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Speaker 1: Hey everyone, and welcome. It's another episode of Hunting Collective.

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Speaker 1: I've been O'Brien and it's a good one. It's a

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Speaker 1: very good one. Uh. Here, as April rounds out, turkey

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Speaker 1: season is uh in the West at least in full swing.

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Speaker 1: I am in the Black Hills of South Dakota. My

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Speaker 1: good friend Sam Soholt. We are hunting turkeys. We are

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Speaker 1: telling stories, and we are talking about turkey Genitalia big news,

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Speaker 1: some big news regarding turkey Genitali in this podcast, um,

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Speaker 1: so stay tuned for that. But we also tell you

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Speaker 1: a little bit about our successful turkey hunt here in

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Speaker 1: the Black Hills, his Turkey tour, my turkey tour, his

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Speaker 1: public land bus, and more. I'm also joined by Alex

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Speaker 1: and Libby Metcalf. You'll hear more about them in the podcast.

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Speaker 1: They're interesting folks, are both professors uh in the forestry

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Speaker 1: department there at the University of Montana in Missoula. That

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Speaker 1: they do a lot of interesting things around human interaction

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Speaker 1: and behavior in regards to hunting. So we're gonna learn

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Speaker 1: a lot about that. It's a really interesting conversation. Um

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Speaker 1: and I learned a lot. So I think those guys

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Speaker 1: and you'll hear that very soon. But before we get

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Speaker 1: to that, we're gonna talk to you about a new

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Speaker 1: partner for the program, and that partner is Uh, It's

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Speaker 1: really not new at all, but we're gonna treat it

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Speaker 1: as new because it's official. I want to welcome a

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Speaker 1: new partner on the program, and that's Yetti. I used

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Speaker 1: to call him, we say Yetti Coolers, but now it's

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Speaker 1: Yetti because they make so much more than just coolers.

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Speaker 1: And I'm sure everyone listening to this, for most of

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Speaker 1: you will know that I was employed at one time

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Speaker 1: by Jetty and really I owe a lot of where

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Speaker 1: I am today, what I've been able to do with

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Speaker 1: my life and all the blessings I have to that

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Speaker 1: company UM and to the people like Roy and Ryan

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Speaker 1: Caesars who you've heard on this podcast previously. So you'll

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Speaker 1: be hearing a lot from those guys UM on this

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Speaker 1: podcast in the future. But I just want to let

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Speaker 1: everyone know that there as we've announced other partners when

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Speaker 1: I announced them as an official partner of the podcast,

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Speaker 1: and very thankful for them again, UM have played a

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Speaker 1: large part in UM marketing their products, but I believe

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Speaker 1: even outside of that, even outside of being a part

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Speaker 1: of the organization. I believe in their products. I believe

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Speaker 1: in what they stand for. I believe in their films

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Speaker 1: and their content and most of all, their people. And

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Speaker 1: so you'll be hearing again a lot more from them

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Speaker 1: in the weeks and months to come. And I'm very

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Speaker 1: lucky to have Jetty on board. So shout out to

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Speaker 1: everybody down in Austin, Texas. So, without further ado, let's

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Speaker 1: get started. I guess I grew up on an older road.

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Speaker 1: Apart to do the meadals, I always did what I

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Speaker 1: told until I found out that my brand new clothes

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Speaker 1: a game second hand from the rich kids next door.

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Speaker 1: And I grew up baths I it's I grew up.

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Speaker 1: I mean, they have a thousand things inside of my

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Speaker 1: head I wish I ain't seen. And now I just

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Speaker 1: wanted to real bad dream being a lack of coming

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Speaker 1: a lot of the seams. But thank you, Jack Daniels.

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Speaker 1: Hey everyone, I've been O'Brien, and it is four thirty nineteen.

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Speaker 1: Man April got away from as fast, but it's gonna

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Speaker 1: be another good show today. And I'm joined right now

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Speaker 1: by my good friend Sam Sohalt, Man of Public Land

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Speaker 1: bus Fame and Sam, it is what your third or

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Speaker 1: fourth time on the podcast, is that correct, y or

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Speaker 1: something like that? First in the new format, So welcome

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Speaker 1: to I mean it's so different, right, I'm excited to

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Speaker 1: be here. Yeah, you don't even you don't even know

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Speaker 1: what I don't know what's happening right now. I don't

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Speaker 1: um as I like to start all these describe Sam

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Speaker 1: where we are currently. So we are in the Black

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Speaker 1: Hills of South Dakota, chasing Miriam's turkeys. Uh, we're currently

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Speaker 1: a little bit more specific, We're currently sitting in my bus. Um,

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Speaker 1: We've got a pot of coffee brewing. It's kind of

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Speaker 1: spitting rain a little bit outside, a little afternoon shower

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Speaker 1: is rolling in and uh, but yeah, it's just been

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Speaker 1: beautiful weather out here in the Black Hills, and everybody's

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Speaker 1: been in turkeys and got a few on the ground already.

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Speaker 1: And yeah, it's the only way to this seems to

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Speaker 1: be a dead turkey. Yeah, I I've I really enjoyed

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Speaker 1: turkey hunting and this spring has been a good one.

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Speaker 1: I've been Uh, I think we were talking about this morning.

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Speaker 1: This is well. I left for the spring turkey tour

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Speaker 1: on March and today it is the April, so I

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Speaker 1: am twenty four days consecutively into my actual turkey hunting

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Speaker 1: and you need a nap. I need a nap. I'm

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Speaker 1: completely exhausted. And as evidence of your tour, I look

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Speaker 1: across the bus here and I guess what you call

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Speaker 1: like the kitchen area. I don't think this is up

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Speaker 1: to code because there is a a number of turkey

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Speaker 1: feet sticking out like a sideboard in the bus, probably

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Speaker 1: what ten ft at least. Yeah, I think there are

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Speaker 1: five sets of feet in there. It can creepily. It's

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Speaker 1: just the clause they're sticking up there with all the

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Speaker 1: tags on them, so it's a little weird. It's uh,

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Speaker 1: you know, it's kind of a nightmarish, but that's yeah.

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Speaker 1: I mean it was better than having like we got

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Speaker 1: here and they were all just like tucked in a

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Speaker 1: corner and I was like, wow, I don't really want

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Speaker 1: to leave a bunch of turkey feet just laying on

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Speaker 1: the floor. So no, it's nice. It shows you guys

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Speaker 1: have had a good a good damn tour and in

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Speaker 1: a good week this week. But before we get to

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Speaker 1: we're gonna tell some turkey stories in the interview portion

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Speaker 1: of the show. Today, you're gonna hear from Alex and

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Speaker 1: Libby Metcalf, who are a couple of professors from the

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Speaker 1: University of Montana there in Missoula, and so we'll get

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Speaker 1: to them in a second. They aren't turkey hunters, hopefully

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Speaker 1: listen to this. Maybe we'll convince them to go. Um,

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Speaker 1: but we're gonna tell some turkey stories. But first, we

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Speaker 1: had a thing in the woods this morning where we

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Speaker 1: were wondering something that I think every turkey hunter thinks

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Speaker 1: they know about but probably doesn't know much about. And

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Speaker 1: Sam and I were trying to google it with a

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Speaker 1: little to no service, and the Google what we were

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Speaker 1: googling was turkey Genitalia, which at like six am, like

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Speaker 1: in the middle of the woods, is a weird thing

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Speaker 1: to be looking up. It's just a weird thing to

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Speaker 1: be talking about, and recording yourself talking about turkey Genitalia

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Speaker 1: is uh, is not so great. But here we are um,

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Speaker 1: and we both decided that we didn't really know and

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Speaker 1: had never having dismembered many turkeys and never really run

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Speaker 1: into a turkey's penis in in our time taking turkeys

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Speaker 1: apart and hunting turkeys all hunt the turkey rut, as

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Speaker 1: we call it. We all hunted turkey rut. We're always

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Speaker 1: doing that. But for whatever reason, when we ever think

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Speaker 1: about the actual act of mating for weeks, I think about,

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Speaker 1: you know, hands, laying eggs and sitting on the nest.

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Speaker 1: But we don't ever really think about at least that's

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Speaker 1: my guess. A lot of people don't actually think about

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Speaker 1: the act of mating for turkeys. Yeah, I guess not

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Speaker 1: very often. I mean other than like setting up uh decoys,

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Speaker 1: which are my buddy, who was not a hunter, described

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Speaker 1: as turkey sex dolls, very sexy, but setting them up

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Speaker 1: basically looking like a tom or jake is about to

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Speaker 1: breed a hand or like, you know, close to breeding

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Speaker 1: a hand. So that's usually in the context in which

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Speaker 1: we in which we look at it. We had and

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Speaker 1: I haven't spent a lot of time in the past

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Speaker 1: years thinking about how it actually all goes down. And

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Speaker 1: I said, you know, we may have seen videos of

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Speaker 1: turkeys mating, what had never have seen turkeys try to

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Speaker 1: mate with my decoys, and I've never seen them doing

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Speaker 1: the thing in the wild. Um, And so I did

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Speaker 1: a little I did a little research, a little reading

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Speaker 1: to educate everyone on you know, following the courtship dance,

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Speaker 1: which we're very familiar with, the active mating, And I'm

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Speaker 1: gonna read a little bit of this. Ah, the male

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Speaker 1: we're going and you know, you kind of can picture

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Speaker 1: the male hopping on the female. Uh, the tom hops

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Speaker 1: on his lady kind of lets his wings down and

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Speaker 1: gets ready for the thing. But the thing that I

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Speaker 1: didn't know is that the sperm is transferred from the

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Speaker 1: male's cloaca to the female's kluwake, so they both basically

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Speaker 1: I have heard it described as like a general opening,

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Speaker 1: so which is an easier way than saying cloaca, but

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Speaker 1: this says like the kloaka is a name for the

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Speaker 1: event that leads to the Turkey sex organs. So they

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Speaker 1: put their cloaks together and that acts as a sort

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Speaker 1: of a channel which too copulate, a conduct for copulation.

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Speaker 1: The Turkeys, they'll place their events next to each other

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Speaker 1: in order to allow the transfers of sperm um. So,

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Speaker 1: so now we know. The more you know, the more

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Speaker 1: you know that little rainbow star thing. So ill of

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Speaker 1: you listening out there, you uh, it's good you have

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Speaker 1: an understanding, a better understanding of turkey sex. Turkey sex

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Speaker 1: that started off. We you know, i'd like to say

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Speaker 1: you're welcome to the listenership, but I don't think I

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Speaker 1: think they we just forced this on them. They probably didn't,

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Speaker 1: They probably didn't want it, probably not, but I hope

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Speaker 1: that they're interested. Really hooked him into service, now, you know. Ah,

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Speaker 1: So moving on. You're a South Dakota native, so you've

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Speaker 1: killed in your life many a turkey. So I I mean,

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Speaker 1: I've killed some turkeys, but I actually didn't start turkey

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Speaker 1: hunting until twelve, was the first year. So I didn't

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Speaker 1: grow up doing it. Um never put in for tags.

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Speaker 1: I just chased water fowl and deer and uh yeah,

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Speaker 1: it wasn't until quite recently that I got in, like

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Speaker 1: got way more into it. Well, and you're and that's

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Speaker 1: and you've rebbed the engine being on a three week

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Speaker 1: long turkey tour, going from that to that, and so

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Speaker 1: I've got seven years yeah doing this. I got four

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Speaker 1: more days here helping just shoot photos and helping guys

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Speaker 1: get birds, and then I've got one archery hunt in

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Speaker 1: eastern South Dakota that I'm gonna try to pull off.

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Speaker 1: And then towards the end of May. I'm meeting up

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Speaker 1: with the Vortex guys, the Hush guys, Born and Raised,

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Speaker 1: and the hunting public and we're all going to chase

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Speaker 1: birds in Wisconsin for one one more grand finale on

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Speaker 1: the air. Yeah, I know we're I'm on my own

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Speaker 1: little tour. It's not quite as long as yours. Um.

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Speaker 1: I don't have a bus, and my wife would probably

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Speaker 1: leave me if if I went for that long, but

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Speaker 1: she knows I want to and she knows that if

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Speaker 1: I could, I would. Um. This is we did a

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Speaker 1: little Texas and then took a tour break. Is it

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Speaker 1: a tour if it takes a break. I think you

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Speaker 1: can take a tour break. I don't know if you

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Speaker 1: can consider it like I feel like Texas was a

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Speaker 1: trip and now you're on a tour like you did

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Speaker 1: a like it was like a like a pre yeah

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Speaker 1: pre tour. Yeah trip, I'll give you that. Uh did

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Speaker 1: this one. I'm gonna go back to Montana, hunt in

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Speaker 1: eastern Montana, drive down to Idaho to do the b

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Speaker 1: h A Andy View. So if you're um, well, by

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Speaker 1: the time you hear this, it's already over. So it

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Speaker 1: was a great time. I had a great time. Um,

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Speaker 1: and then we'll be about the time this airs will

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Speaker 1: be rolling over to Idaho to do a couple of

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Speaker 1: days hunting. Well. I think the Hush guys will be

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Speaker 1: in camp there with me and and possibly even Brian

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Speaker 1: Callahan will make an appearance. And then I'll be rolling

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Speaker 1: out to Oregon Um with benchmate and Federal to do

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Speaker 1: some running around and then back to Montana to hunt

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Speaker 1: up in northern Montana filling on a tag, and then back.

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Speaker 1: That's a pretty solid tour in a short period of time.

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Speaker 1: It's a lot of miles. Yeah, it's it's quite the

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Speaker 1: quite the it's like a hunt and then a long

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Speaker 1: there's like a ten hour drive and then hunt in

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Speaker 1: a ten hour drive. But living in the West, I

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Speaker 1: mean you can't. You do it in the East too,

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Speaker 1: But if you really want to have to see some

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Speaker 1: you know, see the West, the Inner Mountain West. I mean,

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Speaker 1: this is a damn good way to do it, for sure,

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Speaker 1: And I mean a really cool time of year to

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Speaker 1: do it, Like everything is waking back up. And I

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Speaker 1: don't know, like I love the fall because it's all

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Speaker 1: hunting season, but there's something about spring that is just yeah,

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Speaker 1: just awesome. Yeah, yeah, this time of year, for sure.

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Speaker 1: How much of Black Hills history do you have in

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Speaker 1: your head there? Any big? Not much. I grew up

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Speaker 1: on the east side of the state. Different. Yeah, like

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Speaker 1: I've you know, traveled out here for sports and different

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Speaker 1: trips or whatever, but never I don't know much about

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Speaker 1: the Black Hills. I probably should know more. I learned

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Speaker 1: that it was a look like it was named the

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Speaker 1: Black Hills. There's la Coda tribe. I thought, because there's

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Speaker 1: so many pine trees on the hills that they look black,

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Speaker 1: and that's why it was named the Black Hills. That

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Speaker 1: makes sense. That's about as much as I got. But

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Speaker 1: and it was also uh Custer made like a Black Hills.

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Speaker 1: He made a big trip that was written about a

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Speaker 1: lot here to the Black Hills, which popularized the area.

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Speaker 1: And then um, then the gold Rush kind of found

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Speaker 1: its way here. And and for the preceding decades it

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Speaker 1: was very mining and mining centric, extraction centric. But now

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Speaker 1: it seems to be tourism centric, yes for sure. Yeah,

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Speaker 1: and for good reason. Yeah, it's just a really cool area.

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Speaker 1: I mean, even though it's become I mean it's it's

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Speaker 1: still not that populated out here. I mean, there's there's, um,

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Speaker 1: there's a lot of room to roam and a ton

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Speaker 1: of public land out here. And just like you know,

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Speaker 1: like the amount of wildlife that you see, whether it

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Speaker 1: be turkeys or deer or bison or elk or whatever.

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Speaker 1: I mean, just on our drive to go hunt this morning,

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Speaker 1: which whitetail, mule deer, bison, elk and then finally turkeys. Yeah,

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Speaker 1: not to call anybody out, but a member of your

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Speaker 1: party that you've gathered here, you have a lot of

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Speaker 1: people in camp are very popular, um, member of your party.

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Speaker 1: We're not gonna say who it was. Came back. It's

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Speaker 1: not from that's been a lot of time out west.

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Speaker 1: It's a good hunter, but that's spent a lot of

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Speaker 1: time out west. Came back and was like politely asking

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Speaker 1: what bear shit looked like? Well, first, yes, are there

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Speaker 1: bears out here? That's a long way to get around. Yeah,

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Speaker 1: And I said yeah, I mean not a lot, but

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Speaker 1: there are bears out here, and he goes, ah, I saw,

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Speaker 1: I'm pretty sure we saw a bunch of bear shit.

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Speaker 1: It's like then you asked, you know, what did it

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Speaker 1: look like or was it pellets? And you know, I said, well, yeah,

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Speaker 1: bear shits kind of looks a little bit like human

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Speaker 1: ship and you'll see a lot of You said something

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Speaker 1: like you'll see a lot of berries. And I said, well,

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Speaker 1: was it. He's like yeah, but didn't kind of look

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Speaker 1: like that. I said, was it pellets. He's like, yeah,

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Speaker 1: like big pellets. That was definitely. So they did run

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Speaker 1: into a pile about like a lot of elkhit so

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Speaker 1: they there's a lot. They say all that to say

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Speaker 1: there's a lot of elk out here. Yeah. Well, the

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Speaker 1: best is that he asked another guy who's not from

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Speaker 1: out west, and that guy told him that was my favorite.

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Speaker 1: He was like. The dude I was with was like, oh,

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Speaker 1: that's for sure. Bear shit, Ah, I can't believe there's

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Speaker 1: herds of bears roaming the South Dakota els unbelievable, terrifying

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Speaker 1: out here the Black Hills National Forest Herds of bears

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Speaker 1: twelve deep. Um, but yeah, I mean you had a

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Speaker 1: big camp out here. It's cool to be a part of.

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Speaker 1: And we got to roam around the Black Hills National Forest. Now, um,

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Speaker 1: we're not gonna give any hotspots away, but I did

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Speaker 1: ask Alexon let me Metcalf to give some hotspots away

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Speaker 1: at the end of the show. So you will get

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Speaker 1: a hot spot. Uh, kind of a half ass hot spot,

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Speaker 1: but nonetheless you'll get one. Um. But just describing how

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Speaker 1: we approached this morning and how I approached just coming

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Speaker 1: over here from Montana, literally just drove, looked at my

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Speaker 1: onyx maps, looked where it was green for National Forest,

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Speaker 1: and drove around and got out where I thought turkeys

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Speaker 1: might being called hiked hiked in a little bit called

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Speaker 1: nothing there, got to go back in the truck, drive

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Speaker 1: a little more cover, a ton of country glass and

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Speaker 1: for birds calling, trying to get a response. Um. And

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Speaker 1: that's like is as free as a hunter gets. And

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Speaker 1: you know, millions of acres here for us to traverse

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Speaker 1: and little to know, you know other than little small

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Speaker 1: pockets of residential areas and private land and some other

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Speaker 1: controlled access points. It was we were free to roam. Yeah.

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Speaker 1: So last year was my first year hunting turkeys in

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Speaker 1: the Black Hills and UH kind of was asking around,

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Speaker 1: you know, like, what are some good areas to go look?

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Speaker 1: And Uh, a buddy of mine was like, man, just everywhere,

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Speaker 1: Like the turkeys are fairly evenly distributed throughout the hills.

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Speaker 1: So he's like, if it looks like good turkey country.

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Speaker 1: There's chances are there's turkeys in there, so just get

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Speaker 1: out caught, like you said, under your way in. You know,

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Speaker 1: it's like, if it looks like like good turkey country,

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Speaker 1: there's probably gonna be a turkey and they might not

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Speaker 1: may or may not respond, but there's probably gonna be

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Speaker 1: some birds in there. And uh, it's a it's a

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Speaker 1: good way to do it, just to locate something some critters. Yeah,

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Speaker 1: and I was thinking about, um, you know, going to

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Speaker 1: b h A rendezvous being a part of that both

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Speaker 1: you know, your drive, you're we're in the public land

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Speaker 1: bus like by with it is something that you know,

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Speaker 1: we both and we're not alone, like care a whole

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Speaker 1: lot about It's like, you know, you'll will tell the

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Speaker 1: story of this bird we killed. But after that we

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Speaker 1: had killed this turkey. This morning, we had like a

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Speaker 1: three hour session of just sitting in the National forest,

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Speaker 1: drinking a beer, chopping up a turkey, um, having lunch,

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Speaker 1: listening to music. Took a nap. It's like and it

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Speaker 1: was we don't know that land. We didn't pay for

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Speaker 1: it at least so for other taxes. Yeah, now that

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Speaker 1: was pretty amazing. It's it's the idea that that's accessible

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Speaker 1: is um still stuns me. Even though it's something that

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Speaker 1: I've devoted a lot of time and energy and a

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Speaker 1: big part of my life too. It's still it like

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Speaker 1: brings me great joy and passion to know that that exists,

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Speaker 1: and it's does every time that I do it. I

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Speaker 1: feel that way. I think what always gets me is

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Speaker 1: it's it's just hard for me when I start to

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Speaker 1: really sit down and think about it, like how much

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Speaker 1: land there is and how freely accessible it is. It's

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Speaker 1: just hard for me to wrap my head around. Like

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Speaker 1: like today we probably covered let's say forty acres you know,

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Speaker 1: maybe maybe forty to sixty acres of ground. Uh, there's

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Speaker 1: sixty million acres of just federally managed land. So like

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Speaker 1: just trying to wrap your head around, like the how

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Speaker 1: much exploring you can do, like without any cost other

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Speaker 1: than you know, a hunting license, but if you're just

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Speaker 1: hiking or whatever. Um, just being able to go out

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Speaker 1: and use that as a as a resource is pretty amazing.

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Speaker 1: I can't like that idea, you know. And again I

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Speaker 1: was text with Lanta from Bha this morning. I just

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Speaker 1: want I was like, dude, I just want to tell

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00:18:45,080 --> 00:18:50,320
Speaker 1: you that that idea above politics, above all of all

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Speaker 1: our disagreements around the government, and it's working like above that.

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Speaker 1: Like there's nothing that I've experienced the combination of hunting,

356
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Speaker 1: which I love with the freedom of running around in

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Speaker 1: a place that you contribute to and also benefit from

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Speaker 1: in a way that is indescribable for me. If somebody's

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Speaker 1: never experienced it. It is just like I said, every

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Speaker 1: time that I do it, I get something else from

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Speaker 1: It never gets old. Ever, it doesn't matter where I am.

362
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Speaker 1: Turkey's elk, deer, squirrels, doesn't matter. It just doesn't matter. Um.

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Speaker 1: And it's great, It's great. It's in it's raining outside.

364
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Speaker 1: Is here that last time you were on the bus,

365
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Speaker 1: I think for the podcast it was raining, weren't it was?

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Speaker 1: We were actually in the Black South Dakota, the Black Hills.

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Speaker 1: We were um, you know, I think I was on

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Speaker 1: one in Big Sky. But the one previous we were

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Speaker 1: in we were in the Black Hills and it was

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Speaker 1: pouring and there was flooding in the in the aun

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Speaker 1: of the land bus. That was it was crazy. Well,

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Speaker 1: we're gonna get to the interview portion of the show

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Speaker 1: here in a minute. But we're also going to tell

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Speaker 1: you this story. This turkey we killed this morning. Um,

375
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Speaker 1: I've been here. I rolled in last night, like I said,

376
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Speaker 1: just just rolling through. Stopped, got my license, got my tag,

377
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Speaker 1: made sure all that was square. Came rolling through the

378
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Speaker 1: Black Hills, literally just driving around, calling, found a found

379
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Speaker 1: a bird, roosted him. There's a couple of like two

380
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Speaker 1: or three dealers and a group of hands that I

381
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Speaker 1: had roosted, marked them on the old Onyx maps. Came

382
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Speaker 1: back here, I had some beers, had a little food.

383
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Speaker 1: I went sleep, slept for about three three damn hours,

384
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Speaker 1: got up at three thirty, pulled out of here at

385
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Speaker 1: four am, rolled over to our spot and they were

386
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Speaker 1: exactly where we left him. And I thought, now you

387
00:20:37,520 --> 00:20:38,960
Speaker 1: can tell me, Sam, but I thought we were in

388
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Speaker 1: the money. Yeah, I mean, looking at the map and everything,

389
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Speaker 1: it seemed like we were. It seemed like we were

390
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Speaker 1: in the right spot, like a crossroad between like a

391
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Speaker 1: little two tap track trail and a cut through the timber.

392
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Speaker 1: So it was like a good area for them to

393
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Speaker 1: pitch down to and strut down. It was the It

394
00:20:55,080 --> 00:20:58,720
Speaker 1: was a cross section of um, a little trail and

395
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Speaker 1: then a power line and so we were kind of

396
00:21:01,480 --> 00:21:03,000
Speaker 1: right at the acts of that. So we put our

397
00:21:03,040 --> 00:21:04,840
Speaker 1: decoys out. We were, you know, like said, a couple

398
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Speaker 1: hundred yards from the roost tree. They were hammering on

399
00:21:08,000 --> 00:21:11,359
Speaker 1: the roost um. We had them responding a little bit

400
00:21:11,359 --> 00:21:13,920
Speaker 1: as they were starting to fly down and they hit

401
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Speaker 1: the ground and uh, they didn't remember. They weren't totally

402
00:21:17,080 --> 00:21:18,879
Speaker 1: quiet when they hit the ground, but they certainly didn't

403
00:21:18,880 --> 00:21:22,080
Speaker 1: fly in our direction. They they pitched off away from

404
00:21:22,200 --> 00:21:25,199
Speaker 1: us to a bench that we later discovered that was

405
00:21:25,560 --> 00:21:28,159
Speaker 1: I would have been to our north. You know, they

406
00:21:28,280 --> 00:21:31,080
Speaker 1: sent and then their goblin instead of two hundred yards away,

407
00:21:31,119 --> 00:21:35,440
Speaker 1: probably three hundred yards away, which if you're a tricky hunter,

408
00:21:36,200 --> 00:21:39,200
Speaker 1: you understand that disappointment. Like you're you go to sleep

409
00:21:39,240 --> 00:21:42,959
Speaker 1: thinking about having the pitch off. See the decoys come

410
00:21:43,040 --> 00:21:45,280
Speaker 1: running and you crack them. Yeah, I mean, like the

411
00:21:45,280 --> 00:21:47,399
Speaker 1: the textbook hunts, you just get in tight under the

412
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Speaker 1: roost and they just fly on down right to you. Bam. Yeah,

413
00:21:52,440 --> 00:21:55,359
Speaker 1: you had one where you it's a barely hit the ground,

414
00:21:55,880 --> 00:21:58,960
Speaker 1: didn't even have any decoys out, and he yeah, he

415
00:21:59,040 --> 00:22:03,400
Speaker 1: pitched down. This was the last wed this day, yeah,

416
00:22:03,480 --> 00:22:07,119
Speaker 1: week ago. Um, Yeah, pitched down and he had not

417
00:22:07,200 --> 00:22:10,840
Speaker 1: even slowed down yet from his like landing run and

418
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Speaker 1: I shot him. So that hunt lasted from about five

419
00:22:14,240 --> 00:22:19,240
Speaker 1: seconds from fly down to we did pretty good today,

420
00:22:19,280 --> 00:22:22,760
Speaker 1: but we're not that lucky. Um. So yeah, they pitched

421
00:22:22,800 --> 00:22:25,560
Speaker 1: off to the north to which later like both seeing

422
00:22:25,600 --> 00:22:28,000
Speaker 1: it in person and looking at the map, they're like, oh, yeah,

423
00:22:28,040 --> 00:22:30,400
Speaker 1: that makes sense they should be that. That's so good,

424
00:22:30,480 --> 00:22:33,639
Speaker 1: that's where they would fly. Yes, yea, yeah, Now you

425
00:22:33,640 --> 00:22:36,639
Speaker 1: know that's again the disadvantage to not knowing the terrain

426
00:22:36,680 --> 00:22:38,639
Speaker 1: in the country. If we had hunted those birds for

427
00:22:38,680 --> 00:22:41,600
Speaker 1: a couple of days or we're hunted this area, we

428
00:22:41,600 --> 00:22:43,960
Speaker 1: would have kind of seen that country and knowing, hey,

429
00:22:43,960 --> 00:22:45,520
Speaker 1: when they pitch off, they're going to pitch to this

430
00:22:45,560 --> 00:22:48,239
Speaker 1: bench and then from that bench they can access this

431
00:22:48,240 --> 00:22:51,439
Speaker 1: little field. It's a little private, like a private so

432
00:22:51,480 --> 00:22:53,080
Speaker 1: we were kind of like button up against this piece

433
00:22:53,080 --> 00:22:55,239
Speaker 1: of private whether it was we thought either like a

434
00:22:55,240 --> 00:22:57,400
Speaker 1: water trough or a feed or something that the shirkey's

435
00:22:57,480 --> 00:23:00,600
Speaker 1: like to hit. And so you know, I thought in

436
00:23:00,640 --> 00:23:03,280
Speaker 1: the morning was they're gonna, you know, either fly that

437
00:23:03,320 --> 00:23:05,880
Speaker 1: way or pitch down to this power line and access

438
00:23:06,359 --> 00:23:09,600
Speaker 1: this anywhere they want to go from this this area.

439
00:23:10,320 --> 00:23:13,840
Speaker 1: So they they pitched down, and we decided to go

440
00:23:13,920 --> 00:23:15,520
Speaker 1: up on the ridge above them. And you tell them, why,

441
00:23:15,520 --> 00:23:18,160
Speaker 1: why do you think of that? Getting above turkeys and

442
00:23:18,320 --> 00:23:21,720
Speaker 1: this this mountain, this this mountains terrain is a is

443
00:23:21,720 --> 00:23:24,960
Speaker 1: a big deal. So if you if you can get

444
00:23:24,960 --> 00:23:27,199
Speaker 1: above the turkeys, it's a lot easier to call them in.

445
00:23:27,320 --> 00:23:29,720
Speaker 1: And actually I just learned this this year because I've

446
00:23:29,720 --> 00:23:31,600
Speaker 1: never hunted, mean other than last year hunting out here

447
00:23:31,600 --> 00:23:33,639
Speaker 1: a little bit, but just kind of winging it, but

448
00:23:33,800 --> 00:23:35,800
Speaker 1: hanging out with the guys from the hunting public and

449
00:23:35,800 --> 00:23:39,840
Speaker 1: and hunting you know, mountainous areas like Arkansas and um,

450
00:23:39,920 --> 00:23:43,320
Speaker 1: some more hilly terrain down in Tennessee. UM. Just like

451
00:23:43,640 --> 00:23:45,920
Speaker 1: Aaron Warburton, I hunted with him a lot for those

452
00:23:45,920 --> 00:23:48,399
Speaker 1: first two weeks, and he just kept kind of driving

453
00:23:48,400 --> 00:23:49,840
Speaker 1: into my head that if you're gonna go try to

454
00:23:49,880 --> 00:23:51,600
Speaker 1: call in a turkey in hilly terrain, you want to

455
00:23:51,640 --> 00:23:54,280
Speaker 1: try to get above them because if they're having to

456
00:23:54,320 --> 00:23:58,360
Speaker 1: come up over a rise, they're gonna come further in searching.

457
00:23:58,560 --> 00:24:00,359
Speaker 1: Because if they if you get down own hill of

458
00:24:00,400 --> 00:24:02,920
Speaker 1: them and try to call them in. Turkeys have such

459
00:24:02,960 --> 00:24:06,000
Speaker 1: good eyesight that when they're coming down in Like if

460
00:24:06,000 --> 00:24:08,760
Speaker 1: you have decoys, it's one thing, but still like their

461
00:24:09,160 --> 00:24:12,879
Speaker 1: way that the Yeah, their eyesight is so good that

462
00:24:12,880 --> 00:24:15,320
Speaker 1: they're easily going to see what's going on ahead of

463
00:24:15,359 --> 00:24:18,480
Speaker 1: them way further. So if you can kind of take

464
00:24:18,480 --> 00:24:21,200
Speaker 1: away some of their advantage and get above them, they'll

465
00:24:21,200 --> 00:24:25,359
Speaker 1: come marching right up to you. Yeah, man, I think it.

466
00:24:25,359 --> 00:24:27,720
Speaker 1: It makes all the sense in the world. And having

467
00:24:27,760 --> 00:24:29,680
Speaker 1: hunted turkeys, I mean you've done in the last three weeks,

468
00:24:29,680 --> 00:24:31,600
Speaker 1: but you turkeys is always different. You see how they

469
00:24:31,680 --> 00:24:34,640
Speaker 1: used to rain. You kind of learn to read where

470
00:24:34,640 --> 00:24:36,199
Speaker 1: they're going to go. And I think both of us

471
00:24:36,280 --> 00:24:39,639
Speaker 1: kind of today made a bunch of really good calls

472
00:24:39,680 --> 00:24:41,320
Speaker 1: about like this is where they're gonna go. Let's set

473
00:24:41,400 --> 00:24:43,040
Speaker 1: up here. They're gonna want to use the spine to

474
00:24:43,119 --> 00:24:45,919
Speaker 1: come to access this open spot. If we put the

475
00:24:45,960 --> 00:24:50,040
Speaker 1: decoys here, they'll see them first, pull them in, and

476
00:24:50,119 --> 00:24:52,800
Speaker 1: it's it's it's good to know, like when you make

477
00:24:52,840 --> 00:24:54,919
Speaker 1: that guess right and then the turkey does what it

478
00:24:54,960 --> 00:24:58,199
Speaker 1: needs to do, then the turkey dies. Right. Well, we

479
00:24:58,240 --> 00:25:00,680
Speaker 1: did was make a lot of right guesses. It's a

480
00:25:01,320 --> 00:25:04,600
Speaker 1: turkey's fault. Yeah, I blame them any time it goes wrong,

481
00:25:04,600 --> 00:25:06,199
Speaker 1: it's always their fault. They would have been where they

482
00:25:06,200 --> 00:25:09,120
Speaker 1: were supposed to be, we would have been just fine. Yeah,

483
00:25:09,119 --> 00:25:11,720
Speaker 1: because then when we yeah, when we looped up to

484
00:25:11,720 --> 00:25:15,359
Speaker 1: get above them, both of us, we're looking at the

485
00:25:15,400 --> 00:25:19,120
Speaker 1: map and looking down and saw the bench where eventually

486
00:25:19,160 --> 00:25:21,640
Speaker 1: we spotted them. But we were looking at that like, oh,

487
00:25:21,760 --> 00:25:24,440
Speaker 1: let's get to that bench and set up and call again,

488
00:25:24,480 --> 00:25:26,680
Speaker 1: because like they're they're going to use it. That whole

489
00:25:26,800 --> 00:25:29,359
Speaker 1: all those ridges were all scratched up, I mean, tons

490
00:25:29,400 --> 00:25:31,760
Speaker 1: of turkey sign and that whole thing. So assuming that

491
00:25:31,760 --> 00:25:34,120
Speaker 1: that flock of turkeys was just bouncing around in there

492
00:25:34,480 --> 00:25:36,919
Speaker 1: day after day using using that area, and it was

493
00:25:37,400 --> 00:25:38,879
Speaker 1: really I thought it was a kind of a micro

494
00:25:39,800 --> 00:25:42,880
Speaker 1: area that they were running in and they had they

495
00:25:42,920 --> 00:25:45,280
Speaker 1: had they had its circle like a Nascar right, I mean,

496
00:25:45,440 --> 00:25:47,160
Speaker 1: it just looked kind of like they were just using

497
00:25:47,200 --> 00:25:50,560
Speaker 1: the same kind of three fingers at a ridge to travel.

498
00:25:50,880 --> 00:25:53,199
Speaker 1: And so yeah, I mean we looked like, if we

499
00:25:53,200 --> 00:25:55,560
Speaker 1: can just get down near that bench, they're gonna either

500
00:25:55,680 --> 00:25:57,520
Speaker 1: end up there or come off the field and hit

501
00:25:57,600 --> 00:25:59,520
Speaker 1: us if we call, we'll call them in. When we

502
00:25:59,600 --> 00:26:02,439
Speaker 1: got oh, maybe a hundred yards above that bench, and

503
00:26:02,440 --> 00:26:04,800
Speaker 1: I'd set my shotgun down to get the call out

504
00:26:04,840 --> 00:26:07,159
Speaker 1: to hit it to see, um if we get him

505
00:26:07,160 --> 00:26:10,560
Speaker 1: to respond, and I look up and there goes the neighborhood.

506
00:26:11,880 --> 00:26:14,480
Speaker 1: So it turns out, Uh, they were all hanging out

507
00:26:14,560 --> 00:26:17,480
Speaker 1: on that exact bench there, exactly where we thought they were.

508
00:26:18,080 --> 00:26:20,720
Speaker 1: They just were there too soon, and so it is

509
00:26:20,760 --> 00:26:23,879
Speaker 1: their fault. Yeah, it's their fault. We didn't kill. Some

510
00:26:23,960 --> 00:26:27,000
Speaker 1: may also say that we were there too late. Those

511
00:26:27,040 --> 00:26:30,320
Speaker 1: people would be wrong. They weren't there, They didn't. It's

512
00:26:30,400 --> 00:26:34,280
Speaker 1: up to us to decide. Now, Yeah, we just it's

513
00:26:34,560 --> 00:26:37,359
Speaker 1: you know, if you're if you're veteran turkenar and you

514
00:26:37,400 --> 00:26:40,000
Speaker 1: understand this scenario, it's like the running gun to sit

515
00:26:40,119 --> 00:26:44,119
Speaker 1: and get type of attitude, Like you could know that

516
00:26:44,160 --> 00:26:46,639
Speaker 1: bench is great and get five yards from it and

517
00:26:46,680 --> 00:26:49,200
Speaker 1: sit and just call for the next three hours. Or

518
00:26:49,240 --> 00:26:51,520
Speaker 1: you could bump up in there get tight with him.

519
00:26:51,720 --> 00:26:53,399
Speaker 1: And if you're gonna bump around and get tight with him,

520
00:26:53,400 --> 00:26:56,200
Speaker 1: you know you're gonna spook him every once in a while.

521
00:26:56,720 --> 00:26:59,119
Speaker 1: And for us too, you know, we didn't know it.

522
00:26:59,440 --> 00:27:02,080
Speaker 1: We had those birds, like we had all day to hunt,

523
00:27:02,400 --> 00:27:05,080
Speaker 1: and we knew where those birds were and so if

524
00:27:05,119 --> 00:27:07,199
Speaker 1: if we you know, knowing, and you wake up, if

525
00:27:07,240 --> 00:27:10,679
Speaker 1: we screwped those birds were literally is starting over again,

526
00:27:10,680 --> 00:27:14,119
Speaker 1: like we weren't even here. So we did exactly that.

527
00:27:15,880 --> 00:27:19,600
Speaker 1: And yeah, we accomplished all that by and I'm gonna say,

528
00:27:19,600 --> 00:27:22,200
Speaker 1: shout out, you know, shout out the Mike and Ikes. Yes,

529
00:27:22,280 --> 00:27:28,720
Speaker 1: not a sponsor, but I mean, h yeah, clush, we

530
00:27:28,920 --> 00:27:32,639
Speaker 1: ate we've drowned our sorrows in an entire box, fucking

531
00:27:32,640 --> 00:27:35,320
Speaker 1: Mike and Ikes. I mean, I'm a snack guy for sure,

532
00:27:35,680 --> 00:27:38,120
Speaker 1: and so I always have something in my bag. And

533
00:27:38,400 --> 00:27:41,000
Speaker 1: after we buggered those turkeys up, we just sat down

534
00:27:41,000 --> 00:27:43,280
Speaker 1: on the hillside and shared a box of the whole box,

535
00:27:43,320 --> 00:27:48,280
Speaker 1: whole share able size boxes. That's good. It's good to

536
00:27:48,280 --> 00:27:51,320
Speaker 1: get that going. That's turkey on the forty Fox. That's

537
00:27:51,359 --> 00:27:53,960
Speaker 1: ticking in for it. Now. I want to make a

538
00:27:54,040 --> 00:27:56,159
Speaker 1: detour to something that we also another thing that we

539
00:27:56,200 --> 00:27:59,000
Speaker 1: discovered and and this this we can call this segment

540
00:27:59,080 --> 00:28:04,400
Speaker 1: not a sponsor. That's the segment. We had what I'll

541
00:28:04,400 --> 00:28:08,080
Speaker 1: call a revelation while we after we shot this turkey

542
00:28:08,280 --> 00:28:11,000
Speaker 1: and we were having a meal, we discovered this thing

543
00:28:11,080 --> 00:28:16,879
Speaker 1: called oh meals. Yeah, oh meals. Tell people about oh Meals. Again,

544
00:28:16,960 --> 00:28:20,520
Speaker 1: not a sponsor, but if you're listening Oh Meals, bring

545
00:28:20,560 --> 00:28:23,600
Speaker 1: it on because you have a fantastic product. Yeah, it

546
00:28:23,640 --> 00:28:26,000
Speaker 1: was pretty amazing, Like I didn't believe it at first.

547
00:28:26,960 --> 00:28:29,479
Speaker 1: So you it comes in looks like a you know,

548
00:28:29,520 --> 00:28:32,960
Speaker 1: any other freeze dried meal package, except when you open

549
00:28:33,000 --> 00:28:35,919
Speaker 1: it up, there's a heating element in a little bag.

550
00:28:35,960 --> 00:28:38,240
Speaker 1: There's the food in a little bag, and then obviously

551
00:28:38,280 --> 00:28:39,719
Speaker 1: the bag that you cook it in. And so you

552
00:28:39,720 --> 00:28:42,400
Speaker 1: open the heating element, you slip it into the bag

553
00:28:42,440 --> 00:28:45,600
Speaker 1: with the food pouch, and then you pour in three

554
00:28:45,640 --> 00:28:48,920
Speaker 1: to five ounces of any liquid. It said. Basically, it

555
00:28:48,920 --> 00:28:50,959
Speaker 1: just needs to boil liquid, but then the heating element

556
00:28:51,000 --> 00:28:55,240
Speaker 1: activates and in three to five minutes you have it's

557
00:28:55,280 --> 00:28:56,880
Speaker 1: like a little hot hand. It takes a little bit

558
00:28:56,920 --> 00:28:59,200
Speaker 1: for that heating element to get activated, and we learned

559
00:28:59,240 --> 00:29:01,960
Speaker 1: that because we cooked two of them. But once that

560
00:29:02,000 --> 00:29:06,120
Speaker 1: gets going, that water is boiling and steaming in seconds

561
00:29:06,680 --> 00:29:09,120
Speaker 1: and then yeah, a little bit later you have hot food,

562
00:29:09,240 --> 00:29:13,280
Speaker 1: hot food, no boiling water. Sorry jet boil Yeah, I

563
00:29:13,280 --> 00:29:15,400
Speaker 1: mean if you sponsored, will go back to you jet boil.

564
00:29:17,120 --> 00:29:20,160
Speaker 1: But oh meals man, Yeah, that's pretty slick, pretty delicious.

565
00:29:20,680 --> 00:29:23,520
Speaker 1: It saves any any work on heating up water. You

566
00:29:23,520 --> 00:29:26,680
Speaker 1: sit there and watch the little bag gyrade until your

567
00:29:26,760 --> 00:29:30,440
Speaker 1: hash browns are done, and it's quite a bit less water. Uh,

568
00:29:30,480 --> 00:29:32,840
Speaker 1: Like you know, usually you're like on a on a

569
00:29:32,920 --> 00:29:36,400
Speaker 1: normal freeze dry meal, you're gonna use a whatever. It's

570
00:29:36,400 --> 00:29:39,560
Speaker 1: like two cups or you know, it's it's whatever, twelve

571
00:29:39,600 --> 00:29:41,720
Speaker 1: to fourteen ounces of water instead of three to five.

572
00:29:42,760 --> 00:29:46,080
Speaker 1: That's true. But yeah, I mean I think, um, that's

573
00:29:46,120 --> 00:29:47,840
Speaker 1: one of the things that take away from Miss Hunt

574
00:29:48,040 --> 00:29:51,080
Speaker 1: is oh meals. So shout out thanks, oh meals. Might

575
00:29:51,120 --> 00:29:55,240
Speaker 1: have to send them a message. Yeah, life on the road,

576
00:29:55,800 --> 00:29:58,160
Speaker 1: Life on the road, oh meals. I felt like, well,

577
00:29:58,160 --> 00:30:01,200
Speaker 1: I felt very like accomplished, like we were like I

578
00:30:01,240 --> 00:30:04,440
Speaker 1: had achieved something when I had cooked my Southwest rice

579
00:30:04,480 --> 00:30:08,720
Speaker 1: and chicken meal. I just felt less hungry when I

580
00:30:08,840 --> 00:30:11,080
Speaker 1: ate the hash browns. Yeah, a little salty, a little

581
00:30:11,280 --> 00:30:13,640
Speaker 1: little twitch in my left eye from the salt. Yeah,

582
00:30:13,800 --> 00:30:16,760
Speaker 1: But other than that, I felt I felt real good.

583
00:30:16,760 --> 00:30:18,400
Speaker 1: All right. Back to our Turkey star. It's like a

584
00:30:18,440 --> 00:30:21,400
Speaker 1: non linear turkey story, that's all right. It's like drag

585
00:30:21,440 --> 00:30:22,880
Speaker 1: people along. It's like the show This is Us. You

586
00:30:22,920 --> 00:30:25,920
Speaker 1: ever seen that show? That's not okay, Well let's keep

587
00:30:25,960 --> 00:30:30,520
Speaker 1: moving on. If you've seen it, you know what's up. Um.

588
00:30:30,560 --> 00:30:34,080
Speaker 1: So we we booger the turkeys, and we decided that

589
00:30:34,160 --> 00:30:37,760
Speaker 1: it's not worth sticking around jacking with turkeys that have

590
00:30:37,800 --> 00:30:40,640
Speaker 1: already putted at us and given given us the business. Yeah,

591
00:30:40,680 --> 00:30:42,840
Speaker 1: the good news is those birds, like we did hear

592
00:30:42,920 --> 00:30:45,800
Speaker 1: him gobble again about ten minutes later way down the ridge,

593
00:30:45,920 --> 00:30:49,200
Speaker 1: and but we still decided just to bail out of there. Um,

594
00:30:49,280 --> 00:30:51,840
Speaker 1: let him calm down and then possibly circle back around

595
00:30:51,920 --> 00:30:56,080
Speaker 1: into that area and try to that's something in that's right, um.

596
00:30:56,120 --> 00:30:58,960
Speaker 1: And so we got in the truck and we just

597
00:30:59,000 --> 00:31:01,280
Speaker 1: started covering terrain, and like we just knew that west

598
00:31:01,360 --> 00:31:06,320
Speaker 1: and like basically southwest was a giant chunk of national

599
00:31:06,400 --> 00:31:08,880
Speaker 1: forest that we could traverse pretty openly. There was a

600
00:31:08,920 --> 00:31:11,000
Speaker 1: lot of logging roads and two tracks and things we

601
00:31:11,000 --> 00:31:13,360
Speaker 1: could get on. So we found one we looked like,

602
00:31:13,600 --> 00:31:16,520
Speaker 1: looked nice and got going on it. And not too

603
00:31:16,960 --> 00:31:19,920
Speaker 1: too far from that, we were rolling around a corner

604
00:31:19,920 --> 00:31:22,480
Speaker 1: and spotted the tom up on this little you know

605
00:31:22,760 --> 00:31:24,840
Speaker 1: ridge above a grassy meadow, and he just kind of

606
00:31:24,960 --> 00:31:27,960
Speaker 1: saw the truck and slowly meandered his way up into

607
00:31:27,960 --> 00:31:31,760
Speaker 1: the timber, and we parked the truck, got out and

608
00:31:31,800 --> 00:31:35,520
Speaker 1: again try to get above him. Right, so we're going, Yeah,

609
00:31:35,600 --> 00:31:37,640
Speaker 1: so we pulled up the map and where he had

610
00:31:37,640 --> 00:31:39,960
Speaker 1: gone up into the timber was a little drainage that

611
00:31:40,040 --> 00:31:42,800
Speaker 1: kind of basically arcd up the side of this hill

612
00:31:42,880 --> 00:31:45,160
Speaker 1: that you know, we probably climbed about two d feet

613
00:31:45,240 --> 00:31:47,880
Speaker 1: or a hundred fifty feet vertical, but there was a

614
00:31:47,960 --> 00:31:49,360
Speaker 1: drainage that went up and it was like kind of

615
00:31:49,400 --> 00:31:52,480
Speaker 1: like broken meadows all the way up, and so we yeah,

616
00:31:52,520 --> 00:31:55,200
Speaker 1: drove the truck ground parked and then basically went straight

617
00:31:55,240 --> 00:31:58,440
Speaker 1: to the top and had looked at the map and

618
00:31:58,440 --> 00:32:00,400
Speaker 1: saw that there was a bench, a nice like gradual

619
00:32:00,520 --> 00:32:02,840
Speaker 1: like ridge at the top that led to that drainage,

620
00:32:02,840 --> 00:32:04,560
Speaker 1: and if we could get to that area, we should

621
00:32:04,600 --> 00:32:06,520
Speaker 1: be able to probably get him to answer and come

622
00:32:06,600 --> 00:32:09,400
Speaker 1: up that drainage. Yeah, we did, and we set up

623
00:32:10,400 --> 00:32:14,960
Speaker 1: and what the hell happened? What we called and immediately

624
00:32:14,960 --> 00:32:17,840
Speaker 1: stupid turkeys. Well yeah, but there were three of them,

625
00:32:18,040 --> 00:32:20,000
Speaker 1: so we only saw the one. But we called and

626
00:32:20,080 --> 00:32:22,560
Speaker 1: three different tom's answered, and we're like, well that's a

627
00:32:22,560 --> 00:32:24,840
Speaker 1: pretty good sign like that, you know, because they're gonna

628
00:32:24,880 --> 00:32:27,920
Speaker 1: battle for coming in. Like when I sat down and

629
00:32:28,000 --> 00:32:30,160
Speaker 1: heard that, I mean, we didn't set the decoys up.

630
00:32:30,600 --> 00:32:33,560
Speaker 1: You know, we heard three gobbles went around the corner, like, hey,

631
00:32:33,640 --> 00:32:36,480
Speaker 1: let's get in an open area on kind of the

632
00:32:36,520 --> 00:32:39,200
Speaker 1: flat spot where these spines of these ridges will come

633
00:32:39,280 --> 00:32:40,920
Speaker 1: up and meet it. So if they're going to travel

634
00:32:41,040 --> 00:32:42,920
Speaker 1: on the spine to get up here, they're gonna see

635
00:32:42,920 --> 00:32:45,600
Speaker 1: these decoys come across this flat we're gonna be in

636
00:32:45,640 --> 00:32:47,160
Speaker 1: the money. And it wasn't. I mean, we set the

637
00:32:47,240 --> 00:32:49,240
Speaker 1: decoys out and maybe got I didn't even really have

638
00:32:49,280 --> 00:32:51,840
Speaker 1: time to put gloves on or do anything. I mean,

639
00:32:51,880 --> 00:32:54,040
Speaker 1: it was, you know, a hundred yards seventy five yards

640
00:32:54,080 --> 00:32:57,000
Speaker 1: there's bird goblin and it didn't even really do a

641
00:32:57,000 --> 00:32:58,880
Speaker 1: ton of call and say was working the old pott

642
00:32:58,920 --> 00:33:02,360
Speaker 1: and peg fields like and didn't even do a ton

643
00:33:02,440 --> 00:33:04,840
Speaker 1: of that. And this in the first bird, the one

644
00:33:04,880 --> 00:33:06,360
Speaker 1: we had seen in the road, was in on us

645
00:33:07,080 --> 00:33:11,480
Speaker 1: within you know, five minutes, probably setting up and he

646
00:33:11,600 --> 00:33:13,760
Speaker 1: it was it was picture perfect. I mean, came across

647
00:33:13,840 --> 00:33:18,440
Speaker 1: this open this open bench, strutting, spitting, drumming. Given the

648
00:33:18,560 --> 00:33:23,440
Speaker 1: full full show comes out of strut at about sixty

649
00:33:23,560 --> 00:33:26,040
Speaker 1: five yards. There's a little opening where him and I

650
00:33:26,160 --> 00:33:28,560
Speaker 1: kind of he could see me, and I could see

651
00:33:28,640 --> 00:33:31,080
Speaker 1: him pretty clearly. I don't know if he saw me

652
00:33:31,240 --> 00:33:35,320
Speaker 1: or not. Um if he did see me, he didn't

653
00:33:35,360 --> 00:33:38,360
Speaker 1: react like he saw human like. He just he just

654
00:33:38,560 --> 00:33:41,800
Speaker 1: came around the corner and took a couple of looks around.

655
00:33:42,320 --> 00:33:44,920
Speaker 1: It looked like he was looking past Sam, like to

656
00:33:45,160 --> 00:33:48,880
Speaker 1: Sam's right, and saw something he didn't like, something in

657
00:33:49,040 --> 00:33:52,040
Speaker 1: some part of his scanning of of the of what

658
00:33:52,120 --> 00:33:56,080
Speaker 1: he was stepping into, and just putted once or twice

659
00:33:56,240 --> 00:34:01,400
Speaker 1: and just turned around and kind of meandered away. And

660
00:34:01,440 --> 00:34:03,320
Speaker 1: I just kind of worked around the back side of

661
00:34:03,360 --> 00:34:08,200
Speaker 1: that knob and then gobbled going away. Yeah see yeah, peace.

662
00:34:09,280 --> 00:34:12,880
Speaker 1: And so we thought, well, we didn't really spook, and

663
00:34:13,000 --> 00:34:15,759
Speaker 1: he just was wary of of coming any further. So

664
00:34:15,840 --> 00:34:17,759
Speaker 1: let's work our way around the ridge. See if we

665
00:34:17,760 --> 00:34:19,759
Speaker 1: can get in front of him and stay above him

666
00:34:19,800 --> 00:34:21,799
Speaker 1: and work get him to work back up this ridge

667
00:34:21,800 --> 00:34:23,960
Speaker 1: at us. And this is a good tip for any

668
00:34:23,960 --> 00:34:25,719
Speaker 1: of you out there where if you have a bird

669
00:34:25,719 --> 00:34:28,480
Speaker 1: come in and he kind of like doesn't quite commit,

670
00:34:29,080 --> 00:34:32,760
Speaker 1: uh like, let him move off and then get back

671
00:34:32,800 --> 00:34:35,560
Speaker 1: around to where he was gobbling and strutting coming in

672
00:34:36,320 --> 00:34:39,120
Speaker 1: and then call again. A lot of times they'll think

673
00:34:39,160 --> 00:34:41,960
Speaker 1: that a hand was trying to come to meet him,

674
00:34:42,080 --> 00:34:43,839
Speaker 1: and all of a sudden, there's a hand back where

675
00:34:43,840 --> 00:34:45,839
Speaker 1: they wanted to be in the first place. So get

676
00:34:45,880 --> 00:34:48,440
Speaker 1: to where that turkey wants to be. So yeah, we

677
00:34:48,480 --> 00:34:49,960
Speaker 1: just kind of stayed on the back side of the

678
00:34:50,040 --> 00:34:52,839
Speaker 1: ridge and worked down to u different open area about

679
00:34:52,920 --> 00:34:55,400
Speaker 1: two hundred yards hundred fifty yards away. Yeah, and just

680
00:34:55,480 --> 00:34:57,400
Speaker 1: you we were just milling around. I'm like, hey, hit

681
00:34:57,440 --> 00:34:59,759
Speaker 1: the call, let's see see where it is. Hit the

682
00:34:59,800 --> 00:35:02,959
Speaker 1: call all and a different bird is now it's maybe

683
00:35:02,960 --> 00:35:05,360
Speaker 1: a less than hundred yards away that time, So I

684
00:35:05,560 --> 00:35:08,640
Speaker 1: quickly chunk the decoy. Just just put a hen down

685
00:35:08,640 --> 00:35:10,840
Speaker 1: because I'm thinking, well, this last bird might have gotten

686
00:35:10,840 --> 00:35:13,960
Speaker 1: flared by the jake decoy. Let's just put a hand

687
00:35:13,960 --> 00:35:17,120
Speaker 1: out as to not have anything really other than that's

688
00:35:17,120 --> 00:35:21,680
Speaker 1: sexy sexy hen there, um u. Let's get set up

689
00:35:21,680 --> 00:35:25,560
Speaker 1: and I get back, you know, probably thirty yards from

690
00:35:25,600 --> 00:35:30,440
Speaker 1: the decoy gets set down. You are off to my left,

691
00:35:30,560 --> 00:35:32,280
Speaker 1: and now the turkey, like this is not the turkey

692
00:35:32,280 --> 00:35:37,040
Speaker 1: We're we're planning the hunt and where he's coming or

693
00:35:37,040 --> 00:35:38,880
Speaker 1: he's gobbling from I think he's gonna be in between

694
00:35:38,920 --> 00:35:42,279
Speaker 1: you and I or come right to you. And now

695
00:35:42,320 --> 00:35:45,160
Speaker 1: we've got trouble because because originally I had set up

696
00:35:45,280 --> 00:35:46,880
Speaker 1: to call, like to think that we were going to

697
00:35:46,960 --> 00:35:48,839
Speaker 1: call him back basically from the line that the first

698
00:35:48,920 --> 00:35:52,640
Speaker 1: turkey took. But now he's looped around, basically walked past

699
00:35:52,719 --> 00:35:56,839
Speaker 1: where we were sitting originally and is coming to my call.

700
00:35:56,960 --> 00:35:58,799
Speaker 1: So I was on the back side of the tree.

701
00:35:58,840 --> 00:36:00,680
Speaker 1: But yeah, that was pretty were that he was gonna

702
00:36:00,719 --> 00:36:03,399
Speaker 1: come between me and you and that shotgun. Yeah, so

703
00:36:03,440 --> 00:36:05,480
Speaker 1: I was I couldn't where I was. I couldn't see you,

704
00:36:06,000 --> 00:36:07,640
Speaker 1: or at least I when I was looking and trying

705
00:36:07,640 --> 00:36:09,359
Speaker 1: to scan for the turkey and scan for you, like

706
00:36:09,400 --> 00:36:11,840
Speaker 1: I knew the tree you were under. But I was like,

707
00:36:11,840 --> 00:36:14,239
Speaker 1: he's gonna have to be from twelve o'clock to six

708
00:36:14,239 --> 00:36:16,160
Speaker 1: o'clock for me to shoot him. I'm not going to

709
00:36:16,200 --> 00:36:18,880
Speaker 1: shoot him from six to twelve, Like, I'm just gonna

710
00:36:19,400 --> 00:36:20,759
Speaker 1: kind of cut this in a pot because I'm not

711
00:36:20,800 --> 00:36:23,799
Speaker 1: gonna I like Sam more than I want to kill

712
00:36:23,840 --> 00:36:26,200
Speaker 1: a turkey. I don't want to shoot him. So a

713
00:36:26,200 --> 00:36:28,279
Speaker 1: little bit of a sticky situation there, But he came

714
00:36:28,320 --> 00:36:30,640
Speaker 1: around perfect I mean it came right. I mean he

715
00:36:30,719 --> 00:36:33,640
Speaker 1: came right at my like one o'clock and came in

716
00:36:33,719 --> 00:36:36,640
Speaker 1: and I saw him at like seventy yards. I shifted

717
00:36:36,640 --> 00:36:38,520
Speaker 1: a little bit, got set up, and here again this

718
00:36:38,560 --> 00:36:42,719
Speaker 1: turkey comes into about sixty yards fifty five yards and

719
00:36:42,840 --> 00:36:44,560
Speaker 1: just hangs up. And he didn't even I mean, it's

720
00:36:44,719 --> 00:36:47,680
Speaker 1: very similar to the one before him hung up. I

721
00:36:47,719 --> 00:36:49,719
Speaker 1: don't we don't know why they were hanging up, like

722
00:36:49,760 --> 00:36:53,359
Speaker 1: there's no Yeah, we're assuming, I mean not. It could

723
00:36:53,360 --> 00:36:55,640
Speaker 1: have been a lot of things, but um guessing that

724
00:36:55,760 --> 00:36:58,759
Speaker 1: somebody's been in there messing with those birds with the

725
00:36:58,800 --> 00:37:01,359
Speaker 1: decoy or or some you know, and trying to trying

726
00:37:01,360 --> 00:37:02,640
Speaker 1: to get in on him, and they have seen that

727
00:37:03,160 --> 00:37:05,440
Speaker 1: and then like something in our setup that they're seeing.

728
00:37:05,480 --> 00:37:07,799
Speaker 1: I was shooting a weather B eight the new weather

729
00:37:07,880 --> 00:37:10,959
Speaker 1: B eighteen nine. And it's not the synthetic version, because

730
00:37:11,200 --> 00:37:13,319
Speaker 1: we'll just blame this one Ryan Callahan. He took my

731
00:37:13,400 --> 00:37:17,680
Speaker 1: synthetic version. Um, so there's a little shiny nous. Just

732
00:37:17,719 --> 00:37:22,200
Speaker 1: get out the spray paint. He would appreciate that. Actually

733
00:37:22,200 --> 00:37:24,520
Speaker 1: they like that. But it's a fantastic shotgun of got

734
00:37:24,520 --> 00:37:28,000
Speaker 1: the job done. Um So I'm not sure what these

735
00:37:28,040 --> 00:37:30,560
Speaker 1: two birds saw. But this guy, I mean, I'm playing

736
00:37:30,560 --> 00:37:32,839
Speaker 1: the last instance and I had not even knowing at

737
00:37:32,840 --> 00:37:35,080
Speaker 1: this point, I didn't even know which bird this was.

738
00:37:35,160 --> 00:37:39,680
Speaker 1: I thought this might be the same turkey um from

739
00:37:39,680 --> 00:37:41,480
Speaker 1: the first time. So I'm thinking he's doing it again.

740
00:37:41,880 --> 00:37:44,200
Speaker 1: And so he gets about fifty five and starts to

741
00:37:44,239 --> 00:37:48,279
Speaker 1: peel off and he he's facing away from me now

742
00:37:48,320 --> 00:37:50,080
Speaker 1: and I got a clear open shot. I'm like, well,

743
00:37:50,080 --> 00:37:52,439
Speaker 1: if he stops within the next five yards, I'm gonna

744
00:37:52,480 --> 00:37:56,400
Speaker 1: kill him. And he stopped perfect, you know, quartering away,

745
00:37:56,840 --> 00:37:59,600
Speaker 1: just put it on his head and boom. I didn't

746
00:37:59,680 --> 00:38:02,200
Speaker 1: hit him in ahead, but I hit him that crippled him,

747
00:38:02,400 --> 00:38:05,000
Speaker 1: and he took a few flops and just kind of

748
00:38:05,120 --> 00:38:07,480
Speaker 1: laid down. He would have been he was dead on arrival,

749
00:38:07,960 --> 00:38:09,960
Speaker 1: and I put another shot in him and he was done.

750
00:38:10,760 --> 00:38:13,960
Speaker 1: And then we celebrated. We celebrated, and he's like, there's

751
00:38:14,000 --> 00:38:16,759
Speaker 1: something you said this even when we were going up

752
00:38:16,800 --> 00:38:19,759
Speaker 1: this hill to kind of get into this situation. It's

753
00:38:19,800 --> 00:38:22,279
Speaker 1: like like I love this man, like I love this

754
00:38:23,080 --> 00:38:24,879
Speaker 1: I love this so much. So I don't know why.

755
00:38:24,920 --> 00:38:27,120
Speaker 1: It's so much fun. It's the cat and mouse, like

756
00:38:27,120 --> 00:38:30,760
Speaker 1: it's the cat and mouse game that you play knowing

757
00:38:30,800 --> 00:38:33,240
Speaker 1: that this is like a twenty pound rapture that sleeps

758
00:38:33,239 --> 00:38:35,759
Speaker 1: in trees. You look at his feet, it's like you're

759
00:38:35,800 --> 00:38:40,640
Speaker 1: chasing a dinosaur. It has you know. Now we know

760
00:38:40,680 --> 00:38:43,640
Speaker 1: all about it's Cloaka and the sterious sexual intercourse that

761
00:38:43,680 --> 00:38:47,480
Speaker 1: they have, but there's there's something about it at the

762
00:38:47,560 --> 00:38:52,399
Speaker 1: time of year. The way that you, you know, are

763
00:38:52,480 --> 00:38:55,360
Speaker 1: playing this game with a turkey, like you're talking to it.

764
00:38:55,960 --> 00:38:59,440
Speaker 1: You are literally convincing it of something that is is untrue,

765
00:38:59,640 --> 00:39:03,560
Speaker 1: like you are you are setting a narrative for the turkey.

766
00:39:04,160 --> 00:39:06,359
Speaker 1: And so I had the same feeling as you. It's

767
00:39:06,360 --> 00:39:11,560
Speaker 1: just like electric. You are electric, electrified by what's going on,

768
00:39:11,640 --> 00:39:14,960
Speaker 1: and the experience is um, it's just it. Yeah, it's

769
00:39:14,960 --> 00:39:17,640
Speaker 1: so interactive. And when you get a burden close and

770
00:39:17,640 --> 00:39:21,480
Speaker 1: they gobble like within whatever fifty sixty yards, like it's

771
00:39:21,480 --> 00:39:23,839
Speaker 1: just like whatever that sound is that they admit, like

772
00:39:24,200 --> 00:39:26,319
Speaker 1: whatever frequency, it's like one of those like just like

773
00:39:27,000 --> 00:39:29,080
Speaker 1: you can feel it in your heart, like it hits

774
00:39:29,080 --> 00:39:34,080
Speaker 1: so hard. Yeah, there's nothing like I don't think I

775
00:39:34,120 --> 00:39:39,520
Speaker 1: think elk is of course really compared. Can people say

776
00:39:39,560 --> 00:39:41,319
Speaker 1: like turkey hunting is just like elk hunting, but it's

777
00:39:42,080 --> 00:39:44,520
Speaker 1: it's not Yes, you're calling an animal in, but it's

778
00:39:44,520 --> 00:39:46,239
Speaker 1: not the same thing, not the same, not at all.

779
00:39:46,320 --> 00:39:49,200
Speaker 1: And it's just a different time of year. The natural

780
00:39:49,200 --> 00:39:52,600
Speaker 1: wolves just it's coming alive. It's just a different function,

781
00:39:53,440 --> 00:39:55,840
Speaker 1: um for a hunter. And I wouldn't say one is

782
00:39:55,880 --> 00:39:57,840
Speaker 1: better than the other. But god damn, I love turkey hunting.

783
00:39:58,040 --> 00:39:59,880
Speaker 1: It would be hard for me to sit here and

784
00:40:00,000 --> 00:40:01,919
Speaker 1: say that I love l hunting as much but not more.

785
00:40:02,800 --> 00:40:04,960
Speaker 1: I think they're probably on the same plane. But whatever

786
00:40:05,160 --> 00:40:07,879
Speaker 1: I mean, it doesn't really matter. No, the point is,

787
00:40:08,320 --> 00:40:09,800
Speaker 1: if you're not turkey on a lot of people in

788
00:40:09,840 --> 00:40:12,480
Speaker 1: the West, now that I've lived in the West, will say,

789
00:40:12,480 --> 00:40:15,480
Speaker 1: like this bear season. Like listen, man, no it's not.

790
00:40:16,040 --> 00:40:18,400
Speaker 1: It's a turkey season. You get as soon as you

791
00:40:18,400 --> 00:40:21,239
Speaker 1: filled your turkey text, then you can bear hunt. That's

792
00:40:21,239 --> 00:40:24,280
Speaker 1: how it should always be. So let it be written

793
00:40:25,040 --> 00:40:29,040
Speaker 1: speaking of bear seasons and turkey seasons, um, Colorado does

794
00:40:29,080 --> 00:40:32,279
Speaker 1: not have a spring bear season. And last year my

795
00:40:32,520 --> 00:40:36,080
Speaker 1: older brother was turkey turkey hunting and they put a

796
00:40:36,080 --> 00:40:38,800
Speaker 1: bird to roost, went in there in the morning, bird

797
00:40:38,840 --> 00:40:42,960
Speaker 1: flew down and they started calling to him. I had

798
00:40:43,000 --> 00:40:46,279
Speaker 1: this big tom on a rope coming in the hunt

799
00:40:46,280 --> 00:40:48,160
Speaker 1: got busted up because they called in a black bear.

800
00:40:48,360 --> 00:40:52,760
Speaker 1: Their turkey calls scared it off. So yeah, Steve Ronella

801
00:40:52,800 --> 00:40:55,880
Speaker 1: has a story about that exact same thing, realizing he

802
00:40:55,920 --> 00:40:58,759
Speaker 1: was doing he was hunting the same thing that the

803
00:40:58,800 --> 00:41:02,520
Speaker 1: bear was hunting, and having like some some revelation because

804
00:41:02,800 --> 00:41:05,839
Speaker 1: of an understanding of the predatory behaviors. But yeah, I mean,

805
00:41:05,840 --> 00:41:08,799
Speaker 1: this is this is a cool spot. I'm doing the

806
00:41:08,800 --> 00:41:12,480
Speaker 1: one the one day wonder. I am now leaving to

807
00:41:12,560 --> 00:41:15,200
Speaker 1: go back to Montana to try to kill another bird

808
00:41:15,239 --> 00:41:16,960
Speaker 1: before I have to go back home and then hit

809
00:41:17,040 --> 00:41:20,319
Speaker 1: up the b h A. Rodney. So I'm doing. I

810
00:41:20,320 --> 00:41:22,200
Speaker 1: would say what what I would refer to as a

811
00:41:22,239 --> 00:41:25,960
Speaker 1: dick move was just coming into camp eating all your food.

812
00:41:26,280 --> 00:41:28,839
Speaker 1: I'll forgive you. I'll forgive you this time. Yeah. Yeah,

813
00:41:28,880 --> 00:41:33,400
Speaker 1: well I appreciate, uh, I appreciate your rodding. Riding along

814
00:41:33,719 --> 00:41:38,640
Speaker 1: and um go follow Sammy at sam Sohole. You'll see

815
00:41:38,640 --> 00:41:41,120
Speaker 1: all kinds of stuff public land, tease. Go there. They

816
00:41:41,680 --> 00:41:45,160
Speaker 1: actually have turkey T shirts there. We do, which other

817
00:41:45,200 --> 00:41:47,360
Speaker 1: than the meat eater, no one else in the world

818
00:41:47,440 --> 00:41:50,239
Speaker 1: makes a good turkey T shirt. I'm glad I we're

819
00:41:50,239 --> 00:41:52,560
Speaker 1: talking about that. I'm like right on par with you know,

820
00:41:53,320 --> 00:41:56,839
Speaker 1: I mean, go buy meatiators, so first and then yeah

821
00:41:56,920 --> 00:41:59,000
Speaker 1: publicly and so I'm get in trouble with my bosses.

822
00:41:59,080 --> 00:42:01,640
Speaker 1: Yeah you gotta say it, but all Spring say that. Yeah,

823
00:42:01,680 --> 00:42:05,160
Speaker 1: all Spring. Um. Any turkey shirt sold, we're given five

824
00:42:05,239 --> 00:42:08,920
Speaker 1: dollars to the Nash Wild Turkey Federation. Beautiful, Yeah, beautiful,

825
00:42:09,480 --> 00:42:12,120
Speaker 1: And like I said, there's not a whole lot of turkey.

826
00:42:12,400 --> 00:42:14,840
Speaker 1: There's an analetic like what I would call new school

827
00:42:15,560 --> 00:42:19,359
Speaker 1: turkey gear out there. Um that you could feel real proud,

828
00:42:19,360 --> 00:42:22,080
Speaker 1: and I think the public and tease you can what

829
00:42:22,160 --> 00:42:23,799
Speaker 1: I think. Yeah, that's the way I feel about it,

830
00:42:23,800 --> 00:42:25,080
Speaker 1: and say I didn't even ask me to say that.

831
00:42:27,440 --> 00:42:30,440
Speaker 1: He didn't know, he didn't I like him. So I

832
00:42:30,480 --> 00:42:36,040
Speaker 1: happened to be wearing one face. People listening, So go

833
00:42:36,080 --> 00:42:38,279
Speaker 1: buy a T shirt. I appreciate it in advance. Would

834
00:42:38,280 --> 00:42:40,239
Speaker 1: be cool, and so does turkeys, So do turkeys and

835
00:42:40,239 --> 00:42:43,920
Speaker 1: sodas the n w TF so do I. Um. All right,

836
00:42:43,960 --> 00:42:46,960
Speaker 1: we're gonna get into the interview portion of the program,

837
00:42:47,000 --> 00:42:48,960
Speaker 1: and now that we're gonna take a hard left at

838
00:42:49,000 --> 00:42:52,840
Speaker 1: turkey hunting. We're going to move into UM some of

839
00:42:52,880 --> 00:42:58,640
Speaker 1: the social sciences and the human interaction with hunting and wildlife.

840
00:42:58,880 --> 00:43:01,960
Speaker 1: Now Alex and Louis Metcalf are our interview guests today

841
00:43:02,440 --> 00:43:06,360
Speaker 1: and they are professors at the University of Montana in Missoula.

842
00:43:06,360 --> 00:43:07,640
Speaker 1: Am I saying that right? Is that the University of

843
00:43:07,640 --> 00:43:11,040
Speaker 1: Montana in Missoula? I get confused. I'm new. Yeah, is

844
00:43:11,080 --> 00:43:13,040
Speaker 1: that right? Okay? I got that right. So I went

845
00:43:13,080 --> 00:43:16,000
Speaker 1: over there UM a couple of days ago, and I

846
00:43:16,239 --> 00:43:19,439
Speaker 1: right before I came here, and I got to meet

847
00:43:19,480 --> 00:43:21,200
Speaker 1: with some of their students, some of their b h

848
00:43:21,320 --> 00:43:26,359
Speaker 1: Ah club students there at the university, and they blew

849
00:43:26,360 --> 00:43:29,560
Speaker 1: me away. They absolutely blew me away. Um, you know,

850
00:43:29,600 --> 00:43:32,520
Speaker 1: shout out to the Matine and Hannah and a bunch

851
00:43:32,560 --> 00:43:34,920
Speaker 1: of the other people that I met that are doing

852
00:43:35,000 --> 00:43:38,000
Speaker 1: things UM in their college years that I didn't do.

853
00:43:38,080 --> 00:43:42,560
Speaker 1: Sam and I probably were running around being adolescent idiots

854
00:43:42,680 --> 00:43:46,040
Speaker 1: at the time. I'm speaking for you, Sam, That's fine.

855
00:43:46,480 --> 00:43:51,400
Speaker 1: I'll accept that. I definitely was. I speak to myself

856
00:43:51,400 --> 00:43:54,920
Speaker 1: on that one. UM, I definitely was, and I wasn't

857
00:43:54,920 --> 00:44:00,839
Speaker 1: thinking in abroad context like these guys UM close. Yeah,

858
00:44:00,920 --> 00:44:03,239
Speaker 1: like talking to this guy Craig Martin who was the

859
00:44:03,280 --> 00:44:06,680
Speaker 1: president of that the the chapter over there for b H.

860
00:44:06,719 --> 00:44:08,960
Speaker 1: I mean the way that they think that they talk

861
00:44:09,000 --> 00:44:13,200
Speaker 1: about sustainability, they talk about harvesting animals, they talk about

862
00:44:13,440 --> 00:44:18,520
Speaker 1: mentoring new hunters, they have Hunting for Sustainability, UH event

863
00:44:18,600 --> 00:44:21,160
Speaker 1: that they've put on. They have a bunch of mentorship

864
00:44:21,200 --> 00:44:24,680
Speaker 1: programs that they put on. UM. It was it was

865
00:44:25,320 --> 00:44:27,520
Speaker 1: I I wish that I had more time to podcast

866
00:44:27,600 --> 00:44:31,200
Speaker 1: with them and also their professors, so so everyone here

867
00:44:31,239 --> 00:44:34,200
Speaker 1: could learn UM about the way that they see the

868
00:44:34,239 --> 00:44:37,040
Speaker 1: world at the at the stage that that they are

869
00:44:37,040 --> 00:44:39,480
Speaker 1: in it because it is unique. And I was I

870
00:44:39,480 --> 00:44:41,479
Speaker 1: will say hopefully they listened to this at some point,

871
00:44:41,480 --> 00:44:44,040
Speaker 1: but but personally for those folks, I was inspired by

872
00:44:45,080 --> 00:44:47,560
Speaker 1: what you guys had to say, UM and buy your

873
00:44:47,600 --> 00:44:51,560
Speaker 1: passion for the outdoors and public lands and wildlife in

874
00:44:51,600 --> 00:44:54,279
Speaker 1: the way they should look at those things. I will

875
00:44:54,400 --> 00:44:58,200
Speaker 1: do anything I can to help foster that, UM. And

876
00:44:58,239 --> 00:45:01,040
Speaker 1: I think, you know, Montana is lucky to have these

877
00:45:01,080 --> 00:45:03,640
Speaker 1: young people that or that are there at the universe

878
00:45:03,640 --> 00:45:08,280
Speaker 1: of Montana. So thank you for that, UM, guys and gals. UM.

879
00:45:08,320 --> 00:45:10,520
Speaker 1: And then I sat down right after that, I sat

880
00:45:10,520 --> 00:45:15,399
Speaker 1: down with their professors Alex and Libby Metcalfe, and it's

881
00:45:15,440 --> 00:45:18,240
Speaker 1: it's an interesting conversation. It goes to the social sciences

882
00:45:18,280 --> 00:45:22,600
Speaker 1: and the way that you use UH social studies to

883
00:45:22,640 --> 00:45:26,719
Speaker 1: build data sets to kind of tell um. Either they're

884
00:45:26,760 --> 00:45:28,680
Speaker 1: working with state agencies and they're also just working on

885
00:45:28,680 --> 00:45:33,000
Speaker 1: an academic level to tell folks the motivation of hunters

886
00:45:33,120 --> 00:45:35,200
Speaker 1: and how they interact with wildlife. So there's some interesting

887
00:45:35,280 --> 00:45:37,880
Speaker 1: stuff there. It, I will tell you, after thinking and

888
00:45:37,920 --> 00:45:40,800
Speaker 1: listening back to the interview, is a complicated thing to understand.

889
00:45:41,320 --> 00:45:44,560
Speaker 1: It's it's not as simple as here's the data, here's

890
00:45:44,560 --> 00:45:47,360
Speaker 1: the results, um. And so you may find it to

891
00:45:47,360 --> 00:45:50,000
Speaker 1: be a twisting and turning tail. But hopefully you'll listen

892
00:45:50,000 --> 00:45:51,960
Speaker 1: to Alex and listen to to Libby and learn a

893
00:45:52,000 --> 00:45:54,120
Speaker 1: little bit about what they do because it is very

894
00:45:54,120 --> 00:45:56,960
Speaker 1: important in my opinion. So, without further ado, we will

895
00:45:57,000 --> 00:46:00,359
Speaker 1: travel back in time to Missoula, Montana. Well we'll see

896
00:46:00,400 --> 00:46:09,759
Speaker 1: Alex and Libby metcalf Alex and Libby, how are you great? Yeah?

897
00:46:09,840 --> 00:46:11,200
Speaker 1: Good to be here? Could to be here? It's good

898
00:46:11,200 --> 00:46:13,400
Speaker 1: to be here. I always like to do this, like

899
00:46:13,280 --> 00:46:15,359
Speaker 1: like to break the ice here, right, haven't you guys?

900
00:46:15,920 --> 00:46:18,839
Speaker 1: Described the surroundings, so people won't they won't be able

901
00:46:18,840 --> 00:46:21,680
Speaker 1: to see where we are. It's very very mysterious. So Alex,

902
00:46:21,680 --> 00:46:23,440
Speaker 1: you want to kind of describe where we are in

903
00:46:23,480 --> 00:46:26,319
Speaker 1: the in the micro and macro sense of the word. Yeah,

904
00:46:26,360 --> 00:46:28,719
Speaker 1: I mean we invited you specifically to this room and

905
00:46:28,760 --> 00:46:33,120
Speaker 1: not our offices because this is a much better setting. Um.

906
00:46:33,160 --> 00:46:35,960
Speaker 1: But yeah, we're here in uh, you know, Missoula, Montana.

907
00:46:36,000 --> 00:46:39,279
Speaker 1: It's a beautiful day, um, blue skies looking out at

908
00:46:39,280 --> 00:46:41,960
Speaker 1: Mountain Jumbo at main Hall here. We're sitting in the

909
00:46:42,560 --> 00:46:45,000
Speaker 1: in the Forestry building, which is a pretty historic place

910
00:46:45,000 --> 00:46:47,799
Speaker 1: on campus. Um. The college here has been around for

911
00:46:47,960 --> 00:46:51,600
Speaker 1: over a hundred years and founded right here. Um. And

912
00:46:51,600 --> 00:46:54,440
Speaker 1: we're up here on the third floor, um, right outside

913
00:46:54,440 --> 00:46:57,560
Speaker 1: the Wildlife Biology main office, and we're sitting in the

914
00:46:57,600 --> 00:47:03,399
Speaker 1: conference room with a wall of black dissertations that are

915
00:47:03,400 --> 00:47:09,680
Speaker 1: all extremely important, a lot of words. Um. And then

916
00:47:09,960 --> 00:47:14,240
Speaker 1: of course above the dissertations, UM, we have a few

917
00:47:14,600 --> 00:47:19,400
Speaker 1: of our native species here, um, in stuffed form. Yeah. Yeah.

918
00:47:19,600 --> 00:47:22,000
Speaker 1: Where I went to college, there wasn't any taxi germy. Yeah,

919
00:47:22,160 --> 00:47:25,200
Speaker 1: but very jealous. Yeah, we I mean, you know, being

920
00:47:25,360 --> 00:47:28,560
Speaker 1: younger professors are our taxidermy is is coming along. We're

921
00:47:28,600 --> 00:47:31,359
Speaker 1: working on the collection, but they have a better one

922
00:47:31,400 --> 00:47:33,920
Speaker 1: in this room. It's pretty good. Yeah, I like it.

923
00:47:34,000 --> 00:47:40,080
Speaker 1: I like it, Libby, Um tell us about yourself in

924
00:47:40,080 --> 00:47:42,200
Speaker 1: your relationship to Alex two so people know all about that.

925
00:47:42,400 --> 00:47:47,920
Speaker 1: Oh yeah, Alex is my spouse. He's my uh my

926
00:47:48,040 --> 00:47:51,719
Speaker 1: partner and also a faculty member here with me at

927
00:47:51,760 --> 00:47:55,799
Speaker 1: the University of Montana. And I'm an associate professor in

928
00:47:55,840 --> 00:47:58,759
Speaker 1: the Department of Society and Conservation, and I have kind

929
00:47:58,760 --> 00:48:01,040
Speaker 1: of I sent on a couple different curricular programs, but

930
00:48:02,120 --> 00:48:05,239
Speaker 1: I direct our Parks, Tourism and Recreation Management program. But

931
00:48:05,280 --> 00:48:08,239
Speaker 1: I'm also part of the Wildlife Biology program, which is

932
00:48:08,239 --> 00:48:11,640
Speaker 1: the number one wildlife biology program in the nation. It

933
00:48:11,760 --> 00:48:14,080
Speaker 1: gotta mention it here in the College of Worse sound

934
00:48:14,080 --> 00:48:20,279
Speaker 1: effect like yeah, and so I um. I've spent the

935
00:48:20,360 --> 00:48:25,520
Speaker 1: last decade here in Montana thinking about wildlife and how

936
00:48:25,680 --> 00:48:29,520
Speaker 1: humans and wildlife interact. And I've done it from a

937
00:48:29,560 --> 00:48:33,440
Speaker 1: couple of different perspectives. Um uh my. Probably my most

938
00:48:33,480 --> 00:48:36,799
Speaker 1: notable work in the human dimensions of wild I feel

939
00:48:36,840 --> 00:48:39,120
Speaker 1: this is is probably my work on gender and hunting. So

940
00:48:39,200 --> 00:48:41,680
Speaker 1: I've been thinking a lot about how we engage women

941
00:48:41,680 --> 00:48:44,560
Speaker 1: in the sport and which is kind of cool. Yeah,

942
00:48:44,600 --> 00:48:46,920
Speaker 1: we were talking to one of your students, Hannah earlier,

943
00:48:47,000 --> 00:48:49,480
Speaker 1: and she was explained as graduate student. I believe that

944
00:48:49,560 --> 00:48:52,560
Speaker 1: was correct, um, and she was explaining kind of her.

945
00:48:53,840 --> 00:48:56,200
Speaker 1: The thing that struck me was her interaction in like

946
00:48:56,239 --> 00:48:59,480
Speaker 1: Sportsman's warehouse from when she goes to a something I

947
00:48:59,520 --> 00:49:00,919
Speaker 1: had not thought up. When she goes to a big

948
00:49:00,920 --> 00:49:03,080
Speaker 1: box store or really any guns store or hunting store,

949
00:49:03,560 --> 00:49:06,240
Speaker 1: and she's with a male counterpart, whether it's her boyfriend

950
00:49:06,320 --> 00:49:09,160
Speaker 1: or just a friend or whomever, that the the salesperson

951
00:49:09,200 --> 00:49:11,719
Speaker 1: would would talk to her, would talk to the the

952
00:49:11,800 --> 00:49:14,360
Speaker 1: mail and they never even give her any eye contact

953
00:49:14,360 --> 00:49:17,520
Speaker 1: even if she asked the question. Um. And that's not

954
00:49:17,640 --> 00:49:21,080
Speaker 1: something I'd considered before talking to her, so and I

955
00:49:21,120 --> 00:49:23,960
Speaker 1: expressed her, Listen, I understand that we need to we

956
00:49:24,000 --> 00:49:25,799
Speaker 1: need to get across this gap, and we need to

957
00:49:25,800 --> 00:49:29,080
Speaker 1: do better than pandering too women hunters and outdoors been

958
00:49:29,120 --> 00:49:31,319
Speaker 1: with pink things, and then in the way that we've

959
00:49:31,440 --> 00:49:34,520
Speaker 1: the tropes that we devise the kind of to do

960
00:49:34,560 --> 00:49:38,800
Speaker 1: that currently. But that certainly her comment got like really

961
00:49:38,840 --> 00:49:41,760
Speaker 1: fired me up on on that subject. So I'm started

962
00:49:41,840 --> 00:49:44,879
Speaker 1: excited to talk about that. Alex kind of run us through,

963
00:49:45,320 --> 00:49:50,839
Speaker 1: you know, in your professional career what you are up to. Yeah. So, UM,

964
00:49:51,000 --> 00:49:54,759
Speaker 1: let's see, I followed Libby around. UM. Yeah, so I

965
00:49:55,000 --> 00:49:56,960
Speaker 1: we both did our grad work at Penn State. UM.

966
00:49:57,040 --> 00:49:59,600
Speaker 1: We were in different programs there. Libby was in recreation

967
00:49:59,760 --> 00:50:02,920
Speaker 1: part to tourism. UH. There I have to learn all

968
00:50:02,960 --> 00:50:07,560
Speaker 1: the different acronyms for d r M, rpt M. But

969
00:50:07,640 --> 00:50:10,680
Speaker 1: I was over in the forestry UH program at Penn

970
00:50:10,760 --> 00:50:15,200
Speaker 1: State UM and was thinking more about private land conservation

971
00:50:15,400 --> 00:50:19,799
Speaker 1: specifically like forest landowners back east. UM. But you don't

972
00:50:19,840 --> 00:50:21,799
Speaker 1: talk to landowners very long before you end up talking

973
00:50:21,800 --> 00:50:27,719
Speaker 1: about wildlife UM. And so coming coming west, UM, you know,

974
00:50:27,800 --> 00:50:31,080
Speaker 1: the wildlife conversation definitely blew up. And I think you know,

975
00:50:31,120 --> 00:50:36,120
Speaker 1: the wildlife biology program here recognized that they have obviously

976
00:50:36,640 --> 00:50:41,000
Speaker 1: just amazing depth in the biology UM, but that as

977
00:50:41,000 --> 00:50:44,480
Speaker 1: you look around the state, in the country, in the world, UM,

978
00:50:44,520 --> 00:50:46,080
Speaker 1: you know a lot of the problems that we have

979
00:50:46,520 --> 00:50:50,319
Speaker 1: UM with wildlife center around people. UM. The answers aren't

980
00:50:50,320 --> 00:50:52,840
Speaker 1: going to come from the biology. And so yeah, so

981
00:50:52,840 --> 00:50:55,640
Speaker 1: as we came here, UM, you know, me and the

982
00:50:55,760 --> 00:50:59,480
Speaker 1: resource conservation program and Libyan recreation UM you know, our

983
00:50:59,520 --> 00:51:03,200
Speaker 1: interests in wildlife crew and kind of their interest in

984
00:51:03,200 --> 00:51:06,239
Speaker 1: incorporating the Human Dimensions Crew. And so we were able

985
00:51:06,280 --> 00:51:09,800
Speaker 1: to join the faculty goodness five or six years or

986
00:51:10,040 --> 00:51:13,680
Speaker 1: something like that. And UM, how many students do you

987
00:51:13,719 --> 00:51:16,439
Speaker 1: interact with, you know, on a semester basis. I'm trying

988
00:51:16,440 --> 00:51:18,480
Speaker 1: to get my college then go back and it's been

989
00:51:18,480 --> 00:51:21,080
Speaker 1: a while. Yeah, So it depends on the semester for sure.

990
00:51:21,160 --> 00:51:24,719
Speaker 1: For me, I teach UM our large introductory kind of

991
00:51:24,800 --> 00:51:27,680
Speaker 1: introduction to natural resource conservation course. It's about a hundred

992
00:51:27,719 --> 00:51:31,080
Speaker 1: and twenties students in there, mostly freshmen. Uh So it's

993
00:51:31,080 --> 00:51:35,080
Speaker 1: a big lecturer hall. The potential for sleeping is high.

994
00:51:35,120 --> 00:51:38,960
Speaker 1: So I have abandoned power point and I wander the

995
00:51:39,040 --> 00:51:43,320
Speaker 1: room right and I draw on the board and I

996
00:51:43,360 --> 00:51:48,240
Speaker 1: like raise my voice at random intervals. Yeah. Um. And

997
00:51:48,360 --> 00:51:51,160
Speaker 1: so I interact with a lot of those students, um,

998
00:51:51,200 --> 00:51:52,719
Speaker 1: you know, through the fall and it's kind of just

999
00:51:52,760 --> 00:51:54,759
Speaker 1: the beginning of their career here. So it's really fun.

1000
00:51:54,800 --> 00:51:57,000
Speaker 1: They're they're excited to be here, they want to change

1001
00:51:57,000 --> 00:51:58,840
Speaker 1: the world. Um. And I get to kind of be

1002
00:51:58,880 --> 00:52:04,080
Speaker 1: a part of that optimism. UM. And then that same

1003
00:52:04,120 --> 00:52:06,680
Speaker 1: semester I generally teach a graduate theory course on kind

1004
00:52:06,680 --> 00:52:08,800
Speaker 1: of human dimensions that we will be an I swap

1005
00:52:08,800 --> 00:52:13,160
Speaker 1: back and forth on UM and there's generally fifteen or

1006
00:52:13,200 --> 00:52:16,440
Speaker 1: so grad students in there, and then in the spring

1007
00:52:16,480 --> 00:52:19,440
Speaker 1: semester I teach a course on collaboration UM, and I

1008
00:52:19,480 --> 00:52:23,880
Speaker 1: have somewhere between forty and fifty undergrads being there. And

1009
00:52:23,880 --> 00:52:27,279
Speaker 1: then we've got our lab UM that uh, you know,

1010
00:52:27,960 --> 00:52:31,319
Speaker 1: depending on the year, we have yeah, five to eight

1011
00:52:31,400 --> 00:52:34,839
Speaker 1: grad students in there, either Masters or PhD working on there.

1012
00:52:35,480 --> 00:52:38,400
Speaker 1: And we we like a lot of professors here, we

1013
00:52:38,440 --> 00:52:40,920
Speaker 1: run a pretty intimate lab where we're meeting one on

1014
00:52:41,000 --> 00:52:44,160
Speaker 1: one with those students UM. Probably not as frequently as

1015
00:52:44,160 --> 00:52:47,239
Speaker 1: they would like, but as frequently as as we can UM,

1016
00:52:47,280 --> 00:52:48,960
Speaker 1: you know, on a weekly or bi weekly basis, to

1017
00:52:49,000 --> 00:52:53,919
Speaker 1: really work on their particular project. So yeah, a lot,

1018
00:52:54,080 --> 00:52:58,479
Speaker 1: hundreds of hundreds. I was asking to Liby this before

1019
00:52:58,520 --> 00:53:01,879
Speaker 1: we came on UM. Like you said, there's a lot

1020
00:53:01,880 --> 00:53:04,360
Speaker 1: of important work that goes on in the wildlife sciences

1021
00:53:04,360 --> 00:53:08,040
Speaker 1: in this building. And and but for for a conversation

1022
00:53:08,280 --> 00:53:11,160
Speaker 1: as relatively short as this would be, the kind of

1023
00:53:11,480 --> 00:53:14,560
Speaker 1: microwave all this into something that we want to really

1024
00:53:14,560 --> 00:53:16,640
Speaker 1: want to cover and talk about what's important for people

1025
00:53:16,680 --> 00:53:19,960
Speaker 1: to know. I'm gonna give Libby ships to set it up.

1026
00:53:20,440 --> 00:53:22,920
Speaker 1: It's a in a broad sense with what you guys

1027
00:53:22,920 --> 00:53:26,080
Speaker 1: work on with all the I read a lot of

1028
00:53:26,080 --> 00:53:28,080
Speaker 1: the papers and I've I've looked at kind of how

1029
00:53:28,160 --> 00:53:29,920
Speaker 1: you explain what you do and it's not just like

1030
00:53:30,160 --> 00:53:35,800
Speaker 1: chef or driver. It has more nuanced to it, I imagine.

1031
00:53:36,280 --> 00:53:41,200
Speaker 1: So give us, give us a rundown kind of how

1032
00:53:41,200 --> 00:53:42,400
Speaker 1: do you guys think about the world and what you

1033
00:53:42,440 --> 00:53:45,239
Speaker 1: try to achieve here. Yeah, that's a great question. I'll

1034
00:53:45,239 --> 00:53:48,040
Speaker 1: try not to screw it up. There's no wrong answer.

1035
00:53:48,760 --> 00:53:53,680
Speaker 1: You guys ever telling your students no wrong answer except

1036
00:53:53,719 --> 00:53:58,839
Speaker 1: when it's wrong. Everybody gets a trophy. Okay, Um, yeah,

1037
00:53:59,000 --> 00:54:04,120
Speaker 1: we are, our interests are we're social scientists and we

1038
00:54:04,200 --> 00:54:07,600
Speaker 1: study people, and we have the benefit of studying people

1039
00:54:07,760 --> 00:54:12,040
Speaker 1: in really cool natural places, and so are kind of

1040
00:54:12,040 --> 00:54:15,719
Speaker 1: a thread that we've between our research and the work

1041
00:54:15,719 --> 00:54:19,080
Speaker 1: we do here in our different programs is how we

1042
00:54:19,160 --> 00:54:23,640
Speaker 1: incorporate social science into decision making processes for natural resources.

1043
00:54:24,200 --> 00:54:26,640
Speaker 1: And so that's whether that's wildlife and thinking about how

1044
00:54:26,680 --> 00:54:30,560
Speaker 1: we integrate the science to understand how a community might

1045
00:54:30,600 --> 00:54:33,920
Speaker 1: tolerate a certain species, or how we think about different

1046
00:54:33,920 --> 00:54:37,000
Speaker 1: management actions that are coming out from state agencies or

1047
00:54:37,120 --> 00:54:40,360
Speaker 1: all the way through to UM kind of our three efforts,

1048
00:54:40,360 --> 00:54:43,000
Speaker 1: and how we use data and science to kind of

1049
00:54:43,040 --> 00:54:46,959
Speaker 1: inform our initiatives and where we should be directing UM

1050
00:54:47,000 --> 00:54:49,640
Speaker 1: efforts in the state. And so we're really interested in

1051
00:54:49,680 --> 00:54:53,080
Speaker 1: kind of that incorporating that social science into natural resource

1052
00:54:53,120 --> 00:54:56,400
Speaker 1: decision making process. What what brought you to that, I

1053
00:54:56,440 --> 00:54:58,799
Speaker 1: mean a little bit learned of what you currently do

1054
00:54:58,920 --> 00:55:00,960
Speaker 1: and and maybe what brought you do this place, but

1055
00:55:01,040 --> 00:55:04,360
Speaker 1: what brought you personally to those interests? Yeah, that's a

1056
00:55:04,360 --> 00:55:07,759
Speaker 1: good question. Uh, you know, I always think about like

1057
00:55:07,880 --> 00:55:10,400
Speaker 1: people always asked me how I got interested in studying

1058
00:55:10,400 --> 00:55:13,719
Speaker 1: gender and hunting, And I did my masters at West

1059
00:55:13,800 --> 00:55:18,239
Speaker 1: Virginia University, and prior to going to w VU, I

1060
00:55:18,280 --> 00:55:20,360
Speaker 1: really was not interested in hunting at all. It was

1061
00:55:20,400 --> 00:55:22,359
Speaker 1: not an activity I wanted to do. It was not

1062
00:55:22,480 --> 00:55:25,879
Speaker 1: an interest of mine. And starting to work in West

1063
00:55:25,920 --> 00:55:28,440
Speaker 1: Virginia and work with some of the local leaders and

1064
00:55:28,520 --> 00:55:31,040
Speaker 1: some of the locals on the ground, I started to

1065
00:55:31,120 --> 00:55:34,520
Speaker 1: understand how hunting was a critical part of the social

1066
00:55:34,560 --> 00:55:39,280
Speaker 1: fiber of that community and in particular how frequently women

1067
00:55:39,320 --> 00:55:43,160
Speaker 1: were out hunting, and just starting to understand the different

1068
00:55:43,160 --> 00:55:45,759
Speaker 1: motivations that women had. And one of the things I

1069
00:55:45,840 --> 00:55:51,439
Speaker 1: noticed was, um just obviously the bringing game home, game

1070
00:55:51,480 --> 00:55:54,000
Speaker 1: meat home to their families to support the livelihood of

1071
00:55:54,000 --> 00:55:56,520
Speaker 1: those families. And so that was something that stuck with

1072
00:55:56,600 --> 00:55:59,839
Speaker 1: me in my master's and then transferring up to Penn State,

1073
00:55:59,880 --> 00:56:01,560
Speaker 1: I had an opportunity to kind of explore that a

1074
00:56:01,600 --> 00:56:05,120
Speaker 1: little bit more, and so I just started to really

1075
00:56:05,160 --> 00:56:09,160
Speaker 1: think about how hunting as a recreation activity and how

1076
00:56:09,440 --> 00:56:14,120
Speaker 1: um women engaged in that sport, and how our decision

1077
00:56:14,120 --> 00:56:17,680
Speaker 1: makers were not really thinking or considering that particular group

1078
00:56:17,840 --> 00:56:20,720
Speaker 1: or segment of the population. And so that really inspired

1079
00:56:20,800 --> 00:56:23,839
Speaker 1: kind of my dissertation work. And from there it I

1080
00:56:23,920 --> 00:56:27,280
Speaker 1: just I fell in love with thinking about wildlife UM.

1081
00:56:27,360 --> 00:56:30,160
Speaker 1: And you know, I have like the anecdotal kind of

1082
00:56:30,480 --> 00:56:34,720
Speaker 1: like you know, reading um certain books like Prodigal Summer

1083
00:56:35,239 --> 00:56:37,200
Speaker 1: or uh, you know, some of the kind of more

1084
00:56:37,239 --> 00:56:40,759
Speaker 1: popular media books that talked a lot about carnivores or

1085
00:56:40,760 --> 00:56:43,440
Speaker 1: talked about predators in the relationship to animals and humans

1086
00:56:43,960 --> 00:56:47,879
Speaker 1: and just being totally romanticized by that and uh, when

1087
00:56:47,880 --> 00:56:50,560
Speaker 1: we you know, the call came out to work at

1088
00:56:50,640 --> 00:56:52,839
Speaker 1: University of Montana, and I was like, oh, I think

1089
00:56:52,840 --> 00:56:54,399
Speaker 1: I'm going to put my name in for that one.

1090
00:56:54,520 --> 00:56:59,920
Speaker 1: As department goes, that's exactly right, and so it just

1091
00:57:00,200 --> 00:57:03,320
Speaker 1: it just kind of it just developed from there. And Um,

1092
00:57:03,640 --> 00:57:05,320
Speaker 1: what we found when we got here to you M

1093
00:57:05,400 --> 00:57:09,640
Speaker 1: in the state is that our state agencies are colleagues

1094
00:57:09,640 --> 00:57:13,040
Speaker 1: that we're working with across campus. We're really just interested

1095
00:57:13,360 --> 00:57:16,880
Speaker 1: in how we use this social science to make decisions.

1096
00:57:17,120 --> 00:57:19,080
Speaker 1: And so we were able to translate a lot of

1097
00:57:19,080 --> 00:57:22,000
Speaker 1: the theories and the ideas that we've been practicing through

1098
00:57:22,040 --> 00:57:25,040
Speaker 1: graduate work and and actually apply those into a lot

1099
00:57:25,080 --> 00:57:27,480
Speaker 1: of real world settings out here. Cool. Well, give me,

1100
00:57:28,320 --> 00:57:29,600
Speaker 1: well the first thing that comes to your mind with

1101
00:57:29,680 --> 00:57:33,720
Speaker 1: application of those theories, give me the best example. That's

1102
00:57:33,760 --> 00:57:41,160
Speaker 1: a great question, um, and so coming, and that's that's

1103
00:57:41,160 --> 00:57:42,840
Speaker 1: the way that you get to the answer. You're like,

1104
00:57:42,920 --> 00:57:48,120
Speaker 1: you know, that's a wonderful question. I will I will

1105
00:57:48,160 --> 00:57:50,320
Speaker 1: refer back to this often during this conversation. But I

1106
00:57:50,360 --> 00:57:51,880
Speaker 1: just met with some of your students of b h

1107
00:57:51,960 --> 00:57:54,680
Speaker 1: A members and and I've every question they asked me.

1108
00:57:54,760 --> 00:57:57,800
Speaker 1: I replied with great question. Great question. That was only

1109
00:57:57,800 --> 00:58:00,880
Speaker 1: to delay So my sin apps is good fire, and

1110
00:58:00,880 --> 00:58:04,840
Speaker 1: I could think of something to say, UM, yeah, great question,

1111
00:58:05,240 --> 00:58:07,680
Speaker 1: great question. Um I you know it's a that's a

1112
00:58:07,720 --> 00:58:10,720
Speaker 1: great question. So I'll just take my gender work. Um

1113
00:58:11,160 --> 00:58:14,720
Speaker 1: I there's a particular theory called constraints theory, and we've

1114
00:58:14,720 --> 00:58:17,480
Speaker 1: applied this across different recreation settings, and so it's been

1115
00:58:17,600 --> 00:58:21,240
Speaker 1: used on persons with disabilities, it's been used on UM

1116
00:58:21,360 --> 00:58:24,640
Speaker 1: older adults, has been used on indoor recreation settings, outdoor

1117
00:58:24,640 --> 00:58:28,440
Speaker 1: recreation settings, and it had not been applied this theoretical

1118
00:58:28,440 --> 00:58:32,920
Speaker 1: approach to hunting. And so I went through and UH

1119
00:58:33,240 --> 00:58:36,200
Speaker 1: used the model to predict hunting behavior. And so I

1120
00:58:36,280 --> 00:58:39,920
Speaker 1: used how women were constrained by hunting, how they negotiated

1121
00:58:39,960 --> 00:58:43,560
Speaker 1: through that hunting. UM. I use measures like self efficacy,

1122
00:58:43,640 --> 00:58:45,720
Speaker 1: so their confidence that they felt while they were hunting,

1123
00:58:46,000 --> 00:58:48,160
Speaker 1: and also measures of social support. And so if you

1124
00:58:48,240 --> 00:58:50,680
Speaker 1: look through like a lot of the R three literature,

1125
00:58:50,720 --> 00:58:55,000
Speaker 1: these are things that you know, UM organizations are touching on.

1126
00:58:55,040 --> 00:58:57,240
Speaker 1: They're like, oh, you need mentors, you need support. And

1127
00:58:57,280 --> 00:58:59,080
Speaker 1: so what I did is just measure those using kind

1128
00:58:59,080 --> 00:59:02,520
Speaker 1: of tested measures out of psychology and social psychology and

1129
00:59:03,400 --> 00:59:05,800
Speaker 1: those details exactly how do you measure that it's a

1130
00:59:05,840 --> 00:59:09,320
Speaker 1: great question. How do you even do that? Um, Well,

1131
00:59:09,360 --> 00:59:12,400
Speaker 1: we are mixed method researchers and so uh we do

1132
00:59:12,480 --> 00:59:15,080
Speaker 1: a little bit of interviewing, um, but we do a

1133
00:59:15,120 --> 00:59:17,640
Speaker 1: lot of kind of survey work, and so we ask

1134
00:59:17,720 --> 00:59:20,600
Speaker 1: a lot of people questions. UM, and so we often

1135
00:59:20,680 --> 00:59:23,960
Speaker 1: have like a battery of questions. And so it's UM,

1136
00:59:24,000 --> 00:59:27,440
Speaker 1: I might ask you, tell me about your your hunting

1137
00:59:27,480 --> 00:59:29,720
Speaker 1: constraints on a scale of one to five, one being

1138
00:59:30,320 --> 00:59:33,320
Speaker 1: the least constrained, five being the most constrained. Tell me

1139
00:59:33,400 --> 00:59:36,640
Speaker 1: how um constrained were you buy these factors and they

1140
00:59:36,720 --> 00:59:45,880
Speaker 1: might have things like complex rules and regulations. Um, um

1141
00:59:45,920 --> 00:59:50,360
Speaker 1: you know um no time, uh, no resources, No, I

1142
00:59:50,360 --> 00:59:51,960
Speaker 1: don't know where to hunt, I don't have anyone to

1143
00:59:52,040 --> 00:59:54,440
Speaker 1: hunt with. And so then I'll get people to respond

1144
00:59:54,440 --> 00:59:57,000
Speaker 1: on a one to five Ler scale. And so I

1145
00:59:57,000 --> 01:00:02,040
Speaker 1: take that quantitative data and I actually, uh through the

1146
01:00:02,040 --> 01:00:05,480
Speaker 1: theory understand the relationships between certain variables. So I understand

1147
01:00:05,520 --> 01:00:08,360
Speaker 1: that you know you need contint you have constraints, but

1148
01:00:08,400 --> 01:00:11,360
Speaker 1: you also have these motivations that help you overcome those constraints.

1149
01:00:11,400 --> 01:00:19,520
Speaker 1: And so through complex sampling and complex statistical analysis, very complex,

1150
01:00:19,840 --> 01:00:23,240
Speaker 1: the most sophisticated only the most sophisticated modeling techniques that

1151
01:00:23,280 --> 01:00:26,520
Speaker 1: requires a calculator. It does. There's a nice like we

1152
01:00:26,560 --> 01:00:29,280
Speaker 1: have these like computers and these software systems and we

1153
01:00:29,480 --> 01:00:31,880
Speaker 1: throw in all the important details and then it spits

1154
01:00:31,920 --> 01:00:36,400
Speaker 1: out a model at the end um. But we're able

1155
01:00:36,400 --> 01:00:39,760
Speaker 1: to get to kind of these ultimate variables that were

1156
01:00:39,800 --> 01:00:43,280
Speaker 1: interested in. So I'm really interested in what's predicting hunting participation.

1157
01:00:43,840 --> 01:00:46,160
Speaker 1: And so from that, from my kind of model of

1158
01:00:46,320 --> 01:00:49,520
Speaker 1: our understanding women, I'm able to say, Okay, if they

1159
01:00:49,560 --> 01:00:52,160
Speaker 1: have more support, if they're more confident, if they have

1160
01:00:52,240 --> 01:00:54,800
Speaker 1: fewer constraints, than they are more likely to participate in

1161
01:00:54,840 --> 01:00:58,200
Speaker 1: some type of hunting activity. Yeah, I think that you

1162
01:00:58,200 --> 01:01:08,480
Speaker 1: have anything to add to that, alxhol this look what

1163
01:01:08,640 --> 01:01:11,520
Speaker 1: she said. That's it's super interesting to me. I know

1164
01:01:11,520 --> 01:01:13,280
Speaker 1: it always calls back to our three, but I think

1165
01:01:13,320 --> 01:01:16,160
Speaker 1: that there's a lot of conversations I've had recently that

1166
01:01:16,200 --> 01:01:20,280
Speaker 1: are around this the complexity of of those motivations, right,

1167
01:01:20,840 --> 01:01:23,040
Speaker 1: how we get to where we are right sitting in

1168
01:01:23,040 --> 01:01:25,919
Speaker 1: a room with your students here. Half an hour ago,

1169
01:01:26,480 --> 01:01:28,640
Speaker 1: I was just kind of studying their stories to try

1170
01:01:28,640 --> 01:01:31,479
Speaker 1: to determine how each of them came to be where

1171
01:01:31,480 --> 01:01:34,160
Speaker 1: they are today because there because I believe you guys

1172
01:01:34,240 --> 01:01:37,160
Speaker 1: and they are are both in a pretty amazing place

1173
01:01:37,200 --> 01:01:42,640
Speaker 1: where you're able to spend time analyzing these factors, understanding them,

1174
01:01:42,640 --> 01:01:46,240
Speaker 1: and then in articulating then to other folks. UM. So

1175
01:01:46,280 --> 01:01:48,720
Speaker 1: when you when you started on on this particular venture,

1176
01:01:49,120 --> 01:01:52,560
Speaker 1: like what difficulties you run into, what things you're looking for,

1177
01:01:53,160 --> 01:01:56,360
Speaker 1: what pitfalls and these kind of um studies are are

1178
01:01:56,400 --> 01:02:00,280
Speaker 1: out there? Yeah, I mean I can go right to

1179
01:02:00,320 --> 01:02:03,960
Speaker 1: my my most limiting factors of my research, which are

1180
01:02:03,960 --> 01:02:08,360
Speaker 1: always great. Sometimes Uh, it's really hard to get at

1181
01:02:08,640 --> 01:02:11,440
Speaker 1: to understand the people who are not engaging and hunting.

1182
01:02:11,960 --> 01:02:16,360
Speaker 1: There's not a list of non hunters out there. Damn,

1183
01:02:16,360 --> 01:02:20,200
Speaker 1: it is right. We could just do some targeted marketing. UM.

1184
01:02:20,400 --> 01:02:23,320
Speaker 1: They It's the same thing we often hear about kind

1185
01:02:23,320 --> 01:02:26,320
Speaker 1: of this elusive wildlife enthusiast group. Everyone wants to know

1186
01:02:26,360 --> 01:02:29,000
Speaker 1: about the wildlife enthusiasts or like, oh they're increasing more

1187
01:02:29,000 --> 01:02:31,760
Speaker 1: people are wildlife viewing, um, And then you go to

1188
01:02:31,800 --> 01:02:33,800
Speaker 1: want to study that group. There's no list of them,

1189
01:02:33,960 --> 01:02:37,560
Speaker 1: and so one of our challenges as researchers is finding

1190
01:02:37,600 --> 01:02:40,160
Speaker 1: the right sample of people to actually ask questions of

1191
01:02:40,840 --> 01:02:44,160
Speaker 1: and I think it's in particularly interesting with when it's

1192
01:02:44,200 --> 01:02:46,480
Speaker 1: related to our three, because you're really trying to capture

1193
01:02:46,480 --> 01:02:48,439
Speaker 1: the people who are not hunting. And so my work

1194
01:02:48,480 --> 01:02:52,320
Speaker 1: on gender was a study of it was males and females,

1195
01:02:52,360 --> 01:02:54,920
Speaker 1: but it was of people who are already big game hunting,

1196
01:02:55,120 --> 01:02:58,560
Speaker 1: and so I'm asking about the things that are constraining them,

1197
01:02:58,600 --> 01:03:01,800
Speaker 1: but they've overcome the constraints, and so it's almost kind

1198
01:03:01,840 --> 01:03:04,760
Speaker 1: of this like post talk analysis of how they did that,

1199
01:03:05,600 --> 01:03:08,320
Speaker 1: and um, what we're really interested in those people who

1200
01:03:08,320 --> 01:03:11,200
Speaker 1: aren't doing it, and so how do you find them?

1201
01:03:11,320 --> 01:03:12,800
Speaker 1: Is there an answer to that question? There is no

1202
01:03:12,920 --> 01:03:18,560
Speaker 1: answer question you don't hunt. Come over, I'll ask you

1203
01:03:18,600 --> 01:03:21,000
Speaker 1: a few questions. Do you start when you're thinking about

1204
01:03:21,040 --> 01:03:23,800
Speaker 1: these things? Do you start with a hypothesis of this

1205
01:03:23,880 --> 01:03:27,240
Speaker 1: is why more women aren't getting into hunting? Is there

1206
01:03:27,360 --> 01:03:31,240
Speaker 1: their concrete hypothesis? Are you working just from some sort

1207
01:03:31,240 --> 01:03:34,040
Speaker 1: of data set? That's a good question. There are some

1208
01:03:34,800 --> 01:03:38,240
Speaker 1: guiding research questions, and we we find those in hypotheses

1209
01:03:38,280 --> 01:03:41,480
Speaker 1: like when we actually get into the analysis. Um, but

1210
01:03:41,520 --> 01:03:43,880
Speaker 1: we we often try to figure out what's missing out

1211
01:03:43,880 --> 01:03:46,040
Speaker 1: of literature, and so you start with a kind of oh,

1212
01:03:46,040 --> 01:03:47,960
Speaker 1: I have this brilliant idea. Let's see if it's even

1213
01:03:47,960 --> 01:03:51,040
Speaker 1: been studied, and you start going and digging into the literature,

1214
01:03:51,040 --> 01:03:53,640
Speaker 1: which is made. Even in the twenty years that we've

1215
01:03:53,680 --> 01:03:57,080
Speaker 1: been through grad school and here, the internet has been

1216
01:03:57,120 --> 01:03:59,680
Speaker 1: phenomenal in that regard, so we were able to access

1217
01:03:59,720 --> 01:04:02,520
Speaker 1: a lot our research, um, and then we we we

1218
01:04:02,640 --> 01:04:06,440
Speaker 1: develop a research question out of that and UM and

1219
01:04:06,560 --> 01:04:09,200
Speaker 1: go from there. Yeah, I mean the methods will follow

1220
01:04:09,600 --> 01:04:12,560
Speaker 1: based on the question. Right. So you might have something

1221
01:04:12,600 --> 01:04:15,720
Speaker 1: that some phenomenon that you just don't know a lot

1222
01:04:15,720 --> 01:04:17,560
Speaker 1: about and you need to go learn more, and you

1223
01:04:17,600 --> 01:04:18,960
Speaker 1: need to do just what we're doing here. You go

1224
01:04:19,040 --> 01:04:21,960
Speaker 1: talk to people, you you know, train yourself to be

1225
01:04:22,000 --> 01:04:25,040
Speaker 1: a really good listener and ask really open ended questions

1226
01:04:25,200 --> 01:04:28,600
Speaker 1: and follow follow the threads, and those will lead you

1227
01:04:28,680 --> 01:04:33,000
Speaker 1: to you know, it sounds like a podcast absolutely, UM's

1228
01:04:33,040 --> 01:04:40,560
Speaker 1: your own private podcast, private podcast through research protections. Yeah.

1229
01:04:40,640 --> 01:04:43,560
Speaker 1: But then if you you know, let me mention we

1230
01:04:43,640 --> 01:04:45,880
Speaker 1: do kind of mixed methods. So we'll often pair that

1231
01:04:46,320 --> 01:04:50,960
Speaker 1: interview more exploratory research with some sort of quantitative follow

1232
01:04:51,040 --> 01:04:53,600
Speaker 1: up where out of that interviewing we come to a

1233
01:04:53,680 --> 01:04:57,320
Speaker 1: hypothesis and we wonder if if you know A is

1234
01:04:57,360 --> 01:05:01,520
Speaker 1: related to be or um and so will then design

1235
01:05:01,760 --> 01:05:04,640
Speaker 1: a quantitative study with a representative sample that allows us

1236
01:05:04,680 --> 01:05:07,960
Speaker 1: to infer up and scale up to pop you some populations,

1237
01:05:08,360 --> 01:05:11,880
Speaker 1: and so that's where the survey work comes in. So

1238
01:05:11,920 --> 01:05:13,800
Speaker 1: you guys brought some notes, you have some examples of

1239
01:05:13,840 --> 01:05:16,360
Speaker 1: your works. It's time to get in and go. I

1240
01:05:16,440 --> 01:05:21,600
Speaker 1: like to still a good podcast fodder here, papers, papers, rattling,

1241
01:05:23,720 --> 01:05:27,760
Speaker 1: two mediums beating each other. Good academics of our papers

1242
01:05:27,840 --> 01:05:31,000
Speaker 1: right now. I appreciate that I should have brought some papers. Um,

1243
01:05:31,080 --> 01:05:33,439
Speaker 1: so give me like, let's let's let's start with one

1244
01:05:33,480 --> 01:05:35,440
Speaker 1: of pick your favorite. You got looks like you have

1245
01:05:35,440 --> 01:05:40,000
Speaker 1: about eight or nine. Um, pick your favorite and tell

1246
01:05:40,040 --> 01:05:42,600
Speaker 1: me is give us a quick rundown of you know,

1247
01:05:43,160 --> 01:05:46,640
Speaker 1: one of these studies and we're and we'll dissect it.

1248
01:05:46,760 --> 01:05:49,040
Speaker 1: I've read a few of them, and talking about Elkin brucellosis,

1249
01:05:49,080 --> 01:05:50,920
Speaker 1: I was insane. Why would you have not start with

1250
01:05:50,960 --> 01:05:53,360
Speaker 1: that one? It's like my our favorite one, I said,

1251
01:05:53,360 --> 01:05:55,080
Speaker 1: my favorite, your favorite? I don't know. You're just playing

1252
01:05:55,080 --> 01:05:58,320
Speaker 1: the hits right now. Yeah, we're playing the hits. Yeah.

1253
01:05:58,320 --> 01:06:00,480
Speaker 1: One of the first studies that we call liabrated with

1254
01:06:01,120 --> 01:06:05,920
Speaker 1: Montana Fish Wildlife, and Parkson was trying to understand, um,

1255
01:06:05,960 --> 01:06:09,120
Speaker 1: you know, how the agency could approach the elk and

1256
01:06:09,160 --> 01:06:11,720
Speaker 1: brucellois management problem that they have out of Yellowstone and

1257
01:06:12,240 --> 01:06:14,000
Speaker 1: let me see if I can do this briefly. But

1258
01:06:14,040 --> 01:06:18,120
Speaker 1: you know, brucellosis is a plenty plenty of time. Brucellois

1259
01:06:18,160 --> 01:06:21,960
Speaker 1: is a pretty um nasty disease that was introduced by

1260
01:06:22,000 --> 01:06:25,919
Speaker 1: livestock originally you know, hundreds and someone years ago. Uh,

1261
01:06:26,000 --> 01:06:30,320
Speaker 1: it's now in the wildlife populations UM and is often

1262
01:06:30,360 --> 01:06:33,200
Speaker 1: transmitted back to cattle, which is bad news if you

1263
01:06:33,280 --> 01:06:38,000
Speaker 1: like to eat steak or sell steak. UM. And so yeah,

1264
01:06:38,000 --> 01:06:40,840
Speaker 1: so there's lots of options on the table for how

1265
01:06:40,840 --> 01:06:43,960
Speaker 1: to manage kind of elk on the landscape and keep

1266
01:06:43,960 --> 01:06:47,080
Speaker 1: them from interacting with cattle and spreading the disease. And

1267
01:06:47,120 --> 01:06:50,480
Speaker 1: so there's been UM lots of effort by UM, the

1268
01:06:50,520 --> 01:06:53,240
Speaker 1: Cooperative Unit here on campus, Mike Mitchell and some other

1269
01:06:53,240 --> 01:06:56,320
Speaker 1: folks have to WP too, to kind of collaboratively get

1270
01:06:56,600 --> 01:06:59,600
Speaker 1: the major stakeholders involved to come up with some options.

1271
01:07:00,040 --> 01:07:02,040
Speaker 1: But they wanted to know what the broader public thought

1272
01:07:02,040 --> 01:07:07,400
Speaker 1: about that, both just general Montana residents, UM landowners specifically,

1273
01:07:07,720 --> 01:07:10,560
Speaker 1: but also hunters, and so we worked with them to

1274
01:07:10,640 --> 01:07:13,760
Speaker 1: do kind of a three tiered study of those groups

1275
01:07:14,400 --> 01:07:18,520
Speaker 1: UM in a concentrated area right outside Yellowstone, UM as

1276
01:07:18,560 --> 01:07:20,400
Speaker 1: well as across the states. We could just kind of

1277
01:07:20,480 --> 01:07:25,520
Speaker 1: understand how the whole Montana public felt. UM. Yeah. And

1278
01:07:25,520 --> 01:07:27,760
Speaker 1: it's one of those opportunities where you go in with

1279
01:07:27,880 --> 01:07:30,960
Speaker 1: lots of ideas about what might matter. Right, Like we

1280
01:07:31,040 --> 01:07:35,000
Speaker 1: thought going in that when once cattle were infected, that

1281
01:07:35,080 --> 01:07:37,240
Speaker 1: people would change their minds, like it's an emergency, we

1282
01:07:37,320 --> 01:07:42,640
Speaker 1: got to do something about it. UM. We thought that UM,

1283
01:07:42,680 --> 01:07:45,520
Speaker 1: you know, the the kind of status of the elk

1284
01:07:45,600 --> 01:07:49,000
Speaker 1: population would be really important UM. And that that did

1285
01:07:49,040 --> 01:07:51,200
Speaker 1: come out, But what really rose to the top at

1286
01:07:51,200 --> 01:07:53,320
Speaker 1: the end of the day was like public access to

1287
01:07:53,360 --> 01:07:57,960
Speaker 1: private lands. So it didn't really matter what kind of

1288
01:07:57,960 --> 01:08:00,520
Speaker 1: tool we were talking about. It didn't matter what stakeholder

1289
01:08:00,520 --> 01:08:02,840
Speaker 1: group we were talking about. The public, hunters and landowners

1290
01:08:02,920 --> 01:08:09,440
Speaker 1: themselves wanted to see landowners reciprocate with public access if

1291
01:08:09,480 --> 01:08:11,800
Speaker 1: they were going to receive some sort of assistance from

1292
01:08:11,840 --> 01:08:16,080
Speaker 1: the state. UM. And so it puts an interesting kind

1293
01:08:16,080 --> 01:08:19,639
Speaker 1: of context to the discussion UM of the issue here.

1294
01:08:19,840 --> 01:08:21,960
Speaker 1: And so yeah, and what I think what I like

1295
01:08:22,000 --> 01:08:24,639
Speaker 1: about it is that we have this you know, uh

1296
01:08:24,800 --> 01:08:30,599
Speaker 1: nasty publication um with lots of numbers and citations, um,

1297
01:08:30,720 --> 01:08:34,240
Speaker 1: and no pictures. I think I think we successfully avoided

1298
01:08:34,240 --> 01:08:40,080
Speaker 1: any picture pictures to help a public charts. Yeah, I

1299
01:08:40,120 --> 01:08:43,040
Speaker 1: think to lead off and say that what you first

1300
01:08:43,080 --> 01:08:46,280
Speaker 1: found is that these people were united on access is

1301
01:08:46,439 --> 01:08:49,120
Speaker 1: very surprising to me. I don't know what do you

1302
01:08:49,120 --> 01:08:52,240
Speaker 1: attribute that to? Is it the place they live? Because

1303
01:08:52,240 --> 01:08:54,160
Speaker 1: that's not that can't be the case across the country,

1304
01:08:54,240 --> 01:08:56,480
Speaker 1: not in my experience, at least with LU the anecdotal

1305
01:08:56,479 --> 01:09:00,200
Speaker 1: evidence less than yeah. Um yeah, I mean I don't

1306
01:09:00,240 --> 01:09:02,840
Speaker 1: think we've got into the mechanisms of it, so I

1307
01:09:03,720 --> 01:09:08,880
Speaker 1: um hesitate to speculate on what what that is, but um,

1308
01:09:08,920 --> 01:09:12,000
Speaker 1: you know it's it's something that some stakeholders advocate for

1309
01:09:12,160 --> 01:09:15,559
Speaker 1: and other stakeholders advocate against, and so what allows us

1310
01:09:15,600 --> 01:09:18,920
Speaker 1: to live is shaking ahead of me. I'm always I'm

1311
01:09:18,920 --> 01:09:21,880
Speaker 1: always the one who's like, I'm underselling. I'm trying to

1312
01:09:21,880 --> 01:09:24,439
Speaker 1: say at least as possible. I don't even know why

1313
01:09:24,479 --> 01:09:26,920
Speaker 1: you wouldn't just this is a perfect example, Like, so

1314
01:09:26,960 --> 01:09:30,760
Speaker 1: we couch this idea in reciprocity and so when we're

1315
01:09:30,760 --> 01:09:39,360
Speaker 1: thinking about am I right, yeah, yeah, And so the

1316
01:09:39,400 --> 01:09:42,160
Speaker 1: idea that if you're going to get something from the state,

1317
01:09:42,280 --> 01:09:45,120
Speaker 1: that you have to give back. And so this idea

1318
01:09:45,120 --> 01:09:48,080
Speaker 1: of reciprocity is is if we go back to like

1319
01:09:48,200 --> 01:09:51,600
Speaker 1: core human values, this is a thing. This is a

1320
01:09:51,680 --> 01:09:54,439
Speaker 1: thing that people like. They want to know that if

1321
01:09:54,439 --> 01:09:56,920
Speaker 1: they are giving, they're getting something back in return. And

1322
01:09:56,960 --> 01:10:00,240
Speaker 1: that's just kind of human nature. And so the idea

1323
01:10:00,240 --> 01:10:02,760
Speaker 1: of reciprocity in terms of getting assistance from the state

1324
01:10:02,800 --> 01:10:06,320
Speaker 1: and then opening up your your land for hunting is

1325
01:10:06,880 --> 01:10:08,960
Speaker 1: a real thing. But the best case scenario for the

1326
01:10:09,439 --> 01:10:11,720
Speaker 1: shared ideas and the culture of a place used to

1327
01:10:11,760 --> 01:10:14,639
Speaker 1: have that reciprocity be so ingrained that that even when

1328
01:10:14,680 --> 01:10:16,599
Speaker 1: even in a micro case like this that it's it's

1329
01:10:16,640 --> 01:10:19,759
Speaker 1: it's evident, is a mate, it's great, it's great news,

1330
01:10:20,479 --> 01:10:22,800
Speaker 1: It is cool news. What else is in there? It

1331
01:10:22,840 --> 01:10:25,160
Speaker 1: was a good study? Um what what what did you find?

1332
01:10:25,160 --> 01:10:26,960
Speaker 1: In the end? As you as you wrote your paper

1333
01:10:27,000 --> 01:10:28,840
Speaker 1: there with I was gonna say, like, we wrote this

1334
01:10:28,960 --> 01:10:32,479
Speaker 1: nasty thing, but it was nice. Is an FVP really

1335
01:10:32,600 --> 01:10:37,040
Speaker 1: kind of forced us to think, um, you know, outside

1336
01:10:37,080 --> 01:10:39,240
Speaker 1: the box in terms of how to communicate our work

1337
01:10:39,240 --> 01:10:40,880
Speaker 1: at the end of the day, and so we have

1338
01:10:41,080 --> 01:10:44,280
Speaker 1: you know, we survive here by publishing, so that exists,

1339
01:10:44,320 --> 01:10:47,040
Speaker 1: but um, working with them to put together kind of

1340
01:10:47,040 --> 01:10:51,600
Speaker 1: a graphical uh representation of this research at the end

1341
01:10:51,640 --> 01:10:54,559
Speaker 1: of the day. UM. And so what this allows us

1342
01:10:54,600 --> 01:10:57,280
Speaker 1: to do is to take all of these things that

1343
01:10:57,320 --> 01:10:59,599
Speaker 1: people think are important and put them all into one

1344
01:10:59,640 --> 01:11:03,479
Speaker 1: model and understand how they really, um you know what

1345
01:11:03,600 --> 01:11:05,960
Speaker 1: comes out on top. And that's when that public access

1346
01:11:06,000 --> 01:11:09,920
Speaker 1: came you know, came out as kind of the strongest piece.

1347
01:11:10,240 --> 01:11:12,519
Speaker 1: So when we put it up against whether people like

1348
01:11:12,600 --> 01:11:14,439
Speaker 1: to see animals killed or not, whether we put it

1349
01:11:14,520 --> 01:11:18,040
Speaker 1: up against um, whether the elk population is high or low,

1350
01:11:18,240 --> 01:11:20,519
Speaker 1: whether cattle have been infected or not, that's like, that's

1351
01:11:20,520 --> 01:11:24,880
Speaker 1: an amazing together. Yeah. Yeah, you're talking about economic driver

1352
01:11:25,400 --> 01:11:29,640
Speaker 1: for private landowners that is seemingly put set aside at

1353
01:11:29,680 --> 01:11:34,439
Speaker 1: some level for for this idea of respirosity. Yeah. Well,

1354
01:11:34,479 --> 01:11:37,719
Speaker 1: and it's kind of cool because, um, you know, sometimes

1355
01:11:38,120 --> 01:11:41,519
Speaker 1: when we work with FLBP, they're looking um to make

1356
01:11:41,560 --> 01:11:43,800
Speaker 1: sure that they're you know, they they're looking for help

1357
01:11:43,840 --> 01:11:45,840
Speaker 1: to make sure they're thinking about an issue the right

1358
01:11:45,880 --> 01:11:47,800
Speaker 1: way and that they're they so a lot of times

1359
01:11:47,840 --> 01:11:49,680
Speaker 1: we'll work with the state when it's you know, a

1360
01:11:49,720 --> 01:11:52,559
Speaker 1: little bit more of a controversial issue, or they're looking

1361
01:11:52,600 --> 01:11:56,120
Speaker 1: for some kind of um assistance with the scientific kind

1362
01:11:56,160 --> 01:11:59,400
Speaker 1: of robustness of a particular study, and so we'll come

1363
01:11:59,439 --> 01:12:01,880
Speaker 1: in work intimately and closely with the state to come

1364
01:12:01,960 --> 01:12:04,439
Speaker 1: up with an idea, and then they kind of turn

1365
01:12:04,520 --> 01:12:06,200
Speaker 1: it over to us to do the sampling and to

1366
01:12:06,320 --> 01:12:08,280
Speaker 1: make sure we're asking the right questions and who we're

1367
01:12:08,320 --> 01:12:10,840
Speaker 1: asking them of. And so as as we think about this,

1368
01:12:10,920 --> 01:12:14,000
Speaker 1: and my husband would be modest, but he is really

1369
01:12:14,200 --> 01:12:16,920
Speaker 1: good at sampling, and so how do we sample people

1370
01:12:16,960 --> 01:12:19,760
Speaker 1: in a way that statistically sound? And so he thinks

1371
01:12:19,800 --> 01:12:23,040
Speaker 1: about this over and over and over. The ladies guys, yeah,

1372
01:12:24,000 --> 01:12:28,519
Speaker 1: sampling sare just talking. We're just about my college duds.

1373
01:12:30,240 --> 01:12:34,880
Speaker 1: It's really tired grad school. It's as I went to

1374
01:12:34,920 --> 01:12:38,840
Speaker 1: a school that was all girls before I went there

1375
01:12:38,840 --> 01:12:41,759
Speaker 1: and played the numbers that I lost. But I'm still

1376
01:12:41,800 --> 01:12:46,000
Speaker 1: I still stand behind my strategy. But so we thought,

1377
01:12:46,040 --> 01:12:48,960
Speaker 1: think about it. We sampled, and we in the statistics,

1378
01:12:48,960 --> 01:12:51,880
Speaker 1: and we did some waiting and and so this represents

1379
01:12:51,960 --> 01:12:54,080
Speaker 1: the groups that we intended to represent. And so a

1380
01:12:54,080 --> 01:12:56,040
Speaker 1: lot of times people like, oh, it's social science, you've

1381
01:12:56,080 --> 01:12:58,519
Speaker 1: manipulated the data. No, we didn't. This is this is

1382
01:12:58,920 --> 01:13:03,960
Speaker 1: you know, we followed a pretty um you know, rigorous

1383
01:13:04,080 --> 01:13:06,559
Speaker 1: approach from the start, and so we can we are

1384
01:13:06,600 --> 01:13:08,920
Speaker 1: confident when we say this is how people fell across

1385
01:13:08,920 --> 01:13:12,200
Speaker 1: the state, and we didn't just we we sampled landowners

1386
01:13:12,280 --> 01:13:15,040
Speaker 1: as a particular group, We sampled hunters, and then we

1387
01:13:15,080 --> 01:13:17,599
Speaker 1: had a general population as well, and so we got

1388
01:13:17,640 --> 01:13:20,120
Speaker 1: kind of all these these three different groups that the

1389
01:13:20,160 --> 01:13:22,920
Speaker 1: agency is really interested. Like any any science, at the

1390
01:13:22,960 --> 01:13:24,679
Speaker 1: end of the day, it's up to the decision makers

1391
01:13:24,800 --> 01:13:28,560
Speaker 1: in charge to weigh all sorts of different evidence. UM.

1392
01:13:28,760 --> 01:13:32,560
Speaker 1: I think our role is to put numbers to the

1393
01:13:32,640 --> 01:13:36,120
Speaker 1: human dimension to this instead of lots of speculation or

1394
01:13:36,160 --> 01:13:39,400
Speaker 1: people saying they speak for the majority, let's go actually

1395
01:13:39,439 --> 01:13:42,160
Speaker 1: measure that. Yeah. In this podcast, we have been having

1396
01:13:42,200 --> 01:13:45,320
Speaker 1: a lot of conversations about our model of conservation and

1397
01:13:45,400 --> 01:13:49,200
Speaker 1: talking about how you know, each step of that process.

1398
01:13:49,479 --> 01:13:52,760
Speaker 1: And this is heartening to me because it is highlighting

1399
01:13:52,760 --> 01:13:56,760
Speaker 1: how science, um and even social science, which we don't

1400
01:13:56,760 --> 01:13:59,839
Speaker 1: think of a lot as hunters, how social science impacts

1401
01:14:00,000 --> 01:14:03,320
Speaker 1: wildlife management on a state level. Which is what what

1402
01:14:03,439 --> 01:14:06,200
Speaker 1: which really the key, the center point of our model

1403
01:14:06,200 --> 01:14:08,639
Speaker 1: of conservation. And so what you guys are talking about

1404
01:14:08,760 --> 01:14:12,240
Speaker 1: is hopefully for everyone listening, if you were ever to

1405
01:14:12,320 --> 01:14:16,840
Speaker 1: doubt the science or biology that's baked into state wildlife management,

1406
01:14:16,960 --> 01:14:19,680
Speaker 1: they're holding these these animals and trust for all of us.

1407
01:14:20,080 --> 01:14:22,360
Speaker 1: This is a great example of how how this leads

1408
01:14:22,439 --> 01:14:23,880
Speaker 1: up and why I really wanted to come and chat

1409
01:14:23,880 --> 01:14:26,320
Speaker 1: with you guys exactly what you're just said. And it's

1410
01:14:26,360 --> 01:14:31,479
Speaker 1: the fact that you're talking about elk transferring disease to

1411
01:14:32,720 --> 01:14:36,320
Speaker 1: a money crop, which is cattle, and people still not

1412
01:14:36,479 --> 01:14:40,160
Speaker 1: I mean, that's the common trope in the West, is

1413
01:14:40,200 --> 01:14:43,439
Speaker 1: the private landowner versus the public land user. And the

1414
01:14:43,479 --> 01:14:45,840
Speaker 1: way that that all the way that all works out

1415
01:14:46,280 --> 01:14:48,960
Speaker 1: when you guys are talking to these survey folks, how

1416
01:14:49,040 --> 01:14:50,439
Speaker 1: do you how do you speak to them? Do they

1417
01:14:50,439 --> 01:14:52,679
Speaker 1: fill out a form? Do you speak to them personally?

1418
01:14:52,880 --> 01:14:56,679
Speaker 1: Obviously not Again, we do it different ways for different studies,

1419
01:14:56,720 --> 01:14:59,720
Speaker 1: but you know, we do a lot of mail surveys

1420
01:15:00,080 --> 01:15:03,520
Speaker 1: um so we you know, are mailing you a packet

1421
01:15:03,560 --> 01:15:06,880
Speaker 1: of uh, you know, a letter and a questionnaire that

1422
01:15:07,000 --> 01:15:08,559
Speaker 1: you fill out and if you don't fill it out,

1423
01:15:08,760 --> 01:15:11,280
Speaker 1: we will send you a postcard to say, please fill

1424
01:15:11,280 --> 01:15:12,920
Speaker 1: it out. If you don't fill it out, we'll send

1425
01:15:12,960 --> 01:15:16,679
Speaker 1: you another one come to your house. If I couldn't

1426
01:15:16,720 --> 01:15:19,560
Speaker 1: have the time, I would. Yeah. We want the easiest

1427
01:15:19,560 --> 01:15:21,080
Speaker 1: path to be to fill it out and send it

1428
01:15:21,080 --> 01:15:24,599
Speaker 1: back to us. Um. Yeah, so a lot of that. Again,

1429
01:15:24,640 --> 01:15:26,080
Speaker 1: we do a lot of interviews too, so we'll go

1430
01:15:26,120 --> 01:15:28,680
Speaker 1: out and talk to people and record those interviews and

1431
01:15:28,680 --> 01:15:32,040
Speaker 1: the and the words become the data. Particularly with elk

1432
01:15:32,200 --> 01:15:34,840
Speaker 1: in in brucellosis. Did you have any interactions with the

1433
01:15:34,880 --> 01:15:38,719
Speaker 1: private landowners that you felt were impactful. Yeah. So, UM.

1434
01:15:38,880 --> 01:15:42,800
Speaker 1: I sometimes get the UM. The position of being the

1435
01:15:42,840 --> 01:15:46,120
Speaker 1: person of contact on surveys. I think, my this is

1436
01:15:46,160 --> 01:15:48,280
Speaker 1: my husband gladly defers to me to be that person

1437
01:15:49,520 --> 01:15:52,160
Speaker 1: more affable, gets the calls. Yeah. So I get the

1438
01:15:52,200 --> 01:15:57,280
Speaker 1: calls and UM and they end better. I mean I

1439
01:15:57,320 --> 01:15:59,840
Speaker 1: really I I truly enjoy talking to people, and so

1440
01:16:00,240 --> 01:16:02,320
Speaker 1: the idea that I get to pick up the phone

1441
01:16:02,360 --> 01:16:04,760
Speaker 1: and talk somebody through our survey in the importance of

1442
01:16:04,800 --> 01:16:08,960
Speaker 1: filling it out. And it's really interesting because we've got landowners, hunters,

1443
01:16:08,960 --> 01:16:10,519
Speaker 1: we got all sorts of people. We've got husbands and

1444
01:16:10,560 --> 01:16:13,680
Speaker 1: wives like UM, and they all have something they want

1445
01:16:13,680 --> 01:16:16,200
Speaker 1: to tell me about the survey or about the issue

1446
01:16:16,240 --> 01:16:19,280
Speaker 1: that we're actually studying, and so um and so part

1447
01:16:19,320 --> 01:16:22,679
Speaker 1: of this research is sometimes just listening to the person

1448
01:16:22,800 --> 01:16:25,439
Speaker 1: unting of their end of the phone and if they

1449
01:16:25,439 --> 01:16:27,320
Speaker 1: have a complaint or if they have an issue, and

1450
01:16:27,439 --> 01:16:31,680
Speaker 1: just being willing to have that conversation. And so there

1451
01:16:31,760 --> 01:16:35,080
Speaker 1: was like you know, we get minor things like um,

1452
01:16:35,560 --> 01:16:37,439
Speaker 1: one wife called me and said, why didn't I get

1453
01:16:37,479 --> 01:16:39,800
Speaker 1: the survey? I'm a hunter? And so then you have

1454
01:16:39,840 --> 01:16:42,040
Speaker 1: to talk through sampling and you know, this is a

1455
01:16:42,080 --> 01:16:44,799
Speaker 1: simple random sample and so you weren't chosen. Your husband

1456
01:16:44,840 --> 01:16:47,920
Speaker 1: was chosen. And absolutely your voice is important and here

1457
01:16:47,920 --> 01:16:50,240
Speaker 1: are the ways that I think you can contribute to,

1458
01:16:50,760 --> 01:16:54,519
Speaker 1: you know, wildlife conservation. Then you get folks who think

1459
01:16:54,520 --> 01:16:57,160
Speaker 1: you're asking the wrong questions. Why would you ask this question?

1460
01:16:57,200 --> 01:17:00,160
Speaker 1: This is a stupid question, It's totally leading. How do

1461
01:17:00,200 --> 01:17:01,600
Speaker 1: you not how do you live your life as a

1462
01:17:01,680 --> 01:17:03,960
Speaker 1: social scientist and not just want to punch yourself in

1463
01:17:04,040 --> 01:17:07,200
Speaker 1: the faith like I had I had an interaction this morning.

1464
01:17:07,200 --> 01:17:12,000
Speaker 1: We're like social sciences, they're they're not talking le what

1465
01:17:12,479 --> 01:17:15,280
Speaker 1: like I don't how did you possibly make that inference

1466
01:17:15,920 --> 01:17:18,160
Speaker 1: from nothing that you know, and so I think that

1467
01:17:18,800 --> 01:17:20,439
Speaker 1: I'm sure that's you deal with that all the time

1468
01:17:21,479 --> 01:17:23,920
Speaker 1: and then and you have to just I mean, we

1469
01:17:24,040 --> 01:17:26,719
Speaker 1: just systematically go through like here are the stuffs we took,

1470
01:17:26,720 --> 01:17:28,120
Speaker 1: here's why we did it. Let me tell you a

1471
01:17:28,160 --> 01:17:29,960
Speaker 1: little bit about the waiting will do. Here's how I

1472
01:17:30,000 --> 01:17:34,479
Speaker 1: think it represents UM. And that's where we like, what's

1473
01:17:34,479 --> 01:17:37,840
Speaker 1: cool about us. I think as as a university professors

1474
01:17:37,840 --> 01:17:41,040
Speaker 1: and faculty, we we have that training and grounding to

1475
01:17:41,120 --> 01:17:46,120
Speaker 1: feel confident in the design that we've chosen. And UM. Yeah,

1476
01:17:46,200 --> 01:17:48,479
Speaker 1: we don't do it perfectly. We don't ask the perfect

1477
01:17:48,520 --> 01:17:52,639
Speaker 1: questions every single go around UM, but we we strive

1478
01:17:52,760 --> 01:17:57,360
Speaker 1: for kind of developing solid questions and we do all

1479
01:17:57,360 --> 01:18:00,719
Speaker 1: sorts of crazy stuff to UM to check these surveys

1480
01:18:00,760 --> 01:18:03,160
Speaker 1: before they go out. We pre test it on like

1481
01:18:03,280 --> 01:18:05,160
Speaker 1: all of our students, so we make our And you

1482
01:18:05,200 --> 01:18:08,200
Speaker 1: think the public's critical, try giving your survey to all

1483
01:18:08,240 --> 01:18:11,880
Speaker 1: your students. I met some of them pretty critical people.

1484
01:18:14,439 --> 01:18:16,639
Speaker 1: We got that critical part of the critical thinking down.

1485
01:18:16,680 --> 01:18:19,639
Speaker 1: He really didn't give me all your feedback and then

1486
01:18:19,680 --> 01:18:22,160
Speaker 1: it's like tore it apart and they're like, like you know,

1487
01:18:22,240 --> 01:18:24,439
Speaker 1: like yelling at you on paper and you're like, Okay,

1488
01:18:24,479 --> 01:18:28,160
Speaker 1: I have feelings too about this red pen for something,

1489
01:18:29,240 --> 01:18:31,160
Speaker 1: and so we do that. We we test it there.

1490
01:18:31,280 --> 01:18:33,040
Speaker 1: We of course, if we're doing work for the agency,

1491
01:18:33,040 --> 01:18:36,160
Speaker 1: the agency is working with us on that survey development,

1492
01:18:36,200 --> 01:18:38,320
Speaker 1: so they're comfortable with the kind of questions we're asking.

1493
01:18:38,479 --> 01:18:41,240
Speaker 1: We'll send it to colleagues across the country to critique

1494
01:18:41,240 --> 01:18:43,800
Speaker 1: and review. And you know a lot of the a

1495
01:18:43,840 --> 01:18:46,599
Speaker 1: lot of the questions that we use, um, we don't

1496
01:18:46,600 --> 01:18:49,200
Speaker 1: come up with on the fly. They've been used you know,

1497
01:18:49,240 --> 01:18:51,680
Speaker 1: in the literature and in other studies over and over,

1498
01:18:51,760 --> 01:18:54,720
Speaker 1: and so there's some validity that's been built over time.

1499
01:18:56,080 --> 01:18:59,360
Speaker 1: But it's a it's definitely young science. Um, yeah, it is.

1500
01:18:59,560 --> 01:19:01,599
Speaker 1: And like I said, a lot of people there's there's

1501
01:19:02,479 --> 01:19:04,599
Speaker 1: the methodology I think is important to cover here because

1502
01:19:04,600 --> 01:19:07,479
Speaker 1: people it's I think it's relatively easy from the outside

1503
01:19:07,479 --> 01:19:10,240
Speaker 1: looking into poke holes and in some of these methodologies, um,

1504
01:19:10,640 --> 01:19:13,160
Speaker 1: so specifically ELK and brucellosis. When you when you go

1505
01:19:13,240 --> 01:19:16,439
Speaker 1: to write this paper, what's your interaction with f WP,

1506
01:19:17,240 --> 01:19:20,280
Speaker 1: you know, what are they grading you on or are

1507
01:19:20,320 --> 01:19:23,640
Speaker 1: you how are they thinking about the result that you

1508
01:19:23,680 --> 01:19:25,360
Speaker 1: know this paper that you're turning in at the end

1509
01:19:25,360 --> 01:19:27,639
Speaker 1: of the process. Yeah, I mean I think that they

1510
01:19:27,680 --> 01:19:30,320
Speaker 1: want to know. I mean hesitate to speak for them,

1511
01:19:30,360 --> 01:19:32,000
Speaker 1: but but they want to know when they go to

1512
01:19:32,040 --> 01:19:34,840
Speaker 1: the commission to say, you know, just just as they

1513
01:19:34,880 --> 01:19:39,439
Speaker 1: would with a population model of elk UM. They want

1514
01:19:39,439 --> 01:19:43,320
Speaker 1: to say with confidence that you know, the data are

1515
01:19:43,360 --> 01:19:46,200
Speaker 1: what the data are, and that people people's attitudes are

1516
01:19:46,320 --> 01:19:50,640
Speaker 1: this UM. And so the pure review process allows, you know,

1517
01:19:50,680 --> 01:19:53,519
Speaker 1: a higher level of confidence in in those data and

1518
01:19:53,720 --> 01:19:56,960
Speaker 1: in our results. So you know, so they'll defer to

1519
01:19:57,200 --> 01:20:00,360
Speaker 1: us in terms of thinking about what the theoretical aiming

1520
01:20:00,439 --> 01:20:02,400
Speaker 1: is and how to kind of couch this in the

1521
01:20:02,520 --> 01:20:07,519
Speaker 1: existing literature. Um. And then as that goes through the

1522
01:20:07,520 --> 01:20:11,599
Speaker 1: pure review process, the results then are much more robust

1523
01:20:11,680 --> 01:20:13,519
Speaker 1: for them to have some confidence when they present them

1524
01:20:13,520 --> 01:20:17,360
Speaker 1: to the commission. So what did they present this case? Um?

1525
01:20:17,400 --> 01:20:20,360
Speaker 1: I think what's the abstract? I think I presented it

1526
01:20:20,400 --> 01:20:24,960
Speaker 1: and pant I was pregnant, so uncomfortable, so I'm like,

1527
01:20:25,720 --> 01:20:28,080
Speaker 1: I'm only pregnant enough at the time, so it was like,

1528
01:20:28,160 --> 01:20:30,640
Speaker 1: did I eat like an extra hamburger or was that

1529
01:20:30,720 --> 01:20:38,840
Speaker 1: a belly? That's the awkward stage pregnancy that Um. Yeah,

1530
01:20:39,320 --> 01:20:41,800
Speaker 1: now and then and then I had pregnancy brain. So

1531
01:20:41,840 --> 01:20:43,639
Speaker 1: it was actually probably better that I did it, because

1532
01:20:43,640 --> 01:20:46,240
Speaker 1: then if I probably didn't even remember that it happened

1533
01:20:46,240 --> 01:20:52,080
Speaker 1: at the time, he was eating ice cream and you

1534
01:20:52,120 --> 01:20:58,240
Speaker 1: want don't talk. It was it was comical, I remember that. UM.

1535
01:20:58,280 --> 01:21:00,479
Speaker 1: And so we we presented them with kind of our

1536
01:21:00,479 --> 01:21:03,559
Speaker 1: our key findings. We talked about the access to private lands,

1537
01:21:03,840 --> 01:21:11,080
Speaker 1: We talked about having uh that elk population objectives were

1538
01:21:11,160 --> 01:21:15,960
Speaker 1: somewhat UM. People wanted to see some regulation that followed

1539
01:21:16,000 --> 01:21:19,639
Speaker 1: some of the population objectives UM, which like as elk

1540
01:21:19,720 --> 01:21:24,920
Speaker 1: populations were too abundant, like above objective that people were

1541
01:21:24,960 --> 01:21:29,280
Speaker 1: more okay with kind of UM, you know, more lethal control,

1542
01:21:29,400 --> 01:21:33,120
Speaker 1: more heavy hand on the management side, UM, which is

1543
01:21:33,520 --> 01:21:37,000
Speaker 1: it's intuitive UM. But literally no one had put data

1544
01:21:37,080 --> 01:21:39,759
Speaker 1: to that before, which is, you know, sometimes we find

1545
01:21:39,760 --> 01:21:42,320
Speaker 1: exactly what people think we're going to find. But now

1546
01:21:42,360 --> 01:21:46,240
Speaker 1: we have data, we know. It's a great it's a

1547
01:21:46,240 --> 01:21:48,400
Speaker 1: great point. I mean it's there's this anecdotal like, yeah,

1548
01:21:48,439 --> 01:21:50,599
Speaker 1: of course that's to say, but how do you know

1549
01:21:50,720 --> 01:21:53,680
Speaker 1: and how does that interact? How important is that relative

1550
01:21:53,720 --> 01:21:56,680
Speaker 1: to this public access question. Oh, it's not that m

1551
01:21:58,760 --> 01:22:01,080
Speaker 1: that's very get's interesting well, and we were also able

1552
01:22:01,120 --> 01:22:05,360
Speaker 1: to show kind of where on particular management actions where

1553
01:22:05,360 --> 01:22:07,599
Speaker 1: there was a lot more disagreement, and so we used

1554
01:22:07,600 --> 01:22:12,000
Speaker 1: a method that depicts that for our agency, and so UM,

1555
01:22:12,040 --> 01:22:14,799
Speaker 1: like I'm showing you this, there's a bunch of figures

1556
01:22:14,800 --> 01:22:16,599
Speaker 1: with bubbles on them, and some of the bubbles are big,

1557
01:22:16,600 --> 01:22:18,679
Speaker 1: and some of the bubbles are small, and the small

1558
01:22:18,680 --> 01:22:21,439
Speaker 1: bubbles suggests that there's a lot of agreement, whereas the

1559
01:22:21,439 --> 01:22:24,080
Speaker 1: big bubbles suggests that there's a lot of disagreement. And

1560
01:22:24,120 --> 01:22:27,519
Speaker 1: so UM at the time they were considering kill permits,

1561
01:22:27,560 --> 01:22:31,439
Speaker 1: and they were for UM later season kill permits, and

1562
01:22:31,439 --> 01:22:34,760
Speaker 1: there was a lot of disagreement around those kill permits,

1563
01:22:34,760 --> 01:22:38,639
Speaker 1: regardless of your hunter, landowner or general population. And so

1564
01:22:39,080 --> 01:22:40,799
Speaker 1: the other one that was kind of interesting was permanently

1565
01:22:40,800 --> 01:22:43,000
Speaker 1: fencing haystacks was also a place where we saw a

1566
01:22:43,000 --> 01:22:46,320
Speaker 1: lot of disagreement on how to manage ELK. So it's

1567
01:22:46,360 --> 01:22:49,919
Speaker 1: kind of an interesting depiction. It's called potential for conflict

1568
01:22:49,960 --> 01:22:52,439
Speaker 1: Index and it was developed out as some some researchers

1569
01:22:52,479 --> 01:22:57,400
Speaker 1: at Colorado State University and yeah, pc I and you

1570
01:22:57,439 --> 01:22:58,760
Speaker 1: can go I mean you can go to our you

1571
01:22:58,800 --> 01:23:01,240
Speaker 1: can guys can whoever's listening, look us up and on

1572
01:23:01,280 --> 01:23:04,320
Speaker 1: our web page we have the report. So if anyone's

1573
01:23:04,360 --> 01:23:07,000
Speaker 1: interested in kind of thinking about the other thing that's

1574
01:23:07,000 --> 01:23:10,200
Speaker 1: interesting there is that we like to talk about these groups,

1575
01:23:10,200 --> 01:23:12,760
Speaker 1: and we just did in terms of sampling, like landowners,

1576
01:23:12,760 --> 01:23:15,639
Speaker 1: they're all the same hunters, they all feel the same way, um.

1577
01:23:15,720 --> 01:23:20,000
Speaker 1: And that's this data really show where that is appropriate

1578
01:23:20,000 --> 01:23:23,160
Speaker 1: and where it's really not. Where you have, you know,

1579
01:23:23,800 --> 01:23:27,920
Speaker 1: varying views within the hunter population about the acceptability of

1580
01:23:27,920 --> 01:23:32,360
Speaker 1: different management techniques or even hunting itself. Um. And so

1581
01:23:32,640 --> 01:23:35,120
Speaker 1: figuring out when it's appropriate to kind of think about

1582
01:23:35,200 --> 01:23:37,840
Speaker 1: hunters as one group and when you really can't do that. Yeah,

1583
01:23:37,840 --> 01:23:40,080
Speaker 1: that's that's That's something I think about a lot and

1584
01:23:40,479 --> 01:23:42,599
Speaker 1: we've I've talked about in recent podcasts. Are we talked

1585
01:23:42,600 --> 01:23:44,760
Speaker 1: about our three a lot. I just sat down with

1586
01:23:44,800 --> 01:23:47,160
Speaker 1: a group called the Sports AND's Alliance and they they

1587
01:23:47,200 --> 01:23:52,400
Speaker 1: deal with specifically legislation against or fighting against animal rights activists,

1588
01:23:53,320 --> 01:23:55,720
Speaker 1: and they were, you know, and much of that conversation

1589
01:23:55,800 --> 01:23:58,320
Speaker 1: was around how do you feel like you have a

1590
01:23:58,400 --> 01:24:01,719
Speaker 1: united front on one side that opposes that his animal

1591
01:24:01,760 --> 01:24:04,600
Speaker 1: rights and opposes what we do in some level that

1592
01:24:04,800 --> 01:24:06,800
Speaker 1: you know, really kind of right now it's edges, but

1593
01:24:06,880 --> 01:24:10,880
Speaker 1: eventually that would be pushing inward. And then you have

1594
01:24:10,960 --> 01:24:14,439
Speaker 1: this hunting group that's hard to define, right. It's very regional,

1595
01:24:14,560 --> 01:24:17,280
Speaker 1: it's very pursuit base, it's very perspective base and value

1596
01:24:17,280 --> 01:24:20,000
Speaker 1: system based, and it's all just a mess. And so

1597
01:24:20,479 --> 01:24:23,160
Speaker 1: if you guys could please help, Well, it's interesting to

1598
01:24:23,280 --> 01:24:25,400
Speaker 1: find it a little bit better. Well, you know, I

1599
01:24:25,400 --> 01:24:28,200
Speaker 1: always groused me back to this critical piece of literature

1600
01:24:28,240 --> 01:24:31,920
Speaker 1: from the sixties. Um, this is an early recreation study.

1601
01:24:31,920 --> 01:24:34,839
Speaker 1: In the title was the average camper who doesn't exist,

1602
01:24:35,439 --> 01:24:38,360
Speaker 1: and so um, it's literally in one of my papers.

1603
01:24:38,760 --> 01:24:40,400
Speaker 1: As I was scanning, it was like, oh, I got

1604
01:24:40,400 --> 01:24:43,679
Speaker 1: that reference in there. Um. To suggest that all hunters

1605
01:24:43,680 --> 01:24:47,280
Speaker 1: are all women, are all landowners are the exact same

1606
01:24:47,760 --> 01:24:50,759
Speaker 1: is something we we all do this. We all say hunters,

1607
01:24:50,760 --> 01:24:53,919
Speaker 1: we all say landowners. Um, but they are very different

1608
01:24:54,040 --> 01:24:56,880
Speaker 1: and and like you said, it's different regionally. It's different

1609
01:24:56,920 --> 01:24:58,600
Speaker 1: if you're on this side of the Rocky Mountains or

1610
01:24:58,640 --> 01:25:01,360
Speaker 1: that side of the Rocky Mountains, if you're um living

1611
01:25:01,400 --> 01:25:04,439
Speaker 1: with grizzly bears or without grizzly bears. Um, there's just

1612
01:25:04,479 --> 01:25:08,919
Speaker 1: a lot of variation, and so you know, studying UM

1613
01:25:09,000 --> 01:25:11,680
Speaker 1: issues from a very micro level all the way up

1614
01:25:11,680 --> 01:25:13,639
Speaker 1: to a macro level is needed, and so you can't

1615
01:25:13,680 --> 01:25:16,599
Speaker 1: just do one study. There's often kind of a tiered

1616
01:25:16,640 --> 01:25:19,680
Speaker 1: process of trying to understand all the job security there

1617
01:25:19,760 --> 01:25:24,400
Speaker 1: right there, it's never ending future research, never ending story. Yeah, yeah,

1618
01:25:24,479 --> 01:25:26,880
Speaker 1: every paper has a future research. That's where we shove

1619
01:25:26,920 --> 01:25:29,400
Speaker 1: it all. Well, it's like I was just reading on

1620
01:25:29,400 --> 01:25:32,120
Speaker 1: your report here it says that the this pc I

1621
01:25:32,240 --> 01:25:34,960
Speaker 1: revealed that public access for hunting can reduce conflict among

1622
01:25:35,000 --> 01:25:40,880
Speaker 1: cattle producers. That's a sentence that I maybe before moving

1623
01:25:40,880 --> 01:25:43,240
Speaker 1: out west, definitely before talking to you guys, something that

1624
01:25:43,280 --> 01:25:45,360
Speaker 1: I would have I would have bet against rather than

1625
01:25:45,400 --> 01:25:48,160
Speaker 1: bet for UM. So again, I could probably keep coming

1626
01:25:48,160 --> 01:25:50,760
Speaker 1: back this in this conversation. I know this is a

1627
01:25:50,760 --> 01:25:54,479
Speaker 1: little bit different with brucellosis and less ELK is less disease,

1628
01:25:54,640 --> 01:25:57,360
Speaker 1: less disease transferred, things of that nature. But it but

1629
01:25:57,400 --> 01:25:59,600
Speaker 1: again it goes to the point of well, that's a

1630
01:25:59,680 --> 01:26:03,080
Speaker 1: fun stuff. Is like, sometimes we confirm what we already

1631
01:26:03,120 --> 01:26:07,160
Speaker 1: knew and now we have data, but sometimes we find surprises,

1632
01:26:07,520 --> 01:26:10,000
Speaker 1: and that's that's really the exciting stuff. When we go

1633
01:26:10,040 --> 01:26:12,960
Speaker 1: in with one one idea and the data just shows

1634
01:26:13,040 --> 01:26:15,880
Speaker 1: that we're just wrong. Uh, and then another idea. But

1635
01:26:16,360 --> 01:26:18,400
Speaker 1: when well, when you think about like these groups as

1636
01:26:18,400 --> 01:26:20,559
Speaker 1: we talk about, even if you think about outdoor recreation

1637
01:26:20,560 --> 01:26:22,040
Speaker 1: of those as a group, you can break that down

1638
01:26:22,040 --> 01:26:24,920
Speaker 1: at the skiers, climbers, hikers, all these other things. I've

1639
01:26:24,920 --> 01:26:27,080
Speaker 1: done that in the in the past for marketing purposes.

1640
01:26:27,120 --> 01:26:30,360
Speaker 1: But and then you think of hunters as as all

1641
01:26:31,000 --> 01:26:33,479
Speaker 1: this different group of upland hunters, Turkey hunters, you can

1642
01:26:33,520 --> 01:26:35,880
Speaker 1: break it up recently as well. Do you feel that

1643
01:26:35,920 --> 01:26:40,120
Speaker 1: the that the hunting subset is more complicated and it's

1644
01:26:40,160 --> 01:26:43,040
Speaker 1: like in its dissection than than maybe the outdoor wreck group.

1645
01:26:43,160 --> 01:26:46,000
Speaker 1: It's more variedance perspectives, Like, how would you line that up?

1646
01:26:46,120 --> 01:26:49,280
Speaker 1: Because it's it's yeah, that's a really I've actually never

1647
01:26:49,320 --> 01:26:52,559
Speaker 1: thought of it that way. I Mean, what's interesting about hunting,

1648
01:26:52,560 --> 01:26:54,479
Speaker 1: and I would probably lump fishing in this with this

1649
01:26:54,640 --> 01:26:57,760
Speaker 1: as well, is that there's such a variety of how

1650
01:26:57,880 --> 01:27:02,000
Speaker 1: you do it and when you do it. Um, you know, skiing,

1651
01:27:02,040 --> 01:27:06,400
Speaker 1: for example, it's very you know, there's one season, there's resorts,

1652
01:27:06,400 --> 01:27:08,439
Speaker 1: and there's that country and I know there's nuance between

1653
01:27:08,439 --> 01:27:10,360
Speaker 1: wis not you're not but you're not doing in the

1654
01:27:10,400 --> 01:27:15,080
Speaker 1: swamps of Louisiana and in the planes this is not

1655
01:27:15,280 --> 01:27:17,120
Speaker 1: you do it on the mountain and you go down.

1656
01:27:17,320 --> 01:27:23,680
Speaker 1: That's right, and so mountain you're welcome your pursuits and

1657
01:27:23,800 --> 01:27:29,599
Speaker 1: it's crap. And there's and so for hunting like there,

1658
01:27:29,840 --> 01:27:33,519
Speaker 1: I mean, there's the you know, how you harvest an animal,

1659
01:27:33,920 --> 01:27:37,960
Speaker 1: um which firearms use, whether you are into archery, whether

1660
01:27:38,040 --> 01:27:40,760
Speaker 1: you're into big game, small there's so many variations of

1661
01:27:40,760 --> 01:27:43,559
Speaker 1: how you hunt. And then you layer on top of

1662
01:27:43,600 --> 01:27:46,400
Speaker 1: that in recreation we have this theory called specialization and

1663
01:27:46,479 --> 01:27:48,719
Speaker 1: so how you progress through an activity and become highly

1664
01:27:48,720 --> 01:27:52,320
Speaker 1: specialized or not um And so when you start thinking

1665
01:27:52,360 --> 01:27:56,439
Speaker 1: about that, there are they. I feel like hunters and

1666
01:27:56,640 --> 01:28:00,240
Speaker 1: anglers are are very much there's there's a lot of them,

1667
01:28:00,280 --> 01:28:03,479
Speaker 1: and they're all doing it slightly different. And goes back

1668
01:28:03,479 --> 01:28:05,439
Speaker 1: to one of your kind of points on motivations and

1669
01:28:05,479 --> 01:28:07,840
Speaker 1: how do we how are we understanding those motivations from

1670
01:28:08,400 --> 01:28:12,440
Speaker 1: or experiences or recreation experience preferences. How are we understanding

1671
01:28:12,479 --> 01:28:16,000
Speaker 1: those for every activity and making sure we understand the

1672
01:28:16,040 --> 01:28:18,800
Speaker 1: full picture of what's going on in the landscape. Yeah, yeah,

1673
01:28:18,960 --> 01:28:21,320
Speaker 1: so I think the answer is yes, hunting is way complicated,

1674
01:28:21,600 --> 01:28:26,519
Speaker 1: super complicated, super complicated, more complicated. We've built typologies within

1675
01:28:27,080 --> 01:28:31,519
Speaker 1: you know, certain hunting or fishing activities, right, so you

1676
01:28:31,560 --> 01:28:35,599
Speaker 1: have it's not just that you are a saltwater angler.

1677
01:28:35,920 --> 01:28:38,519
Speaker 1: You there's like six different types of saltwater you know,

1678
01:28:38,600 --> 01:28:44,479
Speaker 1: like so um people are different. That's exactly right on

1679
01:28:44,600 --> 01:28:46,760
Speaker 1: your pigeonhole. Yeah, I've got I've got a typology for

1680
01:28:46,800 --> 01:28:48,400
Speaker 1: you there. And they're always range. When we do a

1681
01:28:48,400 --> 01:28:50,760
Speaker 1: typology study, there's like this we call them to all

1682
01:28:50,920 --> 01:28:52,920
Speaker 1: I come to all around enthusiasts. There's someone who's like

1683
01:28:53,360 --> 01:28:56,200
Speaker 1: jazzed about everything, and then there's like the dud group,

1684
01:28:56,240 --> 01:28:57,960
Speaker 1: like the group at the end who's like just kind

1685
01:28:57,960 --> 01:29:00,400
Speaker 1: of low on all motivations. Why are you doing? Like

1686
01:29:03,160 --> 01:29:07,240
Speaker 1: actually don't want that guy, the fact that you're doing anything,

1687
01:29:08,280 --> 01:29:10,400
Speaker 1: because it's a d percent harder to do something that

1688
01:29:10,520 --> 01:29:14,000
Speaker 1: it is to do nothing. That I've found. Um, we

1689
01:29:14,080 --> 01:29:16,200
Speaker 1: talked about about all the time in the hunting group

1690
01:29:16,439 --> 01:29:18,080
Speaker 1: about like just the way we we have a guy

1691
01:29:18,120 --> 01:29:20,080
Speaker 1: that works for our company. His name is Mark Kenyon,

1692
01:29:20,120 --> 01:29:22,120
Speaker 1: and he's a white tail guy and like all he

1693
01:29:22,200 --> 01:29:23,680
Speaker 1: kind of has just a one track mind when it

1694
01:29:23,680 --> 01:29:25,640
Speaker 1: comes to that, and aways making fun of him. I

1695
01:29:25,640 --> 01:29:27,280
Speaker 1: grew up as a white tail hunter. I love white

1696
01:29:27,280 --> 01:29:30,320
Speaker 1: sail hunting. It's a fantastic thing to do, set up

1697
01:29:30,320 --> 01:29:33,280
Speaker 1: in a tree and all. But I can't just do that,

1698
01:29:33,400 --> 01:29:36,360
Speaker 1: and I don't just think about that. But he does.

1699
01:29:36,880 --> 01:29:39,680
Speaker 1: And there's there's folks like that in upland and waterfowl,

1700
01:29:39,720 --> 01:29:42,320
Speaker 1: like they get this niche and even outside of like

1701
01:29:42,320 --> 01:29:44,120
Speaker 1: just the media landscape ward, and it's just kind of

1702
01:29:44,320 --> 01:29:46,679
Speaker 1: a valuable thing, just as just in your your own

1703
01:29:47,240 --> 01:29:50,240
Speaker 1: you know, your own place in the culture. There's a

1704
01:29:50,240 --> 01:29:52,439
Speaker 1: lot of people pick a lane and do you guys

1705
01:29:52,439 --> 01:29:54,400
Speaker 1: have any ideas about why that is or why like

1706
01:29:54,479 --> 01:29:57,720
Speaker 1: what motivates people to kind of stick into one. I

1707
01:29:57,760 --> 01:29:59,960
Speaker 1: think it's like it's boring. White tails get boring after

1708
01:30:00,000 --> 01:30:02,880
Speaker 1: a while, but not other people like wake up and

1709
01:30:02,880 --> 01:30:04,920
Speaker 1: that's all they think about. They name the dear. You're

1710
01:30:04,960 --> 01:30:09,719
Speaker 1: not very good at keeping your audience. I love you guys,

1711
01:30:09,840 --> 01:30:13,280
Speaker 1: come back. Well. It is interesting because obviously it's like

1712
01:30:13,320 --> 01:30:17,800
Speaker 1: generalist versus like highly specialized, right, and we know that,

1713
01:30:18,000 --> 01:30:21,240
Speaker 1: um so if we look at like, you know, we've

1714
01:30:21,280 --> 01:30:24,320
Speaker 1: heard of Maslow's hierarchy of needs and um, it's kind

1715
01:30:24,360 --> 01:30:26,120
Speaker 1: of a psychology theory where you have like you meet

1716
01:30:26,160 --> 01:30:28,000
Speaker 1: your basic needs and you can go up this pyramid

1717
01:30:28,080 --> 01:30:31,360
Speaker 1: and get to self actualization. We also call that kind

1718
01:30:31,360 --> 01:30:35,360
Speaker 1: of flow experiences. And this is um, there's a philosopher

1719
01:30:35,479 --> 01:30:38,000
Speaker 1: I'm going to screw up his name. It's like Shiksimahi

1720
01:30:39,280 --> 01:30:44,840
Speaker 1: and yeah it's really good, really professionality doctor um. But

1721
01:30:44,960 --> 01:30:48,360
Speaker 1: they talk about flow experiences and so, uh, if you

1722
01:30:48,400 --> 01:30:51,000
Speaker 1: can and flow is I mean you can think about

1723
01:30:51,000 --> 01:30:54,120
Speaker 1: your favorite hunting experience or your favorite outdoor recordation experience

1724
01:30:54,160 --> 01:30:58,000
Speaker 1: where like the world just kind of just disappeared around

1725
01:30:58,040 --> 01:31:00,559
Speaker 1: you and you were just highly focused on one thing.

1726
01:31:01,160 --> 01:31:04,000
Speaker 1: And so I think people who who might specialize are

1727
01:31:04,080 --> 01:31:08,479
Speaker 1: looking to achieve that flow experience and so um, if

1728
01:31:08,520 --> 01:31:10,800
Speaker 1: they can get there by doing the same activity and

1729
01:31:10,960 --> 01:31:14,000
Speaker 1: learning it so well, they can quickly get to that

1730
01:31:14,479 --> 01:31:16,800
Speaker 1: point in time where they feel like they are in

1731
01:31:16,880 --> 01:31:20,400
Speaker 1: this absolute state of self actualization. And I know that's

1732
01:31:20,439 --> 01:31:23,120
Speaker 1: a little like no, no, I mean, I've had folks

1733
01:31:23,120 --> 01:31:25,800
Speaker 1: on pockets that were in bear attacks. They're talking about

1734
01:31:25,800 --> 01:31:29,800
Speaker 1: flow states. It's a strange connection between those things. But

1735
01:31:30,720 --> 01:31:33,519
Speaker 1: that's interesting for me to think about because I was

1736
01:31:33,520 --> 01:31:34,840
Speaker 1: getting made fun of the other day. For me, I

1737
01:31:34,840 --> 01:31:36,439
Speaker 1: was like, I'm a generalist, man, I say, I like

1738
01:31:36,479 --> 01:31:38,519
Speaker 1: to do everything. I don't. I can't spend my time

1739
01:31:38,560 --> 01:31:41,439
Speaker 1: only doing a thing when there's so many other things

1740
01:31:41,640 --> 01:31:44,320
Speaker 1: to do. Um, people are making fun of that means

1741
01:31:44,320 --> 01:31:45,880
Speaker 1: you're good at nothing. I'm like, oh, that's probably true,

1742
01:31:45,880 --> 01:31:50,040
Speaker 1: but all trades master master of only. But it's interesting,

1743
01:31:50,600 --> 01:31:53,160
Speaker 1: interesting to hear how that that manifests self and hunting well.

1744
01:31:53,200 --> 01:31:56,320
Speaker 1: And I wonder if, like generalists maybe think about flow

1745
01:31:56,680 --> 01:31:59,280
Speaker 1: and the flow motivations are different. So maybe it's like

1746
01:31:59,320 --> 01:32:02,160
Speaker 1: the scenery or being like, you know, there's some other

1747
01:32:02,200 --> 01:32:04,080
Speaker 1: things that are getting you to that point and it's

1748
01:32:04,120 --> 01:32:06,960
Speaker 1: not just the activity itself. Yeah. Do you guys ever

1749
01:32:06,960 --> 01:32:10,320
Speaker 1: think about motivations like intrinsic versus extrinsic and how people

1750
01:32:10,320 --> 01:32:13,720
Speaker 1: are motivated to do things? Yeah? I think about it

1751
01:32:13,760 --> 01:32:15,519
Speaker 1: like all the time. You should come to my class,

1752
01:32:15,560 --> 01:32:19,080
Speaker 1: which is to cover the section on motivations. Yeah, that

1753
01:32:19,120 --> 01:32:23,680
Speaker 1: was a good guess. So how do you when you

1754
01:32:23,680 --> 01:32:25,680
Speaker 1: think about hunters and obviously when you study it from

1755
01:32:25,680 --> 01:32:28,160
Speaker 1: a social level and the interactions, you have to think

1756
01:32:28,160 --> 01:32:30,760
Speaker 1: about motivations. Um, So how do you think about in

1757
01:32:30,800 --> 01:32:35,120
Speaker 1: the modern social media age the extrinsic and intrinsic motivations

1758
01:32:35,120 --> 01:32:39,920
Speaker 1: of hunters. Yeah, um, that's a good question. We can

1759
01:32:39,960 --> 01:32:44,679
Speaker 1: think back to like motivation theory, so expectantcy balance theory,

1760
01:32:44,920 --> 01:32:49,599
Speaker 1: and so how people, um the outcome or the benefit

1761
01:32:49,640 --> 01:32:52,040
Speaker 1: you're hoping to achieve as being kind of one of

1762
01:32:52,040 --> 01:32:55,160
Speaker 1: these these driving forces. And so a lot of times

1763
01:32:55,160 --> 01:32:58,439
Speaker 1: in in our theories, we're thinking we're interested in that

1764
01:32:58,560 --> 01:33:00,559
Speaker 1: end goal, like what are you hoping what's the benefit

1765
01:33:00,560 --> 01:33:02,200
Speaker 1: you're hoping to achieve at the end of it, and

1766
01:33:02,240 --> 01:33:06,400
Speaker 1: that is closely lined up with your motivation. And there's

1767
01:33:06,400 --> 01:33:10,639
Speaker 1: just really cool paper um by some researchers I don't

1768
01:33:10,640 --> 01:33:13,720
Speaker 1: know in the nineties, um looking at they have a

1769
01:33:13,720 --> 01:33:16,439
Speaker 1: list of like three hundred and seventy five potential outdoor

1770
01:33:16,439 --> 01:33:20,000
Speaker 1: recreation motivations and there's like this massive list. It's like,

1771
01:33:20,320 --> 01:33:22,000
Speaker 1: it's an awesome paper because you can when you're doing

1772
01:33:22,000 --> 01:33:24,280
Speaker 1: survey research, you can just grab it and like avoiding

1773
01:33:24,320 --> 01:33:31,080
Speaker 1: your spouse. Yeah I'm hungry, but it's all yeah exactly. Um.

1774
01:33:31,400 --> 01:33:34,519
Speaker 1: And so when we start thinking about motivations and which

1775
01:33:34,600 --> 01:33:37,080
Speaker 1: ones of that list of three hundred seventy five or

1776
01:33:37,120 --> 01:33:40,759
Speaker 1: whatever it is. Thinking about which ones are tailored mostly

1777
01:33:40,800 --> 01:33:44,559
Speaker 1: to to hunting is important. And so we know that

1778
01:33:45,160 --> 01:33:49,000
Speaker 1: different groups are motivated for different reasons, and so we

1779
01:33:49,280 --> 01:33:53,360
Speaker 1: I looked at motivations by gender and so how why

1780
01:33:53,400 --> 01:33:55,840
Speaker 1: women and men are motivated differently? And there were some

1781
01:33:55,880 --> 01:33:58,880
Speaker 1: motivations that were the same, so being a nature, getting outdoors,

1782
01:33:59,000 --> 01:34:04,000
Speaker 1: things like that. There was some um coalescing around that. Um.

1783
01:34:04,040 --> 01:34:06,360
Speaker 1: I noticed that men tended to hunt more for so

1784
01:34:06,680 --> 01:34:11,040
Speaker 1: like hanging out with their friends rather than women, whereas

1785
01:34:11,040 --> 01:34:14,320
Speaker 1: women tended to hunt for more family related reasons. And

1786
01:34:14,400 --> 01:34:18,720
Speaker 1: so uh uh, which is just funny to me. Um,

1787
01:34:18,760 --> 01:34:20,519
Speaker 1: you know, men are going out to socialize and when

1788
01:34:20,520 --> 01:34:22,840
Speaker 1: we're going out to take care of their family. And

1789
01:34:24,680 --> 01:34:30,439
Speaker 1: I'm going to say something, but I'm I'm also I

1790
01:34:30,520 --> 01:34:34,200
Speaker 1: sent this one out. I had an awesome hunting season

1791
01:34:34,200 --> 01:34:37,040
Speaker 1: this year where I got a total of one day. Um.

1792
01:34:37,120 --> 01:34:39,160
Speaker 1: And this is because of my two very small children.

1793
01:34:39,240 --> 01:34:41,400
Speaker 1: And my husband was going out for like a weak

1794
01:34:41,479 --> 01:34:44,479
Speaker 1: hunting trip. Awesome wife go hunting for a week. Um.

1795
01:34:47,000 --> 01:34:48,479
Speaker 1: And I said to him, He's like, what do you

1796
01:34:48,520 --> 01:34:50,200
Speaker 1: want me to do? I said, get a damn dear,

1797
01:34:50,479 --> 01:34:51,960
Speaker 1: That's what I want you to do we need some

1798
01:34:52,000 --> 01:34:54,000
Speaker 1: meat in our freezer. I said, you know, he's like,

1799
01:34:54,040 --> 01:34:55,600
Speaker 1: should I get it? Wait for a big one? I said, no,

1800
01:34:55,920 --> 01:34:59,040
Speaker 1: you get a deer. And so this idea that some

1801
01:34:59,360 --> 01:35:02,080
Speaker 1: you know, there are are these differences between how men

1802
01:35:02,120 --> 01:35:05,160
Speaker 1: and women hunt and not true. Actually that is inaccurate.

1803
01:35:05,360 --> 01:35:08,760
Speaker 1: I said, do I shoot a dough on day one?

1804
01:35:08,760 --> 01:35:14,240
Speaker 1: And you said, hell no, I need three days, like

1805
01:35:14,479 --> 01:35:21,120
Speaker 1: day two afternoon. Okay, maybe now this is a good podcast.

1806
01:35:21,439 --> 01:35:24,880
Speaker 1: We need to break to swim right into that. It's

1807
01:35:24,880 --> 01:35:29,000
Speaker 1: not hard. That's interesting to think of for me because

1808
01:35:29,000 --> 01:35:32,120
Speaker 1: I was again talking to Hannah, one of your grad

1809
01:35:32,200 --> 01:35:35,519
Speaker 1: students here, and it just struck me that there's so

1810
01:35:35,600 --> 01:35:39,320
Speaker 1: much conversation around women and hunting. I remember when I

1811
01:35:39,400 --> 01:35:41,200
Speaker 1: read there was a study I want to say in

1812
01:35:42,680 --> 01:35:46,240
Speaker 1: responsive Managements are Better Virginia. I probably got the year wrong.

1813
01:35:46,560 --> 01:35:49,920
Speaker 1: Was that. But they started to identify groups, you know,

1814
01:35:50,040 --> 01:35:51,840
Speaker 1: as as honey was on the rise for the first

1815
01:35:51,840 --> 01:35:55,200
Speaker 1: time in many years since the eighties, identified groups that

1816
01:35:55,240 --> 01:35:57,600
Speaker 1: were getting back into it. And there they started with

1817
01:35:57,640 --> 01:36:01,360
Speaker 1: local boards returning military members, and then and then females,

1818
01:36:01,400 --> 01:36:05,640
Speaker 1: and I thought, oh, well, that's a as far as

1819
01:36:05,680 --> 01:36:09,240
Speaker 1: like population sets, it's like half of all of us,

1820
01:36:09,280 --> 01:36:11,400
Speaker 1: more than half, and then a few of us that

1821
01:36:11,560 --> 01:36:13,160
Speaker 1: like to eat, a few of us that were in

1822
01:36:13,200 --> 01:36:16,519
Speaker 1: the military, and then all half of us or is

1823
01:36:16,560 --> 01:36:21,240
Speaker 1: third doesn't make any sense? Well, it's fascinating. So when

1824
01:36:21,280 --> 01:36:24,040
Speaker 1: I was publishing my dissertation work, I had to so

1825
01:36:24,160 --> 01:36:26,120
Speaker 1: we go through like a peer review process, and you

1826
01:36:26,160 --> 01:36:28,479
Speaker 1: send it out and it's blind. You have no idea

1827
01:36:28,520 --> 01:36:30,880
Speaker 1: who's reviewing it, and they like because it's blind, they

1828
01:36:30,960 --> 01:36:33,600
Speaker 1: like shred you. And so it's, uh, it can be

1829
01:36:33,640 --> 01:36:35,680
Speaker 1: a really hard process. And I think I had a

1830
01:36:35,720 --> 01:36:38,559
Speaker 1: statement and and and ultimately my reviews were great, like

1831
01:36:38,960 --> 01:36:41,000
Speaker 1: they really helped push my paper into a better place.

1832
01:36:41,040 --> 01:36:45,400
Speaker 1: But one of the statements was I disagree completely that

1833
01:36:45,439 --> 01:36:48,760
Speaker 1: women are going to um make up for the lack

1834
01:36:48,800 --> 01:36:52,639
Speaker 1: of the decline and hunting population of males. And they

1835
01:36:52,720 --> 01:36:55,320
Speaker 1: just disputed the fact that women were going to engage

1836
01:36:55,320 --> 01:36:58,200
Speaker 1: in the sport as as much as I was making

1837
01:36:58,200 --> 01:37:01,920
Speaker 1: a case for it. And and you know, I've I

1838
01:37:01,920 --> 01:37:04,680
Speaker 1: guess I've that reviewed stuck with me because I keep

1839
01:37:04,720 --> 01:37:08,840
Speaker 1: thinking about it. Can women really make up um met

1840
01:37:08,960 --> 01:37:12,560
Speaker 1: a big piece of that that population decline? And I

1841
01:37:12,960 --> 01:37:17,880
Speaker 1: don't know, And but for me personally, we have to

1842
01:37:17,920 --> 01:37:21,519
Speaker 1: try because, like you said, it's fifty two percent of

1843
01:37:21,560 --> 01:37:25,200
Speaker 1: the population. Um. And so if we are not putting

1844
01:37:25,640 --> 01:37:29,400
Speaker 1: a big push on females and and and in particular

1845
01:37:29,439 --> 01:37:33,639
Speaker 1: maybe uh as women emerged out of college or into college,

1846
01:37:33,640 --> 01:37:36,920
Speaker 1: and then also family unit type hunting, I think we're

1847
01:37:36,960 --> 01:37:40,760
Speaker 1: missing something. I think we're missing a lot. I will

1848
01:37:40,880 --> 01:37:42,400
Speaker 1: I will get a little bit, give you a little

1849
01:37:42,400 --> 01:37:46,000
Speaker 1: bit into the old media kit for this podcast mail

1850
01:37:46,920 --> 01:37:51,400
Speaker 1: female and that's pretty typical reflects the we were just

1851
01:37:51,439 --> 01:37:54,519
Speaker 1: looking at the stats of hunting participation that's in ten

1852
01:37:55,040 --> 01:37:59,720
Speaker 1: really well, at least I'm representative, that's all tried. Yeah

1853
01:37:59,760 --> 01:38:04,400
Speaker 1: you want this is average right there? Um, it's always

1854
01:38:04,439 --> 01:38:06,519
Speaker 1: been interesting me and I've seen that pretty much everywhere

1855
01:38:06,520 --> 01:38:09,719
Speaker 1: I've gone. Um. And so when we say it's rising

1856
01:38:11,240 --> 01:38:15,639
Speaker 1: to what to what end? Right? Um? So getting into

1857
01:38:15,760 --> 01:38:18,360
Speaker 1: your the paper that I read and then some of

1858
01:38:18,400 --> 01:38:22,800
Speaker 1: your work on on this, how do we start this conversation,

1859
01:38:23,120 --> 01:38:26,799
Speaker 1: Like we know it's a growing set, but it's only

1860
01:38:26,840 --> 01:38:29,599
Speaker 1: growing to the point where I couldn't really shrink in

1861
01:38:29,640 --> 01:38:31,960
Speaker 1: my opinion, That's how I start thinking about it. This

1862
01:38:32,000 --> 01:38:35,080
Speaker 1: couldn't shrink anymore. It can't be four percent of the population.

1863
01:38:35,120 --> 01:38:36,880
Speaker 1: It just doesn't make any sense for the future. Funny

1864
01:38:36,920 --> 01:38:43,280
Speaker 1: could be Yeah, um, and so is that how you

1865
01:38:43,280 --> 01:38:45,680
Speaker 1: start thinking about this, Like it can't go down, it's

1866
01:38:45,680 --> 01:38:47,920
Speaker 1: got to go up, or what's the what's the way

1867
01:38:47,960 --> 01:38:52,920
Speaker 1: you approach? Yeah, yeah, it's interesting. Like so when I

1868
01:38:52,960 --> 01:38:56,200
Speaker 1: first got into like looking at women and hunting, I

1869
01:38:56,520 --> 01:39:01,040
Speaker 1: you quickly start looking at women and kind of how

1870
01:39:01,040 --> 01:39:05,800
Speaker 1: women experience recreation, leisure and the different constraints that they

1871
01:39:05,840 --> 01:39:10,360
Speaker 1: have that men just don't have. Um. And it's not

1872
01:39:10,560 --> 01:39:13,840
Speaker 1: it's not I'm not saying that because men don't have

1873
01:39:13,880 --> 01:39:16,680
Speaker 1: constraints hunting. They have they had their whole suite of

1874
01:39:16,680 --> 01:39:19,280
Speaker 1: different things that are preventing them, um from going out there.

1875
01:39:19,760 --> 01:39:22,320
Speaker 1: And you know, we look at like changing gender roles

1876
01:39:22,320 --> 01:39:25,320
Speaker 1: in society that's preventing for men from going at as offten.

1877
01:39:25,400 --> 01:39:27,280
Speaker 1: I mean, I have to have an equal number of

1878
01:39:27,360 --> 01:39:29,559
Speaker 1: days of recreation as my husband does. And that's because

1879
01:39:29,600 --> 01:39:37,960
Speaker 1: we have an equal I mean it's it's hard for me,

1880
01:39:38,160 --> 01:39:41,760
Speaker 1: Like it's hard for me even manage it sometimes. And

1881
01:39:41,920 --> 01:39:43,960
Speaker 1: so I like this idea that like we should be

1882
01:39:44,000 --> 01:39:47,640
Speaker 1: studying both experiences, Like it's not enough to just you know,

1883
01:39:47,800 --> 01:39:49,960
Speaker 1: just focus on women. But that's what I'm really interested in.

1884
01:39:50,040 --> 01:39:53,559
Speaker 1: So we'll focus on that um and thinking about you know,

1885
01:39:54,600 --> 01:39:59,679
Speaker 1: like life stages um. The fact that I hunted twice

1886
01:39:59,680 --> 01:40:02,920
Speaker 1: pregn in and twice while breastfeeding was a different set

1887
01:40:02,920 --> 01:40:04,800
Speaker 1: of constraints that you will ever have to deal with.

1888
01:40:04,840 --> 01:40:07,760
Speaker 1: I had not had that constraint. You didn't have to

1889
01:40:07,800 --> 01:40:10,519
Speaker 1: pump every hour and a half on a hunting trip,

1890
01:40:10,600 --> 01:40:13,800
Speaker 1: and so like that's can you adjust that time where

1891
01:40:13,920 --> 01:40:18,600
Speaker 1: like there's a buck pump in fifteen minutes? Can you

1892
01:40:18,640 --> 01:40:21,439
Speaker 1: do that? I can't do that. Like I was just

1893
01:40:21,479 --> 01:40:28,000
Speaker 1: third square and they'll go there. Took us about forty minutes.

1894
01:40:32,760 --> 01:40:35,040
Speaker 1: But it was hilarious. I mean I I hunted with

1895
01:40:35,120 --> 01:40:36,760
Speaker 1: my girlfriend at the time, who was also doing the

1896
01:40:36,800 --> 01:40:40,000
Speaker 1: same exact thing, and uh, we're like still questioning. I

1897
01:40:40,479 --> 01:40:43,919
Speaker 1: have refrained from asking any biologist if I detracted animals

1898
01:40:43,960 --> 01:40:47,840
Speaker 1: because I was like totally in this state. I have

1899
01:40:47,920 --> 01:40:51,920
Speaker 1: no idea. But there's just different challenges and so understanding

1900
01:40:51,920 --> 01:40:55,759
Speaker 1: like the women's experience and what they are competing against

1901
01:40:55,840 --> 01:40:59,880
Speaker 1: and just that's that's an important inquiry and that's an

1902
01:41:00,000 --> 01:41:02,479
Speaker 1: important piece of trying to get more women involved. In

1903
01:41:02,520 --> 01:41:05,120
Speaker 1: the activity, and it's it's like you said earlier, it's

1904
01:41:05,160 --> 01:41:07,439
Speaker 1: not like a one size fits all model, Like we

1905
01:41:07,520 --> 01:41:10,920
Speaker 1: have amazing Becoming Outdoors women programs and across the States,

1906
01:41:10,960 --> 01:41:13,720
Speaker 1: and that fits certain women and for other women it's not.

1907
01:41:13,800 --> 01:41:15,760
Speaker 1: It's going to be something completely different. Maybe it's the

1908
01:41:15,800 --> 01:41:18,439
Speaker 1: local bore and so that, Like you know, there's no

1909
01:41:18,520 --> 01:41:21,519
Speaker 1: silver bullet with women and hunting, but it's the kind

1910
01:41:21,560 --> 01:41:24,280
Speaker 1: of suite of options, in the suite of support networks

1911
01:41:24,280 --> 01:41:26,400
Speaker 1: and the suite of mentor programs that are really gonna,

1912
01:41:26,479 --> 01:41:29,880
Speaker 1: I think make a difference. And that's where uh, I

1913
01:41:29,920 --> 01:41:33,720
Speaker 1: think conservationists and hunting advocates or others can learn a

1914
01:41:33,760 --> 01:41:37,320
Speaker 1: lot from the marketing and business world right where you know,

1915
01:41:37,439 --> 01:41:39,719
Speaker 1: you don't sell a product by talking about it one way.

1916
01:41:40,439 --> 01:41:43,439
Speaker 1: You know, you figure out all the different market segments

1917
01:41:43,439 --> 01:41:45,240
Speaker 1: are that are out there, and you talk to them

1918
01:41:45,320 --> 01:41:48,200
Speaker 1: specifically about the thing that's in their way. But it's

1919
01:41:48,200 --> 01:41:50,200
Speaker 1: it's hard to talk about it. It's such a reductive

1920
01:41:50,200 --> 01:41:55,560
Speaker 1: fashion to like, hey, ladies, nobody's doing it, like hey,

1921
01:41:56,000 --> 01:41:57,960
Speaker 1: I mentually this is another podcast like that. Some of

1922
01:41:57,960 --> 01:42:01,760
Speaker 1: the problem issues with our three My My Lovely Boss

1923
01:42:01,760 --> 01:42:04,720
Speaker 1: Steve Ornella said, like, you can't tell someone this is

1924
01:42:04,760 --> 01:42:08,439
Speaker 1: a declining activity. Come on, jump on board. When he

1925
01:42:08,479 --> 01:42:10,840
Speaker 1: said that, I was like, dude, this is that's one

1926
01:42:10,880 --> 01:42:13,799
Speaker 1: of the more powerful things around this idea descriptive norms

1927
01:42:13,880 --> 01:42:17,320
Speaker 1: right there. Yeah, I would start using these terms like

1928
01:42:17,479 --> 01:42:20,840
Speaker 1: it sounds smarter, um, But yeah, and I think that's

1929
01:42:20,840 --> 01:42:22,240
Speaker 1: a that's a that's a big thing for us, Like

1930
01:42:22,240 --> 01:42:25,160
Speaker 1: how do we first describe the plight that we're in

1931
01:42:25,200 --> 01:42:29,360
Speaker 1: and recognize that there is an issue here. There's, like

1932
01:42:29,400 --> 01:42:32,360
Speaker 1: you said, there's obvious reasons why were we are where

1933
01:42:32,400 --> 01:42:35,519
Speaker 1: we are, Societal and cultural reasons to kind of have

1934
01:42:36,960 --> 01:42:39,640
Speaker 1: have driven us to where we are right now. We

1935
01:42:39,680 --> 01:42:42,200
Speaker 1: can all probably recognize him, But what do we do

1936
01:42:42,280 --> 01:42:47,240
Speaker 1: with him? There's the question. Yeah, I and I, um, yeah,

1937
01:42:47,240 --> 01:42:49,439
Speaker 1: I've been thinking a lot about this. I've been in

1938
01:42:49,520 --> 01:42:54,120
Speaker 1: these some currently in the throes of the working on

1939
01:42:54,160 --> 01:42:58,960
Speaker 1: the Montana State Comprehensive Outdoor Recreation Plan. I know scorp as.

1940
01:42:58,960 --> 01:43:03,799
Speaker 1: It's finally fondly reading SCORP. SCORP sounds like a small

1941
01:43:03,960 --> 01:43:09,800
Speaker 1: ugly dog, um, But we have so scorps are needed

1942
01:43:10,120 --> 01:43:13,200
Speaker 1: across the fifty states to get LBCF state side funds,

1943
01:43:13,320 --> 01:43:16,000
Speaker 1: and so it's an important document and their guiding documents

1944
01:43:16,040 --> 01:43:19,040
Speaker 1: across you know, they happen every five years Montana is

1945
01:43:19,040 --> 01:43:22,160
Speaker 1: doing there's I've I've worked with Montana the last go around,

1946
01:43:22,160 --> 01:43:23,559
Speaker 1: and so it's a kind of a privilege and an

1947
01:43:23,560 --> 01:43:25,960
Speaker 1: honor to be asked again to help with it. And

1948
01:43:26,000 --> 01:43:29,840
Speaker 1: so I've been interacting with them my little advisory group

1949
01:43:29,880 --> 01:43:33,160
Speaker 1: on that and thinking a lot about how, uh just

1950
01:43:33,240 --> 01:43:37,280
Speaker 1: how we talk about hunting in outdoor recreation and a

1951
01:43:37,280 --> 01:43:41,240
Speaker 1: lot of times it's, um, it's a small piece of

1952
01:43:41,280 --> 01:43:43,760
Speaker 1: these plans, and for me, I want to kind of

1953
01:43:43,800 --> 01:43:47,639
Speaker 1: elevate some of the R three efforts and make sure

1954
01:43:47,680 --> 01:43:52,040
Speaker 1: that's incorporated into our planning, our state planning efforts. UM. Likewise,

1955
01:43:52,080 --> 01:43:54,200
Speaker 1: I've you know, after you haven't talking to my buddy

1956
01:43:54,240 --> 01:43:59,280
Speaker 1: Greg Lemon and you know Greg right, and um, he

1957
01:43:59,320 --> 01:44:02,000
Speaker 1: told me to mention how what was it? Dapper handsome?

1958
01:44:02,040 --> 01:44:05,960
Speaker 1: He was on the podcast. I know he doesn't film them.

1959
01:44:08,880 --> 01:44:16,920
Speaker 1: She got laugh But Greg and I and and Insane

1960
01:44:16,960 --> 01:44:19,519
Speaker 1: with colleague care Josh mill Spot, who's who's been in

1961
01:44:19,560 --> 01:44:22,400
Speaker 1: Crockett chair here and UMS campus and the wildlif Biology program,

1962
01:44:22,600 --> 01:44:24,240
Speaker 1: we've been thinking about how do we we have all

1963
01:44:24,280 --> 01:44:27,200
Speaker 1: these kind of awesome groups popping up thinking about our

1964
01:44:27,280 --> 01:44:29,880
Speaker 1: three things that we have you know, field to fork,

1965
01:44:30,040 --> 01:44:31,920
Speaker 1: we have you know, farm to table. We have all

1966
01:44:31,960 --> 01:44:34,200
Speaker 1: these like you know, cool like local for or like

1967
01:44:34,240 --> 01:44:38,240
Speaker 1: all these cool programs in all of these nonprofits or

1968
01:44:38,439 --> 01:44:42,360
Speaker 1: conservation organizations, and and it seems like we're not even

1969
01:44:42,400 --> 01:44:46,040
Speaker 1: certain who's doing what, and we're not even certain if

1970
01:44:46,040 --> 01:44:48,920
Speaker 1: we're all pointed in the right direction, and so um

1971
01:44:48,960 --> 01:44:52,200
Speaker 1: there is. I think I'm hopeful that in at least

1972
01:44:52,240 --> 01:44:56,280
Speaker 1: in Montana will start thinking about them more comprehensively and holistically,

1973
01:44:56,400 --> 01:44:59,840
Speaker 1: because I think once we can kind of organize all

1974
01:44:59,880 --> 01:45:01,840
Speaker 1: the efforts, we can point us all in the right

1975
01:45:01,840 --> 01:45:04,120
Speaker 1: direction and make sure we know what what is it

1976
01:45:04,120 --> 01:45:07,000
Speaker 1: the left hands doing with the right hand at those

1977
01:45:07,840 --> 01:45:13,720
Speaker 1: hands are doing the same thing. I'm not good with

1978
01:45:19,280 --> 01:45:28,200
Speaker 1: the immediate do any of these things for sure? I

1979
01:45:28,200 --> 01:45:31,880
Speaker 1: I think about this exact thing a lot like is

1980
01:45:31,920 --> 01:45:35,639
Speaker 1: it a marketing issue? Is is it a public relations

1981
01:45:35,680 --> 01:45:38,320
Speaker 1: issue with hunting? In fact, when I started this podcast,

1982
01:45:38,320 --> 01:45:40,160
Speaker 1: that was one of the first things I said, I

1983
01:45:40,200 --> 01:45:42,360
Speaker 1: think there's a pr issue with what we got going on,

1984
01:45:42,560 --> 01:45:45,639
Speaker 1: Because when I sat in the room with your students here,

1985
01:45:45,680 --> 01:45:49,200
Speaker 1: these members of b h A you'd have no marketing

1986
01:45:49,200 --> 01:45:52,120
Speaker 1: problem or pr problem hunting if you just talk to them, right,

1987
01:45:52,400 --> 01:45:53,840
Speaker 1: if you just spoke with them and asked him like,

1988
01:45:53,840 --> 01:45:55,880
Speaker 1: it's hunting good for your life, good for what you do,

1989
01:45:56,240 --> 01:45:58,479
Speaker 1: you would know problem. People would be lining up to

1990
01:45:58,479 --> 01:46:00,519
Speaker 1: take part in the world that they've created for themselves

1991
01:46:00,560 --> 01:46:04,520
Speaker 1: here at this college and in in this town. Um,

1992
01:46:04,680 --> 01:46:07,960
Speaker 1: did you have Lincoln's paper there, because we have a

1993
01:46:08,000 --> 01:46:12,920
Speaker 1: colleague who who wrote a paper kind of on this

1994
01:46:13,240 --> 01:46:15,479
Speaker 1: kind of like we think of hunters as kind of

1995
01:46:15,479 --> 01:46:19,680
Speaker 1: like the rugged individual affords their own path, you know. Um,

1996
01:46:19,800 --> 01:46:24,160
Speaker 1: and sorry, it's not true. Like, Um, you were you know,

1997
01:46:24,479 --> 01:46:27,800
Speaker 1: raised in a family that's supported, and you learned from

1998
01:46:27,280 --> 01:46:31,599
Speaker 1: a mentor or you had resources to teach yourself and

1999
01:46:31,760 --> 01:46:34,679
Speaker 1: while other people didn't, and you live in a town

2000
01:46:34,760 --> 01:46:36,680
Speaker 1: or a place where there's access, and you live in

2001
01:46:36,680 --> 01:46:39,160
Speaker 1: a country that you know has embedded this into their

2002
01:46:39,200 --> 01:46:43,880
Speaker 1: wildlife management. Um. And so yeah, we can reduce it

2003
01:46:43,920 --> 01:46:47,040
Speaker 1: down to thinking about just participation by the individual, But

2004
01:46:47,120 --> 01:46:50,439
Speaker 1: there's this kind of whole, kind of nested rings of

2005
01:46:50,479 --> 01:46:54,120
Speaker 1: support throughout society that constitute what they called like the

2006
01:46:54,160 --> 01:46:57,120
Speaker 1: social habitat for hunting, And all of that has to

2007
01:46:57,160 --> 01:47:00,560
Speaker 1: be intact um for the hunter to even be in

2008
01:47:00,600 --> 01:47:03,839
Speaker 1: a position to say yes and to go do that sport.

2009
01:47:04,920 --> 01:47:07,200
Speaker 1: Is there a place that we as a community can

2010
01:47:07,240 --> 01:47:09,400
Speaker 1: step in and maybe haven't stepped in the like in

2011
01:47:09,479 --> 01:47:13,280
Speaker 1: that in those rings of of support where you know,

2012
01:47:13,360 --> 01:47:17,960
Speaker 1: maybe it's after folks leave the parental the parental nest

2013
01:47:18,000 --> 01:47:20,280
Speaker 1: and get out into this. It's like I think we

2014
01:47:20,400 --> 01:47:24,080
Speaker 1: lose most hunters are Recruitment dies off mostly in this

2015
01:47:24,160 --> 01:47:27,200
Speaker 1: environment in college because people are out from under the

2016
01:47:27,640 --> 01:47:30,920
Speaker 1: think the guys of their parents and that influence. They're

2017
01:47:30,920 --> 01:47:33,360
Speaker 1: seeing all the world around them. Everything is new and

2018
01:47:33,400 --> 01:47:35,160
Speaker 1: exciting and there's all these things you can do with

2019
01:47:35,160 --> 01:47:38,559
Speaker 1: their life. And hunting is takes a lot of money,

2020
01:47:39,080 --> 01:47:41,000
Speaker 1: as your students are telling me earlier, like it's five

2021
01:47:41,600 --> 01:47:44,439
Speaker 1: for an out of state license. That's ridiculous. They can't afford.

2022
01:47:44,479 --> 01:47:47,080
Speaker 1: That takes a lot of time and energy and equipment,

2023
01:47:47,600 --> 01:47:50,240
Speaker 1: and at that time in their life they have little time,

2024
01:47:51,000 --> 01:47:53,400
Speaker 1: little energy, and not a lot of funds to buy

2025
01:47:53,439 --> 01:47:56,040
Speaker 1: things and go and do things. So I think that

2026
01:47:56,439 --> 01:47:59,360
Speaker 1: goes to your point, But it's also an opportunity, Like

2027
01:47:59,520 --> 01:48:02,519
Speaker 1: I think there's they're they're they're um the folks who

2028
01:48:02,560 --> 01:48:05,439
Speaker 1: come out of families that are supporting hunting, and they

2029
01:48:05,439 --> 01:48:08,200
Speaker 1: may lose it in college and maybe they come back

2030
01:48:08,240 --> 01:48:10,599
Speaker 1: to it later in life. But there's also a group

2031
01:48:10,640 --> 01:48:12,640
Speaker 1: of people who didn't have it. And I was in

2032
01:48:12,680 --> 01:48:16,200
Speaker 1: that category, Like I wanted it, never had it growing up.

2033
01:48:16,720 --> 01:48:20,240
Speaker 1: And then as I was, you know, in college and

2034
01:48:20,240 --> 01:48:23,120
Speaker 1: exposed to other people, that gave me the opportunity to

2035
01:48:23,240 --> 01:48:25,519
Speaker 1: learn from other people and to get some of the

2036
01:48:25,600 --> 01:48:27,960
Speaker 1: things that I couldn't get as a kid. And so

2037
01:48:28,000 --> 01:48:31,000
Speaker 1: I think there's there's a lot of opportunity at this

2038
01:48:31,560 --> 01:48:34,800
Speaker 1: at this age, you know, to recruit people who didn't

2039
01:48:34,800 --> 01:48:37,960
Speaker 1: come out of hunting families into the sport. Well, it's

2040
01:48:38,040 --> 01:48:42,400
Speaker 1: it's interesting, I think, Um, it's it's been identified. So

2041
01:48:42,439 --> 01:48:45,919
Speaker 1: I'm part of this larger grant with thirteen other states

2042
01:48:46,200 --> 01:48:53,160
Speaker 1: and we are strategically implementing intro to hunting courses on campuses.

2043
01:48:53,479 --> 01:48:56,439
Speaker 1: And so we just did one two weekends ago, m

2044
01:48:56,520 --> 01:49:00,800
Speaker 1: up at the Boode and Crockett Ranch. Earlier silly I

2045
01:49:00,920 --> 01:49:09,240
Speaker 1: was home with the kids general general yourself into some

2046
01:49:09,320 --> 01:49:14,000
Speaker 1: cartoons and well it was hilarious that we took so

2047
01:49:14,200 --> 01:49:18,000
Speaker 1: Josh mill Spawn I took the students up and UM,

2048
01:49:18,040 --> 01:49:21,680
Speaker 1: the ranch manager, Luca Coli, and Josh and Uh. One

2049
01:49:21,680 --> 01:49:24,759
Speaker 1: of Josh's students, Dan did a lot of the session.

2050
01:49:24,840 --> 01:49:28,720
Speaker 1: I I was fine differing because I felt like I

2051
01:49:28,760 --> 01:49:31,639
Speaker 1: was completely like mom role. I was like love and belonging.

2052
01:49:31,680 --> 01:49:35,519
Speaker 1: I'm like, let's have some who wants more spaghetti? Everyone

2053
01:49:35,560 --> 01:49:39,280
Speaker 1: good enough to eat, please put granola bars in your pocket. Um.

2054
01:49:39,720 --> 01:49:43,400
Speaker 1: And but we had this awesome, this awesome trip and

2055
01:49:43,720 --> 01:49:46,639
Speaker 1: we like rolled out of UM and these like black

2056
01:49:46,720 --> 01:49:49,320
Speaker 1: suburbans and went up look like secret kids on the

2057
01:49:49,320 --> 01:49:53,599
Speaker 1: school bus, Like are you secret service? Were like, no, hunters,

2058
01:49:53,680 --> 01:49:57,840
Speaker 1: hunters can't tell you yea. So we rolled into the

2059
01:49:57,920 --> 01:50:01,320
Speaker 1: ranch and I mean we had a range of experienced

2060
01:50:01,360 --> 01:50:04,280
Speaker 1: levels and some folks had hunted before, and UM, a

2061
01:50:04,280 --> 01:50:07,720
Speaker 1: lot of folks had never even they didn't even know

2062
01:50:07,800 --> 01:50:10,040
Speaker 1: what to do. They never saw a gun, they've never

2063
01:50:10,479 --> 01:50:13,599
Speaker 1: thought about firearms, they've never thought about the regulations. And

2064
01:50:13,600 --> 01:50:16,640
Speaker 1: it just because it was free and because they just

2065
01:50:16,680 --> 01:50:19,360
Speaker 1: had to show up, it was really easy for them

2066
01:50:19,360 --> 01:50:21,519
Speaker 1: to do. And so this grant with their teen states

2067
01:50:21,720 --> 01:50:25,840
Speaker 1: um UH funded by off Well, was the ticket for that.

2068
01:50:25,880 --> 01:50:28,080
Speaker 1: And so we partnered with FWP. We made sure we

2069
01:50:28,080 --> 01:50:29,639
Speaker 1: had a game board, in there kind of going over

2070
01:50:30,000 --> 01:50:33,240
Speaker 1: the rags with the students. He unrolled the new kind

2071
01:50:33,240 --> 01:50:37,360
Speaker 1: of display of FLVPS regulations, which is an improvement. Um,

2072
01:50:37,880 --> 01:50:42,040
Speaker 1: and uh, the students got a chance. Josh and Luke

2073
01:50:42,080 --> 01:50:43,680
Speaker 1: took him out to the range and they had all

2074
01:50:43,720 --> 01:50:46,920
Speaker 1: these different guns to try and the students got to

2075
01:50:46,920 --> 01:50:49,439
Speaker 1: shoot clay pigeons. They just got to do some target practice.

2076
01:50:49,479 --> 01:50:52,040
Speaker 1: They got to just experience what it meant to be

2077
01:50:52,080 --> 01:50:54,840
Speaker 1: around firearms and had that safety around it. And then

2078
01:50:54,880 --> 01:50:58,120
Speaker 1: we did a bunch of you know, habitat and how

2079
01:50:58,120 --> 01:51:00,439
Speaker 1: do you look for deer and elk and things like that,

2080
01:51:00,520 --> 01:51:03,960
Speaker 1: went around the landscape and it was just really cool. Yeah,

2081
01:51:04,000 --> 01:51:06,120
Speaker 1: and hearing about it afterwards, I mean, I think you

2082
01:51:06,240 --> 01:51:10,600
Speaker 1: reflecting on that there's different needs among different students and

2083
01:51:10,640 --> 01:51:14,520
Speaker 1: so there might there's not just like the hunting recruitment program.

2084
01:51:14,560 --> 01:51:16,679
Speaker 1: It's you know, we have people who know what they're

2085
01:51:16,680 --> 01:51:19,200
Speaker 1: doing and they're interested in these programs, but they need

2086
01:51:19,200 --> 01:51:22,439
Speaker 1: a different type of mentorship than the folks who can't

2087
01:51:22,439 --> 01:51:26,080
Speaker 1: spell hunting and what are kind of interested And um,

2088
01:51:26,120 --> 01:51:28,240
Speaker 1: it was fascinating too. I mean b h A in

2089
01:51:28,280 --> 01:51:30,880
Speaker 1: the student club here has done a phenomenal job and

2090
01:51:30,960 --> 01:51:33,720
Speaker 1: they were the precursor for this course. They've been doing

2091
01:51:33,720 --> 01:51:36,479
Speaker 1: the Hunting for Sustainability program and so a lot of

2092
01:51:36,479 --> 01:51:39,400
Speaker 1: the students who were in bh A club came and

2093
01:51:39,439 --> 01:51:41,760
Speaker 1: helped with the weekend, and so we were able to

2094
01:51:41,800 --> 01:51:45,560
Speaker 1: kind of start that mentorship model. What's really cool is

2095
01:51:45,600 --> 01:51:49,519
Speaker 1: that Josh and Josh's leading and I'll assist a course

2096
01:51:49,680 --> 01:51:52,800
Speaker 1: in the fall where you get college credit to do

2097
01:51:53,040 --> 01:51:58,360
Speaker 1: Hunting for Sustainability and I know, game on Game changer um,

2098
01:51:58,400 --> 01:52:00,479
Speaker 1: and so it's a four hundred level course where you can,

2099
01:52:01,080 --> 01:52:04,960
Speaker 1: you know, it's kind of um ala carte style. You

2100
01:52:04,960 --> 01:52:07,600
Speaker 1: can take one credit and do the weekend, or you

2101
01:52:07,600 --> 01:52:09,559
Speaker 1: can do two credits and write a paper in addition,

2102
01:52:09,720 --> 01:52:12,240
Speaker 1: or do a third credit, and so we can have

2103
01:52:12,280 --> 01:52:16,120
Speaker 1: students kind of build their own program. Yeah, I mean

2104
01:52:16,200 --> 01:52:19,360
Speaker 1: it's agains. You keep coming back to that word complex.

2105
01:52:19,400 --> 01:52:21,240
Speaker 1: It's a very complex thing to do to try to

2106
01:52:21,680 --> 01:52:25,240
Speaker 1: first dissect and understand these different groups of people and

2107
01:52:25,280 --> 01:52:29,479
Speaker 1: then come to some conclusion about how to create more

2108
01:52:29,560 --> 01:52:34,760
Speaker 1: hunters out of this gumbo of ingredients you're not really

2109
01:52:34,800 --> 01:52:37,720
Speaker 1: sure of. Yum. It's cool to put some data to

2110
01:52:37,760 --> 01:52:39,760
Speaker 1: that too, Like we're talking about lots of ideas that

2111
01:52:39,840 --> 01:52:42,839
Speaker 1: might work, and we need people that are getting creative

2112
01:52:42,920 --> 01:52:46,519
Speaker 1: and producing things and leading programs, but we also need

2113
01:52:46,560 --> 01:52:50,920
Speaker 1: to kind of learn as to what's working right, um,

2114
01:52:51,000 --> 01:52:54,280
Speaker 1: and so building in some metrics of success to those

2115
01:52:54,320 --> 01:52:57,800
Speaker 1: programs and figuring out you know, which, which you know,

2116
01:52:57,880 --> 01:53:00,200
Speaker 1: approaches are working for which groups and how much, and

2117
01:53:00,240 --> 01:53:03,280
Speaker 1: which are worthy of investment and those sorts of things.

2118
01:53:03,320 --> 01:53:05,559
Speaker 1: That's where some of the data comes in. Do you

2119
01:53:05,560 --> 01:53:08,640
Speaker 1: guys have you know especially I think Women Hunters is

2120
01:53:09,400 --> 01:53:12,639
Speaker 1: probably the most interesting of all those to me personally. Um,

2121
01:53:12,760 --> 01:53:17,720
Speaker 1: do you have suggestions for folks? Do you have things that,

2122
01:53:18,280 --> 01:53:21,320
Speaker 1: based on your works are are something we could all

2123
01:53:21,320 --> 01:53:29,360
Speaker 1: try and do or or give us hope? Ladies, ladies, Um, yeah,

2124
01:53:29,400 --> 01:53:31,960
Speaker 1: it's I think you know again all not all women

2125
01:53:31,960 --> 01:53:34,559
Speaker 1: are the same. But there are things that I was

2126
01:53:35,439 --> 01:53:39,759
Speaker 1: Josh and I were really clued into over the weekends that, um,

2127
01:53:39,840 --> 01:53:42,519
Speaker 1: women do not just step up and say yeah, I

2128
01:53:42,560 --> 01:53:44,880
Speaker 1: want to shoot that up FIREM I want to I

2129
01:53:44,880 --> 01:53:47,400
Speaker 1: want to take more runs at the clay pigeons, you

2130
01:53:47,439 --> 01:53:52,439
Speaker 1: know machine and so um, just being aware of that

2131
01:53:53,600 --> 01:53:57,760
Speaker 1: women might not volunteer and they might they might need

2132
01:53:58,040 --> 01:54:00,479
Speaker 1: a little bit extra assistance to even just step up

2133
01:54:00,479 --> 01:54:02,479
Speaker 1: and do the do the task that we're we put

2134
01:54:02,680 --> 01:54:06,040
Speaker 1: put forward. I really advocate and this is just something

2135
01:54:06,200 --> 01:54:09,679
Speaker 1: over my years of working with high school through college,

2136
01:54:09,720 --> 01:54:14,960
Speaker 1: I advocate at least at this time, Uh, women focus programming,

2137
01:54:15,320 --> 01:54:18,640
Speaker 1: And I think having college courses is awesome, but I

2138
01:54:18,640 --> 01:54:20,920
Speaker 1: would love to see a specific section just for women

2139
01:54:21,400 --> 01:54:25,679
Speaker 1: and thinking about how that experience is just different than

2140
01:54:25,880 --> 01:54:28,360
Speaker 1: the experience of males. And it doesn't mean we always

2141
01:54:28,360 --> 01:54:30,720
Speaker 1: have to do it that way, it just is, you know,

2142
01:54:30,800 --> 01:54:33,600
Speaker 1: I think women focus programming is a thing. Yeah, yeah,

2143
01:54:33,680 --> 01:54:36,360
Speaker 1: I mean, and we struggle with are we pandering if

2144
01:54:36,360 --> 01:54:39,000
Speaker 1: we say like it's a women's hunt. Are we pandering

2145
01:54:39,080 --> 01:54:42,800
Speaker 1: like a do I say, please, everybody come over? It's

2146
01:54:42,800 --> 01:54:45,480
Speaker 1: all it's only women. It's it's very important. What would

2147
01:54:45,480 --> 01:54:48,640
Speaker 1: you treat everyone as equals and say like, hey, everybody,

2148
01:54:48,640 --> 01:54:51,680
Speaker 1: it's a hunt for everyone. But and I struggle with that.

2149
01:54:51,720 --> 01:54:54,400
Speaker 1: But after talking to you and talking, you know, talking

2150
01:54:54,400 --> 01:54:56,680
Speaker 1: to hand In some of your other female students earlier,

2151
01:54:57,080 --> 01:54:59,000
Speaker 1: they were I think because they're around you, guys more

2152
01:54:59,000 --> 01:55:01,000
Speaker 1: open to say like, here's of the things I that

2153
01:55:01,080 --> 01:55:04,520
Speaker 1: I experienced that you'll never like the perspective, You'll never have.

2154
01:55:05,160 --> 01:55:07,680
Speaker 1: I don't think that's very normal in the communication with folks.

2155
01:55:07,720 --> 01:55:10,160
Speaker 1: I think because they're exposed to you guys, and social

2156
01:55:10,640 --> 01:55:13,680
Speaker 1: sciences and the things that you've you've talked about here,

2157
01:55:13,680 --> 01:55:16,120
Speaker 1: they're more willing to say the things they've said to

2158
01:55:16,160 --> 01:55:18,200
Speaker 1: me that were you know, when I go to the

2159
01:55:18,200 --> 01:55:20,600
Speaker 1: sportsman's warehouse, this is what I experienced when I go

2160
01:55:20,640 --> 01:55:23,040
Speaker 1: out in the field, this is what I experienced when

2161
01:55:23,080 --> 01:55:25,280
Speaker 1: I talked to other hunters, this is what I experienced.

2162
01:55:25,960 --> 01:55:27,800
Speaker 1: And so it's cool that they were open enough say that,

2163
01:55:27,800 --> 01:55:30,920
Speaker 1: But I think most female hunters probably aren't. And it's

2164
01:55:30,920 --> 01:55:36,520
Speaker 1: amazing to me just um, yeah, like the women. I mean,

2165
01:55:36,680 --> 01:55:41,960
Speaker 1: you met Madeline Damon, who is here and ah she is,

2166
01:55:42,160 --> 01:55:45,440
Speaker 1: you know, itching for like a woman to go hunting with.

2167
01:55:45,680 --> 01:55:47,440
Speaker 1: She said that to me, Like I if I would

2168
01:55:47,440 --> 01:55:50,880
Speaker 1: just have it's different with a woman. What's the way

2169
01:55:50,920 --> 01:55:53,240
Speaker 1: she put It's like, it's just a different interaction. It's

2170
01:55:53,240 --> 01:55:57,040
Speaker 1: a different way to approach the outdoors. And I'm like, Okay,

2171
01:55:57,600 --> 01:56:01,240
Speaker 1: guys like to think that we're helpful and unhelpful ways,

2172
01:56:01,800 --> 01:56:06,160
Speaker 1: you know, um and over explaining and being overbearing and

2173
01:56:06,240 --> 01:56:12,840
Speaker 1: jumping too much sometimes damn well, we're our own worst.

2174
01:56:13,280 --> 01:56:15,920
Speaker 1: I mean, we've we've experienced that. I mean, I've rarely

2175
01:56:16,000 --> 01:56:21,800
Speaker 1: hunt with you now, thank god, thank god. I'm separation

2176
01:56:22,960 --> 01:56:25,320
Speaker 1: family reasons and friends, and I had to get away

2177
01:56:25,320 --> 01:56:31,280
Speaker 1: from my family the data support. But I mean, it's

2178
01:56:31,320 --> 01:56:34,280
Speaker 1: just a different experience. Like I you know, I told him,

2179
01:56:34,280 --> 01:56:36,000
Speaker 1: he asked me one day what my hunt. I was

2180
01:56:36,040 --> 01:56:37,800
Speaker 1: going away with a girlfriend on a hunting trip. He's like,

2181
01:56:37,800 --> 01:56:39,800
Speaker 1: what's your hunt? I don't even know what you do.

2182
01:56:40,160 --> 01:56:43,120
Speaker 1: He's like, saw me like packing like bottles of wine

2183
01:56:43,160 --> 01:56:45,680
Speaker 1: and goat cheese, and he's like, where are you going?

2184
01:56:46,120 --> 01:56:47,640
Speaker 1: And it's like, oh, we're going over to a cabin,

2185
01:56:47,720 --> 01:56:49,680
Speaker 1: I said. We get in the car and we literally

2186
01:56:49,720 --> 01:56:51,960
Speaker 1: do not stop talking even when we're hunting. We're still

2187
01:56:51,960 --> 01:56:57,400
Speaker 1: having a conversation somehow. And and so it's just a

2188
01:56:57,560 --> 01:57:01,280
Speaker 1: very different social experience when in some women. And I'm

2189
01:57:01,360 --> 01:57:05,240
Speaker 1: feeling the need on our campus right now to UM.

2190
01:57:05,320 --> 01:57:09,200
Speaker 1: I think we are UM is poised to encourage hunting.

2191
01:57:09,200 --> 01:57:13,760
Speaker 1: Our president Bodner is interested in this, are I see

2192
01:57:13,760 --> 01:57:16,560
Speaker 1: it up the ranks. Sardine, our director of Wildlife, like

2193
01:57:16,680 --> 01:57:20,200
Speaker 1: we we are interested in this and getting our students involved.

2194
01:57:20,200 --> 01:57:22,560
Speaker 1: And so I think my next step is working with

2195
01:57:22,640 --> 01:57:24,480
Speaker 1: Josh and figuring out how do we have a women's

2196
01:57:24,480 --> 01:57:28,440
Speaker 1: focused effort on our campus, at least at the college level. Yeah.

2197
01:57:28,480 --> 01:57:30,280
Speaker 1: I mean, if someone would ask me, what, you know,

2198
01:57:30,280 --> 01:57:33,600
Speaker 1: what's my opinion on recruitment, especially for female hunters or

2199
01:57:33,640 --> 01:57:35,120
Speaker 1: just around the bus. I just want more hunters. I

2200
01:57:35,120 --> 01:57:37,280
Speaker 1: don't care how we get it. And the folks like

2201
01:57:37,320 --> 01:57:39,600
Speaker 1: you that are actually thinking through the logistics of this

2202
01:57:39,720 --> 01:57:42,240
Speaker 1: and looking at the data, I'm trying to paint a

2203
01:57:42,960 --> 01:57:45,360
Speaker 1: more accurate picture of exactly how to take that action

2204
01:57:45,760 --> 01:57:48,160
Speaker 1: because I think why it's valuable, because I don't I mean,

2205
01:57:48,240 --> 01:57:50,080
Speaker 1: if we have to have all women classes to get

2206
01:57:50,120 --> 01:57:52,720
Speaker 1: I don't care. I have no I have. I would

2207
01:57:52,720 --> 01:57:54,720
Speaker 1: put no constraints on how we get new hunters in

2208
01:57:54,760 --> 01:57:58,320
Speaker 1: as long as we're speaking and you know, ethical terms

2209
01:57:58,400 --> 01:58:01,720
Speaker 1: and sustainable terms when we do, which we are UM

2210
01:58:01,760 --> 01:58:03,800
Speaker 1: and so I think most hunters would say the same thing,

2211
01:58:03,800 --> 01:58:05,720
Speaker 1: and that would be my gas. It's like, I just

2212
01:58:05,760 --> 01:58:08,080
Speaker 1: want more people to enjoy the thing that I enjoy

2213
01:58:08,200 --> 01:58:12,000
Speaker 1: in responsible and informed way. Do I care how we

2214
01:58:12,040 --> 01:58:15,880
Speaker 1: do it as long as it's within those constitucts. I don't.

2215
01:58:16,360 --> 01:58:20,640
Speaker 1: I don't UM And so you know, bring on the solutions.

2216
01:58:20,960 --> 01:58:23,440
Speaker 1: I think we'll we'll, we'll put them out there. Yeah,

2217
01:58:23,480 --> 01:58:26,440
Speaker 1: I think hunters need to think beyond hunters to write,

2218
01:58:26,440 --> 01:58:30,839
Speaker 1: like thinking about the broader social habitat for hunting um

2219
01:58:31,800 --> 01:58:36,000
Speaker 1: and and the fact that hunting exists not because of hunters,

2220
01:58:36,680 --> 01:58:41,520
Speaker 1: but because all the other people here in the country

2221
01:58:41,560 --> 01:58:44,760
Speaker 1: support hunting. Right that the majority of people in this country,

2222
01:58:44,760 --> 01:58:49,200
Speaker 1: whether they hunt or not, support hunting UM. And you know,

2223
01:58:49,240 --> 01:58:52,720
Speaker 1: doing what we can to represent the sport well, you know,

2224
01:58:52,840 --> 01:58:56,360
Speaker 1: build connections and good communication about what we're up to

2225
01:58:56,800 --> 01:59:00,680
Speaker 1: um with the broader public. UM. So even if you know,

2226
01:59:01,400 --> 01:59:03,560
Speaker 1: as a hunter, I don't want popular I don't want

2227
01:59:03,640 --> 01:59:06,640
Speaker 1: hunting to get so popular, like I think a little

2228
01:59:06,640 --> 01:59:12,040
Speaker 1: bit more fun. But you know, like, well there's a

2229
01:59:12,040 --> 01:59:16,080
Speaker 1: difference with men and women. UM. I was teasing. I

2230
01:59:16,080 --> 01:59:18,080
Speaker 1: had these students come up to me. You know, I

2231
01:59:18,080 --> 01:59:20,720
Speaker 1: talked about hunting my classes all the time, and these

2232
01:59:20,760 --> 01:59:23,040
Speaker 1: like three guys come up to me and they're like, Livy,

2233
01:59:23,080 --> 01:59:25,200
Speaker 1: we're trying to hunt in this one area and we

2234
01:59:25,240 --> 01:59:28,080
Speaker 1: don't know where to go. And I said, yeah, I

2235
01:59:28,120 --> 01:59:31,160
Speaker 1: was like, here, here's how I would tackle this particular

2236
01:59:31,240 --> 01:59:34,280
Speaker 1: block of land. And actually, if you're looking for something

2237
01:59:34,320 --> 01:59:36,000
Speaker 1: close to town. I would also go to this one

2238
01:59:36,080 --> 01:59:38,320
Speaker 1: particular spot that I just discovered. But you're gonna have

2239
01:59:38,320 --> 01:59:40,400
Speaker 1: to hike. You're gonna to do this. And I told

2240
01:59:40,400 --> 01:59:42,600
Speaker 1: Alex this, and he's like, why would you say that?

2241
01:59:43,440 --> 01:59:46,400
Speaker 1: And I said, because I'm interested in getting people outdoors

2242
01:59:46,400 --> 01:59:50,760
Speaker 1: and I'm interested in getting I find the spot. Finally

2243
01:59:50,800 --> 01:59:53,040
Speaker 1: find a good spot, closes down and she goes, I'm

2244
01:59:53,040 --> 01:59:57,280
Speaker 1: gonna learn about it. This is a perfect segue to

2245
01:59:57,400 --> 01:59:59,880
Speaker 1: a thing that I do on this show. I got

2246
02:00:00,000 --> 02:00:01,560
Speaker 1: a lot of heat for it out in the internet.

2247
02:00:02,000 --> 02:00:04,400
Speaker 1: I'm gonna keep doing it. It's perfect. That means you're

2248
02:00:04,400 --> 02:00:06,520
Speaker 1: doing something right. I know a lot of heat people

2249
02:00:06,520 --> 02:00:09,800
Speaker 1: are upset. It's called now here's another part of this conversation.

2250
02:00:09,840 --> 02:00:12,120
Speaker 1: It used to be called before I met you guys,

2251
02:00:12,360 --> 02:00:14,360
Speaker 1: used to be called hot spot cool dude. But now

2252
02:00:15,920 --> 02:00:20,720
Speaker 1: problem hot spot cool person. I think we can work

2253
02:00:20,760 --> 02:00:26,000
Speaker 1: on that cool individual is where this is. This actually

2254
02:00:26,040 --> 02:00:29,200
Speaker 1: is presented by First Light. They make lovely hunting clothing

2255
02:00:29,360 --> 02:00:33,560
Speaker 1: we wear outside. Um, so thank you first Light. I'm

2256
02:00:33,560 --> 02:00:35,760
Speaker 1: going to try to convince you guys to give me

2257
02:00:35,800 --> 02:00:38,880
Speaker 1: a hunting spot, and you have to be very specific

2258
02:00:39,200 --> 02:00:41,200
Speaker 1: can be like these mountain range or something like that.

2259
02:00:41,480 --> 02:00:43,800
Speaker 1: You have to give me a very specific hunting spot

2260
02:00:44,560 --> 02:00:46,480
Speaker 1: for all the listeners this podcast that they would go

2261
02:00:46,520 --> 02:00:50,240
Speaker 1: to and what they would find there. And no, there's

2262
02:00:50,240 --> 02:00:53,280
Speaker 1: only been two guys that actually give me anything. Yeah,

2263
02:00:53,320 --> 02:00:57,240
Speaker 1: I refuse, immediate refused me. Just oh my god, this

2264
02:00:57,320 --> 02:00:59,640
Speaker 1: is the problem. Do you want to know what there are? Three?

2265
02:00:59,640 --> 02:01:01,440
Speaker 1: Issue is that no one's given up their hunting. So

2266
02:01:01,440 --> 02:01:05,560
Speaker 1: that's what I'm saying. That's the bell of disagreement. Yep. Uh,

2267
02:01:05,640 --> 02:01:07,840
Speaker 1: it's the last hurdle that you have to cut. You know,

2268
02:01:07,920 --> 02:01:11,400
Speaker 1: have to clear yourself your own spots exactly right, recruit

2269
02:01:11,400 --> 02:01:15,000
Speaker 1: your own spots. Well, yeah, if you guys want to

2270
02:01:15,000 --> 02:01:18,320
Speaker 1: give somebody, I got a dove spot, and I got

2271
02:01:18,360 --> 02:01:20,680
Speaker 1: like a kind of an elk spot. That's far. That's

2272
02:01:20,680 --> 02:01:22,560
Speaker 1: what you got. That's all I got. And most people

2273
02:01:22,560 --> 02:01:24,240
Speaker 1: don't want to give spots. I don't understand it. What's

2274
02:01:24,240 --> 02:01:26,640
Speaker 1: your end? How many of you asked? It's like eight

2275
02:01:27,400 --> 02:01:29,680
Speaker 1: two out of it's not good. Yeah, not a good data,

2276
02:01:29,760 --> 02:01:32,720
Speaker 1: but than zero. Yeah, So if you guys want to

2277
02:01:32,760 --> 02:01:35,480
Speaker 1: just it could be longitude loaded too, that's fine. It

2278
02:01:35,480 --> 02:01:39,040
Speaker 1: could be the exact like Trailhead give some spots up

2279
02:01:39,040 --> 02:01:48,280
Speaker 1: back in Pennsylvania. I'm not saying I mean the place.

2280
02:01:48,360 --> 02:01:51,160
Speaker 1: I'm really I don't. I get I have no qualms

2281
02:01:51,160 --> 02:01:52,560
Speaker 1: and I go to a place that actually a lot

2282
02:01:52,560 --> 02:01:55,320
Speaker 1: of people use, and so I have no issues giving

2283
02:01:55,360 --> 02:01:58,800
Speaker 1: it up. Um. It's so we we like to go

2284
02:01:58,880 --> 02:02:02,120
Speaker 1: up by Phillipsburg and um, that's kind of a fun

2285
02:02:02,240 --> 02:02:07,000
Speaker 1: space for us as a family, and so we've actually been. Um,

2286
02:02:07,040 --> 02:02:09,600
Speaker 1: you know, there's the East Fork Reservoir up there, and

2287
02:02:09,600 --> 02:02:11,560
Speaker 1: then there's the next road which is kind of where

2288
02:02:11,560 --> 02:02:13,480
Speaker 1: you go to Moose Lake. And as you're going up

2289
02:02:13,480 --> 02:02:16,400
Speaker 1: to Moose Lake, remember that Moose Lake. Everybody Moose Lake

2290
02:02:16,480 --> 02:02:18,800
Speaker 1: on the left in the woods is I think it's

2291
02:02:20,840 --> 02:02:28,120
Speaker 1: like angry calls on surveys grant to after you were

2292
02:02:28,160 --> 02:02:32,720
Speaker 1: tearing down stereotypes. That's right. This is for our three folks. Um,

2293
02:02:34,160 --> 02:02:37,240
Speaker 1: it's called Carpet Lake. And you just get high enough

2294
02:02:37,280 --> 02:02:39,720
Speaker 1: and there's I've seen multiple elk in there. I've never

2295
02:02:39,720 --> 02:02:43,320
Speaker 1: actually taken a shot in there. Um, but it's it's

2296
02:02:43,360 --> 02:02:45,320
Speaker 1: the thing I like about it is it's easy terrain

2297
02:02:45,960 --> 02:02:47,920
Speaker 1: and so you're not having to kind of scale a

2298
02:02:47,960 --> 02:02:50,280
Speaker 1: big hill, although you do have to work a little bit,

2299
02:02:50,360 --> 02:02:54,520
Speaker 1: especially in deep snow. Um and it's just there's some

2300
02:02:54,640 --> 02:02:57,600
Speaker 1: nice kind of paths. There's some nice just it's just

2301
02:02:57,640 --> 02:02:59,760
Speaker 1: a nice area on it. It's wooded, it's has some

2302
02:02:59,840 --> 02:03:04,440
Speaker 1: la makes, it's pretty. It's teeming with elk teeming depending

2303
02:03:04,480 --> 02:03:08,200
Speaker 1: on how people and now people in tends of people.

2304
02:03:08,600 --> 02:03:10,760
Speaker 1: We should study this though, we should say this would

2305
02:03:10,760 --> 02:03:13,160
Speaker 1: be a good Yeah, like is this really a thing?

2306
02:03:13,600 --> 02:03:15,720
Speaker 1: If you talk about your spot to people go there.

2307
02:03:15,800 --> 02:03:17,720
Speaker 1: That's why I did. I'm doing this because they're like

2308
02:03:17,800 --> 02:03:20,120
Speaker 1: want to you need some people. Yeah, I do need data,

2309
02:03:20,160 --> 02:03:23,720
Speaker 1: but I also like mess with folks, So that two things.

2310
02:03:23,720 --> 02:03:26,280
Speaker 1: I like data and mess with folks. You should say

2311
02:03:26,360 --> 02:03:28,960
Speaker 1: the next person you interview, and if they say they're

2312
02:03:29,000 --> 02:03:31,080
Speaker 1: not giving up their spot, you should. You should have

2313
02:03:31,160 --> 02:03:33,560
Speaker 1: them come give them my number, your number. Maybe you

2314
02:03:33,600 --> 02:03:35,880
Speaker 1: could just always call into this segment from now on,

2315
02:03:36,240 --> 02:03:44,680
Speaker 1: just like, yeah, look at the data. Te win assholes.

2316
02:03:45,000 --> 02:03:48,360
Speaker 1: All right, we're gonna the final segment here. It's called

2317
02:03:48,440 --> 02:03:50,480
Speaker 1: first time. Is this a little bit? Let We'll get

2318
02:03:50,520 --> 02:03:53,080
Speaker 1: you out in the easy spot. This is presented by

2319
02:03:53,080 --> 02:03:55,840
Speaker 1: Federal Premium Ammunition. And I've been shooting turkeys in the

2320
02:03:55,880 --> 02:03:59,400
Speaker 1: face with their new TSS load here recently. It's very

2321
02:03:59,480 --> 02:04:03,600
Speaker 1: nice works. Well that's one of the multiple shot size. Yeah,

2322
02:04:03,960 --> 02:04:06,480
Speaker 1: third degree ye shot size. I mean just pole ax

2323
02:04:06,520 --> 02:04:08,560
Speaker 1: and Turkey's like it's ridiculous, it's just knocking her with

2324
02:04:08,600 --> 02:04:11,960
Speaker 1: their feet. Um. But this segment, so thank you Federal Premium.

2325
02:04:12,000 --> 02:04:14,720
Speaker 1: This segment is UH where you're gonna tell me your

2326
02:04:14,800 --> 02:04:17,080
Speaker 1: first like we're gonna goll go with I'll let you

2327
02:04:17,120 --> 02:04:20,640
Speaker 1: pick the first hunting related first. I'd like to go

2328
02:04:20,720 --> 02:04:23,360
Speaker 1: with first rifle because I feel like that's always a

2329
02:04:23,400 --> 02:04:27,880
Speaker 1: big deal. And then maybe first animal you killed, that's

2330
02:04:27,920 --> 02:04:29,760
Speaker 1: also big deal. I'll let I'll let you if you

2331
02:04:29,760 --> 02:04:31,200
Speaker 1: have a more interesting one, you can pick of it.

2332
02:04:31,280 --> 02:04:37,120
Speaker 1: Let's try those two, Alex, give me your first rifle. Well,

2333
02:04:37,200 --> 02:04:43,360
Speaker 1: my first rifle was um uh dough white tail in

2334
02:04:43,400 --> 02:04:49,360
Speaker 1: Pennsylvania UM on opening day, which is um which is

2335
02:04:49,400 --> 02:04:52,400
Speaker 1: an experience dude, I from Western Maryland. I mean they're

2336
02:04:52,480 --> 02:04:55,320
Speaker 1: all about it, but like one point two million hunters

2337
02:04:55,400 --> 02:04:57,960
Speaker 1: or something number might be wrong with Orange Army. It

2338
02:04:58,080 --> 02:05:02,560
Speaker 1: is the pumpkin patch. Um. Yeah. And I had just

2339
02:05:02,800 --> 02:05:07,120
Speaker 1: switched over from UH I wear glasses and I was

2340
02:05:07,160 --> 02:05:09,280
Speaker 1: sick of wearing glasses in the field and I just

2341
02:05:09,360 --> 02:05:14,200
Speaker 1: got contacts like the week before. Brilliant planning. Yeah and

2342
02:05:14,360 --> 02:05:18,880
Speaker 1: uh and so yeah. I was up in in north

2343
02:05:18,920 --> 02:05:21,560
Speaker 1: central Pennsylvania and I was kind of posted outside this

2344
02:05:21,560 --> 02:05:24,920
Speaker 1: this big thicket and I got in there, you know,

2345
02:05:25,000 --> 02:05:28,440
Speaker 1: way before, way before light, and I could there's tons

2346
02:05:28,440 --> 02:05:31,280
Speaker 1: of deer all around. I'm just waiting for the first light.

2347
02:05:31,920 --> 02:05:35,760
Speaker 1: Um and yeah. As it started getting lighter, I'm like

2348
02:05:35,800 --> 02:05:38,680
Speaker 1: squinting through my scope and my contact is my contacts

2349
02:05:38,720 --> 02:05:41,000
Speaker 1: are just like itch in my eyes, and my eyes

2350
02:05:41,040 --> 02:05:44,000
Speaker 1: are watering and streaming. I can't see anything. I finally

2351
02:05:44,000 --> 02:05:45,880
Speaker 1: just take the contacts out and throw them on the ground.

2352
02:05:46,440 --> 02:05:48,880
Speaker 1: Um and raid, it's kind of shooting. Light came up.

2353
02:05:48,920 --> 02:05:51,000
Speaker 1: There was this nice big dough headed into the thicket

2354
02:05:51,200 --> 02:05:57,040
Speaker 1: and pulled the trigger. Um and uh yeah, um, how

2355
02:05:57,320 --> 02:06:00,000
Speaker 1: were you? I was actually in grad school. I didn't

2356
02:06:00,120 --> 02:06:04,160
Speaker 1: really big game until grad school, so I was it

2357
02:06:04,280 --> 02:06:09,800
Speaker 1: was probably two three. I don't know that solo solo mission. Um.

2358
02:06:09,840 --> 02:06:11,520
Speaker 1: I was with a group of guys at a camp

2359
02:06:11,800 --> 02:06:13,520
Speaker 1: up there, but we had kind of split up and

2360
02:06:13,560 --> 02:06:16,200
Speaker 1: had our own spots that we'd scoped out. Oh yeah,

2361
02:06:16,200 --> 02:06:19,760
Speaker 1: I'm I'm very familiar I grew up in western Maryland. Basically,

2362
02:06:19,800 --> 02:06:23,120
Speaker 1: I mean we could walk to the Pennsylvania border and um,

2363
02:06:23,160 --> 02:06:25,800
Speaker 1: I can think twice where bullets wiz by my head

2364
02:06:25,800 --> 02:06:30,360
Speaker 1: on opening day. Yeah, it was a close proximity twenty

2365
02:06:30,360 --> 02:06:33,240
Speaker 1: minutes before shooting light, the shooting begins, and yeah it

2366
02:06:33,280 --> 02:06:36,400
Speaker 1: doesn't stop, don't. Yeah. A couple of times I killed

2367
02:06:36,560 --> 02:06:39,240
Speaker 1: small bucks and already had a few holes in them. Yeah,

2368
02:06:39,800 --> 02:06:42,600
Speaker 1: through a few things slowed them down for you at bit.

2369
02:06:43,400 --> 02:06:45,360
Speaker 1: It's the thing, all right, we'll libby you have like

2370
02:06:45,400 --> 02:06:48,400
Speaker 1: a first I think it would be breaking the Ginger

2371
02:06:48,400 --> 02:06:50,360
Speaker 1: sterotype if you just told us about your first rifle

2372
02:06:50,440 --> 02:06:54,480
Speaker 1: that you were given or purchased or owned. I purchased.

2373
02:06:54,480 --> 02:06:59,760
Speaker 1: I feel like it's very un well, yeah, it's very unceremonial,

2374
02:07:00,120 --> 02:07:05,600
Speaker 1: like an away. I literally I started hunting birds with

2375
02:07:05,920 --> 02:07:08,960
Speaker 1: when I met Alex in Pennsylvania, when we first started dating,

2376
02:07:09,080 --> 02:07:12,200
Speaker 1: and I was like getting it dunting then. And he

2377
02:07:12,280 --> 02:07:15,960
Speaker 1: had two really cute dogs that became my dogs. That's

2378
02:07:15,960 --> 02:07:22,320
Speaker 1: actually my inn sampling of dogs per dogs dogs classic play.

2379
02:07:22,840 --> 02:07:24,800
Speaker 1: I know, I'm a runner, so they were like a

2380
02:07:24,880 --> 02:07:28,000
Speaker 1: perfect match, um to go out and just run with.

2381
02:07:28,320 --> 02:07:32,040
Speaker 1: And um, so when I moved to Montana. I was like, well, jeez,

2382
02:07:32,080 --> 02:07:35,800
Speaker 1: I better getting a big game hunting. And we literally

2383
02:07:35,880 --> 02:07:38,320
Speaker 1: were just driving I think we were driving through Idaho.

2384
02:07:38,360 --> 02:07:41,320
Speaker 1: We're going to Spokane or um, and I just said,

2385
02:07:41,360 --> 02:07:46,040
Speaker 1: let's pull over to Cabella's doing it. I'm doing it

2386
02:07:46,640 --> 02:07:49,720
Speaker 1: like I did. I literally was like, no time, like

2387
02:07:49,800 --> 02:07:52,960
Speaker 1: the president, Let's just grab a rifle and and so

2388
02:07:53,040 --> 02:07:56,320
Speaker 1: I bought my savage and um, I've only I've only

2389
02:07:56,360 --> 02:08:00,240
Speaker 1: shot one animal with it. And when I time, and

2390
02:08:00,280 --> 02:08:03,120
Speaker 1: I shot my first deer on some private land and

2391
02:08:03,160 --> 02:08:06,360
Speaker 1: I was with another woman and we both shot Mulie's

2392
02:08:06,400 --> 02:08:10,160
Speaker 1: that day. And we we had help. We well we

2393
02:08:10,200 --> 02:08:12,560
Speaker 1: could have had help, but we were like, no, we're

2394
02:08:12,600 --> 02:08:15,160
Speaker 1: gonna we're gonna get these guys. And we're doing it

2395
02:08:15,160 --> 02:08:18,360
Speaker 1: all in the field. And we just started going to

2396
02:08:18,400 --> 02:08:26,240
Speaker 1: town and the hand waving's that is not the correct

2397
02:08:26,280 --> 02:08:35,760
Speaker 1: emotion to be begging. But the private lander was like,

2398
02:08:35,920 --> 02:08:37,880
Speaker 1: he's like, oh, I have like all these men that

2399
02:08:37,920 --> 02:08:39,440
Speaker 1: come out and they never do this. We just pick

2400
02:08:39,520 --> 02:08:42,120
Speaker 1: it up and leave. We said, we just wanted to practice,

2401
02:08:42,280 --> 02:08:46,840
Speaker 1: you know, doing it ourselves. Yeah, that's awesome. Well, thank

2402
02:08:46,880 --> 02:08:49,560
Speaker 1: you guys for for joining me and I appreciate your

2403
02:08:50,760 --> 02:08:53,640
Speaker 1: your work here, and I would tell you if if

2404
02:08:53,680 --> 02:08:56,320
Speaker 1: it is any evidence of what your work. It turns

2405
02:08:56,320 --> 02:08:58,000
Speaker 1: out the folks that sat in this room with me

2406
02:08:58,040 --> 02:09:03,120
Speaker 1: that your students were unbelieved. Will um. These these are

2407
02:09:03,400 --> 02:09:07,440
Speaker 1: exceptional humans. The fact that they hunt, it's maybe tangential

2408
02:09:07,480 --> 02:09:10,040
Speaker 1: to like the fact that they seem to be uh,

2409
02:09:10,640 --> 02:09:13,680
Speaker 1: their heads are firmly fixed on their shoulders. Yeah, they are.

2410
02:09:13,720 --> 02:09:17,560
Speaker 1: We have outstanding students and all of our programs around

2411
02:09:17,560 --> 02:09:21,400
Speaker 1: the College of Forestry, they're they're remarkable human beings. Yeah. Yeah,

2412
02:09:21,600 --> 02:09:24,400
Speaker 1: that's why we do what we do. Yeah, if it's

2413
02:09:24,440 --> 02:09:27,360
Speaker 1: any evidence to the future of conservation and forestry and

2414
02:09:27,360 --> 02:09:30,080
Speaker 1: wildlife management, we're will be in good hands at least

2415
02:09:30,200 --> 02:09:39,000
Speaker 1: around here. So thanks guys. That's it. That is all.

2416
02:09:39,600 --> 02:09:44,200
Speaker 1: Thanks for joining us this week, every one. Thanks to

2417
02:09:44,240 --> 02:09:47,400
Speaker 1: Alex and Libby and Sam, Thanks to the Black Hills,

2418
02:09:47,440 --> 02:09:50,080
Speaker 1: thanks to the University of Montana. I love this new

2419
02:09:50,160 --> 02:09:53,280
Speaker 1: format because it blends like the current, which is where

2420
02:09:53,280 --> 02:09:57,320
Speaker 1: I'm sitting right now in the Black Hills, with the evergreen,

2421
02:09:57,840 --> 02:10:00,720
Speaker 1: which is the interview with al X and Luby. It's

2422
02:10:00,720 --> 02:10:02,680
Speaker 1: this It's a cool way to combine where I am

2423
02:10:02,680 --> 02:10:06,640
Speaker 1: and where I've been and when mixed together UM topics

2424
02:10:06,640 --> 02:10:09,040
Speaker 1: and sometimes don't touch on each other, but almost always

2425
02:10:09,360 --> 02:10:14,080
Speaker 1: have some relationship. So I'm very UM happy with my

2426
02:10:14,080 --> 02:10:18,120
Speaker 1: myself personally the new format. But maybe you're not happy

2427
02:10:18,160 --> 02:10:21,080
Speaker 1: with it, maybe you think it's terrible. Please write in

2428
02:10:21,240 --> 02:10:23,640
Speaker 1: and tell me th h C at the meat Eator

2429
02:10:23,680 --> 02:10:26,200
Speaker 1: dot com. Th h C at the meat Eator dot

2430
02:10:26,240 --> 02:10:28,800
Speaker 1: com and that stands for the Hunting Collective. If you're wondering,

2431
02:10:29,080 --> 02:10:31,280
Speaker 1: right into that email address, tell me what you think

2432
02:10:31,320 --> 02:10:34,200
Speaker 1: about the new format. Ask questions which we will answer

2433
02:10:34,240 --> 02:10:39,040
Speaker 1: on this program, and also record yourself asking a question

2434
02:10:39,120 --> 02:10:42,440
Speaker 1: from making a comment about what you've heard on the podcast.

2435
02:10:43,040 --> 02:10:44,920
Speaker 1: Email it to me. Just do it right on your phone,

2436
02:10:45,000 --> 02:10:47,080
Speaker 1: Just go to notes talking to the phone and then

2437
02:10:47,160 --> 02:10:49,760
Speaker 1: hit send to the email at th HC at the

2438
02:10:49,800 --> 02:10:53,920
Speaker 1: metator dot com. You do that, I will listen to

2439
02:10:53,960 --> 02:10:56,440
Speaker 1: it and if it's good enough, if it's under two minutes,

2440
02:10:56,600 --> 02:11:01,200
Speaker 1: it's real clean, we'll put it on the air. So

2441
02:11:01,240 --> 02:11:03,600
Speaker 1: hopefully we can you know, in the months and weeks

2442
02:11:03,600 --> 02:11:05,720
Speaker 1: to come here start putting much of those together in

2443
02:11:05,840 --> 02:11:09,040
Speaker 1: packaging them for you UM as a part another part

2444
02:11:09,200 --> 02:11:12,840
Speaker 1: of the new format of the podcast, So please right

2445
02:11:12,920 --> 02:11:18,360
Speaker 1: in th HC at the meat eater dot com. And

2446
02:11:18,440 --> 02:11:20,960
Speaker 1: what else would I say? I'll say that there's a

2447
02:11:21,080 --> 02:11:23,440
Speaker 1: video out there, hopefully we'll go watch. You go to

2448
02:11:23,440 --> 02:11:26,200
Speaker 1: the meat Eator YouTube channel. You also can get there

2449
02:11:26,240 --> 02:11:31,280
Speaker 1: through the meat Eator's social of Steve and ronnella turkey

2450
02:11:31,360 --> 02:11:34,600
Speaker 1: hunting um and he's hunting with me and it's it's

2451
02:11:35,080 --> 02:11:36,960
Speaker 1: it's one of my favorite turkey videos. I think it's

2452
02:11:36,960 --> 02:11:38,480
Speaker 1: got a lot of a lot of for those of

2453
02:11:38,480 --> 02:11:40,040
Speaker 1: you that aren't turkey veteran, it's got a lot of

2454
02:11:40,160 --> 02:11:43,240
Speaker 1: educational stuff in it. You'll learn how hunter talks to

2455
02:11:43,280 --> 02:11:45,480
Speaker 1: a turkey and how a turkey talks to a hunter.

2456
02:11:45,760 --> 02:11:48,920
Speaker 1: It's a huge um, a huge production for us. We

2457
02:11:49,000 --> 02:11:50,840
Speaker 1: worked a long time on it, so it's important that

2458
02:11:50,880 --> 02:11:53,120
Speaker 1: you go watch it. So go to the YouTube channel

2459
02:11:53,160 --> 02:11:57,480
Speaker 1: for meat Eater and look for Steve and my latest

2460
02:11:57,600 --> 02:12:00,720
Speaker 1: turkey hunt. You're gonna love it, promise, or if you

2461
02:12:00,720 --> 02:12:03,280
Speaker 1: don't love it, okay, right into th HC at the

2462
02:12:03,280 --> 02:12:07,600
Speaker 1: mediator dot com. I'm happy to read your opinions either way.

2463
02:12:07,920 --> 02:12:11,840
Speaker 1: So without with all that done and with this episode done,

2464
02:12:12,120 --> 02:12:14,280
Speaker 1: I'm off to hunt more turkeys and we'll see you

2465
02:12:14,360 --> 02:12:18,440
Speaker 1: next time on the Hunting Collectives enjoy once again old

2466
02:12:18,520 --> 02:12:23,640
Speaker 1: number seven, Oh number seven, Tennessee whiskey got me drinking

2467
02:12:23,880 --> 02:12:27,320
Speaker 1: heaven and h and he stopped. It looks good to me.

2468
02:12:27,640 --> 02:12:33,720
Speaker 1: They're gonna have to department to the far rede to

2469
02:12:34,000 --> 02:12:44,520
Speaker 1: the far red, drinking in dre heaven