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Speaker 1: This is a me eater podcast coming at you shirtless,

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Speaker 1: severely bog bitten and in my case, underwear. Listen, don't

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Speaker 1: eat podcast. You can't predict anything you want to talk

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Speaker 1: about bug bitten. I've referred, of course, when I say

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Speaker 1: you want to talk about referring to our brand, you

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Speaker 1: know we haven't addressed the brand speakiny new intro. Anyone

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Speaker 1: careous about that music in the brand speakinty new intro.

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Speaker 1: That's by a band. And you can see some good

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Speaker 1: hosting right now, because I'm gonna I'm gonna build, I'm

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Speaker 1: gonna make this work a minute. That that's that that

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Speaker 1: piece of music within that intro, and the tree has

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Speaker 1: fallen down here, tree falling. And and there's an intro song.

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Speaker 1: That's a band called Sheerwater. That's that song is from

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Speaker 1: an album jet Playing and Oxbow. I'm friends with that musician.

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Speaker 1: He's very undecided about hunting. I've taken him fishing, and um,

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Speaker 1: he enjoyed being out there, but he said, I just

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Speaker 1: don't view fishing things the way you do. But he's

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Speaker 1: a he's a wonderful musician. And the reason here, here's

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Speaker 1: where the good hosting comes in because for a long time.

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Speaker 1: That musician was based out of Austin. And we're in

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Speaker 1: Texas right now. See how seemless that was. We're in

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Speaker 1: Maverick County. Which is is it fair to say that

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Speaker 1: this is like, this is ground zero, this is like

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Speaker 1: the bass, this is the heart and soul of like

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Speaker 1: the whole Texas white Tail big Buck world. Is not

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Speaker 1: fair to say, yes, yeah, for a giant, for a

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Speaker 1: giant white Tails. That was the voice of Ben Benyon,

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Speaker 1: Benyon Benion. So it's the same sound as your first name. Yeah,

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Speaker 1: it sounds like he stutter a little bit, Ben Benyon. Yeah,

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Speaker 1: does the voice of Ben Benyon. We're gonna get to

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Speaker 1: him a minute. Also, here's uh Chris Gil Chris Um.

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Speaker 1: Chris already warned us he doesn't have much to say.

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Speaker 1: He's just sitting in and listening. Um and Joannice tell

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Speaker 1: us at this point the show. I normally plug Jannice's

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Speaker 1: teacher company, but I'm not anymore because he won't make

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Speaker 1: me my perch flies. Oh, I asked your honest, He's

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Speaker 1: gonna get him one another. I asked you honest, probably

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Speaker 1: about eighteen months eighteen months ago, and give a shot

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Speaker 1: show to make me a couple of perch flies. I'm

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Speaker 1: talking about flies used for yellow perch um. You take

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Speaker 1: a little bit of you take a hook, take a

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Speaker 1: little bit of bucktail, you take a little bit of thread.

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Speaker 1: I'd make it myself, but I gave my damn what's

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Speaker 1: the bobbing bobbing? Yeah, I gave my bob into a

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Speaker 1: buddy mine. And and uh, because I used to tie

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Speaker 1: a couple of flies now, and then I just got

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Speaker 1: enough things i'd like to do, and that got low

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Speaker 1: on the list of things I like to do, and

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Speaker 1: I just gave it all away. And then as yanned

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Speaker 1: to make me someone, he won't make them for me.

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Speaker 1: Can you explain to people why you won't make them

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Speaker 1: over eighteen months? There's no real reason. All my my

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Speaker 1: five times ships packed away. It must be pretty packed away.

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Speaker 1: But like when you asked me to reload its to MAMMO,

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Speaker 1: usually get to that pretty quickly because that bench is

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Speaker 1: operational right now. But the the tie in bench is

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Speaker 1: not man it's under a half inch of dust. That

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Speaker 1: dust is heavy, really. Also, John's in the process of

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Speaker 1: buying himself a new home. Yeah, maybe I'll set up

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Speaker 1: a bench when I get there. So Ben I can't

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Speaker 1: even get There's so many things I want to ask

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Speaker 1: you about, or have you talked about that you've already

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Speaker 1: told me about that I I can't think of where

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Speaker 1: to start. Give me a little give me the bend,

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Speaker 1: the bend bending bio. Uh well, uh I stow them

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Speaker 1: and you're up. Okay, I'm not doing a good job, Ben,

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Speaker 1: Is that? What? What are? What do you call what

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Speaker 1: you do? Land manager? I consider myself a wildlife biologist,

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Speaker 1: all right, bends a wildlife biology that's a good way

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Speaker 1: of putting it. Bends a wildlife biologist working in the

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Speaker 1: private sector, and you run the wildlife program on a

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Speaker 1: large ranch, large property in South Texas. Correct, Okay, Now

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Speaker 1: get into the whole where you came from, what, what

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Speaker 1: kind of education you sought out, and what your what

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Speaker 1: your dictate is? Your you know your mandate? Not dictate?

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Speaker 1: There reminds me an old joke, what your mandate is? Yeah?

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Speaker 1: Uh well, I started out kind of whenever I was

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Speaker 1: when I was younger. My uh well, my parents split

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Speaker 1: up in my uh my stepdad, my mom remarried, and

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Speaker 1: my stepdad ran a took care of a piece of

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Speaker 1: property not too far from here. No, it was. It was,

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Speaker 1: but it was right on the border in Maverick County.

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Speaker 1: Some of the big Bucks straight over into that county.

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Speaker 1: Pretty much. Yeah, it was one of the it was.

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Speaker 1: It was top top five counties for big Bucks. And

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Speaker 1: uh he took care of that place for I guess

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Speaker 1: my pretty much, Mike, from about ten years old on

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Speaker 1: and uh and I saw what was going on there

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Speaker 1: and I wanted to do it, and I was trying

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Speaker 1: to figure out how to go about it. And uh

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Speaker 1: so so basically what idea is is after high school,

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Speaker 1: I went to college to uh pursue a degree in

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Speaker 1: range and wildlife science at Texas A and M Kingsville,

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Speaker 1: which at the time was the number one UH college

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Speaker 1: in the nation for wildlife program and uh and it's

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Speaker 1: part of that system. But uh, like Texas A and

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Speaker 1: M College station, which is the what you see the

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Speaker 1: Aggies on TV. Uh, this is a what do you

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Speaker 1: call it, a like a branch of that satellite campus.

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Speaker 1: Satellite campus. Yeah, we had our own football team in

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Speaker 1: our own mascot and uh. But and we were way

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Speaker 1: or we were much higher on the on the as

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Speaker 1: far as ranked in a wildlife program than the main

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Speaker 1: campus because of the UH is mainly because of the

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Speaker 1: experience experience level that you could get wild in class

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Speaker 1: um firsthand experience, firsthand, and and every every day we

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Speaker 1: were every class, every every junior senior level class you know, plant, plant,

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Speaker 1: I D and those kind of classes were in the field,

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Speaker 1: and our exams were in the field. Our exams were verbal. Uh,

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Speaker 1: I mean walking through walking through brush, cactus, everything that

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Speaker 1: we've been walking through, uh this week. But so I

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Speaker 1: went there and uh while I was working on the

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Speaker 1: ranch and my stepdad took care of and I was

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Speaker 1: kind of, I guess you could say, just more of

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Speaker 1: a ranch hand than anything. Just did odds and ends,

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Speaker 1: fixing fences and everything. But I developed a passion for

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Speaker 1: for deer. Uh. I always love to hunt, and uh

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Speaker 1: but I really really wanted to figure out, you know,

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Speaker 1: what made dear big and why were they big in

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Speaker 1: this area? And so and kind of we're southwest Texas,

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Speaker 1: I guess you can say. And uh, so I started

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Speaker 1: kind of paying attention to everything while I was in

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Speaker 1: college and getting a degree. And were each each new

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Speaker 1: boat white tail deer in college yeah or yes? And no,

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Speaker 1: it was more uh they were they were giving us

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Speaker 1: the tools to to learn, and they didn't. They didn't

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Speaker 1: focus on anyone species. They didn't focus on quail or

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Speaker 1: white tails. They kind of they did a little, you know,

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Speaker 1: they touched on it. But everything that they taught us

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Speaker 1: you can apply to any species. And then, uh and

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Speaker 1: so what I did is I just I took all that,

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Speaker 1: all the everything I learned, and applied it to white

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Speaker 1: tails while we were going through the courses through college.

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Speaker 1: And uh so whenever I graduated, I graduated in a

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Speaker 1: two thousand and eight. I graduated high school and O

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Speaker 1: four college two thousand and eight in spring, and uh

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Speaker 1: it actually the owner of the property uh offered me

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Speaker 1: a job and uh which was kind of the place

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Speaker 1: you grew up on, the place I grew up on,

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Speaker 1: which is kind of the end all plan was my

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Speaker 1: stepdad was gonna retire and I was gonna take over

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Speaker 1: his his position. Well, I graduated in May. In in

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Speaker 1: April of two thousand and eight, my stepdad had an

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Speaker 1: accident and he, uh he fell out of a deer stand.

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Speaker 1: He fell fourteen feet to the ground on a rocky hill.

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Speaker 1: Uh So it's a hard, hard hill and he he

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Speaker 1: uh broke both of his risk compound fractures, broke almost

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Speaker 1: all of his ribs. UH lacerated a kidney, lungs filled

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Speaker 1: up with fluid, created an induced trauma heart attack. The

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Speaker 1: air life came to San Antonio. He was an ICU

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Speaker 1: for thirty days. This this happened on April fourteen. I

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Speaker 1: graduated May tenth, So I didn't walk the stage on

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Speaker 1: graduation because I didn't have any family that would be

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Speaker 1: there to watch me because they're all at the hospital

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Speaker 1: with him in in the ICU. So uh so what

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Speaker 1: I was doing while I was that last month in college,

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Speaker 1: as I was coming back to the ranch because I

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Speaker 1: knew every we had seven employees. I kept the ranch

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Speaker 1: running while he was in the hospital and just the

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Speaker 1: back of your the ranch. This is a cattle operation. Cattle.

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Speaker 1: It was a It's a cattle operation with a side

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Speaker 1: note of hunting um and the heavy emphasis on wildlife, right,

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Speaker 1: a heavy emphasis on wildlife. The family and the family

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Speaker 1: was the main people that hunted it. We did. We

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Speaker 1: It was not a commercial operation. It wasn't fenced. It

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Speaker 1: was it was just a fun place for the family

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Speaker 1: and friends and guests and UH and some business associates

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Speaker 1: at the owner and Uh. So basically what I was

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Speaker 1: kind of thrown head first when my stepdad was in

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Speaker 1: the hospital. I was. I graduated and took the job

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Speaker 1: and took over his position. So I I was never

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Speaker 1: I never, I never was. I was started from the

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Speaker 1: ground level one of our I was in college. As

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Speaker 1: soon as I graduated, I started. I went straight to

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Speaker 1: the top because I was forced into it more than anything.

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Speaker 1: And uh, and I raged a few things on the

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Speaker 1: wildlife side, and we were we were that ranch that

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Speaker 1: or that property was was under pretty intense management for

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Speaker 1: I don't know, fifteen years maybe eighteen years before before

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Speaker 1: I took over, and we had we had really nice

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Speaker 1: white tails and and the white tails were you know,

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Speaker 1: they were there was big, big antler deer everywhere, and uh,

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Speaker 1: but I I never really intended to make them bigger.

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Speaker 1: I was just trying to kind of fill in. And uh.

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Speaker 1: That was about the time that trail cameras started getting

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Speaker 1: real popular as far as infrared and uh, you know

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Speaker 1: started started getting uh, I guess user friendly and and

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Speaker 1: cheap enough, and so I started running trail cameras and

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Speaker 1: we started we started noticing what deer would do from uh,

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Speaker 1: from a year to year as far as antler development, UM,

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Speaker 1: you know movement, uh, rutting habits. Uh. You know, Forge

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Speaker 1: had it's betting, betting areas, everything, everything you could you

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Speaker 1: could figure out what the trail cams and so you

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Speaker 1: feel that that really uh do you feel that really

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Speaker 1: rewrote people's understandings. I think I think that trail cameras

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Speaker 1: that you know, probably the best thing that's happened to

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Speaker 1: hunting and to managing wildlife in my opinion, uh, in

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Speaker 1: in my lifetime. You know, a biologist in New York

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Speaker 1: just put out a book about the significance of what

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Speaker 1: they call camera trap to the field. He published sort

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Speaker 1: of what he thinks of as I think the three

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Speaker 1: or six hundred like very influential trail cam images of

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Speaker 1: camera trap images and talked about the implications that tool

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Speaker 1: had for understanding distribution and range of wildlife, travel patterns

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Speaker 1: of wildlife. UM. I wanted to continue that about is

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Speaker 1: that this thing a few years ago in North Carolina

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Speaker 1: and it was a deer like a wildlife expo. A

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Speaker 1: guy there was telling me the story about someone. Have

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Speaker 1: you talked about this on the podcast The Kentucky Tennessee Bucks.

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Speaker 1: Everything about this you've told me about it. I don't

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Speaker 1: know if we've mentioned on the podcast. All Right, So

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Speaker 1: Kentucky and Tennessee have different season structures hunting season structures,

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Speaker 1: and they obviously share pretty long border. So a guy

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Speaker 1: comes forth with some big buck that he claims they

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Speaker 1: have shot in one or the other. Let's just for

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Speaker 1: arguing for for discussion. Say let's say he comes forth

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Speaker 1: his big bucks as well, I shot at in Kentucky. Okay,

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Speaker 1: it was probably vice versa, because I think Tennessee has

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Speaker 1: the liberal So comes forward and says, I shot this

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Speaker 1: big giant buck of Tennessee. It winds up being like

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Speaker 1: some state record for the year buck. He gets a

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Speaker 1: bunch of publicity. The buck tours around at a couple

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Speaker 1: these shows I'm talking about, these these wild effexpos. Eventually

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Speaker 1: a guy from Kentucky sees the big famous Tennessee buck

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Speaker 1: and says, I know that buck. I'll show you a

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Speaker 1: trail camp picture that buck hundreds of miles away from

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Speaker 1: where this man claims that he shot it, and the

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Speaker 1: buck had such a distinctive rack they successfully prosecuted the

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Speaker 1: man and seized the head. Yeah, because of this, because

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Speaker 1: of this guy's trail camp pictures of where that buck

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Speaker 1: was on, what day it was there, and he had

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Speaker 1: just shot it oddyseason and Jamaica legal came back across

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Speaker 1: the border. There's trail camp story for you. Yeah. Yeah,

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Speaker 1: they used that one, Chris, You like that one, Chris

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Speaker 1: still not. Yeah, the wardens here he used a similar

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Speaker 1: deal where they like if if if a dear interest

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Speaker 1: comes about and uh, shot by a hunter and uh

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Speaker 1: it's poached. You know, the landowner can knows it's missing,

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Speaker 1: and it shows up somewhere, he sees a picture of

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Speaker 1: it somewhere and he says that, you know, that deer

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Speaker 1: came off of my property and he's surrounded by several

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Speaker 1: other private property, like he didn't travel a hundred miles

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Speaker 1: that day or whatever, right, and they prosecuted several people. Now, uh,

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Speaker 1: from this exact same situation. It's probably it wasn't, you know,

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Speaker 1: not nothing that high profile. But but yeah, the same deal.

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Speaker 1: So yeah, so those guy's got a book coming out

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Speaker 1: about just how much that changed our understanding of you know,

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Speaker 1: all different kinds of wild life. Yeah. Yeah, I saw

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Speaker 1: some I saw some trail cam images that came out

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Speaker 1: of Afghanistan one time where they it was some really

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Speaker 1: rare sheet. You can see it going through a pass.

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Speaker 1: And the next images are a couple of dudes with

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Speaker 1: uh with the you know, the Afghanistan and they were

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Speaker 1: also familiar with now the hats that you know from

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Speaker 1: the Afghan War. You see people wearing in long robes

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Speaker 1: and a couple of klisha coughs going through pass right

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Speaker 1: behind it, going chase it after. Yeah, sony out there,

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Speaker 1: you are also your manage in that place, and you

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Speaker 1: start using trail camps. Yeah, we started using trail cams,

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Speaker 1: and I started noticing, uh, noticing changes changes in antler

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Speaker 1: development that from year to year that uh, we're bizarre

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Speaker 1: to meet because these these jumps are these uh increases

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Speaker 1: in uh in antler size on deer that we thought

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Speaker 1: we we would recognize from year to year, from season

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Speaker 1: to season because their home ranges. Uh and tell me

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Speaker 1: if I'm getting off pointed point, but uh, the home

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Speaker 1: ranges are you know, on our mature bucks are about

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Speaker 1: four to eight thousand acres and uh so you always

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Speaker 1: on a piece of property you have, what do you

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Speaker 1: guys figure put that into square mile be like ten

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Speaker 1: to twelve I think tender twelve square miles at six

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Speaker 1: forties of square miles. Uh So, you know, a buck's

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Speaker 1: home ranges tended to tended to have square miles, and

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Speaker 1: of course you have tons of overlap. And uh our

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Speaker 1: our density was about a deer per acres a deer so,

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Speaker 1: and we had a one to one buck do ratio,

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Speaker 1: so we had a buck per fifty acres. Uh So,

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Speaker 1: square miles that would be uh with ten bucks per

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Speaker 1: square mile, so totally maybe square mile, yeah, fifteen fifteen

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Speaker 1: bucks first square mile maybe, um, you know, all different

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Speaker 1: age classes. But anyway, what I started noticing is these

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Speaker 1: bucks that we thought we knew well, let me let

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Speaker 1: me back up. We were shooting, we were harvesting. The

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Speaker 1: family was harvesting trophy bucks every year that we're exceptional.

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Speaker 1: But sometimes we did not know what that deer had been.

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Speaker 1: He just showed up and uh so, and we we

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Speaker 1: harvest them and we look at their teeth based off

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Speaker 1: of the all the studies that have been done on

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Speaker 1: age by tooth wear and replacement, which you know, some

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Speaker 1: people say it's it's you know, it's the only thing

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Speaker 1: we have to go off of, uh it is we

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Speaker 1: have there is by the teeth it's not very accurate,

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Speaker 1: but it's the only thing we have, uh, but that

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Speaker 1: the teeth would be sharp, so they in indicating that

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Speaker 1: they were a young, young buck. So what I started

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Speaker 1: doing is I started documenting these deer with the trail

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Speaker 1: cameras and uh to uh find out why you know,

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Speaker 1: we're shooting these deer that looked old, but they had

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Speaker 1: sharp teeth and we've never seen him before. Because let

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Speaker 1: me just feel in a little bit, what you're suggesting

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Speaker 1: is you guys felt that you could look at the

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Speaker 1: deer's antlers and it immediately recognized him again the next year,

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Speaker 1: because he'd just be a little bit bigger version, right,

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Speaker 1: But then all of a sudden, here's the deer who like,

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Speaker 1: where'd he come from? Because I didn't see a slightly

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Speaker 1: smaller version of him last year. That's exactly correct. That's

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Speaker 1: exactly correct. So, uh, what what I was I started

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Speaker 1: documenting deer based off of their locations and their home

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Speaker 1: ranges and would save pictures from a year to year

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Speaker 1: to see, uh see which ones look similar. And I

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Speaker 1: started noticing that there was there was bucks making huge,

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Speaker 1: huge jumps, and uh, I mean they would go from

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Speaker 1: a hundred and twenty inch deer to a hundred and

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Speaker 1: sixty or a hundred and seventy inch deer in one

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Speaker 1: one growing season. And usually that was, uh, you know

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Speaker 1: what we were guessing to be a three or four

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Speaker 1: year old dear to a four or five year old dear.

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Speaker 1: That that age group was usually the big jumps. So

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Speaker 1: we started doing is documenting those deer as far as

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Speaker 1: based off a trail cams and uh, I started doing that,

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Speaker 1: and we started letting deer go no matter how big

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Speaker 1: they were. They'd be a hundred and seventy inch deer

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Speaker 1: that we would typically shoot. We said, well we'll we'll

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Speaker 1: let him go and see what happens because of his age.

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Speaker 1: Because of his age, we wanted to see. We were

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Speaker 1: trying to figure out how when was the peak? You know,

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Speaker 1: that's what everybody in White till Into Street tries to

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Speaker 1: figure out, is, uh, what's the what's what's the peak age?

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Speaker 1: When do they peek out? And uh, and we think

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Speaker 1: in Texas down here, we think it's we think it's

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Speaker 1: a little older than everywhere else. But we're different, and uh,

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Speaker 1: white tails are really site specific animals. I mean it

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Speaker 1: it changes twenty miles, changes completely as far as dear

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Speaker 1: to dear. Uh So, anyway, what uh but what is

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Speaker 1: the age? Um? Well, what we found or what what

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Speaker 1: my personal research and what other research institutes are are finding.

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Speaker 1: It depends on the ranch, it depends on the property,

338
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Speaker 1: it depends on the location, and it depends on the deer.

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00:20:41,160 --> 00:20:45,119
Speaker 1: They're all individual. But in my opinion, our dear in

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Speaker 1: Maverick County and that county was, uh, we're we're maximizing

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Speaker 1: their antler potential at seven and eight years old, not

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Speaker 1: five and six like previously thought. Uh in those and

343
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Speaker 1: all of that was just to estimation before at five

344
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Speaker 1: and six, and some of those dear people were estimating

345
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Speaker 1: them and they're actually younger. Uh So at the trail cams,

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Speaker 1: we can get a better idea of their age based

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Speaker 1: off of he's not in you know, Okay, if we

348
00:21:15,200 --> 00:21:18,680
Speaker 1: have three years of pictures and he wasn't two years

349
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Speaker 1: old in the first picture, he's at least five or six,

350
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Speaker 1: Does that make sense? And uh So that's kind of

351
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Speaker 1: what we went off of, and we started letting these

352
00:21:27,720 --> 00:21:30,520
Speaker 1: deer grow to be seven and eight years old and

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00:21:30,600 --> 00:21:33,840
Speaker 1: nine years old before we harvest them. And we can

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Speaker 1: see these dear we're we're feeding and they're coming out

355
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Speaker 1: every day and they're not not every day, but I'm

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00:21:39,119 --> 00:21:41,760
Speaker 1: seeing them in the trail cams every day and they're

357
00:21:41,800 --> 00:21:44,520
Speaker 1: they're really they're still hard to hunt their nocturnal um

358
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Speaker 1: even though we're feeding. And uh so I just started,

359
00:21:48,240 --> 00:21:51,439
Speaker 1: we started, uh letting these deer grow to to a

360
00:21:51,440 --> 00:21:53,600
Speaker 1: lot older age class than anybody else was. And we

361
00:21:53,600 --> 00:21:56,560
Speaker 1: started noticing that, Hey, we just stepped up our game.

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Speaker 1: You know. We went from killing a a couple of

363
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Speaker 1: ones sixty class year and a one seventy here and there,

364
00:22:02,440 --> 00:22:05,800
Speaker 1: to killing one eighties every year with an occasional two

365
00:22:05,840 --> 00:22:10,640
Speaker 1: hundred in uh three or four year period and then

366
00:22:10,920 --> 00:22:14,080
Speaker 1: it's no year six. We were killing multiple one nineties

367
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Speaker 1: with a with a two hundred almost every year and

368
00:22:17,520 --> 00:22:21,440
Speaker 1: uh and this was solely due from knowing the individual

369
00:22:21,520 --> 00:22:25,040
Speaker 1: deer through trail camera and uh and that that you

370
00:22:25,080 --> 00:22:28,359
Speaker 1: can't you can't always tell antler's year to year. But

371
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Speaker 1: what we were doing is is we knew where the

372
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Speaker 1: deer was his home range. He did the same thing

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Speaker 1: each year. You know, in October he'd be here, in

374
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Speaker 1: November he'd be here. Then the next year, a deer

375
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Speaker 1: that looked similar to him, but bigger would do the

376
00:22:44,000 --> 00:22:46,480
Speaker 1: same thing, so we assumed it was the same deer.

377
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Speaker 1: We weren't always right or right, I say we. It

378
00:22:48,560 --> 00:22:51,720
Speaker 1: was me more than anything. I wasn't always right on that,

379
00:22:51,760 --> 00:22:54,439
Speaker 1: but most part we were. And we stepped up our

380
00:22:54,480 --> 00:22:57,960
Speaker 1: game big time as far as uh growing, growing big deer.

381
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Speaker 1: And uh so I us about years seven. Uh these

382
00:23:04,880 --> 00:23:07,800
Speaker 1: these current landowners that were on this property we're at

383
00:23:07,840 --> 00:23:11,119
Speaker 1: now in Maverick County, approached me through a mutual friend

384
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Speaker 1: and uh, I asked, I. I guess I met him

385
00:23:16,320 --> 00:23:18,960
Speaker 1: a year six, and they approached me to try to

386
00:23:19,000 --> 00:23:23,199
Speaker 1: find a a They just purchased this this property, and

387
00:23:23,200 --> 00:23:26,879
Speaker 1: they approached me to find a a ranch foreman and

388
00:23:26,960 --> 00:23:29,320
Speaker 1: wildlife bolog just to run this property for him. And

389
00:23:29,320 --> 00:23:32,359
Speaker 1: they wanted nothing else other than to grow giant white tails.

390
00:23:32,560 --> 00:23:34,560
Speaker 1: That's all they wanted to do, or let them grow

391
00:23:34,680 --> 00:23:38,280
Speaker 1: no cattle, no cattle and uh so, and they all

392
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Speaker 1: they asked me, is that would you be willing to

393
00:23:40,200 --> 00:23:42,479
Speaker 1: leave your current position? I said no, I grew up

394
00:23:42,520 --> 00:23:44,520
Speaker 1: here and I'm happy and I don't want to do it.

395
00:23:45,359 --> 00:23:49,160
Speaker 1: Well that went on, and I looked for a couple

396
00:23:49,160 --> 00:23:51,000
Speaker 1: of people for him, but I could never find anybody

397
00:23:51,000 --> 00:23:53,200
Speaker 1: that I thought I could recommend and put my name on.

398
00:23:53,640 --> 00:23:55,960
Speaker 1: About a year later, they made me an offer to

399
00:23:56,040 --> 00:23:58,879
Speaker 1: come over here that I couldn't turn down. So U

400
00:23:59,600 --> 00:24:04,679
Speaker 1: so I aim and UH started applying the same basic

401
00:24:04,760 --> 00:24:06,800
Speaker 1: knowledge that I was doing there with the trail cameras

402
00:24:07,000 --> 00:24:14,320
Speaker 1: and the inventory of the of the deer here and UH.

403
00:24:14,359 --> 00:24:16,639
Speaker 1: And it's a it's a five to six year deal

404
00:24:16,680 --> 00:24:20,399
Speaker 1: before you can really start seeing consistent results on growing

405
00:24:21,160 --> 00:24:25,080
Speaker 1: growing these big white tails. But your job, like you're

406
00:24:25,280 --> 00:24:29,520
Speaker 1: a salary a salary individual, and your job to take

407
00:24:30,200 --> 00:24:36,639
Speaker 1: a sizeable chunkle land here and in the end goal

408
00:24:36,800 --> 00:24:43,320
Speaker 1: that you're pursuing is to increase the number and size

409
00:24:43,320 --> 00:24:48,399
Speaker 1: of big giant white tail box exactly yea. Before on

410
00:24:48,440 --> 00:24:51,080
Speaker 1: the old property I had, I was doing that almost

411
00:24:51,119 --> 00:24:53,800
Speaker 1: as a side note because we had cattle and in

412
00:24:53,960 --> 00:24:58,439
Speaker 1: a little bit of agriculture crop and uh and the

413
00:24:58,680 --> 00:25:02,199
Speaker 1: hunting was a side note. And now you know, and

414
00:25:02,240 --> 00:25:03,840
Speaker 1: that's the part that I enjoyed the most. That's the

415
00:25:03,840 --> 00:25:05,560
Speaker 1: part that I developed a passion for it. And now

416
00:25:05,560 --> 00:25:08,840
Speaker 1: you just strictly wildlife, just strictly wildlife, and UH, and

417
00:25:09,000 --> 00:25:12,440
Speaker 1: we do we don't do. I mean that's what we're

418
00:25:12,560 --> 00:25:16,359
Speaker 1: what we're after is improving the wildlife. Let me ask

419
00:25:16,400 --> 00:25:19,840
Speaker 1: some base real basic stuff. What are and Yanni jump

420
00:25:19,880 --> 00:25:24,760
Speaker 1: in and whenever you need to. This place is not

421
00:25:24,840 --> 00:25:28,760
Speaker 1: a fence place? Correct? Are there fence places here? Like?

422
00:25:28,920 --> 00:25:31,399
Speaker 1: Why are some places in Texas? Wus he about like

423
00:25:31,720 --> 00:25:36,040
Speaker 1: defence properties? What do you gain and lose? Like? Why

424
00:25:36,040 --> 00:25:39,480
Speaker 1: did you why did you men not? Did you you

425
00:25:39,480 --> 00:25:41,439
Speaker 1: still getting that? Why did you not come in and

426
00:25:41,480 --> 00:25:43,359
Speaker 1: be like, first thing we're gonna do, boys, is build

427
00:25:43,359 --> 00:25:47,800
Speaker 1: a big damn fence. Yeah, because that's uh, defenses in

428
00:25:47,880 --> 00:25:53,600
Speaker 1: Texas are Man, it's a it's a touchy subject, just hard.

429
00:25:53,920 --> 00:25:55,480
Speaker 1: You don't even need to weigh in. Just tell me

430
00:25:55,560 --> 00:25:58,879
Speaker 1: like the thinking right, well, the main the main thinking

431
00:25:59,160 --> 00:26:04,520
Speaker 1: in uh, the reason fences were were originally you know,

432
00:26:05,000 --> 00:26:07,560
Speaker 1: set up for deer in Texas. And the year you

433
00:26:07,600 --> 00:26:09,240
Speaker 1: told us earlier in what year did you say they

434
00:26:09,400 --> 00:26:13,200
Speaker 1: became popular? I think the first one, first official one

435
00:26:13,359 --> 00:26:15,800
Speaker 1: was in the late sixties was when the first one

436
00:26:15,840 --> 00:26:18,240
Speaker 1: that was made with railroad ties and some sheep and

437
00:26:18,280 --> 00:26:21,320
Speaker 1: goat net fence and what kind of acreage? Uh? That one?

438
00:26:21,480 --> 00:26:24,960
Speaker 1: That one was eight thousand acres and so big we're

439
00:26:25,119 --> 00:26:29,359
Speaker 1: talking about. No, they started out as large properties, and

440
00:26:29,400 --> 00:26:31,479
Speaker 1: what they started out as is to keep their neighbors

441
00:26:31,560 --> 00:26:35,000
Speaker 1: from killing their deer or for harvesting their dear premature

442
00:26:35,000 --> 00:26:38,040
Speaker 1: because they're like, we're running a management program practiced in

443
00:26:38,080 --> 00:26:42,240
Speaker 1: some restraint, and then inevitably the big box that we're

444
00:26:42,280 --> 00:26:44,520
Speaker 1: producing by providing good habitat and all that are getting

445
00:26:44,560 --> 00:26:48,120
Speaker 1: shot by some holes around the next property. It's done

446
00:26:48,200 --> 00:26:50,600
Speaker 1: what he's done his whole life, and if there's nothing

447
00:26:50,640 --> 00:26:53,439
Speaker 1: wrong with it, he's just hunting um, but he's not

448
00:26:53,520 --> 00:26:56,800
Speaker 1: as intense. That's the way the fences started out, and

449
00:26:56,880 --> 00:27:00,159
Speaker 1: that was a great, great tool, but it was the

450
00:27:00,160 --> 00:27:03,960
Speaker 1: motivation that was a motivation. So what what happened was is,

451
00:27:04,480 --> 00:27:07,440
Speaker 1: in my opinion is uh, it's people just got greedy

452
00:27:07,800 --> 00:27:12,840
Speaker 1: and they started you know, fencing smaller properties in and

453
00:27:13,000 --> 00:27:15,880
Speaker 1: figuring out that they could have a quick fix. It's

454
00:27:15,920 --> 00:27:18,320
Speaker 1: just like, you know, that's just people. They want to

455
00:27:18,320 --> 00:27:24,040
Speaker 1: get it. As far as growing trophy white tails, they could.

456
00:27:24,119 --> 00:27:26,879
Speaker 1: They started they started realizing that you could take a

457
00:27:27,119 --> 00:27:31,480
Speaker 1: take a you know, that's the the pen industry or

458
00:27:31,520 --> 00:27:36,199
Speaker 1: the raising farming wildlife really started up. And then I

459
00:27:36,200 --> 00:27:39,280
Speaker 1: guess about the nineties, which is it took from the

460
00:27:39,280 --> 00:27:42,000
Speaker 1: first ivents in the sixties. There was almost nobody doing

461
00:27:42,000 --> 00:27:46,480
Speaker 1: it for that, you know, almost thirty years. It was.

462
00:27:46,520 --> 00:27:49,240
Speaker 1: That was that first place a private facility. Was it

463
00:27:49,359 --> 00:27:52,800
Speaker 1: like a hunt, like a like a outfit outfitting. It

464
00:27:52,880 --> 00:27:55,439
Speaker 1: was a private research it was it was a private

465
00:27:55,520 --> 00:27:58,119
Speaker 1: it was a private property in the university did it

466
00:27:58,119 --> 00:28:01,520
Speaker 1: as a research project to start and found out that

467
00:28:01,560 --> 00:28:04,320
Speaker 1: it worked, and that's when they started publishing their research

468
00:28:04,400 --> 00:28:09,000
Speaker 1: and that's kind of just escalated from there and uh so,

469
00:28:09,200 --> 00:28:12,399
Speaker 1: uh so, basically people just started they started fencing in

470
00:28:12,480 --> 00:28:15,119
Speaker 1: smaller and smaller properties, and all of a sudden, the

471
00:28:15,200 --> 00:28:19,720
Speaker 1: pen developed kind of almost accidentally, just fencing off small

472
00:28:19,760 --> 00:28:22,200
Speaker 1: pieces of property and seeing what they could they could

473
00:28:22,200 --> 00:28:27,360
Speaker 1: concentrate growing these you know, Frankenstein type deer, and that's

474
00:28:27,400 --> 00:28:29,800
Speaker 1: what it's evolved in. And that's what people see on

475
00:28:29,960 --> 00:28:31,800
Speaker 1: TV on the on the pen and stuff, with all

476
00:28:31,840 --> 00:28:34,680
Speaker 1: these freakishly big deer that are they can barely hold

477
00:28:34,760 --> 00:28:40,200
Speaker 1: up their head. Um. But in my opinion, I don't.

478
00:28:40,240 --> 00:28:43,280
Speaker 1: I mean, that's that's kind of where it started and

479
00:28:43,320 --> 00:28:45,880
Speaker 1: where we are now, and it puts a bad taste

480
00:28:45,880 --> 00:28:49,640
Speaker 1: in people's mouth for for the fences. Um, so it's

481
00:28:49,960 --> 00:28:52,479
Speaker 1: not is not having offense. Like you've worked at two

482
00:28:52,560 --> 00:28:56,160
Speaker 1: places that are not fenced. Are they not fenced for

483
00:28:56,280 --> 00:29:01,160
Speaker 1: aesthetic reasons? Are they not fenced for long term? They're

484
00:29:01,240 --> 00:29:04,000
Speaker 1: they're not fan Well the other one is it is?

485
00:29:04,160 --> 00:29:07,040
Speaker 1: It is. I guess you could say it's not completely fenced.

486
00:29:07,040 --> 00:29:11,840
Speaker 1: It is partially fenced on one side. But that's Uh.

487
00:29:12,080 --> 00:29:16,440
Speaker 1: That one was we we got along with with our

488
00:29:16,480 --> 00:29:19,760
Speaker 1: neighbors and they practiced the same management plans that we are,

489
00:29:19,800 --> 00:29:24,600
Speaker 1: management practices that we did. Uh. This place is uh,

490
00:29:24,640 --> 00:29:31,120
Speaker 1: the owners of this property are super anti uh penn dear,

491
00:29:31,960 --> 00:29:37,000
Speaker 1: super anti high fence. Um. They like Boone and Crockett

492
00:29:37,000 --> 00:29:39,520
Speaker 1: club and they they really want to be able to

493
00:29:39,640 --> 00:29:42,400
Speaker 1: enter dear that we harvest here in the in the

494
00:29:42,400 --> 00:29:46,720
Speaker 1: Boone and Crockett system, which means natural reproduction, which natural reproduction,

495
00:29:46,760 --> 00:29:51,960
Speaker 1: no human contact, no direct human contact. Uh. And that's

496
00:29:52,040 --> 00:29:55,840
Speaker 1: that's pretty much. Uh, that's that's the whole reason. In

497
00:29:55,920 --> 00:30:00,000
Speaker 1: Maverick County, I forgot what what magazine did this stuff

498
00:30:00,120 --> 00:30:02,840
Speaker 1: did the deal, but they rated the top fifty counties

499
00:30:02,840 --> 00:30:06,360
Speaker 1: in the nation for for white tailed entries since two

500
00:30:06,360 --> 00:30:08,840
Speaker 1: thousand four. I can't remember if it was it was

501
00:30:08,920 --> 00:30:12,400
Speaker 1: one of the you know, more common long term magazines,

502
00:30:12,480 --> 00:30:16,320
Speaker 1: but it was. They rated the top fifty counties in

503
00:30:16,320 --> 00:30:20,320
Speaker 1: the nation for for boot and Crockett white tailed entries

504
00:30:20,400 --> 00:30:25,120
Speaker 1: since two thousand four. Maverick County was number one typical

505
00:30:25,880 --> 00:30:30,280
Speaker 1: and number two non typical entries. Uh. And I believe

506
00:30:30,400 --> 00:30:33,760
Speaker 1: that was it was the only it was the only

507
00:30:33,840 --> 00:30:36,960
Speaker 1: Texas county in the top ten. Uh. It might have

508
00:30:36,960 --> 00:30:39,400
Speaker 1: been the only Texas It might I think it might

509
00:30:39,400 --> 00:30:42,479
Speaker 1: have been the only Texas county in the top fifty. Uh,

510
00:30:43,080 --> 00:30:46,520
Speaker 1: but we were. That's why, that's why they chose to

511
00:30:46,520 --> 00:30:49,800
Speaker 1: buy a piece of property in Maverick County and uh.

512
00:30:49,840 --> 00:30:51,240
Speaker 1: And they came to me and they said, can we

513
00:30:51,280 --> 00:30:54,920
Speaker 1: grow big deer without offense? And I said absolutely. All

514
00:30:55,000 --> 00:30:57,480
Speaker 1: you have to do is let them grow and uh.

515
00:30:57,560 --> 00:30:59,360
Speaker 1: But you have to get a property big enough where

516
00:30:59,360 --> 00:31:01,600
Speaker 1: your neighbors are gonna be shooting every single one. So

517
00:31:01,640 --> 00:31:05,720
Speaker 1: if you're on a smaller, smaller property, the deer during

518
00:31:05,720 --> 00:31:08,120
Speaker 1: the rut that you're gonna go across the fence, and

519
00:31:08,120 --> 00:31:11,400
Speaker 1: in anybody in the right mind, deer that looks old,

520
00:31:11,480 --> 00:31:14,200
Speaker 1: mature and has a big rag, they're gonna blast it

521
00:31:15,000 --> 00:31:17,560
Speaker 1: and uh but yeah, they're not gonna care if it's like,

522
00:31:18,920 --> 00:31:21,800
Speaker 1: did you know if you let it go two more years,

523
00:31:21,880 --> 00:31:23,960
Speaker 1: they're not probably I canna see it anyway, right right,

524
00:31:24,120 --> 00:31:26,720
Speaker 1: they're not. They don't. Yeah, they're there for that weekend

525
00:31:26,920 --> 00:31:28,920
Speaker 1: or that day to hunt and they see a big

526
00:31:28,960 --> 00:31:31,040
Speaker 1: deer and they're gonna shoot it. It's it's a completely

527
00:31:31,040 --> 00:31:35,480
Speaker 1: different dynamic than than most most uh but most people

528
00:31:35,480 --> 00:31:39,320
Speaker 1: can consider hunting. It's uh, we're not we're not faring

529
00:31:39,320 --> 00:31:43,040
Speaker 1: and farming them, but we're watching them grow. I guess,

530
00:31:43,600 --> 00:31:47,920
Speaker 1: um it's similar to some guys that have uh good

531
00:31:48,040 --> 00:31:52,200
Speaker 1: mule there in Elk Country out west, that name their

532
00:31:52,360 --> 00:31:55,320
Speaker 1: bulls so that way they can keep up with locating

533
00:31:55,360 --> 00:31:58,440
Speaker 1: them the following year. Um, you know, just you know,

534
00:31:58,520 --> 00:32:02,040
Speaker 1: on public ground even it's real similar to that. We're

535
00:32:02,080 --> 00:32:04,480
Speaker 1: just doing it in the private sector. So how many

536
00:32:04,600 --> 00:32:09,360
Speaker 1: how many bucks are you keeping an eye on? Um?

537
00:32:09,400 --> 00:32:11,800
Speaker 1: I think I have on my inventory list right now,

538
00:32:11,800 --> 00:32:15,160
Speaker 1: I might have three or four hundred. I guess do

539
00:32:15,280 --> 00:32:19,880
Speaker 1: you have photo documentation of how much time do you

540
00:32:19,920 --> 00:32:21,920
Speaker 1: spend besides the trail cameras? How much time do you

541
00:32:21,960 --> 00:32:27,560
Speaker 1: spend out why observing in photograph and deer, just to

542
00:32:27,560 --> 00:32:32,000
Speaker 1: get to know who's all out there. Uh see October

543
00:32:32,280 --> 00:32:37,800
Speaker 1: October one through February. Um, I'm in the in the field,

544
00:32:38,320 --> 00:32:41,000
Speaker 1: uh at least six days a week most of the time,

545
00:32:41,080 --> 00:32:44,959
Speaker 1: seven days a week for you know, morning and evening

546
00:32:45,360 --> 00:32:47,240
Speaker 1: to two or three hours in the morning to three

547
00:32:47,280 --> 00:32:50,440
Speaker 1: hours in the evening almost every day in a stand

548
00:32:50,640 --> 00:32:53,320
Speaker 1: observing deer in a stand observing dear with the with

549
00:32:53,400 --> 00:32:55,720
Speaker 1: the camera, I use a big lands out of the

550
00:32:55,800 --> 00:32:59,800
Speaker 1: stand to uh supplement the trail cameras. Um. And I'm

551
00:33:00,000 --> 00:33:03,440
Speaker 1: on and about thirty five to forty trail cameras from

552
00:33:03,480 --> 00:33:08,000
Speaker 1: August fifteenth to February or March, and uh pictures roughly

553
00:33:08,040 --> 00:33:11,680
Speaker 1: a week. And uh that's uh, that's my Monday Tuesday.

554
00:33:12,640 --> 00:33:15,880
Speaker 1: So and that's just to try to get to know

555
00:33:15,960 --> 00:33:19,720
Speaker 1: who's here. I'm just getting to know. That's all I'm doing.

556
00:33:20,080 --> 00:33:24,240
Speaker 1: And within that, how often do you how often does

557
00:33:24,240 --> 00:33:28,800
Speaker 1: the deer pop up? It depends on his personality. How

558
00:33:28,840 --> 00:33:30,800
Speaker 1: often does the deer pop up that you had no

559
00:33:30,880 --> 00:33:33,520
Speaker 1: idea was here even though you're doing all that time looking?

560
00:33:34,080 --> 00:33:39,440
Speaker 1: How much mystery is left the around the perimeters when

561
00:33:39,440 --> 00:33:42,320
Speaker 1: we get influx from the neighbors during December, during the rut,

562
00:33:42,840 --> 00:33:45,600
Speaker 1: there is uh I'll run into a new deer probably,

563
00:33:46,240 --> 00:33:49,360
Speaker 1: you know. Whenever I say new dear, everything that I'm

564
00:33:49,400 --> 00:33:52,680
Speaker 1: noticing is usually three years old and older because I

565
00:33:52,720 --> 00:33:55,160
Speaker 1: can't it's hard to distinguish the ones twos and three

566
00:33:55,240 --> 00:33:57,760
Speaker 1: year old year to year. But once they once they

567
00:33:57,840 --> 00:34:00,560
Speaker 1: hit three and four, they're easier to distinguish year to hear,

568
00:34:01,080 --> 00:34:04,600
Speaker 1: and you're not distinguishing them off the antlers. Well, it's helpful,

569
00:34:04,720 --> 00:34:07,400
Speaker 1: but other things tell me, like because you explain to

570
00:34:07,400 --> 00:34:10,000
Speaker 1: me some of the things you're actually looking for, which

571
00:34:10,040 --> 00:34:12,839
Speaker 1: allow you to tell it one dear from the other. Yeah. So,

572
00:34:13,000 --> 00:34:17,520
Speaker 1: so explaining the posture of the photographs too, because that's interesting, yeah,

573
00:34:17,680 --> 00:34:21,040
Speaker 1: um so. So my my field photos with my camera

574
00:34:21,080 --> 00:34:23,799
Speaker 1: from the stand, I try to get the I try

575
00:34:23,840 --> 00:34:28,960
Speaker 1: to get the bucks broadside looking looking in my direction

576
00:34:29,480 --> 00:34:33,440
Speaker 1: with their ears perked in their hawks offset And I

577
00:34:33,480 --> 00:34:37,800
Speaker 1: do that because you can tell age based off the hawks.

578
00:34:38,560 --> 00:34:41,080
Speaker 1: You can't tell an exact age, but it helps you

579
00:34:41,719 --> 00:34:45,200
Speaker 1: narrow down the age. And then the broadside, of course

580
00:34:45,280 --> 00:34:48,120
Speaker 1: lets you look at all the different traits such as

581
00:34:48,200 --> 00:34:54,440
Speaker 1: the chest, the brisket. You know the the uh swaying

582
00:34:54,480 --> 00:34:58,440
Speaker 1: belly or flat belly or flat back or swaying back. Um.

583
00:34:58,480 --> 00:35:01,080
Speaker 1: But what I do age she is all for age

584
00:35:01,080 --> 00:35:04,319
Speaker 1: purposes only. But usually if I've been watching them, I'm

585
00:35:04,320 --> 00:35:06,719
Speaker 1: not worried about aging them on those pictures. I'm worried

586
00:35:06,719 --> 00:35:09,920
Speaker 1: about and identifier what I call an identifier and uh,

587
00:35:09,960 --> 00:35:12,439
Speaker 1: what I what I consider an identify or something like

588
00:35:12,480 --> 00:35:16,200
Speaker 1: a split here, like a you know, I'm talking like

589
00:35:16,239 --> 00:35:19,040
Speaker 1: a quarter inch nick on the tip of the right here,

590
00:35:19,920 --> 00:35:23,600
Speaker 1: or you know, on the bottom side of the year

591
00:35:23,640 --> 00:35:26,080
Speaker 1: there's you know, a quarter of the way up there's

592
00:35:26,120 --> 00:35:30,000
Speaker 1: a there's a black spot. And they'll carry these characteristics

593
00:35:30,040 --> 00:35:34,080
Speaker 1: year to year. And uh, or a dark forehead or

594
00:35:34,400 --> 00:35:37,960
Speaker 1: or a double throat patch double white throat patch, or

595
00:35:38,000 --> 00:35:43,360
Speaker 1: a bobtail um or any kind of distinguishing scar or

596
00:35:44,560 --> 00:35:47,279
Speaker 1: you know, there's a there's a ton of them when

597
00:35:47,280 --> 00:35:49,680
Speaker 1: you start, when you start really studying and looking, there's

598
00:35:49,719 --> 00:35:51,960
Speaker 1: there's a ton of different characteristics that you can look

599
00:35:52,000 --> 00:35:55,239
Speaker 1: at that are not associated with antlers. Because antlers changed

600
00:35:55,280 --> 00:35:58,759
Speaker 1: so much, you never know you can usually recognize them

601
00:35:58,760 --> 00:36:01,840
Speaker 1: a year to year once they get older. But but

602
00:36:02,000 --> 00:36:05,920
Speaker 1: the ear splits and the tails and stuff like that,

603
00:36:05,920 --> 00:36:08,680
Speaker 1: that little stuff that you can pick up on and

604
00:36:08,800 --> 00:36:11,279
Speaker 1: uh and I can't remember at all. That's why we're

605
00:36:11,320 --> 00:36:16,440
Speaker 1: documented it with We're we documented with the or the

606
00:36:16,440 --> 00:36:19,719
Speaker 1: infield photos from the stand and that's why I try

607
00:36:19,760 --> 00:36:23,560
Speaker 1: to get them in that that posture, that position two. Uh.

608
00:36:23,680 --> 00:36:26,439
Speaker 1: That way, I may not know that deer this year

609
00:36:27,560 --> 00:36:31,000
Speaker 1: because I didn't notice something, but I take a picture

610
00:36:31,000 --> 00:36:33,040
Speaker 1: of a deer in that same area next year it

611
00:36:33,160 --> 00:36:36,120
Speaker 1: looks kind of similar, and I put the two two together.

612
00:36:36,520 --> 00:36:38,880
Speaker 1: Then the third year, I take another picture of that

613
00:36:38,920 --> 00:36:41,400
Speaker 1: same deer in that same deal. So then I create

614
00:36:41,440 --> 00:36:44,120
Speaker 1: a catalog of inventory of deer from a year to year,

615
00:36:44,120 --> 00:36:46,959
Speaker 1: and it helps me understand their age better and uh,

616
00:36:47,000 --> 00:36:50,920
Speaker 1: and I can let them. We can therefore decide if

617
00:36:50,920 --> 00:36:54,440
Speaker 1: we want to harvest them or not. And uh and

618
00:36:54,440 --> 00:36:57,239
Speaker 1: it and some people that you're making that decision, I'm

619
00:36:57,239 --> 00:36:59,919
Speaker 1: making that decision. Yeah, And uh. Some people think that's

620
00:37:00,560 --> 00:37:03,759
Speaker 1: you know, that's a little bit uh too far into it,

621
00:37:03,800 --> 00:37:06,359
Speaker 1: I guess, or thinking too much about it. And it's

622
00:37:06,400 --> 00:37:10,239
Speaker 1: taken some of the hunting part of way. But my

623
00:37:10,360 --> 00:37:13,880
Speaker 1: boss is don't know that I know that, dear, or

624
00:37:13,880 --> 00:37:16,000
Speaker 1: they know I know that dear, But they don't know that, dear.

625
00:37:16,480 --> 00:37:19,680
Speaker 1: They haven't never they've never seen him before. Uh so

626
00:37:19,719 --> 00:37:25,200
Speaker 1: it's still hunting to the right people. Um and uh

627
00:37:25,239 --> 00:37:28,800
Speaker 1: but there's several several of these bucks that I'm getting

628
00:37:28,840 --> 00:37:34,200
Speaker 1: pictures of. I'll I'll have thirty to thirty five hunts

629
00:37:34,520 --> 00:37:38,520
Speaker 1: looking for him and never see him. Meaning you'll you'll

630
00:37:38,560 --> 00:37:41,600
Speaker 1: identify a buck and you'll be like, if you're gonna

631
00:37:41,600 --> 00:37:43,279
Speaker 1: get him, this is the year to do it right.

632
00:37:43,480 --> 00:37:46,799
Speaker 1: But he's not going to uphill from here right and

633
00:37:46,840 --> 00:37:50,640
Speaker 1: then nor and he never turns up right right well

634
00:37:50,880 --> 00:37:53,279
Speaker 1: even to the point where what I what I'm what

635
00:37:53,360 --> 00:37:57,600
Speaker 1: I meant by that was where my statement was, if

636
00:37:57,640 --> 00:38:00,400
Speaker 1: I have a deer on trail camera, does drue cameras

637
00:38:00,400 --> 00:38:02,160
Speaker 1: just they just give me something to go look at

638
00:38:02,400 --> 00:38:04,840
Speaker 1: more than anything. You can tell a lot, but you

639
00:38:04,880 --> 00:38:07,360
Speaker 1: can't tell everything. So what I'll do is I'll use

640
00:38:07,400 --> 00:38:12,280
Speaker 1: the choke cameras to find a find a deer of interest,

641
00:38:12,800 --> 00:38:16,760
Speaker 1: you know, say he's a one d O. I yeah, yeah,

642
00:38:16,840 --> 00:38:19,480
Speaker 1: And uh so I'll find a one fifty class whatever

643
00:38:19,760 --> 00:38:22,560
Speaker 1: something or other that I have I don't know. I'll

644
00:38:22,600 --> 00:38:24,319
Speaker 1: go sit on that deer with my big lens to

645
00:38:24,320 --> 00:38:27,239
Speaker 1: find an identifier, you know, to find a split here

646
00:38:27,239 --> 00:38:30,319
Speaker 1: because you can't always notice those little uh spot on

647
00:38:30,360 --> 00:38:33,960
Speaker 1: the ears, uh uh different characteristic on the body. You

648
00:38:33,960 --> 00:38:36,600
Speaker 1: can't always notice those in troick camps the first time

649
00:38:36,640 --> 00:38:39,560
Speaker 1: you see one, So you have to see him in person,

650
00:38:39,560 --> 00:38:41,279
Speaker 1: and then I get a What I'll do is I'll

651
00:38:41,280 --> 00:38:43,640
Speaker 1: get him, get a picture of them broadside printed out

652
00:38:43,680 --> 00:38:45,360
Speaker 1: in an eight by ten, put it in the folder,

653
00:38:46,120 --> 00:38:49,200
Speaker 1: and then next year, uh do the same thing. Then

654
00:38:49,200 --> 00:38:51,040
Speaker 1: I can put those pictures right next to each other

655
00:38:51,080 --> 00:38:56,920
Speaker 1: and see who's who. Uh. But but usually when we

656
00:38:57,000 --> 00:39:00,480
Speaker 1: do green light a buck a trophy trophy buck to shoot.

657
00:39:01,440 --> 00:39:06,160
Speaker 1: We shot one two years ago. That was I think

658
00:39:06,200 --> 00:39:09,200
Speaker 1: it took him thirty or thirty five sits before he

659
00:39:09,280 --> 00:39:14,879
Speaker 1: killed him because what what was happening. It's nocturnal. They're

660
00:39:14,880 --> 00:39:17,640
Speaker 1: just nocturnal and will not show up in the daylight.

661
00:39:17,760 --> 00:39:19,920
Speaker 1: Even with all the feed in the world that you

662
00:39:19,960 --> 00:39:23,440
Speaker 1: want to put out, they get. Uh. We're we we

663
00:39:23,520 --> 00:39:28,520
Speaker 1: practice uh. We we do a lot of selective harvest

664
00:39:28,560 --> 00:39:32,919
Speaker 1: for population control. And what we're trying to do is

665
00:39:32,920 --> 00:39:35,480
Speaker 1: is we reduce the stress by reducing the population and

666
00:39:36,239 --> 00:39:39,399
Speaker 1: uh creating more feed. But that, and you know that's

667
00:39:39,400 --> 00:39:40,600
Speaker 1: one of the things I want to ask you about

668
00:39:41,120 --> 00:39:43,319
Speaker 1: when we back up minute, don't ask about an other thing,

669
00:39:43,480 --> 00:39:47,000
Speaker 1: you guys like couple bad dates, you have anything. Nothing,

670
00:39:47,320 --> 00:39:52,000
Speaker 1: It's all coming out nothing your your little brain. Nothing

671
00:39:52,120 --> 00:39:54,799
Speaker 1: is going like, Oh I wish I knew a little

672
00:39:54,840 --> 00:39:57,560
Speaker 1: more about that. It's all coming out. You're asking the

673
00:39:57,600 --> 00:40:00,319
Speaker 1: good questions, man, at least like You'll have something on

674
00:40:00,320 --> 00:40:01,759
Speaker 1: the tip of your tongue and then I'll say it

675
00:40:02,880 --> 00:40:05,200
Speaker 1: well or ill or you just keep talking and then

676
00:40:05,239 --> 00:40:09,440
Speaker 1: I'll think about something else, and then more it keeps

677
00:40:09,480 --> 00:40:12,000
Speaker 1: drifting away. I started to think that sound's wrong with

678
00:40:12,040 --> 00:40:17,560
Speaker 1: you guys. No, man, I'm just fascinated learning about white Tail. Um, okay,

679
00:40:19,320 --> 00:40:22,040
Speaker 1: I'm gonna jump you around a little bit. I can't

680
00:40:22,080 --> 00:40:23,920
Speaker 1: remember I interrupt you before you got into something I

681
00:40:23,960 --> 00:40:25,239
Speaker 1: wanted to ask you about. What were you just gonna

682
00:40:25,239 --> 00:40:26,960
Speaker 1: get into. I don't know. I'm not the one paying

683
00:40:27,000 --> 00:40:30,200
Speaker 1: attention about bringing the population. Oh yeah, about the importance

684
00:40:30,200 --> 00:40:34,799
Speaker 1: and not having too many deer. Right. But as a kid,

685
00:40:34,960 --> 00:40:37,400
Speaker 1: and Yanny can back me up on this, as a

686
00:40:37,440 --> 00:40:39,560
Speaker 1: kid growing up in white Tail Country in Michigan, and

687
00:40:39,560 --> 00:40:41,440
Speaker 1: I was like our big game in our only big

688
00:40:41,440 --> 00:40:47,440
Speaker 1: game animals, white tails. It was like you aged dear

689
00:40:48,280 --> 00:40:52,040
Speaker 1: at least in your head, you age dear by what

690
00:40:52,080 --> 00:40:57,400
Speaker 1: their antlers looked like. So everyone knew that a spiker

691
00:40:57,440 --> 00:41:01,200
Speaker 1: fork was a year and a half old if he

692
00:41:01,400 --> 00:41:05,560
Speaker 1: was a Michigan six or Michigan eight so or Western three.

693
00:41:05,920 --> 00:41:08,040
Speaker 1: Let's just make a deal with you, guys, use Eastern

694
00:41:08,160 --> 00:41:10,560
Speaker 1: count Yeah five on one side five near a studies

695
00:41:10,600 --> 00:41:15,000
Speaker 1: the ten point right counts. We started calling the Michigan

696
00:41:15,000 --> 00:41:17,320
Speaker 1: six because everybody in the damn country is differently accountable

697
00:41:17,719 --> 00:41:23,000
Speaker 1: only speaking Eastern. So a six or an eight was

698
00:41:23,080 --> 00:41:28,000
Speaker 1: two yeah, right, And that was like just accepted wisdom.

699
00:41:28,040 --> 00:41:32,839
Speaker 1: The other piece of accepted wisdom was a spike wasn't

700
00:41:32,840 --> 00:41:39,160
Speaker 1: going to become big because he's already small. Yeah, now

701
00:41:39,480 --> 00:41:44,839
Speaker 1: speak to that stuff, the like what what can you

702
00:41:44,960 --> 00:41:49,600
Speaker 1: actually tell with age by looking at the antlers on

703
00:41:49,719 --> 00:41:53,040
Speaker 1: the deer? Uh? That's that's a tough one, because I mean,

704
00:41:53,080 --> 00:41:57,920
Speaker 1: I've seen, I've seen antlers are I guess in a

705
00:41:58,000 --> 00:42:02,440
Speaker 1: way they're they're an indication of age bait. If you

706
00:42:02,480 --> 00:42:05,440
Speaker 1: look at the if you look at mass mass and

707
00:42:05,640 --> 00:42:09,359
Speaker 1: uh and uh. Just but as far as a number

708
00:42:09,400 --> 00:42:11,920
Speaker 1: of points and spread. None of that seems to matter

709
00:42:11,960 --> 00:42:14,880
Speaker 1: on age. It's because you were just showing me an

710
00:42:15,040 --> 00:42:18,040
Speaker 1: eight point it was a year and a half old. Yeah, yeah,

711
00:42:18,080 --> 00:42:19,960
Speaker 1: we had We had an eleven point this year that

712
00:42:20,080 --> 00:42:22,360
Speaker 1: was a year and a half old. I had. I

713
00:42:22,400 --> 00:42:25,320
Speaker 1: had a six pointer with a drop time. It was

714
00:42:25,320 --> 00:42:27,040
Speaker 1: a year and a half old this year. So his

715
00:42:27,160 --> 00:42:30,560
Speaker 1: first rack, first track, he had a drop time. And

716
00:42:30,600 --> 00:42:33,000
Speaker 1: then we have we have, you know, seven and eight

717
00:42:33,040 --> 00:42:37,719
Speaker 1: year old deer that have eight points barely do you

718
00:42:37,800 --> 00:42:41,279
Speaker 1: ever get do you ever get a dear older than

719
00:42:41,640 --> 00:42:46,359
Speaker 1: than one who's a forky? Yeah? Yeah, I shot one.

720
00:42:46,680 --> 00:42:49,000
Speaker 1: I shot one a few years ago. That was he

721
00:42:49,080 --> 00:42:52,640
Speaker 1: was a two bye two four point uh and uh

722
00:42:52,680 --> 00:42:56,000
Speaker 1: he was. He was five and a half by his toothwear,

723
00:42:56,600 --> 00:43:00,160
Speaker 1: which he could have been older. So he's never just

724
00:43:00,800 --> 00:43:03,080
Speaker 1: yeah he was a heavy two points. Oh he was

725
00:43:03,120 --> 00:43:06,920
Speaker 1: a big too. He looked at him, knew he was.

726
00:43:07,080 --> 00:43:09,960
Speaker 1: Oh yeah he was. He was. He was probably eighteen

727
00:43:09,960 --> 00:43:13,799
Speaker 1: inches wide inside with with like eight or nine inch

728
00:43:13,880 --> 00:43:16,640
Speaker 1: g twos. But that's all he had. Yeah, he had

729
00:43:16,719 --> 00:43:18,560
Speaker 1: nothing else. He was just too big forks like it

730
00:43:18,640 --> 00:43:21,719
Speaker 1: look like a mule mule here. Yeah, Now I'm gonna

731
00:43:21,719 --> 00:43:24,200
Speaker 1: do something else. I'm gonna distracting another way, just to

732
00:43:24,239 --> 00:43:26,560
Speaker 1: throw this out, just just want to throw this out.

733
00:43:28,200 --> 00:43:32,720
Speaker 1: Tell me the number of wild pigs that you have

734
00:43:32,920 --> 00:43:37,359
Speaker 1: handled in by trapping and whatnot. How many wild pigs

735
00:43:37,360 --> 00:43:41,200
Speaker 1: have you handled here in South Texas As this morning,

736
00:43:41,480 --> 00:43:44,799
Speaker 1: four thousand, seven ninety five wild pigs have passed through

737
00:43:44,800 --> 00:43:51,080
Speaker 1: your hands since I started counting. Tell me how how

738
00:43:51,080 --> 00:43:59,400
Speaker 1: old areen you weld it up your first pig trap? Alight? So, dear, um,

739
00:43:59,560 --> 00:44:02,440
Speaker 1: that's just a old teaser for later. So dear now

740
00:44:02,560 --> 00:44:04,719
Speaker 1: you're saying, and you told you're talking about this too,

741
00:44:06,040 --> 00:44:09,879
Speaker 1: that too many like if you have too many deer

742
00:44:09,960 --> 00:44:16,440
Speaker 1: running around, they're not gonna get as big. It Uh, okay,

743
00:44:16,560 --> 00:44:18,520
Speaker 1: get into that a little bit, okay, It it all

744
00:44:18,719 --> 00:44:21,719
Speaker 1: uh yeah that the it's all boils down to population

745
00:44:21,800 --> 00:44:25,480
Speaker 1: dynamics as far as uh you know, mother Nature's way

746
00:44:25,560 --> 00:44:28,000
Speaker 1: is is grow, grow, grow, grow, and then have a

747
00:44:28,000 --> 00:44:30,879
Speaker 1: big die off and then grow grow, grow and once

748
00:44:30,920 --> 00:44:35,279
Speaker 1: it once it surpasses carrying capacity, once the land surpasses

749
00:44:35,280 --> 00:44:38,840
Speaker 1: the carrying capacity, yeah, it has a die off, and

750
00:44:38,920 --> 00:44:41,920
Speaker 1: it it's uh to basically have these big spikes on

751
00:44:41,960 --> 00:44:44,680
Speaker 1: the graph up and down up and don't some species

752
00:44:44,719 --> 00:44:48,719
Speaker 1: just hit carrying capacity and then level off. Um, I'm

753
00:44:48,760 --> 00:44:51,319
Speaker 1: sure they do. The ones that I'm studying, don't, or

754
00:44:51,440 --> 00:44:56,640
Speaker 1: that I'm dealing with, um, quail and deer for instance. Um,

755
00:44:56,800 --> 00:45:01,000
Speaker 1: they hit carrying capacity and they keep reproduce, and then

756
00:45:01,200 --> 00:45:04,080
Speaker 1: all of a sudden there's you know, too many less

757
00:45:04,080 --> 00:45:07,319
Speaker 1: and less food, more competition, and they start getting the

758
00:45:07,440 --> 00:45:09,800
Speaker 1: first species people look at when they're kind of talking

759
00:45:09,840 --> 00:45:15,279
Speaker 1: about that that phenomenon is people like to look at

760
00:45:15,320 --> 00:45:19,640
Speaker 1: snowshoe hairs. Yeah. Yeah, it's where it's so cyclical that

761
00:45:20,680 --> 00:45:23,839
Speaker 1: it falls into line. It's seven years. I mean it's

762
00:45:23,880 --> 00:45:27,120
Speaker 1: like dialed in right, and then you look at They

763
00:45:27,120 --> 00:45:30,000
Speaker 1: did this study where they looked at snowshoe hair patterns

764
00:45:30,120 --> 00:45:32,719
Speaker 1: and they went back through all the Hudson Bay Company

765
00:45:32,880 --> 00:45:39,000
Speaker 1: records on links, how many hides, links, hides We're getting

766
00:45:39,040 --> 00:45:44,840
Speaker 1: handled and it was offset but links who their primary

767
00:45:44,880 --> 00:45:48,600
Speaker 1: pray species and snowshoe rabbits. They looked at Hudson Bay

768
00:45:48,640 --> 00:45:52,319
Speaker 1: Company links hide receipts and realize that links high links

769
00:45:52,480 --> 00:45:55,480
Speaker 1: seemed to bounce along in a seven year span off

770
00:45:55,520 --> 00:45:59,279
Speaker 1: set from the snowshoe hair seven year span. Yeah, like

771
00:45:59,400 --> 00:46:03,880
Speaker 1: just respond under that direct response. Yeah, yeah, that makes sense.

772
00:46:03,920 --> 00:46:07,680
Speaker 1: But and see white tails, white tails do it. It's

773
00:46:07,719 --> 00:46:11,160
Speaker 1: more gradual. And now that now that people there's there's

774
00:46:11,200 --> 00:46:14,719
Speaker 1: such a high profile animal and game animal that people

775
00:46:14,719 --> 00:46:17,919
Speaker 1: are never gonna let them die off. But they will

776
00:46:18,000 --> 00:46:21,319
Speaker 1: let him overpopulate. And the first thing, the first thing

777
00:46:21,360 --> 00:46:24,480
Speaker 1: that they but they won't ever let them reach that

778
00:46:24,480 --> 00:46:27,879
Speaker 1: that uh point where they just they start dying off.

779
00:46:28,080 --> 00:46:30,719
Speaker 1: But what happens is is is people get greedy and

780
00:46:30,719 --> 00:46:35,960
Speaker 1: they want to let as many survive as possible, thinking

781
00:46:36,000 --> 00:46:41,000
Speaker 1: that even even the biggest possible, thinking that someone's gonna

782
00:46:41,040 --> 00:46:44,520
Speaker 1: turn off who's real big deer they think they think

783
00:46:44,560 --> 00:46:48,839
Speaker 1: that giant deer and anomenaly anomaly and uh and and

784
00:46:48,840 --> 00:46:54,640
Speaker 1: they're not there. They're a low percentage. They're not they

785
00:46:54,719 --> 00:46:58,239
Speaker 1: I mean they're there's there's a certain percentage of white

786
00:46:58,239 --> 00:47:01,080
Speaker 1: tails that are gonna be big. And it's a it's

787
00:47:01,160 --> 00:47:04,320
Speaker 1: just a straight up bell curve and the middle range

788
00:47:04,440 --> 00:47:09,839
Speaker 1: down here is about a hundred and thirty and uh so, so,

789
00:47:10,080 --> 00:47:12,800
Speaker 1: uh well, we do or what I do to lower

790
00:47:12,840 --> 00:47:15,799
Speaker 1: the population. We we we call animals to lower the

791
00:47:15,840 --> 00:47:21,239
Speaker 1: population to uh reduce stress. And white tails in my

792
00:47:21,280 --> 00:47:26,919
Speaker 1: opinion are completely stress oriented. Rather, it's food, water, bedding cover.

793
00:47:27,280 --> 00:47:30,560
Speaker 1: Everything is stress related. So if you have too many,

794
00:47:31,239 --> 00:47:33,960
Speaker 1: it may not look like the habitat is suffering, but

795
00:47:34,200 --> 00:47:37,799
Speaker 1: they're competing directly with food and uh, same thing with

796
00:47:37,840 --> 00:47:41,160
Speaker 1: bedding cover. And uh so the first thing to go

797
00:47:41,440 --> 00:47:43,400
Speaker 1: on a white tails when it when it's trying to

798
00:47:43,440 --> 00:47:47,920
Speaker 1: survive is antler growth. It's a luxury. It's yeah, pure

799
00:47:48,080 --> 00:47:52,680
Speaker 1: pure luxury luxury. And uh so what uh and we

800
00:47:52,680 --> 00:47:56,200
Speaker 1: we do feed here, so that's that's uh, we're trying

801
00:47:56,200 --> 00:48:01,040
Speaker 1: to certain people in Texas feed to off set they

802
00:48:01,040 --> 00:48:07,160
Speaker 1: think they can offset that stress level of competition in uh.

803
00:48:07,200 --> 00:48:11,959
Speaker 1: In natural habitat, we feed as a supplement to help

804
00:48:12,000 --> 00:48:15,399
Speaker 1: them out through drought conditions. So you don't have those

805
00:48:15,400 --> 00:48:17,600
Speaker 1: spikes in the in the in the graph like we

806
00:48:17,600 --> 00:48:19,759
Speaker 1: were talking about. And we try to level it out

807
00:48:19,840 --> 00:48:22,400
Speaker 1: as much as we can too, because that reduces the

808
00:48:22,400 --> 00:48:28,319
Speaker 1: stress anything any the I guess, the the spike up

809
00:48:28,440 --> 00:48:31,840
Speaker 1: or the spike down or all creating stress on the

810
00:48:32,480 --> 00:48:41,359
Speaker 1: on individual animals. So cooling is the practice of going

811
00:48:41,400 --> 00:48:48,360
Speaker 1: out and uh killing deer. Yeah, both the reduced numbers

812
00:48:48,400 --> 00:48:50,560
Speaker 1: and to make some kind of selection about who's gonna

813
00:48:50,560 --> 00:48:52,840
Speaker 1: be on the property and who's not right? Correct? Correct,

814
00:48:53,160 --> 00:48:56,399
Speaker 1: and just so explain this because Texas runs wild, it's

815
00:48:56,440 --> 00:49:01,080
Speaker 1: so differently in this place in the US. The state

816
00:49:01,200 --> 00:49:03,040
Speaker 1: will come out to a big chunk of ground in

817
00:49:03,120 --> 00:49:06,400
Speaker 1: Texas and make an assessment about how many deer you

818
00:49:06,440 --> 00:49:09,000
Speaker 1: guys are supposed to kill because the state's trying to

819
00:49:09,080 --> 00:49:11,720
Speaker 1: encourage you to not let them get overrun. The state

820
00:49:12,080 --> 00:49:17,640
Speaker 1: is worried about habitat. They don't want they want the

821
00:49:17,680 --> 00:49:20,879
Speaker 1: habitat to be healthy. They don't care about or they

822
00:49:20,920 --> 00:49:24,799
Speaker 1: do they do care about, uh, the animals. But there

823
00:49:24,840 --> 00:49:27,799
Speaker 1: they realize that if you have great habitat, you're gonna

824
00:49:27,800 --> 00:49:30,239
Speaker 1: have healthy animals. And that's their number one folks. So

825
00:49:30,239 --> 00:49:33,480
Speaker 1: their number one focus is that you're not gonna allow

826
00:49:33,600 --> 00:49:38,120
Speaker 1: your habitat to become degraded, to have long term degradation

827
00:49:38,239 --> 00:49:40,200
Speaker 1: in the name of short term bunch of deer running

828
00:49:40,160 --> 00:49:44,319
Speaker 1: around or cattle or cattle. But in those but in

829
00:49:44,400 --> 00:49:48,359
Speaker 1: those are on private land. See this it's mostly privately land.

830
00:49:48,400 --> 00:49:55,160
Speaker 1: And that's all uh the state. Those are recommendations by

831
00:49:55,160 --> 00:49:59,480
Speaker 1: the state. The state's not forcing you, you know, uh

832
00:49:59,760 --> 00:50:01,839
Speaker 1: in but the people that are want to be good

833
00:50:01,880 --> 00:50:05,319
Speaker 1: land stewards and want to grow better deer and have

834
00:50:05,960 --> 00:50:10,640
Speaker 1: better long term wildlife programs and cattle grazing programs. Requests

835
00:50:10,680 --> 00:50:13,960
Speaker 1: the state's assistants to come out and tell them what

836
00:50:14,000 --> 00:50:16,320
Speaker 1: they should or shouldn't do. And they'll come out and say,

837
00:50:17,719 --> 00:50:20,000
Speaker 1: like just using it doesn't have to be specific to

838
00:50:20,040 --> 00:50:21,920
Speaker 1: this place. But they'll come out to a property like this,

839
00:50:22,680 --> 00:50:25,360
Speaker 1: they'll come out and say, you boys would be wise

840
00:50:25,920 --> 00:50:31,840
Speaker 1: to kill four deer this year. Here are your tags.

841
00:50:31,840 --> 00:50:35,399
Speaker 1: Here are your certificates for those four deer. Yeah, and uh,

842
00:50:35,440 --> 00:50:38,680
Speaker 1: they they based that on several different Uh. They do

843
00:50:38,960 --> 00:50:41,720
Speaker 1: browse surveys, so they look at the whatever the deer eating,

844
00:50:42,120 --> 00:50:44,680
Speaker 1: and if if the plants, if the plants look stressed out,

845
00:50:44,840 --> 00:50:48,239
Speaker 1: then they'll then they'll, uh, I guess uh give you

846
00:50:48,320 --> 00:50:51,920
Speaker 1: more more tags or less tags versus based off of

847
00:50:51,960 --> 00:50:55,239
Speaker 1: what they notice on the plants. Um. They do surveys,

848
00:50:55,440 --> 00:51:00,760
Speaker 1: population surveys to see what that particular piece of ground is,

849
00:51:00,760 --> 00:51:03,719
Speaker 1: is uh capable of handling? And the best way to

850
00:51:03,760 --> 00:51:06,359
Speaker 1: count dear here is helicopter, right, helicopter here. You can

851
00:51:06,440 --> 00:51:09,680
Speaker 1: use spotlights too, but it's too thick here, so we

852
00:51:09,800 --> 00:51:12,839
Speaker 1: use predominantly what I do is I try to use

853
00:51:13,000 --> 00:51:17,560
Speaker 1: a helicopter survey in tandem with the cameras, and I

854
00:51:17,600 --> 00:51:19,960
Speaker 1: try to get an individual buck count on the cameras

855
00:51:20,440 --> 00:51:23,160
Speaker 1: and then get your buck Do ray show from the

856
00:51:23,200 --> 00:51:27,600
Speaker 1: helicopter and your faone survival from your helicopter. So you

857
00:51:27,600 --> 00:51:30,120
Speaker 1: take your individual buck count from the from the camera

858
00:51:30,560 --> 00:51:33,160
Speaker 1: and apply that to the buck Do ray show, and

859
00:51:33,160 --> 00:51:34,560
Speaker 1: then you get your number of dose and then you

860
00:51:34,680 --> 00:51:37,239
Speaker 1: foll your phone crop to that and get your total number.

861
00:51:37,239 --> 00:51:39,080
Speaker 1: A dear, and when they come out and give you

862
00:51:39,719 --> 00:51:41,600
Speaker 1: there's three hundred, like a decent number for a big

863
00:51:41,640 --> 00:51:45,840
Speaker 1: chunkle land. Three hundred? Are you raising your hand? Holy

864
00:51:45,880 --> 00:51:49,640
Speaker 1: can put as a wolf up? Woke up and has

865
00:51:49,640 --> 00:51:52,840
Speaker 1: a thought. I have a question too? After thank god,

866
00:51:54,680 --> 00:51:56,720
Speaker 1: you want to interrupt men with like a dumb question.

867
00:51:56,760 --> 00:51:58,719
Speaker 1: You guys got such good questions. I want to be like, hey,

868
00:51:58,760 --> 00:52:00,360
Speaker 1: what is this mean? You know what? Chris being so

869
00:52:00,480 --> 00:52:02,279
Speaker 1: polite right now, I'll tell you what the deal is.

870
00:52:02,320 --> 00:52:04,839
Speaker 1: There's so much talking that goes on that it's hard

871
00:52:04,880 --> 00:52:09,880
Speaker 1: to even slip in the conversation. And I'll break in

872
00:52:09,960 --> 00:52:16,400
Speaker 1: right now. Okay, you start talking, say something, hey, hey,

873
00:52:16,520 --> 00:52:19,040
Speaker 1: uh so here's what I'm wondering, just like it's just

874
00:52:19,080 --> 00:52:21,640
Speaker 1: like as simple as that. Tell me about how when

875
00:52:21,680 --> 00:52:25,160
Speaker 1: you do a helicopter survey kind of like give me

876
00:52:25,200 --> 00:52:27,640
Speaker 1: the breakdown of how that happens, like the main steps

877
00:52:27,680 --> 00:52:29,600
Speaker 1: like skip the you know, before I got in, I

878
00:52:29,640 --> 00:52:31,799
Speaker 1: took a pee. But once you get in there, you

879
00:52:31,880 --> 00:52:34,480
Speaker 1: take off deer, start flushing and what are you actually

880
00:52:34,800 --> 00:52:37,279
Speaker 1: looking for and what are you recording? Right down? Well,

881
00:52:37,320 --> 00:52:39,680
Speaker 1: the way I do it, so everybody does it different,

882
00:52:39,680 --> 00:52:41,799
Speaker 1: but the way I do it, uh is what you

883
00:52:41,880 --> 00:52:45,600
Speaker 1: What you do is you you you separate the property

884
00:52:45,600 --> 00:52:48,400
Speaker 1: and do like a grid or transax line transax and

885
00:52:48,440 --> 00:52:51,800
Speaker 1: those could be depending on visibility, if the vegetation is

886
00:52:51,880 --> 00:52:55,759
Speaker 1: high or the vegetation is low. That depends on that

887
00:52:55,920 --> 00:52:59,239
Speaker 1: makes uh decides what your transax are gonna be. You know,

888
00:52:59,520 --> 00:53:02,920
Speaker 1: rather they're gonna be a hundred yards apart where you're

889
00:53:02,960 --> 00:53:06,040
Speaker 1: running down, you know, running down, turning around, coming back,

890
00:53:06,120 --> 00:53:09,719
Speaker 1: running down, turning back, uh, or if they're gonna be

891
00:53:09,719 --> 00:53:13,800
Speaker 1: four hundred yards apart, and based off of the density

892
00:53:13,800 --> 00:53:16,160
Speaker 1: of the brush or density of vegetation and what you

893
00:53:16,200 --> 00:53:20,080
Speaker 1: can see, that's how you estimate how much how much

894
00:53:20,120 --> 00:53:22,279
Speaker 1: of the property you can cover with the helicopter. How

895
00:53:22,360 --> 00:53:26,760
Speaker 1: much you're survey, say, in this sort of thick gass country,

896
00:53:26,800 --> 00:53:29,280
Speaker 1: what is the transsept It's usually about two hundred yards

897
00:53:29,480 --> 00:53:32,000
Speaker 1: because you can see two hundred yards. You can usually

898
00:53:32,000 --> 00:53:35,319
Speaker 1: see a hundred yards out both sides, so you'll move over.

899
00:53:36,320 --> 00:53:38,959
Speaker 1: How many how many feet? How you flying? I don't

900
00:53:39,040 --> 00:53:42,799
Speaker 1: it's it varies depending on the vegetation. But it's not,

901
00:53:42,920 --> 00:53:48,200
Speaker 1: it's not. I guess it'd be probably fifty. You're just skimmings. No,

902
00:53:48,320 --> 00:53:51,040
Speaker 1: it's it's like airplane. No, the skids are touching the

903
00:53:51,080 --> 00:53:54,680
Speaker 1: tops of the trees. Sometimes it's it's pretty low. And

904
00:53:54,960 --> 00:53:56,920
Speaker 1: depending on the wind too. If it's real windy, we'll

905
00:53:56,920 --> 00:54:00,520
Speaker 1: get hired just so we don't crash. Uh uh. But

906
00:54:00,640 --> 00:54:02,279
Speaker 1: so what we'll do is we'll try we'll fly these

907
00:54:02,280 --> 00:54:04,480
Speaker 1: transac and I guess they'd be four hundred yard transax

908
00:54:04,520 --> 00:54:07,560
Speaker 1: if you can see a hundred yards either way. Uh

909
00:54:07,680 --> 00:54:10,920
Speaker 1: is what it would boil down to. And uh So

910
00:54:11,000 --> 00:54:14,759
Speaker 1: what you're looking for is when a deer flushes, you

911
00:54:14,880 --> 00:54:17,160
Speaker 1: usually can't see them if they stand still, but so

912
00:54:17,200 --> 00:54:18,759
Speaker 1: you usually want to get them to flush. So you

913
00:54:18,800 --> 00:54:20,560
Speaker 1: don't want to fly on a windy day or a

914
00:54:20,560 --> 00:54:23,319
Speaker 1: hot day where they're gonna be betted or not. Here

915
00:54:23,400 --> 00:54:25,919
Speaker 1: you you want to fly on a calm, cool day.

916
00:54:26,080 --> 00:54:28,440
Speaker 1: Usually cloudy works, so that way they're moving as soon

917
00:54:28,440 --> 00:54:30,560
Speaker 1: as they hear you. And what we'll do is we'll

918
00:54:30,640 --> 00:54:35,680
Speaker 1: count uh bucks does and fawns. It's pretty much what

919
00:54:35,800 --> 00:54:37,920
Speaker 1: you're counting. And you can tell the difference between the

920
00:54:37,960 --> 00:54:40,480
Speaker 1: dose and the fawns pretty well. We usually fly in October,

921
00:54:40,680 --> 00:54:43,239
Speaker 1: so the fallons are pretty pretty small. And then the

922
00:54:43,320 --> 00:54:47,120
Speaker 1: bucks break into subcategories, and I break them into young bucks,

923
00:54:47,440 --> 00:54:50,799
Speaker 1: middle aged bucks, and old bucks and then uh And

924
00:54:50,880 --> 00:54:54,360
Speaker 1: like I said, that gives you your sex ratio and

925
00:54:54,480 --> 00:54:58,640
Speaker 1: your ratio of young versus middle aged versus old bucks,

926
00:54:58,640 --> 00:55:01,000
Speaker 1: and then it also gives you your fallon survival for

927
00:55:01,120 --> 00:55:03,920
Speaker 1: that summer. And you take those ratios and apply them

928
00:55:03,920 --> 00:55:10,759
Speaker 1: to your individual buck count from your cameras and through

929
00:55:10,800 --> 00:55:14,000
Speaker 1: all that. The state will take those numbers and say,

930
00:55:14,280 --> 00:55:17,080
Speaker 1: and they accept your numbers. They well, they accept mine.

931
00:55:17,520 --> 00:55:20,279
Speaker 1: They don't accept everybody. Sometimes they have to have a

932
00:55:21,000 --> 00:55:25,359
Speaker 1: you know, a state employee in the helicopter with you.

933
00:55:25,760 --> 00:55:27,120
Speaker 1: But if you're trained in it, you can get to

934
00:55:27,239 --> 00:55:29,280
Speaker 1: point whe they'll accept your numbers. Yeah, if you're trained

935
00:55:29,320 --> 00:55:32,120
Speaker 1: in it, and and they trust you and they know

936
00:55:32,200 --> 00:55:35,000
Speaker 1: you're you're not going to screw up, then they'll take

937
00:55:35,040 --> 00:55:37,000
Speaker 1: your numbers. And I've been doing it for ten or

938
00:55:37,000 --> 00:55:42,080
Speaker 1: twelve or almost fourteen years, I guess now, But what's

939
00:55:42,080 --> 00:55:45,440
Speaker 1: your level of accuracy? Like do you plus and minus? Like? No,

940
00:55:45,840 --> 00:55:49,480
Speaker 1: you're not. Well. See with the with the helicopter ratios,

941
00:55:49,520 --> 00:55:52,600
Speaker 1: you're not You're not trying to get a number, You're

942
00:55:52,640 --> 00:55:56,239
Speaker 1: just trying to get the ratio. So so within then

943
00:55:56,280 --> 00:55:59,840
Speaker 1: with the individual buck counts, so say you have you know,

944
00:56:00,000 --> 00:56:02,280
Speaker 1: one to one ratio and you see three hundred bucks

945
00:56:02,320 --> 00:56:04,640
Speaker 1: on the on the trail camera, so you have three

946
00:56:04,680 --> 00:56:07,040
Speaker 1: hundred dolls on a wonder one ratio, So you have

947
00:56:07,080 --> 00:56:09,759
Speaker 1: six hundred deer. But then you have a fifty fond

948
00:56:09,840 --> 00:56:12,600
Speaker 1: survival and what fifty fons reproval means you have three

949
00:56:12,640 --> 00:56:16,000
Speaker 1: hundred dolls, you have a hundred and fifty fonts. That's

950
00:56:16,000 --> 00:56:18,760
Speaker 1: so in that situation, you have seven hundred and fifty

951
00:56:18,800 --> 00:56:22,840
Speaker 1: total deer on the property. And uh, and you can't

952
00:56:22,840 --> 00:56:28,000
Speaker 1: really a lot of people do the helicopter survey, you know,

953
00:56:28,200 --> 00:56:31,000
Speaker 1: and that's how many deer they think they have. But

954
00:56:32,040 --> 00:56:36,600
Speaker 1: what you just mentioned. Your level of accuracy is changes

955
00:56:36,760 --> 00:56:39,880
Speaker 1: from property to property, depending on who's flying, depending on

956
00:56:39,960 --> 00:56:43,719
Speaker 1: whether it's there's too many variables too, that it gives

957
00:56:43,719 --> 00:56:47,320
Speaker 1: you a good idea and better than nothing exactly exactly.

958
00:56:47,360 --> 00:56:49,720
Speaker 1: What was the other question, because that question was prompted

959
00:56:49,719 --> 00:56:52,360
Speaker 1: by something that was spoken after you expressed interest in

960
00:56:52,400 --> 00:56:58,520
Speaker 1: asking the question. Was it was yeah, yeah, yeah, um

961
00:56:58,640 --> 00:57:07,120
Speaker 1: you all up speed? Okay, Now, these tags, there's a

962
00:57:07,120 --> 00:57:11,200
Speaker 1: penalty if you go over. There's no penalty for going under.

963
00:57:11,680 --> 00:57:17,240
Speaker 1: They frown upon going under. So when they come out

964
00:57:17,280 --> 00:57:21,640
Speaker 1: and say, son, we're thinking that you need to do

965
00:57:21,760 --> 00:57:24,840
Speaker 1: some deer shooting out here, they're not happy if you

966
00:57:24,920 --> 00:57:28,120
Speaker 1: just don't do any deer shooting. No, I mean they

967
00:57:28,240 --> 00:57:31,560
Speaker 1: if you're if you're if you go through the process

968
00:57:31,600 --> 00:57:34,480
Speaker 1: of getting the permits, and it's a long process, so

969
00:57:34,680 --> 00:57:36,520
Speaker 1: you can you can just will never bring any of

970
00:57:36,520 --> 00:57:38,440
Speaker 1: this up and never get any permits and and do

971
00:57:38,520 --> 00:57:43,000
Speaker 1: whatever you wanted to the to what your your license allows,

972
00:57:43,680 --> 00:57:47,080
Speaker 1: which is which is your over to counter what right.

973
00:57:47,080 --> 00:57:48,760
Speaker 1: And the way people get around that is they just

974
00:57:48,800 --> 00:57:52,120
Speaker 1: bring in more gas, you know, more guests to shoot,

975
00:57:52,600 --> 00:57:54,880
Speaker 1: so then they can overshoot deer that way. So this

976
00:57:54,960 --> 00:57:57,520
Speaker 1: is the thing you kind of a thing you've been

977
00:57:57,720 --> 00:58:00,840
Speaker 1: rolling in in a plan you can rolling. Yeah, it's

978
00:58:00,880 --> 00:58:03,320
Speaker 1: a it's a long term, several years system just to

979
00:58:03,400 --> 00:58:05,960
Speaker 1: get started in the program. And when they give you

980
00:58:06,000 --> 00:58:11,120
Speaker 1: the tags, it doesn't matter who's pulling the trigger. Uh. Okay.

981
00:58:11,160 --> 00:58:14,280
Speaker 1: There's three levels of these permits. Uh. And I believe

982
00:58:14,520 --> 00:58:18,240
Speaker 1: the first level. Uh, I don't. I don't remember. I

983
00:58:18,240 --> 00:58:20,120
Speaker 1: havn't been in the first and second level in in

984
00:58:20,640 --> 00:58:23,560
Speaker 1: ten years, so I don't remember. But the in in

985
00:58:23,680 --> 00:58:25,520
Speaker 1: Scott would know if we get him on here later.

986
00:58:26,000 --> 00:58:32,280
Speaker 1: But uh, the level three anybody can shoot is many deers.

987
00:58:32,280 --> 00:58:34,280
Speaker 1: So if you get a hundred tags, one person could

988
00:58:34,280 --> 00:58:39,200
Speaker 1: shoot deer legally and they could they could use all

989
00:58:39,240 --> 00:58:42,320
Speaker 1: the tags, or you could have a hundred different people

990
00:58:42,360 --> 00:58:46,880
Speaker 1: shoot one deer. Uh, it makes no difference. And on

991
00:58:46,920 --> 00:58:49,360
Speaker 1: the let on the highest level, so someone hunting on

992
00:58:49,400 --> 00:58:51,360
Speaker 1: that property, he's ever a hunting license. They have to

993
00:58:51,400 --> 00:58:53,840
Speaker 1: have a hunting license, yes, And there's a stack of tags,

994
00:58:54,280 --> 00:58:56,200
Speaker 1: and when a deer is killing that property, one of

995
00:58:56,200 --> 00:58:58,680
Speaker 1: those tags goes out of that deer. One of the

996
00:58:58,960 --> 00:59:02,240
Speaker 1: state issued permit, it's goes on that dear one of

997
00:59:02,400 --> 00:59:04,680
Speaker 1: your license your tag off of your over the counter

998
00:59:04,720 --> 00:59:07,920
Speaker 1: license does not go on that dear if your property

999
00:59:07,960 --> 00:59:11,120
Speaker 1: is enrolled in that permit system. So when you go

1000
00:59:11,200 --> 00:59:13,160
Speaker 1: buy a tag and it comes with five dear tags,

1001
00:59:13,160 --> 00:59:14,840
Speaker 1: but you're only hunting on your property and you have

1002
00:59:14,920 --> 00:59:18,080
Speaker 1: state issued tags in your property, you never touch your tags. Correct.

1003
00:59:18,160 --> 00:59:20,800
Speaker 1: I have not used a a white tail tag off

1004
00:59:20,840 --> 00:59:24,080
Speaker 1: of my license in six or seven years, because you're

1005
00:59:24,120 --> 00:59:27,640
Speaker 1: just doing I'm only hunting here or or on properties

1006
00:59:27,680 --> 00:59:32,360
Speaker 1: that that have the same permitting, same permitting system. Okay, No,

1007
00:59:33,760 --> 00:59:41,080
Speaker 1: earlier you were talking about that a buck. You're telling

1008
00:59:41,120 --> 00:59:46,400
Speaker 1: me that when a doe has twin fawns, eight percent

1009
00:59:46,480 --> 00:59:51,800
Speaker 1: of the time those twin fawns have different fathers. The

1010
00:59:51,920 --> 00:59:56,000
Speaker 1: last study that I read, uh, was was in in

1011
00:59:56,280 --> 01:00:02,200
Speaker 1: this southwest Texas. This information is somewhat specific to this area. Yeah,

1012
01:00:02,760 --> 01:00:06,000
Speaker 1: that's what that. Yeah, it's it's everything sites specific with

1013
01:00:06,040 --> 01:00:08,560
Speaker 1: white tails. They changed so much from area to area.

1014
01:00:09,120 --> 01:00:12,200
Speaker 1: And uh, but yeah, they because we have such tight

1015
01:00:12,600 --> 01:00:15,040
Speaker 1: sex ratios one to one most of the time, or

1016
01:00:15,080 --> 01:00:18,200
Speaker 1: even even higher bucks than does. Yeah, and I'll point

1017
01:00:18,200 --> 01:00:21,000
Speaker 1: out that they're born one to one, Yeah, right, right,

1018
01:00:21,080 --> 01:00:22,880
Speaker 1: A little heavier on the bucks, a little heavy on

1019
01:00:22,880 --> 01:00:24,800
Speaker 1: the bucks. So when you're sitting like when when I

1020
01:00:24,840 --> 01:00:27,040
Speaker 1: was growing up, you'd be sitting in there in the

1021
01:00:27,080 --> 01:00:29,960
Speaker 1: woods and you see about ninety dolls for every bucky

1022
01:00:29,960 --> 01:00:34,320
Speaker 1: saw right in in Michigan, because that was like I

1023
01:00:34,440 --> 01:00:36,120
Speaker 1: moved away from Michigan, but I was born. You know,

1024
01:00:36,120 --> 01:00:38,120
Speaker 1: I'm forty two years old. So I started hunting when

1025
01:00:38,160 --> 01:00:41,080
Speaker 1: I was eleven twelve years old. And back then people

1026
01:00:41,080 --> 01:00:44,959
Speaker 1: don't want to shoot dolls. Everybody shot every buck they saw,

1027
01:00:45,720 --> 01:00:47,800
Speaker 1: right and you'd sit up there and be like, I

1028
01:00:47,840 --> 01:00:49,760
Speaker 1: remember sitting there one time in the cornfield, and I

1029
01:00:49,760 --> 01:00:52,560
Speaker 1: remember it was like a late season hunt, so rifle

1030
01:00:52,600 --> 01:00:54,760
Speaker 1: season ended. I was hunting in the December season with

1031
01:00:54,840 --> 01:00:56,959
Speaker 1: my boat, and I remember counting nineties some white tailed

1032
01:00:57,000 --> 01:01:01,000
Speaker 1: dolls without a buck hotly cah. Yeah. I wonder if

1033
01:01:01,080 --> 01:01:04,880
Speaker 1: that was it was that. I wonder if that was

1034
01:01:04,920 --> 01:01:06,920
Speaker 1: a good indication of this X ratio or was it

1035
01:01:06,960 --> 01:01:10,600
Speaker 1: a indication of hunting pressure for the bucks. I don't know,

1036
01:01:10,960 --> 01:01:13,240
Speaker 1: but my feeling was growing up, and it was a

1037
01:01:13,320 --> 01:01:14,840
Speaker 1: long time ago, and I didn't have it. It wasn't

1038
01:01:14,840 --> 01:01:17,520
Speaker 1: taking a scientific approach to it. My feeling was back

1039
01:01:17,560 --> 01:01:21,000
Speaker 1: then in those days that the that the ratios were

1040
01:01:21,040 --> 01:01:23,480
Speaker 1: as ridiculous. They they got to be as ridiculous as

1041
01:01:23,520 --> 01:01:26,840
Speaker 1: like you'd here thrown around, you'd have twenty dollars for

1042
01:01:26,840 --> 01:01:30,280
Speaker 1: every part. Yeah, there's there's places in Texas like that

1043
01:01:30,280 --> 01:01:34,760
Speaker 1: that are neglected or not uh not neglected, but not

1044
01:01:34,760 --> 01:01:38,439
Speaker 1: not managed and only they only shoot the bucks. Same

1045
01:01:38,520 --> 01:01:40,720
Speaker 1: same deal like you're talking about that that happened right

1046
01:01:40,760 --> 01:01:43,640
Speaker 1: now today. But yeah, so it's interesting in that they're

1047
01:01:43,640 --> 01:01:46,440
Speaker 1: born one to one. But of course one thing to

1048
01:01:46,480 --> 01:01:49,000
Speaker 1: excuse it is, I'm sure the dolls gotta have a

1049
01:01:49,120 --> 01:01:54,320
Speaker 1: much longer life expectancy. Yeah, is that true? Um in

1050
01:01:54,320 --> 01:01:58,680
Speaker 1: in unmanaged places, I would believe so, yes, and managed

1051
01:01:58,720 --> 01:02:02,720
Speaker 1: places I don't. I don't think so. Yeah. So let's

1052
01:02:02,760 --> 01:02:07,280
Speaker 1: just say all people died right now, Okay, humans cease

1053
01:02:07,360 --> 01:02:12,280
Speaker 1: to exist, and we jump into the future one years.

1054
01:02:12,600 --> 01:02:16,000
Speaker 1: Based on your understanding, white tails, would white tails exist

1055
01:02:16,120 --> 01:02:21,320
Speaker 1: then at a one to one ratio? And it just

1056
01:02:21,400 --> 01:02:23,360
Speaker 1: I guess it depends on their location, but I kind

1057
01:02:23,360 --> 01:02:25,600
Speaker 1: of I would believe, Yes, you believe they'd find a

1058
01:02:25,600 --> 01:02:28,840
Speaker 1: way towards that. I believe, especially in this area, they

1059
01:02:28,840 --> 01:02:34,800
Speaker 1: gravitate to one one. So the twin fawn thing that

1060
01:02:34,920 --> 01:02:39,120
Speaker 1: the dough is is uh getting bread by a bunch

1061
01:02:39,160 --> 01:02:41,760
Speaker 1: of different bucks. I watched the dough on a with

1062
01:02:41,880 --> 01:02:45,040
Speaker 1: a with a red train. One time I had seven bucks,

1063
01:02:45,040 --> 01:02:47,160
Speaker 1: seven bucks with one dough. It was hot and she

1064
01:02:47,360 --> 01:02:50,120
Speaker 1: they she was in a field. I watched six of

1065
01:02:50,160 --> 01:02:53,160
Speaker 1: those bucks readers, a couple of them multiple times. Weren't

1066
01:02:53,200 --> 01:02:55,080
Speaker 1: you tell me all? But the big one the only

1067
01:02:55,080 --> 01:02:57,320
Speaker 1: one that never bred? Or was the big one while

1068
01:02:57,400 --> 01:03:00,520
Speaker 1: you watched? Well, yeah, wow, because he was so paranoid

1069
01:03:00,560 --> 01:03:02,760
Speaker 1: about trying to beat all the other ones off. Hey,

1070
01:03:02,840 --> 01:03:04,960
Speaker 1: chase one yards the other way, and another one to

1071
01:03:05,080 --> 01:03:07,800
Speaker 1: run in and breeder, mounter breeder, and then he'd turned

1072
01:03:07,840 --> 01:03:10,280
Speaker 1: around and see that one breeder turned around and chase

1073
01:03:10,400 --> 01:03:11,920
Speaker 1: him off, and then another one to come in from

1074
01:03:11,960 --> 01:03:14,120
Speaker 1: the other side. There was there was a couple of

1075
01:03:14,120 --> 01:03:16,600
Speaker 1: those bucks that bred her multiple times, and he never

1076
01:03:16,640 --> 01:03:20,160
Speaker 1: bred her. It's the time frame that that's even like

1077
01:03:20,200 --> 01:03:22,760
Speaker 1: biologically possible to be bred by two different bucks. Is

1078
01:03:22,760 --> 01:03:25,120
Speaker 1: it like the same day or yeah? I think their

1079
01:03:25,120 --> 01:03:29,360
Speaker 1: astresses is uh eight or something like that. So she

1080
01:03:29,360 --> 01:03:32,840
Speaker 1: she forms two embryos, and just because she's in there

1081
01:03:33,880 --> 01:03:41,680
Speaker 1: being so trashy, wind's up carrying in her the children

1082
01:03:41,680 --> 01:03:44,120
Speaker 1: of two different bucks. Right. It works with dogs if

1083
01:03:44,120 --> 01:03:47,520
Speaker 1: you can breed. Uh, if you breed three male dogs

1084
01:03:47,560 --> 01:03:51,320
Speaker 1: to the same female, they can have, you know, puppies

1085
01:03:51,320 --> 01:03:59,120
Speaker 1: from all three. Is it? Like? Here's the another thing

1086
01:03:59,120 --> 01:04:02,160
Speaker 1: we say when we were kids. A buck bread a

1087
01:04:02,280 --> 01:04:04,480
Speaker 1: big buck. Once he got to be the big man,

1088
01:04:04,640 --> 01:04:09,640
Speaker 1: Like the biggest buck around heat breed ten to twenty dopes.

1089
01:04:11,080 --> 01:04:15,520
Speaker 1: That's possible, it doesn't happen on what I notice here

1090
01:04:15,520 --> 01:04:20,000
Speaker 1: with a one one ratio, I think every buck is

1091
01:04:20,040 --> 01:04:25,240
Speaker 1: pretty well equal from my from my observations yearling bucks

1092
01:04:25,920 --> 01:04:28,960
Speaker 1: in this area, in this area of Texas and this,

1093
01:04:29,240 --> 01:04:33,560
Speaker 1: I mean this is a small, minute little spot, but uh,

1094
01:04:33,640 --> 01:04:37,480
Speaker 1: in my observations, yearling bucks breed as much as older bucks.

1095
01:04:38,640 --> 01:04:45,040
Speaker 1: All age classes are pretty well consistent depending on the individual.

1096
01:04:45,480 --> 01:04:48,240
Speaker 1: Depending on the individual you get. It's just like people.

1097
01:04:48,320 --> 01:04:49,960
Speaker 1: You get the real horny ones and you get the

1098
01:04:49,960 --> 01:04:51,560
Speaker 1: ones that are just laid back and all they do

1099
01:04:51,640 --> 01:04:54,600
Speaker 1: is want to eat. Yeah, it's the same deal with deer.

1100
01:04:55,400 --> 01:04:57,600
Speaker 1: And uh, I mean some bucks may not breed any

1101
01:04:57,680 --> 01:05:00,520
Speaker 1: any dose their whole life for one or to just

1102
01:05:00,680 --> 01:05:04,640
Speaker 1: they just tapping to stop and squat in front of him.

1103
01:05:04,720 --> 01:05:06,919
Speaker 1: What's that valarious guist theory. I think we were talking

1104
01:05:06,920 --> 01:05:09,960
Speaker 1: to you founder effect. Huh. I was gonna bring up

1105
01:05:09,960 --> 01:05:12,400
Speaker 1: the founder effect earlier. Is that the one where the

1106
01:05:12,400 --> 01:05:17,040
Speaker 1: buck takes himself out of the breedings. Uh problem was

1107
01:05:17,080 --> 01:05:20,360
Speaker 1: that vale Geist? I think so? I never really believed

1108
01:05:20,440 --> 01:05:24,080
Speaker 1: that theory. Yeah, is that something he put forward? I

1109
01:05:24,080 --> 01:05:26,439
Speaker 1: gotta google it, do it because I'll tell another vale

1110
01:05:26,480 --> 01:05:29,760
Speaker 1: guyst thing. I think it was Vlarious Guys who there's

1111
01:05:29,760 --> 01:05:34,920
Speaker 1: a there's a very famous uh mammalogist in Calgary at

1112
01:05:34,920 --> 01:05:37,160
Speaker 1: the university there. He's still living and there met him

1113
01:05:37,360 --> 01:05:41,480
Speaker 1: named Vlarious Geist and and he has he's like a

1114
01:05:41,520 --> 01:05:45,000
Speaker 1: big ideas guy about animals, and and he wrote about it.

1115
01:05:45,200 --> 01:05:46,720
Speaker 1: They might even have come up coined the term the

1116
01:05:46,720 --> 01:05:52,120
Speaker 1: founder effect. Basically about the um when animals come into

1117
01:05:52,160 --> 01:05:57,040
Speaker 1: a new area, when they discover new range or having

1118
01:05:57,240 --> 01:06:00,400
Speaker 1: arrange expansion from something like retreating glaze. Sure's at the

1119
01:06:00,480 --> 01:06:05,240
Speaker 1: end of the ice age whatever. The um the tendency

1120
01:06:05,280 --> 01:06:10,520
Speaker 1: towards gigantism that happens with animals moving into a new

1121
01:06:10,800 --> 01:06:17,840
Speaker 1: piece of habitat. And we see it with introductions, wildlife introductions, explosions, right,

1122
01:06:18,640 --> 01:06:21,360
Speaker 1: giant specimens, a whole bunch of them and then you

1123
01:06:21,440 --> 01:06:23,480
Speaker 1: have like a collapse and then you kind of find

1124
01:06:23,520 --> 01:06:27,840
Speaker 1: a norm. But that was about guyst thing. Yeah, it's

1125
01:06:27,880 --> 01:06:30,000
Speaker 1: gonna dig it up. Yeah, I heard this theory like

1126
01:06:30,080 --> 01:06:33,200
Speaker 1: the box It just yeah, I don't even need to

1127
01:06:33,200 --> 01:06:36,840
Speaker 1: look the damn thing up. It was this idea that

1128
01:06:36,920 --> 01:06:39,960
Speaker 1: I think you were talking about your honest that a

1129
01:06:40,120 --> 01:06:42,760
Speaker 1: book will be like, hey, man, I got an idea.

1130
01:06:43,040 --> 01:06:46,880
Speaker 1: I'm gonna pull myself out of the genetic pool and

1131
01:06:46,920 --> 01:06:50,840
Speaker 1: go off and hide out for several years and get

1132
01:06:50,880 --> 01:06:53,600
Speaker 1: real big and bad, and then I'm gonna come down

1133
01:06:53,640 --> 01:06:56,000
Speaker 1: and pour the coals to every dough I can find.

1134
01:06:56,600 --> 01:07:00,120
Speaker 1: I'm gonna come out of like hiding like I'm the

1135
01:07:00,240 --> 01:07:03,440
Speaker 1: Hollywood movie and pour the coals to every dole that

1136
01:07:03,480 --> 01:07:05,440
Speaker 1: I could find. Yeah, I was gonna ask you if

1137
01:07:05,440 --> 01:07:07,400
Speaker 1: you've ever seen that, if you had seen box Set

1138
01:07:07,480 --> 01:07:10,400
Speaker 1: for like four or five years, has been just real mellow,

1139
01:07:10,520 --> 01:07:14,240
Speaker 1: weren't very aggressive, and because of that, you know, I

1140
01:07:14,240 --> 01:07:17,040
Speaker 1: had put on weight and gotten big, and then all

1141
01:07:17,080 --> 01:07:18,600
Speaker 1: of a sudden one year they just turned it on

1142
01:07:18,760 --> 01:07:21,240
Speaker 1: and kind of started kicking. But it's like a version

1143
01:07:21,240 --> 01:07:24,720
Speaker 1: of the old like hey, let's run down and breed

1144
01:07:24,800 --> 01:07:27,439
Speaker 1: one of those cows and the old ones, like let's

1145
01:07:27,480 --> 01:07:29,440
Speaker 1: walk down and breed them all. It's kind of like

1146
01:07:29,480 --> 01:07:32,840
Speaker 1: an extreme version of that. Yeah, yeah, I haven't I

1147
01:07:32,880 --> 01:07:37,680
Speaker 1: haven't noticed that here. Um it seems you haven't noticed

1148
01:07:37,720 --> 01:07:42,200
Speaker 1: a big buck hiding somewhere for many years and then

1149
01:07:42,240 --> 01:07:45,120
Speaker 1: all of a sudden coming out and just it's sealaging

1150
01:07:45,200 --> 01:07:50,520
Speaker 1: the women. I'll say, what I've noticed is when they're

1151
01:07:50,520 --> 01:07:54,360
Speaker 1: horny at one their horny their whole life, when all

1152
01:07:54,400 --> 01:07:56,040
Speaker 1: they want to do is eat and they don't really

1153
01:07:56,040 --> 01:07:58,479
Speaker 1: look at the girls. They're like that their whole life.

1154
01:07:58,840 --> 01:08:01,120
Speaker 1: You know. As far as bud like folks fighting and

1155
01:08:01,160 --> 01:08:05,320
Speaker 1: breaking times, there's bucks that never break even a tip

1156
01:08:05,400 --> 01:08:07,960
Speaker 1: for eight or nine years of their life. Then there's

1157
01:08:08,000 --> 01:08:11,360
Speaker 1: other bucks that are have every time on their head

1158
01:08:11,440 --> 01:08:15,680
Speaker 1: broken by November. He's just gonna fight, He's just that's

1159
01:08:16,120 --> 01:08:18,960
Speaker 1: guys like that exactly. It's they're just like people and

1160
01:08:18,960 --> 01:08:22,519
Speaker 1: they're so individual that that's what makes it fun, and

1161
01:08:22,600 --> 01:08:24,800
Speaker 1: that's what makes it hard, and that's what also makes

1162
01:08:24,800 --> 01:08:29,960
Speaker 1: it so so interesting to me, because nobody's ever right,

1163
01:08:30,360 --> 01:08:34,320
Speaker 1: and nobody's ever wrong. Your your your theories and everything

1164
01:08:34,320 --> 01:08:38,439
Speaker 1: that you do. You know, it has an application somewhere,

1165
01:08:38,920 --> 01:08:42,559
Speaker 1: so you're not h you're not shooting all the giant bucks.

1166
01:08:42,840 --> 01:08:45,880
Speaker 1: Now you don't shoot the two bucks, and you know

1167
01:08:45,960 --> 01:08:47,559
Speaker 1: you get paid to do it. You can probably paid

1168
01:08:47,560 --> 01:08:50,120
Speaker 1: to do all kinds of stuff. What do you get

1169
01:08:50,160 --> 01:08:54,080
Speaker 1: out of it? Uh? It's I mean, it's it's a passion.

1170
01:08:54,560 --> 01:08:57,280
Speaker 1: It's just something that I've developed over the years, and

1171
01:08:57,320 --> 01:08:59,840
Speaker 1: now it's more of an addiction. It started out as

1172
01:08:59,840 --> 01:09:01,479
Speaker 1: a ash and now it's more of an addiction. I

1173
01:09:01,479 --> 01:09:03,280
Speaker 1: couldn't turn my back to it now if I wanted to.

1174
01:09:04,160 --> 01:09:09,080
Speaker 1: And just watching, just just watching. Uhh. We talked about

1175
01:09:09,080 --> 01:09:12,320
Speaker 1: this word earlier. Watching like a system. Yeah, just just

1176
01:09:12,360 --> 01:09:15,640
Speaker 1: a wildlife system, right, just learning as much as I

1177
01:09:15,720 --> 01:09:20,240
Speaker 1: possibly can about you know, that animal. How much do

1178
01:09:20,320 --> 01:09:23,479
Speaker 1: you feel that you're manipulating it to the point where

1179
01:09:23,800 --> 01:09:28,559
Speaker 1: you're you're farming, dear, And how much do you feel

1180
01:09:28,600 --> 01:09:32,400
Speaker 1: you're just making room for things, You're making room to

1181
01:09:32,439 --> 01:09:36,120
Speaker 1: allow things that would happen happen. I feel I feel

1182
01:09:36,240 --> 01:09:40,240
Speaker 1: very strongly that as far as I feel like we're

1183
01:09:43,240 --> 01:09:48,520
Speaker 1: trying to let things occur that would naturally occur and

1184
01:09:48,600 --> 01:09:52,280
Speaker 1: maybe putting them on a fast track without with an

1185
01:09:52,320 --> 01:09:56,360
Speaker 1: indirect approach, meaning in really like again, in this scenario,

1186
01:09:56,400 --> 01:10:00,240
Speaker 1: this hypothetic scenario where all humans die, you would all

1187
01:10:00,320 --> 01:10:04,720
Speaker 1: humans are dead. You would see that some dear we're

1188
01:10:04,760 --> 01:10:08,040
Speaker 1: growing to nine years old and dying of old age,

1189
01:10:08,360 --> 01:10:11,680
Speaker 1: which is not happening in Mosquito County, Michigan, where I

1190
01:10:11,680 --> 01:10:16,000
Speaker 1: grew up. Even kind of is there hunting? Yeah, so

1191
01:10:16,040 --> 01:10:19,120
Speaker 1: if there wasn't people, No, there is no old buck.

1192
01:10:19,880 --> 01:10:21,720
Speaker 1: We about ship our pants when you're in My dad

1193
01:10:21,760 --> 01:10:23,160
Speaker 1: shot a buck. They're looking back. It must have been

1194
01:10:23,160 --> 01:10:25,720
Speaker 1: a two and a half ye old buck. It was

1195
01:10:25,840 --> 01:10:34,400
Speaker 1: a giant. Yeah, he even got in the newspaper. Yeah. No, uh, man,

1196
01:10:34,439 --> 01:10:38,120
Speaker 1: I don't know that they all revert back. It's it

1197
01:10:38,240 --> 01:10:40,600
Speaker 1: goes back to those spikes in the in the populations.

1198
01:10:41,280 --> 01:10:44,600
Speaker 1: What I'm trying to do is avoid the spikes. If if, if,

1199
01:10:44,640 --> 01:10:47,960
Speaker 1: if people disappeared in a hundred years from now, it

1200
01:10:48,000 --> 01:10:53,280
Speaker 1: would be the it would be the up and down population. Yes,

1201
01:10:53,439 --> 01:10:56,760
Speaker 1: and uh there would be years or points in that

1202
01:10:56,920 --> 01:11:00,880
Speaker 1: process or that system of ups and downs that would

1203
01:11:00,920 --> 01:11:06,000
Speaker 1: be mirror to what we're trying to do here, But

1204
01:11:06,320 --> 01:11:09,760
Speaker 1: it wouldn't be consistent. You know what. You know what

1205
01:11:09,800 --> 01:11:11,639
Speaker 1: I'm saying. You know it would be up and down,

1206
01:11:12,000 --> 01:11:14,400
Speaker 1: but while it was going up, it would be what

1207
01:11:14,479 --> 01:11:17,880
Speaker 1: we're trying to hit here, um, And that's all we're

1208
01:11:17,880 --> 01:11:20,759
Speaker 1: trying to do, is we're just trying to slow that down.

1209
01:11:23,160 --> 01:11:27,200
Speaker 1: How will you like right now, if you had to

1210
01:11:27,200 --> 01:11:31,600
Speaker 1: sit right now and say, in my career, UM, I

1211
01:11:31,600 --> 01:11:35,080
Speaker 1: would measure success by what what would it be? Not

1212
01:11:35,080 --> 01:11:38,439
Speaker 1: on means that your career because you're you're young, like

1213
01:11:38,560 --> 01:11:41,160
Speaker 1: in and what would be the ideal thing that you

1214
01:11:41,160 --> 01:11:43,800
Speaker 1: would see happen? Not a property you were managing, like

1215
01:11:44,000 --> 01:11:50,960
Speaker 1: what would be a ten year goal? Uh uh uh, well,

1216
01:11:51,160 --> 01:11:54,559
Speaker 1: like a tenure. I don't know. I don't know if

1217
01:11:54,600 --> 01:11:57,519
Speaker 1: I could fathom what I really want to happen. But

1218
01:11:57,600 --> 01:11:59,719
Speaker 1: you don't know what it would look like. No, there's

1219
01:12:00,000 --> 01:12:02,080
Speaker 1: that's that's I don't have any idea what it would

1220
01:12:02,080 --> 01:12:04,760
Speaker 1: look because see the situation you're in. Remember earlier you

1221
01:12:04,880 --> 01:12:07,280
Speaker 1: mentioning that um and you were putting us as a

1222
01:12:07,360 --> 01:12:08,760
Speaker 1: life goal. But you were just saying, like a thing

1223
01:12:08,760 --> 01:12:12,000
Speaker 1: that would happen perhaps is that ever you'd get it

1224
01:12:12,000 --> 01:12:17,080
Speaker 1: to be where you had a handful two three, four

1225
01:12:17,840 --> 01:12:23,960
Speaker 1: truly like outstanding white tails come off your property. But

1226
01:12:24,840 --> 01:12:26,840
Speaker 1: one would point out you could do that right now

1227
01:12:27,439 --> 01:12:32,880
Speaker 1: by going online and buying like you know, big thunder

1228
01:12:32,960 --> 01:12:36,040
Speaker 1: fox semen, do you know what I mean, and putting

1229
01:12:36,080 --> 01:12:39,080
Speaker 1: them in a pen and giving him a bunch of stuff. Right. So,

1230
01:12:39,240 --> 01:12:41,280
Speaker 1: it's like, you want to get there, but you want

1231
01:12:41,280 --> 01:12:43,120
Speaker 1: to get there in a in a route that is

1232
01:12:43,160 --> 01:12:45,479
Speaker 1: acceptable to you, or a route that's interesting to you,

1233
01:12:45,600 --> 01:12:47,720
Speaker 1: and not through a route that's not interesting to you.

1234
01:12:48,400 --> 01:12:50,080
Speaker 1: Like I want to have a million dollars, I can

1235
01:12:50,120 --> 01:12:52,200
Speaker 1: make it crooked, I'm not saying me, but so he'd

1236
01:12:52,240 --> 01:12:53,840
Speaker 1: be like, I want a million dollars. I want to

1237
01:12:53,880 --> 01:12:55,800
Speaker 1: make it through running like a great company that treats

1238
01:12:55,800 --> 01:12:58,919
Speaker 1: his employees really well and has like stable growth patterns

1239
01:12:58,960 --> 01:13:01,040
Speaker 1: and and and a good environ mental record. Or I

1240
01:13:01,040 --> 01:13:02,640
Speaker 1: want to make a million dollars, don't care I have

1241
01:13:02,680 --> 01:13:05,240
Speaker 1: to kill you to do it, right. That's exactly I mean,

1242
01:13:05,360 --> 01:13:08,880
Speaker 1: exactly exactly right. My my problem is is as far

1243
01:13:08,880 --> 01:13:12,280
Speaker 1: as seeing into the future, my goals would be, Yeah,

1244
01:13:12,479 --> 01:13:16,439
Speaker 1: to have a couple of gigantic white tail bucks at

1245
01:13:16,439 --> 01:13:24,519
Speaker 1: a harvestable age each year. Uh, However, nobody's doing what

1246
01:13:24,520 --> 01:13:26,720
Speaker 1: what we're trying to do here, or has done what

1247
01:13:26,760 --> 01:13:29,439
Speaker 1: we're trying to do here to the intensity that we're

1248
01:13:29,439 --> 01:13:34,679
Speaker 1: doing it, so you can't really predict what's going to happen. Uh,

1249
01:13:35,400 --> 01:13:39,040
Speaker 1: you follow this recipe X well, right nobody. Yeah, and

1250
01:13:39,040 --> 01:13:41,759
Speaker 1: and it's so different, you know, from side to side.

1251
01:13:41,800 --> 01:13:44,200
Speaker 1: And that's why that's why that question is difficult for

1252
01:13:44,200 --> 01:13:48,679
Speaker 1: me to answer, um, because I don't really know something

1253
01:13:48,760 --> 01:13:51,320
Speaker 1: might happen that we don't see, because this is never

1254
01:13:51,680 --> 01:13:54,439
Speaker 1: you know, nobody's nobody's done this. It's not like you know,

1255
01:13:54,560 --> 01:13:56,080
Speaker 1: like you said, you follow a recipe and this is

1256
01:13:56,120 --> 01:13:58,840
Speaker 1: what you're gonna end up with. Nobody knows what's gonna happen.

1257
01:13:59,200 --> 01:14:04,360
Speaker 1: Mother nature is that awesome way I was saying, screw you,

1258
01:14:04,360 --> 01:14:06,320
Speaker 1: you know, and throwing a wrench into things when you

1259
01:14:06,400 --> 01:14:09,160
Speaker 1: try to start messing with her. And uh, and that's

1260
01:14:09,200 --> 01:14:14,000
Speaker 1: another fun part for me. Yeah. You mentioned earlier like

1261
01:14:14,040 --> 01:14:20,439
Speaker 1: an unintended consequences when we're talking about quail, and you

1262
01:14:20,439 --> 01:14:24,360
Speaker 1: were saying, you can think you're helping out quail by

1263
01:14:24,360 --> 01:14:26,639
Speaker 1: putting out quail feeders, but what you might be doing

1264
01:14:27,160 --> 01:14:29,519
Speaker 1: is helping out Bobcats and Kyle. It's by giving them

1265
01:14:29,520 --> 01:14:33,479
Speaker 1: a great place to kill quail exactly. And that's exactly right.

1266
01:14:33,880 --> 01:14:37,360
Speaker 1: That's exactly right, like intuitively be like, oh yeah, put

1267
01:14:37,360 --> 01:14:39,320
Speaker 1: the food on, dude, you have tons of quail. That's how.

1268
01:14:39,400 --> 01:14:41,200
Speaker 1: That's how. There's a lot of things that got screwed

1269
01:14:41,280 --> 01:14:43,640
Speaker 1: up in in the US that are started out as

1270
01:14:43,680 --> 01:14:50,840
Speaker 1: good intentions and the byproducts were you know, completely disastrous. Yeah,

1271
01:14:51,360 --> 01:14:54,320
Speaker 1: speaking of unintended consequences. You know, that's what's cool about

1272
01:14:54,400 --> 01:14:56,960
Speaker 1: this place is that it's all you guys are trying

1273
01:14:57,000 --> 01:15:00,920
Speaker 1: to do all like native flora and while we you know,

1274
01:15:00,960 --> 01:15:02,760
Speaker 1: you come down here and you've gotten the whole high

1275
01:15:02,760 --> 01:15:05,320
Speaker 1: fenced thing in your head and you're thinking about exotics

1276
01:15:05,360 --> 01:15:07,720
Speaker 1: and there's gonna be zebras running around this, that and

1277
01:15:07,760 --> 01:15:11,439
Speaker 1: the other. Like, let's like list off the cool stuff

1278
01:15:11,439 --> 01:15:15,439
Speaker 1: that we've seen this week. The four spieces of snakes. Yeah,

1279
01:15:16,040 --> 01:15:20,439
Speaker 1: a horny toad, Uh, what is Texas Texas tortis, a

1280
01:15:20,560 --> 01:15:26,639
Speaker 1: greener which is three hundred jack rabbits, five hund cotton

1281
01:15:26,640 --> 01:15:33,240
Speaker 1: tail rabbits, unbelievable Mexican whisp black billy whistling ducks, unbelievable

1282
01:15:33,320 --> 01:15:36,360
Speaker 1: varieties of birds. Yeah, I haven't seen this one kudu

1283
01:15:36,520 --> 01:15:41,000
Speaker 1: roll through yet. My. That's kind of why I want

1284
01:15:41,000 --> 01:15:43,880
Speaker 1: to have this discussion is because my impression, like the

1285
01:15:43,920 --> 01:15:48,240
Speaker 1: first time I ever came down here two like the

1286
01:15:48,240 --> 01:15:50,599
Speaker 1: famous Texas white Tail Country was when I came down

1287
01:15:50,640 --> 01:15:53,639
Speaker 1: with Ben O'Brien to come down here and just look

1288
01:15:53,680 --> 01:15:56,439
Speaker 1: at Quail. I remember walking around being like, this is

1289
01:15:56,520 --> 01:16:01,480
Speaker 1: just not what I imagined. You know it is, uh,

1290
01:16:01,800 --> 01:16:07,960
Speaker 1: Hue is vast expanses of I don't want to say pristine.

1291
01:16:08,040 --> 01:16:10,120
Speaker 1: The hand of man has felt like we, for instance,

1292
01:16:10,160 --> 01:16:13,880
Speaker 1: talked about the implications of fire suppression right we were

1293
01:16:13,960 --> 01:16:16,559
Speaker 1: you and I were having been and I have been

1294
01:16:16,720 --> 01:16:19,519
Speaker 1: bending here. We were discussing like, wow, would you what

1295
01:16:19,600 --> 01:16:21,160
Speaker 1: would you have paid to rod a horse or here

1296
01:16:21,200 --> 01:16:24,120
Speaker 1: two years ago? And he feels that it would have

1297
01:16:24,120 --> 01:16:28,120
Speaker 1: been more mixed grasslands from from making mosaics of burned

1298
01:16:28,160 --> 01:16:30,920
Speaker 1: areas and unburned areas, and and the animal the wild,

1299
01:16:30,920 --> 01:16:34,519
Speaker 1: it was a little different. Uh, buffalo or bison ranged

1300
01:16:35,400 --> 01:16:37,640
Speaker 1: down in this area, which suggests more open country and

1301
01:16:37,680 --> 01:16:40,200
Speaker 1: a little profound down here, which is suggests more open country.

1302
01:16:40,320 --> 01:16:42,519
Speaker 1: So it's the hand of man has felt, you know,

1303
01:16:43,120 --> 01:16:46,920
Speaker 1: through that same way interrupting systems, fire systems and things. However,

1304
01:16:47,760 --> 01:16:53,800
Speaker 1: vast expanses of what by a relative standard of what

1305
01:16:53,840 --> 01:16:59,880
Speaker 1: goes on in the US would be undisturbed environment, privately owned,

1306
01:17:00,400 --> 01:17:09,320
Speaker 1: but vast expanses of undisturbed landscape while they've habitat, and

1307
01:17:10,360 --> 01:17:16,160
Speaker 1: a pretty stunning array of of of native wildlife. You know. Yeah,

1308
01:17:16,680 --> 01:17:22,519
Speaker 1: it's some tremendous wildlife viewing here an unusual thing. We

1309
01:17:22,560 --> 01:17:24,360
Speaker 1: saw a snake. I had never heard of the blue

1310
01:17:25,400 --> 01:17:31,840
Speaker 1: what's you call the blue indigo? So souped up bringing rattlesnake.

1311
01:17:34,280 --> 01:17:35,160
Speaker 1: It's been interesting