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Speaker 1: Welcome to the Wired to Hunt podcast, your home for

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Speaker 1: deer hunting news, stories and strategies, and now your host,

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Speaker 1: Mark Kenyon. Welcome to the Wired to Hunt podcast. I'm

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Speaker 1: your host, Mark Kenyon in this episode number seventy eight.

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Speaker 1: Today in the show, we're joined by certified wildlife biologist

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Speaker 1: Matt Ross, and we're discussing the science of the white

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Speaker 1: tail rut. All right, welcome to the Wired to Hunt podcast,

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Speaker 1: brought to you by Sick of Gear, and today we're

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Speaker 1: diving straight into the heart of the topic that I

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Speaker 1: know is on the top of all of your our

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Speaker 1: minds and mine and Dan's the white tail rut. And

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Speaker 1: our guest today is a wildlife biologist and Quality Deer

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Speaker 1: Management Association staff member, Matt Ross. And we brought Matt

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Speaker 1: in the show today to help us dive into the

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Speaker 1: science of the white tail rut. And you know, we

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Speaker 1: hear a lot about different theories and ideas about the rut,

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Speaker 1: and a lot of that is just kind of one

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Speaker 1: off stuff thought up by a random hunter or quote

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Speaker 1: unquote expert, but there actually is some real data and

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Speaker 1: research that's been done across the country related to white

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Speaker 1: tales and their behavior at this time of year, and

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Speaker 1: Matt is an expert on this stuff as he studied

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Speaker 1: many of the reports and research projects that have been

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Speaker 1: done related to deer and the rut. So today he's

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Speaker 1: going to share with us everything he's learned on that front.

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Speaker 1: But before we do give him out a call, as

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Speaker 1: we like to do every week, staying right on task

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Speaker 1: and on topic, we're going to give you a low

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Speaker 1: down on what's happening with me and our co host

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Speaker 1: Dan Johnson. So, Dan, I hear you've been seeing some bucks. Well,

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Speaker 1: let me talk about what I had for lunch first. Yeah,

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Speaker 1: let's get to that. Wait wait, wait, wait wait, speaking

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Speaker 1: of food, Speaking of food, can I just say I

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Speaker 1: posted a picture diet ship. Yeah. I posted a picture

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Speaker 1: of the junk food that I bought for my all

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Speaker 1: day sits during the rug and I get, you know,

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Speaker 1: easy to eat package stuff that will get me through

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Speaker 1: snacking throughout the whole day. So, I got some Mountain dew,

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Speaker 1: I've got some cheese it's I've got some oreos, I've

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Speaker 1: got apples, and I've got peanut butter and jelly for

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Speaker 1: you crunchy peanut butter. Um. So I posted a picture

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Speaker 1: of all my snacks, and then people just came out

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Speaker 1: of the woodwork slang me saying how unhealthy I am

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Speaker 1: and how I can do better, and how they don't

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Speaker 1: want me to die because they want to keep listening

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Speaker 1: to the podcast, and where's my diabetics testing kit? And

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Speaker 1: all sorts of up. I got lamb basted, Dan, I

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Speaker 1: tell you, it's almost like you went on Archery Talk

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Speaker 1: and asked asked for product information. That's what happens when

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Speaker 1: I whenever I go anywhere, it's like, oh man, that sucks,

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Speaker 1: or stupid like Mark Kenyon. Maybe they're just worried for

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Speaker 1: your well being. I mean, I appreciate that if that's

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Speaker 1: the case, But that's the last time I post. Any

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Speaker 1: pictures are laid to the food I eat. No way,

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Speaker 1: no what you gotta keep doing it every year every year. No,

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Speaker 1: I want you to take a picture every every meal

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Speaker 1: you eat, like when you're stuffing a twinkie slowly in

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Speaker 1: your mouth. I might do that careful to ask for

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Speaker 1: that would be awesome if there was if you had

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Speaker 1: food in that picture that was not like carryer friendly,

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Speaker 1: like you had a tenderloin, or like you had mashed

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Speaker 1: potatoes and gravy. That would be amazing. If you could

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Speaker 1: bring a little ziploc bag if mashed potatoes and venison

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Speaker 1: to eat in the stand, that would be a heck

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Speaker 1: of an all day set right there. Just imagine the

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Speaker 1: scent profile that that would create. And it's just like,

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Speaker 1: what the hell is there a KFC in the woods

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Speaker 1: because I'm heading there. But back to, uh, what you

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Speaker 1: were going to talk about before I circus on tangent? Yeah,

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Speaker 1: what's going on? Oh man, Well, I'm just gonna tell

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Speaker 1: you a little bit about my weekend. Uh long story short.

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Speaker 1: Let's see, I've gotten to um a stand where like

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Speaker 1: this year some a little bit of my focus is

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Speaker 1: annual patterns, right based off you know, trail cameras for

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Speaker 1: you know, trail camera information and um information that I've

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Speaker 1: received from sitting in the stand and trying to put

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Speaker 1: myself in those positions this year, UM, because I'll be honest,

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Speaker 1: I'm behind on my trail cameras. I only have one

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Speaker 1: maybe two out right now, and I'm just I've been

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Speaker 1: extra busy with the family. My wife's business is picking

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Speaker 1: up and that means that I have to do more

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Speaker 1: tasks around the house so she can work, and I've

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Speaker 1: just I haven't had to. I have not hunted as

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Speaker 1: much as I wanted to, so I've been thinking about this. Yeah,

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Speaker 1: I think we got to talk to Sarah. She needs

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Speaker 1: to quit this side job because it's interfering with your

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Speaker 1: hunting time. Dan's right. Let me, let me make sure

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Speaker 1: I'm wearing a mouth guard when you tell her that

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Speaker 1: she'll she'll or she'll low blow you. She will, she

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Speaker 1: will kick. She would kick your ass, she'd kick my ass.

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Speaker 1: She seems like the type that I don't want to

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Speaker 1: mess with her. She's a fire, but I love her

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Speaker 1: to death. She won't listen to this, so it doesn't

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Speaker 1: really sorry continue so anyway. Um, So that's as far

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Speaker 1: as anal patterns are concerned, That's what I've been trying

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Speaker 1: trying to do. So I went to a location off

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Speaker 1: of Marsh where last year I was getting daylight pictures

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Speaker 1: at the beginning of a cold front. So it just

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Speaker 1: so so happened to coincide as with last year's kind

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Speaker 1: of weather as well, and I hunted. Um, I hunted

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Speaker 1: a stand near a marsh on I see Friday night,

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Speaker 1: and I had a couple of young deer come through

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Speaker 1: right off the bat and uh, just kind of mill

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Speaker 1: around and they didn't do much. I saw a couple

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Speaker 1: of dolls in the distance, but no mature deer. Um.

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Speaker 1: So then Saturday morning, I was going into one of

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Speaker 1: my best stands. I had the right wind for it,

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Speaker 1: everything was perfect, and on my way in, I walked

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Speaker 1: by with my head lamp on. I could see the

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Speaker 1: glow in their eyes, like fifty yards away from me,

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Speaker 1: probably about seven or eight doze, just kind of working

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Speaker 1: their way back towards this pattern. So my access route

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Speaker 1: in there, I decided to go straight line in and

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Speaker 1: I should have taken a different route, but um, because

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Speaker 1: typically I never run into deer on here. So it

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Speaker 1: just so happened that we crossed paths at the same time.

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Speaker 1: They didn't spook, that didn't blow. I made it to

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Speaker 1: my stand and they or That morning I had an

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Speaker 1: encounter with a really good three year old. UM. I

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Speaker 1: don't know you. Did you happen to watch the footage

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Speaker 1: I posted online? I did? Yeah, what would you? He's

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Speaker 1: probably one forty maybe low one forties, if if one

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Speaker 1: forty at all. We're talking about the one that comes

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Speaker 1: right with your stand right right right. Yeah, I would

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Speaker 1: say that I was thinking a little less. Yeah, probably

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Speaker 1: maybe one thirty five ish maybe, I don't know, but

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Speaker 1: you know what what stuck up to me is and

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Speaker 1: I'm I don't claim to be an expert on it,

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Speaker 1: but man, his neck was huge. Yeah he was. He

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Speaker 1: had a huge neck. And I'll tell you what, I'll

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Speaker 1: be honest with you. I had thoughts of shooting that

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Speaker 1: dear for you know, he was a big He had

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Speaker 1: a big neck, but passed his shoulders, said three year

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Speaker 1: old all the way. I mean, he had a skinnier body,

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Speaker 1: and uh, he just wasn't the mature dear that I'm

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Speaker 1: looking for. Or um. I was just like, man, I

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Speaker 1: should shoot him, and I should Uh, I should shoot him,

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Speaker 1: and I should try to, you know, just end my

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Speaker 1: season right now. And but my inner, I guess uh

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Speaker 1: management started talking and was like, no, you gotta let

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Speaker 1: him go, bud. So I let him walk. I tore

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Speaker 1: everything down out of that stand, left the stand up

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Speaker 1: because I didn't know what where I was going to

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Speaker 1: hunt that night, and I had a couple of options

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Speaker 1: in mind, and so I I saw that that deer

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Speaker 1: and I'm just like, you know what, I saw plenty

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Speaker 1: of deer. I'm just gonna go back to the same stand.

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Speaker 1: So I went back to the same stand Saturday night,

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Speaker 1: and uh, you know it, it was cloudy and sprinkle

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Speaker 1: e and it didn't I mean it was sprinkling and

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Speaker 1: missing and it just and then it started clearing up.

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Speaker 1: As the evening went on, the wind started blowing, and

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Speaker 1: then it started settling down, and I started seeing some doze.

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Speaker 1: I'm not a huge fan of sitting on field edges

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Speaker 1: as I've as you know, and um, these deer coming

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Speaker 1: from a different place than I've ever hunted before. Out

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Speaker 1: onto this field. There's a couple of doughs that started

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Speaker 1: feeding and then um, later on I saw a young buck,

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Speaker 1: maybe one two year old come out and uh start

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Speaker 1: pushing some of these doughs around, and then outsteps I

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Speaker 1: mean you can just tell a darker coat, a way

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Speaker 1: bigger body than the other buck that was out there,

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Speaker 1: and he was a big ten pointer. Um, he was

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Speaker 1: about a hundred fifty yards. I was able to um

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Speaker 1: look at him just a bit through my binoculars and uh,

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Speaker 1: he wasn't chasing does, but he was bumping them. So

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Speaker 1: he was going up to him smelling him. He would

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Speaker 1: know that they're not ready yet, right, and then they

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Speaker 1: would run up. Then they'd kind of run and he

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Speaker 1: wouldn't follow him. So he did that to like two

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Speaker 1: or three of the dose, and then he just walked

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Speaker 1: across the field. And then as the as the young

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Speaker 1: buck was chasing him, he put his ears back and

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Speaker 1: he started making aggressive, aggressive moves towards this buck, this

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Speaker 1: younger buck. So I thought to myself, Hey, I'm gonna rattle.

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Speaker 1: I'm gonna see if I can get him in. And

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Speaker 1: I rattled, and he just kept working his way down

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Speaker 1: the down the field, and uh, then I just lost

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Speaker 1: him and time ran out, and um, I didn't hunt

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Speaker 1: Sunday morning because the wind. Uh, the wind was not

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Speaker 1: right for any of the stands that I had set,

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Speaker 1: and I didn't want to go in and set up

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Speaker 1: a new stand for um in a place where I

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Speaker 1: thought there might be potential shooters. It's just it's it's

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Speaker 1: a little risky of making all that noise and leaving

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Speaker 1: all that scent. Got Well, hey, it sounds like you

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Speaker 1: had some fun sets. You saw some pretty nice bucks. Yeah,

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Speaker 1: so I got a I got an idea of where

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Speaker 1: where some of them are coming in, Where they're going out.

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Speaker 1: Not a lot of sign yet. I haven't. I didn't

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Speaker 1: see a lot of sign um, but I did. Kind

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Speaker 1: of a side story, I've seen a guy out working

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Speaker 1: his cat also. I stopped and I talked to him.

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Speaker 1: He's a neighboring landowner, and it's always kind of good

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Speaker 1: to see know for a fact what happens to deer.

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Speaker 1: He's like, oh man, what happened to this year? I've

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Speaker 1: seen him two years in a row. Now he's gone, well,

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Speaker 1: I had the buck that I passed, or well I

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Speaker 1: would have shot him if he was just a little

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Speaker 1: bit closer or offered a more of a broadside shot

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Speaker 1: last year, like the first two weeks so of October,

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Speaker 1: I think big nine pointer, big nine pointer. He ended

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Speaker 1: up shooting that deer during shotgun season. So it's kind

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Speaker 1: of cool to know that, hey, this buck has make it.

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Speaker 1: Now here's the cool thing. This guy tells me. He goes,

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Speaker 1: this was the biggest buck I've ever seen, really, so

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Speaker 1: I shot it. Yeah. So that just tells me that

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Speaker 1: these people that are out, these landowners, these people that

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Speaker 1: are out hunting, they don't really pay attention like us

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Speaker 1: bow hunters do. I'm not saying, you know, I'm not

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Speaker 1: trying to categorize shotgun hunters and bow hunters, but there's

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Speaker 1: a you know, some of these people they just don't

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Speaker 1: focus like us hardcore guys do. And you know, I

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Speaker 1: got like six deer that are bigger than this nine

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Speaker 1: pointer out there and there. You know, they go in,

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Speaker 1: they do their thing, and when they're done, they're done.

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Speaker 1: You know, no big deal if that's the way you hunt,

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Speaker 1: and that's the way you hunt. So but it's kind

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Speaker 1: of cool knowing that, hey, this is why this is

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Speaker 1: this is one of the another reason why there's big

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Speaker 1: deer in the area. Yeah, And I think it also

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Speaker 1: speaks to the fact that if you pay attention to

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Speaker 1: the details like we try to do, it gives us

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Speaker 1: the opportunities to see some of these deer that a

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Speaker 1: lot of people don't. So his off. How about you, UM,

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Speaker 1: relatively uneventful weekend? Um sort of? I was originally, I

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Speaker 1: think I think last time we talked, I might have

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Speaker 1: been talking about the fact that I was originally planning

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Speaker 1: going to Ohio last weekend, UM, but the weather forecast

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Speaker 1: just did not look good. It was gonna be really warm,

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Speaker 1: like seventies even almost eighty degrees on Saturday. UM, so

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Speaker 1: I kind of looked at, Okay, this looks like it's

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Speaker 1: going to be kind of subpar weekend down there. Do

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Speaker 1: I go down there when I'm not really having high

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Speaker 1: hopes of any real potential or that I nixed the

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Speaker 1: hunt and instead put in some time with the family.

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Speaker 1: And that's what I end up deciding to do. So

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Speaker 1: I did not go to Ohio, and instead I just

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Speaker 1: spent some time with the wives, spent some time with

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Speaker 1: the in laws, spent some time with my mom, dad, um,

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Speaker 1: and just trying to get things in the line before

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Speaker 1: my big rut trip. But I did get out for

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Speaker 1: two evenings back home here in Michigan hunted Thursday night.

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Speaker 1: I saw a bunch of doughs, but nothing of too

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Speaker 1: much interest and couldn't get a shot at one of them.

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Speaker 1: And then Sunday night, I wasn't planning on hunting, but

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Speaker 1: I got home back from my family event earlier than

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Speaker 1: I thought I would, and I had like an hour

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Speaker 1: and a half a daylight left, and it just felt

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Speaker 1: good outside and I was like, I want to be

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Speaker 1: in a tree right now. So I just scurried ran

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Speaker 1: out to one of my closest tree stands um that

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Speaker 1: I can get too close for my house, and gotten

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Speaker 1: that true with like an hour and fifty minutes a

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Speaker 1: daylight left, and I ended up shooting a nice deal

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Speaker 1: that night. And right after I shot this dough, out

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Speaker 1: of this little pocket of bedding cover comes the top

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Speaker 1: buck on my Michigan property. Um. Now, since I had

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Speaker 1: killed a buck on this farm earlier this year, I

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Speaker 1: wasn't going to shoot any other deer unless like some

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Speaker 1: random deer from out of nowhere showed up. There was

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Speaker 1: a mega giant. But if one of the deer that

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Speaker 1: I knew was living in the area showed up, I

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Speaker 1: decided that I wasn't going to shoot him. So this

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Speaker 1: was one of those nice year. And he's a three

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Speaker 1: year old um, but a really nice Michigan three year

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Speaker 1: old um in my opinion, for for Michigan. He was cool.

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Speaker 1: So it was really fun to see him coming too

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Speaker 1: the food plot and he just fed foot ten fifteen

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Speaker 1: minutes and I just watched and light faded and it

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Speaker 1: got too dark, and then he walks right underneath my

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Speaker 1: tree stand. Um, which is fun just you know, yeah,

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Speaker 1: but it was it was fun because you know, in

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Speaker 1: so many situations. One a buck that you would usually

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Speaker 1: shoot when you see him, you're in shoot mode, you're

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Speaker 1: in hunt mode, and you're you know, all fired up

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Speaker 1: and focusing on just trying to get the shop. But

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Speaker 1: you know, in this case, it was fun just to

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Speaker 1: not worry about that and to just you know, it's

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Speaker 1: fun to sometimes pass under and just get to enjoy

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Speaker 1: the moment um, which is what I did there. But

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Speaker 1: as soon as he came underneath my stand, he saw

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Speaker 1: these doughs and then he started chasing these doughs all around, um,

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Speaker 1: which you know, is a little bit earlier than most

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Speaker 1: of the time that I see in Michigan these three

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Speaker 1: year olds. Again, I think these three year olds in

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Speaker 1: Michigan act more like four or five year olds and

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Speaker 1: some of the lower pressure states just because of the

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Speaker 1: intense pressure here, so lots of times I'm not seeing

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Speaker 1: a buck of that age getting after it till you know,

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Speaker 1: another week from now. But but he was getting a

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Speaker 1: little frisky, so that was nice to see. It was

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Speaker 1: fun and saw lots of young bucks chasing around like crazy.

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Speaker 1: There was a deer run and all over that night,

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Speaker 1: so it was a fun hunt. And uh, I got

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Speaker 1: a door on the ground and the fraser. So I'm primed,

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Speaker 1: I'm feeling good. Had a nice clean kill on her.

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Speaker 1: She was dead in like ten seconds. She ran off

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Speaker 1: thirty yards and flipped over and that was it. So

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Speaker 1: it feels good to you know, have that in the

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Speaker 1: back pocket heading into the rut. So the cool thing

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Speaker 1: about this is is what I really like the story

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Speaker 1: that you said is the fact that you you you

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Speaker 1: took a buck and then you said to yourself, you know,

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Speaker 1: I don't need to take another buck off this property,

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Speaker 1: even though it was your your top hitlist off the property. Now,

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Speaker 1: what you've done is you've made a conscious effort to

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Speaker 1: put you know, basically actions behind your words as far

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Speaker 1: as management is concerned. And you know, for anybody who's

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Speaker 1: listening that that's a great that's a that's a great

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Speaker 1: thing to help not only you and your property, but

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Speaker 1: the entire state of Michigan to improve their dear their

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Speaker 1: dear quality. Yeah, yeah, I think you're right, And I think,

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Speaker 1: you know, more and more people every year are starting

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Speaker 1: to practice some form of of deer management, and um,

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Speaker 1: you know, it's helping, and you know, I know there's

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Speaker 1: a good chance that these Bucks could get killed during

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Speaker 1: guns season, but you know, if I shot him, there's

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Speaker 1: no chance to make it through. So um, So yeah,

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Speaker 1: I'm really hopeful that this buck and then the eight

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Speaker 1: pointer that I missed on opening night. Um, and then

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Speaker 1: there's one other eight pointer who has been off and

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Speaker 1: on in the area. If a couple of those guys

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Speaker 1: make it through, they'll be just they'll be awesome. Michigan

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Speaker 1: there next year, just toad probably big eight pointers four

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Speaker 1: year old and that would be awesome if I had

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Speaker 1: a couple of nice four year olds to chase next

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Speaker 1: year in Michigan. So that's my hope. My fingers are

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Speaker 1: crossed hoping they're gonna make it. And I'd love to,

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Speaker 1: you know, continue to get to know these deer, learn

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Speaker 1: about them this year, watch them and get pictures of

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Speaker 1: them so that next year I'll have a good idea

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Speaker 1: of what I need to do to get an air

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Speaker 1: on one. So and just kind of heads up to

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Speaker 1: those who are listening as far as if you know,

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Speaker 1: if you pay attention to the moon at all this

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Speaker 1: week going into this weekend, um, we have a setting

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Speaker 1: moon and a rising sun. So I'm not sure what

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Speaker 1: day it is this week if it's this later this

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Speaker 1: week or this weekend, we're gonna have the moon setting,

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Speaker 1: you know, like ten degrees in the air and the

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Speaker 1: sun rising at the same time. And according to some

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Speaker 1: of these guys who believe in that moon's phase, that's

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Speaker 1: an optimal and optimal time. Yeah, great point, Dan, And

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Speaker 1: also another thing, um, And we'll talk to Matt here

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Speaker 1: in second, and he'll share some research that they've shown

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Speaker 1: about the moon. Um. But there is a lot of

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Speaker 1: anecdotal evidence that support some of these. There is an

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Speaker 1: Adam Hayes, one of our past podcast guests you remember,

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Speaker 1: probably talking about the moon guy he uses and paying

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Speaker 1: attention to the overhead under foot times. Well, the moon

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Speaker 1: will be overhead during the last couple of hours of

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Speaker 1: daylight on this Thursday, Friday and Saturday. Perfect. You should

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Speaker 1: be really good days in the evening. So um, I'm

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Speaker 1: gonna be out in Ohio on Thursday and Friday, hoping

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Speaker 1: to take advantage of that. And there's a little bit

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Speaker 1: of cool weather Thursday, Friday, Saturday, and then Saturday morning

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Speaker 1: I'm gonna drive to Iowa in your home state and

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Speaker 1: hunt there for the next week. So exciting stuff to come.

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Speaker 1: I can't wait to help you drag a deer out, man,

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Speaker 1: I hope so I uh um, like I know, for

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Speaker 1: like Friday is Friday night. I got a south southeast

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Speaker 1: wind right and I'm going into Mark Kenyan territory. Oh baby,

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Speaker 1: so off this ridge that he's He's been known to

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Speaker 1: bed Truill Cameron pictures of him throughout the entire season.

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Speaker 1: So I'm I'm foaming at the mouth and trying to

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Speaker 1: you know, I'm getting out of work early, going to

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Speaker 1: get into the stand early and get my win blowing

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Speaker 1: off into this ridge and hopefully h he comes through

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Speaker 1: or somebody or comes through that and bingo bengo, right,

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Speaker 1: bengo bango. But hey, man, we are as we tend

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Speaker 1: to get doing lately on we need to get the

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Speaker 1: pro on the line here. We need to give Mat

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Speaker 1: a call, So let's go ahead and do that right now.

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Speaker 1: But as you might have expected, we do need to

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Speaker 1: pause briefly for a word from our partners at Sick

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Speaker 1: of Gear, who are making this podcast possible. So as

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Speaker 1: we've been doing over the past couple of months, we've

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Speaker 1: got Sick of Product category leader Dennis Suck with us,

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Speaker 1: and I want Dennis to share with us what is

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Speaker 1: ideal layering system from SICKA would be for a typical

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Speaker 1: November rut hunt. Here's Dennis. Yeah, Mark, I think a

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Speaker 1: lot of that had to do with your your and

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Speaker 1: I'm in the same boat. You know, I'm gonna be

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Speaker 1: here all day, you know, So if I'm going out,

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Speaker 1: I'm gonna spend all day. Um, it's gonna be pretty cold.

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Speaker 1: I'm not gonna be create. I'm not moving at all.

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Speaker 1: I'm seditary, you know. I got to maintain and hold

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Speaker 1: every bit of warmth I might have, you know, So

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Speaker 1: I'm gonna make sure that you know, this is where

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Speaker 1: I might pull my marino out or get a marino

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00:20:07,600 --> 00:20:09,639
Speaker 1: bass layer, you know, something that's going to be warmth

393
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Speaker 1: to wait, really warm. I'm also probably be hunt and

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Speaker 1: so that range emotion still matters a lot to me.

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Speaker 1: So I'm gonna gonna make sure I have an insulation layer,

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Speaker 1: so I have something that that I can bulk up

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Speaker 1: if things get cold. I want to make sure I

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Speaker 1: have a good bass layer that's gonna still keep me

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Speaker 1: warm right up against my skin. Um, I'm gonna make

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Speaker 1: sure that I have some kind of rain protection in

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00:20:29,160 --> 00:20:31,440
Speaker 1: my bag, you know, so I have, you know, whether

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00:20:31,480 --> 00:20:33,160
Speaker 1: it's a pack up piece or something that I can

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Speaker 1: pull out if it gets if it gets nasty, I

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00:20:34,840 --> 00:20:37,000
Speaker 1: don't wanna have to walk out, you know. So I'm

405
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Speaker 1: thinking about all those things. Um if I'm thinking about

406
00:20:39,600 --> 00:20:42,080
Speaker 1: that for sitcom, I'm thinking about that with probably our

407
00:20:42,080 --> 00:20:44,320
Speaker 1: Marino bass layers. And I'm thinking about that with our

408
00:20:44,320 --> 00:20:47,720
Speaker 1: fanatic system um our fanatic coodies. One that's important to

409
00:20:47,760 --> 00:20:49,760
Speaker 1: me because there's a lot of that day that I

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Speaker 1: may not wear my jacket. You know, it's warmer, I

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00:20:52,880 --> 00:20:55,480
Speaker 1: can wear that hoodie and I feel really good. And

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Speaker 1: I'll probably put a downpour system in my backpack. So

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Speaker 1: those are the things that for me, I like to have.

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Speaker 1: I think that's what I would wear doing the right

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Speaker 1: you know, people are honest, is what I do. Were

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Speaker 1: doing the hunt. So there you have it. If you're

417
00:21:07,480 --> 00:21:09,600
Speaker 1: interested in picking up some last minute gear before the

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00:21:09,680 --> 00:21:12,640
Speaker 1: rut or checking out any other items from sick, visit

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Speaker 1: sick of gear dot com. And now let's get Matt

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Speaker 1: on the line. All right with us. Now on the

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Speaker 1: line is Matt Ross. Welcome to show. Matt, thanks for

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Speaker 1: having me. Yeah, I uh, you know, I get to

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Speaker 1: talk to you a lot with some of the work

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Speaker 1: that we do. But I'm excited to actually have you

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Speaker 1: on the show here to speak with a lot of

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Speaker 1: our listeners because you're a guy that I know has

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Speaker 1: a lot of insight and education when it comes to

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Speaker 1: wildlife and deer and what they do. And you know,

429
00:21:43,240 --> 00:21:44,919
Speaker 1: me and Daniel a little bit about your background, and

430
00:21:44,920 --> 00:21:46,399
Speaker 1: I shared just a little bit at the top of

431
00:21:46,400 --> 00:21:48,919
Speaker 1: the show. But for our listeners who aren't familiar with

432
00:21:48,960 --> 00:21:50,320
Speaker 1: you or what you do, could you give us a

433
00:21:50,320 --> 00:21:53,080
Speaker 1: little bit of background into your education and background about

434
00:21:53,200 --> 00:21:55,520
Speaker 1: what you do relate to white tails? Now you know

435
00:21:55,600 --> 00:21:58,840
Speaker 1: how you've got to that point. Yeah, sure, I'd be

436
00:21:58,880 --> 00:22:01,880
Speaker 1: happy to so. I currently work at the Quality Deer

437
00:22:01,880 --> 00:22:05,280
Speaker 1: Management Association. You probably said that, but um, I'm from

438
00:22:05,600 --> 00:22:08,840
Speaker 1: the Northeast. I live in New York State. Um, you know,

439
00:22:09,240 --> 00:22:12,199
Speaker 1: first and foremost, I'm a deer hunter. Grew up, you know,

440
00:22:12,240 --> 00:22:14,920
Speaker 1: in a family of deer owners, and it's what drove

441
00:22:14,960 --> 00:22:17,360
Speaker 1: me to a career of looking at deer and wanted

442
00:22:17,359 --> 00:22:20,920
Speaker 1: to do stuff with deer. Um And I vividly remember

443
00:22:20,960 --> 00:22:23,639
Speaker 1: growing up, you know, wanting to do something along those lines.

444
00:22:24,200 --> 00:22:27,200
Speaker 1: And when I was in high school, I found out

445
00:22:27,240 --> 00:22:28,840
Speaker 1: there was a career that you could do this, and

446
00:22:28,840 --> 00:22:32,000
Speaker 1: then it was you know, just drove me right towards

447
00:22:32,000 --> 00:22:36,159
Speaker 1: it right away. So I went to school for and

448
00:22:36,160 --> 00:22:39,919
Speaker 1: got a degree as a bachelor's for wildlife and actually

449
00:22:39,920 --> 00:22:43,119
Speaker 1: worked for our local Department of Environmental Conservation that's kind

450
00:22:43,160 --> 00:22:45,960
Speaker 1: of our d n R in New York State for

451
00:22:46,000 --> 00:22:48,160
Speaker 1: a few years as a technician, and then went back

452
00:22:48,200 --> 00:22:53,080
Speaker 1: to school and got my master's and uh, you know,

453
00:22:53,560 --> 00:22:55,360
Speaker 1: and they had to do with deer. My my master's

454
00:22:55,359 --> 00:22:58,280
Speaker 1: project actually had to do with deer in northern New

455
00:22:58,280 --> 00:23:01,640
Speaker 1: England up in New Hampshire, and I get to work

456
00:23:01,720 --> 00:23:04,280
Speaker 1: one on one with deer that we're in a research facility,

457
00:23:04,320 --> 00:23:08,840
Speaker 1: which was an amazing experience. And when I finished school,

458
00:23:09,800 --> 00:23:12,119
Speaker 1: actually was in the middle of writing my thesis, I

459
00:23:12,720 --> 00:23:16,600
Speaker 1: got a job working for a consulting company throughout the Northeast.

460
00:23:17,240 --> 00:23:20,399
Speaker 1: Mostly they were a forestry based consultant company. I was

461
00:23:20,480 --> 00:23:24,400
Speaker 1: hired as the as the wildlife person on staff, and

462
00:23:24,440 --> 00:23:27,800
Speaker 1: I got to work with landowners and townships and uh

463
00:23:28,040 --> 00:23:31,840
Speaker 1: some other private entities writing management plans sometimes about deer,

464
00:23:31,840 --> 00:23:36,119
Speaker 1: but not always and uh, I really enjoyed that experience,

465
00:23:36,160 --> 00:23:39,560
Speaker 1: and that company actually did a lot of forest management.

466
00:23:39,640 --> 00:23:42,320
Speaker 1: So while I was there, I started picking up some

467
00:23:42,359 --> 00:23:44,639
Speaker 1: of the forest management stuff. I had actually had a

468
00:23:44,680 --> 00:23:48,040
Speaker 1: minor in that, and UH enjoyed that so much. I

469
00:23:48,119 --> 00:23:51,720
Speaker 1: ended up following that side of the profession as well

470
00:23:51,720 --> 00:23:54,640
Speaker 1: and became licensed as a forester. And by the time

471
00:23:54,680 --> 00:23:58,719
Speaker 1: I was done working at that firm, I was marking

472
00:23:58,760 --> 00:24:03,280
Speaker 1: timber and working with and contractors and prescribing forest management

473
00:24:03,280 --> 00:24:05,720
Speaker 1: as well as wildlife And it was a really really

474
00:24:05,800 --> 00:24:10,800
Speaker 1: valuable part of my professional experience, and as a deer

475
00:24:10,800 --> 00:24:15,360
Speaker 1: honor to seeing that marriage between managing habitat and UH

476
00:24:15,400 --> 00:24:17,679
Speaker 1: you know what you can do with deer and are

477
00:24:17,680 --> 00:24:21,240
Speaker 1: along the time it was like thousand that's when I

478
00:24:21,320 --> 00:24:23,280
Speaker 1: learned about q d M A And I actually was

479
00:24:23,320 --> 00:24:26,399
Speaker 1: introduced to q d M A M from a colleague

480
00:24:26,520 --> 00:24:30,600
Speaker 1: who I think you've had on the show before, Kip Adams,

481
00:24:30,840 --> 00:24:33,639
Speaker 1: and I learned about it and I joined, and I

482
00:24:33,680 --> 00:24:37,199
Speaker 1: became a member initially and actually started a local what

483
00:24:37,280 --> 00:24:42,159
Speaker 1: we call branches are chapters, little grassroot movements, and UH

484
00:24:42,400 --> 00:24:45,280
Speaker 1: did that with friends and started up doing that as

485
00:24:45,280 --> 00:24:49,160
Speaker 1: a volunteer, and eventually a job opened up and I applied,

486
00:24:49,200 --> 00:24:51,960
Speaker 1: and now it's almost ten years later, I've been working

487
00:24:51,960 --> 00:24:54,000
Speaker 1: for q d m A and I've done a variety

488
00:24:54,000 --> 00:24:57,119
Speaker 1: of different things at qt m A. But today I

489
00:24:57,200 --> 00:25:00,240
Speaker 1: run our private lands program, that's what I call it.

490
00:25:00,400 --> 00:25:02,240
Speaker 1: I'm my title a little bit different than that, but

491
00:25:02,280 --> 00:25:06,800
Speaker 1: I run our dear Steward courses and which are individual

492
00:25:06,840 --> 00:25:10,600
Speaker 1: classes people can take, and our land sort of vacation program.

493
00:25:10,640 --> 00:25:12,520
Speaker 1: So if you own land or your lease in land

494
00:25:12,560 --> 00:25:15,200
Speaker 1: and you want to get that property certified or assessed

495
00:25:15,200 --> 00:25:18,320
Speaker 1: by a q d m A inspector, I run both

496
00:25:18,320 --> 00:25:22,879
Speaker 1: of those, among many other things at the organization as well.

497
00:25:23,800 --> 00:25:26,719
Speaker 1: So in short, you do a lot of stuff related

498
00:25:26,760 --> 00:25:30,120
Speaker 1: Deer every day. Yeah, every day. It's a good job.

499
00:25:30,200 --> 00:25:34,200
Speaker 1: It's a good job, a good job. So what we're

500
00:25:34,600 --> 00:25:37,680
Speaker 1: hoping to garner from you today, Matt, given your background,

501
00:25:37,760 --> 00:25:40,080
Speaker 1: given the fact that you've been deep into this stuff

502
00:25:40,119 --> 00:25:42,960
Speaker 1: for you know, fifteen years or more, it sounds like

503
00:25:42,960 --> 00:25:46,400
Speaker 1: well over that actually. You know, we talk a lot

504
00:25:46,440 --> 00:25:48,920
Speaker 1: on this podcast about strategies and tactics, and we have

505
00:25:48,920 --> 00:25:50,400
Speaker 1: a lot of different people come on here and share

506
00:25:50,440 --> 00:25:52,800
Speaker 1: their ideas and their theories and what they've seen, and

507
00:25:53,600 --> 00:25:56,479
Speaker 1: a lot of that is anecdotal though, and I do

508
00:25:56,560 --> 00:25:58,440
Speaker 1: know though there's been a lot of research done. There's

509
00:25:58,440 --> 00:26:00,280
Speaker 1: a lot of science related to deer because you're are,

510
00:26:00,400 --> 00:26:03,280
Speaker 1: you know, the most popular abundant game species out there,

511
00:26:03,280 --> 00:26:04,879
Speaker 1: and so because of that, obviously there's a lot of

512
00:26:04,880 --> 00:26:07,840
Speaker 1: attention paid to them. Um, but we don't often actually

513
00:26:07,880 --> 00:26:11,159
Speaker 1: get to dive into that science. So I thought with

514
00:26:11,240 --> 00:26:13,840
Speaker 1: you here, we could really dig deep into that the

515
00:26:13,880 --> 00:26:18,760
Speaker 1: actual research science data behind some of these theories or

516
00:26:18,960 --> 00:26:20,520
Speaker 1: ideas that we have. And I don't think I know

517
00:26:20,560 --> 00:26:22,720
Speaker 1: many people that understand the stuff better than you do.

518
00:26:22,880 --> 00:26:26,600
Speaker 1: So that's kind of the the plan and theme where

519
00:26:26,600 --> 00:26:28,960
Speaker 1: we're going here. High high pressure on you, met, because

520
00:26:28,960 --> 00:26:32,640
Speaker 1: we're really depending on you to educate us. So yeah,

521
00:26:32,960 --> 00:26:35,760
Speaker 1: no worries and and you know I always remember too,

522
00:26:35,920 --> 00:26:37,720
Speaker 1: I already said it once. You know, I am a

523
00:26:37,720 --> 00:26:39,360
Speaker 1: deer hunter. And there's a lot of things out there

524
00:26:39,359 --> 00:26:41,359
Speaker 1: in the research, you know, when you get into like

525
00:26:41,440 --> 00:26:43,840
Speaker 1: peer reviewed research, and we can talk about all the

526
00:26:43,920 --> 00:26:46,600
Speaker 1: nuances of that too. You know, it's looking at something

527
00:26:46,640 --> 00:26:49,800
Speaker 1: that's site specific, and um, you can also take some

528
00:26:49,880 --> 00:26:52,159
Speaker 1: second guess of there. But being a deer hunter is

529
00:26:52,200 --> 00:26:54,760
Speaker 1: there's some results in some of the research out there

530
00:26:54,800 --> 00:26:57,760
Speaker 1: that myself and other colleagues and stuff. It just seems

531
00:26:57,800 --> 00:26:59,840
Speaker 1: like head scratches like that just doesn't seem like it's

532
00:26:59,880 --> 00:27:03,080
Speaker 1: the case. But um, you know, from what I've seen

533
00:27:03,160 --> 00:27:05,840
Speaker 1: in my own anecdotes, but the research says that, you

534
00:27:05,960 --> 00:27:08,760
Speaker 1: kind of it's not always a gospel. You can't always

535
00:27:08,800 --> 00:27:10,840
Speaker 1: just say you know, the research says this, so it

536
00:27:10,960 --> 00:27:14,119
Speaker 1: must be true. UM. It gives you clues and you

537
00:27:14,160 --> 00:27:16,560
Speaker 1: kind of piece it all together. So yeah, I'm happy

538
00:27:16,600 --> 00:27:19,719
Speaker 1: to share what I've learned. And UH actually had the

539
00:27:19,800 --> 00:27:23,600
Speaker 1: advantage a couple of years ago for convention UM I

540
00:27:23,680 --> 00:27:27,840
Speaker 1: was assigned the task of presenting all this material as

541
00:27:27,920 --> 00:27:32,119
Speaker 1: one of our presentations at our national convention about specifically

542
00:27:32,160 --> 00:27:36,600
Speaker 1: mature box, looking at UH mature box and what they

543
00:27:36,840 --> 00:27:39,359
Speaker 1: how they moved, how their home ranges looked UM and

544
00:27:39,400 --> 00:27:43,840
Speaker 1: looking at GPS research because over the last probably decade

545
00:27:43,920 --> 00:27:46,919
Speaker 1: or so, a lot of the movement research on deer

546
00:27:47,320 --> 00:27:51,240
Speaker 1: and again specifically talking about bucks has evolved because the

547
00:27:51,320 --> 00:27:55,399
Speaker 1: collars that they're using today are just um, just phenomenal

548
00:27:55,480 --> 00:27:58,360
Speaker 1: compared to the technology fifteen years ago, over twenty years ago,

549
00:27:58,400 --> 00:28:02,000
Speaker 1: where there was res with radio collars that they're you know,

550
00:28:02,400 --> 00:28:05,919
Speaker 1: triangulating and using transmitters to try to locate a deer

551
00:28:06,200 --> 00:28:08,400
Speaker 1: based on getting a couple of different lines of sight

552
00:28:08,480 --> 00:28:11,280
Speaker 1: of where that that buck might be. But now, I mean,

553
00:28:11,880 --> 00:28:14,359
Speaker 1: you guys all know, I mean the technology and a

554
00:28:14,400 --> 00:28:17,760
Speaker 1: smartphone today is just amazing. The same technology exists in

555
00:28:17,840 --> 00:28:21,719
Speaker 1: GPS units where these deer getting located by the minute,

556
00:28:21,840 --> 00:28:24,680
Speaker 1: sometimes in the middle of the rot and they really

557
00:28:24,720 --> 00:28:27,240
Speaker 1: know where they are. So, uh, that has fine tuned

558
00:28:27,240 --> 00:28:30,760
Speaker 1: a lot of it. And looking at that research, the

559
00:28:31,040 --> 00:28:34,399
Speaker 1: more recent research on box and compiling that for that

560
00:28:34,520 --> 00:28:37,960
Speaker 1: presentation really allowed me to all sort of just frame

561
00:28:38,000 --> 00:28:41,000
Speaker 1: into my own mind what what's happening. And Uh, there's

562
00:28:41,000 --> 00:28:44,360
Speaker 1: been a lot of positive feedback at the organization in

563
00:28:44,400 --> 00:28:48,200
Speaker 1: the magazine and um on our website, you know, cutium

564
00:28:48,360 --> 00:28:50,760
Speaker 1: dot com. People love talking about that stuff. So I'm

565
00:28:50,760 --> 00:28:53,080
Speaker 1: happy to share what I've learned. Yeah, I'm excited to

566
00:28:53,080 --> 00:28:55,320
Speaker 1: get into that because those are some of the studies

567
00:28:55,320 --> 00:28:58,400
Speaker 1: that I've taken a look at two that are pretty fascinating. Um.

568
00:28:58,440 --> 00:29:01,680
Speaker 1: But but real quickly, before we dive into that aspect

569
00:29:01,680 --> 00:29:03,480
Speaker 1: of it, I want to kind of set the stage

570
00:29:03,600 --> 00:29:07,440
Speaker 1: with two pieces that I think kind of get us

571
00:29:07,480 --> 00:29:10,480
Speaker 1: properly framed for the rest of the conversation. And number one,

572
00:29:11,240 --> 00:29:14,840
Speaker 1: you know, take us from a deer's life at the

573
00:29:14,880 --> 00:29:17,960
Speaker 1: end of the summer and how they are changing physiologically

574
00:29:18,160 --> 00:29:19,959
Speaker 1: as you progress from the end of the summer up

575
00:29:19,960 --> 00:29:22,040
Speaker 1: to this point, because a lot of things change in

576
00:29:22,080 --> 00:29:25,920
Speaker 1: a deer's actual biology and body that that affect then

577
00:29:26,040 --> 00:29:27,800
Speaker 1: some of these behavioral things that we're gonna talk about.

578
00:29:27,800 --> 00:29:30,440
Speaker 1: Can you just walk us through how a buck is

579
00:29:30,520 --> 00:29:33,400
Speaker 1: changing and where they're at right now? Um, And then

580
00:29:33,400 --> 00:29:35,920
Speaker 1: I want to talk about what actually triggers the start

581
00:29:35,960 --> 00:29:39,160
Speaker 1: of the run, but let's start start with the physiological

582
00:29:39,200 --> 00:29:43,000
Speaker 1: aspects of what's happening. Okay, so with Box particular, and

583
00:29:43,080 --> 00:29:44,560
Speaker 1: let's just talk about Box. If you want to talk

584
00:29:44,600 --> 00:29:47,800
Speaker 1: about all deer or or you know, talk about specific

585
00:29:47,840 --> 00:29:51,640
Speaker 1: segments of the herd, we can jump into that. But um,

586
00:29:51,680 --> 00:29:55,560
Speaker 1: specifically about Box. A lot of the research what it's

587
00:29:55,600 --> 00:30:00,520
Speaker 1: saying and in terms of both the resource use, um,

588
00:30:00,520 --> 00:30:03,680
Speaker 1: where they exist on the landscape. You know, what they're using,

589
00:30:03,840 --> 00:30:09,120
Speaker 1: what they're eating that's changing and their physiological uh, their

590
00:30:09,160 --> 00:30:12,640
Speaker 1: body is changing too because they're preparing not for the

591
00:30:12,720 --> 00:30:15,880
Speaker 1: rigors of the rout, but to make it through the winter.

592
00:30:16,080 --> 00:30:19,600
Speaker 1: I mean that's they're evolved a long time to be

593
00:30:19,640 --> 00:30:24,120
Speaker 1: able to live off of times of surplus, when there's

594
00:30:24,120 --> 00:30:27,600
Speaker 1: abundance such as green food out there. It's not always

595
00:30:27,640 --> 00:30:29,600
Speaker 1: you know, row crops in every part of the country.

596
00:30:29,960 --> 00:30:32,280
Speaker 1: That certainly exists in a lot of the country, but

597
00:30:32,640 --> 00:30:35,760
Speaker 1: if you go back eons ago, you know when when

598
00:30:35,800 --> 00:30:40,120
Speaker 1: deer were around before there was large scale commercial agriculture,

599
00:30:40,440 --> 00:30:42,800
Speaker 1: they lived off of what was abundant and what was green.

600
00:30:42,880 --> 00:30:45,360
Speaker 1: And then in times of scarcity, when you're going into

601
00:30:45,360 --> 00:30:48,320
Speaker 1: the fall, as a lot of that vegetation that's in

602
00:30:48,720 --> 00:30:52,800
Speaker 1: abundance and high water content and high nutrient content is

603
00:30:52,800 --> 00:30:55,320
Speaker 1: starting to what we call sinesse, you know, it's all

604
00:30:55,400 --> 00:30:57,680
Speaker 1: dying back. You're losing some of that vegetation. And then

605
00:30:57,840 --> 00:31:02,880
Speaker 1: again into winter, even in or temperate climates where they

606
00:31:02,960 --> 00:31:05,920
Speaker 1: might not have deep snow or bad winners, there's still

607
00:31:06,120 --> 00:31:10,520
Speaker 1: a time of scarcity when those food sources are disappearing.

608
00:31:11,080 --> 00:31:14,520
Speaker 1: And in some of the truest sense of the word

609
00:31:14,560 --> 00:31:17,480
Speaker 1: of living off their body and living off that, you know,

610
00:31:17,560 --> 00:31:20,640
Speaker 1: deer are getting ready for that. So they're bulking up

611
00:31:20,640 --> 00:31:23,200
Speaker 1: and they need to change what they're eating and change

612
00:31:23,240 --> 00:31:26,640
Speaker 1: where they're on their landscape. So in its simplicit, you know,

613
00:31:26,800 --> 00:31:30,160
Speaker 1: in its simplicity, what deer doing is going from a

614
00:31:30,200 --> 00:31:34,280
Speaker 1: time when they're eating a lot of broad leaved, nonwoody

615
00:31:34,400 --> 00:31:39,720
Speaker 1: vegetation forbes, um, things like you know in row crop

616
00:31:39,800 --> 00:31:44,000
Speaker 1: agg or herbaceous naturally occurring vegetation that you might find

617
00:31:44,000 --> 00:31:46,400
Speaker 1: in fields or on the wood edges or even in

618
00:31:46,680 --> 00:31:50,720
Speaker 1: wood wooded settings too, a time where they're trying to

619
00:31:50,840 --> 00:31:55,760
Speaker 1: change to a high carb, high fat diet where they're

620
00:31:55,800 --> 00:31:59,040
Speaker 1: trying to put on weight, so that food change is

621
00:31:59,120 --> 00:32:02,760
Speaker 1: also is also driving where they're going to be UM.

622
00:32:03,040 --> 00:32:06,040
Speaker 1: So when a deer is existing in it's in its

623
00:32:06,160 --> 00:32:08,640
Speaker 1: own home range. That's what we call it. Where a

624
00:32:08,680 --> 00:32:13,640
Speaker 1: deer is about of the year UM where they will

625
00:32:13,680 --> 00:32:17,280
Speaker 1: be found within their home range is definitely there's a

626
00:32:17,280 --> 00:32:20,200
Speaker 1: lot of variation to it, and they're changing at this

627
00:32:20,280 --> 00:32:23,600
Speaker 1: time of year specifically one of the biggest changes. The

628
00:32:23,600 --> 00:32:25,840
Speaker 1: next time it will change again is probably when they're

629
00:32:25,840 --> 00:32:28,760
Speaker 1: going into in the areas that have really bad winners

630
00:32:28,760 --> 00:32:31,800
Speaker 1: and severe snowstorms and things like that, they'll change again.

631
00:32:31,840 --> 00:32:35,400
Speaker 1: But you might see dear all summer going into September,

632
00:32:36,000 --> 00:32:39,800
Speaker 1: UM even into early October, and now is where they're

633
00:32:39,960 --> 00:32:42,920
Speaker 1: they're shifting where they live and they're shifting what they eat.

634
00:32:43,400 --> 00:32:46,520
Speaker 1: And that is the primary reason why people start seeing

635
00:32:46,560 --> 00:32:52,000
Speaker 1: differences in activity and visibility and observations of box because

636
00:32:52,000 --> 00:32:54,480
Speaker 1: they're just changing and they're getting ready for it. Um

637
00:32:54,600 --> 00:32:57,880
Speaker 1: certainly with the rock coming up, they're they're going to

638
00:32:57,960 --> 00:33:02,840
Speaker 1: be uh using more of that that space, more of

639
00:33:02,880 --> 00:33:07,400
Speaker 1: their home range uh and that willing cause and they

640
00:33:07,440 --> 00:33:09,840
Speaker 1: also reduced their intake. That was actually some of the

641
00:33:09,880 --> 00:33:12,280
Speaker 1: research I got to be part of in New Hampshire.

642
00:33:13,080 --> 00:33:17,240
Speaker 1: It was really really interesting. A lot of people don't realize.

643
00:33:17,280 --> 00:33:19,760
Speaker 1: I mean, there's kind of theories out there, I guess,

644
00:33:19,840 --> 00:33:24,120
Speaker 1: myths that deer reduced them metabolism in winter. That's not

645
00:33:24,160 --> 00:33:26,360
Speaker 1: the case. They don't change their metabolic rate at all.

646
00:33:26,400 --> 00:33:28,320
Speaker 1: It's not something they have the choice of doing. Their

647
00:33:28,560 --> 00:33:31,440
Speaker 1: top Their metabolic rate doesn't change. But what deer do

648
00:33:31,640 --> 00:33:34,120
Speaker 1: was just reduce activity going out of the right in

649
00:33:34,160 --> 00:33:39,120
Speaker 1: the winter and they live off their h their body fat,

650
00:33:39,280 --> 00:33:41,200
Speaker 1: you know, all those cards that they're trying to take

651
00:33:41,240 --> 00:33:44,320
Speaker 1: in their bulking up, and they can lose up to

652
00:33:45,560 --> 00:33:47,480
Speaker 1: of their body weight over the winter when they're in

653
00:33:47,480 --> 00:33:51,440
Speaker 1: that time scarcity. And the really interesting thing. When I

654
00:33:51,520 --> 00:33:54,640
Speaker 1: was at this research facility in grad school, we had

655
00:33:54,720 --> 00:33:57,440
Speaker 1: deer that were raised from you know, they were bottle

656
00:33:57,440 --> 00:34:00,560
Speaker 1: fed um. You could almost like them to cattle, but

657
00:34:00,800 --> 00:34:02,760
Speaker 1: they were they were a lot more wild than that.

658
00:34:02,800 --> 00:34:08,440
Speaker 1: But they were fed pellatic grain or just basically bag feed,

659
00:34:08,960 --> 00:34:11,719
Speaker 1: and we monitored that, you know, what we bought and

660
00:34:11,719 --> 00:34:13,920
Speaker 1: what we put out there for them. And this is

661
00:34:13,960 --> 00:34:17,480
Speaker 1: the case throughout the country. But they would just voluntarily

662
00:34:17,560 --> 00:34:22,200
Speaker 1: stop eating in the winter, even though they had free

663
00:34:22,239 --> 00:34:25,040
Speaker 1: choice to it. You know, it was they were in

664
00:34:25,080 --> 00:34:28,000
Speaker 1: a time of deep cold temperatures. You're talking about northern

665
00:34:28,000 --> 00:34:30,760
Speaker 1: New England, you know, deep snows, and they had food

666
00:34:30,760 --> 00:34:33,920
Speaker 1: there and you would think these deer would walk, you know,

667
00:34:34,000 --> 00:34:37,160
Speaker 1: a short distance within their pens to eat this food

668
00:34:37,160 --> 00:34:40,200
Speaker 1: and they'd be fine. Now they you know, their ancestors

669
00:34:40,239 --> 00:34:45,640
Speaker 1: had had, I guess, given them the gift of bulking

670
00:34:45,719 --> 00:34:48,240
Speaker 1: up and their and their intake would go up throughout

671
00:34:48,239 --> 00:34:51,560
Speaker 1: the fall and then it would stop and they would

672
00:34:51,600 --> 00:34:53,919
Speaker 1: stop eating. I mean, that's just what they do. They've

673
00:34:53,960 --> 00:34:57,480
Speaker 1: evolved to do that. So as the year is changing,

674
00:34:57,960 --> 00:35:02,320
Speaker 1: going from you know again July August, when we're seeing

675
00:35:02,400 --> 00:35:04,799
Speaker 1: dear doing what we see them do, and they're very

676
00:35:04,920 --> 00:35:09,440
Speaker 1: very visible right now, you know, getting into late October,

677
00:35:09,880 --> 00:35:12,560
Speaker 1: and of course you know many people are your listeners

678
00:35:12,600 --> 00:35:15,600
Speaker 1: are deer hunters. They're changing again in November December for

679
00:35:15,680 --> 00:35:18,200
Speaker 1: most of the country, that's their breathing season and they're

680
00:35:18,239 --> 00:35:22,600
Speaker 1: going to change again. So Um, they're very adaptable. And

681
00:35:22,640 --> 00:35:26,719
Speaker 1: it's based on the evolution of the animal surviving and

682
00:35:26,800 --> 00:35:30,480
Speaker 1: needing to use those resources. So that that's in essence,

683
00:35:30,560 --> 00:35:34,160
Speaker 1: the core of why dear behavior and activity changes is

684
00:35:34,680 --> 00:35:38,080
Speaker 1: they're they're changing to survive. I have a real quick

685
00:35:38,160 --> 00:35:42,600
Speaker 1: question regarding survival based off of you know, like body

686
00:35:42,760 --> 00:35:47,680
Speaker 1: weight loss from the winner. Um. From my experience, I've

687
00:35:47,719 --> 00:35:52,680
Speaker 1: also seen bucks lose a lot of weight during the

688
00:35:52,800 --> 00:35:55,320
Speaker 1: rut because you know, they're just running all over the place.

689
00:35:56,440 --> 00:36:00,120
Speaker 1: Does that happen to affect a mortality rate higher in

690
00:36:00,200 --> 00:36:03,800
Speaker 1: bucks from winter kill because they're going into a winner

691
00:36:03,880 --> 00:36:06,279
Speaker 1: Let's say, if it's hard, if it's a hard winter,

692
00:36:06,400 --> 00:36:09,480
Speaker 1: lots of snow, um, not a lot of food. Have

693
00:36:09,560 --> 00:36:13,239
Speaker 1: you have you had any research that like that. Most

694
00:36:13,239 --> 00:36:15,400
Speaker 1: of that's a great question. Damn. Most of the research

695
00:36:15,440 --> 00:36:17,319
Speaker 1: suggests and this is the case in a lot of

696
00:36:17,320 --> 00:36:21,040
Speaker 1: those extreme environments you know, the loss of the deer

697
00:36:21,120 --> 00:36:22,880
Speaker 1: heard the animals that are going to die first or

698
00:36:22,920 --> 00:36:26,560
Speaker 1: the young and the oldest um. And certainly bucks are

699
00:36:26,600 --> 00:36:29,719
Speaker 1: part of that, even if they're not of older age. Um,

700
00:36:29,760 --> 00:36:32,000
Speaker 1: if you have an advanced age structure in your area,

701
00:36:32,040 --> 00:36:34,720
Speaker 1: that they would be ones they would lose. But bucks

702
00:36:34,719 --> 00:36:39,120
Speaker 1: are are just like you know they uh with young

703
00:36:39,160 --> 00:36:41,719
Speaker 1: men driving you know cars are insurance rates tend to

704
00:36:41,719 --> 00:36:44,160
Speaker 1: be higher than with women. You know, bucks throw a

705
00:36:44,200 --> 00:36:46,719
Speaker 1: lot more risk out there, um, so you do tend

706
00:36:46,760 --> 00:36:49,880
Speaker 1: to see a higher mortality from bucks. So a couple

707
00:36:49,920 --> 00:36:52,759
Speaker 1: of the specifically when you're talking about research, a couple

708
00:36:52,760 --> 00:36:54,640
Speaker 1: of the things that you might see there is in

709
00:36:54,640 --> 00:36:59,479
Speaker 1: a situation where you have a deer herd that there

710
00:36:59,760 --> 00:37:03,880
Speaker 1: is um a lot of imbalance to it, you know,

711
00:37:04,160 --> 00:37:07,839
Speaker 1: but heavy winners, you might see mortality in a little

712
00:37:07,840 --> 00:37:11,399
Speaker 1: bit younger ages with bucks than in other situations because

713
00:37:11,400 --> 00:37:16,000
Speaker 1: those younger bucks uh are are busy trying to breed,

714
00:37:16,080 --> 00:37:17,800
Speaker 1: so that they might be going into the winner with

715
00:37:17,840 --> 00:37:21,120
Speaker 1: a little bit more weight loss. Um. But when you

716
00:37:21,160 --> 00:37:24,280
Speaker 1: have a good, well balanced gar herd, that doesn't necessarily exist.

717
00:37:24,400 --> 00:37:27,000
Speaker 1: So yeah, that can happen. I mean you can see

718
00:37:27,000 --> 00:37:32,080
Speaker 1: some of your older box. Um. In situations where they're

719
00:37:32,120 --> 00:37:36,080
Speaker 1: just so rut drawn down and the winter might hit

720
00:37:36,160 --> 00:37:39,600
Speaker 1: early and it could be a really long they had winner, Uh,

721
00:37:39,640 --> 00:37:41,840
Speaker 1: you might lose some of them. The key there, though,

722
00:37:42,360 --> 00:37:47,359
Speaker 1: is not necessarily how early the winner is, or even

723
00:37:47,400 --> 00:37:50,920
Speaker 1: really how how late your winner exists. Um. You can

724
00:37:50,960 --> 00:37:54,280
Speaker 1: almost set a clock by it. Where this is something

725
00:37:54,280 --> 00:37:57,000
Speaker 1: called a winter severity index. I'm sure Mark's familiar with that,

726
00:37:57,120 --> 00:38:00,600
Speaker 1: being from Michigan. But um, there's basically be a ninety

727
00:38:00,640 --> 00:38:04,520
Speaker 1: day clock of having winter that deer have that fat

728
00:38:04,600 --> 00:38:09,600
Speaker 1: reserve there there there body can take loss. Uh. And

729
00:38:09,640 --> 00:38:12,840
Speaker 1: that's really those late March early April for most of

730
00:38:12,880 --> 00:38:15,480
Speaker 1: the North um Any, and that would be included where

731
00:38:15,480 --> 00:38:18,439
Speaker 1: you are, Dan. That ninety day clock is ticking once

732
00:38:18,480 --> 00:38:20,960
Speaker 1: it starts. It hasn't set right yet in most of

733
00:38:21,000 --> 00:38:23,880
Speaker 1: the country. I'm sure there's parts of extreme north and

734
00:38:24,000 --> 00:38:25,960
Speaker 1: up into Canada that might be it. But for the

735
00:38:26,000 --> 00:38:28,759
Speaker 1: most part that clock isn't ticking yet. Um. But that

736
00:38:29,480 --> 00:38:33,200
Speaker 1: clock starts sticking and once, and it's a combination of

737
00:38:33,200 --> 00:38:35,720
Speaker 1: cold temperatures. You don't necessarily have to have deep snow,

738
00:38:36,040 --> 00:38:40,799
Speaker 1: but either deep temperature or very low temperatures or really

739
00:38:40,840 --> 00:38:44,120
Speaker 1: deep snows or a combination of the two. Um At

740
00:38:44,120 --> 00:38:47,800
Speaker 1: that ninety day limit is when you start seeing loss.

741
00:38:48,040 --> 00:38:50,160
Speaker 1: But for the most part, you're not gonna lose deer.

742
00:38:50,560 --> 00:38:53,000
Speaker 1: If you're you could have a couple of really uh

743
00:38:53,480 --> 00:38:56,520
Speaker 1: site specific bad storms in the middle of January February,

744
00:38:56,800 --> 00:38:59,480
Speaker 1: deer can make it through that. They they're built to

745
00:38:59,520 --> 00:39:03,640
Speaker 1: do it. Um. It's those late storms that really really

746
00:39:03,680 --> 00:39:06,759
Speaker 1: can take out some of those individuals. So UM with

747
00:39:06,840 --> 00:39:10,239
Speaker 1: bucks in particular, I mean, you want to see good

748
00:39:10,320 --> 00:39:12,480
Speaker 1: rotting behavior, right. You want to see bucks chasing, you

749
00:39:12,520 --> 00:39:15,120
Speaker 1: want to see um them running all over the place.

750
00:39:15,160 --> 00:39:18,319
Speaker 1: So if you have a good balanced age structure, you

751
00:39:18,400 --> 00:39:21,640
Speaker 1: should enjoy that aspect of it, not worried about losing

752
00:39:21,680 --> 00:39:25,120
Speaker 1: that buck. To winner. The key there is UH. If

753
00:39:25,120 --> 00:39:27,600
Speaker 1: you have a long winter that's longer than ninety days,

754
00:39:28,400 --> 00:39:30,799
Speaker 1: do they have the resources on your property? Have you

755
00:39:30,840 --> 00:39:34,160
Speaker 1: managed it so that they at least can get access

756
00:39:34,200 --> 00:39:36,479
Speaker 1: to something that will keep them through that last week

757
00:39:36,600 --> 00:39:39,600
Speaker 1: or two or three to the point where snow starts

758
00:39:39,640 --> 00:39:45,040
Speaker 1: disappearing or temperatures start increasing. Interesting. So, so we we

759
00:39:45,080 --> 00:39:47,799
Speaker 1: talked a little about foods impact earlier in the years,

760
00:39:47,800 --> 00:39:49,439
Speaker 1: are starting to ramp up and now we've talked about

761
00:39:49,480 --> 00:39:52,080
Speaker 1: the impact of the clock, the winter clock in the

762
00:39:52,160 --> 00:39:54,560
Speaker 1: late season and then getting that food eventual in the spring.

763
00:39:54,600 --> 00:39:59,480
Speaker 1: But the other aspect of changing, dear physiology, and this

764
00:40:00,000 --> 00:40:03,160
Speaker 1: we're talking you know, September October coming into this time

765
00:40:03,200 --> 00:40:05,560
Speaker 1: period right now, that the second piece of white tailed

766
00:40:05,560 --> 00:40:09,320
Speaker 1: biology that's changing, as we all know, is the aspect

767
00:40:09,360 --> 00:40:13,000
Speaker 1: related to breeding and rising to stosterone levels and bucks

768
00:40:13,040 --> 00:40:16,880
Speaker 1: and everything like that. And the topic of the rut

769
00:40:17,120 --> 00:40:19,840
Speaker 1: and when it's actually going to happen is probably like

770
00:40:19,880 --> 00:40:23,719
Speaker 1: the most contentious debated desire to know topic out there

771
00:40:23,760 --> 00:40:25,239
Speaker 1: when it comes to deer. I mean, this thing is

772
00:40:25,239 --> 00:40:29,640
Speaker 1: just google to all get out all fall, um, and

773
00:40:29,640 --> 00:40:31,799
Speaker 1: there's lots of strong opinions on it. I know where

774
00:40:31,800 --> 00:40:33,640
Speaker 1: you stand on this map, but I would love to

775
00:40:33,719 --> 00:40:38,800
Speaker 1: hear from you an explanation of what impacts or influences

776
00:40:38,840 --> 00:40:41,280
Speaker 1: the timing of the rut, What are those, what's the factors,

777
00:40:41,560 --> 00:40:44,239
Speaker 1: what's the science behind it so everyone can understand what's

778
00:40:44,280 --> 00:40:48,000
Speaker 1: happening here. Okay, So when it comes down to a

779
00:40:48,000 --> 00:40:50,720
Speaker 1: lot of things in the dearest physiology, and I imagine

780
00:40:50,760 --> 00:40:53,719
Speaker 1: that's what you're hinting at even earlier, Um, a lot

781
00:40:53,760 --> 00:40:56,239
Speaker 1: of it is driven by photo period. And I'm sure

782
00:40:56,320 --> 00:40:58,239
Speaker 1: most people have heard that, but I'll explain it. That's

783
00:40:58,280 --> 00:41:00,960
Speaker 1: the amount of daylight in a twenty for our period.

784
00:41:01,040 --> 00:41:04,160
Speaker 1: So right now, you know, actually I think it's next weekend.

785
00:41:04,160 --> 00:41:08,840
Speaker 1: Our clocks can uh get changed for the fall fall period.

786
00:41:09,280 --> 00:41:12,239
Speaker 1: We all know that. You know, it's getting lighter later

787
00:41:12,280 --> 00:41:14,800
Speaker 1: in the morning and it's getting darker earlier in the evening,

788
00:41:14,800 --> 00:41:17,800
Speaker 1: and that's just the amount of daylight we have. Um,

789
00:41:17,840 --> 00:41:19,880
Speaker 1: A lot of things in a in a world of

790
00:41:19,960 --> 00:41:23,920
Speaker 1: deer is dependent on that change of photo period, and

791
00:41:23,920 --> 00:41:25,239
Speaker 1: that's where you kind of get into some of this

792
00:41:25,320 --> 00:41:28,359
Speaker 1: other stuff with moon and other things. I can tell

793
00:41:28,400 --> 00:41:31,200
Speaker 1: you what we know through research. Um, you know, the

794
00:41:31,400 --> 00:41:35,200
Speaker 1: cycle of antler growth is dependent on photo period to

795
00:41:35,280 --> 00:41:38,319
Speaker 1: the point where I mean a lot of folks felt

796
00:41:38,360 --> 00:41:40,760
Speaker 1: they haven't heard this before. But back in the day

797
00:41:41,160 --> 00:41:43,320
Speaker 1: they were able to do a little bit different stuff

798
00:41:43,360 --> 00:41:47,080
Speaker 1: with uh, you know, animal care and stuff with research. Um,

799
00:41:47,120 --> 00:41:50,200
Speaker 1: there has been research that was has tested photo period

800
00:41:50,200 --> 00:41:53,879
Speaker 1: with deer just to make bucks grow more than one

801
00:41:53,920 --> 00:41:56,360
Speaker 1: set out of antlers in one year, just by altering

802
00:41:56,360 --> 00:41:58,920
Speaker 1: the photo period of what that deer was seeing. So

803
00:41:59,280 --> 00:42:01,880
Speaker 1: we all know that. You know, they grow velvet antlers,

804
00:42:02,320 --> 00:42:05,640
Speaker 1: they shed that velvet, the anilers hardened. Um. They hold

805
00:42:05,680 --> 00:42:07,719
Speaker 1: those hard antlers for a period of time and then

806
00:42:08,320 --> 00:42:10,200
Speaker 1: um they drop them and they grow a new set

807
00:42:10,239 --> 00:42:13,680
Speaker 1: next year. Um. In research, they actually have done this

808
00:42:13,840 --> 00:42:17,879
Speaker 1: in a couple instances where they had uh photo controlled

809
00:42:18,080 --> 00:42:20,840
Speaker 1: rooms where the deer were in and we're able to

810
00:42:20,880 --> 00:42:25,280
Speaker 1: alter the amount of light to mimic basically two days

811
00:42:25,280 --> 00:42:28,759
Speaker 1: in a twenty four hour period and and make a

812
00:42:28,800 --> 00:42:31,600
Speaker 1: deer grow multiple sets of antlers in the year. Uh.

813
00:42:31,760 --> 00:42:33,920
Speaker 1: Maybe not quite exactly like that, but that that is

814
00:42:34,000 --> 00:42:37,359
Speaker 1: the case. They can do some of those things. Um. Yeah,

815
00:42:37,360 --> 00:42:41,160
Speaker 1: so photo period drives antler growth. We know photo period

816
00:42:41,200 --> 00:42:44,640
Speaker 1: also drives the rot or the breeding season. When you're

817
00:42:44,640 --> 00:42:48,359
Speaker 1: talking about the rot, the act of you know, the

818
00:42:48,400 --> 00:42:54,319
Speaker 1: popular at a population level, most dear successfully breeding and

819
00:42:54,920 --> 00:42:59,239
Speaker 1: raising young you know, becoming pregnant and raising another off

820
00:42:59,520 --> 00:43:02,680
Speaker 1: group of offspring another cohord Um. How do we know that?

821
00:43:02,800 --> 00:43:06,400
Speaker 1: So it's a it's kind of a domino effect of

822
00:43:06,520 --> 00:43:10,160
Speaker 1: chemicals and the deer's body. But as the photo period

823
00:43:11,160 --> 00:43:15,600
Speaker 1: changes and there's less daylight, um, that domino effect. The

824
00:43:15,719 --> 00:43:20,600
Speaker 1: end result is uh, testosterone increases in the box. Actually,

825
00:43:20,640 --> 00:43:24,279
Speaker 1: their testes increase in size, and so does their neck.

826
00:43:24,320 --> 00:43:28,000
Speaker 1: Their neck swells from testosterone. Just like a bodybuilder given

827
00:43:28,080 --> 00:43:32,040
Speaker 1: him shelf self shots of testosterone, he's growing and muscle.

828
00:43:32,640 --> 00:43:36,759
Speaker 1: That that is what's happening, and that domino effect is

829
00:43:36,800 --> 00:43:40,439
Speaker 1: this chain reaction of UM. The amount of daylight going

830
00:43:40,440 --> 00:43:45,200
Speaker 1: in endears eyeball, a buck's eyeball, it triggers the release

831
00:43:45,480 --> 00:43:48,520
Speaker 1: of you know, the pituitary gland. There's a there's a

832
00:43:48,560 --> 00:43:53,240
Speaker 1: direct line between the the eyeball and the pineal gland

833
00:43:53,840 --> 00:43:57,880
Speaker 1: which is in the brain, and that releases like a

834
00:43:58,960 --> 00:44:04,400
Speaker 1: type of hormone which releases uh. It's it's down the line.

835
00:44:04,440 --> 00:44:08,200
Speaker 1: But basically what it does is it tells the testies

836
00:44:08,239 --> 00:44:11,719
Speaker 1: to get bigger and to start producing more testosterone, and

837
00:44:11,760 --> 00:44:15,080
Speaker 1: it gets the bucks primed. And uh, the same thing

838
00:44:15,160 --> 00:44:20,000
Speaker 1: with with those Uh. Photo period is driving her ability

839
00:44:20,040 --> 00:44:23,080
Speaker 1: to come into estrus or coming to eat heat. And

840
00:44:23,120 --> 00:44:27,360
Speaker 1: they've done experiments again in the instance where they can

841
00:44:27,480 --> 00:44:30,160
Speaker 1: you know, alter some of that and make a make

842
00:44:30,239 --> 00:44:32,719
Speaker 1: a buck a lot more than once a year or

843
00:44:32,760 --> 00:44:36,040
Speaker 1: those types of things, so UM in controlled experience, they

844
00:44:36,080 --> 00:44:39,360
Speaker 1: know photo period is at the heart of all that um.

845
00:44:39,400 --> 00:44:42,520
Speaker 1: You know, then you get into the nuances of well,

846
00:44:42,719 --> 00:44:46,919
Speaker 1: is the moon offering more light during times of the year,

847
00:44:47,520 --> 00:44:50,840
Speaker 1: and it's gonna you know, cuua win a deer breeds

848
00:44:50,840 --> 00:44:53,120
Speaker 1: and things like that, and there's there's a lot of

849
00:44:53,239 --> 00:44:56,040
Speaker 1: ambiguity there, you know, it's it's a little bit confusing

850
00:44:56,120 --> 00:44:59,200
Speaker 1: because what we see is hunters isn't necessarily the truth

851
00:44:59,280 --> 00:45:03,319
Speaker 1: of when when copulations or breeding is occurring. But um

852
00:45:03,719 --> 00:45:07,360
Speaker 1: for for for the most part, none of that is

853
00:45:07,400 --> 00:45:11,439
Speaker 1: impacted more than anything than daylight. And if you think

854
00:45:11,440 --> 00:45:14,200
Speaker 1: about it from the perspective of most of the country,

855
00:45:14,920 --> 00:45:18,480
Speaker 1: especially you know, northern northern US and going up in Canada,

856
00:45:18,520 --> 00:45:20,760
Speaker 1: you're talking about a large large section of North America

857
00:45:20,800 --> 00:45:25,719
Speaker 1: where deer are, it wouldn't make sense to have the

858
00:45:25,719 --> 00:45:29,440
Speaker 1: moon really change when the breeding is occurring by a

859
00:45:29,520 --> 00:45:32,560
Speaker 1: lot um And it can be you know, moon phase

860
00:45:32,640 --> 00:45:36,160
Speaker 1: can can be a little bit different um every year,

861
00:45:36,239 --> 00:45:38,879
Speaker 1: but it can be several weeks off and you could

862
00:45:38,920 --> 00:45:42,000
Speaker 1: be talking about, you know, from year to year, and

863
00:45:42,040 --> 00:45:45,040
Speaker 1: you could be talking about the pregnancy of the deer's

864
00:45:45,080 --> 00:45:49,720
Speaker 1: two hundred days. So when you're changing when deer breeding,

865
00:45:50,400 --> 00:45:53,080
Speaker 1: you're changing when the bulk of the fonds are being

866
00:45:53,160 --> 00:45:56,360
Speaker 1: born and it just doesn't make It's an environmental advantage

867
00:45:56,360 --> 00:45:59,600
Speaker 1: for them to have to give birth early enough in

868
00:45:59,600 --> 00:46:02,480
Speaker 1: the summer or those so those fawns can get on

869
00:46:02,520 --> 00:46:05,160
Speaker 1: the ground and start eating real vegetation and grow big

870
00:46:05,280 --> 00:46:07,960
Speaker 1: enough so that they can make it the following winter. Um.

871
00:46:08,000 --> 00:46:11,200
Speaker 1: If they're born too late, they might not make it

872
00:46:11,239 --> 00:46:13,279
Speaker 1: their first winter. If they're born too early, they might

873
00:46:13,320 --> 00:46:15,000
Speaker 1: not even make it to see a couple of months old.

874
00:46:15,040 --> 00:46:18,120
Speaker 1: Because they could you could have one of those late storms. Um.

875
00:46:18,160 --> 00:46:20,120
Speaker 1: Just like with turkey broods, you know, you might have

876
00:46:20,160 --> 00:46:23,560
Speaker 1: something that happens and you lose it. And for deer,

877
00:46:23,600 --> 00:46:26,279
Speaker 1: they are going to breed once a year. It's not Uh,

878
00:46:26,440 --> 00:46:28,480
Speaker 1: it's not going to happen multiple times. So they have

879
00:46:28,560 --> 00:46:32,200
Speaker 1: that one shot. So photo period is the core of

880
00:46:32,200 --> 00:46:37,680
Speaker 1: of everything. How how long does a dough ovulate? How

881
00:46:37,680 --> 00:46:40,520
Speaker 1: long does she ovulate? They're much like any other mammal,

882
00:46:40,600 --> 00:46:43,760
Speaker 1: just like a human. They will come into a stress

883
00:46:43,760 --> 00:46:49,160
Speaker 1: every twenty eight days. Um. So in the wild, Uh,

884
00:46:49,160 --> 00:46:51,720
Speaker 1: you know, a deer can go if she's not bred

885
00:46:52,320 --> 00:46:55,360
Speaker 1: a couple of times to three times. I think the

886
00:46:55,440 --> 00:46:58,400
Speaker 1: most ever recorded in captivity was five or six or

887
00:46:58,440 --> 00:47:00,920
Speaker 1: seven times. Now you're talking about five or six or

888
00:47:00,960 --> 00:47:03,640
Speaker 1: seven months, and some of that was probably altered with

889
00:47:04,520 --> 00:47:07,560
Speaker 1: what the research we're doing. But you would see, you know,

890
00:47:07,680 --> 00:47:11,959
Speaker 1: for a early breeding deer October late October like right now.

891
00:47:12,040 --> 00:47:16,440
Speaker 1: I'm sure there are some cases. It's a small small

892
00:47:16,520 --> 00:47:19,520
Speaker 1: portion considering the bulk of deer out there, but you

893
00:47:19,560 --> 00:47:22,080
Speaker 1: know there are there's deer breeding right now across the country.

894
00:47:22,080 --> 00:47:25,360
Speaker 1: It's late October. H ones that come into heat and

895
00:47:25,360 --> 00:47:28,319
Speaker 1: miss it. You're talking about late November, they missed it again,

896
00:47:28,320 --> 00:47:31,520
Speaker 1: you're talking about late December. That's probably going to be

897
00:47:31,840 --> 00:47:33,680
Speaker 1: for the ball. There might be a couple other ones

898
00:47:33,719 --> 00:47:35,520
Speaker 1: that might do it a fourth time, but I mean,

899
00:47:35,560 --> 00:47:38,920
Speaker 1: that's two or three times in the wild is about

900
00:47:38,920 --> 00:47:42,840
Speaker 1: what you'll see. So so then Matt, if what I

901
00:47:42,920 --> 00:47:45,800
Speaker 1: you know, from what I understand, given this this science,

902
00:47:45,880 --> 00:47:48,640
Speaker 1: that that proves that the photo period is impacting the roup,

903
00:47:48,800 --> 00:47:51,440
Speaker 1: and the photo period is consistent year after year, that

904
00:47:51,560 --> 00:47:53,480
Speaker 1: for the majority of the country that you're talking about,

905
00:47:53,560 --> 00:47:57,600
Speaker 1: especially in the northern portion, peak breeding dates then would

906
00:47:57,600 --> 00:48:00,799
Speaker 1: be quite consistent year after and then it's a bell

907
00:48:00,880 --> 00:48:03,799
Speaker 1: curve from there. So hypothetically, let's say in a lot

908
00:48:03,800 --> 00:48:06,440
Speaker 1: of States. From what I understand, peak breeding is usually

909
00:48:06,440 --> 00:48:09,320
Speaker 1: around that middle of November. So let's say November fifteen

910
00:48:09,440 --> 00:48:12,000
Speaker 1: maybe is your peak breeding date where the highest proportion

911
00:48:12,080 --> 00:48:14,759
Speaker 1: of the population is bred. And then it declines a

912
00:48:14,760 --> 00:48:16,680
Speaker 1: little bit on either side of that peak. So then

913
00:48:16,680 --> 00:48:19,080
Speaker 1: there's there's some breeding on the fourteenth and sixteenth, and

914
00:48:19,120 --> 00:48:20,960
Speaker 1: a little bit less than the thirteenth and seventeenth, and

915
00:48:21,000 --> 00:48:23,239
Speaker 1: a little bit less on the twelfth and the eighteenth, etcetera.

916
00:48:23,760 --> 00:48:25,680
Speaker 1: Is that is that accurate? That that is what we're

917
00:48:25,680 --> 00:48:28,480
Speaker 1: seeing when we actually look at the actual breeding dates

918
00:48:28,800 --> 00:48:31,000
Speaker 1: and then the research that shows you know when those

919
00:48:31,040 --> 00:48:34,000
Speaker 1: actually happened. Yeah, you're nailed on the head. I mean,

920
00:48:34,000 --> 00:48:36,440
Speaker 1: it's all bell shaped curve. The difference there. And again

921
00:48:36,440 --> 00:48:38,240
Speaker 1: this is coming back to me being a deer hunter.

922
00:48:38,680 --> 00:48:40,759
Speaker 1: It's different than what you're seeing though. You know what

923
00:48:40,880 --> 00:48:44,920
Speaker 1: you're seeing in terms of activity when deer actually breeding. UM,

924
00:48:45,120 --> 00:48:49,120
Speaker 1: their behavior is very specific in terms of how white

925
00:48:49,160 --> 00:48:53,840
Speaker 1: tail actually breeds. UM. They're not gregarious like elk or

926
00:48:53,880 --> 00:48:57,040
Speaker 1: other herding animals, where you know, one bowl will have

927
00:48:57,239 --> 00:49:02,400
Speaker 1: multiple cows. Um. White ls are driven to a phase

928
00:49:02,440 --> 00:49:06,800
Speaker 1: of breeding where um, they're segregated. You know, their boxing

929
00:49:06,880 --> 00:49:10,000
Speaker 1: dolls are separate in different groups. Obviously you guys have

930
00:49:10,080 --> 00:49:13,160
Speaker 1: talked about this before. The bucks will form bachelor groups.

931
00:49:13,160 --> 00:49:14,920
Speaker 1: In the summer, they break up and those bucks are

932
00:49:14,960 --> 00:49:17,440
Speaker 1: loners for the rest of the fall, you know, searching

933
00:49:17,440 --> 00:49:22,759
Speaker 1: out doors. And the time spent with doll when he's

934
00:49:22,880 --> 00:49:26,440
Speaker 1: breeding her is going to be a day or a

935
00:49:26,440 --> 00:49:28,520
Speaker 1: couple of days. So he'll spend a couple of days

936
00:49:28,600 --> 00:49:33,160
Speaker 1: chasing around, uh, looking for locating a doll that's receptive,

937
00:49:33,200 --> 00:49:35,600
Speaker 1: will spend a day or two with her and keep looking.

938
00:49:36,239 --> 00:49:38,760
Speaker 1: The frenzy of when a lot of that is happening.

939
00:49:38,760 --> 00:49:40,960
Speaker 1: You know, when you're sitting in your standing there there's

940
00:49:41,040 --> 00:49:45,040
Speaker 1: three or four bucks chasing one dough um or multiple

941
00:49:45,080 --> 00:49:48,200
Speaker 1: box just cruising by. That would not be considered the

942
00:49:48,200 --> 00:49:52,440
Speaker 1: peak of the rut, the breeding phase, because these are

943
00:49:52,440 --> 00:49:54,920
Speaker 1: dear outlooking. That's probably just prior to all of that,

944
00:49:55,080 --> 00:49:57,719
Speaker 1: so you know, and one of the cool things is

945
00:49:57,880 --> 00:50:01,480
Speaker 1: observations of hunters can be area from property to property,

946
00:50:01,560 --> 00:50:04,160
Speaker 1: from county to county, and definitely from state to state.

947
00:50:04,239 --> 00:50:07,160
Speaker 1: So um, when you get down to it, well hunters

948
00:50:07,200 --> 00:50:08,560
Speaker 1: want to know about the run is how can they

949
00:50:08,640 --> 00:50:11,799
Speaker 1: kill something? Right? When should I be out there. Yes,

950
00:50:11,960 --> 00:50:15,360
Speaker 1: for the most part, it's consistent year to year. You

951
00:50:15,400 --> 00:50:18,640
Speaker 1: can pick the first or second and in some cases

952
00:50:18,719 --> 00:50:21,600
Speaker 1: third week in November and take time off and go

953
00:50:21,640 --> 00:50:24,160
Speaker 1: out there and hunt, and you're gonna see some activity.

954
00:50:24,680 --> 00:50:26,520
Speaker 1: It's a bomber when you're out there and you're not

955
00:50:26,600 --> 00:50:29,040
Speaker 1: seeing much and that is impacted by other things. There

956
00:50:29,080 --> 00:50:33,160
Speaker 1: are other influences, um, that can change that. Again, this

957
00:50:33,239 --> 00:50:35,520
Speaker 1: goes back to the research where you know, what I

958
00:50:35,560 --> 00:50:38,320
Speaker 1: can tell you, uh, you know, in terms of weather

959
00:50:38,400 --> 00:50:40,840
Speaker 1: and things, what the research says. You know, my gut

960
00:50:40,840 --> 00:50:42,920
Speaker 1: tells me some of that stuff is not you know,

961
00:50:42,960 --> 00:50:45,400
Speaker 1: there's something that we haven't found out yet. Um. And

962
00:50:45,400 --> 00:50:47,040
Speaker 1: I'll just tell you for the most part, there hasn't

963
00:50:47,040 --> 00:50:50,600
Speaker 1: been any research that says weather and I'm talking about

964
00:50:50,640 --> 00:50:53,840
Speaker 1: everything from their metric pressure, to rain events, to temperature

965
00:50:53,880 --> 00:50:58,040
Speaker 1: drops to all this stuff has We're talking about collar deer,

966
00:50:58,239 --> 00:51:01,320
Speaker 1: hundreds of collar deer in some races in some of

967
00:51:01,360 --> 00:51:04,799
Speaker 1: these studies and have not seen a correlation to a

968
00:51:04,800 --> 00:51:08,200
Speaker 1: weather change. Almost every variable you can think of with

969
00:51:08,280 --> 00:51:12,080
Speaker 1: weather and see any difference in deer activity. Again, we

970
00:51:12,120 --> 00:51:14,680
Speaker 1: don't know. We don't have cameras on these deer. We

971
00:51:14,680 --> 00:51:16,520
Speaker 1: don't know if they're actually breeding, but we can actually

972
00:51:16,560 --> 00:51:19,359
Speaker 1: monitor activity, how much they're moving in a day UM

973
00:51:19,560 --> 00:51:22,879
Speaker 1: or twenty four hour period or how long those distances are.

974
00:51:22,920 --> 00:51:25,120
Speaker 1: And there hasn't been any My gut tells me there's

975
00:51:25,160 --> 00:51:29,359
Speaker 1: something weather related out there. UM. But and I still

976
00:51:29,400 --> 00:51:32,720
Speaker 1: want to plan when I'm hunting based on some of that. UM.

977
00:51:32,760 --> 00:51:35,040
Speaker 1: But the neat thing is I can go out there

978
00:51:35,080 --> 00:51:37,239
Speaker 1: and sit out there and see a friends the activity

979
00:51:37,600 --> 00:51:39,600
Speaker 1: I get. Have a buddy two counties over that I'm

980
00:51:39,640 --> 00:51:44,000
Speaker 1: texting that's seeing completely something different, and that's property specific.

981
00:51:44,520 --> 00:51:47,400
Speaker 1: It's even the deer herds specific to that property. Based

982
00:51:47,440 --> 00:51:51,360
Speaker 1: on those deer. I mean, maybe the dose on the

983
00:51:51,400 --> 00:51:54,840
Speaker 1: property I'm on are all synchronized and they're all coming

984
00:51:54,840 --> 00:51:57,640
Speaker 1: into estres around the same time or just before, or

985
00:51:57,880 --> 00:52:01,839
Speaker 1: maybe there's those handful of really breeding events that are

986
00:52:01,840 --> 00:52:04,440
Speaker 1: happening that are making all bucks go crazy. I mean,

987
00:52:04,520 --> 00:52:06,719
Speaker 1: it's so site specific and one of the cool things

988
00:52:06,719 --> 00:52:09,480
Speaker 1: that we've done at q d M. A UM is

989
00:52:09,520 --> 00:52:14,360
Speaker 1: partnered with some other organizations uh Sitka, Cabella's and others

990
00:52:14,920 --> 00:52:17,759
Speaker 1: with powder Hook and developed an app to track some

991
00:52:17,880 --> 00:52:20,920
Speaker 1: of that stuff to create a heat map UM of

992
00:52:21,040 --> 00:52:24,880
Speaker 1: daytime activity where you can just log in your observations

993
00:52:24,880 --> 00:52:27,879
Speaker 1: of what you're seeing or the deer you're killing, um,

994
00:52:28,000 --> 00:52:30,040
Speaker 1: and they take all that into account and create that

995
00:52:30,040 --> 00:52:32,799
Speaker 1: It's a really really neat thing. So when it comes

996
00:52:32,800 --> 00:52:34,399
Speaker 1: down to the rut, I mean, why do people want

997
00:52:34,400 --> 00:52:36,239
Speaker 1: to talk about it. I want to talk about it

998
00:52:36,239 --> 00:52:38,359
Speaker 1: because they want to figure out how they can best

999
00:52:38,400 --> 00:52:40,319
Speaker 1: be successful to go out there and shoot a deer,

1000
00:52:40,480 --> 00:52:43,840
Speaker 1: specifically a buck. One of the best things that I

1001
00:52:43,840 --> 00:52:46,560
Speaker 1: can offer to you is take this science and use

1002
00:52:46,640 --> 00:52:48,600
Speaker 1: it to the best of your ability. I mean, but

1003
00:52:48,640 --> 00:52:50,640
Speaker 1: at the same time, a lot of it has to

1004
00:52:50,680 --> 00:52:53,640
Speaker 1: be site specific. And some of the stuff that you

1005
00:52:53,640 --> 00:52:57,080
Speaker 1: guys talk about on your show is you as a hunter,

1006
00:52:57,239 --> 00:53:01,240
Speaker 1: you as a leasy or a landowner, just keeping tabs

1007
00:53:01,239 --> 00:53:04,839
Speaker 1: on that dear heart, either through trail cameras or individual

1008
00:53:04,920 --> 00:53:06,799
Speaker 1: box and tracking them throughout the year and getting a

1009
00:53:06,840 --> 00:53:09,520
Speaker 1: sense of when stuff is happening and trying to be

1010
00:53:09,640 --> 00:53:12,200
Speaker 1: ready for when it happens within the window of when

1011
00:53:12,239 --> 00:53:14,800
Speaker 1: the bigger science says, you know what, there's about a

1012
00:53:14,840 --> 00:53:16,560
Speaker 1: two two and a half week window when I should

1013
00:53:16,560 --> 00:53:18,879
Speaker 1: be out there, and then just try to target when

1014
00:53:18,920 --> 00:53:21,480
Speaker 1: you need to be out Yeah, that makes a lot

1015
00:53:21,480 --> 00:53:23,440
Speaker 1: of sense, and I think it's, you know, right in

1016
00:53:23,560 --> 00:53:26,560
Speaker 1: line with with what you said, is is looking at

1017
00:53:26,600 --> 00:53:29,560
Speaker 1: this the high level scientific data, but then to your point,

1018
00:53:30,120 --> 00:53:33,719
Speaker 1: understanding the site specific uniqueness of your property in the

1019
00:53:33,760 --> 00:53:37,319
Speaker 1: situation at hand. And that brings me to something that

1020
00:53:37,360 --> 00:53:40,200
Speaker 1: I that I've am equally fascinated by that I know

1021
00:53:40,280 --> 00:53:44,520
Speaker 1: you've looked into, which is actual buck behavior during the rut.

1022
00:53:44,960 --> 00:53:46,960
Speaker 1: I know there's been a number of GPS studies that

1023
00:53:47,000 --> 00:53:50,440
Speaker 1: have looked into this. Two things specifically that I have

1024
00:53:50,480 --> 00:53:53,200
Speaker 1: found interesting about behavior that these studies have shown are

1025
00:53:53,360 --> 00:53:56,839
Speaker 1: the phenomena of how they relate to focal points and

1026
00:53:56,840 --> 00:54:00,839
Speaker 1: then also this other phenomena of taking these excursion. Could

1027
00:54:00,840 --> 00:54:02,640
Speaker 1: you share with us a little bit about what these

1028
00:54:02,640 --> 00:54:06,080
Speaker 1: studies have found about buck behavior during the rut related

1029
00:54:06,080 --> 00:54:09,640
Speaker 1: to those two things, Yeah, no problem. Let me talk

1030
00:54:09,640 --> 00:54:12,680
Speaker 1: about the focal points first. Um. Aaron Foley, he was

1031
00:54:12,719 --> 00:54:14,800
Speaker 1: a research at Texas A and M and and a

1032
00:54:14,880 --> 00:54:16,759
Speaker 1: lot of his co authors looked at this. There was

1033
00:54:16,800 --> 00:54:20,040
Speaker 1: a multiple year study looking at a bunch of different

1034
00:54:20,160 --> 00:54:24,200
Speaker 1: things related to to buck and their use of space.

1035
00:54:24,239 --> 00:54:27,040
Speaker 1: And again it was out of Texas and for people

1036
00:54:27,080 --> 00:54:30,279
Speaker 1: that aren't qt m A members. This was actually a

1037
00:54:30,360 --> 00:54:33,000
Speaker 1: feature article in Quality White Till that's our publication that

1038
00:54:33,040 --> 00:54:35,320
Speaker 1: comes out every other month. UM. I think it was

1039
00:54:35,360 --> 00:54:39,040
Speaker 1: the last issue. UM. Really really interesting stuff in terms

1040
00:54:39,120 --> 00:54:42,880
Speaker 1: of how bucks use UM again, their home range or

1041
00:54:42,920 --> 00:54:46,759
Speaker 1: their co core areas over during the rut and how

1042
00:54:46,800 --> 00:54:50,359
Speaker 1: that changes. And for the most part, we've always and

1043
00:54:50,719 --> 00:54:54,080
Speaker 1: the research does point to bucks being individuals. You know,

1044
00:54:54,160 --> 00:54:56,520
Speaker 1: Some are up on their feet a lot, and they

1045
00:54:56,560 --> 00:54:59,000
Speaker 1: move a lot, you know, day or night. Some don't

1046
00:54:59,000 --> 00:55:01,759
Speaker 1: move that very much, have large home ranges, some have

1047
00:55:01,880 --> 00:55:04,279
Speaker 1: very small home ranges, and there's combinations of all four

1048
00:55:04,320 --> 00:55:07,799
Speaker 1: of those UM, and it really varies based on the

1049
00:55:07,880 --> 00:55:12,760
Speaker 1: individual book UM. When it comes to focal points. What

1050
00:55:12,960 --> 00:55:15,480
Speaker 1: Mark is asking about is this was one of the

1051
00:55:15,520 --> 00:55:21,319
Speaker 1: first studies that actually showed spatial memory, meaning a buck remembering,

1052
00:55:22,520 --> 00:55:26,200
Speaker 1: if you will, where dough groups are and returning to

1053
00:55:26,280 --> 00:55:30,919
Speaker 1: those places on a on a fairly consistent basis. UM.

1054
00:55:30,920 --> 00:55:33,680
Speaker 1: What the researchers found there was about every twenty to

1055
00:55:33,760 --> 00:55:38,080
Speaker 1: twenty eight hours UM. They had both Bucks and does

1056
00:55:38,200 --> 00:55:42,719
Speaker 1: collared UH, and they were able to document UH multiple

1057
00:55:42,800 --> 00:55:47,439
Speaker 1: box visiting what the researchers called focal areas. There would

1058
00:55:47,440 --> 00:55:51,200
Speaker 1: be some somewhere between one to three focal areas within

1059
00:55:51,239 --> 00:55:53,880
Speaker 1: that box home range. So if a buck was traveling,

1060
00:55:54,200 --> 00:55:56,839
Speaker 1: you know, thousand acres, that's what their home ranges. I'm

1061
00:55:56,880 --> 00:56:00,879
Speaker 1: just that's a um, just a ra number I'm coming

1062
00:56:00,960 --> 00:56:05,520
Speaker 1: up with. They might have a core area throughout most

1063
00:56:05,560 --> 00:56:09,200
Speaker 1: of the year of five to ten percent of that

1064
00:56:09,239 --> 00:56:12,360
Speaker 1: and that's basically what the research shows. UM. You know,

1065
00:56:12,480 --> 00:56:14,640
Speaker 1: between five to ten percent of a bucks home range

1066
00:56:14,640 --> 00:56:16,120
Speaker 1: will be its core are and it might not be

1067
00:56:16,239 --> 00:56:19,760
Speaker 1: one spot, it might be one or two. UM. During

1068
00:56:19,800 --> 00:56:24,160
Speaker 1: the rut, their home range expands, sometimes excessively three or

1069
00:56:24,200 --> 00:56:27,759
Speaker 1: four times a size, and they are using more of

1070
00:56:27,800 --> 00:56:32,400
Speaker 1: that space. UM. So the home range I defined it

1071
00:56:32,480 --> 00:56:36,200
Speaker 1: earlier as the space a buck is of the time

1072
00:56:36,520 --> 00:56:39,440
Speaker 1: the core area. As many hunters columns like their bedroom,

1073
00:56:39,480 --> 00:56:41,680
Speaker 1: they're there fifty percent of the time. Half the time

1074
00:56:41,680 --> 00:56:45,680
Speaker 1: you'll find the buck there. During the rut, bucks, he's

1075
00:56:45,800 --> 00:56:49,160
Speaker 1: less of their core area less often. They're not in

1076
00:56:49,239 --> 00:56:53,080
Speaker 1: that fifty space that as much, and they're they're using

1077
00:56:53,880 --> 00:56:57,359
Speaker 1: way more of that of their home range. They're out

1078
00:56:57,360 --> 00:56:59,000
Speaker 1: there a lot more than they used to, so they're

1079
00:56:59,000 --> 00:57:03,240
Speaker 1: shifting where they are in their home range. The really

1080
00:57:03,320 --> 00:57:08,280
Speaker 1: interesting thing though, is these researchers found that these bucks

1081
00:57:08,320 --> 00:57:12,120
Speaker 1: are not doing it randomly. They are picking these focal areas.

1082
00:57:12,440 --> 00:57:16,080
Speaker 1: They're you know, handful of them, usually three or four

1083
00:57:16,560 --> 00:57:19,080
Speaker 1: of them within the buck, within that buck's home range,

1084
00:57:19,600 --> 00:57:24,360
Speaker 1: where he's concentrating on it, spending some time there, leaving it,

1085
00:57:24,440 --> 00:57:27,480
Speaker 1: going to another one, leaving it, going to another one,

1086
00:57:27,800 --> 00:57:29,720
Speaker 1: leaving and going to another one, and returning to the

1087
00:57:29,760 --> 00:57:34,560
Speaker 1: original one. Every hours, that buck is returning to one

1088
00:57:34,600 --> 00:57:39,040
Speaker 1: of those spots. And with multiple bucks Collard um, they

1089
00:57:39,040 --> 00:57:42,040
Speaker 1: were able to see this on the landscape where there

1090
00:57:42,160 --> 00:57:45,800
Speaker 1: was and they also had dose Collard that there were

1091
00:57:46,880 --> 00:57:50,440
Speaker 1: spatial memory where bucks were returning to these spots saying

1092
00:57:50,880 --> 00:57:53,320
Speaker 1: you know there's a doe group there and you'd have

1093
00:57:53,400 --> 00:57:55,840
Speaker 1: one or two or three bucks returning to that spot

1094
00:57:56,000 --> 00:57:58,440
Speaker 1: at different periods to find them. So that gives a

1095
00:57:58,440 --> 00:58:02,080
Speaker 1: lot of confirmation to you know, the whole adage. You know,

1096
00:58:02,160 --> 00:58:04,760
Speaker 1: if you hunt where the does are, um, you'll see

1097
00:58:04,800 --> 00:58:08,919
Speaker 1: box or along those lines. Um. Yeah, that is true.

1098
00:58:08,960 --> 00:58:11,080
Speaker 1: I mean during the rut, bucks are trying to find

1099
00:58:11,120 --> 00:58:14,600
Speaker 1: these doughs, are checking the receptiveness possibly and returning And

1100
00:58:14,640 --> 00:58:16,919
Speaker 1: that research is ongoing, but that that is something that's

1101
00:58:16,960 --> 00:58:21,200
Speaker 1: really interesting. The other thing that Mark asked about was

1102
00:58:21,840 --> 00:58:25,600
Speaker 1: UM about excursions, and that's something else I've I've been

1103
00:58:25,640 --> 00:58:28,520
Speaker 1: able to look in depth at. And one of the

1104
00:58:28,560 --> 00:58:32,080
Speaker 1: things that we found with excursions is that they happen

1105
00:58:32,240 --> 00:58:36,320
Speaker 1: year round. By far, they're more rut related fall time

1106
00:58:36,400 --> 00:58:40,400
Speaker 1: excursions and there are spring but there has been documented

1107
00:58:40,440 --> 00:58:43,360
Speaker 1: cases from Pennsylvania all the way down to Louisiana and

1108
00:58:43,400 --> 00:58:48,600
Speaker 1: everywhere in between, from agriculture environments like Iowa and Maryland

1109
00:58:49,000 --> 00:58:54,400
Speaker 1: to heavily forested environments. UM. But bucks are making these excursions,

1110
00:58:54,400 --> 00:58:58,560
Speaker 1: and what they are is within that that home range

1111
00:58:58,560 --> 00:59:01,560
Speaker 1: where buck is ninety nine five percent a time, they

1112
00:59:01,640 --> 00:59:08,200
Speaker 1: might spend take sometimes one, sometimes multiple events where they

1113
00:59:08,320 --> 00:59:11,680
Speaker 1: leave that space. They're gone for a very short period

1114
00:59:11,720 --> 00:59:14,440
Speaker 1: of time, usually a day to thirty six hours, and

1115
00:59:14,480 --> 00:59:20,520
Speaker 1: they returned quickly. UM. There's by far more rut related

1116
00:59:20,560 --> 00:59:23,320
Speaker 1: excursions that are happening, almost probably a three to one

1117
00:59:23,920 --> 00:59:28,000
Speaker 1: UM and it's generally about half of bucks make them

1118
00:59:28,600 --> 00:59:33,480
Speaker 1: UM and the ones that do go the majority do

1119
00:59:33,600 --> 00:59:37,160
Speaker 1: it multiple times. It's almost going back to that individuality

1120
00:59:37,160 --> 00:59:39,960
Speaker 1: where you know, if a buck's got the propensity to

1121
00:59:40,040 --> 00:59:42,560
Speaker 1: do this, he might do that, so it lends a

1122
00:59:42,560 --> 00:59:45,480
Speaker 1: lot of credibility to the hunter. That's he's a buck

1123
00:59:45,520 --> 00:59:47,520
Speaker 1: show up on his trail camera, or you're sitting there

1124
00:59:47,560 --> 00:59:51,400
Speaker 1: and his deer comes cruising through that you've never seen before. Um,

1125
00:59:51,520 --> 00:59:54,480
Speaker 1: and you know you miss your chance at it and

1126
00:59:54,520 --> 00:59:57,040
Speaker 1: you never see that dear again. That could be a

1127
00:59:57,080 --> 01:00:00,520
Speaker 1: buck that was on an excursion or l wise, if

1128
01:00:00,560 --> 01:00:04,280
Speaker 1: you've been following a deer and you have great documentation

1129
01:00:04,360 --> 01:00:07,520
Speaker 1: of that buck even out of the summer getting into

1130
01:00:07,600 --> 01:00:09,800
Speaker 1: pre rod or even getting into you know, in the

1131
01:00:09,800 --> 01:00:11,720
Speaker 1: next couple of weeks, you're seeing this deer on camera

1132
01:00:12,160 --> 01:00:16,040
Speaker 1: and then all of a sudden, poof that deer is gone. Um,

1133
01:00:16,120 --> 01:00:18,400
Speaker 1: he may have actually made one of those excursions. And

1134
01:00:18,440 --> 01:00:21,120
Speaker 1: the ones that this isn't confirmed, the ones that are

1135
01:00:21,160 --> 01:00:25,520
Speaker 1: revelated are assumed obviously uh to be in search of dolls.

1136
01:00:25,600 --> 01:00:28,120
Speaker 1: There might not be enough receptive dose in his home range.

1137
01:00:28,120 --> 01:00:31,480
Speaker 1: She's checked out all his focal areas and he's going elsewhere,

1138
01:00:32,040 --> 01:00:34,880
Speaker 1: or you know, very likely the case she's on a

1139
01:00:34,960 --> 01:00:37,880
Speaker 1: doll that's not quite receptive and she takes them outside

1140
01:00:37,880 --> 01:00:41,000
Speaker 1: of his home range. Um. There's actually been one documented

1141
01:00:41,080 --> 01:00:44,680
Speaker 1: case of a booty calling deer where uh there was

1142
01:00:44,720 --> 01:00:48,600
Speaker 1: a dough that was uh collard and she left her

1143
01:00:48,640 --> 01:00:51,000
Speaker 1: home range and he left his where they were both

1144
01:00:51,120 --> 01:00:53,720
Speaker 1: ninety nine, and they overlapped a little bit and they

1145
01:00:53,760 --> 01:00:57,480
Speaker 1: rendezvous and uh they were together for a day or so,

1146
01:00:57,640 --> 01:00:59,800
Speaker 1: and that was in Tennessee and they went back to

1147
01:00:59,800 --> 01:01:07,880
Speaker 1: the respective home ranges or a college bar. Yeah, so

1148
01:01:08,280 --> 01:01:11,320
Speaker 1: there's all this interesting stuff going out there. Um, and

1149
01:01:11,360 --> 01:01:13,360
Speaker 1: that's probably also you know, when one of those guys

1150
01:01:13,400 --> 01:01:16,800
Speaker 1: that uh you you know, you see a social media

1151
01:01:16,880 --> 01:01:19,280
Speaker 1: post or somebody shoots a buck that looks a lot

1152
01:01:19,360 --> 01:01:21,640
Speaker 1: like the buck you've been following, and it's a couple

1153
01:01:21,640 --> 01:01:23,400
Speaker 1: of miles away. I mean, it could very well be

1154
01:01:23,480 --> 01:01:25,840
Speaker 1: the same, dear, and don't travel anywhere between one to

1155
01:01:25,920 --> 01:01:30,440
Speaker 1: five miles. That's the average distance in these excursions. So

1156
01:01:30,560 --> 01:01:37,400
Speaker 1: the question, I'm sorry in regards to the annual patterning then, um,

1157
01:01:37,560 --> 01:01:39,520
Speaker 1: me and Mark have been talking a lot about annual

1158
01:01:39,560 --> 01:01:42,720
Speaker 1: pattering patterning um the past couple of weeks and trying to,

1159
01:01:42,920 --> 01:01:46,080
Speaker 1: you know, maybe hunt where we got a trail camera

1160
01:01:46,160 --> 01:01:49,040
Speaker 1: picture of a deer of the previous year. Are these

1161
01:01:49,120 --> 01:01:54,560
Speaker 1: excursions or focal points like annual like on the second

1162
01:01:54,560 --> 01:01:56,640
Speaker 1: week of October, you can expect the deer to do

1163
01:01:56,680 --> 01:02:01,160
Speaker 1: the same thing. No, there's not a lot of there's

1164
01:02:01,200 --> 01:02:03,280
Speaker 1: not a lot of research to say that they are

1165
01:02:04,200 --> 01:02:08,000
Speaker 1: continuous in the same place or direction. Um. Some of

1166
01:02:08,040 --> 01:02:12,920
Speaker 1: the research does show, UM some weird stuff where they

1167
01:02:13,000 --> 01:02:15,560
Speaker 1: might have a lot of the collar deer going in

1168
01:02:15,560 --> 01:02:17,400
Speaker 1: the same way, and I think some of that has

1169
01:02:17,440 --> 01:02:21,160
Speaker 1: to do with the terrain in the landscape in those cases. UM.

1170
01:02:21,800 --> 01:02:24,000
Speaker 1: I don't know of anything dan that has said that,

1171
01:02:24,040 --> 01:02:25,800
Speaker 1: you know, you can count that on that deer leaving

1172
01:02:25,800 --> 01:02:28,640
Speaker 1: and then coming back. I wouldn't be surprised if something

1173
01:02:28,680 --> 01:02:31,280
Speaker 1: like that was the case. But again going down to

1174
01:02:31,320 --> 01:02:35,000
Speaker 1: the individuality of a deer, um, you know, you might

1175
01:02:35,040 --> 01:02:37,680
Speaker 1: have some that are are likely to do that and

1176
01:02:37,720 --> 01:02:39,600
Speaker 1: other ones that are way more random. They just pick

1177
01:02:39,680 --> 01:02:42,439
Speaker 1: up and leave because their brain told them to. UM.

1178
01:02:42,480 --> 01:02:44,720
Speaker 1: The reason I wouldn't be surprised if that happened was

1179
01:02:45,240 --> 01:02:48,600
Speaker 1: there's a lot of there's a lot of habitual behavior

1180
01:02:48,640 --> 01:02:50,920
Speaker 1: with deer. That's how they survive. Obviously, they know how

1181
01:02:50,960 --> 01:02:53,919
Speaker 1: to how to do something. UM. And even coming down

1182
01:02:53,920 --> 01:02:56,280
Speaker 1: to like when they dropped their antlers. You know you've

1183
01:02:56,400 --> 01:02:59,320
Speaker 1: seen before and some of the research you know bucks

1184
01:02:59,360 --> 01:03:01,880
Speaker 1: can drop antlers within a day or two of when

1185
01:03:01,880 --> 01:03:04,360
Speaker 1: they did them the last year. So it wouldn't shock

1186
01:03:04,440 --> 01:03:08,440
Speaker 1: me if somebody had had a collar box and they

1187
01:03:08,480 --> 01:03:12,040
Speaker 1: showed that these deer were doing the same thing year

1188
01:03:12,080 --> 01:03:15,040
Speaker 1: and you're you're out around the same time. I just

1189
01:03:15,080 --> 01:03:17,880
Speaker 1: don't remember or recall any of the research showing that,

1190
01:03:17,920 --> 01:03:20,920
Speaker 1: and that's probably because the bucks would have to be

1191
01:03:20,960 --> 01:03:23,800
Speaker 1: collared for multiple years, and a lot of these collars

1192
01:03:23,800 --> 01:03:26,960
Speaker 1: don't have the longevity of that. I mean, they're very expensive,

1193
01:03:27,000 --> 01:03:30,040
Speaker 1: but they usually only last a year. Sometimes they only

1194
01:03:30,120 --> 01:03:33,240
Speaker 1: last a couple of months, believe or not. But um,

1195
01:03:33,360 --> 01:03:36,280
Speaker 1: so that hasn't been documented it to my knowledge. But

1196
01:03:36,520 --> 01:03:39,480
Speaker 1: I'm I'm a huge fan of what you're asking. Yeah,

1197
01:03:39,520 --> 01:03:41,720
Speaker 1: I mean, I'm kind of in a in a little

1198
01:03:41,760 --> 01:03:43,800
Speaker 1: bit different stage. I was talking to a friend the

1199
01:03:43,800 --> 01:03:46,240
Speaker 1: other day about the stages of hunting. You know, you're

1200
01:03:46,280 --> 01:03:48,920
Speaker 1: supposed to go through the shooter stage, and then the

1201
01:03:49,000 --> 01:03:52,320
Speaker 1: limiting out stage, and then the trophy stage, and then

1202
01:03:52,360 --> 01:03:55,360
Speaker 1: it goes on to um I think the fourth one

1203
01:03:55,440 --> 01:03:58,120
Speaker 1: is the type of tactic you use, and then finally

1204
01:03:58,120 --> 01:04:01,520
Speaker 1: a sportsman stage where you're just joining the experience. I'm

1205
01:04:01,560 --> 01:04:03,040
Speaker 1: somewhere in the middle of that, I don't. I think

1206
01:04:03,080 --> 01:04:07,400
Speaker 1: there's something missing for the young father who's got a

1207
01:04:07,400 --> 01:04:10,080
Speaker 1: a toddler and a preschooler and flies around the country

1208
01:04:10,080 --> 01:04:12,240
Speaker 1: a lot, And I don't know what I'm doing this year,

1209
01:04:12,240 --> 01:04:17,280
Speaker 1: but I'm a big fan of of patterning based on

1210
01:04:17,360 --> 01:04:20,960
Speaker 1: everything from finding sheds to trail camera images in the

1211
01:04:21,000 --> 01:04:24,000
Speaker 1: same part of the property year and year out um

1212
01:04:24,080 --> 01:04:27,640
Speaker 1: and learning a deer and actually going deeper than that,

1213
01:04:28,240 --> 01:04:34,480
Speaker 1: finding a buck early in his life that's patternable that

1214
01:04:35,080 --> 01:04:39,240
Speaker 1: has daylight behaviors, that seems to be up and out

1215
01:04:39,320 --> 01:04:42,840
Speaker 1: at daytime, a lot that's got above average halar growth,

1216
01:04:43,240 --> 01:04:45,720
Speaker 1: and trying to protect that buck and see him through

1217
01:04:45,720 --> 01:04:48,800
Speaker 1: an older age that that that's kind of the the

1218
01:04:48,880 --> 01:04:51,120
Speaker 1: niche that I like is just finding a deer that's

1219
01:04:51,440 --> 01:04:54,800
Speaker 1: one or two or even three that's just showing extreme potential,

1220
01:04:55,400 --> 01:04:57,320
Speaker 1: that is up and at him a lot of daytime,

1221
01:04:57,320 --> 01:04:59,640
Speaker 1: and just trying to keep him safe to the point

1222
01:04:59,640 --> 01:05:03,520
Speaker 1: where you might get a shot. That's pretty fascinating when

1223
01:05:03,520 --> 01:05:05,720
Speaker 1: you can learn a single deer like that over the

1224
01:05:05,840 --> 01:05:08,080
Speaker 1: course of several years, and then you know if if

1225
01:05:08,120 --> 01:05:10,160
Speaker 1: you're fortunate enough to put all the pieces together by

1226
01:05:10,200 --> 01:05:12,520
Speaker 1: the time he is fully mature, and then actually, you know,

1227
01:05:12,560 --> 01:05:15,920
Speaker 1: harvest that deer. That that's about as cool as it gets.

1228
01:05:15,960 --> 01:05:19,320
Speaker 1: So here here's kind of related to this point. All

1229
01:05:19,360 --> 01:05:21,520
Speaker 1: the ideas here about when you're trying to pattern a

1230
01:05:21,600 --> 01:05:24,400
Speaker 1: deer and understand the deer. And I have two takeaways

1231
01:05:24,400 --> 01:05:27,000
Speaker 1: from the study that you just mentioned that tracked mature

1232
01:05:27,040 --> 01:05:29,800
Speaker 1: buck movement during the rut, and the two big takeaways

1233
01:05:29,800 --> 01:05:32,640
Speaker 1: obviously mentioned that, yes, deer are taking these excursions, which

1234
01:05:32,680 --> 01:05:35,160
Speaker 1: I think is something that popular common knowledge when it

1235
01:05:35,200 --> 01:05:39,000
Speaker 1: comes to dear behavior during the rut has always been,

1236
01:05:39,040 --> 01:05:42,400
Speaker 1: you know, during the rut, bucks are going everywhere, they're

1237
01:05:42,440 --> 01:05:45,440
Speaker 1: going different places that they're changing the you know, changing

1238
01:05:45,480 --> 01:05:48,000
Speaker 1: the usual routine, and you can't pattern a buck. So

1239
01:05:48,000 --> 01:05:50,000
Speaker 1: so part of this I'm seeing in the data here

1240
01:05:50,000 --> 01:05:52,280
Speaker 1: shows it, Yes, there is some of that excursion behavior.

1241
01:05:52,600 --> 01:05:54,480
Speaker 1: But you know, from what you said and from the

1242
01:05:54,480 --> 01:05:56,280
Speaker 1: stuff I've read, it sounds like that's a little bit

1243
01:05:56,360 --> 01:05:58,520
Speaker 1: less than maybe some have made it out to be.

1244
01:05:58,560 --> 01:06:00,280
Speaker 1: I think a lot of people think it's happened every

1245
01:06:00,280 --> 01:06:02,480
Speaker 1: single day all the time. These bucks are NonStop moving

1246
01:06:02,520 --> 01:06:06,520
Speaker 1: all over to new places, But it sounds like they're

1247
01:06:06,560 --> 01:06:08,840
Speaker 1: actually the majority of time yes, they might take a

1248
01:06:08,840 --> 01:06:10,840
Speaker 1: couple of these excursions, but the majority of the time

1249
01:06:10,880 --> 01:06:13,320
Speaker 1: they're focusing still in their home range on a couple

1250
01:06:13,480 --> 01:06:16,640
Speaker 1: consistent places. So my big takeaway from this, and you

1251
01:06:16,680 --> 01:06:18,760
Speaker 1: tell me, man if this is correct for me to

1252
01:06:18,760 --> 01:06:21,840
Speaker 1: take this, But my big takeaway is that during the rut,

1253
01:06:21,880 --> 01:06:25,280
Speaker 1: while there is going to be some randomness, there actually

1254
01:06:25,400 --> 01:06:28,520
Speaker 1: is still some type of consistency that we can dial

1255
01:06:28,560 --> 01:06:32,080
Speaker 1: in on and potentially pattern to a degree to take

1256
01:06:32,120 --> 01:06:34,960
Speaker 1: advantage of during the rut and while you're hunting. Is

1257
01:06:34,960 --> 01:06:39,320
Speaker 1: that accurate? Absolutely, because you're talking about the law of

1258
01:06:39,360 --> 01:06:43,040
Speaker 1: averages there. And although I'm telling you about every other

1259
01:06:43,120 --> 01:06:46,120
Speaker 1: buck will go on an excursion and when they leave,

1260
01:06:46,960 --> 01:06:50,400
Speaker 1: um they're gone for a short period of time. I

1261
01:06:50,400 --> 01:06:53,400
Speaker 1: mean it's a day or two, you're talking about multiple weeks.

1262
01:06:53,400 --> 01:06:56,600
Speaker 1: That the rut can last two weeks even um in

1263
01:06:56,680 --> 01:07:00,919
Speaker 1: terms of all the craziness of of all that randomness, Um,

1264
01:07:00,960 --> 01:07:04,400
Speaker 1: it is small percentages of when those things are occurring.

1265
01:07:04,480 --> 01:07:09,240
Speaker 1: It helps explain some of the head scratchers. But for

1266
01:07:09,280 --> 01:07:12,840
Speaker 1: the most part, if you can be in tune with

1267
01:07:12,880 --> 01:07:17,439
Speaker 1: your property and you can locate where deer are they

1268
01:07:17,560 --> 01:07:21,880
Speaker 1: like to be during that frenzy um because certainly, and

1269
01:07:21,920 --> 01:07:23,840
Speaker 1: you can build your property that way too. You can

1270
01:07:23,880 --> 01:07:27,040
Speaker 1: manage it so that your property has specific locations where

1271
01:07:27,560 --> 01:07:30,080
Speaker 1: you know dear will hold up um where they like

1272
01:07:30,200 --> 01:07:32,160
Speaker 1: to be. You know, it's got better cover in it,

1273
01:07:32,280 --> 01:07:34,920
Speaker 1: or things like that. That adds a lot of predictability

1274
01:07:34,960 --> 01:07:38,240
Speaker 1: to it. I mean, being within bow range or gun

1275
01:07:38,360 --> 01:07:41,520
Speaker 1: range and actually making a shot count. That comes down

1276
01:07:41,520 --> 01:07:45,800
Speaker 1: to skill and practice and being proficient and being able

1277
01:07:45,840 --> 01:07:50,840
Speaker 1: to perform under pressure. But you can absolutely change the

1278
01:07:50,880 --> 01:07:55,680
Speaker 1: trajectory your success by practicing QDM and and managing the

1279
01:07:55,760 --> 01:07:59,840
Speaker 1: property and letting dear go and watching all those things

1280
01:08:00,200 --> 01:08:03,920
Speaker 1: unfold and practicing a little patients. I mean, there's tens

1281
01:08:03,920 --> 01:08:06,920
Speaker 1: of thousands of qt m A members and other QUTUM

1282
01:08:06,960 --> 01:08:10,960
Speaker 1: practitioners across the country that have extremely high success rates

1283
01:08:11,800 --> 01:08:14,000
Speaker 1: above the average hunter. And all, you know, in all

1284
01:08:14,040 --> 01:08:16,200
Speaker 1: due respects, were all for the millions of hunters out there,

1285
01:08:16,200 --> 01:08:20,080
Speaker 1: But guys that are like you too, and the listeners

1286
01:08:20,080 --> 01:08:22,400
Speaker 1: that are on this, that are listening to this, you

1287
01:08:22,439 --> 01:08:25,519
Speaker 1: can change your fate by that predictability. So I I

1288
01:08:25,560 --> 01:08:28,920
Speaker 1: absolutely agree with that. So then here's the next question, then,

1289
01:08:28,920 --> 01:08:31,920
Speaker 1: Because if we're if we're learning, trying to learn these bucks,

1290
01:08:32,000 --> 01:08:34,800
Speaker 1: and if we know that, hey, there is some ability

1291
01:08:34,960 --> 01:08:37,920
Speaker 1: to still learn and to some degree pattern and hunt

1292
01:08:37,960 --> 01:08:41,960
Speaker 1: these bucks during the rut, even as we understand the

1293
01:08:42,040 --> 01:08:44,720
Speaker 1: doughes do control the rut though, right, because everything a

1294
01:08:44,760 --> 01:08:46,960
Speaker 1: buck is doing during the rut during these next couple

1295
01:08:47,000 --> 01:08:49,200
Speaker 1: of weeks is revolved around trying to find that dough

1296
01:08:49,320 --> 01:08:52,200
Speaker 1: that's ready to breed. So when it comes to hunting

1297
01:08:52,200 --> 01:08:54,760
Speaker 1: the rut, then I think a big portion of, you know,

1298
01:08:54,760 --> 01:08:57,360
Speaker 1: what we're trying to do here is understanding where those

1299
01:08:57,400 --> 01:08:59,360
Speaker 1: doughes are what they're doing, because that's where the buck

1300
01:08:59,400 --> 01:09:02,000
Speaker 1: wants to be. So is there anything out there that

1301
01:09:02,040 --> 01:09:04,840
Speaker 1: you've learned or that you know? I guess what is

1302
01:09:04,880 --> 01:09:07,320
Speaker 1: a dough doing during the rut? Because we talked a

1303
01:09:07,320 --> 01:09:09,280
Speaker 1: lot about what bucks are doing, But I guess the

1304
01:09:09,280 --> 01:09:11,000
Speaker 1: first thing we need understands what are the dose doing?

1305
01:09:11,040 --> 01:09:14,320
Speaker 1: So how does doughe behavior changed during the rut? That's

1306
01:09:14,320 --> 01:09:17,519
Speaker 1: a great question. So a lot of it's similar, but

1307
01:09:17,560 --> 01:09:19,880
Speaker 1: there's some key differences. Obviously, It's just like you know,

1308
01:09:19,960 --> 01:09:23,360
Speaker 1: Mener from Mars and all that. Uh, those do not

1309
01:09:23,520 --> 01:09:28,760
Speaker 1: have obviously influence of the immensity of what bucks do

1310
01:09:28,960 --> 01:09:32,320
Speaker 1: during the rout. There actually is some evidence, um, like

1311
01:09:32,400 --> 01:09:35,200
Speaker 1: that booty call example I gave you a few minutes ago, um,

1312
01:09:35,240 --> 01:09:39,120
Speaker 1: and some other research that actually show uh dose going

1313
01:09:39,160 --> 01:09:41,920
Speaker 1: out and seeking box. I mean that has been documented.

1314
01:09:41,960 --> 01:09:44,519
Speaker 1: It's again it's a proportion and it's a small proportion

1315
01:09:44,560 --> 01:09:46,920
Speaker 1: of the research of that theme. But it's not like

1316
01:09:47,560 --> 01:09:51,160
Speaker 1: acent of time the buck is the purstorer. I mean,

1317
01:09:51,160 --> 01:09:53,840
Speaker 1: there is some of that happening, but for the most part,

1318
01:09:53,880 --> 01:09:56,679
Speaker 1: what those are doing is going through that same diet change,

1319
01:09:56,760 --> 01:09:59,080
Speaker 1: the physiological change. The bucks are that we talked to

1320
01:09:59,520 --> 01:10:02,960
Speaker 1: the beginning of the show. They're getting ready for winter. Um,

1321
01:10:03,240 --> 01:10:05,479
Speaker 1: They're they're they're bulking up. They need to be ready

1322
01:10:05,520 --> 01:10:07,960
Speaker 1: to survive. They need to make sure that their offspring

1323
01:10:08,240 --> 01:10:10,559
Speaker 1: are in the best condition because they're they're good mothers

1324
01:10:10,960 --> 01:10:13,880
Speaker 1: and they're trying to get to that point. Um. They're

1325
01:10:13,920 --> 01:10:17,320
Speaker 1: also at the beginning, like right now, really, I mean

1326
01:10:17,360 --> 01:10:21,320
Speaker 1: there's still the majority of dose are not um quite

1327
01:10:21,320 --> 01:10:25,280
Speaker 1: ready to breed. So that's not going on in there.

1328
01:10:25,320 --> 01:10:28,400
Speaker 1: You know what they're focusing on. They're still trying to

1329
01:10:28,439 --> 01:10:31,960
Speaker 1: bulk up and eat and stay safe and probably the

1330
01:10:32,360 --> 01:10:35,240
Speaker 1: number one thing that you can do in terms of

1331
01:10:35,800 --> 01:10:40,720
Speaker 1: tracking dose is managing your hunting pressure, because they will

1332
01:10:40,800 --> 01:10:43,920
Speaker 1: key in on hunting pressure at a much finer level

1333
01:10:43,920 --> 01:10:48,000
Speaker 1: than bucks will because bucks are rut crazy testosterone filled

1334
01:10:48,040 --> 01:10:50,200
Speaker 1: and they're not paying attention to what they're doing. Every

1335
01:10:50,280 --> 01:10:52,519
Speaker 1: hunter knows that, and that's why guys like to hunt,

1336
01:10:52,640 --> 01:10:54,960
Speaker 1: and guys like to hunt the rut because it's a

1337
01:10:55,000 --> 01:10:58,880
Speaker 1: time when you have the best chance at a buck,

1338
01:10:58,920 --> 01:11:02,479
Speaker 1: because he's gonna make mistake. Um, he'll be out in daylight,

1339
01:11:02,600 --> 01:11:04,400
Speaker 1: he's gonna come by you and not be looking up.

1340
01:11:04,479 --> 01:11:07,040
Speaker 1: All of those things are happening. Those aren't under the

1341
01:11:07,120 --> 01:11:10,080
Speaker 1: same influence of testosterone. I mean, clearly, it's a pretty

1342
01:11:10,080 --> 01:11:12,720
Speaker 1: obvious thing. So the thing you need to really be

1343
01:11:12,760 --> 01:11:18,000
Speaker 1: cautious of is hunting pressure. UM, where you don't uh,

1344
01:11:18,160 --> 01:11:21,720
Speaker 1: too heavily hunt the property to really find balance, but

1345
01:11:21,960 --> 01:11:24,720
Speaker 1: where you don't too heavily hunt the property, where you're

1346
01:11:25,560 --> 01:11:29,200
Speaker 1: alerting dose to hunting pressure, elevating you know, being on

1347
01:11:29,240 --> 01:11:32,280
Speaker 1: the property, all of those things that might make a

1348
01:11:32,360 --> 01:11:35,519
Speaker 1: dough change her behavior. But at the same time be

1349
01:11:35,600 --> 01:11:38,360
Speaker 1: able to manage all the things that we talk about

1350
01:11:38,400 --> 01:11:41,439
Speaker 1: in QDM UM taking the right number of dose and

1351
01:11:41,479 --> 01:11:43,920
Speaker 1: balancing the deer heard in the sex ratio and all

1352
01:11:43,960 --> 01:11:46,680
Speaker 1: those things, And there's some research out there behind it.

1353
01:11:46,720 --> 01:11:48,720
Speaker 1: I mean, for the most part, I may I can

1354
01:11:48,760 --> 01:11:51,120
Speaker 1: give you some real basic numbers, but a lot of

1355
01:11:51,120 --> 01:11:54,479
Speaker 1: the concurrent research out there that and they agree with

1356
01:11:54,520 --> 01:11:58,519
Speaker 1: each other. Things out Oklahoma and UM, South Carolina and

1357
01:11:58,600 --> 01:12:01,519
Speaker 1: some other places show that it really only takes a

1358
01:12:01,520 --> 01:12:04,240
Speaker 1: few days of heavy pressure to to alert a deer

1359
01:12:04,280 --> 01:12:06,320
Speaker 1: heard and they start changing the way they behave And

1360
01:12:06,320 --> 01:12:10,320
Speaker 1: this includes dozen bucks, but they'll they'll change when they're

1361
01:12:10,360 --> 01:12:14,200
Speaker 1: out during day versus night, how they get across the property.

1362
01:12:14,439 --> 01:12:16,920
Speaker 1: They still might do that bead to feed movement, but

1363
01:12:17,080 --> 01:12:19,920
Speaker 1: instead of going in a direct line, their path becomes

1364
01:12:20,040 --> 01:12:25,040
Speaker 1: much more complex. Um, they're the observations of those animals

1365
01:12:25,120 --> 01:12:27,920
Speaker 1: go down. All of this stuff happened after about really

1366
01:12:28,000 --> 01:12:32,840
Speaker 1: three or plus days of pressure. So that's where kind

1367
01:12:32,840 --> 01:12:35,920
Speaker 1: of strategy changes how you do that. So I guess

1368
01:12:36,400 --> 01:12:38,759
Speaker 1: what I would recommend to somebody that wants to focus

1369
01:12:38,800 --> 01:12:43,120
Speaker 1: on that side of it is, UM, first figure out

1370
01:12:43,200 --> 01:12:45,880
Speaker 1: how many does you need to take, because that's the

1371
01:12:45,920 --> 01:12:47,920
Speaker 1: lowest hole in the bucket. If you have too many

1372
01:12:47,960 --> 01:12:51,040
Speaker 1: deer on the property, UM and not enough food or

1373
01:12:51,120 --> 01:12:54,360
Speaker 1: some combination of those two new things depending on Again,

1374
01:12:54,400 --> 01:12:57,880
Speaker 1: if you're Dan and you live in Iowa, Um, you know,

1375
01:12:57,920 --> 01:13:00,280
Speaker 1: if you have abundant food, you can help hold a

1376
01:13:00,280 --> 01:13:02,400
Speaker 1: lot more dear, But if you're if you're limited by

1377
01:13:02,479 --> 01:13:05,360
Speaker 1: food taking, those is the thing you need to worry

1378
01:13:05,400 --> 01:13:08,479
Speaker 1: about beyond tracking a big deer, because that box is

1379
01:13:08,520 --> 01:13:10,120
Speaker 1: only going to be as big as he possibly can

1380
01:13:10,120 --> 01:13:12,320
Speaker 1: be if he's fed as well as he possibly can be.

1381
01:13:12,520 --> 01:13:16,200
Speaker 1: It's all antlers take a big game from nutrition, you know.

1382
01:13:16,280 --> 01:13:20,240
Speaker 1: So I apologize for interrupting her mat but I want

1383
01:13:20,280 --> 01:13:21,880
Speaker 1: to make sure I asked you this question because this

1384
01:13:21,920 --> 01:13:24,680
Speaker 1: is something that's been hypothesizing about related to something you

1385
01:13:24,760 --> 01:13:27,200
Speaker 1: just said there, um, And I'm really curious about your

1386
01:13:27,200 --> 01:13:30,639
Speaker 1: opinion on this. But before we get to that question

1387
01:13:30,640 --> 01:13:33,120
Speaker 1: of mine, we need to pause briefly for a word

1388
01:13:33,120 --> 01:13:36,800
Speaker 1: from our sponsors of this podcast episode, Ozonics. And you've

1389
01:13:36,800 --> 01:13:38,840
Speaker 1: heard me and Dan talk a lot about this product

1390
01:13:38,920 --> 01:13:41,160
Speaker 1: over the past couple of years, and that's because we've

1391
01:13:41,200 --> 01:13:44,599
Speaker 1: found it to really help us way before Ozonics ever

1392
01:13:44,640 --> 01:13:47,200
Speaker 1: started working with us officially. We try it out and

1393
01:13:47,240 --> 01:13:49,479
Speaker 1: found it to make a big difference. And we're not

1394
01:13:49,520 --> 01:13:51,960
Speaker 1: the only ones. So today we're going to be hearing

1395
01:13:52,000 --> 01:13:55,719
Speaker 1: from Dean Partridge post of Canadian White Tailed Television about

1396
01:13:55,720 --> 01:14:00,439
Speaker 1: how Zonis has changed how he hunts. Here's Dean for sure,

1397
01:14:00,640 --> 01:14:04,960
Speaker 1: and that's sometimes, I think an aspect of the affectionments

1398
01:14:04,960 --> 01:14:07,960
Speaker 1: of vonics that sometimes overlooked. And I think there's two

1399
01:14:07,960 --> 01:14:09,760
Speaker 1: sides of that, and one is within a single deer

1400
01:14:09,800 --> 01:14:12,600
Speaker 1: season prout. We spend most of our time on a

1401
01:14:12,640 --> 01:14:15,040
Speaker 1: specific buck. And when you're hunting one buck, that can

1402
01:14:15,040 --> 01:14:16,840
Speaker 1: happen on day one or it can happen on day forty.

1403
01:14:18,560 --> 01:14:21,839
Speaker 1: And every day that you hunt, do you add pressure

1404
01:14:21,880 --> 01:14:23,800
Speaker 1: to that area, whether whether you whether you like it

1405
01:14:23,880 --> 01:14:25,320
Speaker 1: or not, whether you realize you do it or not.

1406
01:14:26,680 --> 01:14:28,680
Speaker 1: And a lot of times that stand will start to

1407
01:14:28,680 --> 01:14:30,400
Speaker 1: go cold as you go on. So if you're hunting

1408
01:14:30,400 --> 01:14:32,599
Speaker 1: that buck on the edge of a field and you're

1409
01:14:32,600 --> 01:14:34,640
Speaker 1: sitting that stand, every time your win is right that

1410
01:14:34,760 --> 01:14:36,920
Speaker 1: there's no way to win a d percent of the time,

1411
01:14:36,960 --> 01:14:39,400
Speaker 1: there's always a dough, a young buck, another deer that

1412
01:14:39,439 --> 01:14:41,639
Speaker 1: goes down when a hundred yards a hundred and fifty

1413
01:14:41,720 --> 01:14:44,960
Speaker 1: yards away that you never see, and they'll know, and

1414
01:14:44,960 --> 01:14:47,120
Speaker 1: you'll notice if the season goes on, your deer encounters

1415
01:14:47,160 --> 01:14:49,920
Speaker 1: will go down they'll get later. While you're hoping for

1416
01:14:49,960 --> 01:14:52,960
Speaker 1: an opportunity at that target buck, what happens is that

1417
01:14:53,000 --> 01:14:56,320
Speaker 1: target buck that you're after, he's a lot better at

1418
01:14:56,360 --> 01:14:58,960
Speaker 1: understanding his environment than we are. Otherwise it would be

1419
01:14:59,000 --> 01:15:01,639
Speaker 1: so hard to hunt. So even if that target buck

1420
01:15:01,680 --> 01:15:04,160
Speaker 1: hasn't caught you or hasn't become aware of your presence,

1421
01:15:04,200 --> 01:15:06,720
Speaker 1: if other deer in that area have, he's going to

1422
01:15:06,800 --> 01:15:09,240
Speaker 1: realize that. So that one time that you're that you're there,

1423
01:15:09,240 --> 01:15:10,840
Speaker 1: that he is going to step out in that field,

1424
01:15:11,439 --> 01:15:13,680
Speaker 1: he's going to realize that the deer acting differently and

1425
01:15:13,680 --> 01:15:16,680
Speaker 1: everything is different. And what we've found is when we

1426
01:15:16,760 --> 01:15:22,280
Speaker 1: use thosonics of every single sit that that downward trend

1427
01:15:22,320 --> 01:15:24,439
Speaker 1: of a stands starting to go cold or starting to

1428
01:15:24,479 --> 01:15:28,320
Speaker 1: wear that spot out, it eliminates it because any non

1429
01:15:28,360 --> 01:15:31,200
Speaker 1: target deer that are down, when any issues you have

1430
01:15:31,280 --> 01:15:35,400
Speaker 1: with that, they're removed. So when we go from you know,

1431
01:15:35,479 --> 01:15:38,559
Speaker 1: having deer in a plot on day one, we used

1432
01:15:38,560 --> 01:15:40,840
Speaker 1: to have by day twelve or day fifteen, we'd have

1433
01:15:41,600 --> 01:15:43,400
Speaker 1: you know, twelve deer because some of them had caught

1434
01:15:43,439 --> 01:15:46,080
Speaker 1: you and called you know, sort of a residual damage.

1435
01:15:47,160 --> 01:15:49,519
Speaker 1: We eliminate that. Now where we're able to hunt those

1436
01:15:49,520 --> 01:15:53,479
Speaker 1: stands longer throughout the season and have a more normalized

1437
01:15:53,520 --> 01:15:55,960
Speaker 1: effect in that area where the deer aren't quite so

1438
01:15:56,160 --> 01:16:00,120
Speaker 1: sensitive to the other deer that have caught you. They

1439
01:16:00,120 --> 01:16:02,759
Speaker 1: are coming later now that are more where to your presence.

1440
01:16:03,800 --> 01:16:06,080
Speaker 1: So there you go, And if you are interested in

1441
01:16:06,160 --> 01:16:10,040
Speaker 1: learning more about osonics yourself, you can visit osonics hunting

1442
01:16:10,360 --> 01:16:13,679
Speaker 1: dot com. And now let's get back to that interesting

1443
01:16:13,760 --> 01:16:19,120
Speaker 1: question I had for Matt so. On my main Michigan property,

1444
01:16:19,439 --> 01:16:22,040
Speaker 1: I used to see a lot of mature bucks. Um

1445
01:16:22,120 --> 01:16:25,679
Speaker 1: but the dope population in and around this property has

1446
01:16:25,760 --> 01:16:27,880
Speaker 1: just gotten out of control, and I've tried to do

1447
01:16:27,920 --> 01:16:29,760
Speaker 1: a better job of managing what I can on my

1448
01:16:29,920 --> 01:16:32,240
Speaker 1: end um but I don't think my neighbors are killing

1449
01:16:32,280 --> 01:16:38,320
Speaker 1: does and I haven't killed enough um so. So my

1450
01:16:38,400 --> 01:16:42,640
Speaker 1: issue here is that I've got an astronomically high dope population,

1451
01:16:43,520 --> 01:16:45,920
Speaker 1: and over the most more recent years, the number of

1452
01:16:45,960 --> 01:16:48,400
Speaker 1: mature bucks I've been seeing have been less and less

1453
01:16:48,400 --> 01:16:50,960
Speaker 1: and less, despite the fact that I'm passing on lots

1454
01:16:50,960 --> 01:16:53,240
Speaker 1: and lots of young bucks, and from what I understand,

1455
01:16:53,280 --> 01:16:55,080
Speaker 1: most of my neighbors are too. The guys I've been

1456
01:16:55,080 --> 01:16:57,519
Speaker 1: able to talk to you. So my hypothesis has been

1457
01:16:58,320 --> 01:17:01,000
Speaker 1: I don't know if food is necessarily the limiting factor,

1458
01:17:00,960 --> 01:17:04,360
Speaker 1: because I've got lots of food, But could there be

1459
01:17:04,479 --> 01:17:07,400
Speaker 1: the potential simply of the fact that there's so many

1460
01:17:07,479 --> 01:17:11,400
Speaker 1: does that's overcrowding the mature bucks. Because I've heard from

1461
01:17:11,400 --> 01:17:13,840
Speaker 1: a lot of people that mature bucks tend to when

1462
01:17:13,880 --> 01:17:16,080
Speaker 1: they're trying to find a betting area in their core

1463
01:17:16,240 --> 01:17:18,200
Speaker 1: range and stuff, they prefer a little bit of isolation.

1464
01:17:18,240 --> 01:17:20,960
Speaker 1: They prefer to have a little space. And if there's

1465
01:17:21,080 --> 01:17:23,400
Speaker 1: so many Doe family groups spread out in every single

1466
01:17:23,400 --> 01:17:25,400
Speaker 1: different pocket of cover in a you know, two or

1467
01:17:25,400 --> 01:17:29,040
Speaker 1: three area, could that potentially be reducing how many mature

1468
01:17:29,040 --> 01:17:33,000
Speaker 1: bucks are are spending time on my property. That's a

1469
01:17:33,000 --> 01:17:37,000
Speaker 1: good question. Now, dere are territorial in the sense of

1470
01:17:37,120 --> 01:17:42,439
Speaker 1: you know what territorial the word means. But um, and

1471
01:17:42,520 --> 01:17:45,599
Speaker 1: certainly the are segregated. You know, I mentioned it earlier.

1472
01:17:45,600 --> 01:17:49,519
Speaker 1: They're not like elk Um throughout most of the year. Um,

1473
01:17:49,600 --> 01:17:53,240
Speaker 1: your bachelor groups and your Dope family groups are gonna

1474
01:17:53,240 --> 01:17:55,200
Speaker 1: be separate from each other. They're gonna be different using

1475
01:17:55,200 --> 01:17:58,519
Speaker 1: different space. Um. It's particularly when it comes to fawning

1476
01:17:58,560 --> 01:18:01,439
Speaker 1: season that's probably the one time that year that territoriality

1477
01:18:01,520 --> 01:18:04,720
Speaker 1: might be the closest to the truth and dear. But

1478
01:18:04,760 --> 01:18:06,680
Speaker 1: when it comes down to the run, you know, in

1479
01:18:06,720 --> 01:18:09,599
Speaker 1: the fall, things are a lot more random and uses

1480
01:18:09,840 --> 01:18:13,639
Speaker 1: is scattered. But it can lay the groundwork for where

1481
01:18:13,800 --> 01:18:15,720
Speaker 1: deer set up their home ranges, you know, at the

1482
01:18:15,840 --> 01:18:19,120
Speaker 1: very beginning. So if you have a property that has

1483
01:18:19,160 --> 01:18:23,040
Speaker 1: above high you know, above what the lamp can support,

1484
01:18:23,280 --> 01:18:27,920
Speaker 1: the carring capacity is painted, and you don't you have

1485
01:18:27,960 --> 01:18:31,000
Speaker 1: too many deer and you have a lot of dose, um,

1486
01:18:31,120 --> 01:18:34,800
Speaker 1: it could potentially impact what box are there during the

1487
01:18:34,840 --> 01:18:37,400
Speaker 1: majority of the year. Now, on the flip side, you

1488
01:18:37,479 --> 01:18:39,240
Speaker 1: might be able to pull in a random buck or

1489
01:18:39,280 --> 01:18:41,720
Speaker 1: two later in the year through an excursion because you

1490
01:18:41,760 --> 01:18:44,400
Speaker 1: have so many does. But then again you're you're playing

1491
01:18:44,400 --> 01:18:46,960
Speaker 1: with the law of averages there again, right, So you're

1492
01:18:47,000 --> 01:18:50,360
Speaker 1: you're hoping that a buck that you're not seeing throughout

1493
01:18:50,760 --> 01:18:54,360
Speaker 1: three hundred sixty days a year shows up for a

1494
01:18:54,520 --> 01:18:58,160
Speaker 1: random event as opposed to the bucks that are calling

1495
01:18:58,200 --> 01:19:01,479
Speaker 1: the place home. We're king with them and managing around

1496
01:19:01,479 --> 01:19:05,599
Speaker 1: them because and and giving them that space. Um, So

1497
01:19:05,640 --> 01:19:08,720
Speaker 1: that certainly can be an impact. Yes, I mean if

1498
01:19:08,720 --> 01:19:11,320
Speaker 1: that helps to answer that question. So one of the

1499
01:19:11,360 --> 01:19:13,960
Speaker 1: things that I always recommend is the first thing you

1500
01:19:14,000 --> 01:19:15,599
Speaker 1: need to look at is you know where's your dear

1501
01:19:15,680 --> 01:19:19,000
Speaker 1: heart at. Here's an example. So the property I hunt on,

1502
01:19:19,560 --> 01:19:23,640
Speaker 1: I hunted on a QUM cooperative. It's a several farms

1503
01:19:23,720 --> 01:19:28,480
Speaker 1: that are next to each other. UM they're all contiguous,

1504
01:19:28,520 --> 01:19:30,400
Speaker 1: so there's no open space between it. But it's not

1505
01:19:30,439 --> 01:19:33,840
Speaker 1: a giant, giant chunk land, but it's it's good. UM.

1506
01:19:33,960 --> 01:19:36,760
Speaker 1: We really focused on reducing deer density. This is our

1507
01:19:36,800 --> 01:19:40,080
Speaker 1: sixth season going in UM and it took us about

1508
01:19:40,760 --> 01:19:45,639
Speaker 1: three or four seasons to get there, and the dear

1509
01:19:45,760 --> 01:19:47,960
Speaker 1: visibility has gone down. I mean, I'll tell you it

1510
01:19:48,040 --> 01:19:51,679
Speaker 1: was kind of tracking it through through hunter observations. UM,

1511
01:19:51,880 --> 01:19:55,559
Speaker 1: we're seeing whereas the beginning about two deer an hour,

1512
01:19:56,160 --> 01:19:58,639
Speaker 1: under a deer an hour now it's I think point

1513
01:19:58,720 --> 01:20:02,040
Speaker 1: eight last season. So as a hunter, it feels very different.

1514
01:20:02,040 --> 01:20:03,599
Speaker 1: I go out there, I don't see as many deer

1515
01:20:03,600 --> 01:20:05,320
Speaker 1: as I used to. But that's the point. I mean

1516
01:20:05,320 --> 01:20:08,080
Speaker 1: that we needed to reduce it. UM. The number of

1517
01:20:08,120 --> 01:20:11,680
Speaker 1: bucks I'm seeing out of that that, you know, the observations,

1518
01:20:11,960 --> 01:20:14,280
Speaker 1: it's higher than it used to be. We're seeing a

1519
01:20:14,280 --> 01:20:17,320
Speaker 1: lot more does and we're bucks. Um, are there more

1520
01:20:17,360 --> 01:20:21,000
Speaker 1: older bucks? UM? Last year I would absolutely said, yeah,

1521
01:20:21,040 --> 01:20:23,519
Speaker 1: this is a strange year, and there's some good bucks

1522
01:20:23,560 --> 01:20:25,360
Speaker 1: on there, but nothing like there was last year. And

1523
01:20:25,400 --> 01:20:28,000
Speaker 1: I'm not sure why the case, but that's going to

1524
01:20:28,080 --> 01:20:31,640
Speaker 1: come and go. So my I feel very confident in

1525
01:20:31,640 --> 01:20:34,680
Speaker 1: the decision of managing the dose to begin with. UM,

1526
01:20:34,920 --> 01:20:39,040
Speaker 1: and the images we get on trail cameras, and certainly

1527
01:20:39,080 --> 01:20:41,160
Speaker 1: the bucks we're seeing and killing the last two or

1528
01:20:41,200 --> 01:20:43,840
Speaker 1: three years is way way better than the first two

1529
01:20:43,920 --> 01:20:46,200
Speaker 1: or three years. UM. And you're not going to have

1530
01:20:46,280 --> 01:20:47,760
Speaker 1: that every year, So you might be in a in

1531
01:20:47,840 --> 01:20:51,160
Speaker 1: a point mark where that could be impacting you. You

1532
01:20:51,200 --> 01:20:55,400
Speaker 1: could just have a year um where you know, a

1533
01:20:55,840 --> 01:21:00,240
Speaker 1: bigger buck or two uh, disappeared from the landscape. Um.

1534
01:21:00,320 --> 01:21:02,360
Speaker 1: You know, and the deer that are they're just not

1535
01:21:02,439 --> 01:21:06,360
Speaker 1: on the age yet. UM. You know, bucks aren't necessarily bullies.

1536
01:21:06,360 --> 01:21:08,640
Speaker 1: They're not going to push buck other bucks out and

1537
01:21:08,680 --> 01:21:11,760
Speaker 1: make another older big buck not show up. That's not

1538
01:21:11,800 --> 01:21:15,759
Speaker 1: necessarily true. UM. But you've got to kind of handle

1539
01:21:15,800 --> 01:21:18,080
Speaker 1: what's there. So the bucks that are living on the property,

1540
01:21:18,400 --> 01:21:21,639
Speaker 1: identify their age, figure out which one's got the potential

1541
01:21:21,680 --> 01:21:24,840
Speaker 1: to be big, I guess, and UH see him through.

1542
01:21:25,680 --> 01:21:28,360
Speaker 1: So this brings me to kind of a related question

1543
01:21:28,439 --> 01:21:31,400
Speaker 1: that ties into this UM. You know, we've talked about

1544
01:21:31,439 --> 01:21:35,320
Speaker 1: some of these impacts that might occur if I were

1545
01:21:35,360 --> 01:21:38,000
Speaker 1: to know better manage some aspects of this property, which

1546
01:21:38,040 --> 01:21:40,120
Speaker 1: is my goal. And there's there's one thing on my

1547
01:21:40,160 --> 01:21:41,960
Speaker 1: mind that I that I think is an impact. But

1548
01:21:42,000 --> 01:21:43,880
Speaker 1: I want to hear from you first man, when you

1549
01:21:43,920 --> 01:21:47,599
Speaker 1: actually start implementing quality deer management practices, so you know,

1550
01:21:48,080 --> 01:21:50,680
Speaker 1: managing and harvesting deer to have the appropriate level of

1551
01:21:50,720 --> 01:21:53,880
Speaker 1: does the appropriate level of bucks, appropriate age structure, all

1552
01:21:53,880 --> 01:21:57,280
Speaker 1: these things. Not not the management that some people talk

1553
01:21:57,320 --> 01:21:59,519
Speaker 1: about on TV just trying to shoot giant racked bucks,

1554
01:21:59,560 --> 01:22:03,040
Speaker 1: but I mean real quality dear management, trying to you know,

1555
01:22:03,320 --> 01:22:06,080
Speaker 1: be smart about your harvest to achieve that proper balance

1556
01:22:06,080 --> 01:22:08,080
Speaker 1: and your heard when you have a heard like that,

1557
01:22:09,160 --> 01:22:12,080
Speaker 1: How is the rut different in a managed herd like that?

1558
01:22:12,200 --> 01:22:16,479
Speaker 1: And how so it is different once the and this

1559
01:22:16,560 --> 01:22:19,880
Speaker 1: is one of the things we tell any introductor remembered.

1560
01:22:20,040 --> 01:22:22,200
Speaker 1: One of the things that we explain about q DM

1561
01:22:22,800 --> 01:22:27,080
Speaker 1: is once you balance that ratio of bucks to dose,

1562
01:22:27,760 --> 01:22:30,920
Speaker 1: UM a lot of the signpost. Behavior that you see

1563
01:22:31,080 --> 01:22:34,519
Speaker 1: on a property will increase by a lot, meaning rubs

1564
01:22:34,520 --> 01:22:36,320
Speaker 1: and scrapes and that type of stuff and stuff you

1565
01:22:36,320 --> 01:22:38,000
Speaker 1: get excited to see when you go in the woods,

1566
01:22:38,880 --> 01:22:41,880
Speaker 1: because if you think about it, they're competing for a

1567
01:22:41,920 --> 01:22:45,320
Speaker 1: limited resource when you're when you're balancing your doughs, if

1568
01:22:45,320 --> 01:22:48,360
Speaker 1: you have too many doughs, that's a again talking like

1569
01:22:48,439 --> 01:22:52,400
Speaker 1: we spoke earlier in the show, Um, they're in abundance, right,

1570
01:22:52,400 --> 01:22:55,000
Speaker 1: so bucks don't need need to necessarily compete for it.

1571
01:22:55,320 --> 01:22:59,200
Speaker 1: And through competition like leaving sign rubbed and scrapes or

1572
01:22:59,200 --> 01:23:04,080
Speaker 1: even fighting um or in those that respect, responding to

1573
01:23:04,160 --> 01:23:09,160
Speaker 1: aggressive tactics like using decoys and rattling and grunting and

1574
01:23:09,200 --> 01:23:11,880
Speaker 1: getting you know, really aggressive with how you're trying to

1575
01:23:11,880 --> 01:23:14,839
Speaker 1: get deer in front of you. All of that changes

1576
01:23:15,000 --> 01:23:18,960
Speaker 1: when you balance what's out there because instead of having

1577
01:23:19,000 --> 01:23:23,559
Speaker 1: a surplus of female deer on the property, um, there's

1578
01:23:23,680 --> 01:23:27,160
Speaker 1: more balance to it, meaning the bucks have to compete

1579
01:23:27,160 --> 01:23:30,800
Speaker 1: for it and you're hunting success and really the fun

1580
01:23:30,880 --> 01:23:34,600
Speaker 1: and hunting improves. So that does change on a property,

1581
01:23:34,720 --> 01:23:37,240
Speaker 1: especially at a landscape level, if you're working with neighbors

1582
01:23:37,240 --> 01:23:40,479
Speaker 1: and everybody's contributing. So in your situation, Mark, if you

1583
01:23:40,479 --> 01:23:44,280
Speaker 1: have neighbors that are at least in uh contact with you,

1584
01:23:44,320 --> 01:23:47,720
Speaker 1: even if it's not a formal co op um, if

1585
01:23:47,760 --> 01:23:51,880
Speaker 1: you guys are uh talking and talking about letting deer

1586
01:23:51,920 --> 01:23:54,519
Speaker 1: go and um taking the right number, dear, you will

1587
01:23:54,520 --> 01:23:59,760
Speaker 1: definitely improve your hunting by by making some of those decisions.

1588
01:24:00,160 --> 01:24:04,599
Speaker 1: Now there's textbook and then there's the reality of working

1589
01:24:04,640 --> 01:24:08,760
Speaker 1: with people and it can be hard. And that's where

1590
01:24:08,760 --> 01:24:13,400
Speaker 1: you talk about expectations of not letting yourself down. If

1591
01:24:13,760 --> 01:24:16,920
Speaker 1: you expect to change things and to turn into a

1592
01:24:16,960 --> 01:24:20,000
Speaker 1: TV show, I mean that that can happen. I mean,

1593
01:24:21,520 --> 01:24:24,080
Speaker 1: just as an example, hunter on the property that I

1594
01:24:24,160 --> 01:24:27,080
Speaker 1: hunt on killed the fifth biggest buck in our county

1595
01:24:27,160 --> 01:24:30,240
Speaker 1: last year on the co op. That happened because of

1596
01:24:30,280 --> 01:24:33,720
Speaker 1: the co op um. You know, there's no doubt in

1597
01:24:33,880 --> 01:24:37,160
Speaker 1: my mind that's what happened. But for the most part,

1598
01:24:37,360 --> 01:24:39,280
Speaker 1: that's not every book out there. I mean, we have

1599
01:24:39,439 --> 01:24:42,800
Speaker 1: very average antler scores and ages. I mean, we have

1600
01:24:42,880 --> 01:24:45,240
Speaker 1: deer that are three and four years old, that are

1601
01:24:45,360 --> 01:24:47,679
Speaker 1: you know, one twenties, one thirties. It's not like every

1602
01:24:47,680 --> 01:24:50,040
Speaker 1: bucks a giant. So that's where you kind of set

1603
01:24:50,040 --> 01:24:53,240
Speaker 1: your expectations and even set your goals if you're happy

1604
01:24:53,520 --> 01:24:56,680
Speaker 1: going for maturity, which makes me very happy, you know,

1605
01:24:56,760 --> 01:24:59,400
Speaker 1: looking for a deer that's mature depending on what's on

1606
01:24:59,439 --> 01:25:01,960
Speaker 1: his head. That changes all the same thing with with

1607
01:25:02,040 --> 01:25:05,559
Speaker 1: does so um Practicing QTM will make you a better hunter,

1608
01:25:05,640 --> 01:25:07,720
Speaker 1: It makes you hunting more fun, and it makes you

1609
01:25:08,080 --> 01:25:12,400
Speaker 1: more intense. All of that is absolutely true. Something you

1610
01:25:12,439 --> 01:25:15,840
Speaker 1: talked about there, um is another thing I'm curious about

1611
01:25:15,840 --> 01:25:17,880
Speaker 1: hearing from you. And you mentioned the fact that sign

1612
01:25:17,920 --> 01:25:21,519
Speaker 1: posting might increase UM in a property that's properly managed,

1613
01:25:22,240 --> 01:25:24,040
Speaker 1: kind of outside of just the cutium and piece, but

1614
01:25:24,080 --> 01:25:27,280
Speaker 1: just in general, can you dive into the science of

1615
01:25:27,320 --> 01:25:30,160
Speaker 1: sign posting? So rubs and scrapes are something that you know,

1616
01:25:30,200 --> 01:25:33,559
Speaker 1: we hunters associate with the rut, but can you go

1617
01:25:33,600 --> 01:25:35,920
Speaker 1: into both of those and you know why our bucks

1618
01:25:35,960 --> 01:25:38,559
Speaker 1: making those? What are they doing with them? And when

1619
01:25:38,560 --> 01:25:40,400
Speaker 1: are they doing them? I guess is what I'm first

1620
01:25:40,439 --> 01:25:45,040
Speaker 1: curious about from you. Okay, yeah, there's actually very predictable

1621
01:25:45,120 --> 01:25:49,040
Speaker 1: times when both of those behaviors peak in the woods.

1622
01:25:49,600 --> 01:25:53,760
Speaker 1: Um scraping, let's talk about that. One first bucks will

1623
01:25:53,800 --> 01:25:57,479
Speaker 1: start making scrapes. Really after velvet peel, they'll start doing

1624
01:25:57,520 --> 01:26:00,960
Speaker 1: a little bit, but by far it ramps up going

1625
01:26:01,080 --> 01:26:04,800
Speaker 1: through UM early fall. You know, it's just called the

1626
01:26:05,160 --> 01:26:09,160
Speaker 1: the second week in November. UM, you'll see scraping activity

1627
01:26:09,240 --> 01:26:13,080
Speaker 1: peak about a week and a half to fourteen days

1628
01:26:13,960 --> 01:26:16,120
Speaker 1: prior to that. That's when it peaks, and it will

1629
01:26:16,240 --> 01:26:21,040
Speaker 1: maintain that peak up until when breeding starts occurring. So

1630
01:26:21,560 --> 01:26:26,360
Speaker 1: right now late October UM is the time when you

1631
01:26:26,439 --> 01:26:29,960
Speaker 1: see scrap more scrapes than any other time of the year. UM.

1632
01:26:30,000 --> 01:26:32,160
Speaker 1: It will continue for a couple of weeks and actually

1633
01:26:32,240 --> 01:26:35,880
Speaker 1: in the probably second week in November, when most breeding

1634
01:26:35,960 --> 01:26:38,120
Speaker 1: is occurring, it starts to drop off. There's usually a

1635
01:26:38,160 --> 01:26:40,439
Speaker 1: little bit of peak after that when you see a

1636
01:26:40,680 --> 01:26:44,160
Speaker 1: second rod occurring or things like that, but there should

1637
01:26:44,200 --> 01:26:47,599
Speaker 1: be the most scrapes on your properties right now. UM.

1638
01:26:48,120 --> 01:26:52,240
Speaker 1: Rubbing actually increases and peaks with the peak of breeding,

1639
01:26:52,720 --> 01:26:56,519
Speaker 1: so that usually will peak a little bit later in

1640
01:26:56,520 --> 01:27:00,160
Speaker 1: the fall. About when bucks are indoors are actually starting

1641
01:27:00,200 --> 01:27:04,400
Speaker 1: to breed? And why what's the science say about why

1642
01:27:04,400 --> 01:27:08,559
Speaker 1: they're doing those two things? All the science behind it

1643
01:27:08,640 --> 01:27:11,639
Speaker 1: is what they're doing is they're leaving sign for other

1644
01:27:11,680 --> 01:27:16,840
Speaker 1: deer I mean, deer are very social animals. Um. They

1645
01:27:17,000 --> 01:27:19,960
Speaker 1: beat to each others through vocalizations. That's why we buy

1646
01:27:20,040 --> 01:27:23,880
Speaker 1: grunt calls and dobeleats and cans and all those things,

1647
01:27:23,920 --> 01:27:27,040
Speaker 1: because we know that, you know, deer are very vocal

1648
01:27:27,080 --> 01:27:31,200
Speaker 1: with each other. UM. They have a lot of scent production.

1649
01:27:32,040 --> 01:27:35,519
Speaker 1: They will leave sent through seven different glands on their

1650
01:27:35,560 --> 01:27:40,479
Speaker 1: body with box at seven does six. Um, they leave

1651
01:27:40,600 --> 01:27:45,200
Speaker 1: scent on scrapes. They leave by urinating and or end

1652
01:27:45,320 --> 01:27:48,240
Speaker 1: or rub urinating in that spot. They will leave sent

1653
01:27:48,320 --> 01:27:51,840
Speaker 1: on a rub by once they make the rub their

1654
01:27:51,880 --> 01:27:56,040
Speaker 1: forehead bland that's that dark spot between the antlers. All

1655
01:27:56,040 --> 01:27:58,960
Speaker 1: that hair gets really dark because there's a very oily

1656
01:27:59,680 --> 01:28:02,840
Speaker 1: uh substance basically like um. You know, if you don't

1657
01:28:02,840 --> 01:28:05,679
Speaker 1: shower for a couple of days, your hair gets really greasy.

1658
01:28:06,080 --> 01:28:09,040
Speaker 1: Every single hair follicle on our body has a spacious

1659
01:28:09,040 --> 01:28:12,840
Speaker 1: plant produces a little bit of oil to it. Uh.

1660
01:28:13,040 --> 01:28:15,639
Speaker 1: Dear mammals, they have the same thing. But these areas

1661
01:28:15,680 --> 01:28:19,800
Speaker 1: of high glandular activity, like the forehead um or the

1662
01:28:19,880 --> 01:28:23,280
Speaker 1: tarsal bland um. You know, these areas will actually produce

1663
01:28:23,520 --> 01:28:27,240
Speaker 1: an abundance of those oils, and they're depositing scent through that.

1664
01:28:27,400 --> 01:28:30,800
Speaker 1: So what they're doing is they're basically leaving their calling card.

1665
01:28:30,960 --> 01:28:35,200
Speaker 1: So any deer, fawn, dell buck can go to those places,

1666
01:28:35,240 --> 01:28:41,280
Speaker 1: those signpost locations and smell it and pick up the

1667
01:28:41,280 --> 01:28:44,760
Speaker 1: pheromones of other individuals. And it's basically like going to

1668
01:28:44,840 --> 01:28:47,320
Speaker 1: the deli and leaving your business card to you know,

1669
01:28:47,400 --> 01:28:49,880
Speaker 1: win a free sandwich or a free HOGI they're leaving

1670
01:28:49,920 --> 01:28:53,280
Speaker 1: their their business card. They're saying I was here. UM. Again,

1671
01:28:53,320 --> 01:28:57,160
Speaker 1: it kind of blends into that territoriality of deer territorial

1672
01:28:57,200 --> 01:29:00,760
Speaker 1: they're not, They're just they're just leaving their sign out there.

1673
01:29:00,800 --> 01:29:04,200
Speaker 1: And it also alerts and also queues a little bit

1674
01:29:04,240 --> 01:29:07,160
Speaker 1: to the rut, you know, when those are priming and

1675
01:29:07,200 --> 01:29:10,639
Speaker 1: getting ready to come into astress. There's some suggestions out

1676
01:29:10,640 --> 01:29:17,320
Speaker 1: there UM through well known researchers. I haven't seen research

1677
01:29:17,400 --> 01:29:20,920
Speaker 1: that says it it's unfounded, but there's a lot of

1678
01:29:20,920 --> 01:29:23,240
Speaker 1: good research out there that talks about the number of

1679
01:29:23,680 --> 01:29:28,040
Speaker 1: chemical receptors and pheromones in box um and immature box

1680
01:29:28,400 --> 01:29:32,679
Speaker 1: versus mature bucks that that that's irresputable that UM mature

1681
01:29:32,720 --> 01:29:35,719
Speaker 1: bucks do leave different sense, different types of sense, different

1682
01:29:35,760 --> 01:29:38,519
Speaker 1: types of compounds and young bucks, do you know. So

1683
01:29:38,600 --> 01:29:41,200
Speaker 1: the theory there, and that's the theory, is that they're

1684
01:29:41,280 --> 01:29:44,240
Speaker 1: leaving their sign or their scent for others to smell

1685
01:29:44,760 --> 01:29:49,400
Speaker 1: as a marking of we're here or I'm ready and uh.

1686
01:29:49,479 --> 01:29:53,280
Speaker 1: There's also some suggested evidence that those can be que

1687
01:29:53,479 --> 01:29:57,760
Speaker 1: quicker into breeding or being ready to breed with some

1688
01:29:57,920 --> 01:30:00,360
Speaker 1: of that out there with more mature box and those

1689
01:30:00,439 --> 01:30:03,840
Speaker 1: those right compounds. So um, it's very interconnected. There's a

1690
01:30:03,880 --> 01:30:07,000
Speaker 1: lot we don't know about deer um, but there's a

1691
01:30:07,040 --> 01:30:10,639
Speaker 1: lot of very interesting things going on, and they certainly

1692
01:30:10,640 --> 01:30:14,599
Speaker 1: are are tied together to each other through communication like that.

1693
01:30:15,479 --> 01:30:22,120
Speaker 1: So is there any takeaway for hunters in regards to signposts,

1694
01:30:22,160 --> 01:30:24,559
Speaker 1: because there's lots of different ideas and theories and it's

1695
01:30:24,640 --> 01:30:27,599
Speaker 1: it's changed over the years about hunting over or near

1696
01:30:27,680 --> 01:30:31,000
Speaker 1: rubs or scrapes, But is there any definitive takeaway that

1697
01:30:31,080 --> 01:30:33,880
Speaker 1: we that we have now regards to if it's worth

1698
01:30:33,960 --> 01:30:37,759
Speaker 1: hunting over those two different types of sign well, scrapes.

1699
01:30:37,920 --> 01:30:40,920
Speaker 1: The research shows and I didn't actually say this a minute,

1700
01:30:40,960 --> 01:30:43,880
Speaker 1: you know, the scrapes have been shown the majority of

1701
01:30:43,880 --> 01:30:48,000
Speaker 1: them do happen at night. Um, and rubs I don't

1702
01:30:48,040 --> 01:30:51,160
Speaker 1: actually remember what the research says when thows occur, but

1703
01:30:51,520 --> 01:30:53,720
Speaker 1: I do know that that will increase, you know, the

1704
01:30:53,760 --> 01:30:58,200
Speaker 1: more you have of well balanced deer heard. Um. But

1705
01:30:58,439 --> 01:31:01,439
Speaker 1: just like any hunter that that's listening, you know, I

1706
01:31:01,479 --> 01:31:02,960
Speaker 1: go into a wood lot and I see a bunch

1707
01:31:02,960 --> 01:31:05,800
Speaker 1: of rubs, scripts I get excited. It looks like there's

1708
01:31:05,840 --> 01:31:10,400
Speaker 1: a buck using that property. Um, that's part of the property.

1709
01:31:10,520 --> 01:31:13,639
Speaker 1: Now you can set up over that scrape and hope

1710
01:31:13,680 --> 01:31:16,799
Speaker 1: that you see that deer, but no, that he's probably

1711
01:31:16,920 --> 01:31:21,040
Speaker 1: checking those at night. It's about of the research says

1712
01:31:21,160 --> 01:31:23,960
Speaker 1: that scrapes are made and checked at night. You could

1713
01:31:23,960 --> 01:31:26,920
Speaker 1: be a fift center. I have great daytime pictures of

1714
01:31:26,960 --> 01:31:29,639
Speaker 1: bucks using scrapes, you know, and I could have been

1715
01:31:29,680 --> 01:31:32,479
Speaker 1: sitting there in that standard in that time. Again, if

1716
01:31:32,520 --> 01:31:34,920
Speaker 1: you want to play the law of averages and listen

1717
01:31:34,920 --> 01:31:38,240
Speaker 1: to the research, you can say, well, okay, there's a

1718
01:31:38,280 --> 01:31:40,720
Speaker 1: scrape line going through this part of the property, and

1719
01:31:40,720 --> 01:31:43,360
Speaker 1: there's really no true scrape line. A lot of the

1720
01:31:43,400 --> 01:31:47,479
Speaker 1: research has shown and disputed. You might find us several

1721
01:31:47,479 --> 01:31:50,200
Speaker 1: scrapes on a ridge. Um, you could have a completely

1722
01:31:50,240 --> 01:31:53,559
Speaker 1: different set of box using. It's not made by one

1723
01:31:53,600 --> 01:31:56,960
Speaker 1: deer walking in a line. This is just a concentration

1724
01:31:57,000 --> 01:32:00,680
Speaker 1: of activity where box are leaving their sign and it's

1725
01:32:00,680 --> 01:32:03,240
Speaker 1: probably because there's dose near there, so they're leaving their

1726
01:32:03,280 --> 01:32:07,280
Speaker 1: sign for dose. Um. You know, so I can go

1727
01:32:07,360 --> 01:32:09,320
Speaker 1: in there with my climber and say, well, there's a

1728
01:32:09,320 --> 01:32:11,280
Speaker 1: bunch of scrapes right here. I'm gonna set up right

1729
01:32:11,320 --> 01:32:13,880
Speaker 1: here and have the expectation of seeing a buck. I

1730
01:32:13,960 --> 01:32:17,000
Speaker 1: know as a researcher, you know in a dear biologist

1731
01:32:17,040 --> 01:32:19,400
Speaker 1: that you know what, these are probably being made at night.

1732
01:32:20,080 --> 01:32:23,320
Speaker 1: Um eight, these are being made at night, and there's

1733
01:32:23,320 --> 01:32:25,000
Speaker 1: probably a chance I'm not going to see the book,

1734
01:32:25,240 --> 01:32:27,000
Speaker 1: but I might still set up there saying, you know what,

1735
01:32:27,240 --> 01:32:29,280
Speaker 1: it could be one of those fifteen percent times that

1736
01:32:29,320 --> 01:32:31,439
Speaker 1: a buck coming through. And I've gotten I've seen a

1737
01:32:31,439 --> 01:32:34,960
Speaker 1: lot of different, you know, responses on our website and

1738
01:32:35,240 --> 01:32:37,960
Speaker 1: social media posts and other things when this research gets

1739
01:32:38,280 --> 01:32:41,720
Speaker 1: put out there in articles or posts or things like that.

1740
01:32:41,720 --> 01:32:44,200
Speaker 1: Is somebody put a picture of a buck making a scrape. Well,

1741
01:32:44,200 --> 01:32:46,160
Speaker 1: of course, yes, that doesn't. I mean, you can't say

1742
01:32:46,200 --> 01:32:49,439
Speaker 1: absolutely anything. And that's one of the things I mentioned

1743
01:32:49,439 --> 01:32:54,360
Speaker 1: about science is what peer reviewed research gives us is

1744
01:32:54,400 --> 01:32:58,240
Speaker 1: a is a moment in time. Um, the researchers collared

1745
01:32:58,479 --> 01:33:00,800
Speaker 1: box or they did this or did that on a

1746
01:33:00,840 --> 01:33:04,679
Speaker 1: property in you know, Iowa, Maryland to Texas to New York,

1747
01:33:05,200 --> 01:33:07,479
Speaker 1: and you can say, well, that's the case in New York.

1748
01:33:08,000 --> 01:33:12,599
Speaker 1: That the true test of science is repeatability, being able

1749
01:33:12,640 --> 01:33:15,080
Speaker 1: to try it again. And some of his research has

1750
01:33:15,120 --> 01:33:17,360
Speaker 1: been repeated in different parts of the country and they've

1751
01:33:17,400 --> 01:33:20,919
Speaker 1: done the same test and they've shown the same results.

1752
01:33:21,760 --> 01:33:24,519
Speaker 1: The that's the real true part of science is learning

1753
01:33:24,520 --> 01:33:27,800
Speaker 1: what the majority of the things happen. But as a

1754
01:33:27,880 --> 01:33:30,679
Speaker 1: hunter you need to take that and synthesize and say,

1755
01:33:30,800 --> 01:33:33,880
Speaker 1: how do I apply that to my situation? Shoot, Mark

1756
01:33:33,960 --> 01:33:35,439
Speaker 1: and Dan, I'm still going to go out and set

1757
01:33:35,479 --> 01:33:37,679
Speaker 1: up a stand and be near scrapes because that means

1758
01:33:37,680 --> 01:33:39,960
Speaker 1: there's bucks in the area. I'm not going to think

1759
01:33:40,000 --> 01:33:41,880
Speaker 1: as a you know, as a hunter, that's what I'm

1760
01:33:41,920 --> 01:33:46,200
Speaker 1: going to do. I know my expectations might be, uh

1761
01:33:46,360 --> 01:33:49,760
Speaker 1: that bock might not be here during daylight, um, but

1762
01:33:50,400 --> 01:33:52,200
Speaker 1: I also know that there's a lot of activity in

1763
01:33:52,200 --> 01:33:54,040
Speaker 1: that area, so it might be a shot. So you

1764
01:33:54,080 --> 01:33:57,360
Speaker 1: have to just kind of balance all that. Yeah, so true,

1765
01:33:57,560 --> 01:34:01,479
Speaker 1: it's the it's six one half doesn't the other but finding,

1766
01:34:01,520 --> 01:34:03,479
Speaker 1: you know, taking what you can learn from that, and

1767
01:34:03,520 --> 01:34:06,559
Speaker 1: then you say, okay, well exactly like what you said.

1768
01:34:06,560 --> 01:34:08,360
Speaker 1: The way I think about it is, okay, I understand

1769
01:34:08,360 --> 01:34:13,280
Speaker 1: that this might be happening during dark. But at the

1770
01:34:13,320 --> 01:34:15,120
Speaker 1: same time, if you look at that point where there's

1771
01:34:15,120 --> 01:34:16,720
Speaker 1: a scrape, where I could say, okay, I know that

1772
01:34:16,760 --> 01:34:19,040
Speaker 1: there's a twenty chance he's touching that he's coming to

1773
01:34:19,080 --> 01:34:21,519
Speaker 1: this place potentially, or I could go to some other

1774
01:34:21,600 --> 01:34:23,719
Speaker 1: random place a hundred yards away where there's no scrapes

1775
01:34:23,760 --> 01:34:25,479
Speaker 1: at all, and you know, okay, do I have a

1776
01:34:26,120 --> 01:34:28,080
Speaker 1: chance of about coming here. Maybe it's even less there

1777
01:34:28,120 --> 01:34:30,880
Speaker 1: because there's you know, no particular reasons. So it's one

1778
01:34:30,880 --> 01:34:33,560
Speaker 1: more little piece of the puzzle you can put potentially

1779
01:34:33,560 --> 01:34:36,080
Speaker 1: in your favor if you apply it um. But maybe

1780
01:34:36,240 --> 01:34:40,920
Speaker 1: maybe it's not something to rest your entire strategy on. So, uh, Dan,

1781
01:34:41,920 --> 01:34:44,960
Speaker 1: are you? Are you okay? Over there? You live in

1782
01:34:45,320 --> 01:34:47,479
Speaker 1: your thoughts, I'm sponging it up. I want to know

1783
01:34:47,880 --> 01:34:53,599
Speaker 1: one thing based off Yeah, just well, I mean there's

1784
01:34:53,640 --> 01:34:56,840
Speaker 1: literally another episode worth of questions that we could ask

1785
01:34:56,920 --> 01:35:00,240
Speaker 1: you and go detail to, you know, to all get out.

1786
01:35:00,320 --> 01:35:06,240
Speaker 1: But you know, a lot of people use, I guess,

1787
01:35:06,320 --> 01:35:12,000
Speaker 1: hunting information that's not scientific to learn how to hunt. Um, Like,

1788
01:35:12,120 --> 01:35:15,280
Speaker 1: oh man, when when the rooster crows, you better be

1789
01:35:15,360 --> 01:35:18,240
Speaker 1: in the timber. Or you know, when the cows are

1790
01:35:18,320 --> 01:35:21,000
Speaker 1: standing with their wind they're back to the east, you

1791
01:35:21,080 --> 01:35:23,080
Speaker 1: better be in the timber. You know, those kind of

1792
01:35:23,120 --> 01:35:27,519
Speaker 1: things or even myths that are um, even things that

1793
01:35:27,600 --> 01:35:31,120
Speaker 1: are on like the outdoor channel or on the you know,

1794
01:35:31,320 --> 01:35:34,920
Speaker 1: these celebrities are telling you how to do these things.

1795
01:35:34,960 --> 01:35:39,439
Speaker 1: Are there any myths that science has disproven? That's basically

1796
01:35:39,479 --> 01:35:45,559
Speaker 1: just like, hey, that's that's you're you're wrong. That's a

1797
01:35:45,560 --> 01:35:48,920
Speaker 1: great question. There's probably a pile of them, uh, you know,

1798
01:35:49,760 --> 01:35:52,160
Speaker 1: one of the things. And again getting back to the

1799
01:35:52,400 --> 01:35:56,000
Speaker 1: you know what peer reviewed research says, um, the biggest

1800
01:35:56,040 --> 01:35:58,640
Speaker 1: is probably the moon phase. I mean that that is

1801
01:35:58,640 --> 01:36:01,040
Speaker 1: the one smack dab in the you know, elephant in

1802
01:36:01,080 --> 01:36:03,519
Speaker 1: the room when it comes to the rot um. As

1803
01:36:03,560 --> 01:36:05,680
Speaker 1: far as I know, you know, I've looked at a

1804
01:36:05,720 --> 01:36:10,920
Speaker 1: lot of different projects, um where they've looked at moon

1805
01:36:11,000 --> 01:36:15,080
Speaker 1: phase in comparison to buck activity. Again, you don't necessarily

1806
01:36:15,080 --> 01:36:19,080
Speaker 1: know when deer are breeding when they have a collar on,

1807
01:36:19,160 --> 01:36:20,719
Speaker 1: but you can just see when they're on their feet,

1808
01:36:21,160 --> 01:36:25,639
Speaker 1: and that hasn't shown any evidence of, you know, being

1809
01:36:25,680 --> 01:36:29,800
Speaker 1: correlated when moon phase changes. Um that it's going to

1810
01:36:29,920 --> 01:36:32,960
Speaker 1: impact the deer's behavior. Is it has to do with

1811
01:36:33,240 --> 01:36:37,040
Speaker 1: everything else. I do think the one thing that along

1812
01:36:37,040 --> 01:36:39,880
Speaker 1: those lines is the whether I mentioned earlier. You know,

1813
01:36:40,000 --> 01:36:42,360
Speaker 1: something tells me that whether it must impact when deer

1814
01:36:42,439 --> 01:36:45,080
Speaker 1: or movement, But that also has been shown to not

1815
01:36:45,200 --> 01:36:47,720
Speaker 1: be correlated. Which that's a head scratcher for me. So

1816
01:36:48,080 --> 01:36:51,240
Speaker 1: you know, I wouldn't be surprised if either of those cases,

1817
01:36:51,240 --> 01:36:56,280
Speaker 1: some some researchers finds evidence that you know, moon phase

1818
01:36:56,360 --> 01:36:59,479
Speaker 1: in in a certain situation. I'm talking about five six

1819
01:36:59,479 --> 01:37:03,000
Speaker 1: different objects that have looked at that and in some cases,

1820
01:37:03,120 --> 01:37:05,679
Speaker 1: you know, half a million data points off of hundreds

1821
01:37:05,720 --> 01:37:08,679
Speaker 1: of bucks that are colored haven't found it. You've got

1822
01:37:08,680 --> 01:37:11,519
Speaker 1: to feel like, okay, well, you know there's got to

1823
01:37:11,560 --> 01:37:14,000
Speaker 1: be some truth to that. It wouldn't be some surprise

1824
01:37:14,080 --> 01:37:17,120
Speaker 1: if somebody found one project that said yeah, it does

1825
01:37:18,120 --> 01:37:21,000
Speaker 1: on the flip side. Uh So somebody could do the

1826
01:37:21,000 --> 01:37:23,240
Speaker 1: same with weather, and me, as a hunter wants to

1827
01:37:23,240 --> 01:37:26,000
Speaker 1: say I knew it, but I also know there's half

1828
01:37:26,040 --> 01:37:28,080
Speaker 1: a dozen projects out there that have tied all those

1829
01:37:28,160 --> 01:37:32,439
Speaker 1: data points to weather events, you know, barometric pressure and

1830
01:37:32,880 --> 01:37:36,080
Speaker 1: cold fronts and rain and all those things, and haven't

1831
01:37:36,080 --> 01:37:39,280
Speaker 1: found anything. So, you know, I gotta be a hunter

1832
01:37:39,360 --> 01:37:42,560
Speaker 1: in some cases, and I gotta be a researcher and others.

1833
01:37:42,600 --> 01:37:45,920
Speaker 1: So as someone like myself who likes to follow the science,

1834
01:37:45,960 --> 01:37:48,960
Speaker 1: I'm gonna say something. I'm gonna say this out loud

1835
01:37:49,240 --> 01:37:54,600
Speaker 1: just so people hear it. Based Yeah, based on the

1836
01:37:54,760 --> 01:37:59,360
Speaker 1: research that has been done, moon the moon phase does

1837
01:37:59,520 --> 01:38:04,040
Speaker 1: not influence deer movement has been shown not to influence

1838
01:38:04,080 --> 01:38:08,160
Speaker 1: dear movement. Is that an accurate statement? Okay, very accurate?

1839
01:38:08,720 --> 01:38:15,600
Speaker 1: Based on research, weather patterns do have been shown to

1840
01:38:15,960 --> 01:38:22,720
Speaker 1: not change dear movement or like influence deer movement. That's

1841
01:38:22,720 --> 01:38:26,040
Speaker 1: another accurate statement. Correct. That is also another accurate statement.

1842
01:38:26,400 --> 01:38:32,600
Speaker 1: So everything that we have as hunters have you know,

1843
01:38:33,120 --> 01:38:38,920
Speaker 1: thought over the years, science is showing that, Yeah, guess what,

1844
01:38:39,479 --> 01:38:44,120
Speaker 1: it's really not so so then that just brings up

1845
01:38:44,160 --> 01:38:48,360
Speaker 1: these questions again, what is influencing dear movement? Here here's

1846
01:38:48,400 --> 01:38:51,080
Speaker 1: something I'd like to add on to that, dan Um,

1847
01:38:51,120 --> 01:38:55,040
Speaker 1: because I like mash my brain together trying to figure

1848
01:38:55,040 --> 01:38:56,840
Speaker 1: this out too, Because just like what you said, Matt,

1849
01:38:56,920 --> 01:38:59,960
Speaker 1: you said the research this that are these certain research

1850
01:39:00,040 --> 01:39:04,800
Speaker 1: scenarios have said this, But as a hunter, so many

1851
01:39:04,840 --> 01:39:08,479
Speaker 1: of us have anecdotally seen evidence that maybe there's something different.

1852
01:39:08,880 --> 01:39:11,920
Speaker 1: I wonder, as I try to think through this, could

1853
01:39:12,760 --> 01:39:15,840
Speaker 1: we be comparing apples to oranges here, and that the

1854
01:39:15,880 --> 01:39:19,160
Speaker 1: study is looking at a certain criteria is saying, you know,

1855
01:39:19,880 --> 01:39:22,519
Speaker 1: you know, dear movement or dear activity as they are

1856
01:39:22,560 --> 01:39:26,439
Speaker 1: measuring it might be very different from quote unquote dear

1857
01:39:26,520 --> 01:39:28,680
Speaker 1: movement or dear activity that we hunters are looking for.

1858
01:39:28,800 --> 01:39:33,160
Speaker 1: So hypothetically, could this be a scenario where the researcher

1859
01:39:33,280 --> 01:39:38,080
Speaker 1: is studying actual you know, um number of feet traveled

1860
01:39:38,120 --> 01:39:40,720
Speaker 1: throughout a twenty four hour period something like that, you know,

1861
01:39:40,880 --> 01:39:43,720
Speaker 1: the actual movement of this deer in twenty four hours,

1862
01:39:43,760 --> 01:39:47,839
Speaker 1: and they're saying, regardless of temperature or moon phase, the

1863
01:39:47,880 --> 01:39:51,280
Speaker 1: amount of actual distance traveled is not any different. While

1864
01:39:51,400 --> 01:39:54,120
Speaker 1: from a hunter standpoint, I might be curious in how

1865
01:39:54,200 --> 01:39:57,720
Speaker 1: much movement in the open is happening during daylight, that

1866
01:39:57,840 --> 01:39:59,920
Speaker 1: kind of thing, you know, that's the activity that I

1867
01:40:00,000 --> 01:40:02,519
Speaker 1: I'm interested in. So could a cold front increase the

1868
01:40:02,520 --> 01:40:05,599
Speaker 1: amount of movement out of their bedding area during daylight

1869
01:40:06,240 --> 01:40:08,479
Speaker 1: is that, you know, maybe that's what I'm interested in

1870
01:40:08,560 --> 01:40:10,639
Speaker 1: from a hunter standpoint, and maybe the cold front does

1871
01:40:10,680 --> 01:40:14,040
Speaker 1: trigger increased activity there, but it doesn't necessarily change the

1872
01:40:14,120 --> 01:40:17,240
Speaker 1: absolute distance of total travel in twenty four hours. That's

1873
01:40:17,320 --> 01:40:20,040
Speaker 1: my hypothesis. There might be some difference in the actual

1874
01:40:20,479 --> 01:40:24,000
Speaker 1: measurement criteria met Is there any possible Does that make

1875
01:40:24,000 --> 01:40:27,400
Speaker 1: any sense at all? It does, And not every one

1876
01:40:27,439 --> 01:40:29,559
Speaker 1: of those projects has looked in that, but some of

1877
01:40:29,600 --> 01:40:33,519
Speaker 1: them have. They've looked at vulnerability to harvest from daylight

1878
01:40:33,560 --> 01:40:39,240
Speaker 1: to night versus. And also things like distance from tree stands,

1879
01:40:39,280 --> 01:40:42,600
Speaker 1: having like tree stands GPS on some of these properties

1880
01:40:42,960 --> 01:40:45,559
Speaker 1: and looking at how vulnerable they were within a hundred

1881
01:40:45,920 --> 01:40:48,160
Speaker 1: or a hundred yards distance if it was gun season

1882
01:40:48,320 --> 01:40:52,320
Speaker 1: or you know, thirty yard distance from those stands uh

1883
01:40:52,720 --> 01:40:55,559
Speaker 1: during bow And again none of that stuff has shown

1884
01:40:55,600 --> 01:40:59,720
Speaker 1: any correlation. Stuff. Yeah, a lot of stuff with the

1885
01:40:59,760 --> 01:41:04,240
Speaker 1: moon phase UH that was initially done looked at conceptions

1886
01:41:04,240 --> 01:41:06,639
Speaker 1: and that was all based on fetal measurements. They looked

1887
01:41:06,680 --> 01:41:09,679
Speaker 1: at when the bulk of the deer those were being bred,

1888
01:41:10,240 --> 01:41:13,960
Speaker 1: and correlated that to moon. No, no correlation. But a

1889
01:41:13,960 --> 01:41:18,160
Speaker 1: lot of this GPS research is also looking at breeding dates,

1890
01:41:18,640 --> 01:41:23,080
Speaker 1: but they're also looking at UM movements over twenty four

1891
01:41:23,120 --> 01:41:27,439
Speaker 1: period and some of them to degree that Mark is saying,

1892
01:41:27,479 --> 01:41:30,400
Speaker 1: you know, daytime versus night and and other things. So

1893
01:41:30,880 --> 01:41:34,960
Speaker 1: and again you know I said this before. Uh, it

1894
01:41:35,040 --> 01:41:37,720
Speaker 1: comes down to the property. I mean it really does.

1895
01:41:37,800 --> 01:41:40,120
Speaker 1: I mean you can talk about this big umbrella of

1896
01:41:40,160 --> 01:41:43,280
Speaker 1: what research is saying if you want to believe, I

1897
01:41:43,280 --> 01:41:46,080
Speaker 1: mean I will. I'm glad Dan said that. That is

1898
01:41:46,080 --> 01:41:48,240
Speaker 1: the take on message. There's no research to sup for

1899
01:41:48,400 --> 01:41:52,320
Speaker 1: any of that those theories. It doesn't it doesn't come out. However,

1900
01:41:53,000 --> 01:41:56,360
Speaker 1: you know, when it comes down to it, don't don't

1901
01:41:56,439 --> 01:41:58,439
Speaker 1: throw that away. You don't throw it in the trash

1902
01:41:58,600 --> 01:42:01,200
Speaker 1: paper basket when you get off listen to this and

1903
01:42:01,240 --> 01:42:04,040
Speaker 1: say that guy doesn't know what he's talking about or

1904
01:42:04,120 --> 01:42:07,519
Speaker 1: what I know because I saw this. That's not good

1905
01:42:07,600 --> 01:42:11,000
Speaker 1: enough because you're not talking about hundreds of deers with

1906
01:42:11,120 --> 01:42:14,559
Speaker 1: collars or you know, thousands or ten thousands of data

1907
01:42:14,600 --> 01:42:18,599
Speaker 1: points that are collared. That's very different. But I would

1908
01:42:18,600 --> 01:42:22,400
Speaker 1: still suggest to the hunter that wants to micro manage

1909
01:42:22,400 --> 01:42:26,080
Speaker 1: the property and understand this research might say all this,

1910
01:42:26,600 --> 01:42:30,559
Speaker 1: It might show that these things aren't correlated. UM but

1911
01:42:30,680 --> 01:42:33,960
Speaker 1: I can tell you you might be the day that

1912
01:42:34,080 --> 01:42:36,200
Speaker 1: you go out there and say, you know what the

1913
01:42:36,200 --> 01:42:39,599
Speaker 1: moon phase is telling me this, or there's a cold front.

1914
01:42:39,720 --> 01:42:41,559
Speaker 1: And again I'm telling you, as a hunter, I feel

1915
01:42:41,600 --> 01:42:44,760
Speaker 1: like weather must do more than what the researchers said.

1916
01:42:44,800 --> 01:42:47,559
Speaker 1: But it hasn't shown up. Um, it just has to

1917
01:42:47,560 --> 01:42:50,559
Speaker 1: be something related to it. But again, I'm a deer

1918
01:42:50,600 --> 01:42:55,040
Speaker 1: hunter too. Um. You could be in a stand and

1919
01:42:55,200 --> 01:42:57,840
Speaker 1: have a buck make a decision that changes his fate

1920
01:42:57,880 --> 01:43:00,680
Speaker 1: and you kill him. And you might hie that to

1921
01:43:00,960 --> 01:43:04,880
Speaker 1: one of those multiple things we're talking about. Um, but

1922
01:43:04,960 --> 01:43:07,840
Speaker 1: that's still anecdotal. But who cares? You still kill that

1923
01:43:07,880 --> 01:43:10,800
Speaker 1: dear he changed his behavior. Um. Or even at a

1924
01:43:10,800 --> 01:43:14,000
Speaker 1: property level, you might be on a property where things

1925
01:43:14,000 --> 01:43:15,880
Speaker 1: are in a frenzy. It has nothing to do with

1926
01:43:15,960 --> 01:43:20,439
Speaker 1: moon or weather. Is just because dear is so social.

1927
01:43:21,040 --> 01:43:23,960
Speaker 1: You know, something impacted them. You know a couple of

1928
01:43:23,960 --> 01:43:26,600
Speaker 1: does that went into estress early, or a buck just

1929
01:43:26,920 --> 01:43:29,760
Speaker 1: that felt so you know, Randy, he was getting dose

1930
01:43:29,880 --> 01:43:32,000
Speaker 1: up and moving them around, and that just triggered other

1931
01:43:32,000 --> 01:43:33,880
Speaker 1: deer to get up and move. I mean, I know

1932
01:43:33,920 --> 01:43:35,559
Speaker 1: you guys have seen this where you're in a in

1933
01:43:35,600 --> 01:43:39,599
Speaker 1: a stand and you see dear almost playing another dear

1934
01:43:39,640 --> 01:43:42,720
Speaker 1: react to it by playing or deer running away from

1935
01:43:42,920 --> 01:43:45,519
Speaker 1: fear from a kyle or a hunter or a buck

1936
01:43:45,600 --> 01:43:49,160
Speaker 1: chasing and other do dear do that? I mean, there's

1937
01:43:49,200 --> 01:43:52,759
Speaker 1: no way to measure that randomness. All you can do

1938
01:43:53,040 --> 01:43:57,040
Speaker 1: as a hunter is know when your best chance of

1939
01:43:57,080 --> 01:43:59,679
Speaker 1: shooting a buck is or your best chance of getting

1940
01:43:59,680 --> 01:44:03,080
Speaker 1: that deer within range, and spend as much time as

1941
01:44:03,120 --> 01:44:06,240
Speaker 1: you possibly can understand, because it's going to increase that

1942
01:44:06,320 --> 01:44:08,360
Speaker 1: percentage of Yes, you're going to get a shot. And

1943
01:44:08,360 --> 01:44:11,479
Speaker 1: I talked about earlier. Your proficiency and your ability to

1944
01:44:11,479 --> 01:44:13,760
Speaker 1: pick a good stand location is going to be a

1945
01:44:13,760 --> 01:44:16,120
Speaker 1: big part of that success. So your skill elbow as

1946
01:44:16,160 --> 01:44:19,080
Speaker 1: a hunter certainly will play a part of it. And luck,

1947
01:44:19,280 --> 01:44:22,120
Speaker 1: of course obviously comes into it too. But if I

1948
01:44:22,200 --> 01:44:25,080
Speaker 1: was a betting man, I would you know. We know

1949
01:44:25,160 --> 01:44:27,320
Speaker 1: that deer are most active at dawn and dusk or

1950
01:44:27,360 --> 01:44:30,120
Speaker 1: around those hours. Deer killed all the time in the

1951
01:44:30,120 --> 01:44:33,479
Speaker 1: middle of the day. Um, but you know, the bulk

1952
01:44:33,520 --> 01:44:37,160
Speaker 1: of the research says they're most active at dawn and dusk. Uh,

1953
01:44:37,840 --> 01:44:40,439
Speaker 1: they're gonna be most vulnerable during the rot. You know,

1954
01:44:40,439 --> 01:44:43,160
Speaker 1: the first couple of weeks in November, they're going to

1955
01:44:43,240 --> 01:44:48,840
Speaker 1: be most vulnerable. Uh. What I feel like is when

1956
01:44:48,920 --> 01:44:51,599
Speaker 1: a weather event is happening. Although the research doesn't say

1957
01:44:51,600 --> 01:44:53,880
Speaker 1: that I'm going to spend time in a stand when

1958
01:44:53,920 --> 01:44:56,559
Speaker 1: that stuff is happening, and just the fact that I'm

1959
01:44:56,600 --> 01:44:59,040
Speaker 1: spending time out there is going to increase my chances.

1960
01:44:59,439 --> 01:45:02,320
Speaker 1: You know, I'm my believe a magic rock will increase

1961
01:45:02,360 --> 01:45:04,240
Speaker 1: my chances, and I might keep it in my pocket

1962
01:45:04,520 --> 01:45:06,160
Speaker 1: and I might kill a bucket. I'm gonna say, you

1963
01:45:06,160 --> 01:45:09,439
Speaker 1: know what, that rock made that that happen. That doesn't necessary,

1964
01:45:09,479 --> 01:45:11,960
Speaker 1: It's not a cause and effect thing. But it doesn't

1965
01:45:12,000 --> 01:45:15,960
Speaker 1: matter because you know, through science, when it's telling you

1966
01:45:16,000 --> 01:45:18,280
Speaker 1: to spend the most time and just be out there,

1967
01:45:18,439 --> 01:45:23,000
Speaker 1: be present and be one, you know, mentally recording all

1968
01:45:23,000 --> 01:45:25,360
Speaker 1: of this stuff or just physically recording it like through

1969
01:45:25,400 --> 01:45:28,640
Speaker 1: that deer tracker app I mentioned earlier, to you know,

1970
01:45:29,520 --> 01:45:33,760
Speaker 1: allow for a better uh documentation of what's happening on

1971
01:45:33,800 --> 01:45:36,960
Speaker 1: the property and across the country. UM as well as

1972
01:45:37,000 --> 01:45:38,680
Speaker 1: just being there to be able to make some of

1973
01:45:38,720 --> 01:45:41,760
Speaker 1: those choices and react to them. If you see there's

1974
01:45:41,760 --> 01:45:44,080
Speaker 1: a lot of activity in one corner of the property,

1975
01:45:44,280 --> 01:45:47,599
Speaker 1: be adapted to move your stand that day, get down,

1976
01:45:47,720 --> 01:45:51,559
Speaker 1: move it, and uh you might be more successful because

1977
01:45:51,560 --> 01:45:55,960
Speaker 1: of it. Yeah. I Uh, this is one of those

1978
01:45:55,960 --> 01:46:01,320
Speaker 1: topics that is it's the bullet. It's just it's for me.

1979
01:46:01,360 --> 01:46:03,960
Speaker 1: It's one of those things where it's like, man, you

1980
01:46:04,320 --> 01:46:07,320
Speaker 1: talked to so many people and they and they say, Man,

1981
01:46:07,360 --> 01:46:09,439
Speaker 1: I'm telling you what you get in the stand when

1982
01:46:09,479 --> 01:46:11,759
Speaker 1: the moon is right here and then there's high pressure,

1983
01:46:11,840 --> 01:46:13,920
Speaker 1: or when there's a coal front coming through and you're

1984
01:46:13,920 --> 01:46:17,879
Speaker 1: gonna kill a buck. And then here's a research, actual

1985
01:46:18,520 --> 01:46:26,400
Speaker 1: factual research that shows that they're not a correct But

1986
01:46:26,439 --> 01:46:30,000
Speaker 1: then to Matt's point, to nothing is nothing is solid,

1987
01:46:30,120 --> 01:46:33,160
Speaker 1: nothing solid, And to his point about to your point

1988
01:46:33,160 --> 01:46:36,000
Speaker 1: mad about whether I mean, you talk to any serious

1989
01:46:36,000 --> 01:46:37,960
Speaker 1: deer hunter and they're gonna say, yes, we are seeing

1990
01:46:38,000 --> 01:46:41,120
Speaker 1: different dear behavior when the weather front comes through, but

1991
01:46:41,160 --> 01:46:44,000
Speaker 1: the research doesn't support it. So that I mean that

1992
01:46:44,000 --> 01:46:46,280
Speaker 1: that raises similar questions about some other things too. There

1993
01:46:46,360 --> 01:46:49,799
Speaker 1: might be you know, I'm not I find this very interesting.

1994
01:46:50,080 --> 01:46:51,800
Speaker 1: I take it into account, I put it in the

1995
01:46:51,800 --> 01:46:54,400
Speaker 1: tool chest, but I'm not necessarily throwing out some of

1996
01:46:54,439 --> 01:46:57,120
Speaker 1: these other theories too that are intriguing because you know,

1997
01:46:57,160 --> 01:46:59,600
Speaker 1: because I think here's one interesting thing that kind of

1998
01:46:59,640 --> 01:47:03,920
Speaker 1: my fine thought on this is that you take a guy, hypothetically,

1999
01:47:04,000 --> 01:47:05,680
Speaker 1: let's say one of these, one of these hunters that

2000
01:47:05,880 --> 01:47:10,280
Speaker 1: really strongly believes in the position of the moon, and

2001
01:47:10,320 --> 01:47:12,680
Speaker 1: that influencing, you know, a little bit of increased to

2002
01:47:12,720 --> 01:47:14,559
Speaker 1: your activity. And that's something that both you and me, Dan,

2003
01:47:14,640 --> 01:47:16,080
Speaker 1: We've been listening to a lot of guys talk about

2004
01:47:16,080 --> 01:47:18,240
Speaker 1: and it's really interesting and intriguing, and I've been trying

2005
01:47:18,240 --> 01:47:20,400
Speaker 1: to pay more attention to it too. But let's take

2006
01:47:20,400 --> 01:47:22,200
Speaker 1: a guy who is a die hard believer in it.

2007
01:47:23,200 --> 01:47:27,160
Speaker 1: When that person, let's hypothetical Calum Ben. When Ben goes

2008
01:47:27,200 --> 01:47:30,400
Speaker 1: into the woods with this very strong belief in this

2009
01:47:30,479 --> 01:47:32,720
Speaker 1: theory that when the moon's overhead or whatever, that he's

2010
01:47:32,720 --> 01:47:35,040
Speaker 1: gonna have a great chance. When you go into a

2011
01:47:35,080 --> 01:47:37,000
Speaker 1: tree stand with a piece of data like that or

2012
01:47:37,000 --> 01:47:39,679
Speaker 1: a belief like that, you believe in it so strongly.

2013
01:47:40,400 --> 01:47:44,080
Speaker 1: I believe your confidence level can be an influencer of

2014
01:47:44,120 --> 01:47:46,920
Speaker 1: the success you have, merely because when you are very

2015
01:47:46,960 --> 01:47:49,240
Speaker 1: confident in your stand site and in the conditions on

2016
01:47:49,280 --> 01:47:52,080
Speaker 1: that day and on why you're hunting there, when your

2017
01:47:52,080 --> 01:47:54,479
Speaker 1: confidence is that high, I believe that you operate at

2018
01:47:54,479 --> 01:47:57,479
Speaker 1: a different level of efficiency and effectiveness as a hunter.

2019
01:47:58,000 --> 01:48:00,679
Speaker 1: So when you're super confident, you're paying at engine everything

2020
01:48:00,680 --> 01:48:04,200
Speaker 1: around you, you notice every flicker movement, You're super quiet,

2021
01:48:04,240 --> 01:48:06,679
Speaker 1: you're super detailed, You're crossing all your teas and dotting

2022
01:48:06,680 --> 01:48:09,120
Speaker 1: all of your eyes. And I think maybe there's almost

2023
01:48:09,120 --> 01:48:11,880
Speaker 1: a self fulfilling prophecy happening here, where when you have

2024
01:48:11,960 --> 01:48:14,760
Speaker 1: such a strong belief in something happening, you just hunt

2025
01:48:14,800 --> 01:48:17,400
Speaker 1: better and because of that, you have more success. And

2026
01:48:17,439 --> 01:48:22,799
Speaker 1: I'm curious if maybe there's something to that, I'll comment,

2027
01:48:22,840 --> 01:48:24,960
Speaker 1: and I think there is. And I think not only

2028
01:48:25,280 --> 01:48:29,280
Speaker 1: that mark is that um. Not only they might be

2029
01:48:29,320 --> 01:48:33,120
Speaker 1: more confident and more efficient, um, but that type of hunter,

2030
01:48:33,560 --> 01:48:37,120
Speaker 1: that type of deer hunter that cares to look deeper

2031
01:48:37,720 --> 01:48:42,040
Speaker 1: and ask questions and try to improve their own ability,

2032
01:48:42,240 --> 01:48:45,480
Speaker 1: is the type of hunter that's going to improve anyway,

2033
01:48:45,560 --> 01:48:48,720
Speaker 1: do you know what I mean? Instead of just haphazardly

2034
01:48:48,760 --> 01:48:54,400
Speaker 1: going in the woods or hunting uh as a as

2035
01:48:54,439 --> 01:48:58,040
Speaker 1: a means of tradition, you know, going to the stand

2036
01:48:58,080 --> 01:49:00,920
Speaker 1: that grand Pappy talked me to opening day and that's

2037
01:49:00,960 --> 01:49:03,080
Speaker 1: the only day that he goes out or she goes out.

2038
01:49:03,560 --> 01:49:07,440
Speaker 1: The person that's saying, how can I be better? UM,

2039
01:49:07,600 --> 01:49:09,960
Speaker 1: some of that is going to be self fulfilling. It

2040
01:49:10,080 --> 01:49:13,639
Speaker 1: has to be because they're trying to up their bad

2041
01:49:14,240 --> 01:49:16,479
Speaker 1: I also think that there's probably as many, if not

2042
01:49:16,640 --> 01:49:19,559
Speaker 1: more people out there that are the hardcore you know,

2043
01:49:19,640 --> 01:49:23,799
Speaker 1: in this example, moon theory believers that are not killing

2044
01:49:23,800 --> 01:49:27,479
Speaker 1: a buck that day and the moon is the cause

2045
01:49:27,520 --> 01:49:33,360
Speaker 1: of it. You know, something happened that was wrong. And again,

2046
01:49:33,920 --> 01:49:36,000
Speaker 1: when it comes down to science, is really hard to

2047
01:49:36,120 --> 01:49:38,800
Speaker 1: argue with UM, And there's always going to be uh,

2048
01:49:39,360 --> 01:49:40,880
Speaker 1: you know, well that didn't work for me because that

2049
01:49:41,080 --> 01:49:44,040
Speaker 1: project was from Texas or you know, I live in

2050
01:49:44,080 --> 01:49:48,160
Speaker 1: New York and that research was from Florida. Yeah, of course,

2051
01:49:48,200 --> 01:49:50,040
Speaker 1: I mean there's no way you can test at all.

2052
01:49:50,400 --> 01:49:53,400
Speaker 1: But if you can repeat results, you get a better

2053
01:49:53,439 --> 01:49:55,240
Speaker 1: sense of what's going on. But we're never going to

2054
01:49:55,320 --> 01:49:58,639
Speaker 1: have all the answers UM. And that's the case. So yeah,

2055
01:49:58,640 --> 01:50:01,400
Speaker 1: I do think, yeah, there's some truth to that, UM.

2056
01:50:01,439 --> 01:50:03,439
Speaker 1: But I think it's also the type of hunter that

2057
01:50:03,520 --> 01:50:07,080
Speaker 1: you're talking about, your categorizing. Out of the eleven to

2058
01:50:07,200 --> 01:50:10,200
Speaker 1: thirteen million deer hunters out there, I guarantee you not

2059
01:50:10,240 --> 01:50:13,160
Speaker 1: all of them are paying attention to moon face. UM,

2060
01:50:13,479 --> 01:50:18,680
Speaker 1: the ones that are are trying to make their situation better. Yeah, yeah, absolutely,

2061
01:50:19,240 --> 01:50:20,960
Speaker 1: well I think anyway you look at it, this is

2062
01:50:20,960 --> 01:50:25,080
Speaker 1: some pretty interesting stuff. And UM, we are conversations not over. Yeah,

2063
01:50:25,479 --> 01:50:28,040
Speaker 1: I wish the conversation wasn't over, but we do have

2064
01:50:28,080 --> 01:50:30,160
Speaker 1: to end this conversation because we are over time and

2065
01:50:30,160 --> 01:50:32,440
Speaker 1: we've kept you way too long, Matt, so I apologize

2066
01:50:32,479 --> 01:50:34,960
Speaker 1: for that, but thank you for taking the time to

2067
01:50:34,960 --> 01:50:38,160
Speaker 1: to talk through all this stuff because it's awesome. UM.

2068
01:50:38,200 --> 01:50:42,519
Speaker 1: If our listeners want to learn more about qualitier management

2069
01:50:42,560 --> 01:50:46,240
Speaker 1: and the quality or management association where you work, where

2070
01:50:46,280 --> 01:50:48,320
Speaker 1: can they go to get some information about this kind

2071
01:50:48,320 --> 01:50:51,959
Speaker 1: of stuff. The easiest thing is to find us online

2072
01:50:52,479 --> 01:50:56,120
Speaker 1: cut m A dot com. UM. You can follow us

2073
01:50:56,120 --> 01:50:58,800
Speaker 1: through social media too. We have very active Facebook and

2074
01:50:58,840 --> 01:51:04,080
Speaker 1: Twitter platforms. Um A membership is fairly inexpensive. It's on

2075
01:51:04,200 --> 01:51:07,439
Speaker 1: par with the other conservation groups UM, and I would

2076
01:51:07,960 --> 01:51:11,320
Speaker 1: encourage and challenge all listeners. If you're a deer hunter,

2077
01:51:11,960 --> 01:51:17,120
Speaker 1: UM join one reason you'll you'll improve your deer hunting knowledge.

2078
01:51:17,240 --> 01:51:19,400
Speaker 1: You'll make yourself a better deer hunter and be able

2079
01:51:19,439 --> 01:51:21,720
Speaker 1: to make better decisions because of it. It will make

2080
01:51:21,760 --> 01:51:25,280
Speaker 1: your deer hunting more fun and beyond all that, you know,

2081
01:51:25,479 --> 01:51:28,799
Speaker 1: there's a lot of stuff happening in the dear world

2082
01:51:28,960 --> 01:51:33,120
Speaker 1: that UM could be better. And as a conservation organization,

2083
01:51:33,280 --> 01:51:36,800
Speaker 1: we fight for every single one of those eleven plus

2084
01:51:36,880 --> 01:51:40,960
Speaker 1: deer million hunter rights on a daily basis. That's what

2085
01:51:41,040 --> 01:51:44,759
Speaker 1: we go to work every day for. And I challenge

2086
01:51:44,760 --> 01:51:47,040
Speaker 1: you to support an organization that's fighting for your right

2087
01:51:47,120 --> 01:51:50,800
Speaker 1: for deer hunting. So um quum dot com and it's

2088
01:51:50,840 --> 01:51:54,840
Speaker 1: a it's a great organization. I hope you decided to join. Yeah,

2089
01:51:54,880 --> 01:51:58,000
Speaker 1: I'll second everything you said there. I'll add one other challenge.

2090
01:51:58,600 --> 01:52:01,679
Speaker 1: I think there's a lot of misconceptions about the Quality

2091
01:52:01,680 --> 01:52:04,680
Speaker 1: Dear Management Association and about Quality Deer Management because that

2092
01:52:04,800 --> 01:52:06,880
Speaker 1: term QDM has kind of been stolen by a lot

2093
01:52:06,920 --> 01:52:10,040
Speaker 1: of people and applied to things that don't really fall

2094
01:52:10,080 --> 01:52:13,240
Speaker 1: in line with what you guys actually are fundamentally focused

2095
01:52:13,240 --> 01:52:15,720
Speaker 1: on UM. So I would challenge anyone who's you know,

2096
01:52:15,800 --> 01:52:18,320
Speaker 1: been anti QUDUM or q d M A or just

2097
01:52:18,400 --> 01:52:21,160
Speaker 1: not cared about it because of different, you know, assumptions

2098
01:52:21,160 --> 01:52:23,280
Speaker 1: you have. Just go to the website and read the

2099
01:52:23,320 --> 01:52:27,360
Speaker 1: about page and the mission and the philosophy, and I

2100
01:52:27,400 --> 01:52:30,000
Speaker 1: think people have a hard time reading those things that you,

2101
01:52:30,120 --> 01:52:32,680
Speaker 1: as the organization, the people working there are actually fighting for.

2102
01:52:33,120 --> 01:52:35,360
Speaker 1: That is really hard to argue with. I mean, there's

2103
01:52:35,360 --> 01:52:38,719
Speaker 1: some incredible things you guys are working on and promoting UM,

2104
01:52:38,800 --> 01:52:40,799
Speaker 1: and in a lot of cases it's it's very different

2105
01:52:40,840 --> 01:52:42,840
Speaker 1: from what Joe Blow on TV is talking about. So

2106
01:52:42,880 --> 01:52:45,080
Speaker 1: I would say, learn a little bit about it from

2107
01:52:45,120 --> 01:52:46,960
Speaker 1: the source before you make a decision, and I think

2108
01:52:46,960 --> 01:52:49,920
Speaker 1: if you do, you'll likely make a decision similar to

2109
01:52:49,960 --> 01:52:52,000
Speaker 1: what I have, and that is to become a member

2110
01:52:52,400 --> 01:52:54,320
Speaker 1: and take advantage of those resources that you said, Matt,

2111
01:52:54,400 --> 01:52:56,760
Speaker 1: You're great magazine, website, and the many other things you

2112
01:52:56,760 --> 01:52:59,000
Speaker 1: guys are doing. UM. It's been a it's been a

2113
01:52:59,000 --> 01:53:01,000
Speaker 1: great thing to be a part of. So, Matt, thank

2114
01:53:01,040 --> 01:53:03,880
Speaker 1: you so much for joining us here today. This has

2115
01:53:03,920 --> 01:53:07,840
Speaker 1: been really interesting. We appreciate your time. Thank you for

2116
01:53:07,880 --> 01:53:09,880
Speaker 1: having me. And I'll tell you on a personal I

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01:53:09,920 --> 01:53:12,240
Speaker 1: really enjoy what you guys are doing. I listened to

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01:53:12,360 --> 01:53:15,600
Speaker 1: podcasts and uh, um, keep doing what you're doing. I

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01:53:15,600 --> 01:53:18,639
Speaker 1: think you guys are doing a phenomenal job and changing

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01:53:18,640 --> 01:53:21,080
Speaker 1: things were deer hunters out there. Thank you man, I

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01:53:21,120 --> 01:53:23,719
Speaker 1: appreciate that. And hey, good luck on these upcoming hunts.

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01:53:24,439 --> 01:53:27,920
Speaker 1: Thanks you guys too, have a good one here, all right.

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01:53:28,080 --> 01:53:31,400
Speaker 1: So there you have it, another podcast in the books.

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Speaker 1: And before we go though, a couple of quick announcements.

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01:53:34,479 --> 01:53:37,840
Speaker 1: First off, we've got some new Wired Hunt gear available

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01:53:38,040 --> 01:53:39,800
Speaker 1: just in time for the rut. We've got a couple

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01:53:39,800 --> 01:53:42,760
Speaker 1: of different styles of trucker hats, a flatbill, and some

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01:53:42,920 --> 01:53:46,080
Speaker 1: lightweight hoodies, so check out wired to hunt dot com

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01:53:46,160 --> 01:53:48,679
Speaker 1: slash shop to grab some of that stuff, and please

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01:53:48,720 --> 01:53:52,120
Speaker 1: do your purchases go directly to keep this podcast and

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01:53:52,160 --> 01:53:54,720
Speaker 1: the Wired Hunt blog going, so thank you so much

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01:53:54,720 --> 01:53:57,639
Speaker 1: for that in advance. Also, be sure to check out

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01:53:57,640 --> 01:53:59,680
Speaker 1: the White Tail Q and A podcast, which is my

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01:53:59,760 --> 01:54:02,160
Speaker 1: short or Q and A format show, as we've got

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01:54:02,160 --> 01:54:05,920
Speaker 1: some great related episodes this week too and next. And

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01:54:06,080 --> 01:54:08,599
Speaker 1: also my co host Dan has launched a brand new

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01:54:08,680 --> 01:54:10,720
Speaker 1: podcast of his own, so be sure to look up

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01:54:10,720 --> 01:54:14,240
Speaker 1: the Nine Finger Chronicles podcast. Finally, we do need to

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01:54:14,240 --> 01:54:16,320
Speaker 1: give a big thank you to our partners who helped

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01:54:16,320 --> 01:54:19,120
Speaker 1: make this podcast possible. So big thank you too, Sick

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01:54:19,120 --> 01:54:23,960
Speaker 1: of Gear, Trophy, Ridge, Bear Archery, Redneck Blinds, Hunter, A, maps, Ozonics,

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01:54:24,040 --> 01:54:27,680
Speaker 1: Carbon Express, Lacrosse Boots, and the White Tail Institute of

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01:54:27,720 --> 01:54:32,040
Speaker 1: North America. So with all that said, the rut is

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01:54:32,080 --> 01:54:35,280
Speaker 1: about to pop, So get in the tree, good luck.

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01:54:35,760 --> 01:54:38,800
Speaker 1: Until next time, stay wired to Hunt.