519
Speaker 6: year old, when he gets killed, you've now created a

1826
01:40:28,600 --> 01:40:32,280
Speaker 6: vacuum where there's an opportunity for another big, mature buck

1827
01:40:32,320 --> 01:40:34,960
Speaker 6: to come in and take that home range and own

1828
01:40:35,000 --> 01:40:37,719
Speaker 6: that food source, own that betting area, own those doughs.

1829
01:40:38,120 --> 01:40:40,400
Speaker 6: Do you ever see that with your movement studies, that

1830
01:40:40,479 --> 01:40:43,599
Speaker 6: a big buck disappears until a new big buck moves in.

1831
01:40:44,760 --> 01:40:49,160
Speaker 4: No, I'm really interested in that. I do think that

1832
01:40:49,240 --> 01:40:52,439
Speaker 4: has a lot of logic and appeal, and I want

1833
01:40:52,520 --> 01:40:55,920
Speaker 4: that to happen because I think that's something as managers

1834
01:40:55,920 --> 01:40:59,880
Speaker 4: we can manipulate doing that, removing particular bucks and creating

1835
01:41:00,000 --> 01:41:03,000
Speaker 4: space for others to move in. Uh, we did not

1836
01:41:03,240 --> 01:41:06,080
Speaker 4: have enough data. Well, first of all, we didn't want

1837
01:41:06,080 --> 01:41:11,320
Speaker 4: to shoot all of our mature bucks. But to my knowledge,

1838
01:41:11,360 --> 01:41:14,800
Speaker 4: there's been no good experiment to demonstrate that. But but

1839
01:41:14,920 --> 01:41:17,640
Speaker 4: I would love to try it if we could. I

1840
01:41:17,920 --> 01:41:19,040
Speaker 4: do think it's logical.

1841
01:41:20,479 --> 01:41:22,759
Speaker 3: Yeah, some little bucks like now's my time to shine?

1842
01:41:22,840 --> 01:41:27,680
Speaker 6: Yeah? Yeah, Yeah, that's the best cornfield in the neighborhood.

1843
01:41:28,360 --> 01:41:29,439
Speaker 6: Does all beding here?

1844
01:41:30,640 --> 01:41:33,400
Speaker 3: Have you ever heard that bucks avoid certain kinds of

1845
01:41:33,400 --> 01:41:36,360
Speaker 3: cover when they're in velvet and they're more comfortable going

1846
01:41:36,400 --> 01:41:38,200
Speaker 3: into that cover once their antlers are hard?

1847
01:41:38,640 --> 01:41:38,800
Speaker 4: No?

1848
01:41:40,479 --> 01:41:42,240
Speaker 1: You you never heard that with elk and stuff like

1849
01:41:42,280 --> 01:41:42,720
Speaker 1: that too.

1850
01:41:43,320 --> 01:41:47,240
Speaker 4: Well, I don't think a lot about elk, but I'm

1851
01:41:47,280 --> 01:41:50,840
Speaker 4: biased with my time in South Texas and so man

1852
01:41:51,200 --> 01:41:53,840
Speaker 4: thorny up in that helicopter. I say, a lot of

1853
01:41:53,920 --> 01:41:57,360
Speaker 4: bucks and velvet going through. Yeah, the pair and the

1854
01:41:57,439 --> 01:41:58,800
Speaker 4: mesquite and got it.

1855
01:41:59,160 --> 01:42:00,920
Speaker 3: That's really a good testing ground.

1856
01:42:01,000 --> 01:42:03,320
Speaker 1: Yeah. Yeah, there's a price to pay for going through

1857
01:42:03,360 --> 01:42:05,000
Speaker 1: that mesquite.

1858
01:42:04,680 --> 01:42:07,439
Speaker 4: And the awareness that they have, you know, when you're

1859
01:42:07,560 --> 01:42:09,840
Speaker 4: you're pushing them with the helicopter and and there's a

1860
01:42:09,840 --> 01:42:12,720
Speaker 4: big mesquite branch coming up, and they know how to

1861
01:42:12,760 --> 01:42:15,320
Speaker 4: tilt their head just enough to get their antlers under it.

1862
01:42:15,360 --> 01:42:19,719
Speaker 4: And it's a thing of beauty to watch moose question.

1863
01:42:21,040 --> 01:42:22,080
Speaker 4: I mean, you can ask.

1864
01:42:21,960 --> 01:42:26,800
Speaker 1: If you're maybe there's a deer parallel. You're calling. You're

1865
01:42:26,800 --> 01:42:29,400
Speaker 1: calling to a moose. You're making cow calls to a moose.

1866
01:42:30,000 --> 01:42:33,320
Speaker 1: And then he comes from a mile away and he

1867
01:42:33,360 --> 01:42:38,080
Speaker 1: gets up, he comes just b line stops, his head's

1868
01:42:38,120 --> 01:42:39,680
Speaker 1: pointing towards you.

1869
01:42:39,680 --> 01:42:41,360
Speaker 3: You call, he comes, you call, he comes.

1870
01:42:41,360 --> 01:42:45,080
Speaker 1: He gets five hundred yards away and lays down, lays

1871
01:42:45,120 --> 01:42:47,080
Speaker 1: down for an hour, gets up, walks the other direction.

1872
01:42:48,960 --> 01:42:50,160
Speaker 6: Dawn's in his head.

1873
01:42:50,720 --> 01:42:56,120
Speaker 2: You were supposed to come to him.

1874
01:42:54,040 --> 01:42:54,439
Speaker 1: You think so?

1875
01:42:55,160 --> 01:42:55,759
Speaker 3: Was there.

1876
01:42:57,439 --> 01:42:59,840
Speaker 1: Was the wind in his face? No, there's no wind.

1877
01:43:00,080 --> 01:43:02,960
Speaker 1: Isn't a human thing it wasn't a human thing. Wind's

1878
01:43:03,000 --> 01:43:08,719
Speaker 1: totally wrong. He hadn't seen nothing. Yeah.

1879
01:43:08,840 --> 01:43:12,320
Speaker 4: My My only guess was there was no there was

1880
01:43:12,360 --> 01:43:16,120
Speaker 4: no visual queue to stimulate him coming any further.

1881
01:43:16,479 --> 01:43:19,240
Speaker 1: That would make sense because he's like, I'm looking at

1882
01:43:19,240 --> 01:43:23,280
Speaker 1: the whole hill, dude, there's nothing there. I'll cow standing there.

1883
01:43:23,880 --> 01:43:26,439
Speaker 1: Yeah you know that. Yeah.

1884
01:43:26,960 --> 01:43:28,519
Speaker 3: He's like at some points, like at some point I

1885
01:43:28,520 --> 01:43:29,160
Speaker 3: need to see.

1886
01:43:28,960 --> 01:43:31,080
Speaker 4: The cow, so you need a cow decoy.

1887
01:43:32,280 --> 01:43:34,120
Speaker 1: I've seen this sap two times in the same place,

1888
01:43:34,479 --> 01:43:36,600
Speaker 1: comes all that way, and it's lays down staring and

1889
01:43:36,640 --> 01:43:37,479
Speaker 1: gets up and leaves.

1890
01:43:39,439 --> 01:43:40,920
Speaker 2: Sounds like you've gotta be able to shoot at five

1891
01:43:41,000 --> 01:43:42,160
Speaker 2: hundred yards next time.

1892
01:43:42,280 --> 01:43:45,719
Speaker 1: We did one time got him, but it's it's thick

1893
01:43:45,800 --> 01:43:46,920
Speaker 1: and yeah, it's hard.

1894
01:43:50,439 --> 01:43:52,200
Speaker 2: If we have time, I could lay out the shirt

1895
01:43:52,280 --> 01:43:53,000
Speaker 2: or buck, but I know.

1896
01:43:52,960 --> 01:43:55,080
Speaker 1: We're a shirt. Yeah.

1897
01:43:55,160 --> 01:43:56,200
Speaker 3: He's big believer in us.

1898
01:43:56,560 --> 01:44:02,639
Speaker 2: That's not true. But I did re Valgeist a couple

1899
01:44:02,680 --> 01:44:07,439
Speaker 2: of his books, and he observed watching mule deer he

1900
01:44:07,640 --> 01:44:13,920
Speaker 2: felt he observed, yeah, that there were bucks that he

1901
01:44:13,960 --> 01:44:18,880
Speaker 2: would watch that would shirk the responsibility of breeding for

1902
01:44:19,080 --> 01:44:21,920
Speaker 2: many seasons in a row, and then all of a

1903
01:44:21,960 --> 01:44:26,439
Speaker 2: sudden year five year six come in there and because

1904
01:44:26,479 --> 01:44:29,840
Speaker 2: they had reserved all those resources for that many years

1905
01:44:29,880 --> 01:44:33,840
Speaker 2: and built up an extra whatever amount of body weight,

1906
01:44:33,880 --> 01:44:36,719
Speaker 2: bigger antlers or whatever, then they could come in.

1907
01:44:36,800 --> 01:44:39,920
Speaker 1: And rule the roost, just lay waste.

1908
01:44:40,280 --> 01:44:44,080
Speaker 2: That's one way to put it. Yeah, did you ever

1909
01:44:44,120 --> 01:44:47,640
Speaker 2: see that in your captive heard where the bucks would shirk.

1910
01:44:48,720 --> 01:44:52,439
Speaker 4: Not at that that scale. But so he valarious guys

1911
01:44:52,520 --> 01:44:57,080
Speaker 4: is talking about a multi year right, what we would

1912
01:44:57,160 --> 01:45:00,360
Speaker 4: see which we attributed to, but we don't know this,

1913
01:45:00,479 --> 01:45:05,800
Speaker 4: you know, buck personality in this case hormonally higher testosterone

1914
01:45:05,840 --> 01:45:10,080
Speaker 4: levels or something. But there were definitely some bucks that

1915
01:45:10,160 --> 01:45:14,080
Speaker 4: at the beginning of the rut they were absolute mad men.

1916
01:45:14,720 --> 01:45:17,080
Speaker 4: I mean, they wanted to fight. Everybody hated them. The

1917
01:45:17,120 --> 01:45:19,200
Speaker 4: dos hated them, other bucks hated them. They just want

1918
01:45:19,240 --> 01:45:23,960
Speaker 4: to fight, fight, fight, And their breeding success was always

1919
01:45:24,120 --> 01:45:29,400
Speaker 4: greater the first path and maybe even longer into the

1920
01:45:29,400 --> 01:45:32,799
Speaker 4: breeding season. So you know, we were able to enumerate

1921
01:45:32,840 --> 01:45:34,639
Speaker 4: how many fawns you know that they sired.

1922
01:45:35,040 --> 01:45:37,519
Speaker 1: He's a fighter, he's a fighter, and he does good

1923
01:45:37,800 --> 01:45:39,080
Speaker 1: in the beginning of the breeding season.

1924
01:45:39,200 --> 01:45:42,519
Speaker 4: Yeah, okay, yeah, yeah yeah, and then his body condition,

1925
01:45:42,920 --> 01:45:46,760
Speaker 4: all of that fighting begins to take its toll on him.

1926
01:45:46,960 --> 01:45:49,439
Speaker 4: Now keep in mind too, these are captive deer. They

1927
01:45:49,439 --> 01:45:53,479
Speaker 4: got ad lib food, So I mean he's avoiding eating.

1928
01:45:53,960 --> 01:45:57,519
Speaker 4: He is so consumed and obsessed with fighting and breeding.

1929
01:45:57,960 --> 01:46:01,000
Speaker 4: But when you get a month, six weeks whatever into it,

1930
01:46:01,200 --> 01:46:04,519
Speaker 4: his body condition begins to suffer. And now he starts

1931
01:46:04,600 --> 01:46:08,200
Speaker 4: getting his butt kicked by the more passive deer who

1932
01:46:08,280 --> 01:46:10,760
Speaker 4: now weighed even though they're the same age, even though

1933
01:46:10,760 --> 01:46:14,000
Speaker 4: they weigh twenty pounds more. Those guys may be the shirkers.

1934
01:46:14,280 --> 01:46:17,000
Speaker 4: Then they have higher breeding success later in the year.

1935
01:46:17,720 --> 01:46:20,760
Speaker 4: So we kind of saw that, but compressed within year.

1936
01:46:23,920 --> 01:46:27,760
Speaker 1: It's super interesting. But it's different than the idea that well,

1937
01:46:27,760 --> 01:46:29,720
Speaker 1: we told this the one deer biologist. I'm sure you're

1938
01:46:29,720 --> 01:46:31,720
Speaker 1: familiar with Jim half a finger. Oh yeah, yeah, So

1939
01:46:31,760 --> 01:46:34,000
Speaker 1: we told this the one deer biologist, and he felt

1940
01:46:34,040 --> 01:46:37,640
Speaker 1: that it was just like he felt, it was a

1941
01:46:37,760 --> 01:46:42,880
Speaker 1: very questionable approach from an evolutionary standpoint, to be that, like,

1942
01:46:43,000 --> 01:46:48,439
Speaker 1: you're alive now, you're sexually mature now, to put off

1943
01:46:48,600 --> 01:46:52,559
Speaker 1: breeding opportunity after breeding opportunity after breeding opportunity in order

1944
01:46:52,600 --> 01:46:56,120
Speaker 1: to really kick ass some year down the road just

1945
01:46:56,120 --> 01:46:59,479
Speaker 1: didn't make sense. Risky, Yeah, like, you know, it just

1946
01:46:59,479 --> 01:47:02,719
Speaker 1: didn't make sense as a way to really to to

1947
01:47:02,960 --> 01:47:06,800
Speaker 1: put more progeny on the landscape that your banking that. Well,

1948
01:47:07,520 --> 01:47:09,800
Speaker 1: I'm gonna have a hell of a year when I'm five. Yeah,

1949
01:47:09,840 --> 01:47:12,320
Speaker 1: and I'm taking off two, three and four.

1950
01:47:12,720 --> 01:47:14,320
Speaker 4: Yeah, I agree with that.

1951
01:47:14,439 --> 01:47:22,240
Speaker 7: Yeah, what are the the guest reasons for this? I mean,

1952
01:47:22,280 --> 01:47:26,599
Speaker 7: it's it's not I don't believe it's like a buck

1953
01:47:26,720 --> 01:47:29,920
Speaker 7: makes a conscious choice to do this. So, like, what

1954
01:47:30,080 --> 01:47:35,120
Speaker 7: would be the biological underpinnings if this were a thing.

1955
01:47:36,000 --> 01:47:40,320
Speaker 4: Yeah, my well, I don't remember what hilarious geist all

1956
01:47:40,360 --> 01:47:43,160
Speaker 4: of his reasoning, But I'm I'm trying to think about

1957
01:47:43,320 --> 01:47:45,599
Speaker 4: a mechanism of how that could work.

1958
01:47:45,760 --> 01:47:48,360
Speaker 7: And like onset of hormones and things.

1959
01:47:48,160 --> 01:47:55,439
Speaker 4: Are happening differing testosterone levels, and whereas the example I

1960
01:47:55,560 --> 01:47:59,559
Speaker 4: was giving with our data, I think it's within season,

1961
01:48:00,160 --> 01:48:05,080
Speaker 4: different timing in the surging of testosterone. But there's some

1962
01:48:05,120 --> 01:48:08,120
Speaker 4: great research out of Auburn University showing that there's a

1963
01:48:08,240 --> 01:48:12,439
Speaker 4: lot of variation by age class, and so it could

1964
01:48:12,439 --> 01:48:14,720
Speaker 4: be that those younger Bucks, and then there's gonna be

1965
01:48:14,800 --> 01:48:17,360
Speaker 4: variation within an age class where some have born, some

1966
01:48:17,400 --> 01:48:19,280
Speaker 4: have less, and so some of them, they just don't

1967
01:48:19,320 --> 01:48:21,080
Speaker 4: have a lot of testosterone. When they're two or three

1968
01:48:21,160 --> 01:48:26,920
Speaker 4: years of age. They're looking at this particular older, dominant, bigger, antlered,

1969
01:48:26,920 --> 01:48:31,400
Speaker 4: bigger bodied buck and maybe it's a survival strategy. Man,

1970
01:48:31,439 --> 01:48:35,000
Speaker 4: I'm not gonna risk it. But then later in life

1971
01:48:35,160 --> 01:48:39,439
Speaker 4: greater surgeon testosterone and they risk it and go for it.

1972
01:48:40,520 --> 01:48:41,719
Speaker 3: What do you wind up seeing?

1973
01:48:43,360 --> 01:48:45,200
Speaker 1: If you think of an old buck that gets a

1974
01:48:45,240 --> 01:48:49,200
Speaker 1: reputation with hunters as being like, he's so stealthy, he's shy,

1975
01:48:49,520 --> 01:48:51,799
Speaker 1: he's sly, right.

1976
01:48:55,160 --> 01:48:58,400
Speaker 3: That that's got to be real, right, But what is that?

1977
01:48:58,479 --> 01:48:58,760
Speaker 1: What is it?

1978
01:48:58,840 --> 01:49:00,240
Speaker 3: What do you think he's doing?

1979
01:49:00,360 --> 01:49:02,880
Speaker 1: What is he not doing? You know?

1980
01:49:03,080 --> 01:49:04,840
Speaker 3: When he gets to be that they just seem like

1981
01:49:05,280 --> 01:49:06,160
Speaker 3: they vanish.

1982
01:49:06,439 --> 01:49:10,320
Speaker 4: Yeah, right, And and to me that that's a really

1983
01:49:10,320 --> 01:49:13,519
Speaker 4: good question of ways you have to think about it.

1984
01:49:14,200 --> 01:49:19,439
Speaker 4: So is it that that buck has always been that

1985
01:49:19,600 --> 01:49:24,040
Speaker 4: way and the ones that were dumber were killed? So

1986
01:49:24,200 --> 01:49:25,840
Speaker 4: selection that's great going on?

1987
01:49:25,960 --> 01:49:27,000
Speaker 1: Yeah?

1988
01:49:27,160 --> 01:49:31,679
Speaker 4: Or are they literally learning and modifying their behavior over time?

1989
01:49:32,680 --> 01:49:35,479
Speaker 1: Like I love, I love what you're saying. I would

1990
01:49:35,520 --> 01:49:37,880
Speaker 1: have when I approached the question. I was approaching that

1991
01:49:37,920 --> 01:49:40,599
Speaker 1: he learned it, yeah, not that he's just always been paranoid.

1992
01:49:40,800 --> 01:49:44,160
Speaker 4: Yeah, it's probably a little bit of both as well,

1993
01:49:44,360 --> 01:49:49,160
Speaker 4: would be my guess. Yeah, so what what are they

1994
01:49:49,200 --> 01:49:52,840
Speaker 4: doing different? I think it's probably just being more perceptive

1995
01:49:52,960 --> 01:49:57,280
Speaker 4: and maybe being more slow in how they process what's

1996
01:49:57,320 --> 01:49:59,639
Speaker 4: going on. They're not as much of a risk taker,

1997
01:50:00,479 --> 01:50:02,600
Speaker 4: and so they're playing for the long game of like

1998
01:50:03,400 --> 01:50:05,960
Speaker 4: I might not breed as many doves within a year,

1999
01:50:06,080 --> 01:50:10,479
Speaker 4: but lifetime reproductive success I may win. Yeah, things like that.

2000
01:50:10,960 --> 01:50:16,400
Speaker 1: Yeah, there seems like there's some learn stuff like looking

2001
01:50:16,479 --> 01:50:20,080
Speaker 1: up in trees, you know what I mean, like learning

2002
01:50:20,160 --> 01:50:22,479
Speaker 1: like in certain areas. He's just like looking up, looking up,

2003
01:50:22,520 --> 01:50:27,639
Speaker 1: looking up, like because he's seen before, yeah, trees. Yeah,

2004
01:50:27,680 --> 01:50:30,479
Speaker 1: and like the coming out of the box, like a

2005
01:50:30,640 --> 01:50:32,840
Speaker 1: year and a half old buck probably hasn't figured out

2006
01:50:32,920 --> 01:50:36,519
Speaker 1: yet to like yeah look up. Yeah you know.

2007
01:50:37,560 --> 01:50:40,840
Speaker 4: Yeah, and so does that yearling buck have to live

2008
01:50:40,960 --> 01:50:45,559
Speaker 4: through a bad experience and then he's able to he's

2009
01:50:45,600 --> 01:50:47,439
Speaker 4: going to be looking from this point forward.

2010
01:50:47,560 --> 01:50:50,959
Speaker 1: Yeah, or a yearling bucks that are just so paranoid

2011
01:50:50,960 --> 01:50:52,480
Speaker 1: they're looking all around, And.

2012
01:50:52,240 --> 01:50:54,760
Speaker 2: It's good they learn it from their five year old mother.

2013
01:50:55,720 --> 01:50:56,439
Speaker 4: I think they do.

2014
01:50:56,680 --> 01:51:00,400
Speaker 1: Oh that's a good point too. Yeah, she's like the

2015
01:51:00,439 --> 01:51:04,200
Speaker 1: big cherry tree at the point, the point that juts

2016
01:51:04,200 --> 01:51:05,040
Speaker 1: out between the fields.

2017
01:51:05,080 --> 01:51:06,360
Speaker 3: Don't go by that cherry tree.

2018
01:51:06,400 --> 01:51:09,400
Speaker 1: You know. The other thing is specific cherry tree I

2019
01:51:09,400 --> 01:51:12,559
Speaker 1: grew up by with the deer dude, like the Ranella's

2020
01:51:12,680 --> 01:51:13,759
Speaker 1: are always in that tree.

2021
01:51:15,040 --> 01:51:18,559
Speaker 2: There's less of those bucks on the landscape too, so

2022
01:51:18,600 --> 01:51:22,559
Speaker 2: we just we have this perception that we see them less.

2023
01:51:22,640 --> 01:51:25,400
Speaker 2: So there's sneakier though, but it's just like a numbers

2024
01:51:25,439 --> 01:51:27,920
Speaker 2: game where you're just gonna see less of those bucks,

2025
01:51:28,200 --> 01:51:29,880
Speaker 2: even if they're moving just as much as the two

2026
01:51:29,960 --> 01:51:33,320
Speaker 2: year olds, because there's I don't know where percentage is

2027
01:51:33,360 --> 01:51:37,200
Speaker 2: in most populations, but yeah, much less.

2028
01:51:37,800 --> 01:51:42,800
Speaker 4: Yeah, all depends on punting rate and mortality. But but yeah,

2029
01:51:42,880 --> 01:51:46,200
Speaker 4: that's gonna be uh yeah. I mean even in a

2030
01:51:46,439 --> 01:51:50,000
Speaker 4: well managed population, less than twenty five percent of the

2031
01:51:50,040 --> 01:51:54,000
Speaker 4: bucks are going to be something like that. And that's

2032
01:51:54,040 --> 01:51:56,040
Speaker 4: just based on age. And then when you start adding

2033
01:51:56,040 --> 01:51:58,799
Speaker 4: in antler size, it's gonna be less than ten percent

2034
01:51:58,920 --> 01:52:01,519
Speaker 4: are gonna resemble something like that. So they're very rare.

2035
01:52:03,240 --> 01:52:05,400
Speaker 6: In twenty fifteen, I tried very hard to kill a

2036
01:52:05,439 --> 01:52:07,400
Speaker 6: cactus buck. And if you're listening, you don't know what

2037
01:52:07,400 --> 01:52:09,200
Speaker 6: that is. It's A cactus buck is a buck who

2038
01:52:09,240 --> 01:52:12,160
Speaker 6: does not shut his velvet, and sometimes he will grow

2039
01:52:12,320 --> 01:52:14,439
Speaker 6: a unique rack as a result of that. It could

2040
01:52:14,479 --> 01:52:17,840
Speaker 6: be a testosterone problem that his testicles never dropped. It

2041
01:52:17,840 --> 01:52:20,519
Speaker 6: could be that he was crossing a fence and ripped

2042
01:52:20,520 --> 01:52:24,120
Speaker 6: his sack open one time. And that cactus buck was

2043
01:52:24,240 --> 01:52:26,160
Speaker 6: very hard to kill because it seemed as though he

2044
01:52:26,160 --> 01:52:28,880
Speaker 6: didn't participate in the rut. He just like didn't loosen

2045
01:52:29,000 --> 01:52:32,439
Speaker 6: up and become reckless like the other bucks would. Have

2046
01:52:32,520 --> 01:52:35,080
Speaker 6: you ever looked at the movement of a cactus buck?

2047
01:52:35,640 --> 01:52:36,200
Speaker 4: Have not?

2048
01:52:36,760 --> 01:52:37,120
Speaker 1: Have not?

2049
01:52:37,360 --> 01:52:40,880
Speaker 4: We've never, I guess been lucky enough to have a

2050
01:52:40,920 --> 01:52:45,960
Speaker 4: collar on one, but a property that a hunt has one.

2051
01:52:46,360 --> 01:52:50,360
Speaker 4: Right now, He just got pictures from a puny buddy

2052
01:52:50,360 --> 01:52:53,040
Speaker 4: about a week ago that the cactus buck is back.

2053
01:52:53,120 --> 01:52:55,080
Speaker 4: So see there last year, It was there last year.

2054
01:52:55,120 --> 01:52:56,479
Speaker 6: What did you notice him due last year?

2055
01:52:57,280 --> 01:52:57,519
Speaker 5: He?

2056
01:52:57,720 --> 01:52:59,519
Speaker 4: Uh, he hung out with the doze.

2057
01:52:59,680 --> 01:53:00,600
Speaker 1: Yeah.

2058
01:53:00,680 --> 01:53:02,519
Speaker 6: Yeah, they just like don't participate in the room.

2059
01:53:02,560 --> 01:53:05,280
Speaker 4: Nope, not at all.

2060
01:53:05,720 --> 01:53:06,200
Speaker 6: Uh.

2061
01:53:07,080 --> 01:53:12,760
Speaker 1: The deer writer Pat Durkin, he had an observation where

2062
01:53:12,760 --> 01:53:15,600
Speaker 1: he when he was the editor Deer and Deer Hunting magazine,

2063
01:53:15,800 --> 01:53:21,200
Speaker 1: he profiled a great many big buck killers okay, and

2064
01:53:21,240 --> 01:53:25,920
Speaker 1: he had come to this kind of realization after a while.

2065
01:53:25,960 --> 01:53:30,040
Speaker 1: There's a lot of amazing big buck killers. They couldn't

2066
01:53:30,040 --> 01:53:31,880
Speaker 1: tell you what kind of tree their tree stands hanging in,

2067
01:53:32,680 --> 01:53:36,280
Speaker 1: meaning it's just like it's not like a wood's there's

2068
01:53:36,320 --> 01:53:38,559
Speaker 1: a point at which it's not like a woodsmanship thing.

2069
01:53:38,760 --> 01:53:41,439
Speaker 1: It's like they're just good at killing box. They're not

2070
01:53:41,680 --> 01:53:47,920
Speaker 1: generalist woodsmen. You know, do you ever feel like your research,

2071
01:53:49,960 --> 01:53:53,880
Speaker 1: like in real on the ground application as a deer hunter,

2072
01:53:53,960 --> 01:53:56,920
Speaker 1: does your research guide your activities or is like deer

2073
01:53:57,040 --> 01:54:01,640
Speaker 1: hunting is just deer hunting and it doesn't matter what

2074
01:54:01,680 --> 01:54:03,920
Speaker 1: you know to be true from all your projects.

2075
01:54:04,280 --> 01:54:11,040
Speaker 4: Yeah, yes, it does guides. Yeah, And a lot of

2076
01:54:11,040 --> 01:54:15,240
Speaker 4: that is about hunting pressure and thinking about and you know,

2077
01:54:15,320 --> 01:54:18,640
Speaker 4: this doesn't work everywhere in the US. In the southeast,

2078
01:54:18,720 --> 01:54:20,640
Speaker 4: you know a lot a lot of stand hunting, a

2079
01:54:20,640 --> 01:54:23,800
Speaker 4: lot of permanent stand hunting and so forth, and and

2080
01:54:24,000 --> 01:54:27,919
Speaker 4: just recognizing that deer know when you're on the property

2081
01:54:28,479 --> 01:54:32,600
Speaker 4: and it's and it's not gunshots, it's it's you being there,

2082
01:54:32,840 --> 01:54:37,080
Speaker 4: you being on an ATV. It's the smells, the sounds,

2083
01:54:37,120 --> 01:54:40,760
Speaker 4: all that they they know when you're there. And one

2084
01:54:40,800 --> 01:54:43,800
Speaker 4: thing that has really changed when we try to really

2085
01:54:43,840 --> 01:54:49,240
Speaker 4: advise now is when when you hunt, if you're going

2086
01:54:49,280 --> 01:54:52,480
Speaker 4: to hunt a particular stand, particular area, only go on

2087
01:54:52,560 --> 01:54:56,000
Speaker 4: the days where you're going to minimize the opportunity of

2088
01:54:56,080 --> 01:54:59,760
Speaker 4: bumping deer, because we know the research I talked about earlier.

2089
01:55:00,080 --> 01:55:02,919
Speaker 4: After a couple days and deer know you're on the property,

2090
01:55:03,360 --> 01:55:07,120
Speaker 4: they're going to start behaving differently. So doing whatever you

2091
01:55:07,160 --> 01:55:11,440
Speaker 4: can to minimize your footprint, so to speak, on the property.

2092
01:55:12,120 --> 01:55:15,760
Speaker 4: That's probably one of the biggest things. And then some

2093
01:55:15,880 --> 01:55:20,600
Speaker 4: really boring stuff that people roll their eyes about. But

2094
01:55:21,080 --> 01:55:26,080
Speaker 4: in terms of antler quality, herd condition, things like that density,

2095
01:55:26,800 --> 01:55:31,400
Speaker 4: deer density, dough harvest, stuff like that. I know how

2096
01:55:31,440 --> 01:55:34,840
Speaker 4: critically important that is. And people are trying to figure

2097
01:55:34,840 --> 01:55:36,880
Speaker 4: out what the heck's going on with our deer. The

2098
01:55:36,960 --> 01:55:39,320
Speaker 4: quality of the deer is down, we're doing all this,

2099
01:55:39,440 --> 01:55:41,440
Speaker 4: that and the other. You just got too many deer.

2100
01:55:42,120 --> 01:55:45,120
Speaker 4: You just have too many mouths relative to the amount

2101
01:55:45,160 --> 01:55:49,080
Speaker 4: of range that you have in the food supply. So

2102
01:55:49,840 --> 01:55:51,680
Speaker 4: pretty mundane. But stuff like that.

2103
01:55:51,840 --> 01:55:56,840
Speaker 1: Yeah, well, I could definitely picture management information, But just

2104
01:55:56,920 --> 01:55:59,880
Speaker 1: like how you go about where you're putting your stand,

2105
01:56:00,080 --> 01:56:02,240
Speaker 1: when you're out there what you're doing with the wind,

2106
01:56:02,720 --> 01:56:04,920
Speaker 1: But I could see with the stuff, with the research

2107
01:56:04,960 --> 01:56:08,400
Speaker 1: you've done around how they handle pressure, you might look

2108
01:56:08,440 --> 01:56:11,360
Speaker 1: at a place, look what everybody's up to, and then

2109
01:56:11,560 --> 01:56:13,560
Speaker 1: based on what you've seen, be like I think when

2110
01:56:13,600 --> 01:56:15,320
Speaker 1: the pressure hits, I think you're going to see more

2111
01:56:15,320 --> 01:56:17,080
Speaker 1: of this, You're gonna see less of that, and that

2112
01:56:17,160 --> 01:56:18,240
Speaker 1: might guide your movements.

2113
01:56:18,560 --> 01:56:21,440
Speaker 4: Yeah, what I do all the time. So, yeah, what

2114
01:56:21,480 --> 01:56:24,400
Speaker 4: we talked about approach, try to minimize your disturbance of

2115
01:56:24,440 --> 01:56:29,000
Speaker 4: the deer. I think about during the rut, I think

2116
01:56:29,040 --> 01:56:33,680
Speaker 4: about where are those dough focal groups on the landscape.

2117
01:56:34,200 --> 01:56:37,320
Speaker 4: What are going to be the movement or cover corridors

2118
01:56:37,680 --> 01:56:41,440
Speaker 4: that might link those areas up and so it won't

2119
01:56:41,440 --> 01:56:44,040
Speaker 4: be hunting on food. It's going to be hunting on

2120
01:56:44,120 --> 01:56:47,480
Speaker 4: a corridor. And then finally when you get to the

2121
01:56:47,520 --> 01:56:50,720
Speaker 4: post rut, I'm focusing on food. So the evidence is

2122
01:56:50,800 --> 01:56:54,080
Speaker 4: really really clear with that. When you get a month

2123
01:56:54,200 --> 01:56:56,600
Speaker 4: past the peak of the rut, they got to recover

2124
01:56:56,680 --> 01:56:59,640
Speaker 4: that twenty percent of their body weight. They're hungry, and

2125
01:56:59,720 --> 01:57:01,720
Speaker 4: food plots in my neck of the woods us a

2126
01:57:01,760 --> 01:57:02,680
Speaker 4: great place to haunt.

2127
01:57:03,240 --> 01:57:07,960
Speaker 3: M think, well, that spencer Newhart.

2128
01:57:08,600 --> 01:57:10,120
Speaker 6: Can I make two study requests?

2129
01:57:10,720 --> 01:57:13,080
Speaker 4: Absolutely well, okay one of them.

2130
01:57:13,360 --> 01:57:15,760
Speaker 6: I haunt a lot of places in the West where

2131
01:57:16,080 --> 01:57:20,920
Speaker 6: whitetail habitat and mule deer habitat overlap, but I never

2132
01:57:20,920 --> 01:57:23,120
Speaker 6: see them interact with each other. I'm always like pretty

2133
01:57:23,120 --> 01:57:25,040
Speaker 6: shocked that I could. I could, in the same hunt

2134
01:57:25,400 --> 01:57:27,840
Speaker 6: see a couple of white tails and a couple of

2135
01:57:27,920 --> 01:57:31,040
Speaker 6: mule deers, but they like don't have any social interaction

2136
01:57:31,840 --> 01:57:34,640
Speaker 6: anything to do with them. I would be very interested in,

2137
01:57:34,840 --> 01:57:36,480
Speaker 6: like if if you took that same study and you

2138
01:57:36,480 --> 01:57:40,160
Speaker 6: put a dough down a corral and she got to

2139
01:57:40,240 --> 01:57:42,360
Speaker 6: choose between a muley buck and a white tail buck,

2140
01:57:42,560 --> 01:57:45,760
Speaker 6: I imagine would be very high highly skewed for the white

2141
01:57:45,760 --> 01:57:47,960
Speaker 6: tail buck, like ninety plus percent, just based on what

2142
01:57:48,000 --> 01:57:51,080
Speaker 6: I've seen. But I don't know that I'm interested in

2143
01:57:51,120 --> 01:57:53,800
Speaker 6: anything like what a white tail buck and a mule

2144
01:57:53,880 --> 01:57:56,320
Speaker 6: deer buck would do if they encountered each other.

2145
01:57:56,480 --> 01:57:58,240
Speaker 1: That's a great thing. Or if you just took like

2146
01:57:59,400 --> 01:58:04,200
Speaker 1: if you just took like older arrays hmm, like order

2147
01:58:04,320 --> 01:58:07,240
Speaker 1: from a mild deer dough and estriss and odor from

2148
01:58:07,240 --> 01:58:09,880
Speaker 1: a white tail dough and estrus and like put it

2149
01:58:09,920 --> 01:58:11,840
Speaker 1: in front of both boxes. He like, oh, that's the

2150
01:58:11,880 --> 01:58:13,680
Speaker 1: white tail, you know, Yeah, that's a great.

2151
01:58:13,560 --> 01:58:16,720
Speaker 6: And in my observations, they interact as though like an

2152
01:58:16,760 --> 01:58:19,040
Speaker 6: elk in a white tail would interact. They just show

2153
01:58:19,120 --> 01:58:21,360
Speaker 6: no interest in each other. But I can't imagine it's

2154
01:58:21,360 --> 01:58:21,840
Speaker 6: that simple.

2155
01:58:21,880 --> 01:58:23,000
Speaker 3: You know, how you get funding for this?

2156
01:58:23,720 --> 01:58:25,520
Speaker 1: Remember how a few years ago you couldn't get funding

2157
01:58:25,520 --> 01:58:28,200
Speaker 1: for anything if it didn't have to do with climate. Yeah, okay,

2158
01:58:29,120 --> 01:58:31,839
Speaker 1: so pitch it like this. More and more white tails

2159
01:58:31,920 --> 01:58:34,640
Speaker 1: moving into more and more mildier country, mild deer are

2160
01:58:34,680 --> 01:58:36,840
Speaker 1: in a tough spot. Milder are probably going to be

2161
01:58:36,880 --> 01:58:39,880
Speaker 1: in a tougher spot with increased competition from white tails

2162
01:58:40,000 --> 01:58:43,240
Speaker 1: increase competition for elk. So go to the Mild Deer

2163
01:58:43,400 --> 01:58:46,680
Speaker 1: Foundation and be like, we need to understand more about

2164
01:58:46,720 --> 01:58:49,240
Speaker 1: as these as these white tails are colonizing more and

2165
01:58:49,280 --> 01:58:51,960
Speaker 1: more mildier country, how do they interact? We did, and

2166
01:58:52,000 --> 01:58:54,280
Speaker 1: here's all you're funding. Now there you go, got that problem.

2167
01:58:54,800 --> 01:58:56,960
Speaker 4: What do you think on like how they interact with

2168
01:58:57,000 --> 01:58:59,960
Speaker 4: each other in the wild. Don't know a lot about

2169
01:59:00,160 --> 01:59:02,280
Speaker 4: that because that's out of my that's side of my

2170
01:59:02,360 --> 01:59:05,760
Speaker 4: home range over there, But I do think it would

2171
01:59:05,800 --> 01:59:10,320
Speaker 4: be interesting to challenge a white tailed dough with a

2172
01:59:10,520 --> 01:59:15,360
Speaker 4: fully mature, large antlered mule deer and then a smaller,

2173
01:59:15,680 --> 01:59:21,360
Speaker 4: younger whitetail. Really, is it the species straw or the

2174
01:59:21,360 --> 01:59:25,160
Speaker 4: the phenotype of this is a good father, a good sire.

2175
01:59:25,120 --> 01:59:27,560
Speaker 6: And biology would tell us that she would be making

2176
01:59:27,560 --> 01:59:30,400
Speaker 6: a poor decision by going with the Muley right, because

2177
01:59:30,440 --> 01:59:34,280
Speaker 6: their offspring really fail with their escape mechanism, like they

2178
01:59:34,320 --> 01:59:39,280
Speaker 6: can't start or something like that is viable. I don't

2179
01:59:39,320 --> 01:59:40,280
Speaker 6: know if that's is that true?

2180
01:59:40,360 --> 01:59:41,960
Speaker 1: I think that I think it's like I think it's

2181
01:59:42,040 --> 01:59:43,760
Speaker 1: like a horse.

2182
01:59:43,400 --> 01:59:44,800
Speaker 3: And a donkey throwing a mule.

2183
01:59:45,040 --> 01:59:45,640
Speaker 6: I thought.

2184
01:59:48,080 --> 01:59:50,320
Speaker 1: They're viable. Okay, they're sexually viable.

2185
01:59:50,320 --> 01:59:51,800
Speaker 6: We're gonna learn when he does the study.

2186
01:59:52,320 --> 01:59:54,240
Speaker 1: You know what I'd throw into that study? Man, if

2187
01:59:54,280 --> 01:59:58,240
Speaker 1: you got like time to burn, man, if there's any

2188
01:59:58,400 --> 02:00:03,760
Speaker 1: like h if symmetry matters to dose joan, is there

2189
02:00:03,760 --> 02:00:09,720
Speaker 1: any like disadvantage to being atypical? It probably gets hard

2190
02:00:09,760 --> 02:00:12,400
Speaker 1: after a while to tease out all these little differences, though,

2191
02:00:12,440 --> 02:00:12,760
Speaker 1: don't it.

2192
02:00:12,920 --> 02:00:20,240
Speaker 4: Yeah, but you could manipulate it. It would be obvious. Yeah, yeah, nine, yeah, yeah,

2193
02:00:20,240 --> 02:00:22,800
Speaker 4: you could attach stuff to where it's really.

2194
02:00:22,920 --> 02:00:24,480
Speaker 3: He's got a club on one side.

2195
02:00:24,720 --> 02:00:26,560
Speaker 1: Yeah, yeah, you can do that.

2196
02:00:27,200 --> 02:00:29,920
Speaker 6: The other study I'd be interested in is a deer's

2197
02:00:30,000 --> 02:00:32,920
Speaker 6: response to yellow soybeans. I've been told all my life,

2198
02:00:33,000 --> 02:00:34,680
Speaker 6: and I feel like I've maybe witnessed it some but

2199
02:00:34,720 --> 02:00:37,080
Speaker 6: I don't know if I'm witnessing it because I'm supposed

2200
02:00:37,120 --> 02:00:39,680
Speaker 6: to witness it. But a deer given the choice in

2201
02:00:39,760 --> 02:00:41,960
Speaker 6: a in a big old soybean field, if there's some

2202
02:00:42,200 --> 02:00:45,800
Speaker 6: green beans, some yellow beans, and some brown beans, which

2203
02:00:45,840 --> 02:00:48,360
Speaker 6: the yellow is the ripening stage going from green to brown,

2204
02:00:48,800 --> 02:00:51,160
Speaker 6: they won't pick the yellow ones. They just taste worse,

2205
02:00:51,760 --> 02:00:55,000
Speaker 6: taste worse. Is that something you've heard seen?

2206
02:00:56,000 --> 02:01:00,840
Speaker 4: No, I haven't, but I think that's logical. So turning

2207
02:01:00,920 --> 02:01:03,280
Speaker 4: yellow from the desiccation that they're growing.

2208
02:01:05,160 --> 02:01:08,360
Speaker 1: Sounds like yeah, good? Like that. You know. I got

2209
02:01:08,360 --> 02:01:11,200
Speaker 1: some friends that are songwriters, and over the years, I've

2210
02:01:11,240 --> 02:01:12,720
Speaker 1: learned that they just do not want to hear our

2211
02:01:12,760 --> 02:01:16,880
Speaker 1: song ideas. But they don't even when you try to

2212
02:01:16,880 --> 02:01:18,280
Speaker 1: do it like a joke and give them a song

2213
02:01:18,320 --> 02:01:19,960
Speaker 1: idea but you're serious, but you're trying to act like

2214
02:01:19,960 --> 02:01:21,440
Speaker 1: it's a joke, they don't want to hear it.

2215
02:01:21,720 --> 02:01:25,840
Speaker 4: I like how you use the word hour. But but

2216
02:01:26,240 --> 02:01:28,400
Speaker 4: do they give you the obligatory that's a good.

2217
02:01:29,840 --> 02:01:32,120
Speaker 3: Just nothing to it. Do you like hearing study ideas?

2218
02:01:32,840 --> 02:01:38,520
Speaker 1: I do. Snow, you got a pile of.

2219
02:01:39,360 --> 02:01:42,160
Speaker 4: Some of them. Some of them can be really cuckoo.

2220
02:01:43,040 --> 02:01:46,040
Speaker 4: So you're you know, you're given a seminar and you

2221
02:01:46,080 --> 02:01:50,840
Speaker 4: always have what you ought to do? Is sure that

2222
02:01:50,880 --> 02:01:51,480
Speaker 4: can get old?

2223
02:01:53,360 --> 02:01:54,040
Speaker 1: What else? Man?

2224
02:01:54,160 --> 02:01:55,120
Speaker 3: I could go on all day.

2225
02:01:55,600 --> 02:01:57,680
Speaker 6: They just like to cap it off. If if hunters

2226
02:01:57,720 --> 02:02:00,000
Speaker 6: want to take what you've seen in your movement still

2227
02:02:00,000 --> 02:02:01,640
Speaker 6: but he's an apply it to the rut this year?

2228
02:02:01,800 --> 02:02:02,760
Speaker 6: What does that look like?

2229
02:02:02,920 --> 02:02:03,160
Speaker 1: Yeah?

2230
02:02:03,200 --> 02:02:05,200
Speaker 6: Yeah, how can they be more successful?

2231
02:02:06,840 --> 02:02:11,520
Speaker 4: So if you again, if you're going after a target buck,

2232
02:02:11,720 --> 02:02:16,640
Speaker 4: a particular buck, your greater opportunity for him to demonstrate

2233
02:02:17,000 --> 02:02:19,320
Speaker 4: site fidelity. So if you know where he's hanging out,

2234
02:02:19,920 --> 02:02:23,360
Speaker 4: you need to do that in the pre rut. If

2235
02:02:23,400 --> 02:02:26,160
Speaker 4: on the other hand, you are just gonna there's a

2236
02:02:26,200 --> 02:02:28,200
Speaker 4: lot of big bucks in the area. I just want

2237
02:02:28,200 --> 02:02:31,640
Speaker 4: to increase my odds for intercepting one that's going to

2238
02:02:31,720 --> 02:02:33,960
Speaker 4: be during the peak of the rut, a.

2239
02:02:33,840 --> 02:02:36,040
Speaker 6: Pre rut window being like late October.

2240
02:02:36,720 --> 02:02:39,000
Speaker 4: Well it depends when you is, say it's like a.

2241
02:02:39,080 --> 02:02:40,960
Speaker 6: November fifteen rut, that's the peak rut.

2242
02:02:41,040 --> 02:02:44,320
Speaker 4: Yeah, so let's go one month or greater before the

2243
02:02:44,360 --> 02:02:47,600
Speaker 4: peak of the rut. Okay, yeah, so like October fifteen

2244
02:02:47,680 --> 02:02:50,440
Speaker 4: then in your neck of the woods. Yeah okay, yeah,

2245
02:02:50,440 --> 02:02:51,160
Speaker 4: that'd be about right.

2246
02:02:51,440 --> 02:02:54,360
Speaker 1: Okay, So just make sure I'm track what you're saying,

2247
02:02:54,400 --> 02:02:56,600
Speaker 1: Like when we when you pick the November fifteenth, we

2248
02:02:56,640 --> 02:02:59,120
Speaker 1: would agree that peak rut is sort of like the

2249
02:02:59,200 --> 02:03:02,640
Speaker 1: day when you have the highest relative number of doughs

2250
02:03:02,640 --> 02:03:05,400
Speaker 1: in estres. That's what is that fair to define peak

2251
02:03:05,440 --> 02:03:05,960
Speaker 1: rut that way?

2252
02:03:06,360 --> 02:03:09,080
Speaker 4: Yeah, but rather than day, we might say over a

2253
02:03:09,120 --> 02:03:12,960
Speaker 4: two week, over a two week period, about half of

2254
02:03:13,040 --> 02:03:16,560
Speaker 4: the does have been into estres. So yes, that is

2255
02:03:16,600 --> 02:03:19,800
Speaker 4: going to be the series of days where the greatest

2256
02:03:19,840 --> 02:03:20,920
Speaker 4: number and greatest proportion.

2257
02:03:21,480 --> 02:03:23,880
Speaker 1: So there's a there's a two week window, like if

2258
02:03:23,920 --> 02:03:26,640
Speaker 1: you take a like just generally with white tail deer,

2259
02:03:26,680 --> 02:03:29,760
Speaker 1: there's a two week window in which fifty percent of

2260
02:03:29,760 --> 02:03:32,640
Speaker 1: the does come into estres. And we're going to declare

2261
02:03:32,680 --> 02:03:34,360
Speaker 1: that two week window peak rut.

2262
02:03:34,560 --> 02:03:38,240
Speaker 4: Yeah, you know, if it's a synchronized rut and so forth.

2263
02:03:38,480 --> 02:03:41,200
Speaker 1: Yeah, generally speaking, So that that's kind of funny because

2264
02:03:41,200 --> 02:03:43,960
Speaker 1: then when you hear guys killing some giant that no

2265
02:03:44,000 --> 02:03:48,920
Speaker 1: one has ever seen, never showed up on their cameras, like,

2266
02:03:49,040 --> 02:03:52,320
Speaker 1: that's that, dude, it's cruise, an excursion, he's an excursion book. Yeah,

2267
02:03:52,360 --> 02:03:55,520
Speaker 1: he excurreted off your place. Yeah, and excirted on some

2268
02:03:55,600 --> 02:03:56,200
Speaker 1: other goal.

2269
02:03:56,240 --> 02:03:57,480
Speaker 4: Somebody else and they got him.

2270
02:03:57,680 --> 02:03:58,720
Speaker 1: Yeah, exactly right.

2271
02:04:00,640 --> 02:04:03,280
Speaker 4: And then if you didn't get them pre rut, if

2272
02:04:03,280 --> 02:04:05,880
Speaker 4: you didn't get them during the rut, hunt food in

2273
02:04:05,920 --> 02:04:11,400
Speaker 4: the post rut, okay, yeah, and during the rut you

2274
02:04:11,480 --> 02:04:16,160
Speaker 4: might want to here's an interesting finding. We actually looked

2275
02:04:16,200 --> 02:04:19,480
Speaker 4: at food plot use, two different types of food plot use,

2276
02:04:21,280 --> 02:04:23,920
Speaker 4: and so on our study area. By the way, our

2277
02:04:23,920 --> 02:04:27,400
Speaker 4: study area was fifty to sixty thousand acres, so pretty big,

2278
02:04:27,440 --> 02:04:30,600
Speaker 4: pretty big footprint, and we had every making model of

2279
02:04:30,640 --> 02:04:32,800
Speaker 4: food plot you could have. We had quarter acre food

2280
02:04:32,800 --> 02:04:36,440
Speaker 4: plots acre all the way up to twenty acre food plots,

2281
02:04:36,920 --> 02:04:39,640
Speaker 4: and so we wanted to look at is there any

2282
02:04:39,800 --> 02:04:45,560
Speaker 4: food plot size that deer would come to that disproportionately and.

2283
02:04:45,520 --> 02:04:48,760
Speaker 2: So the size you weren't varying what you were growing.

2284
02:04:50,000 --> 02:04:54,760
Speaker 4: Good, good question. We had so many food plots that

2285
02:04:54,800 --> 02:04:57,160
Speaker 4: we had to assume that some of them had wheat

2286
02:04:57,160 --> 02:04:59,680
Speaker 4: and clover some of them had brassicas. We had to

2287
02:04:59,680 --> 02:05:02,920
Speaker 4: assume all that kind of smoothed, doubt that the actual

2288
02:05:03,080 --> 02:05:06,400
Speaker 4: plantings within it. But yes, it was just size and

2289
02:05:06,920 --> 02:05:12,920
Speaker 4: what we found. Even though two times the amount of

2290
02:05:12,960 --> 02:05:18,200
Speaker 4: like the smaller one acre food plots, the sweet spot

2291
02:05:18,360 --> 02:05:23,880
Speaker 4: was three four five acres. Really they disproportionately selected that

2292
02:05:24,280 --> 02:05:25,440
Speaker 4: size of plot.

2293
02:05:26,040 --> 02:05:27,360
Speaker 1: That feels secure to them.

2294
02:05:27,480 --> 02:05:32,560
Speaker 4: So why why would they do that? And so we

2295
02:05:33,040 --> 02:05:38,160
Speaker 4: think it's because what do small food plots not provide

2296
02:05:38,560 --> 02:05:42,360
Speaker 4: over the course of the hunting season. What happens to them?

2297
02:05:42,680 --> 02:05:43,520
Speaker 2: They get eaten out.

2298
02:05:43,440 --> 02:05:47,040
Speaker 4: They get over brows, they get overwhelmed. So not only

2299
02:05:47,080 --> 02:05:49,240
Speaker 4: because of the size of it and the number of

2300
02:05:49,320 --> 02:05:52,120
Speaker 4: deer on it. You don't have as many hours of

2301
02:05:52,400 --> 02:05:55,640
Speaker 4: photosynthesis going on because the smaller in the shade all that.

2302
02:05:56,040 --> 02:05:58,960
Speaker 4: Then you get to this three four five acre. Now

2303
02:05:59,000 --> 02:06:03,120
Speaker 4: you've got a big area. You're now producing more forage

2304
02:06:03,440 --> 02:06:07,680
Speaker 4: per acre, and now we've got a social aspect of

2305
02:06:07,720 --> 02:06:10,160
Speaker 4: it too, which I'll get to in a second. But

2306
02:06:10,200 --> 02:06:12,680
Speaker 4: then after that it was diminishing returns. So we didn't

2307
02:06:12,680 --> 02:06:14,920
Speaker 4: see anything greater of a ten acre plot versus a

2308
02:06:14,920 --> 02:06:15,680
Speaker 4: three acre plot.

2309
02:06:17,080 --> 02:06:22,320
Speaker 1: Oh okay, they didn't prefer five over twenty.

2310
02:06:22,360 --> 02:06:22,800
Speaker 4: They did.

2311
02:06:23,320 --> 02:06:24,080
Speaker 1: I'm sorry they did.

2312
02:06:24,160 --> 02:06:26,760
Speaker 4: Yeah, yeah, yeah, And so we saw a big drop

2313
02:06:26,800 --> 02:06:32,560
Speaker 4: off in relative to their availability on the landscape. Deer

2314
02:06:32,600 --> 02:06:38,320
Speaker 4: were disproportionately choosing those plots over the ones smaller and

2315
02:06:38,400 --> 02:06:39,440
Speaker 4: the ones larger.

2316
02:06:39,600 --> 02:06:41,640
Speaker 1: What's the argument against a bigger plot? Do you think

2317
02:06:41,760 --> 02:06:42,360
Speaker 1: in his head?

2318
02:06:43,640 --> 02:06:46,600
Speaker 4: I think you reach a particular size and there's just

2319
02:06:46,640 --> 02:06:49,640
Speaker 4: only so many deer in the area or are gonna

2320
02:06:49,760 --> 02:06:50,320
Speaker 4: use it.

2321
02:06:51,400 --> 02:06:52,800
Speaker 6: And I would say they're vulnerable.

2322
02:06:53,040 --> 02:06:59,240
Speaker 1: There's it's like a like like why do you feel

2323
02:06:59,760 --> 02:07:06,440
Speaker 1: a avoids? Like why is he avoiding a big food plot?

2324
02:07:06,960 --> 02:07:09,280
Speaker 4: I see what you mean. Now, yeah, he doesn't want

2325
02:07:09,280 --> 02:07:11,680
Speaker 4: to go into the middle of a big, old ten

2326
02:07:11,800 --> 02:07:16,240
Speaker 4: or twenty acres. Yeah, because that's security possibly, so yes, exposure.

2327
02:07:15,800 --> 02:07:16,680
Speaker 1: It's exposed.

2328
02:07:16,760 --> 02:07:22,080
Speaker 4: Yeah. So when you look at during the year, if

2329
02:07:22,120 --> 02:07:27,440
Speaker 4: you look at the number of visits per day, you

2330
02:07:27,440 --> 02:07:31,040
Speaker 4: will see that they are visiting more during the rut.

2331
02:07:31,680 --> 02:07:33,680
Speaker 4: So you think about how we analyze the data, it's

2332
02:07:33,720 --> 02:07:35,920
Speaker 4: just ding, did he visit the plot or not? Yes,

2333
02:07:36,000 --> 02:07:39,800
Speaker 4: and you tally those up. So they're visiting those food

2334
02:07:39,840 --> 02:07:43,640
Speaker 4: plots more during the day. So some of that is food,

2335
02:07:44,200 --> 02:07:47,800
Speaker 4: some of it is also socially. I mean they're cruising

2336
02:07:47,480 --> 02:07:50,960
Speaker 4: looking for dose. When you get to the end of

2337
02:07:51,040 --> 02:07:54,080
Speaker 4: the year, during the post rut, they will have just

2338
02:07:54,120 --> 02:07:59,000
Speaker 4: as many or less visits, but their duration is longer.

2339
02:07:59,520 --> 02:08:02,960
Speaker 4: So now they are visiting for the purpose of forage

2340
02:08:03,480 --> 02:08:05,640
Speaker 4: and not socially looking for a female.

2341
02:08:05,760 --> 02:08:10,880
Speaker 1: Yep, cow man. No, it's a lot of great information.

2342
02:08:13,840 --> 02:08:16,200
Speaker 1: I got such a good study. I had to say

2343
02:08:16,960 --> 02:08:17,960
Speaker 1: so hard to explain.

2344
02:08:19,360 --> 02:08:22,000
Speaker 2: I'm like a post book right now, and all I

2345
02:08:22,000 --> 02:08:23,760
Speaker 2: can think about is some food. And we got to

2346
02:08:23,800 --> 02:08:25,440
Speaker 2: do this trivia in like thirty minutes.

2347
02:08:26,200 --> 02:08:27,680
Speaker 3: Dude, thanks for coming on and wrap it up.

2348
02:08:27,760 --> 02:08:32,920
Speaker 1: Yeah, man, I love your the extension, like, tell people

2349
02:08:33,000 --> 02:08:34,920
Speaker 1: go how to go find your work and to see exauce.

2350
02:08:34,960 --> 02:08:37,120
Speaker 1: I mean, you got you have your academic publications, but

2351
02:08:37,120 --> 02:08:39,960
Speaker 1: you're also producing stuff for just guys like us. Yeah,

2352
02:08:40,000 --> 02:08:42,000
Speaker 1: so tell people how to go, how to go kind

2353
02:08:42,000 --> 02:08:45,000
Speaker 1: of find some of your infographics.

2354
02:08:44,000 --> 02:08:48,360
Speaker 4: And yeah, a couple places so you can go to

2355
02:08:48,400 --> 02:08:51,760
Speaker 4: the Msudar lab dot com. That's our website that has

2356
02:08:51,880 --> 02:08:55,200
Speaker 4: all of these publications on there. We also do a

2357
02:08:55,200 --> 02:08:58,960
Speaker 4: lot of this on social media, so we're on Facebook, Instagram,

2358
02:08:59,320 --> 02:09:01,720
Speaker 4: we have a YouTube channel with a lot of different videos,

2359
02:09:01,800 --> 02:09:04,960
Speaker 4: podcasts where we talk about this type of stuff. Podcast

2360
02:09:05,080 --> 02:09:10,920
Speaker 4: is Deer University, so MSU Deer Lab, the website, social media,

2361
02:09:11,600 --> 02:09:14,000
Speaker 4: uh YouTube. You ought to be able to get us.

2362
02:09:14,560 --> 02:09:18,160
Speaker 4: If it's on the private side outside of the university.

2363
02:09:18,240 --> 02:09:21,040
Speaker 4: If you're looking for help with land management, go to

2364
02:09:21,080 --> 02:09:24,560
Speaker 4: Wildlife Investments dot com and there's a lot of us there.

2365
02:09:24,560 --> 02:09:28,160
Speaker 4: A little company consulting work that's for consulting work.

2366
02:09:28,200 --> 02:09:31,920
Speaker 1: Yeah, that's great, man. And on that consulting work you

2367
02:09:32,000 --> 02:09:34,919
Speaker 1: kind of you probably do. You go survey the property,

2368
02:09:35,000 --> 02:09:36,720
Speaker 1: talk about what's going on, what could be better?

2369
02:09:37,000 --> 02:09:43,920
Speaker 4: Right, what strategies, habitat habitat management, deer ducks, turkey, quail,

2370
02:09:44,240 --> 02:09:47,040
Speaker 4: whatever you want with wildlife management. All right, we've got

2371
02:09:47,080 --> 02:09:47,760
Speaker 4: an expert.

2372
02:09:47,560 --> 02:09:54,200
Speaker 1: To help you. Right again, doctor Bronson Strickland from University

2373
02:09:54,200 --> 02:09:55,560
Speaker 1: of Mississippi.

2374
02:09:56,880 --> 02:09:58,680
Speaker 4: Hale State, Mississippi State.

2375
02:09:58,560 --> 02:10:01,960
Speaker 1: University, Mississippi State University. We have that same problem in

2376
02:10:02,000 --> 02:10:03,680
Speaker 1: Michigan because we've got U of M and M s

2377
02:10:03,760 --> 02:10:04,760
Speaker 1: U well.

2378
02:10:08,760 --> 02:10:13,440
Speaker 2: With the M specific with them specifically specifically.

2379
02:10:13,600 --> 02:10:17,520
Speaker 1: And then the the extension material is like the extension

2380
02:10:17,880 --> 02:10:20,000
Speaker 1: piece I was talking about that shows like that kind

2381
02:10:20,000 --> 02:10:23,920
Speaker 1: of puts your study on the lunar stuff. That's that's uh,

2382
02:10:24,160 --> 02:10:30,280
Speaker 1: that's a Michigan State University Extension pieced a Mississippi State

2383
02:10:30,360 --> 02:10:35,560
Speaker 1: University Extension piece that puts down it's a great graphic

2384
02:10:36,040 --> 02:10:41,640
Speaker 1: because it puts down what people think, the idiosyncrasies of

2385
02:10:41,640 --> 02:10:46,000
Speaker 1: what people think, what's found, and then it puts it

2386
02:10:46,040 --> 02:10:49,600
Speaker 1: into all these like percentages, and then whatever kind of

2387
02:10:49,640 --> 02:10:53,240
Speaker 1: guy you are, moon underfoot, moon overhead, full moon rising,

2388
02:10:53,400 --> 02:10:57,240
Speaker 1: full moon setting, you can go and track every possible

2389
02:10:57,360 --> 02:10:58,959
Speaker 1: variation and find out.

2390
02:11:01,040 --> 02:11:04,760
Speaker 3: Yards per hour all that, and you can go put

2391
02:11:04,760 --> 02:11:06,400
Speaker 3: your mind at ease about what's going on.

2392
02:11:06,560 --> 02:11:09,360
Speaker 1: That's right. I mean, it's very It is a when

2393
02:11:09,400 --> 02:11:11,960
Speaker 1: you look through it. I spent thirty minutes staring at

2394
02:11:11,960 --> 02:11:17,000
Speaker 1: it today. It is a very convincing portrayal of like

2395
02:11:17,520 --> 02:11:19,080
Speaker 1: looking at something quite thoroughly.

2396
02:11:19,280 --> 02:11:19,760
Speaker 6: Yeah.

2397
02:11:19,840 --> 02:11:21,080
Speaker 1: Yeah, it's a great piece.

2398
02:11:21,200 --> 02:11:21,880
Speaker 4: Appreciate that.

2399
02:11:21,920 --> 02:11:22,160
Speaker 1: Thank you.

2400
02:11:22,240 --> 02:11:25,160
Speaker 3: In poster form, it would take up a lot of walls.

2401
02:11:24,880 --> 02:11:26,760
Speaker 4: It sure would, it sure would.

2402
02:11:27,080 --> 02:11:30,640
Speaker 1: Yeah, but you might think about a small poster. We will, yeah,

2403
02:11:30,920 --> 02:11:33,120
Speaker 1: with the real salient points in it next time.

2404
02:11:33,280 --> 02:11:35,600
Speaker 3: Okay, thank you very much for coming on.

2405
02:11:36,840 --> 02:11:39,200
Speaker 1: We're all going to be, if not better deer hunters, better,

2406
02:11:39,240 --> 02:11:41,200
Speaker 1: Dear observers now, thank

2407
02:11:41,240 --> 02:11:42,560
Speaker 2: You, thanks Ronson,