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Speaker 1: This is the meater podcast coming at you shirtless, severely,

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

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Speaker 2: Listening past, you can't predict.

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

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

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

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

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

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Speaker 1: T E dot com. All right, real quick, right up

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Speaker 1: right up top for anything that happens. You know, it's

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Speaker 1: hunting season. When Phil starts prepping for a theater production.

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Speaker 3: That's how I mark the seasons too.

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Speaker 1: Yeah, yeah, Phil, Phil stepped away from theater. I never

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Speaker 1: really stepped away. It's just tough.

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Speaker 3: It's tough on the family for me to do shows

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Speaker 3: because I missed bedtime for months, and it's just a

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Speaker 3: lot of commuting.

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Speaker 4: You know, I live out of town.

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Speaker 1: So and that one year he was kissing the other

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Speaker 1: lady besides his wife, a whole bunch. I was in

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Speaker 1: the play. He had to kiss a lady.

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Speaker 3: It was scandalous to know one besides Steve.

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Speaker 1: But yeah, rehearse that for all fall.

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Speaker 2: Well I did.

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Speaker 5: I did one, as long as you keep it to

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Speaker 5: the regularly scheduled rehearsal.

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Speaker 3: That's correct. I did a play in January, Steve, you

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Speaker 3: just weren't there.

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Speaker 4: You didn't see it. I think the only person at

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Speaker 4: the company saw it was Randall.

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Speaker 1: So you're prepping up now to do I'm.

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Speaker 3: Doing Christmas Carol again straight? Yeah, I think we're doing

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Speaker 3: it straight. We're no no steampunk icing on it, which

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Speaker 3: I think you were referring to.

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Speaker 1: That's why I wanted to talk touch on this very quickly. Okay,

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Speaker 1: there's one modification. Yeah, when they're always talking about buying

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Speaker 1: that goose.

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Speaker 5: You know, sure, yeah, the big Christmas goose.

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Speaker 1: Farthing a shilling for a farthing, like is that an

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Speaker 1: expensive goose or not? You know what I mean?

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Speaker 3: I think it's just supposed to be an expensive get.

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Speaker 1: If they would, if you would just try this this year, okay,

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Speaker 1: switch it to US currency and just for inflation.

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Speaker 3: Okay, So I'm the kids like three dollars for a goose,

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Speaker 3: or maybe they.

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Speaker 1: Would probably be like, oh, ship, that's a very expensive goose.

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Speaker 3: Sure, or they they could say, you know, a shilling

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Speaker 3: and a farthing and then just turn to the audience

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Speaker 3: break character and just kind of whisper.

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Speaker 1: It's like three hundred dollars today.

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Speaker 5: Isn't that nuts?

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Speaker 4: Can you? Okay?

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Speaker 5: Back to the program? Is it?

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Speaker 1: I would to enjoy that place so much more? Talk

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Speaker 1: about that?

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Speaker 5: Yeah, currency conversion live? Does he? Is it an actual liner?

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Speaker 5: Is it from Scrooge where he says the biggest goose

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Speaker 5: in all of London? Because then when that imply it's

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Speaker 5: going to be expensive?

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Speaker 3: Yeah, yeah, when he's I had a change of heart.

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Speaker 3: I think you know, bud go buy the biggest goose.

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Speaker 3: You can find something like that.

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Speaker 4: That's a great accent.

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Speaker 1: Oh I could do that whole damn play?

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Speaker 4: Yeah, I might.

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Speaker 2: You should.

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Speaker 5: Christmas Tours coming up?

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Speaker 1: All right, The Wild Turkey Doc is back. Now we're

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Speaker 1: actually starting the show. The Wild Turkey Doc is back.

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Speaker 1: Mike Chamberlain, very popular guest on the show. It came

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Speaker 1: in and then tells you everything you ever want to

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Speaker 1: know about turkeys. Today, we're not talking about turkeys though,

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Speaker 1: except we're gonna talk about turkeys a little bit, of course.

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Speaker 1: We're here to talk about chronic waste and disease and

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Speaker 1: interesting some interesting findings about that, which is gonna stir

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Speaker 1: the old pot, the hoax. The c w d's a hoax.

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Speaker 1: C w d's a scam pot. You know the pot.

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Speaker 1: Oh yeah, a lot of guys stirring that pie there.

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Speaker 1: It is a big pot with lots of spoons. Uh, Mike.

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Speaker 1: Doctor Chamberlain is from the Warnell School of Forestry and

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Speaker 1: Natural Resources at the University of Georgia. He's the National

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Speaker 1: Wild Turkey Federation Distinguished Professor sir A or the the

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Speaker 1: the the is only one.

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Speaker 4: Only one. This is the first endowed position that's Turkey centric.

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Speaker 1: I might like to have that role.

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Speaker 4: Come on. I'm a few years from retirement.

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Speaker 1: And he leads the Wild Turkey Lab.

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Speaker 4: Uh.

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Speaker 1: Mark Ruter? Am I saying that right?

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Speaker 2: Correct?

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Speaker 1: Okay? Mark Ruter's here a colleague of doctor Chamberlain's. He's

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Speaker 1: from the College of Veterinary Medicine at the University of Georgia.

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Speaker 1: You got some accolades here that I don't understand. Southeastern

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Speaker 1: Cooperative Wildlife Disease Study. What's that mean?

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Speaker 2: So it's squiddest for short. You'll hear most in the

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Speaker 2: wildlife community call it squidis, even though it has nothing

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Speaker 2: to do with squids. So we're a cooperative. So Squidist

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Speaker 2: was founded in nineteen fifty seven by state wildlife agencies

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Speaker 2: in the southeastern United States, and it was really founded

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Speaker 2: at a time where we had no no capacity, no

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Speaker 2: expertise within state wildlife management agencies for disease and health topics.

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Speaker 2: And it was actually founded in the face of one

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Speaker 2: of the better known diseases of white tail deer, and

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Speaker 2: that's hemorrhagic disease HD and blue tongue. And so we

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Speaker 2: were founded at this time to sort of provide expertise,

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Speaker 2: diagnostic capacity, and understanding of diseases in white tail deer

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Speaker 2: at a time where restoration efforts were still kind of ongoing.

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Speaker 2: Because the fear was that this disease was going to

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Speaker 2: complicate the recovery of white tail deer, and so states

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Speaker 2: couldn't individually stand up capacity to have a person or

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Speaker 2: facility for just focused on disease. So they went the

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Speaker 2: cooperative model. And so that was a long time ago

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Speaker 2: and we're still still here. We have today we have

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Speaker 2: seventeen state wildlife agencies one territory in the Southeast, and

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Speaker 2: then have federal partners US fishali Life Service and US

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Speaker 2: Geological sort of provides our core sort of funding, and

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Speaker 2: we serve the States and.

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Speaker 1: You're the director, correct. Do you carry one of these

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Speaker 1: in your wallet? Someone gave me this.

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Speaker 5: Not that your insurance card.

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Speaker 1: It's this little card that if you start dying or something,

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Speaker 1: it tells people what you did at the hospital. Someone

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Speaker 1: gave that to me at Coronell. It tells people at

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Speaker 1: the hospital, Hey, man.

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Speaker 2: I do some weird stuff.

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Speaker 1: Yeah, I should give that card to you. I don't

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Speaker 1: have one of these cards, but I feel obligated to

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Speaker 1: give you that card because it apply more to your

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Speaker 1: line of work than my line of work.

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Speaker 5: Oh yeah, does somebody ever go have you ever come

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Speaker 5: in contact with.

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Speaker 1: Have you been in contact with any animals that seems sick?

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Speaker 2: And that's my job.

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Speaker 1: And then doctor Callahan's here.

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Speaker 5: Oh he's not a doctor, got an honorary doctor, straight.

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Speaker 1: Up, old cal doc Doc Doc Callahan's grandkid Callahan.

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Speaker 4: I like that.

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Speaker 1: Yeah, we're gonna talk about some interesting findings around chronic

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Speaker 1: wasting disease, and don't be worried. We will start out

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Speaker 1: by talking about what in the hell is chronic wasting

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Speaker 1: disease and why is it controversial? Not yet, because first

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Speaker 1: let everybody know, we got we got a new show

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Speaker 1: coming out called Meat Eater Sheds. It's drops Thursday, September

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Speaker 1: twenty five. We got episodes. We don't go into people's homes.

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Speaker 1: We go into their sheds, barns, whatever. We profile their properties.

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Speaker 1: We got one with Jeff Foxworthy's game room, Kevin Murphy's

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Speaker 1: exceptionally chaotic shed, Heather Duville's fur processing facilities, and more.

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Speaker 1: One episode every Thursday, kicking off on September twenty five.

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Speaker 1: All right, I've been thinking out for a couple of

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Speaker 1: minutes at a time. For days, I've been thinking about

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Speaker 1: how to start this conversation. I think I want to

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Speaker 1: start like this, one of you guys, and you can

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Speaker 1: pick you can you can thumb wrestler, So who gets

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Speaker 1: to do it? One of you guys has to very quickly,

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Speaker 1: just to get people up to speed, very quickly, explain

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Speaker 1: what is chronic wasting disease. Okay, the super quick explanation

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Speaker 1: of what is chronic wasting disease. Then I'm gonna explain

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Speaker 1: I'm gonna Devil's advocate a little bit. And now I'm

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Speaker 1: going to explain what guys on the street in the bars,

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Speaker 1: not so much on the street. Well, guys, in the

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Speaker 1: field and in the bars, say about it, okay, in

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Speaker 1: a way that will capture my own concerns and then

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Speaker 1: capture the other people's concerns, and then we'll dig in.

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Speaker 1: Is that fair?

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Speaker 4: Yeah?

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Speaker 1: Yeah, because I want to do a little bit about

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Speaker 1: like what are we talking about? And then and then

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Speaker 1: kind of why someone should be paying attention to this.

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Speaker 4: Yeah, all right, Yeah. So chronic wasting disease is, if you,

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Speaker 4: if you kind of think about it, thirty thousand foot

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Speaker 4: so proteins or if you go back to grade school,

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Speaker 4: proteins are comprised of amino acids, right, They're the building clocks,

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Speaker 4: I believe you. Okay, So these amino acids that build

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Speaker 4: these proteins are supposed to fold naturally, and though they

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Speaker 4: fold to support basic cell functions in the body. So

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Speaker 4: what happens with CWD is you have this particular type

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Speaker 4: of protein called a preon protein, and it misfolds. And

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Speaker 4: we don't know why that misfolding occurs, but when it misfolds,

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Speaker 4: the body can't shed the protein through enzymatic breakdowns like

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Speaker 4: it would normally shed proteins, and so the proteins accumulate

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Speaker 4: and they tend to accumulate in the brain, and what

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Speaker 4: that accumulation causes is neurological. If you look at the

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Speaker 4: brain through microscopically, it essentially looks like it has holes

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Speaker 4: in it.

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Speaker 1: Why does something accumulating create.

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Speaker 4: Holes because the body cannot shed the protein, and so

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Speaker 4: this is this is the dumb.

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Speaker 1: But I feel like that would make a ball, not

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Speaker 1: a hole. If it was shedding too many, it make

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Speaker 1: a hole. I mean, this is not coming from a

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Speaker 1: professional person.

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Speaker 4: Yeah, Mark, what happened like a tumor build up.

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Speaker 2: Once you have this, you know, the normal protein in

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Speaker 2: the body, which we all have right now, it goes

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Speaker 2: through a sort of a recycle process, right it's all

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Speaker 2: a lot of proteins in our body are built and

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Speaker 2: then after it's sort of lifespan, enzymes in the body

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Speaker 2: will kind of surgically kind of break it apart and

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Speaker 2: recycle those components and you start over with other proteins.

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Speaker 2: Once this prenom protein takes this different shape, then the

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Speaker 2: enzymes that the body has to snippet apart don't recognize

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Speaker 2: it anymore. They can't get to those sites. And so

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Speaker 2: rather than naturally degrade and recycle this protein over time,

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Speaker 2: it just persists, and then it's sticky and more sort

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Speaker 2: of kind of can can glob onto it, and so

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Speaker 2: you end up accumulating these proteins that your body can't

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Speaker 2: break down anymore, where the deer's body can't break down anymore.

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Speaker 2: And so it's that accumulation of material in a very

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Speaker 2: sensitive space neurons around neurons in the brain, that's your

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Speaker 2: information super highway controls everything in your body. And you

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Speaker 2: start to put stuff in there that's not supposed to

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Speaker 2: be in there, it's going to be less efficient.

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Speaker 1: Okay, have you ever tried to when you say a hole,

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Speaker 1: do you mean a whole?

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Speaker 2: So how that starts. What they're talking about is when

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Speaker 2: you're looking at a tissue microscopically. So if we were

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Speaker 2: to take a deer's brain out and cut it into

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Speaker 2: super thin chips, you know, we put that on a

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Speaker 2: microscope slide, we stain it, we look at it under

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Speaker 2: a microscope. Then you can see the individual cells and.

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Speaker 1: Oh, at that level, at that level.

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Speaker 2: So we're talking about in a neuron, which is right.

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Speaker 2: It's kind of the workhourse of your the central like

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Speaker 2: the brain and sending you know, information down to everywhere

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Speaker 2: in your body. Those neurons that are the cell you know,

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Speaker 2: you can get we call them vacuoles clear spaces. Basically

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Speaker 2: when you're looking at it in the neuron and around

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Speaker 2: the neuron, and when you do a special stain to

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Speaker 2: look at that, you'll see that's where this preon is accumulating.

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Speaker 2: So you can see a lot of these these preon

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Speaker 2: proteins and abnormal preons accumulating in a very sensitive spot

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Speaker 2: in the body.

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Speaker 4: I use the bed sheet analogy. If you ever tried

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Speaker 4: to fold a fitted bed sheet.

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Speaker 1: Oh, you know what, it's funny you mentioned that my

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Speaker 1: wife is yelling at me a whole bunch of sat

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Speaker 1: Night about that.

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Speaker 4: Yep, there's only if I was.

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Speaker 1: Almost gonna look it up.

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Speaker 4: There's only one.

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Speaker 1: I don't understand how she gets a legit fold right.

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Speaker 5: And and so I was in my early thirties when

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Speaker 5: we had a literal barroom discussion on what a duvet

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Speaker 5: cover is, and that's when I learned what it was.

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Speaker 1: Yeah, I hate them. We use them, and I hate them.

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Speaker 5: Yeah, how I thought that that was an option. Yeah,

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Speaker 5: it's not a mandatory piece of bedkit.

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Speaker 1: It's a blanket for your blanket.

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Speaker 5: Yeah.

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Speaker 4: Years ago when I when I started reading about CWD,

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Speaker 4: I was trying to think of an analogy that would

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Speaker 4: allow me to conceptualize it and dumb Mike speak and

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Speaker 4: I was like, okay, so these these proteins are they're

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Speaker 4: folding and it's misfolded. And then the fitted bed sheet

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Speaker 4: came to mind because I've never understood why I can't

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Speaker 4: fold it and my wife can't. But all I know

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Speaker 4: is the way she does it is perfect and it fits,

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Speaker 4: and the way I do it and Mark does it

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Speaker 4: and you do it is all wrong.

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Speaker 1: I mean to fold it up and put it on

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Speaker 1: like a shelf.

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Speaker 4: Yes, it never fits in the same space. And see

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Speaker 4: what she's got going on that her sheet fits. And

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Speaker 4: that's the way I kind of in my dumb mic brain,

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Speaker 4: that's how I kind of think about it. Is when

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Speaker 4: it's folded perfectly, it works every time. When it misfolds,

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Speaker 4: it never functions the same.

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Speaker 1: Well.

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Speaker 5: Plus, it's just another level of a household too, to

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Speaker 5: have more than one of those or more than one

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Speaker 5: per bed.

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Speaker 1: Now we got a lot of beds, a lot of

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Speaker 1: people living there. Okay, so keep going. So that's what

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Speaker 1: that is. That's a preon disease. Yes, and humans we

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Speaker 1: call there's is there only one preon disease in humans?

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Speaker 4: There's krutz Felt Jacob's disease.

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Speaker 1: Okay, that's it.

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Speaker 4: Yeah.

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Speaker 5: And I didn't understand that that we all carry these

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Speaker 5: these preons currently either whatever reason. I think that's the

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Speaker 5: first time I've heard that.

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Speaker 2: We all have normal in animals as well, normal prion proteins.

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Speaker 2: The functions aren't entirely known, but their their fate is

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Speaker 2: right there. Recycle and they have a lifespan, and they

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Speaker 2: move and when when they don't, And it's that accumulation

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Speaker 2: slowly over time that that leads to the actual disease.

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Speaker 1: And we they're in cattle, there's a prion disease called

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Speaker 1: mad cow disease, and sheep there's a prion disease called

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Speaker 1: scrapy humans yaka crutch felt.

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Speaker 2: What is it?

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Speaker 4: Utch felt?

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Speaker 1: Crush? I always screw up which one comes first. These

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Speaker 1: are all kind of the same thing. It's just manifests

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Speaker 1: a certain way in cattle, manifest a certain way in sheep.

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Speaker 1: Is that a fair way to think about it.

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Speaker 2: It's a family, it's it's basically a category of pathogen, right,

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Speaker 2: So we think, you know, normally more commonly about bacteria

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Speaker 2: or a virus or a fungus or a parasite. So

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Speaker 2: the prions are sort of in this umbrella category known

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Speaker 2: as transmissible sponge of form encephalopathy or t SE. Transmissible

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Speaker 2: meaning you know, moving from one animal to the other.

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Speaker 2: Bunge of form gets at what we just talked about

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Speaker 2: with those prions accumulating kind of greeding holes more or

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Speaker 2: less in the brain. In Cephalopathy just means the disease

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Speaker 2: of the brain, and so chattle b sc bovine sponge

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Speaker 2: of form, and cephalopathies, scrapies c j D, and humans UH.

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Speaker 2: One of the earlier described was kuru in Papua New Guinea,

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Speaker 2: some ritualistic cannibalism that led to in humans, you know,

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Speaker 2: a prion disease. There's transmissible mink uh encephalopathy. So there's

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Speaker 2: there's banks, so there's there's others. But they all kind

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Speaker 2: of share similar traits. The one that makes CWD so

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Speaker 2: wicked is that it it's shed and passes from animal

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Speaker 2: to animal efficiently, so scrapey does as well. Those two

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Speaker 2: kind of set apart. As far as uniqueness among some

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Speaker 2: of the t ses.

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Speaker 5: And and scrapy is is preventable through a a vaccine, right.

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Speaker 2: Not a vaccine, it's it's really through so one thing,

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Speaker 2: scraping and scraping and cwds share some similarities relative to

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Speaker 2: you know, like I just said that the prions actually

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Speaker 2: leave the animal's body and can transmit to one another.

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Speaker 2: There's environmental components, so animals can get infected from the environment,

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Speaker 2: or they can get infected from their buddies. But one

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Speaker 2: thing that that Scrapey had sort of that that led

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Speaker 2: to some effective management for the domestic livestock industry is

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Speaker 2: that genetically there are some some different genotypes of sheep

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Speaker 2: related to that that you know, the preon protein that

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Speaker 2: I mentioned, Well, that preon protein is encoded by a gene,

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Speaker 2: and so there's a there's a particular genotype in domestic

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Speaker 2: sheep that they're they're pretty resistant, very resistant to cw

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Speaker 2: or to scrapey. And so through intensive you know, breeding

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Speaker 2: management and domestic sheep and then culling of everybody else,

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Speaker 2: they've been able to get on top of it. And

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Speaker 2: so that's a tool that scrapeye has that we don't

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Speaker 2: we don't have access to.

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Speaker 5: God, dear God, I didn't I didn't realize that I know.

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Speaker 5: I do know that the culling part of that in

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Speaker 5: the domestic world is severe. There's no nobody gets left behind.

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Speaker 1: And when we talk about chronic waste disease, we're talking

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Speaker 1: about one of these prion diseases that afflicts members of

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Speaker 1: the deer family. Yeah, so servants, deer, white tailed deer, mule, deer, elk, moose, caribou, servants. Ye,

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Speaker 1: think of things that if you're sitting there at home,

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Speaker 1: think of things that have antlers and shed those antlers.

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Speaker 4: Yes, and it's it's a one hundred percent fatal disease.

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Speaker 1: This has been Now we're going to lay out I

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Speaker 1: want to I want to briefly lay out what what different,

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Speaker 1: what you hear different hunters say about this situation. It's

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Speaker 1: part of while Yeah, it was first identified in the

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Speaker 1: seventies in Colorado, nineteen sixty seven. I was a sixty

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Speaker 1: seven on a research facility.

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Speaker 4: That's right. I think it was formerly described an eighty

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Speaker 4: nineteen eighty, I believe.

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Speaker 1: Yeah, So we found out about it, not to say it,

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Speaker 1: you know, who knows the history of it. Who knows

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Speaker 1: did it? Did it emerge one day? Did it emerge

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Speaker 1: that year? And we found it. That's like an outstanding question.

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Speaker 1: But it was identified on a research facility in Colorado,

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Speaker 1: and as we've looked for it more, we find more

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Speaker 1: of it. Though it definitely seems to spread. It's not

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Speaker 1: just detection, right fair, Yes, we tend to find a

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Speaker 1: lot of CWD in places that have a lot of deer,

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Speaker 1: which leads people has historically led people to say, if

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Speaker 1: it's in a place that has a lot of deer,

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Speaker 1: then it must not be that much of a problem,

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Speaker 1: because how could it be that bad if the places

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Speaker 1: that have the most deer have CWD. I'm still shooting bucks.

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Speaker 1: I'm still shooting big bucks. We got some of the

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Speaker 1: highest deer densities in the country. Where's the problem? And

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Speaker 1: in fact, at times people have come in early on,

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Speaker 1: in the early on in the battle against c w D,

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Speaker 1: you'd have an outbreak in an area and wildlife managers

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Speaker 1: would propose, well, let's try to go in and eradicate

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Speaker 1: every deer in the area to stop the spread, which

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Speaker 1: struck people as like quite counterintuitive. Here we're talking about

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Speaker 1: a disease that could potentially kill the deer, but there's

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Speaker 1: a ton of them around, and the remedy is to

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Speaker 1: kill them, all right, that seems odd, right, So that

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Speaker 1: strikes people's odd. Another thing will come in and they'll say, hey,

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Speaker 1: we have this disease that's spreading from seems to be

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Speaker 1: spreading from animal to animal, and so we're gonna make

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Speaker 1: it that you're not supposed to bait out on the

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Speaker 1: ground because that'll make deer come together. And people might

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Speaker 1: point out, I don't use bait, but I see deer

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Speaker 1: together all the time, right, They have sex, they hang out,

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Speaker 1: they nurse from one each other, they socialize.

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Speaker 4: The same tree.

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Speaker 1: Yeah, they play grab ass whatever, like, they're always in contact.

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Speaker 1: I don't see how me not putting out and see

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Speaker 1: how me putting bait out is making deer socialized when

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Speaker 1: I've been watching deer my whole life in the socialize.

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Speaker 1: So what's the big deal. Another thing guys might come

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Speaker 1: and say, and again this is all stuff from like

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Speaker 1: well meaning people that love deer. Guys might come and

393
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Speaker 1: say they're they're advising me against eating deer. That that

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Speaker 1: you know I should no deer. No dear test negative.

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Speaker 1: A deer might test not detectable, right, meaning you get

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Speaker 1: either if you submit if you kill a deer and

397
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Speaker 1: you want to be like, hey, I want to find

398
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Speaker 1: out if it's got CWD. You don't get negative, you

399
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Speaker 1: get not found, you get not detected. So off of

400
00:22:42,560 --> 00:22:45,480
Speaker 1: guys will say it tested negative, and people will point out,

401
00:22:45,480 --> 00:22:49,400
Speaker 1: it didn't test negative, it tested not found. Okay, so

402
00:22:49,760 --> 00:22:54,439
Speaker 1: we have no case. We have no case ever in

403
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Speaker 1: the history of the United States of America, the world, whatever.

404
00:22:58,520 --> 00:23:01,960
Speaker 1: There's no case ever where it has been shown that

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00:23:02,040 --> 00:23:07,720
Speaker 1: a human has contracted chronic wasting disease. So people will say,

406
00:23:07,880 --> 00:23:12,120
Speaker 1: why is my game agency, Why is centers for Disease Control?

407
00:23:12,480 --> 00:23:17,600
Speaker 1: Why are they saying don't eat positive meat because of

408
00:23:17,600 --> 00:23:24,639
Speaker 1: a health risk, but there's no demonstrative health risk. It

409
00:23:24,960 --> 00:23:27,320
Speaker 1: winds up smacking a little bit of to people, it

410
00:23:27,320 --> 00:23:30,800
Speaker 1: winds up smacking a little bit of COVID. Right, be

411
00:23:30,920 --> 00:23:33,359
Speaker 1: really afraid, be really afraid, but we don't really know

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00:23:33,359 --> 00:23:36,000
Speaker 1: what you're supposed to. Just be afraid. And that is

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Speaker 1: the thing that strikes people's like, you keep telling me

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00:23:38,640 --> 00:23:44,200
Speaker 1: not to do it, but no one's gotten it. Various

415
00:23:44,760 --> 00:23:50,240
Speaker 1: versions of this, the annoyances around baiting restrictions, the idea

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Speaker 1: that we're gonna coll or eradicate deer in certain areas,

417
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Speaker 1: The restriction like you're not supposed to bait, you can't

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00:23:59,240 --> 00:24:04,679
Speaker 1: put bait down anymore, has, in my view, has turned

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00:24:04,680 --> 00:24:06,879
Speaker 1: people a lot where they don't want to hear about

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00:24:07,160 --> 00:24:12,160
Speaker 1: research anymore. They just want to say it's all bullshit, right, yep.

421
00:24:12,880 --> 00:24:15,120
Speaker 1: To bring COVID back, I'm about done setting this whole

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Speaker 1: thing up. But I'm just trying to tell you, like,

423
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Speaker 1: to bring COVID back would be there was a thing.

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Speaker 1: People were getting sick, people were dying of COVID nineteen.

425
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Speaker 1: At the same time, people are like, oh, if someone

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Speaker 1: brings a box your house, don't touch the box. Your

427
00:24:30,320 --> 00:24:33,200
Speaker 1: kids can't go to school, you can't fly in an airplane,

428
00:24:33,280 --> 00:24:35,040
Speaker 1: your business needs to go out of business.

429
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Speaker 4: You need to change your behavior.

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Speaker 1: Yeah, right, And then in the end people are like, man,

431
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Speaker 1: I'm not going to listen to anything anybody says. I'm

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Speaker 1: just fed up.

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Speaker 4: Yep, I'm done.

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Speaker 1: And then they're done.

435
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Speaker 4: Yep.

436
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Speaker 1: We've hit this is my view. In my view, we've

437
00:24:54,359 --> 00:24:57,919
Speaker 1: hit a dangerous spot around conversations around chronic waste and

438
00:24:57,920 --> 00:25:01,800
Speaker 1: disease because we've had a lot of guys are like

439
00:25:01,960 --> 00:25:08,639
Speaker 1: hit the done phase. They're done, and I don't think

440
00:25:08,680 --> 00:25:12,639
Speaker 1: we should be done right, Like we should be asking

441
00:25:12,720 --> 00:25:14,840
Speaker 1: questions and looking at what's going to happen. Because I

442
00:25:14,880 --> 00:25:19,439
Speaker 1: think that this conversation, the conversations about this could be

443
00:25:19,560 --> 00:25:22,160
Speaker 1: very different in twenty years.

444
00:25:23,520 --> 00:25:26,760
Speaker 5: I think it would be worthwhile to kind of dissect

445
00:25:26,840 --> 00:25:27,680
Speaker 5: the done.

446
00:25:27,960 --> 00:25:30,800
Speaker 1: Like what done looks like? Yeah, well, because.

447
00:25:30,640 --> 00:25:34,399
Speaker 5: There's, as with everything, there's people who get there through

448
00:25:34,920 --> 00:25:36,840
Speaker 5: for a bunch of different reasons, right.

449
00:25:36,760 --> 00:25:39,640
Speaker 1: Yeah, like self like selfish reasons.

450
00:25:39,800 --> 00:25:40,159
Speaker 4: Yeah.

451
00:25:40,200 --> 00:25:45,600
Speaker 5: There's like the the what we talk about in hunting

452
00:25:45,640 --> 00:25:49,840
Speaker 5: all the time, which is like the the heritage part.

453
00:25:50,119 --> 00:25:54,280
Speaker 5: It's like, well, Grandpa managed white tails this way. Grandpa

454
00:25:54,320 --> 00:25:57,959
Speaker 5: was awesome. How could anything he do be wrong? And

455
00:25:58,000 --> 00:26:03,720
Speaker 5: that offends me personally, can't change. There's the I don't

456
00:26:03,760 --> 00:26:05,960
Speaker 5: care what anybody says. I just want big bucks. This

457
00:26:06,080 --> 00:26:10,320
Speaker 5: is the way that we get big bucks. And then

458
00:26:10,480 --> 00:26:13,760
Speaker 5: there's the vein of folks who are like, well, what's

459
00:26:13,800 --> 00:26:20,720
Speaker 5: the bigger crime here? Eating CWD meat or throwing it away?

460
00:26:21,720 --> 00:26:21,880
Speaker 4: Right?

461
00:26:21,920 --> 00:26:25,280
Speaker 5: And there's people who are like, this is my time

462
00:26:25,320 --> 00:26:27,200
Speaker 5: in the deer woods and the meat is a huge

463
00:26:27,240 --> 00:26:30,120
Speaker 5: part of it. And they struggle And I run into

464
00:26:30,160 --> 00:26:38,080
Speaker 5: these people a lot. They really struggle with having to

465
00:26:38,119 --> 00:26:42,880
Speaker 5: face that decision. So instead of facing that decision, they

466
00:26:42,920 --> 00:26:46,200
Speaker 5: just go full ignorance. They're like, I will not get

467
00:26:46,200 --> 00:26:48,280
Speaker 5: this thing tested because I don't want to face that

468
00:26:48,359 --> 00:26:52,960
Speaker 5: decision right and notify me and if things change.

469
00:26:53,080 --> 00:26:56,400
Speaker 4: All of that that you just brought up as context

470
00:26:56,640 --> 00:26:58,719
Speaker 4: is what Mark and I have been talking about for

471
00:26:58,760 --> 00:27:05,640
Speaker 4: weeks and is largely why we're here sitting with you,

472
00:27:06,040 --> 00:27:12,120
Speaker 4: is to have that conversation because as researchers, we look

473
00:27:12,160 --> 00:27:15,680
Speaker 4: at CWD through a certain lens. As a deer hunter,

474
00:27:15,920 --> 00:27:18,720
Speaker 4: I look at CWD through an entirely different lens. I

475
00:27:19,680 --> 00:27:25,240
Speaker 4: understand the frustration that you just mentioned cal and then

476
00:27:25,320 --> 00:27:28,560
Speaker 4: I have to I have to step back and realize

477
00:27:28,640 --> 00:27:31,959
Speaker 4: that one thing we're seeing with CWD is that it

478
00:27:32,000 --> 00:27:35,600
Speaker 4: doesn't function the same across the landscape. It can affect

479
00:27:35,640 --> 00:27:42,280
Speaker 4: certain populations differently. We are also seeing that you it

480
00:27:42,400 --> 00:27:47,399
Speaker 4: takes this disease has a long incubation period, and it

481
00:27:47,520 --> 00:27:52,720
Speaker 4: takes decades to run its course, not months or years, decades,

482
00:27:53,400 --> 00:27:56,399
Speaker 4: And so within a population, within a population, so not

483
00:27:56,480 --> 00:27:59,199
Speaker 4: within an animal, but within within a population. Yeah, so

484
00:27:59,280 --> 00:28:01,800
Speaker 4: within at the end animal level, you're talking, you know,

485
00:28:02,240 --> 00:28:05,840
Speaker 4: eighteen to twenty four months for this disease to progress.

486
00:28:06,960 --> 00:28:11,120
Speaker 4: And at the population level, you're talking decades for the population.

487
00:28:13,000 --> 00:28:15,680
Speaker 4: So in essence, kind of think about it like this.

488
00:28:15,840 --> 00:28:19,040
Speaker 4: You have these two axes on the graph. On the

489
00:28:19,080 --> 00:28:22,600
Speaker 4: bottom you have time, you have years, and on the

490
00:28:22,680 --> 00:28:28,920
Speaker 4: vertical axis you have prevalence, right, And what you're seeing

491
00:28:29,160 --> 00:28:34,240
Speaker 4: is that in low prevalence, a population can literally trend

492
00:28:34,320 --> 00:28:39,840
Speaker 4: through time at one percent prevalence, almost undetectable for years,

493
00:28:40,920 --> 00:28:44,720
Speaker 4: and then it slowly starts to increase in prevalence. And

494
00:28:44,760 --> 00:28:47,080
Speaker 4: when I say slow, I'm talking a decade to go

495
00:28:47,200 --> 00:28:52,040
Speaker 4: from one to two percent, and then two to three percent,

496
00:28:52,320 --> 00:28:54,840
Speaker 4: and then to five percent and then to twenty percent.

497
00:28:55,000 --> 00:28:59,960
Speaker 4: And you start seeing this exponential increase in prevalence rates

498
00:29:01,000 --> 00:29:02,560
Speaker 4: and we don't know.

499
00:29:04,280 --> 00:29:07,200
Speaker 1: What. Give me like a place, give me a place

500
00:29:07,240 --> 00:29:10,840
Speaker 1: in the country where we could be talking about we're

501
00:29:10,960 --> 00:29:12,680
Speaker 1: like one percent for a decade.

502
00:29:12,960 --> 00:29:15,400
Speaker 5: So and then there but you said there is like

503
00:29:15,680 --> 00:29:16,720
Speaker 5: a takeoff point.

504
00:29:17,200 --> 00:29:20,240
Speaker 4: Yeah, so what So what Mark and I run into

505
00:29:20,400 --> 00:29:25,640
Speaker 4: is we do research like this Arkansas study we just finished,

506
00:29:26,120 --> 00:29:28,600
Speaker 4: and you don't know when you start to study where

507
00:29:28,640 --> 00:29:32,080
Speaker 4: you are on the curve. Oh yeah, and so you

508
00:29:32,240 --> 00:29:35,720
Speaker 4: have prevalence data, so in other words as we can

509
00:29:35,720 --> 00:29:38,200
Speaker 4: talk about. You know, an agency collects prevalence data and

510
00:29:38,240 --> 00:29:42,000
Speaker 4: they let's say they think they're at five percent prevalence. Well,

511
00:29:42,040 --> 00:29:46,120
Speaker 4: then they start expanding testing and they realize, yeah, we

512
00:29:46,160 --> 00:29:48,720
Speaker 4: are at five, or maybe we're at fifteen, or maybe

513
00:29:48,760 --> 00:29:52,520
Speaker 4: we're at twenty. And then you have other situations where

514
00:29:52,560 --> 00:29:55,240
Speaker 4: you have we think we're at twenty and we're at

515
00:29:55,280 --> 00:29:59,040
Speaker 4: thirty five or forty. And then you have other situations

516
00:29:59,080 --> 00:30:03,920
Speaker 4: where you have a single detection and then after lots

517
00:30:03,960 --> 00:30:06,680
Speaker 4: and lots of testing in that area, you have two

518
00:30:07,280 --> 00:30:12,200
Speaker 4: or three or five animals that are positive. So the

519
00:30:12,680 --> 00:30:17,360
Speaker 4: disease is functioning differently across the landscape, and so that

520
00:30:17,440 --> 00:30:22,800
Speaker 4: creates confusion and frustration and uncertainty because this disease, as

521
00:30:22,880 --> 00:30:25,440
Speaker 4: Mark can explain, didn't read the book on how to

522
00:30:25,480 --> 00:30:29,480
Speaker 4: be a disease. So that creates a lot of uncertainty.

523
00:30:29,520 --> 00:30:33,760
Speaker 4: And so when we go design these field studies trying

524
00:30:33,840 --> 00:30:37,120
Speaker 4: to get information to assist agencies with their decision making,

525
00:30:37,280 --> 00:30:39,960
Speaker 4: we don't really know where we are on that curve.

526
00:30:40,840 --> 00:30:45,680
Speaker 4: And once we think we figure out where we are, sometimes,

527
00:30:45,760 --> 00:30:47,400
Speaker 4: you know, some of the some of the work that's

528
00:30:47,440 --> 00:30:52,040
Speaker 4: coming out now Arkansas West Virginia, Wisconsin. They're seeing that

529
00:30:52,360 --> 00:30:56,400
Speaker 4: they they're at a different point along this curve than

530
00:30:56,440 --> 00:30:59,720
Speaker 4: they believe they were when the research project started, which

531
00:30:59,760 --> 00:31:02,800
Speaker 4: is what we saw in Arkansas. We thought we were

532
00:31:03,160 --> 00:31:06,600
Speaker 4: at a point and in reality we were much farther

533
00:31:06,800 --> 00:31:10,920
Speaker 4: up the curve to where prevalence was extremely high. And

534
00:31:11,320 --> 00:31:14,120
Speaker 4: that just speaks to the complexity of the disease.

535
00:31:14,840 --> 00:31:16,680
Speaker 2: Yeah, just to follow up on a couple of things,

536
00:31:16,800 --> 00:31:20,720
Speaker 2: I think at the root of so much confusion relative

537
00:31:20,760 --> 00:31:25,160
Speaker 2: to c TOWD is adjusting our time scale. Right, So

538
00:31:26,120 --> 00:31:28,800
Speaker 2: heemorrhagic disease, for instance, there's not a deer hunter who

539
00:31:28,840 --> 00:31:33,520
Speaker 2: doesn't fear haemorrhagic disease. You know, messing up a season, right,

540
00:31:33,560 --> 00:31:36,760
Speaker 2: and it's sweeping through and that's actively happening right now.

541
00:31:36,920 --> 00:31:40,400
Speaker 1: Yes, So like just just for people that know some terms,

542
00:31:40,880 --> 00:31:44,920
Speaker 1: you might hear EHD, you might hear blue tongue YEP,

543
00:31:45,360 --> 00:31:47,600
Speaker 1: which comes in and just wham.

544
00:31:47,200 --> 00:31:50,760
Speaker 2: Yes, it's it's it comes in. You know, it's a flood,

545
00:31:51,320 --> 00:31:54,000
Speaker 2: a quick one, right. You can go from zero to

546
00:31:54,040 --> 00:31:57,680
Speaker 2: sixty in the span of weeks, right, and you'll have

547
00:31:58,080 --> 00:32:02,120
Speaker 2: it's very visible, it's explosive of it's clustered, so you

548
00:32:02,160 --> 00:32:06,000
Speaker 2: can you see death, you smell death. It's everywhere, right,

549
00:32:06,080 --> 00:32:10,760
Speaker 2: it's very jarring, very alarming. And so you know, and

550
00:32:10,800 --> 00:32:13,840
Speaker 2: I've spent a long time studying that disease, and it's

551
00:32:13,920 --> 00:32:19,000
Speaker 2: you know, it's a it's it's got a lot of

552
00:32:19,040 --> 00:32:23,560
Speaker 2: sort of it'll grab your attention really quick. Right, it's

553
00:32:23,680 --> 00:32:27,320
Speaker 2: very concerning c w D and it's and it's all boom, right,

554
00:32:27,440 --> 00:32:29,920
Speaker 2: it's it's in. It's in a matter of weeks or

555
00:32:30,000 --> 00:32:33,080
Speaker 2: months exactly exactly.

556
00:32:34,200 --> 00:32:35,040
Speaker 1: They didn't know where.

557
00:32:35,400 --> 00:32:37,400
Speaker 2: Yeah, you're wondering about how do I deal with all

558
00:32:37,440 --> 00:32:40,880
Speaker 2: these carcases. They're starting to smell bad, right, Flip that

559
00:32:41,000 --> 00:32:46,240
Speaker 2: to CWD. It's it's completely opposite. There's there's multiple examples

560
00:32:46,280 --> 00:32:49,240
Speaker 2: in the country of hiding in plain sight, not for years,

561
00:32:49,520 --> 00:32:52,720
Speaker 2: but for decades. Right, it's cryptic on the landscape. You

562
00:32:52,800 --> 00:32:56,760
Speaker 2: don't see it until you until you see it. And

563
00:32:56,840 --> 00:32:58,960
Speaker 2: so when I think about CWD, I think about it

564
00:32:59,000 --> 00:33:01,640
Speaker 2: in individuals and I think about it in populations at

565
00:33:01,640 --> 00:33:04,760
Speaker 2: the individual level. You know, we're talking about we think

566
00:33:04,800 --> 00:33:08,480
Speaker 2: of it in terms of months and years, not days

567
00:33:08,480 --> 00:33:11,040
Speaker 2: and weeks like we would hemorrhagic disease. So months and

568
00:33:11,120 --> 00:33:14,040
Speaker 2: years for an individual, but like Mike said, for a population,

569
00:33:15,000 --> 00:33:18,720
Speaker 2: we think in terms of years and decades. And so

570
00:33:18,960 --> 00:33:23,320
Speaker 2: it's that slow, cryptic nature of the disease that just

571
00:33:24,240 --> 00:33:26,360
Speaker 2: I think at that is the root of so many

572
00:33:26,440 --> 00:33:29,120
Speaker 2: challenges for people to wrap their heads around in terms of,

573
00:33:29,800 --> 00:33:31,200
Speaker 2: you know, do we need to care about it? Why

574
00:33:31,240 --> 00:33:32,920
Speaker 2: do I need to care about it. I'm not seeing

575
00:33:32,960 --> 00:33:36,280
Speaker 2: anything on the landscape. Heemorrhagic disease just stacked up a

576
00:33:36,280 --> 00:33:39,920
Speaker 2: bunch of bodies in my property. I don't see anything.

577
00:33:40,040 --> 00:33:42,720
Speaker 1: Yeah, Meaning some guy turns in a deer for testing

578
00:33:43,800 --> 00:33:46,680
Speaker 1: first time in his county. There's a deer that's positive

579
00:33:46,680 --> 00:33:51,600
Speaker 1: in his county. Wildlife managers then like, good lord, let's

580
00:33:51,640 --> 00:33:56,440
Speaker 1: rewrite the rule book. And people at home, deer hunters

581
00:33:56,480 --> 00:33:59,560
Speaker 1: at home, are like, I just don't see the issue, right,

582
00:34:00,280 --> 00:34:02,320
Speaker 1: that that might be a thing that they come away

583
00:34:02,360 --> 00:34:06,440
Speaker 1: with because they're like, I don't get it. I saw

584
00:34:06,520 --> 00:34:09,160
Speaker 1: all kinds of deer, yeah, and I can't. I'm having

585
00:34:09,200 --> 00:34:10,880
Speaker 1: great hunting. Why is there a problem?

586
00:34:10,960 --> 00:34:13,759
Speaker 4: Right? I can't speak for a state agency, but Mark

587
00:34:13,800 --> 00:34:17,160
Speaker 4: and I can both. You know, state agencies take a

588
00:34:17,320 --> 00:34:22,120
Speaker 4: very Most state agencies take a fairly scripted approach to

589
00:34:22,280 --> 00:34:25,640
Speaker 4: dealing with CWD, and what they're trying to do is

590
00:34:25,680 --> 00:34:31,040
Speaker 4: they're trying to reduce transmission rates amongst individuals. They're trying

591
00:34:31,600 --> 00:34:35,799
Speaker 4: to prevent the transport of the disease outside of the

592
00:34:35,800 --> 00:34:38,880
Speaker 4: im mediatet local area. Because what we do know with

593
00:34:38,920 --> 00:34:42,880
Speaker 4: CWD is it starts out as a focal spot on

594
00:34:42,920 --> 00:34:47,800
Speaker 4: the landscape and then it slowly spreads outward from that spot.

595
00:34:48,200 --> 00:34:51,479
Speaker 4: And so what agencies are trying to do, you'll see

596
00:34:51,520 --> 00:34:55,439
Speaker 4: common responses be the creation of a CWD management zone, right,

597
00:34:55,520 --> 00:34:59,120
Speaker 4: So they'll delineate in an area, a geographic area, and

598
00:34:59,160 --> 00:35:03,719
Speaker 4: they'll create restrictions on import and export of carcasses or

599
00:35:03,760 --> 00:35:08,480
Speaker 4: parts of carcasses. They will ban sometimes you know ban

600
00:35:08,719 --> 00:35:11,719
Speaker 4: or alter how feed is applied to the landscape.

601
00:35:12,000 --> 00:35:13,319
Speaker 5: Yeah, beating bands, yep.

602
00:35:13,360 --> 00:35:19,920
Speaker 4: They'll often liberalize exactly and remove antler point restrictions and

603
00:35:19,960 --> 00:35:21,760
Speaker 4: things like that because what they're doing.

604
00:35:21,600 --> 00:35:25,080
Speaker 5: And here's like one of those major friction points is

605
00:35:25,120 --> 00:35:29,040
Speaker 5: like the state is actively working against the quality of

606
00:35:29,120 --> 00:35:30,920
Speaker 5: my personal deer hunting yep.

607
00:35:31,080 --> 00:35:33,719
Speaker 4: And what what's so what's at play there? And I

608
00:35:33,800 --> 00:35:35,879
Speaker 4: get it as a deer hunter, I totally get that,

609
00:35:36,560 --> 00:35:38,720
Speaker 4: but you have to look at it through their lens.

610
00:35:39,000 --> 00:35:43,440
Speaker 4: They are publicly, by law charged with managing for conservation

611
00:35:43,560 --> 00:35:46,600
Speaker 4: and sustainability of the species of wildlife in their state,

612
00:35:47,520 --> 00:35:50,760
Speaker 4: and so they're dealt this gut punch of being told

613
00:35:51,280 --> 00:35:56,879
Speaker 4: you have this disease on on your landscape. They they

614
00:35:56,920 --> 00:36:00,200
Speaker 4: have two approaches. They can They could be nihilistic and

615
00:36:00,320 --> 00:36:03,160
Speaker 4: just say I'm not doing anything, or they could take

616
00:36:03,320 --> 00:36:06,520
Speaker 4: this approach that we don't know where we are on

617
00:36:06,560 --> 00:36:10,680
Speaker 4: the curve, so we're going to create this zone. We're

618
00:36:10,719 --> 00:36:15,680
Speaker 4: going to expand our surveillance and testing, and meanwhile we're

619
00:36:15,680 --> 00:36:19,440
Speaker 4: going to try to reduce transmission. Right, we know that

620
00:36:19,560 --> 00:36:22,760
Speaker 4: deer are licking each other, and we know that they're

621
00:36:22,880 --> 00:36:25,680
Speaker 4: feeding under the same tree and all of that. But

622
00:36:26,360 --> 00:36:31,719
Speaker 4: for instance, what feeding is doing is putting animals at

623
00:36:31,719 --> 00:36:38,040
Speaker 4: the same spot on the landscape repeatedly and therefore changing

624
00:36:38,120 --> 00:36:41,839
Speaker 4: how the preon can get into the environment and then

625
00:36:41,920 --> 00:36:45,840
Speaker 4: remain in the environment. So an animal coming to a

626
00:36:45,880 --> 00:36:49,879
Speaker 4: feeder every day and eating at that feeder every day

627
00:36:50,600 --> 00:36:55,319
Speaker 4: is very different from a preon accumulation standpoint than if

628
00:36:55,360 --> 00:36:58,040
Speaker 4: he's walking around in a food plot or going under

629
00:36:58,040 --> 00:37:01,520
Speaker 4: an oak tree, and the ac warns are there, he's

630
00:37:01,600 --> 00:37:04,440
Speaker 4: around other deer for a couple of weeks, and then

631
00:37:04,440 --> 00:37:07,320
Speaker 4: he's gone. That's not the way a feed or functions.

632
00:37:07,360 --> 00:37:09,880
Speaker 4: So that's what the agencies I'm not I'm not trying

633
00:37:09,880 --> 00:37:13,239
Speaker 4: to justify their actions. I'm simply explaining that that's the

634
00:37:13,320 --> 00:37:15,520
Speaker 4: logic is that let's put this.

635
00:37:15,840 --> 00:37:18,120
Speaker 1: More dear from farther away and put them on the

636
00:37:18,200 --> 00:37:20,920
Speaker 1: same like literally the same square photograph.

637
00:37:20,960 --> 00:37:24,200
Speaker 2: I'm mixing social groups that normally wouldn't have those interactions.

638
00:37:24,280 --> 00:37:26,840
Speaker 4: That has been shown that you know, you will bring

639
00:37:26,920 --> 00:37:31,720
Speaker 4: multiple social groups, think about dose, for instance, matriarchal family groups.

640
00:37:32,040 --> 00:37:34,760
Speaker 4: You will bring multiple family groups to the same location

641
00:37:34,880 --> 00:37:37,120
Speaker 4: and otherwise would not be there at that time.

642
00:37:38,440 --> 00:37:42,399
Speaker 5: One of the issues is like just like how I

643
00:37:42,440 --> 00:37:47,400
Speaker 5: personally contextualize these things. And when we talked about like

644
00:37:47,480 --> 00:37:52,440
Speaker 5: preon's around the landscape forever, you can't get rid of them.

645
00:37:52,480 --> 00:37:56,040
Speaker 5: My visual my mental visual right is like that little

646
00:37:56,080 --> 00:37:58,600
Speaker 5: tiny sucker group of them is sitting there on the

647
00:37:58,640 --> 00:38:07,520
Speaker 5: tip of that forber grass forever. And then I saw

648
00:38:07,600 --> 00:38:13,960
Speaker 5: some body produced something that showed like how those preawns

649
00:38:14,000 --> 00:38:17,560
Speaker 5: eventually like work their their way down into the soil

650
00:38:18,160 --> 00:38:22,560
Speaker 5: to where they're they're just effectively not able to come

651
00:38:22,600 --> 00:38:26,320
Speaker 5: in contact with any sort of a grazer, right, which

652
00:38:26,400 --> 00:38:28,640
Speaker 5: makes like it rains, there's dew in the morning, it

653
00:38:28,680 --> 00:38:34,280
Speaker 5: starts like working its way down into the soil. And

654
00:38:35,080 --> 00:38:38,120
Speaker 5: that to me was one of those like really, like, boy,

655
00:38:38,160 --> 00:38:40,080
Speaker 5: you're kind of stupid for not having thought about this

656
00:38:40,160 --> 00:38:44,840
Speaker 5: yourself moments, right, but that is how you kind of

657
00:38:44,880 --> 00:38:48,359
Speaker 5: think about these things on first glance. Right, it's like, oh,

658
00:38:48,360 --> 00:38:51,080
Speaker 5: it's there forever, which she means then then was the

659
00:38:51,080 --> 00:38:51,960
Speaker 5: point in controlling this?

660
00:38:52,320 --> 00:38:52,800
Speaker 4: Yeah?

661
00:38:52,920 --> 00:38:55,680
Speaker 2: Right, I wanted to revisit one of the things you

662
00:38:55,719 --> 00:39:01,600
Speaker 2: said cal about sort of the disruption CWD has once

663
00:39:01,640 --> 00:39:05,640
Speaker 2: it's detected in an area to someone's here and now opportunity, right,

664
00:39:06,160 --> 00:39:08,600
Speaker 2: And I think a lot of those those you know,

665
00:39:08,719 --> 00:39:13,360
Speaker 2: common actions that an agency takes it does it seems restrictive.

666
00:39:13,400 --> 00:39:16,480
Speaker 2: It's how CWD has kind of become vilified in some ways,

667
00:39:17,239 --> 00:39:22,080
Speaker 2: but really those those actions target trying to lower the

668
00:39:22,239 --> 00:39:27,120
Speaker 2: risk of other deer getting CWD. So again, timescale, it's

669
00:39:27,960 --> 00:39:31,279
Speaker 2: we've got to adjust it. Those actions are they're further now,

670
00:39:31,320 --> 00:39:33,520
Speaker 2: but they're also for the future. To Mike's point about

671
00:39:33,520 --> 00:39:36,960
Speaker 2: stewardship and sustainability of the population, because we've got these

672
00:39:37,000 --> 00:39:40,080
Speaker 2: examples now of when we're at the end of that curve,

673
00:39:40,280 --> 00:39:44,000
Speaker 2: like when we're way towards decades down the road, we

674
00:39:44,000 --> 00:39:47,040
Speaker 2: we have glimpses into what that picture looks like, and

675
00:39:47,080 --> 00:39:49,480
Speaker 2: so so a lot of those actions are trying to

676
00:39:49,600 --> 00:39:54,920
Speaker 2: prevent or slow the movement in time along this this

677
00:39:55,000 --> 00:39:59,120
Speaker 2: sort of what phase of disease is the population at?

678
00:40:00,120 --> 00:40:02,360
Speaker 1: I desperately want to get into what you guys found

679
00:40:02,840 --> 00:40:05,359
Speaker 1: when you did your work in Arkansas, but I wanted

680
00:40:05,480 --> 00:40:09,040
Speaker 1: just a little more. We're very heavy on front loading here,

681
00:40:09,160 --> 00:40:14,560
Speaker 1: so apologies, But has it ever been demonstrated this is

682
00:40:14,560 --> 00:40:21,560
Speaker 1: a huge question, apologies, have any of these early detection restrictions.

683
00:40:21,880 --> 00:40:25,400
Speaker 1: Has any of them ever been demonstrated to be effective?

684
00:40:27,920 --> 00:40:30,000
Speaker 1: Is that yes they have? Or yes? You understand the

685
00:40:30,040 --> 00:40:30,640
Speaker 1: question I.

686
00:40:30,600 --> 00:40:33,600
Speaker 6: Do that I think that I do is to both

687
00:40:33,680 --> 00:40:38,719
Speaker 6: as well as the uh yeah, that's it's that's challenging, right,

688
00:40:38,840 --> 00:40:42,040
Speaker 6: because that that's a big.

689
00:40:41,880 --> 00:40:44,799
Speaker 2: Desire among many, right, is in the and we and

690
00:40:44,840 --> 00:40:48,160
Speaker 2: we often will sort of isolate one, right, will isolate

691
00:40:48,719 --> 00:40:52,040
Speaker 2: you know, carcass movement, or will isolate baiting restrictions or

692
00:40:52,040 --> 00:40:56,560
Speaker 2: feeding restrictions or faun rehabilitation or or removal of aprs

693
00:40:56,640 --> 00:40:59,239
Speaker 2: or whatever. You know, it's sort of the all la

694
00:40:59,320 --> 00:41:02,640
Speaker 2: carte you of options for these are the tools we

695
00:41:02,680 --> 00:41:08,400
Speaker 2: got in the toolbox. The challenge with evalue, like evaluating

696
00:41:08,440 --> 00:41:11,880
Speaker 2: one at a time, is that's not how they've really deployed.

697
00:41:11,520 --> 00:41:13,960
Speaker 1: When you apply it. Let's say I'm saying does applying

698
00:41:14,040 --> 00:41:17,600
Speaker 1: the whole toolbox? I don't mean to carve out what

699
00:41:17,719 --> 00:41:22,800
Speaker 1: restriction was effective. Have we ever had a situation where

700
00:41:22,840 --> 00:41:26,560
Speaker 1: there was a detection of the disease of a novel detection,

701
00:41:26,680 --> 00:41:29,279
Speaker 1: so a detection of the disease in a in a

702
00:41:29,400 --> 00:41:33,600
Speaker 1: place that had been previously unknown, The toolbox is applied,

703
00:41:34,120 --> 00:41:37,200
Speaker 1: and then lo and behold, we never get another detection

704
00:41:37,920 --> 00:41:42,520
Speaker 1: New York Or is it always it's just full blast ahead?

705
00:41:43,000 --> 00:41:45,480
Speaker 2: No, it's not always there. There are successes, right, so

706
00:41:45,560 --> 00:41:48,799
Speaker 2: there's you know, there's you also have to kind of

707
00:41:48,800 --> 00:41:52,160
Speaker 2: reframe the version of success too, Like the best example

708
00:41:52,200 --> 00:41:54,960
Speaker 2: of success would be New York right where they had

709
00:41:54,960 --> 00:42:00,279
Speaker 2: a detection there there was a captive facility involved, there

710
00:42:00,320 --> 00:42:05,240
Speaker 2: was depopulation of those facilities and aggressive removal of deer

711
00:42:05,480 --> 00:42:10,319
Speaker 2: in a in a tight radius around that area. That

712
00:42:10,400 --> 00:42:12,319
Speaker 2: was sustained for several years, and they did not have

713
00:42:12,360 --> 00:42:15,439
Speaker 2: another detection, despite having detections not only inside the fence

714
00:42:15,480 --> 00:42:17,479
Speaker 2: but also in wild deer outside the fence.

715
00:42:17,480 --> 00:42:21,200
Speaker 1: So that's that's reminding me. I'm familiar with that story.

716
00:42:21,239 --> 00:42:23,120
Speaker 4: So they caught it early. They caught it early enough

717
00:42:23,120 --> 00:42:25,880
Speaker 4: as that epicenter was growing that that focal area was

718
00:42:25,920 --> 00:42:28,560
Speaker 4: small enough around that captive facility that they could catch

719
00:42:28,600 --> 00:42:31,600
Speaker 4: it in time. And with that intensive culling around that facility,

720
00:42:32,280 --> 00:42:36,200
Speaker 4: they caught the spread before it had gotten too far,

721
00:42:36,320 --> 00:42:38,080
Speaker 4: which is what we're finding in a lot of our

722
00:42:38,200 --> 00:42:43,960
Speaker 4: wild populations. By the time an animals detect that is

723
00:42:44,000 --> 00:42:47,799
Speaker 4: being positive, the follow up surveillance is showing that it's

724
00:42:47,840 --> 00:42:52,160
Speaker 4: more widespread and more prevalent in some situations. In that situation,

725
00:42:52,239 --> 00:42:56,839
Speaker 4: to Mark's point, that is incredibly challenging to try to

726
00:42:56,960 --> 00:43:00,720
Speaker 4: manage that disease when you realize that you're there along

727
00:43:00,760 --> 00:43:02,200
Speaker 4: that curve than you thought you were.

728
00:43:02,360 --> 00:43:05,120
Speaker 1: Yeah, Like, you get a county. I keep talking about

729
00:43:05,160 --> 00:43:07,719
Speaker 1: county level, but a county's a county, and I don't know,

730
00:43:07,840 --> 00:43:10,839
Speaker 1: pick a state. A county in Missouri gets its first

731
00:43:10,920 --> 00:43:19,120
Speaker 1: ever CWD hit from a hunter submitted deer that's the first.

732
00:43:19,480 --> 00:43:21,359
Speaker 1: But then you're saying, then they'll come in and be like, okay,

733
00:43:21,440 --> 00:43:24,120
Speaker 1: let's go test a thousand deer, and they test a

734
00:43:24,160 --> 00:43:27,239
Speaker 1: thousand deer and they're like, well, shit, there's fifty there's

735
00:43:27,280 --> 00:43:32,080
Speaker 1: fifty positives. So they didn't catch the first deer. It

736
00:43:32,200 --> 00:43:34,839
Speaker 1: had been there for some time, like yeah, we at

737
00:43:34,840 --> 00:43:36,800
Speaker 1: that point, you're like, is it the first, and they're like,

738
00:43:36,880 --> 00:43:39,120
Speaker 1: oh no, it's not the first. This has obviously been here.

739
00:43:39,200 --> 00:43:40,960
Speaker 1: We just never caught it. We were looking, and now

740
00:43:40,960 --> 00:43:42,880
Speaker 1: that we're looking, it's all over the damn place. Right.

741
00:43:44,000 --> 00:43:46,799
Speaker 1: It's too late to it's too late to isolate that

742
00:43:46,840 --> 00:43:50,520
Speaker 1: little square mile of ground.

743
00:43:50,640 --> 00:43:50,920
Speaker 4: Yeah.

744
00:43:51,120 --> 00:43:53,440
Speaker 2: Yeah, So it changes the options, right, and if you

745
00:43:53,880 --> 00:43:55,719
Speaker 2: because that's you know, if you have if you have

746
00:43:55,880 --> 00:43:58,560
Speaker 2: say robust surveillance in a state, and you really have

747
00:43:58,680 --> 00:44:02,000
Speaker 2: some confidence that like this might not be the first,

748
00:44:02,440 --> 00:44:06,480
Speaker 2: but maybe it's really early, right, that that could that

749
00:44:06,520 --> 00:44:09,879
Speaker 2: could sort of justify some pretty severe aggression to try

750
00:44:09,920 --> 00:44:11,600
Speaker 2: to like, okay, if we got a chance, let's try

751
00:44:11,600 --> 00:44:14,160
Speaker 2: to stamp this out and to that to that point,

752
00:44:14,200 --> 00:44:18,000
Speaker 2: to your your victory point earlier, you know, there are

753
00:44:18,080 --> 00:44:22,440
Speaker 2: examples Minnesota, like a you know, within a state. Sometimes

754
00:44:22,480 --> 00:44:25,719
Speaker 2: we get we get focused on the state, but but

755
00:44:25,800 --> 00:44:28,359
Speaker 2: there are victories within states too, right. So you might

756
00:44:28,400 --> 00:44:30,480
Speaker 2: have an endemic region in a state or an area

757
00:44:30,520 --> 00:44:33,400
Speaker 2: that has c to BED established and you get a

758
00:44:33,440 --> 00:44:36,799
Speaker 2: spark somewhere else and through you know it's early, through

759
00:44:36,840 --> 00:44:39,120
Speaker 2: aggressive action, they kind of stamp it out and there's

760
00:44:39,160 --> 00:44:42,680
Speaker 2: no new cases, right, and so that shouldn't be lost,

761
00:44:42,719 --> 00:44:47,239
Speaker 2: I think in terms of victory even within an unaffected

762
00:44:47,280 --> 00:44:49,880
Speaker 2: region of a state. States are big areas, and the

763
00:44:49,960 --> 00:44:52,440
Speaker 2: disease moves slowly. So as long as we can be

764
00:44:53,280 --> 00:44:57,560
Speaker 2: aggressive on those outliers, you know, that will save you

765
00:44:57,600 --> 00:45:00,680
Speaker 2: know it, it will reset the time scale of this

766
00:45:00,719 --> 00:45:03,040
Speaker 2: disease in those areas. Right, then we're not marching up

767
00:45:03,080 --> 00:45:05,360
Speaker 2: that path where we're kind of starting over again and

768
00:45:05,600 --> 00:45:09,799
Speaker 2: waiting until the next one. As far as other successes,

769
00:45:11,120 --> 00:45:14,120
Speaker 2: that's where it gets a little bit more challenging with

770
00:45:14,239 --> 00:45:17,920
Speaker 2: some of these regulations. In areas where c TOBD is established,

771
00:45:18,800 --> 00:45:23,280
Speaker 2: it's about living with CWD, right, and so our goals

772
00:45:23,360 --> 00:45:26,880
Speaker 2: might be different. You know, some agencies are are controlling

773
00:45:26,920 --> 00:45:30,960
Speaker 2: you'll you'll you'll hear you know the term managing for prevalence, right,

774
00:45:31,200 --> 00:45:34,680
Speaker 2: So basically these actions are just trying to keep that

775
00:45:34,760 --> 00:45:39,120
Speaker 2: prevalence down to the to that likes as Mike was

776
00:45:39,160 --> 00:45:42,000
Speaker 2: talking about earlier, like you know, one percent to five percent,

777
00:45:42,120 --> 00:45:45,480
Speaker 2: you know, trying to prevent it from increasing sort of

778
00:45:45,520 --> 00:45:49,359
Speaker 2: exponentially up that slope. The more you can keep it

779
00:45:49,400 --> 00:45:54,600
Speaker 2: suppressed down, the the more you suppress the very negative

780
00:45:54,600 --> 00:45:57,440
Speaker 2: consequences at the population level. Right, and so a lot

781
00:45:57,440 --> 00:45:59,840
Speaker 2: of agencies are doing that. That's a hard that's a

782
00:45:59,840 --> 00:46:02,640
Speaker 2: hard like happy pill to swallow sometimes. Right, It's like

783
00:46:02,719 --> 00:46:04,920
Speaker 2: we're sort of redefining what success means.

784
00:46:04,920 --> 00:46:07,399
Speaker 1: When we're talking success, we're no longer putting it back

785
00:46:07,400 --> 00:46:07,920
Speaker 1: in the bottle.

786
00:46:08,040 --> 00:46:11,920
Speaker 2: No, no, no, yeah, thats As a deer hunter, I

787
00:46:11,960 --> 00:46:14,680
Speaker 2: think about it like like like this, okay, so the

788
00:46:14,719 --> 00:46:17,759
Speaker 2: agency is telling me I have to behave differently, Well,

789
00:46:17,760 --> 00:46:18,759
Speaker 2: why are they doing that?

790
00:46:18,960 --> 00:46:22,480
Speaker 4: To Mark's point, they're trying if the prevalence is low,

791
00:46:23,320 --> 00:46:27,759
Speaker 4: they're trying to keep it low because a deer that

792
00:46:28,120 --> 00:46:32,680
Speaker 4: contracts CWD is going to die, and so that is

793
00:46:32,719 --> 00:46:35,680
Speaker 4: an animal that is not as we're going to talk about,

794
00:46:35,760 --> 00:46:39,359
Speaker 4: They're not going to have the same reproductive potential as

795
00:46:39,440 --> 00:46:43,719
Speaker 4: other deer. They're going to have lower survival they are

796
00:46:43,760 --> 00:46:46,520
Speaker 4: not going to contribute to the population in the same

797
00:46:46,560 --> 00:46:51,400
Speaker 4: way as a CWD negative animal, and therefore they're not

798
00:46:51,640 --> 00:46:56,040
Speaker 4: part of that surplus, that harvestable surplus moving forward, particularly

799
00:46:56,080 --> 00:46:58,759
Speaker 4: if they contract the disease when they're young. And so

800
00:46:58,880 --> 00:47:02,040
Speaker 4: what the agencies are trying to do is keep CWD

801
00:47:02,280 --> 00:47:06,040
Speaker 4: from not being a relevant form of mortality, if that

802
00:47:06,160 --> 00:47:08,520
Speaker 4: makes sense. They're trying to keep it to where it's

803
00:47:08,560 --> 00:47:12,640
Speaker 4: really not relevant at a population scale, and if they

804
00:47:13,080 --> 00:47:15,759
Speaker 4: if they can do that, then that is in many

805
00:47:15,800 --> 00:47:19,200
Speaker 4: ways a success. Like to see to your point, you're

806
00:47:19,239 --> 00:47:22,080
Speaker 4: not putting it back in the bottle, but what you're

807
00:47:22,120 --> 00:47:25,080
Speaker 4: doing is you're minimizing the impacts of the disease at

808
00:47:25,080 --> 00:47:29,280
Speaker 4: a population scale so that you don't go to where

809
00:47:29,280 --> 00:47:32,160
Speaker 4: some of these populations are going, which is there is

810
00:47:32,280 --> 00:47:37,560
Speaker 4: no more harvestable surplus. The disease has affected the population

811
00:47:37,719 --> 00:47:41,040
Speaker 4: in a way the prevalence has gotten so high that

812
00:47:41,120 --> 00:47:43,000
Speaker 4: there is no more surplus there.

813
00:47:44,200 --> 00:47:48,960
Speaker 5: Any hunter harvest is going to have a population level effect.

814
00:47:49,520 --> 00:47:53,200
Speaker 4: You start getting to a point where harvest is truly additive,

815
00:47:53,640 --> 00:47:56,960
Speaker 4: Like you have such a significant percentage of animals that

816
00:47:57,000 --> 00:48:01,880
Speaker 4: are dying solely from CWD that when you start tacking

817
00:48:01,920 --> 00:48:04,840
Speaker 4: on harvest and predation and these things that just affect

818
00:48:04,840 --> 00:48:09,000
Speaker 4: deer populations, you've chained, you've tipped the pendulum to the

819
00:48:09,040 --> 00:48:13,600
Speaker 4: point where the lens doesn't look at all like it

820
00:48:13,640 --> 00:48:16,359
Speaker 4: looked if the prevalence was two percent. When you get

821
00:48:16,360 --> 00:48:19,319
Speaker 4: to twenty percent or thirty percent or even higher as

822
00:48:19,480 --> 00:48:22,359
Speaker 4: we see in some populations, that's what the agencies are

823
00:48:22,360 --> 00:48:24,480
Speaker 4: trying to do is keep it low enough to where

824
00:48:24,480 --> 00:48:25,320
Speaker 4: it's not relevant.

825
00:48:26,280 --> 00:48:29,000
Speaker 2: And that's that's scary what Mike is outlining there. But

826
00:48:29,080 --> 00:48:32,560
Speaker 2: I think it's really important for listeners to understand that

827
00:48:32,560 --> 00:48:36,960
Speaker 2: that that can happen at the same time, even in

828
00:48:37,000 --> 00:48:42,080
Speaker 2: the same state, in different areas as record harvests. You know,

829
00:48:42,360 --> 00:48:44,680
Speaker 2: everything you would want as a deer hunter is available

830
00:48:44,680 --> 00:48:47,239
Speaker 2: to you in one area and then in another. That

831
00:48:47,400 --> 00:48:51,080
Speaker 2: it's this focal nature of these very severe impacts and

832
00:48:51,160 --> 00:48:55,160
Speaker 2: that slow sort of expansion over time. And that's where

833
00:48:55,160 --> 00:48:58,120
Speaker 2: it's like that that can happen, you know, in the

834
00:48:58,160 --> 00:49:00,920
Speaker 2: same state or in the same general area for a

835
00:49:00,920 --> 00:49:04,480
Speaker 2: long time, where you have great opportunity, great abundance sort

836
00:49:04,520 --> 00:49:08,360
Speaker 2: of juxtaposed with this other scenario. It's hard to I

837
00:49:08,360 --> 00:49:11,440
Speaker 2: think that that's challenging for people because unless you've been

838
00:49:11,480 --> 00:49:14,000
Speaker 2: on the ground and you see sort of some of

839
00:49:14,000 --> 00:49:16,320
Speaker 2: the stuff Mike's talking about. You're on the landscape and

840
00:49:16,360 --> 00:49:20,240
Speaker 2: you see some of these these population level impacts of CWD.

841
00:49:20,840 --> 00:49:24,640
Speaker 2: You just hear about them. It's different from seeing it,

842
00:49:24,760 --> 00:49:28,120
Speaker 2: you know, and experiencing it. And so I think that's

843
00:49:28,160 --> 00:49:30,319
Speaker 2: a challenge for people because you know, you harvest the

844
00:49:30,320 --> 00:49:32,920
Speaker 2: buck and it tests positive. It was you know, it

845
00:49:33,000 --> 00:49:37,000
Speaker 2: was a healthy that, you know, totally normal looking deer.

846
00:49:37,480 --> 00:49:41,040
Speaker 2: That's your experience as a hunter with CWD, the real experience.

847
00:49:41,320 --> 00:49:43,719
Speaker 2: You hear all this stuff, but then your real experience

848
00:49:43,840 --> 00:49:46,200
Speaker 2: was that was a great looking deer. And to cow

849
00:49:46,280 --> 00:49:47,520
Speaker 2: it is all this noise about.

850
00:49:47,360 --> 00:49:49,360
Speaker 4: CW and to Cal's point, now I have to I

851
00:49:49,440 --> 00:49:52,920
Speaker 4: have to discard that deer, right, Yeah, that's extremely frustrating

852
00:49:52,960 --> 00:49:54,280
Speaker 4: it and it causes confusion.

853
00:49:54,400 --> 00:49:57,080
Speaker 5: Yeah, I shout to know at Doug Duran's place that

854
00:49:57,120 --> 00:49:59,520
Speaker 5: you were just like, like people stopped and looked at

855
00:49:59,560 --> 00:50:03,279
Speaker 5: it and they're like, that is a damn good looking animal, right,

856
00:50:03,360 --> 00:50:08,720
Speaker 5: You're just like, she's mature and just big and healthy

857
00:50:08,719 --> 00:50:12,040
Speaker 5: and always and she tested positive right for CWD, And

858
00:50:12,080 --> 00:50:13,600
Speaker 5: that was just a gut punch, you know.

859
00:50:13,760 --> 00:50:16,320
Speaker 4: And what Doug is experienced, and I spoke with Doug

860
00:50:17,000 --> 00:50:20,120
Speaker 4: prior to coming here, and what he's experiencing is very

861
00:50:20,160 --> 00:50:24,080
Speaker 4: comparable to what's going on in northwest Arkansas, where you've

862
00:50:24,120 --> 00:50:28,240
Speaker 4: got parts of the landscape where to Mark's point, where

863
00:50:28,480 --> 00:50:32,400
Speaker 4: you're in these focal centers, and you flip a coin

864
00:50:32,480 --> 00:50:36,360
Speaker 4: and every other deer is testing positive or more particularly

865
00:50:36,360 --> 00:50:40,959
Speaker 4: for bucks. And then in the next county over they're

866
00:50:41,040 --> 00:50:45,359
Speaker 4: testing positive and the prevalence is lower, but the penulum

867
00:50:45,440 --> 00:50:50,000
Speaker 4: hasn't swung far enough to start seeing these population level consequences.

868
00:50:50,239 --> 00:50:53,400
Speaker 4: You still see deer, you still harvest deer. They're not

869
00:50:53,480 --> 00:50:56,640
Speaker 4: all positive. And so the chatter at the local feed

870
00:50:56,719 --> 00:51:01,839
Speaker 4: store is different from this county to this because it's

871
00:51:01,920 --> 00:51:06,280
Speaker 4: taken thirty years for this disease to get to where

872
00:51:07,000 --> 00:51:10,080
Speaker 4: the snapshot that we as human beings are seeing right

873
00:51:10,120 --> 00:51:14,120
Speaker 4: now today, and we can't. I suck at this. I

874
00:51:14,239 --> 00:51:18,000
Speaker 4: think about today and tomorrow. That's just the way I'm wired.

875
00:51:18,239 --> 00:51:21,080
Speaker 4: It's hard for me to think about twenty years from now.

876
00:51:21,280 --> 00:51:24,160
Speaker 4: What you know, what's my camp in Louisiana going to

877
00:51:24,200 --> 00:51:28,560
Speaker 4: look like twenty years from now versus today? What's a

878
00:51:28,600 --> 00:51:33,040
Speaker 4: client's property going to look like thirty years from now? Now,

879
00:51:33,080 --> 00:51:36,520
Speaker 4: the prevalence you know in that area that he manages

880
00:51:36,560 --> 00:51:40,120
Speaker 4: that property is one percent, Well, what's it going to

881
00:51:40,120 --> 00:51:43,400
Speaker 4: look like in thirty years if we just throw our

882
00:51:43,400 --> 00:51:47,960
Speaker 4: hands up and do nothing versus if we try to

883
00:51:48,000 --> 00:51:53,480
Speaker 4: minimize transmission potential and try to do these things that

884
00:51:53,480 --> 00:51:59,200
Speaker 4: that logically would impact pre on accumulation in the environment.

885
00:52:00,640 --> 00:52:03,800
Speaker 4: That's hard to conceptualize and wrap your head around thirty

886
00:52:03,880 --> 00:52:05,680
Speaker 4: years from now or fifty years from now.

887
00:52:08,680 --> 00:52:12,759
Speaker 1: Among people that are among guys such as myself, that

888
00:52:12,840 --> 00:52:16,880
Speaker 1: are concerned about CWD, that want more information about CWD,

889
00:52:17,000 --> 00:52:19,040
Speaker 1: that want us to pay attention to CWD, I think

890
00:52:19,080 --> 00:52:22,120
Speaker 1: there's like these kind of camps we're talking about. Doug Durn,

891
00:52:22,160 --> 00:52:24,480
Speaker 1: Like Doug Durn and I sit in sort of different camps.

892
00:52:24,480 --> 00:52:28,640
Speaker 1: He gets frustrated with my camp because I have always

893
00:52:28,640 --> 00:52:31,840
Speaker 1: looked at it. I've always looked at it as primarily

894
00:52:33,000 --> 00:52:39,360
Speaker 1: a food safety issue. How heartbreaking culturally devastating for American

895
00:52:39,440 --> 00:52:43,680
Speaker 1: hunters it would be if all of a sudden, a

896
00:52:43,760 --> 00:52:48,320
Speaker 1: deer wasn't like a good source of venison, wasn't something

897
00:52:48,360 --> 00:52:52,480
Speaker 1: people were excited to see on their property wasn't something

898
00:52:52,520 --> 00:52:55,160
Speaker 1: that we celebrated, right, But all of a sudden, they

899
00:52:55,200 --> 00:52:59,399
Speaker 1: were like the way you'd look at a rat, like, ah,

900
00:52:59,520 --> 00:53:02,839
Speaker 1: get that out of here, shoot like shoot the deer.

901
00:53:02,880 --> 00:53:05,399
Speaker 1: There's a deer in the yard right before we all

902
00:53:05,400 --> 00:53:07,719
Speaker 1: get sick. Like that, it would just what a deer

903
00:53:07,840 --> 00:53:11,600
Speaker 1: stands forward change from a human safety standpoint, that haunts

904
00:53:11,640 --> 00:53:16,719
Speaker 1: me and my own the diet that my family, which

905
00:53:16,800 --> 00:53:20,360
Speaker 1: is like me too, like the bulk of the protein

906
00:53:20,400 --> 00:53:23,319
Speaker 1: we take in is from servants. It'd be devastating, it'd

907
00:53:23,320 --> 00:53:28,479
Speaker 1: be heartbreaking. I've looked at it like that. Doug looks

908
00:53:28,480 --> 00:53:31,759
Speaker 1: at it one just animal welfare, meaning you know, he

909
00:53:32,000 --> 00:53:36,960
Speaker 1: grew up with a farm background. Sick animals equals no

910
00:53:37,080 --> 00:53:41,600
Speaker 1: good okay, So he just instinctively doesn't like the thought

911
00:53:41,600 --> 00:53:43,880
Speaker 1: of sick animals. Loves deer, doesn't like the thought of

912
00:53:43,920 --> 00:53:48,000
Speaker 1: sick deer, so that turns them on two. He's often said,

913
00:53:48,800 --> 00:53:51,000
Speaker 1: we will get to a point, and he reads more

914
00:53:51,040 --> 00:53:53,360
Speaker 1: and studies more than I do, we will get to

915
00:53:53,400 --> 00:53:58,560
Speaker 1: a point where this does impact deer hunting. He feels,

916
00:53:58,640 --> 00:54:00,919
Speaker 1: we'll get to a point where we don't see big

917
00:54:00,920 --> 00:54:04,840
Speaker 1: bucks anymore. And it used to be kind of like

918
00:54:04,920 --> 00:54:07,400
Speaker 1: I felt like it was like he was predicting or

919
00:54:08,440 --> 00:54:11,839
Speaker 1: or you know, prophesizing or trying to crystal ball it, right.

920
00:54:12,400 --> 00:54:15,000
Speaker 1: But that's like two different things, and I think there's

921
00:54:15,000 --> 00:54:17,160
Speaker 1: probably a lot of people to hold both those at

922
00:54:17,160 --> 00:54:19,080
Speaker 1: the same time, where they're like very concerned with food

923
00:54:19,120 --> 00:54:22,719
Speaker 1: safety and then very concerned down the road of are

924
00:54:22,719 --> 00:54:25,439
Speaker 1: we going to have big white tails? Yeah, we're still

925
00:54:25,440 --> 00:54:26,959
Speaker 1: gonna be able to grow seven year old bucks.

926
00:54:27,080 --> 00:54:30,400
Speaker 4: I also think part of Doug's frustration is what I

927
00:54:30,520 --> 00:54:34,920
Speaker 4: see with with private landowners all over the South, is

928
00:54:34,960 --> 00:54:39,239
Speaker 4: that they buy these recreational properties. They put so much

929
00:54:39,280 --> 00:54:44,879
Speaker 4: of themselves and their resources into creating this recreational opportunity

930
00:54:44,960 --> 00:54:47,520
Speaker 4: for them and their families. They want their kids and

931
00:54:47,560 --> 00:54:50,880
Speaker 4: their grandkids to come experience and to have this legacy

932
00:54:50,880 --> 00:54:55,960
Speaker 4: of all and they've got this grand plan. I'm envisioning

933
00:54:55,960 --> 00:54:58,400
Speaker 4: one of my clients at seventy two, he has this

934
00:54:59,040 --> 00:55:03,880
Speaker 4: like zat actually what he's wanted forever. He finally worked

935
00:55:04,080 --> 00:55:07,360
Speaker 4: his ass off enough to be able to afford this property,

936
00:55:07,719 --> 00:55:10,799
Speaker 4: to put the resources on it. He hires a biologist.

937
00:55:10,880 --> 00:55:14,280
Speaker 4: He does these things, and his dear herd is terrific

938
00:55:15,239 --> 00:55:21,800
Speaker 4: and the thought of that being undermined by this disease

939
00:55:22,280 --> 00:55:27,160
Speaker 4: is something that causes him incredible frustration and angst and

940
00:55:27,239 --> 00:55:32,120
Speaker 4: because and then having clients that own properties in CWDS owns,

941
00:55:32,560 --> 00:55:36,640
Speaker 4: that is what they tell me. They're like, I'm having

942
00:55:36,680 --> 00:55:40,759
Speaker 4: a hard time thinking through what the future is going

943
00:55:40,800 --> 00:55:46,640
Speaker 4: to look like because I'm sixty and I want my grandkids.

944
00:55:46,640 --> 00:55:51,120
Speaker 4: You know, I have two new grandsons, and this is theirs.

945
00:55:51,600 --> 00:55:55,360
Speaker 4: I've been working all these years to create this opportunity

946
00:55:55,440 --> 00:55:59,760
Speaker 4: for them so that I can facilitate the next generation

947
00:55:59,800 --> 00:56:03,600
Speaker 4: of hunters and land managers and conservationists. And now you're

948
00:56:03,640 --> 00:56:06,200
Speaker 4: telling me that there's a chance that could be undermined

949
00:56:06,239 --> 00:56:09,960
Speaker 4: by this disease, and that is incredibly frustrating and upsetting

950
00:56:10,000 --> 00:56:13,160
Speaker 4: for them. That's what I hear, Not so much the food,

951
00:56:13,520 --> 00:56:19,400
Speaker 4: although that is incredibly frustrating. Is the legacy, the property legacy,

952
00:56:19,640 --> 00:56:24,640
Speaker 4: the generational impact that this disease could have on land management,

953
00:56:25,040 --> 00:56:29,080
Speaker 4: on land value, on the deer hunting, you know, fraternity.

954
00:56:29,680 --> 00:56:33,120
Speaker 4: That's what I hear with the conversations that I have.

955
00:56:35,760 --> 00:56:39,520
Speaker 1: Okay, so is the guy that's worried, how warranted is

956
00:56:39,560 --> 00:56:43,319
Speaker 1: someone who's worried about the future big buck potential in

957
00:56:43,360 --> 00:56:43,880
Speaker 1: their area.

958
00:56:44,880 --> 00:56:47,800
Speaker 4: Well, there's no question like what we're seeing with these

959
00:56:48,280 --> 00:56:53,440
Speaker 4: with the research that is occurring in populations with high prevalence,

960
00:56:55,040 --> 00:56:58,560
Speaker 4: the age structure which Doug is seeing in his area

961
00:56:58,600 --> 00:57:03,839
Speaker 4: as well, the age structures progressively younger, meaning that you're

962
00:57:03,960 --> 00:57:08,840
Speaker 4: just not you're not carrying older males over into the

963
00:57:08,920 --> 00:57:11,440
Speaker 4: five and six year old age class. And so I

964
00:57:11,480 --> 00:57:15,040
Speaker 4: know we're going to talk about Arkansas, but so what

965
00:57:15,120 --> 00:57:18,840
Speaker 4: we found in Arkansas which we'll circle back to, but

966
00:57:19,520 --> 00:57:21,520
Speaker 4: you know, we found that fifty percent of all two

967
00:57:21,600 --> 00:57:24,640
Speaker 4: and a half year old males tested positive, more than

968
00:57:24,680 --> 00:57:26,840
Speaker 4: fifty percent of three and a half year old males.

969
00:57:27,520 --> 00:57:30,760
Speaker 4: And so if you look across the South, a lot

970
00:57:30,760 --> 00:57:33,120
Speaker 4: of the buck harvest is comprised of three and a

971
00:57:33,160 --> 00:57:37,200
Speaker 4: half year old males. So if you're in a you know,

972
00:57:37,240 --> 00:57:40,760
Speaker 4: you think about this population in Arkansas super high prevalence,

973
00:57:40,760 --> 00:57:43,760
Speaker 4: which we'll talk about, most of your bucks by the

974
00:57:43,800 --> 00:57:47,960
Speaker 4: time they're three have the disease. Well over sixty percent

975
00:57:48,040 --> 00:57:51,480
Speaker 4: have the disease when they're four, and if half of

976
00:57:51,520 --> 00:57:54,880
Speaker 4: them have it at two, they're not surviving past four.

977
00:57:55,840 --> 00:57:59,080
Speaker 4: And so you know, I'm thinking that.

978
00:57:58,880 --> 00:58:02,000
Speaker 5: That timeline is so crucial to these arguments as well.

979
00:58:02,080 --> 00:58:04,360
Speaker 1: Right, it's like, sure, because he's a jumbo at five

980
00:58:04,440 --> 00:58:04,840
Speaker 1: or six.

981
00:58:05,440 --> 00:58:08,920
Speaker 4: Well, I mean in my world working with landowners, you know,

982
00:58:09,520 --> 00:58:13,600
Speaker 4: we're not we're not harvesting at least southern white tails.

983
00:58:13,600 --> 00:58:17,040
Speaker 4: We're not. We're not harvesting many of our bucks until

984
00:58:17,080 --> 00:58:20,960
Speaker 4: they're at least four and most we're going to five.

985
00:58:21,840 --> 00:58:26,960
Speaker 4: And so in that vein, you know, under that scenario

986
00:58:27,120 --> 00:58:30,760
Speaker 4: I just described, which is on the ground in northwest Arkansas,

987
00:58:31,160 --> 00:58:34,480
Speaker 4: you're not going to have five and six year old bucks.

988
00:58:34,560 --> 00:58:37,640
Speaker 5: And well, I guess I bring up that timeline too,

989
00:58:37,680 --> 00:58:39,680
Speaker 5: because you do hear in certain areas of the country

990
00:58:39,720 --> 00:58:41,600
Speaker 5: they're like, well, who cares our beer don't live till

991
00:58:41,640 --> 00:58:42,240
Speaker 5: six anyway?

992
00:58:42,400 --> 00:58:43,200
Speaker 4: Right, right? Right?

993
00:58:43,240 --> 00:58:46,120
Speaker 5: And so if they're if they're showing signs of the

994
00:58:46,160 --> 00:58:50,280
Speaker 5: disease at six, what is it again to me? Like

995
00:58:50,720 --> 00:58:53,360
Speaker 5: why is this a backyard issue to me? And how

996
00:58:53,360 --> 00:58:56,840
Speaker 5: I hunt and managed here? Right? But you're saying that

997
00:58:57,720 --> 00:59:01,560
Speaker 5: in it progresses to where when by the time they're

998
00:59:01,600 --> 00:59:04,920
Speaker 5: showing signs of the disease, that that gets younger.

999
00:59:06,360 --> 00:59:07,440
Speaker 4: Yeah as well?

1000
00:59:07,520 --> 00:59:12,000
Speaker 2: Right, Another thing is the farther we keep talking about

1001
00:59:12,000 --> 00:59:15,480
Speaker 2: that time scale, right, and the farther down that path

1002
00:59:15,520 --> 00:59:18,040
Speaker 2: you get and sort of the percentage of animals and

1003
00:59:18,080 --> 00:59:23,080
Speaker 2: infected in the population is that increases. The age at

1004
00:59:23,120 --> 00:59:27,880
Speaker 2: which those animals get infected tends to be earlier in life.

1005
00:59:28,320 --> 00:59:31,479
Speaker 2: And I was just talking with Mike about this this morning.

1006
00:59:31,520 --> 00:59:36,960
Speaker 2: There's a particular spot in the Arkansas study site where

1007
00:59:37,720 --> 00:59:40,040
Speaker 2: the prevalence is very high. We suspect it's been on

1008
00:59:40,040 --> 00:59:43,200
Speaker 2: the landscape for the longest and we've got you know,

1009
00:59:43,320 --> 00:59:47,120
Speaker 2: all these collar deer. We you know that we investigated

1010
00:59:47,160 --> 00:59:50,440
Speaker 2: the you know, the death site. You know, full field

1011
00:59:50,480 --> 00:59:53,520
Speaker 2: nee cropsies, lots of photos, you know, sent back, lots

1012
00:59:53,520 --> 00:59:56,080
Speaker 2: of laboratory analysis to sort of sort of understand why

1013
00:59:56,080 --> 01:00:00,560
Speaker 2: these deer died. Individual causes of death. So there's a

1014
01:00:00,680 --> 01:00:04,800
Speaker 2: there's a particular buck that was that was captured in

1015
01:00:04,840 --> 01:00:07,360
Speaker 2: this area. He was about eight or nine months at

1016
01:00:07,360 --> 01:00:09,840
Speaker 2: the time of capture, just this kind of a normal,

1017
01:00:09,920 --> 01:00:14,960
Speaker 2: average looking body weight. Did a rectal biopsy he was

1018
01:00:16,080 --> 01:00:19,120
Speaker 2: So this is a common diagnostic test that you could

1019
01:00:19,240 --> 01:00:22,320
Speaker 2: use for CWD. You take a little snip of sounds

1020
01:00:22,400 --> 01:00:25,440
Speaker 2: kind of weird, but like of the rectal like tissue,

1021
01:00:26,440 --> 01:00:28,840
Speaker 2: it was positive, right, And so.

1022
01:00:29,080 --> 01:00:32,760
Speaker 1: How did you get this deer in your hands, tranquilise it.

1023
01:00:33,360 --> 01:00:34,840
Speaker 4: Yeah, so let you want.

1024
01:00:36,200 --> 01:00:36,760
Speaker 2: Visit it later.

1025
01:00:36,840 --> 01:00:37,440
Speaker 4: Let's cover this.

1026
01:00:37,480 --> 01:00:38,280
Speaker 2: We'll come back to that.

1027
01:00:38,600 --> 01:00:39,640
Speaker 5: Yeah, that's a big deal.

1028
01:00:39,720 --> 01:00:41,120
Speaker 2: I'll come back to the end of his life.

1029
01:00:41,240 --> 01:00:43,440
Speaker 4: Okay, yeah, yeah. So what we did in Arkansas is

1030
01:00:43,720 --> 01:00:49,040
Speaker 4: so Arkansas Game Fish Commission first detected CWD in twenty

1031
01:00:49,120 --> 01:00:52,560
Speaker 4: fifteen in an elk. They subsequently detected it in a

1032
01:00:52,560 --> 01:00:56,200
Speaker 4: white tail in twenty sixteen far milk. No, this was

1033
01:00:56,200 --> 01:00:59,960
Speaker 4: a wild wow though, and so they as an age

1034
01:01:00,000 --> 01:01:05,840
Speaker 4: and decided to submit an RFP Request for Proposals a

1035
01:01:05,840 --> 01:01:11,840
Speaker 4: few years later to solicit proposals from researchers to try

1036
01:01:11,880 --> 01:01:16,600
Speaker 4: to understand as soon as they started testing. Once these

1037
01:01:16,600 --> 01:01:21,040
Speaker 4: two positives occurred, they realized their prevalence was well over

1038
01:01:21,080 --> 01:01:23,120
Speaker 4: twenty percent and so.

1039
01:01:23,000 --> 01:01:24,600
Speaker 1: And that's from Hunter's submissions.

1040
01:01:24,680 --> 01:01:29,400
Speaker 4: Yes, and so suddenly they went a while, we need

1041
01:01:29,440 --> 01:01:31,200
Speaker 4: to understand where we're at, what's going on.

1042
01:01:31,360 --> 01:01:35,880
Speaker 1: So they found one, started testing promptly, started taking a

1043
01:01:35,920 --> 01:01:38,320
Speaker 1: lot of samples. Yep, people turn in their deer head

1044
01:01:39,240 --> 01:01:39,760
Speaker 1: some of it.

1045
01:01:39,680 --> 01:01:43,240
Speaker 2: Was agency collection too, and that initial response their goal

1046
01:01:43,360 --> 01:01:46,680
Speaker 2: was to shoot they basically so they had that positive

1047
01:01:46,680 --> 01:01:48,959
Speaker 2: elk and They also had a positive white tailed deer

1048
01:01:49,120 --> 01:01:52,280
Speaker 2: that was clinically affected. So they kind of drew big

1049
01:01:52,320 --> 01:01:55,240
Speaker 2: circles around these used them together, and their goal was, right,

1050
01:01:55,280 --> 01:01:57,200
Speaker 2: We're going to go shoot three hundred deer within this

1051
01:01:57,280 --> 01:01:59,919
Speaker 2: area because we need to understand what we're facing.

1052
01:02:00,080 --> 01:02:02,280
Speaker 5: Where that area. Is that a lot?

1053
01:02:02,880 --> 01:02:05,200
Speaker 2: It's a lot of deer. Yeah, it had been more

1054
01:02:05,200 --> 01:02:07,919
Speaker 2: than they had sampled there previously. Yeah, but they didn't

1055
01:02:07,920 --> 01:02:10,040
Speaker 2: even get to three hundred because by two sixty they

1056
01:02:10,040 --> 01:02:13,160
Speaker 2: saw that they were facing this twenty percent plus prevalence. Yeah,

1057
01:02:13,160 --> 01:02:14,160
Speaker 2: so they're like, okay, aout.

1058
01:02:14,240 --> 01:02:16,640
Speaker 1: They wanted to go get an immediate snap shot. Yes,

1059
01:02:16,840 --> 01:02:20,880
Speaker 1: and their immediate snapshot was like one in five deer, Yeah,

1060
01:02:21,080 --> 01:02:22,760
Speaker 1: are positive for chronic waste and disease.

1061
01:02:22,800 --> 01:02:24,840
Speaker 2: Yah. It was a gut punch.

1062
01:02:24,680 --> 01:02:27,760
Speaker 4: Yeah, and Mark was living that. I was not involved

1063
01:02:27,800 --> 01:02:31,840
Speaker 4: at that time. I was hearing about this peripherally. And

1064
01:02:31,880 --> 01:02:35,680
Speaker 4: then I got this email with a request saying that

1065
01:02:35,800 --> 01:02:38,680
Speaker 4: we would like you, among others. It was sent to

1066
01:02:38,720 --> 01:02:41,800
Speaker 4: a number of researchers, We'd like you to consider putting

1067
01:02:41,800 --> 01:02:45,240
Speaker 4: together a research project. Excuse me, they would answer these

1068
01:02:45,320 --> 01:02:50,600
Speaker 4: relevant questions we have and so what I did, excuse me,

1069
01:02:50,760 --> 01:02:54,000
Speaker 4: what I did was I reached out to Mark and

1070
01:02:54,520 --> 01:02:58,280
Speaker 4: colleagues at the University of Georgia. We reached out collectively

1071
01:02:58,360 --> 01:03:01,800
Speaker 4: to colleagues at Colorado State at the pre owned Research

1072
01:03:01,840 --> 01:03:05,040
Speaker 4: Center there, and we put together this this very large

1073
01:03:05,160 --> 01:03:09,440
Speaker 4: five year study to try to help the agency do

1074
01:03:09,640 --> 01:03:15,360
Speaker 4: everything from understand abundance or deer density UH prevalence rates,

1075
01:03:15,800 --> 01:03:19,680
Speaker 4: to look at behavior of CWD positive and negative deer,

1076
01:03:20,600 --> 01:03:25,920
Speaker 4: to look at to survival and habitat use, and all

1077
01:03:25,960 --> 01:03:28,440
Speaker 4: these things that you would get from just capturing and

1078
01:03:28,480 --> 01:03:33,240
Speaker 4: collaring deer. And then we designed this study plan to

1079
01:03:33,280 --> 01:03:37,320
Speaker 4: come back at the end and to also collect coll

1080
01:03:37,520 --> 01:03:39,720
Speaker 4: animals that were radio marked at the end of the

1081
01:03:39,760 --> 01:03:43,080
Speaker 4: study to try to figure out if their disease trying

1082
01:03:43,200 --> 01:03:47,479
Speaker 4: if their disease you know, prevalent I'm sorry, if their

1083
01:03:47,520 --> 01:03:50,440
Speaker 4: positive or negative would change at the end, you know,

1084
01:03:50,480 --> 01:03:53,160
Speaker 4: by the time the end of the study occurred. So

1085
01:03:53,200 --> 01:03:57,880
Speaker 4: what we did is we we captured and GPS collared

1086
01:03:58,600 --> 01:04:02,520
Speaker 4: hundreds of deer. We ended up trap we would dart them,

1087
01:04:02,720 --> 01:04:06,440
Speaker 4: rocketing at them and dropping at them. And what we

1088
01:04:06,440 --> 01:04:09,600
Speaker 4: were trying to do is put GPS collars on adults

1089
01:04:10,280 --> 01:04:13,720
Speaker 4: and we put vaginal implant transmitters in doors, which are

1090
01:04:13,760 --> 01:04:17,720
Speaker 4: these as you know, these transmitters that when they give birth,

1091
01:04:17,760 --> 01:04:20,840
Speaker 4: it kicks the transmitter out, alerts the researcher that there's

1092
01:04:20,880 --> 01:04:22,640
Speaker 4: fawns on the ground. We would then go in and

1093
01:04:22,680 --> 01:04:27,160
Speaker 4: collar the fawns at every capture. Of course, to Mark's point,

1094
01:04:27,160 --> 01:04:30,000
Speaker 4: which he can explain, we would take a rectal biopsy

1095
01:04:30,080 --> 01:04:33,920
Speaker 4: for CWD testing. We would then track these deer. We

1096
01:04:34,400 --> 01:04:39,080
Speaker 4: programmed the callers to have battery life over several years.

1097
01:04:39,520 --> 01:04:42,440
Speaker 4: Because we were interested in obviously studying the deer for

1098
01:04:42,720 --> 01:04:46,280
Speaker 4: as long a term, you know, timeframe as we could,

1099
01:04:47,360 --> 01:04:50,040
Speaker 4: we tried to recapture as many deer as we possibly

1100
01:04:50,080 --> 01:04:52,360
Speaker 4: could from year to year so that we could repeatedly

1101
01:04:52,440 --> 01:04:57,200
Speaker 4: test them. We set up camera arrays all over the

1102
01:04:57,200 --> 01:05:01,400
Speaker 4: study site. And the way the initial old study site

1103
01:05:01,520 --> 01:05:05,800
Speaker 4: came to fruition is through the testing that Arkansas game

1104
01:05:05,880 --> 01:05:09,720
Speaker 4: Fish had already done. They had evidence to show that

1105
01:05:09,800 --> 01:05:13,600
Speaker 4: there was a progression of prevalence from higher to lower

1106
01:05:13,640 --> 01:05:16,680
Speaker 4: as you went from west to east. So we set

1107
01:05:16,720 --> 01:05:20,560
Speaker 4: our study design up to where we captured that variation.

1108
01:05:20,800 --> 01:05:23,840
Speaker 4: We had. We had sampling in the highest prep what

1109
01:05:23,960 --> 01:05:25,920
Speaker 4: appeared to be the highest prevalence all the way to

1110
01:05:25,960 --> 01:05:29,280
Speaker 4: the lowest prevalence, and we captured deer and put camera

1111
01:05:29,440 --> 01:05:33,120
Speaker 4: arrays and did all of this work the same across

1112
01:05:33,320 --> 01:05:38,200
Speaker 4: all kind of three study sites that that span from

1113
01:05:38,240 --> 01:05:42,040
Speaker 4: high prevalence to lower prevalence certainly not low. And we

1114
01:05:42,080 --> 01:05:44,800
Speaker 4: did this for for four years, and then we had

1115
01:05:45,080 --> 01:05:47,240
Speaker 4: a fifth year where we went in and tried to

1116
01:05:47,240 --> 01:05:53,600
Speaker 4: collect marked animals off of public lands at the same time,

1117
01:05:53,840 --> 01:05:56,440
Speaker 4: which Mark can talk about because he saw this with

1118
01:05:56,520 --> 01:06:00,320
Speaker 4: his own eyes. He you know, where deer dying while

1119
01:06:00,600 --> 01:06:02,320
Speaker 4: this study is ongoing.

1120
01:06:02,960 --> 01:06:05,040
Speaker 1: Deer with your collars on them, yes, are.

1121
01:06:05,040 --> 01:06:08,680
Speaker 4: Dying and we're recovering those animals, and we are field

1122
01:06:08,760 --> 01:06:12,800
Speaker 4: nee crop seeing and beyond we are testing them for CWD,

1123
01:06:13,560 --> 01:06:17,600
Speaker 4: and we are seeing that this disease is becoming more

1124
01:06:17,640 --> 01:06:22,600
Speaker 4: prevalent right before our eyes. And so we did this.

1125
01:06:22,760 --> 01:06:28,000
Speaker 4: We recently provided the findings to the agency. The penultimate

1126
01:06:28,040 --> 01:06:31,080
Speaker 4: piece of information from this study was a population model,

1127
01:06:31,200 --> 01:06:34,000
Speaker 4: an integrated population model, where we took all of this

1128
01:06:34,160 --> 01:06:37,360
Speaker 4: data and we used it to model to tell the

1129
01:06:37,400 --> 01:06:41,920
Speaker 4: agency where are you at on that curve and more importantly,

1130
01:06:42,120 --> 01:06:45,000
Speaker 4: where's the what's the future for you? Given where you

1131
01:06:45,040 --> 01:06:47,560
Speaker 4: are on the curve? What does the next ten years

1132
01:06:47,640 --> 01:06:50,760
Speaker 4: or twenty years look like for you as an agency

1133
01:06:50,800 --> 01:06:56,000
Speaker 4: relative to this population. And what we realized pretty quickly

1134
01:06:56,120 --> 01:06:59,200
Speaker 4: is we were we as a as a research group

1135
01:06:59,240 --> 01:07:02,840
Speaker 4: and the agency were farther along on that curve than

1136
01:07:02,880 --> 01:07:08,440
Speaker 4: we thought. And so as of twenty twenty five, the

1137
01:07:08,520 --> 01:07:13,720
Speaker 4: prevalence rate is about fifty percent in that part of Arkansas,

1138
01:07:13,800 --> 01:07:17,360
Speaker 4: about thirty five percent for doze in about sixty eight

1139
01:07:17,400 --> 01:07:22,920
Speaker 4: percent for bucks, So most bucks have CWD in that area,

1140
01:07:23,440 --> 01:07:27,680
Speaker 4: and so incredibly high prevalence, which is that's context. The

1141
01:07:27,760 --> 01:07:31,280
Speaker 4: listener needs to understand that CWD had been on this

1142
01:07:31,440 --> 01:07:35,000
Speaker 4: landscape for years before it was ever detected, and so

1143
01:07:35,160 --> 01:07:41,840
Speaker 4: this population had gone quote unquote unmanaged, just normal harvest

1144
01:07:41,920 --> 01:07:45,000
Speaker 4: regulations that the state would implement. There were antle point

1145
01:07:45,040 --> 01:07:49,320
Speaker 4: restrictions in place, trying to improve aid structure and allow

1146
01:07:49,400 --> 01:07:52,560
Speaker 4: animals to grow to be older. And so what was

1147
01:07:52,640 --> 01:07:57,360
Speaker 4: occurring is for decades, prevalence was just slowly creeping up

1148
01:07:57,400 --> 01:08:01,760
Speaker 4: and then suddenly and animals detec acted positive because they're clinical,

1149
01:08:02,600 --> 01:08:06,200
Speaker 4: and the agency realizes, oh, wow, we're farther along.

1150
01:08:06,800 --> 01:08:08,479
Speaker 5: Sorry, when you get to say clinical, are you saying

1151
01:08:08,480 --> 01:08:10,320
Speaker 5: like it visually is showing signs of.

1152
01:08:10,520 --> 01:08:12,160
Speaker 1: A sick deer shows up someone's yard.

1153
01:08:12,840 --> 01:08:17,400
Speaker 4: Yes, sorry, yeah, And that's not something you know that market.

1154
01:08:17,479 --> 01:08:19,320
Speaker 4: That's something Mark and I talk about a lot. Is

1155
01:08:19,520 --> 01:08:24,599
Speaker 4: these clinical animals. You're not likely to see this unlike

1156
01:08:24,680 --> 01:08:28,720
Speaker 4: a heemorrhagic disease outbreak where you've got animals laying everywhere.

1157
01:08:29,400 --> 01:08:32,280
Speaker 4: As we saw with our with our movement data, these

1158
01:08:32,320 --> 01:08:37,200
Speaker 4: animals as they're becoming positive as there as the disease

1159
01:08:37,280 --> 01:08:40,240
Speaker 4: is progressing. So I'll give you a scenario. You catch

1160
01:08:40,280 --> 01:08:43,599
Speaker 4: a two year old buck, you put a radio collar

1161
01:08:43,640 --> 01:08:47,759
Speaker 4: on him, and he tests positive. He looks fine, everything,

1162
01:08:47,840 --> 01:08:51,240
Speaker 4: he looks great, but he he tests positive. Now we're

1163
01:08:51,320 --> 01:08:55,080
Speaker 4: tracking his movements over the next two years as the

1164
01:08:55,120 --> 01:09:01,800
Speaker 4: disease progresses and he starts becoming comprom mist. And so

1165
01:09:01,880 --> 01:09:05,280
Speaker 4: what we saw is they don't behave like uninfected deer.

1166
01:09:06,000 --> 01:09:12,080
Speaker 4: They are less vigilant, they move differently. They will expand

1167
01:09:12,120 --> 01:09:15,320
Speaker 4: their home range. They which is interesting if you think

1168
01:09:15,320 --> 01:09:18,679
Speaker 4: about pre on transmission, that they're actually expanding their area

1169
01:09:19,280 --> 01:09:21,720
Speaker 4: that puts them in contact with other animals that they

1170
01:09:21,720 --> 01:09:21,960
Speaker 4: may know.

1171
01:09:22,000 --> 01:09:24,040
Speaker 1: Why are they doing that? Don't know if they're sick, I.

1172
01:09:24,080 --> 01:09:26,240
Speaker 5: Don't know the preon wanting to spread. It's like a

1173
01:09:26,280 --> 01:09:27,360
Speaker 5: sci fi magazine.

1174
01:09:27,560 --> 01:09:30,559
Speaker 4: It's hard to say. I mean, I would think that

1175
01:09:30,600 --> 01:09:33,360
Speaker 4: they would honker down. Oh sure, man, But we didn't

1176
01:09:33,400 --> 01:09:36,439
Speaker 4: see that. We saw the opposite, that they actually expanded

1177
01:09:36,479 --> 01:09:37,320
Speaker 4: their home range.

1178
01:09:37,680 --> 01:09:39,519
Speaker 1: And you should have not just like its function of

1179
01:09:39,520 --> 01:09:40,200
Speaker 1: his age.

1180
01:09:42,560 --> 01:09:46,040
Speaker 4: No, no, I mean, so we we control for.

1181
01:09:46,040 --> 01:09:48,360
Speaker 1: Age, and our got all kinds of other ones that

1182
01:09:48,400 --> 01:09:49,040
Speaker 1: aren't positive.

1183
01:09:51,000 --> 01:09:55,639
Speaker 4: We also saw that, interestingly enough, they started interacting as

1184
01:09:55,680 --> 01:09:59,679
Speaker 4: they became positive. They started interacting with other deer differently,

1185
01:10:00,400 --> 01:10:02,960
Speaker 4: and they were much more likely to interact with another

1186
01:10:03,080 --> 01:10:07,640
Speaker 4: positive deer. And so they start changing kind because.

1187
01:10:07,360 --> 01:10:10,799
Speaker 5: Of the change in their behaviors and movements. Maybe maybe

1188
01:10:10,960 --> 01:10:15,800
Speaker 5: they're they're less likely to run with uh.

1189
01:10:15,280 --> 01:10:18,639
Speaker 4: They're more likely to be around another deer, which makes sense.

1190
01:10:19,000 --> 01:10:20,719
Speaker 1: Why does that make sense? He's sick.

1191
01:10:22,280 --> 01:10:23,719
Speaker 5: They're letting them do the thinking.

1192
01:10:24,040 --> 01:10:26,200
Speaker 4: Maybe I don't yeah, I mean, I don't. I don't

1193
01:10:26,200 --> 01:10:28,760
Speaker 4: know the I mean, could it be could it be

1194
01:10:28,800 --> 01:10:32,599
Speaker 4: a combination of the change in vigilance behavior with Hey,

1195
01:10:32,640 --> 01:10:37,800
Speaker 4: I don't, I'm not. Things just aren't clicking with me. So,

1196
01:10:37,920 --> 01:10:40,800
Speaker 4: for instance, we had a you remember that polar vortex.

1197
01:10:41,400 --> 01:10:45,320
Speaker 4: We had a severe weather outbreak? Was that the first

1198
01:10:45,400 --> 01:10:50,240
Speaker 4: year or the second year we had a couple Yeah,

1199
01:10:51,600 --> 01:10:56,080
Speaker 4: so we had positive deer that just laid down in

1200
01:10:56,160 --> 01:10:59,960
Speaker 4: the woods and died like and they didn't seek refuge

1201
01:11:00,040 --> 01:11:02,519
Speaker 4: at all, got it? And so there's something that that.

1202
01:11:02,560 --> 01:11:04,759
Speaker 5: Where the term stiff as a pecker comes from.

1203
01:11:05,200 --> 01:11:06,840
Speaker 1: I don't know, but you know this. You remember that

1204
01:11:06,880 --> 01:11:10,040
Speaker 1: massive cold snap we went down to hunt squirrels and

1205
01:11:10,160 --> 01:11:13,879
Speaker 1: out in the woods. I mean it was like national

1206
01:11:13,920 --> 01:11:16,680
Speaker 1: news cold, yeah, freezing everything to death. But out in

1207
01:11:16,720 --> 01:11:21,240
Speaker 1: the woods all over the place, it's just birds totally fine,

1208
01:11:21,479 --> 01:11:27,120
Speaker 1: except dead underground, not a feather ruffle, freezing to death

1209
01:11:27,160 --> 01:11:28,920
Speaker 1: in the trees, falling off the ground, I mean, we

1210
01:11:29,240 --> 01:11:34,440
Speaker 1: like all day long. So there's Clay's whole bamboo patch.

1211
01:11:34,400 --> 01:11:37,600
Speaker 4: And something that you know, their behavior is becoming compromised

1212
01:11:37,640 --> 01:11:39,320
Speaker 4: in some way, which makes sense.

1213
01:11:39,160 --> 01:11:42,400
Speaker 1: With yeah that like that clicks Yeah, like that click

1214
01:11:42,479 --> 01:11:44,760
Speaker 1: did it? Did it did? It doesn't have the wherewithal

1215
01:11:44,840 --> 01:11:46,400
Speaker 1: to do what it needs to stay alive. But just

1216
01:11:46,439 --> 01:11:50,559
Speaker 1: like increase social unless that's somehow was attributed to its

1217
01:11:50,760 --> 01:11:54,200
Speaker 1: lack of vigilance or it's paranoia.

1218
01:11:53,720 --> 01:11:56,160
Speaker 4: Is some of that some of that we couldn't possibly

1219
01:11:56,240 --> 01:11:59,439
Speaker 4: understand what this resolution of the data we have because

1220
01:11:59,520 --> 01:12:03,280
Speaker 4: our vigil and data are coming from cameras from observing animals,

1221
01:12:03,400 --> 01:12:06,679
Speaker 4: you know, head up, head down. The spatial and interaction

1222
01:12:06,840 --> 01:12:09,720
Speaker 4: data are coming from GPS locations, and we know we

1223
01:12:09,760 --> 01:12:13,479
Speaker 4: don't have all deer marked, right, so there's inherent bias there.

1224
01:12:13,720 --> 01:12:15,800
Speaker 1: Well, I can tell you a sick kid is more

1225
01:12:15,920 --> 01:12:17,719
Speaker 1: likely to end up in his mom and dad's bet.

1226
01:12:18,120 --> 01:12:18,400
Speaker 4: Yeah.

1227
01:12:18,760 --> 01:12:20,360
Speaker 1: Yeah, I don't know why.

1228
01:12:20,439 --> 01:12:26,000
Speaker 5: In a long time, uh, marketing communications folks for the

1229
01:12:26,040 --> 01:12:30,679
Speaker 5: state agency saying like, are you sure you want to

1230
01:12:30,720 --> 01:12:32,960
Speaker 5: capture sick deer and then let them go again?

1231
01:12:33,720 --> 01:12:36,679
Speaker 4: Yeah? So Mark and I talked about this this is morning.

1232
01:12:36,920 --> 01:12:44,200
Speaker 4: We wanted to understand how this disease looked without intervention, like,

1233
01:12:44,680 --> 01:12:47,519
Speaker 4: so we wanted to see exactly what was going on

1234
01:12:47,640 --> 01:12:51,680
Speaker 4: with these animals. So, yes, we were capturing animals and

1235
01:12:51,760 --> 01:12:55,440
Speaker 4: we were allowing this to proceed as it would.

1236
01:12:55,400 --> 01:12:57,439
Speaker 1: Like what would have happened if you weren't doing the study?

1237
01:12:58,040 --> 01:13:02,960
Speaker 4: Yeah, yeah, yeah, And so we we do we collect

1238
01:13:02,960 --> 01:13:07,360
Speaker 4: all this information we see. You know. For instance, one

1239
01:13:07,439 --> 01:13:11,360
Speaker 4: of the more kind of concerning outcomes was the prevalence

1240
01:13:11,920 --> 01:13:17,320
Speaker 4: is so high. Another outcome that was interesting. If you

1241
01:13:17,400 --> 01:13:23,960
Speaker 4: look at dough survival, like annual survival of negative dose,

1242
01:13:24,040 --> 01:13:27,519
Speaker 4: it was about eighty percent pretty high. It was sixty

1243
01:13:27,560 --> 01:13:32,920
Speaker 4: percent for positive dose. God, if you looked at buck

1244
01:13:33,000 --> 01:13:36,360
Speaker 4: survival an your survival, if it was a negative cohort,

1245
01:13:36,520 --> 01:13:39,960
Speaker 4: it was about seventy percent pretty high. It was forty

1246
01:13:40,000 --> 01:13:41,400
Speaker 4: percent positive.

1247
01:13:42,000 --> 01:13:47,559
Speaker 1: And that is above and beyond normal. Well is that

1248
01:13:47,800 --> 01:13:51,080
Speaker 1: above and beyond just the disease killing them? Because you know,

1249
01:13:51,200 --> 01:13:56,479
Speaker 1: like like like if you think back to like HIV AIDS, right,

1250
01:13:57,600 --> 01:14:01,800
Speaker 1: people that die are dying from pneumonia or they're dying

1251
01:14:01,800 --> 01:14:05,720
Speaker 1: from complications from other things right there, they more likely

1252
01:14:05,800 --> 01:14:07,559
Speaker 1: like die from the flu.

1253
01:14:07,960 --> 01:14:08,200
Speaker 4: Yep.

1254
01:14:08,479 --> 01:14:12,840
Speaker 1: So if if if it takes two years to kill

1255
01:14:12,840 --> 01:14:16,680
Speaker 1: a deer, if the disease takes two years to kill

1256
01:14:16,720 --> 01:14:20,040
Speaker 1: a deer, then of course from one year to the next,

1257
01:14:20,080 --> 01:14:21,920
Speaker 1: fifty percent of the deer that have it should be

1258
01:14:21,920 --> 01:14:25,920
Speaker 1: dead because it kills them. It's always fatal. So yes,

1259
01:14:26,439 --> 01:14:28,599
Speaker 1: so like no shit, like like of course they're dead

1260
01:14:28,640 --> 01:14:30,639
Speaker 1: because they have a disease that always kills them.

1261
01:14:31,040 --> 01:14:33,120
Speaker 5: But are they but if they get hit by a car?

1262
01:14:33,760 --> 01:14:38,040
Speaker 4: Yeah, So what we did is we categorized if they

1263
01:14:38,120 --> 01:14:41,320
Speaker 4: even if they were CWD positive, but they died from

1264
01:14:41,640 --> 01:14:45,920
Speaker 4: a car, a vehicle collision, or harvest or predation. We

1265
01:14:46,040 --> 01:14:48,719
Speaker 4: considered that not CWD related.

1266
01:14:48,760 --> 01:14:50,120
Speaker 1: Oh well, okay, wow.

1267
01:14:50,600 --> 01:14:55,960
Speaker 4: We only categorized mortalities to CWD that had no other links.

1268
01:14:56,000 --> 01:14:58,160
Speaker 1: And Mark was it lays down and dies.

1269
01:14:58,280 --> 01:15:00,280
Speaker 5: Yes, that's fascinating, and.

1270
01:15:00,360 --> 01:15:03,240
Speaker 1: So that's what I was. Yeah, that addresses what I

1271
01:15:03,280 --> 01:15:05,400
Speaker 1: was getting. A meaning he's positive and gets smoked by

1272
01:15:05,400 --> 01:15:08,280
Speaker 1: a car. That's maybe he's a little bit less vigilant.

1273
01:15:08,280 --> 01:15:09,760
Speaker 1: But how do you fracture that in?

1274
01:15:10,040 --> 01:15:13,360
Speaker 4: Right? So we were trying to be a conservative in

1275
01:15:13,360 --> 01:15:20,320
Speaker 4: that vein to not link mortalities to CWD that had approximate,

1276
01:15:20,560 --> 01:15:24,360
Speaker 4: you know, some other type of cause. And what we

1277
01:15:24,479 --> 01:15:28,320
Speaker 4: found was about twenty percent, just under twenty percent of

1278
01:15:28,360 --> 01:15:33,559
Speaker 4: all mortalities were linked directly to CWD. And so that's

1279
01:15:33,760 --> 01:15:38,280
Speaker 4: that's in addition to predation and harvest and these other things.

1280
01:15:40,600 --> 01:15:44,920
Speaker 1: Have you ever tested a live deer with the rectal

1281
01:15:44,920 --> 01:15:46,880
Speaker 1: thing you're talking about, that's what we do. Yeah, but

1282
01:15:46,960 --> 01:15:49,840
Speaker 1: have you ever tested a live deer and then had

1283
01:15:49,840 --> 01:15:54,200
Speaker 1: it be that that deer was still alive twenty five

1284
01:15:54,320 --> 01:15:54,960
Speaker 1: months later?

1285
01:15:58,160 --> 01:16:01,320
Speaker 4: Are you asking if you if it tested positive at.

1286
01:16:01,200 --> 01:16:03,759
Speaker 1: The rect Have you ever had a deer test positive

1287
01:16:04,520 --> 01:16:07,880
Speaker 1: and then twenty five months later that deer is still

1288
01:16:07,960 --> 01:16:08,880
Speaker 1: running around alive.

1289
01:16:11,280 --> 01:16:13,200
Speaker 4: I have to look at the data.

1290
01:16:13,400 --> 01:16:15,519
Speaker 2: I would think that would be the app you know,

1291
01:16:15,640 --> 01:16:18,679
Speaker 2: that would be the exception, not the rule, but not impossible. Well,

1292
01:16:18,800 --> 01:16:20,599
Speaker 2: this based on the incubation period.

1293
01:16:20,800 --> 01:16:23,800
Speaker 5: I wanted to ask this too, because this test is

1294
01:16:23,800 --> 01:16:26,400
Speaker 5: pretty darn new, right, I mean I feel like I

1295
01:16:26,680 --> 01:16:29,040
Speaker 5: just was talking about this last week and I'm like,

1296
01:16:29,160 --> 01:16:35,680
Speaker 5: there's not a test for CWD for live deer that so,

1297
01:16:35,800 --> 01:16:41,439
Speaker 5: is there a And this was because that it takes

1298
01:16:41,439 --> 01:16:43,840
Speaker 5: a while for the prions to build up to a

1299
01:16:43,880 --> 01:16:50,080
Speaker 5: detectable stage unless you're taking biopsies from the brain, brain stem,

1300
01:16:50,520 --> 01:16:57,519
Speaker 5: spinal column. Then lymph notes, So is the the rectal test?

1301
01:16:57,960 --> 01:17:04,479
Speaker 5: Is that uh only giving you positives at a certain

1302
01:17:05,439 --> 01:17:07,320
Speaker 5: progression point of the disease.

1303
01:17:08,040 --> 01:17:11,080
Speaker 2: Yeah, there's there's a lot of nuance here with the testing.

1304
01:17:11,160 --> 01:17:13,200
Speaker 2: But it also gets back to that time scale that

1305
01:17:13,240 --> 01:17:16,080
Speaker 2: I was talking about with in an individual deer, We're

1306
01:17:16,120 --> 01:17:19,760
Speaker 2: talking about you know, months and years, and so a

1307
01:17:19,800 --> 01:17:21,559
Speaker 2: lot of that has to do with the progression of

1308
01:17:21,640 --> 01:17:25,880
Speaker 2: the disease, the movement of the abnormal preon in the body.

1309
01:17:25,960 --> 01:17:29,120
Speaker 2: So you know, if a deer gets exposed to, you know,

1310
01:17:29,160 --> 01:17:34,400
Speaker 2: infected with CWD, the first place where we're typically going

1311
01:17:34,479 --> 01:17:37,800
Speaker 2: to have a detectable amount in there is in the

1312
01:17:37,880 --> 01:17:41,360
Speaker 2: lymph noodes, right, And everybody's probably familiar with the retroferringial lymphodes.

1313
01:17:43,360 --> 01:17:46,280
Speaker 2: That's part of what people will call the lymphoid system.

1314
01:17:46,360 --> 01:17:49,040
Speaker 2: So like you know, there's lymph nodes all around the body.

1315
01:17:49,080 --> 01:17:51,160
Speaker 2: So that little piece of the rectum that we're taking

1316
01:17:51,439 --> 01:17:54,200
Speaker 2: there happens to be like little tiny they're not lymph nodes.

1317
01:17:54,200 --> 01:17:57,759
Speaker 2: They're a little almost like little islands of lymphoid tissue.

1318
01:17:58,280 --> 01:18:00,840
Speaker 2: That's what we have those all throughout our all throughout

1319
01:18:00,880 --> 01:18:04,200
Speaker 2: our intestinal tract, and so that's what we're grabbing there.

1320
01:18:04,479 --> 01:18:07,960
Speaker 2: But that's typically a little bit later in disease. So

1321
01:18:08,000 --> 01:18:10,640
Speaker 2: you could easily have if we were to just have

1322
01:18:10,720 --> 01:18:14,280
Speaker 2: a deer that, you know, several months or you know,

1323
01:18:14,360 --> 01:18:18,360
Speaker 2: three months, four months, five months after infection, we test

1324
01:18:18,400 --> 01:18:21,280
Speaker 2: its lymph node and we test its rectal biopsy, there'd

1325
01:18:21,320 --> 01:18:23,720
Speaker 2: be a decent chance that that lymph node sample is

1326
01:18:23,760 --> 01:18:26,320
Speaker 2: positive and that rectal biopsy is not positive.

1327
01:18:26,439 --> 01:18:27,400
Speaker 4: Got it, got it.

1328
01:18:27,600 --> 01:18:29,240
Speaker 2: And a lot of that just has to do with

1329
01:18:29,280 --> 01:18:31,840
Speaker 2: the timing. The last place that it goes is going

1330
01:18:31,880 --> 01:18:35,160
Speaker 2: to be the brain, right, the brain stem. The obex

1331
01:18:35,200 --> 01:18:38,879
Speaker 2: people will have that referred to the information super Highway

1332
01:18:38,920 --> 01:18:44,559
Speaker 2: for us, right, And so that process takes a long time.

1333
01:18:44,840 --> 01:18:48,240
Speaker 2: That's the months in years process. Right. So you can

1334
01:18:48,280 --> 01:18:52,600
Speaker 2: have an animal it's you know, where that preon is

1335
01:18:52,680 --> 01:18:56,679
Speaker 2: kind of just slowly accumulating in these tissues and it's

1336
01:18:57,439 --> 01:19:01,040
Speaker 2: doing normal deer stuff and it looks totally healthy. That's

1337
01:19:01,040 --> 01:19:04,680
Speaker 2: why you can harvest an animal that tests positive for CWD.

1338
01:19:05,560 --> 01:19:09,040
Speaker 2: It's hard to say does that animal have CWD the disease, Well,

1339
01:19:09,320 --> 01:19:11,920
Speaker 2: probably not exhibiting any signs of it yet, but he's

1340
01:19:11,960 --> 01:19:15,680
Speaker 2: test positives on the path to disease, right, and so

1341
01:19:16,760 --> 01:19:19,360
Speaker 2: you know by the time by the time you get

1342
01:19:19,479 --> 01:19:24,720
Speaker 2: you know, a year, sometimes two years. Sometimes there's been

1343
01:19:24,880 --> 01:19:27,639
Speaker 2: experimental studies where they don't really see disease out until

1344
01:19:27,680 --> 01:19:31,640
Speaker 2: three four years, so the time is is pretty weird sometimes.

1345
01:19:31,640 --> 01:19:35,799
Speaker 1: Okay, So why do people say that CWD is always

1346
01:19:35,840 --> 01:19:40,960
Speaker 1: fatal because you start like like life, always like life.

1347
01:19:40,680 --> 01:19:43,759
Speaker 2: As yeah, yeah, we're all gonna die, right, suthing's fatal

1348
01:19:43,920 --> 01:19:44,280
Speaker 2: and so.

1349
01:19:44,280 --> 01:19:48,320
Speaker 1: If he can have it for four years. Why do

1350
01:19:48,439 --> 01:19:50,799
Speaker 1: people also often say that they're dead in two years.

1351
01:19:51,000 --> 01:19:53,720
Speaker 2: I guess it's like you can predict. Okay, so if

1352
01:19:53,760 --> 01:19:56,280
Speaker 2: something else you can start a clock. But here gets

1353
01:19:56,320 --> 01:19:59,200
Speaker 2: CWD test positive for CWD. It's like, I don't know

1354
01:19:59,240 --> 01:20:02,559
Speaker 2: when if you evade all other causes of mortality, this

1355
01:20:02,680 --> 01:20:04,920
Speaker 2: is what you're going to die from. There's very few

1356
01:20:04,960 --> 01:20:05,880
Speaker 2: of us that can say that.

1357
01:20:05,880 --> 01:20:10,120
Speaker 1: Yeah, okay, but at what point? So I'm saying like

1358
01:20:10,439 --> 01:20:11,920
Speaker 1: if he if.

1359
01:20:13,000 --> 01:20:15,920
Speaker 5: Yeah, the point would have to be prior to the

1360
01:20:16,120 --> 01:20:19,799
Speaker 5: naturally natural average mortality mark.

1361
01:20:20,320 --> 01:20:22,719
Speaker 1: Right, So yeah, So when they say it's always fatal,

1362
01:20:23,360 --> 01:20:25,479
Speaker 1: meaning if he doesn't get shot, doesn't get hit by

1363
01:20:25,479 --> 01:20:29,679
Speaker 1: a car, doesn't get killed by kyo, whatever, that will

1364
01:20:29,680 --> 01:20:30,800
Speaker 1: be his cause of death.

1365
01:20:31,120 --> 01:20:31,519
Speaker 2: Correct.

1366
01:20:33,800 --> 01:20:36,320
Speaker 1: But if it could be that he carries it for

1367
01:20:36,360 --> 01:20:39,240
Speaker 1: four years, it almost kind of doesn't matter because most

1368
01:20:39,320 --> 01:20:43,000
Speaker 1: like dear, don't live that long. Do you follow me?

1369
01:20:43,040 --> 01:20:45,160
Speaker 1: Like if you could if you tested a deer, like

1370
01:20:45,280 --> 01:20:47,200
Speaker 1: if you guys go out and put if you go

1371
01:20:47,200 --> 01:20:49,679
Speaker 1: out and test deer and collar them and you're like, okay,

1372
01:20:49,680 --> 01:20:54,360
Speaker 1: here's a positive deer. Uh, I would expect you to

1373
01:20:54,400 --> 01:20:58,320
Speaker 1: say since that he's already had it, he's already somewhere

1374
01:20:58,320 --> 01:21:00,040
Speaker 1: along the line. I would expect you to say that

1375
01:21:00,120 --> 01:21:05,880
Speaker 1: mortality CWD mortality in and of itself is sixty percent

1376
01:21:06,000 --> 01:21:10,120
Speaker 1: or seventy percent, or certainly more than fifty percent, because

1377
01:21:10,160 --> 01:21:12,519
Speaker 1: it's always fatal and it kills them within a couple

1378
01:21:12,520 --> 01:21:16,120
Speaker 1: of years. So any deer that's already positive, the clock

1379
01:21:16,160 --> 01:21:19,000
Speaker 1: has already started ticking. He's already into his two years

1380
01:21:19,000 --> 01:21:22,720
Speaker 1: of life. So why is it not that by two

1381
01:21:22,800 --> 01:21:24,200
Speaker 1: years every one of them is dead?

1382
01:21:25,479 --> 01:21:29,960
Speaker 2: Yeah, well that's part of the you know, Mike mentioned earlier,

1383
01:21:30,000 --> 01:21:33,679
Speaker 2: like this disease is just atypical. It doesn't read read

1384
01:21:33,720 --> 01:21:35,960
Speaker 2: the book. You know, there's not a you know, with

1385
01:21:36,080 --> 01:21:41,800
Speaker 2: most infectious diseases, there's a highly predictable time course. It's

1386
01:21:41,840 --> 01:21:45,360
Speaker 2: a little bit unpredictable once you get into sort of

1387
01:21:45,400 --> 01:21:47,760
Speaker 2: that when is a deer going to start to show

1388
01:21:47,800 --> 01:21:48,719
Speaker 2: clinical signs?

1389
01:21:48,880 --> 01:21:49,120
Speaker 1: Right?

1390
01:21:50,080 --> 01:21:54,120
Speaker 2: Usually once that happens, you know, whether it's sixteen months,

1391
01:21:54,160 --> 01:21:58,160
Speaker 2: eighteen months, twenty months, once they start to you if

1392
01:21:58,240 --> 01:22:00,559
Speaker 2: you were watching a deer and you're like that years off,

1393
01:22:00,600 --> 01:22:04,320
Speaker 2: it's not doing not doing right, that course is going

1394
01:22:04,360 --> 01:22:08,160
Speaker 2: to be pretty quick, probably within weeks or a couple months.

1395
01:22:08,560 --> 01:22:11,639
Speaker 2: So once they hit that point, it's downhill, and those

1396
01:22:11,800 --> 01:22:15,200
Speaker 2: those are the deer that you can you know, like

1397
01:22:15,240 --> 01:22:18,280
Speaker 2: some of those subtle changes that Mike was talking about

1398
01:22:18,320 --> 01:22:20,960
Speaker 2: relative to vigilance or home range size, all that stuff.

1399
01:22:21,280 --> 01:22:24,320
Speaker 2: That's probably even something different than we can perceive visually.

1400
01:22:24,360 --> 01:22:27,599
Speaker 2: Sometimes even you know, it's the classic deer everybody sees

1401
01:22:27,640 --> 01:22:30,680
Speaker 2: in the pictures. It's a frame stance, head drooped, slobbering,

1402
01:22:31,200 --> 01:22:34,000
Speaker 2: zombie kind of stare, just like looking into space. Nothing

1403
01:22:34,080 --> 01:22:37,040
Speaker 2: like those deer are circling the drain. Those deer are

1404
01:22:37,120 --> 01:22:40,240
Speaker 2: so far down this path, you know, they a lot

1405
01:22:40,280 --> 01:22:42,360
Speaker 2: of them would have died earlier. You know, I look

1406
01:22:42,439 --> 01:22:48,040
Speaker 2: at animals as like wild animals as akin to professional athletes, right.

1407
01:22:48,200 --> 01:22:52,479
Speaker 2: They they have to be at their peak constantly to migrate,

1408
01:22:52,600 --> 01:22:56,720
Speaker 2: spar evade predators, evade threats. If you're if you're just

1409
01:22:56,800 --> 01:22:58,759
Speaker 2: like a little bit off. Think about how many professional

1410
01:22:58,760 --> 01:23:01,320
Speaker 2: athletes sit on the bench and they're just I'm just

1411
01:23:01,520 --> 01:23:05,040
Speaker 2: not a little bit right, you know. So that's where

1412
01:23:05,040 --> 01:23:08,360
Speaker 2: it gets really hard. Those other mortalities, you know, killed

1413
01:23:08,360 --> 01:23:11,479
Speaker 2: by a hunter, nabbed by a predator, hit by a car, whatever,

1414
01:23:12,240 --> 01:23:14,720
Speaker 2: you know, what role did it have in sort of

1415
01:23:15,680 --> 01:23:18,720
Speaker 2: sealing its fate into that like there is there is

1416
01:23:18,760 --> 01:23:21,080
Speaker 2: something there. It's hard to quantify. There have been studies

1417
01:23:21,080 --> 01:23:23,720
Speaker 2: that have shown, you know, more prone to predation, more

1418
01:23:23,720 --> 01:23:27,880
Speaker 2: prone to harvest, more prone to vehicle strike. There seems

1419
01:23:27,880 --> 01:23:30,360
Speaker 2: to be regional differences with that stuff, but certainly it

1420
01:23:30,400 --> 01:23:33,400
Speaker 2: gives us the impression that like this stuff matters, right

1421
01:23:33,479 --> 01:23:36,960
Speaker 2: that when you're when you're adjusting an animal's ability to

1422
01:23:37,080 --> 01:23:41,360
Speaker 2: interact with its environment, perceived threats, move, all these things,

1423
01:23:42,040 --> 01:23:44,559
Speaker 2: it's going to be more prone to an unthrifty life,

1424
01:23:44,560 --> 01:23:44,760
Speaker 2: you know.

1425
01:23:44,800 --> 01:23:46,800
Speaker 1: And and we one time saw a kylete that must have

1426
01:23:46,840 --> 01:23:48,439
Speaker 1: got hit by a road going up the hill by

1427
01:23:48,439 --> 01:23:51,840
Speaker 1: our house, got hit by a car, but eagles were

1428
01:23:51,880 --> 01:23:54,960
Speaker 1: killing them. So did the eagles kill them?

1429
01:23:55,800 --> 01:23:56,080
Speaker 4: Right?

1430
01:23:56,280 --> 01:24:00,559
Speaker 2: This is tricky And your question is he's just.

1431
01:24:00,520 --> 01:24:03,160
Speaker 1: Dragging himself along and you're just like taking advantage of

1432
01:24:03,160 --> 01:24:05,680
Speaker 1: the situation. So yeah, it's hard to sort it out.

1433
01:24:06,120 --> 01:24:07,720
Speaker 1: But I'm just trying to get to again, I'm trying

1434
01:24:07,760 --> 01:24:10,960
Speaker 1: to get from the perspective of someone looking at someone

1435
01:24:10,960 --> 01:24:14,439
Speaker 1: looking at it and saying like like if I took

1436
01:24:14,479 --> 01:24:18,360
Speaker 1: a human like you take an American male, like okay,

1437
01:24:18,400 --> 01:24:24,040
Speaker 1: if he doesn't die of you know, he doesn't die

1438
01:24:24,080 --> 01:24:27,760
Speaker 1: of an opioid overdose, if he doesn't die in a

1439
01:24:27,840 --> 01:24:33,200
Speaker 1: vehicular car accident, he doesn't die from lung cancer. He

1440
01:24:33,240 --> 01:24:38,479
Speaker 1: will die from heart disease. Right, It's always fatal because like,

1441
01:24:38,800 --> 01:24:41,559
Speaker 1: of course something will end up getting you, and if

1442
01:24:41,600 --> 01:24:43,400
Speaker 1: you take all the other things that kills shit and

1443
01:24:43,439 --> 01:24:46,240
Speaker 1: set it asides, like, of course it'll be heart disease.

1444
01:24:46,400 --> 01:24:48,439
Speaker 4: But I think that I think the point that that

1445
01:24:48,680 --> 01:24:52,120
Speaker 4: argument misses is that these animals on average are not

1446
01:24:52,240 --> 01:24:57,479
Speaker 4: living as long as non diseased animals. Therefore their net

1447
01:24:57,560 --> 01:25:03,000
Speaker 4: reproductive potential is less than negative animals, and therefore you

1448
01:25:03,479 --> 01:25:07,880
Speaker 4: factor in that reduced lifespan. That's the answer to that

1449
01:25:08,000 --> 01:25:11,599
Speaker 4: question from my perspective is these animals are not going

1450
01:25:11,680 --> 01:25:15,080
Speaker 4: to live as long on average as a negative animal,

1451
01:25:15,120 --> 01:25:19,240
Speaker 4: and therefore the consequences to the population are going to be.

1452
01:25:20,680 --> 01:25:23,880
Speaker 5: Yeah, you get along that curve. You go from a

1453
01:25:23,960 --> 01:25:28,439
Speaker 5: population that on average you can take like one of

1454
01:25:28,479 --> 01:25:32,080
Speaker 5: those crazy Maryland deer. Remember learning about those, well the

1455
01:25:32,520 --> 01:25:35,759
Speaker 5: white tails on like the all the weird government ground

1456
01:25:35,800 --> 01:25:38,120
Speaker 5: in Maryland that you know they have like ancient white

1457
01:25:38,120 --> 01:25:42,360
Speaker 5: tail doughs that lived to regularly like sixteen or whatever.

1458
01:25:42,600 --> 01:25:45,320
Speaker 1: I don't know about this, yeah.

1459
01:25:44,479 --> 01:25:49,400
Speaker 5: But like on average, the population starts as like they

1460
01:25:49,439 --> 01:25:53,080
Speaker 5: lived to eight years old, and then a decade goes

1461
01:25:53,120 --> 01:25:54,679
Speaker 5: by and it's like, well it's seven and a half,

1462
01:25:54,840 --> 01:25:57,519
Speaker 5: and then all of a sudden, it's like, oh, on average,

1463
01:25:57,560 --> 01:26:01,040
Speaker 5: everybody lives till five. On average, everybody lives till three

1464
01:26:01,120 --> 01:26:04,400
Speaker 5: and a half. Right, And then you got serious problems

1465
01:26:05,080 --> 01:26:07,400
Speaker 5: because and that's you're not producing deer.

1466
01:26:07,439 --> 01:26:10,280
Speaker 4: That's why the agencies are trying to keep that prevalence

1467
01:26:10,320 --> 01:26:14,400
Speaker 4: so low is because at a low prevalence, these this

1468
01:26:14,479 --> 01:26:19,160
Speaker 4: discussion that we're having about you know, mortality causes, and

1469
01:26:19,600 --> 01:26:23,320
Speaker 4: it becomes largely a relevant because only a tiny percentage

1470
01:26:23,320 --> 01:26:27,160
Speaker 4: of animals have the disease to begin with, and therefore

1471
01:26:27,360 --> 01:26:31,040
Speaker 4: an even smaller percentage of that are dying specifically just

1472
01:26:31,120 --> 01:26:31,960
Speaker 4: from CWD.

1473
01:26:32,760 --> 01:26:34,800
Speaker 5: You're killing big bucks, people are getting food ea.

1474
01:26:35,000 --> 01:26:38,040
Speaker 4: But as you get up closer farther up that curve,

1475
01:26:38,280 --> 01:26:43,799
Speaker 4: then this conversation becomes more relevant because now you're losing

1476
01:26:43,840 --> 01:26:48,479
Speaker 4: a significant percentage of your population to just the disease.

1477
01:26:48,600 --> 01:26:52,559
Speaker 4: And so if we looked at at of all the

1478
01:26:52,600 --> 01:26:55,880
Speaker 4: positive deer that we put our hands on, a third

1479
01:26:55,920 --> 01:27:00,400
Speaker 4: of them died just from CWD. So about twenty of

1480
01:27:00,400 --> 01:27:05,040
Speaker 4: the total population was impacted, but a third of the

1481
01:27:05,080 --> 01:27:09,840
Speaker 4: animals that were positive died solely from CWD. And so

1482
01:27:10,640 --> 01:27:11,679
Speaker 4: again that's why.

1483
01:27:11,760 --> 01:27:15,120
Speaker 1: Because prevalence rates are so high, you're losing twenty percent

1484
01:27:15,200 --> 01:27:19,519
Speaker 1: of the population to the disease strictly to the disease, Yes,

1485
01:27:19,880 --> 01:27:24,320
Speaker 1: and in harvest wouldn't even be that high hunter harvest's uh.

1486
01:27:24,560 --> 01:27:28,439
Speaker 4: It was so the most impactful. You know, from a

1487
01:27:28,600 --> 01:27:32,879
Speaker 4: from a population perspective, you had three competing mortality sources.

1488
01:27:33,720 --> 01:27:39,479
Speaker 4: You had harvest, predation, and CWD, whereas in a normal

1489
01:27:39,560 --> 01:27:43,080
Speaker 4: population you would have harvest and predation, right, and so

1490
01:27:43,160 --> 01:27:47,320
Speaker 4: you're adding this mortality source that's becoming increasingly more relevant

1491
01:27:47,360 --> 01:27:52,400
Speaker 4: as prevalence increases. And so not surprisingly, the final product

1492
01:27:52,400 --> 01:27:55,000
Speaker 4: that we produced with this with this study was this

1493
01:27:55,080 --> 01:27:58,519
Speaker 4: population model, and what we what we showed clearly is

1494
01:27:58,560 --> 01:28:02,439
Speaker 4: this population's declining about thirteen to fourteen percent per year.

1495
01:28:03,800 --> 01:28:07,040
Speaker 4: And so now you're looking at deer densities that are

1496
01:28:07,080 --> 01:28:09,800
Speaker 4: in the one to five deer per square.

1497
01:28:09,560 --> 01:28:12,880
Speaker 1: Mile range from a high of what well.

1498
01:28:12,840 --> 01:28:16,000
Speaker 4: We came in at us we only have a snap shot, right,

1499
01:28:16,080 --> 01:28:17,559
Speaker 4: We we came in and.

1500
01:28:17,520 --> 01:28:21,640
Speaker 1: Well, because you don't trust other you can't trust other guesses.

1501
01:28:21,880 --> 01:28:23,840
Speaker 4: Well, you don't know where I mean, we don't know

1502
01:28:24,080 --> 01:28:27,200
Speaker 4: twenty years ago, what the I mean. We come in

1503
01:28:27,240 --> 01:28:29,479
Speaker 4: as researchers and we get a snapshot of where we

1504
01:28:29,560 --> 01:28:32,160
Speaker 4: are right now. And that's another problem with this, with

1505
01:28:33,000 --> 01:28:36,840
Speaker 4: trying to understand this disease. It's kind of like the

1506
01:28:36,920 --> 01:28:39,400
Speaker 4: other analogy I have. It's kind of like wild Turkey declines.

1507
01:28:39,960 --> 01:28:41,800
Speaker 4: I mean, you're you're coming in and you're trying to

1508
01:28:41,840 --> 01:28:44,839
Speaker 4: study something that's been occurring in the South over twenty

1509
01:28:44,880 --> 01:28:47,800
Speaker 4: five years, and you come in and you get a

1510
01:28:47,800 --> 01:28:51,080
Speaker 4: little snapshot of data from a population, and then now

1511
01:28:51,080 --> 01:28:53,960
Speaker 4: you're trying to figure out from a snapshot what the

1512
01:28:53,960 --> 01:28:56,679
Speaker 4: bigger picture is. And we're dealing, you know, you're talking

1513
01:28:56,720 --> 01:28:59,920
Speaker 4: about a disease that takes decades to kind of operate.

1514
01:29:00,040 --> 01:29:02,960
Speaker 4: Eight And we come in and a five year study

1515
01:29:03,000 --> 01:29:06,479
Speaker 4: is a pretty long field study in my world, and

1516
01:29:06,560 --> 01:29:09,599
Speaker 4: even in that's not near enough. I would have loved

1517
01:29:09,640 --> 01:29:12,639
Speaker 4: to have had fifteen years of data before, and I'd

1518
01:29:12,680 --> 01:29:15,160
Speaker 4: like to keep studying the population, but that's just not

1519
01:29:15,720 --> 01:29:19,320
Speaker 4: that's just not realistic. But and so we we show

1520
01:29:19,400 --> 01:29:23,080
Speaker 4: clearly that this population is declining and it's going to

1521
01:29:23,120 --> 01:29:27,519
Speaker 4: continue to decline. And now you have prevalence that you

1522
01:29:27,560 --> 01:29:30,799
Speaker 4: know is exceeding you know, is that fifty percent across

1523
01:29:30,800 --> 01:29:34,799
Speaker 4: the population, which is incredibly high. And now you start

1524
01:29:35,280 --> 01:29:40,360
Speaker 4: thinking through scenarios of what does the agency do right?

1525
01:29:40,520 --> 01:29:43,200
Speaker 4: And so back to where kind of where we started.

1526
01:29:44,080 --> 01:29:47,759
Speaker 4: When the agency detected this disease, they took a fairly

1527
01:29:47,880 --> 01:29:52,759
Speaker 4: standard approach. Let's create his own let's an increase harvest

1528
01:29:52,880 --> 01:29:57,800
Speaker 4: or opportunity. Let's liberalize bag limits, let's remove antler pointler restrictions,

1529
01:29:58,280 --> 01:30:01,960
Speaker 4: let's ban feeding. And what they're trying to do is

1530
01:30:02,439 --> 01:30:06,120
Speaker 4: controlled the spread of the disease. But they didn't know

1531
01:30:06,240 --> 01:30:07,639
Speaker 4: where they were on the curve.

1532
01:30:07,960 --> 01:30:10,840
Speaker 1: So now that they know it's too late to do

1533
01:30:11,000 --> 01:30:16,200
Speaker 1: that and they know that the population is declining, at

1534
01:30:16,200 --> 01:30:18,600
Speaker 1: what point do they reverse strategy?

1535
01:30:19,439 --> 01:30:22,680
Speaker 4: I think that that speaks to the complexity of this disease. Is,

1536
01:30:22,920 --> 01:30:25,600
Speaker 4: you know, in some situations, and this is certainly not

1537
01:30:25,800 --> 01:30:28,960
Speaker 4: doom and gloom, but when you get to prevalence as

1538
01:30:29,040 --> 01:30:32,120
Speaker 4: high as what you see in Northwest Arkansas, your your

1539
01:30:32,200 --> 01:30:36,519
Speaker 4: management options have changed from where you are. If you're

1540
01:30:36,560 --> 01:30:40,559
Speaker 4: at two percent prevalence at two or three or you know,

1541
01:30:40,560 --> 01:30:43,360
Speaker 4: on the low end of the curve, you have these options. Mark,

1542
01:30:43,360 --> 01:30:46,439
Speaker 4: and I've talked about when you get up to fifty percent,

1543
01:30:47,280 --> 01:30:51,120
Speaker 4: now your options are limited because now your population is declining,

1544
01:30:51,960 --> 01:30:56,160
Speaker 4: and now you're thinking about the future sustainability of the population.

1545
01:30:56,400 --> 01:30:59,400
Speaker 1: Yeah, that's what. Yeah, So if you go to a

1546
01:30:59,400 --> 01:31:06,720
Speaker 1: place that has thirty for prevalency, you're not going to

1547
01:31:06,760 --> 01:31:07,800
Speaker 1: shoot your way out of it.

1548
01:31:09,720 --> 01:31:11,439
Speaker 2: No, no, because you're not going to get rid of

1549
01:31:11,479 --> 01:31:14,000
Speaker 2: the disease. But that's the version of living with it.

1550
01:31:14,479 --> 01:31:18,839
Speaker 4: Yeah, at that prevalence, it's there, and so.

1551
01:31:18,160 --> 01:31:21,240
Speaker 1: So would you Is there an argument that you'd want

1552
01:31:21,520 --> 01:31:25,040
Speaker 1: more deer on the landscape, to have a higher amount

1553
01:31:25,080 --> 01:31:30,800
Speaker 1: of deer and test more that you'd have some sort

1554
01:31:30,840 --> 01:31:34,439
Speaker 1: of natural selection play out. Do you have more deer,

1555
01:31:34,720 --> 01:31:39,360
Speaker 1: more genetic diversity, and you'd start some new strategy of

1556
01:31:39,439 --> 01:31:41,160
Speaker 1: seeing who's resistant?

1557
01:31:41,439 --> 01:31:43,439
Speaker 4: Did one of the were you asked this at that here?

1558
01:31:44,479 --> 01:31:51,080
Speaker 2: You know there's there's yeah, the deer there are. It's

1559
01:31:51,200 --> 01:31:55,160
Speaker 2: basically trying to establish a new normal. Okay, Right, it's

1560
01:31:55,200 --> 01:31:59,240
Speaker 2: trying to the theory with CWD is that you're eventually

1561
01:31:59,320 --> 01:32:01,920
Speaker 2: going to hit some equilibrium right where you have your

1562
01:32:01,920 --> 01:32:04,280
Speaker 2: prevalence is so high, that percentage of deer that are

1563
01:32:04,320 --> 01:32:07,400
Speaker 2: positive is so high, and you have this continual you

1564
01:32:07,400 --> 01:32:10,840
Speaker 2: know sort of you know, the clock ticks and deer die,

1565
01:32:11,479 --> 01:32:14,360
Speaker 2: but you still have recruitment into the population, and so

1566
01:32:14,439 --> 01:32:18,200
Speaker 2: you really can't. At some point you'll have that percentage

1567
01:32:18,240 --> 01:32:21,160
Speaker 2: of positive deer is going to kind of like yeah.

1568
01:32:20,960 --> 01:32:24,000
Speaker 5: Because if it's good, right, like, it's going to suck

1569
01:32:24,080 --> 01:32:26,439
Speaker 5: in other deer who are like, oh, there's not deer here,

1570
01:32:26,560 --> 01:32:28,639
Speaker 5: m h lots fo Yeah.

1571
01:32:28,680 --> 01:32:32,479
Speaker 2: And and there is that there are studies ongoing and

1572
01:32:32,640 --> 01:32:35,519
Speaker 2: this is like real world Mother Nature experiments right now,

1573
01:32:35,600 --> 01:32:38,439
Speaker 2: like trying to look at these populations that are at

1574
01:32:38,479 --> 01:32:42,160
Speaker 2: this state and start to understand genetics, like what is

1575
01:32:42,160 --> 01:32:46,120
Speaker 2: that equilibrium, what's the new balance? Is there shifting of

1576
01:32:46,920 --> 01:32:50,000
Speaker 2: you know, like we talked about that that preon gene,

1577
01:32:50,000 --> 01:32:52,800
Speaker 2: the pr NP gene. That's kind of a metric that

1578
01:32:52,880 --> 01:32:57,519
Speaker 2: some places will use to sort of monitor, you know,

1579
01:32:57,600 --> 01:33:01,200
Speaker 2: how how a population is maybe shifting based on a

1580
01:33:01,200 --> 01:33:04,160
Speaker 2: new selection pressure. Right like this is a relatively new

1581
01:33:04,200 --> 01:33:10,280
Speaker 2: selection pressure for most most populations, and so all that

1582
01:33:10,360 --> 01:33:13,160
Speaker 2: work is sort of you know ongoing. I think we're

1583
01:33:13,160 --> 01:33:16,600
Speaker 2: a little bit down the road from understanding it, but

1584
01:33:16,640 --> 01:33:18,960
Speaker 2: it's a very important area to sort of understand, is

1585
01:33:19,000 --> 01:33:21,960
Speaker 2: what do we expect from these populations once they get

1586
01:33:22,000 --> 01:33:24,160
Speaker 2: to that point. I do want to circle back to

1587
01:33:24,200 --> 01:33:26,120
Speaker 2: one thing we were talking about dead deer, because that's

1588
01:33:26,160 --> 01:33:30,280
Speaker 2: my jam. So yeah, you like, say a buck, you

1589
01:33:30,320 --> 01:33:33,599
Speaker 2: can definitely have a scenario where Okay, he first tests,

1590
01:33:33,680 --> 01:33:36,559
Speaker 2: you know, he gets infected at two and a half.

1591
01:33:37,160 --> 01:33:39,360
Speaker 2: Yeah he'll lift to four and a half and you know,

1592
01:33:39,520 --> 01:33:43,840
Speaker 2: honky dory, everything's great, you know. But I'll go back

1593
01:33:43,840 --> 01:33:46,160
Speaker 2: to that original story I was talking about with one

1594
01:33:46,160 --> 01:33:48,759
Speaker 2: of our collar deer in sort of the hot zone

1595
01:33:48,800 --> 01:33:51,320
Speaker 2: where we are. And I do this not to like

1596
01:33:52,360 --> 01:33:55,400
Speaker 2: I fear that sometimes this is the kind of stories

1597
01:33:55,439 --> 01:33:58,800
Speaker 2: that you know, you get accused of fear mongering, but

1598
01:33:59,720 --> 01:34:02,839
Speaker 2: very ill tell you it's really not, you know, because

1599
01:34:02,960 --> 01:34:05,080
Speaker 2: like I just said, you can also have a scenario

1600
01:34:05,160 --> 01:34:06,720
Speaker 2: where you harvest be four and a half year old

1601
01:34:06,760 --> 01:34:10,200
Speaker 2: buck right gets to these ages that are desirable. The

1602
01:34:10,200 --> 01:34:13,280
Speaker 2: opposite is also true, and we know that as prevalence

1603
01:34:13,280 --> 01:34:16,960
Speaker 2: increases in a population, that percent increases you get to

1604
01:34:17,000 --> 01:34:21,480
Speaker 2: this point where it the age at which you're infected

1605
01:34:22,000 --> 01:34:25,439
Speaker 2: early in an infection cycle, you know, it's usually like

1606
01:34:25,479 --> 01:34:28,759
Speaker 2: those the males are at greater risk of becoming infected.

1607
01:34:28,800 --> 01:34:31,240
Speaker 2: Older males are more likely of being tested and positive.

1608
01:34:31,280 --> 01:34:35,840
Speaker 2: But as it becomes a highly endemic area, so you've

1609
01:34:35,880 --> 01:34:40,000
Speaker 2: had preons shed into the environment, into that habitat for

1610
01:34:40,280 --> 01:34:44,080
Speaker 2: many years, lots of direct contact between animals, the age

1611
01:34:44,080 --> 01:34:47,080
Speaker 2: of like the writ, there's accumulation of risk. Right, your

1612
01:34:47,160 --> 01:34:52,720
Speaker 2: chances once you are born of encountering CWD are greatly increased. Right,

1613
01:34:52,720 --> 01:34:55,240
Speaker 2: if you're born into that environment, chances are you're going

1614
01:34:55,280 --> 01:34:57,720
Speaker 2: to see CBD sooner rather than later. And so that

1615
01:34:57,880 --> 01:35:01,800
Speaker 2: to that point. You know, there was a buck that

1616
01:35:02,040 --> 01:35:06,599
Speaker 2: was captured in twenty twenty two. He was about eight

1617
01:35:06,680 --> 01:35:09,720
Speaker 2: or nine months old at the time of capture, relatively

1618
01:35:10,120 --> 01:35:13,960
Speaker 2: normal body condition, wasn't thin, wasn't you know, super chunky,

1619
01:35:14,120 --> 01:35:17,680
Speaker 2: just kind of kind of average. We got the recto biopsy,

1620
01:35:18,400 --> 01:35:20,400
Speaker 2: and that's not an immediate test. Right, months go by

1621
01:35:20,520 --> 01:35:24,280
Speaker 2: before we get that answer. Ended up testing positive. So

1622
01:35:24,360 --> 01:35:29,200
Speaker 2: that was in March. Okay, we got a mortality signal

1623
01:35:29,280 --> 01:35:34,120
Speaker 2: in September. He was dead along the Buffalo River, right

1624
01:35:34,160 --> 01:35:38,840
Speaker 2: on the shoreline. And to say emaciated is kind of

1625
01:35:38,880 --> 01:35:41,080
Speaker 2: an understatement. You know, this is a one point five

1626
01:35:41,160 --> 01:35:45,599
Speaker 2: year old deer at this point died of chronic wasting disease.

1627
01:35:45,720 --> 01:35:47,760
Speaker 2: He was completely wasted away. I can show you guys

1628
01:35:47,840 --> 01:35:53,920
Speaker 2: picture later. No muscle mass, no subcontinuous fat, no visceral fat,

1629
01:35:54,000 --> 01:35:59,400
Speaker 2: fat inside, you know. And he had aspiration pneumonia, which

1630
01:35:59,479 --> 01:36:03,760
Speaker 2: is a common problem you see an end stage clinical CWD.

1631
01:36:04,479 --> 01:36:07,680
Speaker 2: You know, as as you as this disease begins to

1632
01:36:07,760 --> 01:36:12,599
Speaker 2: affect pretty much everything, right, because it's it's it's filling

1633
01:36:12,680 --> 01:36:14,879
Speaker 2: up the space in that brain stem like your information

1634
01:36:15,000 --> 01:36:19,000
Speaker 2: super highway for your body. They lose control of their

1635
01:36:19,400 --> 01:36:22,200
Speaker 2: you know, reflexes, right, so they're swallowing. Reflex goes away,

1636
01:36:22,240 --> 01:36:26,080
Speaker 2: so they aspirate feed and then that settles down into

1637
01:36:26,080 --> 01:36:29,439
Speaker 2: the lung. So he had aspiration pneumonia. And he had

1638
01:36:29,640 --> 01:36:34,240
Speaker 2: an old injury on his foot, which a crops you

1639
01:36:34,320 --> 01:36:36,639
Speaker 2: a lot of deer and an old injury on a foot.

1640
01:36:36,680 --> 01:36:40,240
Speaker 2: Deer do fine for a long time putting up with

1641
01:36:40,280 --> 01:36:43,280
Speaker 2: little pesky problems like that, but by it was it

1642
01:36:43,320 --> 01:36:46,160
Speaker 2: was kind of an eye opening, you know. And I'm

1643
01:36:46,160 --> 01:36:48,960
Speaker 2: a disease nerd, you know, I like I like, I

1644
01:36:49,040 --> 01:36:51,720
Speaker 2: like this stuff. But there's these certain moments where you

1645
01:36:51,760 --> 01:36:54,519
Speaker 2: see and touch something and it kind of hits different.

1646
01:36:54,560 --> 01:36:56,280
Speaker 2: And that was one of those moments, you know, like,

1647
01:36:56,360 --> 01:36:59,120
Speaker 2: here's here's a year and a half old male you

1648
01:36:59,160 --> 01:37:05,000
Speaker 2: know in this area that literally fell over dead in

1649
01:37:05,080 --> 01:37:09,120
Speaker 2: a riparian corridor on the Buffalo River from CWD, you know,

1650
01:37:09,240 --> 01:37:11,759
Speaker 2: And that's just a kind of a jarring moment. But again,

1651
01:37:11,800 --> 01:37:14,200
Speaker 2: that can happen. But you can also harvest in the

1652
01:37:14,200 --> 01:37:16,880
Speaker 2: same population a four and a half old male that

1653
01:37:17,040 --> 01:37:20,200
Speaker 2: you know looks okay. But both things happen, and over time,

1654
01:37:20,280 --> 01:37:23,960
Speaker 2: as you get more one of the hallmarks of as

1655
01:37:23,960 --> 01:37:26,479
Speaker 2: it sets in that young those younger age classes start

1656
01:37:26,520 --> 01:37:29,559
Speaker 2: to become a little more commonly infected, and then that

1657
01:37:29,640 --> 01:37:30,719
Speaker 2: clock ticks earlier.

1658
01:37:34,479 --> 01:37:38,200
Speaker 5: How much of the conversation, like legitimate conversation is there

1659
01:37:38,320 --> 01:37:44,679
Speaker 5: around CWD resistant deer? Obviously, State of Oklahoma is going

1660
01:37:44,800 --> 01:37:49,160
Speaker 5: great guns in a way that I think is concerning.

1661
01:37:49,600 --> 01:37:52,960
Speaker 5: And I don't honestly know how it's legal to release

1662
01:37:53,040 --> 01:37:57,599
Speaker 5: game farm animals that are quote unquote CWD resistant that

1663
01:37:58,520 --> 01:38:02,440
Speaker 5: unless they know also know how to read state boundaries

1664
01:38:02,439 --> 01:38:09,360
Speaker 5: and maps and things to stay in Oklahoma. How much

1665
01:38:09,479 --> 01:38:15,400
Speaker 5: like is there a conversation there of identifying deer that

1666
01:38:16,920 --> 01:38:21,320
Speaker 5: do have a resistance or long term carriers to the

1667
01:38:21,360 --> 01:38:26,759
Speaker 5: point where it just never manifests, or like what is the.

1668
01:38:27,240 --> 01:38:31,320
Speaker 2: So we know we know there with CWD, you know,

1669
01:38:31,479 --> 01:38:33,880
Speaker 2: say in white tailed deer like that again, that that

1670
01:38:33,920 --> 01:38:36,840
Speaker 2: preon protein gene. They'll refer to it as the pr

1671
01:38:36,920 --> 01:38:39,880
Speaker 2: and P gene. We've known for a long time that

1672
01:38:40,080 --> 01:38:48,160
Speaker 2: certain genotypes. So the basically the configuration of that gene,

1673
01:38:48,560 --> 01:38:54,519
Speaker 2: certain genotypes are less susceptible doesn't mean resistant, It means

1674
01:38:55,200 --> 01:38:58,519
Speaker 2: they don't they aren't as commonly infected. And when they

1675
01:38:58,560 --> 01:39:02,040
Speaker 2: are infected typically what happens to your point, Steve, earlier,

1676
01:39:03,200 --> 01:39:06,880
Speaker 2: that incubation period is longer, So those deer with certain

1677
01:39:06,920 --> 01:39:11,599
Speaker 2: genotypes might rather than you know, head and downhill at

1678
01:39:12,000 --> 01:39:14,880
Speaker 2: two years after maybe that pushes out to three years

1679
01:39:14,920 --> 01:39:18,200
Speaker 2: after four years after, right, So that's been known. That's

1680
01:39:18,560 --> 01:39:22,280
Speaker 2: that's a thing, right, But they ultimately will to our

1681
01:39:22,320 --> 01:39:25,519
Speaker 2: conversation earlier, if they live through all, if they you know,

1682
01:39:25,600 --> 01:39:28,200
Speaker 2: dance through all the other flaming hoops of dear mortality causes,

1683
01:39:28,360 --> 01:39:33,200
Speaker 2: they'll ultimately bite it from chronic waste disease. So you know,

1684
01:39:33,280 --> 01:39:37,200
Speaker 2: we can't manipulate that. But mother nature can if there's

1685
01:39:37,240 --> 01:39:42,280
Speaker 2: adequate selection pressure, those more favorable like less susceptible genotypes

1686
01:39:42,400 --> 01:39:48,760
Speaker 2: historically and most like free ranging populations are not well represented. Right,

1687
01:39:48,840 --> 01:39:53,559
Speaker 2: it's the exception, those more like those less susceptible CWD

1688
01:39:53,720 --> 01:39:57,640
Speaker 2: genotypes are the exception, not the rule. So kind of

1689
01:39:57,640 --> 01:39:59,519
Speaker 2: in a simple sense, I'm not a geneticist, but it

1690
01:39:59,560 --> 01:40:03,080
Speaker 2: tells you that that there's not adequate selection pressure on that. Right,

1691
01:40:03,160 --> 01:40:05,120
Speaker 2: Fitness is greater in some of these other ones, so

1692
01:40:05,120 --> 01:40:09,679
Speaker 2: there's concern there. But as CWD sets in and selection

1693
01:40:09,800 --> 01:40:13,120
Speaker 2: pressure hits, you know, maybe I would anticipate that in

1694
01:40:13,160 --> 01:40:15,680
Speaker 2: some of these populations we start to see that, and

1695
01:40:15,720 --> 01:40:19,479
Speaker 2: they've they've they've started to do some of that work

1696
01:40:19,560 --> 01:40:23,960
Speaker 2: in mule deer populations in Colorado, you know, where they've

1697
01:40:23,960 --> 01:40:24,760
Speaker 2: seen a.

1698
01:40:24,720 --> 01:40:26,520
Speaker 1: Little bit of a shift.

1699
01:40:26,240 --> 01:40:30,240
Speaker 2: Maybe to some of these less susceptible you know, genotypes.

1700
01:40:30,280 --> 01:40:33,760
Speaker 2: But again, this is this is it takes time, and

1701
01:40:34,280 --> 01:40:36,559
Speaker 2: there's a lot of smart people working on that, but

1702
01:40:36,600 --> 01:40:38,599
Speaker 2: I do think it's going to take time. To your

1703
01:40:38,640 --> 01:40:42,640
Speaker 2: point though, relative to the issue in Oklahoma, so on

1704
01:40:42,920 --> 01:40:50,400
Speaker 2: the farm servet industry, that's where that sort of desire originated. Right,

1705
01:40:50,560 --> 01:40:56,640
Speaker 2: Let's let's try to selectively breed whitetail deer two that

1706
01:40:56,720 --> 01:41:00,680
Speaker 2: are resistant to CWD, all right, and they're doing some approaches.

1707
01:41:00,720 --> 01:41:03,000
Speaker 2: It's genome wide, so they're looking at the whole genome

1708
01:41:03,080 --> 01:41:06,160
Speaker 2: and all the other you know, genes within the body

1709
01:41:06,160 --> 01:41:13,040
Speaker 2: that might impact susceptibility. And so that has bled out

1710
01:41:13,120 --> 01:41:17,760
Speaker 2: into you know, it's kind of been talked about as

1711
01:41:18,800 --> 01:41:22,880
Speaker 2: the great hope in some degree, right, And I think

1712
01:41:22,920 --> 01:41:26,880
Speaker 2: that's because this is a it sucks to talk about

1713
01:41:26,920 --> 01:41:29,439
Speaker 2: this disease. It's just not it's not a great disease

1714
01:41:29,439 --> 01:41:32,960
Speaker 2: to talk about. We don't have clear solutions, and so here,

1715
01:41:33,040 --> 01:41:35,960
Speaker 2: let's let's try to march down this path of you know,

1716
01:41:36,280 --> 01:41:37,639
Speaker 2: let's breed our way out of this.

1717
01:41:39,479 --> 01:41:43,000
Speaker 5: You know that's because we can seem more proactive in

1718
01:41:43,080 --> 01:41:49,760
Speaker 5: certain circles. Then well, there's this naturally occurring test that's

1719
01:41:49,760 --> 01:41:52,840
Speaker 5: going on in Colorado mule deer, and in a few

1720
01:41:52,840 --> 01:41:56,400
Speaker 5: decades or longer, we might have something that comes out.

1721
01:41:56,439 --> 01:41:58,719
Speaker 4: And we want a silver bullet. That's the bottom line.

1722
01:41:58,760 --> 01:42:02,080
Speaker 4: We want something that will fix this. And I think,

1723
01:42:02,600 --> 01:42:05,519
Speaker 4: you know a few things that Mark said, I think

1724
01:42:05,560 --> 01:42:10,160
Speaker 4: are important. There's a difference between resistant and less susceptible.

1725
01:42:10,800 --> 01:42:14,960
Speaker 4: There's context there. The other thing to go back to

1726
01:42:15,240 --> 01:42:18,320
Speaker 4: Steve's question is, you know, so if you have if

1727
01:42:18,360 --> 01:42:21,320
Speaker 4: you have an animal that lives an extra two years

1728
01:42:21,360 --> 01:42:26,519
Speaker 4: longer because he has a different genotype, he's still spreading

1729
01:42:26,560 --> 01:42:30,439
Speaker 4: the preon in the environment for two additional years, right,

1730
01:42:30,520 --> 01:42:35,320
Speaker 4: So that I get it from the standpoint of that

1731
01:42:36,120 --> 01:42:39,000
Speaker 4: those deo are living longer, But if they have the disease,

1732
01:42:39,080 --> 01:42:43,720
Speaker 4: they're still contributing to a transmission. There's still you know,

1733
01:42:43,760 --> 01:42:47,360
Speaker 4: there's still preons that they're putting into the environment. And

1734
01:42:47,800 --> 01:42:52,080
Speaker 4: you know, I think my perspective from the genetics standpoint is,

1735
01:42:53,120 --> 01:42:58,479
Speaker 4: I think the scientific community recognizes that genetics may be

1736
01:42:58,720 --> 01:43:03,200
Speaker 4: one tool that we have at our disposal, but we're

1737
01:43:03,240 --> 01:43:07,120
Speaker 4: not there yet as a scientific community. And the idea

1738
01:43:07,240 --> 01:43:11,320
Speaker 4: that you're going to I look at it like antlers

1739
01:43:11,920 --> 01:43:15,439
Speaker 4: antler quality. That you're going to take deer of a

1740
01:43:15,439 --> 01:43:19,000
Speaker 4: certain antler quality and release them into the environment and

1741
01:43:19,120 --> 01:43:23,559
Speaker 4: expect them to elevate the antler quality for the entire herd.

1742
01:43:23,720 --> 01:43:28,560
Speaker 4: Given that deer whitetails are promiscuous, is kind of crazy

1743
01:43:28,720 --> 01:43:32,080
Speaker 4: to think that. And when I look at kind of

1744
01:43:32,080 --> 01:43:37,840
Speaker 4: this scenario, I thought Okay, so that the idea that

1745
01:43:37,880 --> 01:43:41,400
Speaker 4: you're going to release animals into the wild, regardless of

1746
01:43:41,600 --> 01:43:46,080
Speaker 4: whether where they go from when they're released, and that's

1747
01:43:46,160 --> 01:43:51,920
Speaker 4: going to immediately change how this population is functioning. I

1748
01:43:51,960 --> 01:43:55,240
Speaker 4: think that logically to me doesn't make sense.

1749
01:43:55,640 --> 01:43:59,240
Speaker 1: Do you think it might have that that might have

1750
01:43:59,280 --> 01:44:04,759
Speaker 1: an application if the worst fears come true, we wind

1751
01:44:04,840 --> 01:44:08,840
Speaker 1: up the areas that have CWD, whether it's twenty years

1752
01:44:08,880 --> 01:44:11,799
Speaker 1: down the road, thirty years down the road, forty whatever,

1753
01:44:12,360 --> 01:44:13,800
Speaker 1: that it's going to wind up being that you're going

1754
01:44:13,880 --> 01:44:18,120
Speaker 1: to have, you know, seventy percent prevalency, and you're going

1755
01:44:18,200 --> 01:44:21,400
Speaker 1: to have a d or two per square mile, right

1756
01:44:21,479 --> 01:44:24,639
Speaker 1: like if it lands there at that point that might

1757
01:44:24,680 --> 01:44:28,280
Speaker 1: become we might land in a place where that is

1758
01:44:28,280 --> 01:44:29,839
Speaker 1: a conversation that warrants happening.

1759
01:44:30,400 --> 01:44:35,439
Speaker 2: The thing that you know with I think within the fence,

1760
01:44:35,920 --> 01:44:39,240
Speaker 2: inside the fence, you know they're going to go down

1761
01:44:39,240 --> 01:44:43,320
Speaker 2: this path, right and if that leads to lowering risk

1762
01:44:44,040 --> 01:44:48,080
Speaker 2: of things getting out of control inside the fence, yeah,

1763
01:44:48,360 --> 01:44:51,559
Speaker 2: you know that that could be a favorable thing. I

1764
01:44:51,560 --> 01:44:57,360
Speaker 2: would not prefer it to be happening in replacement of surveillance, biosecurity,

1765
01:44:57,680 --> 01:45:01,360
Speaker 2: all of these these routine standard methods we do to

1766
01:45:01,400 --> 01:45:04,400
Speaker 2: prevent and manage disease and animal populations. That stuff has

1767
01:45:04,439 --> 01:45:09,040
Speaker 2: to invigorate and maintain in the face of this new

1768
01:45:09,080 --> 01:45:16,400
Speaker 2: tool if it's potentially useful. The fact is, right now,

1769
01:45:16,479 --> 01:45:19,479
Speaker 2: it's still in that investigation phase right. Science is going

1770
01:45:19,560 --> 01:45:22,559
Speaker 2: to take time to understand if this is a tool

1771
01:45:22,600 --> 01:45:27,240
Speaker 2: that can be leveraged within captive service populations, and so

1772
01:45:27,320 --> 01:45:30,960
Speaker 2: that research should continue. But I think people are so

1773
01:45:31,080 --> 01:45:34,479
Speaker 2: desperately wanting an answer and a solution, a silver bullet,

1774
01:45:34,520 --> 01:45:37,360
Speaker 2: whatever the case may be, that we elevate it before

1775
01:45:37,360 --> 01:45:39,320
Speaker 2: it should be elevated as a tool. It's not a

1776
01:45:39,320 --> 01:45:41,000
Speaker 2: tool in the toolbox right now.

1777
01:45:41,680 --> 01:45:45,760
Speaker 5: Because one point in time, if there was CWD, it

1778
01:45:45,840 --> 01:45:51,120
Speaker 5: was almost certainly associated with a captive servant facility. Now

1779
01:45:51,160 --> 01:45:55,160
Speaker 5: we're much further down the road, and the state of

1780
01:45:55,160 --> 01:46:01,479
Speaker 5: Oklahoma is very serious about allowing the captive service industry

1781
01:46:01,479 --> 01:46:09,719
Speaker 5: in that state to grow and sell h a deer

1782
01:46:09,840 --> 01:46:15,760
Speaker 5: that those breeders have determined to be uh tolerant or

1783
01:46:15,800 --> 01:46:19,880
Speaker 5: resistant to CWD by their own standards, meaning that they

1784
01:46:20,080 --> 01:46:21,760
Speaker 5: they're just going to live a little a little bit

1785
01:46:21,840 --> 01:46:27,920
Speaker 5: longer and then sell those outside of the fence for

1786
01:46:28,240 --> 01:46:30,120
Speaker 5: six hundred bucks a pop to people in the state

1787
01:46:30,120 --> 01:46:30,800
Speaker 5: of Oklahoma.

1788
01:46:31,640 --> 01:46:33,920
Speaker 2: Mm hmm. Yeah. And it's it's that.

1789
01:46:34,320 --> 01:46:36,479
Speaker 1: That feels a little crazy. Like if you're trying to

1790
01:46:36,479 --> 01:46:40,720
Speaker 1: control the typhoid outreak and you had you're like, well, listen, man,

1791
01:46:40,880 --> 01:46:45,479
Speaker 1: normal people get typhoid and they die in six months. Uh,

1792
01:46:45,600 --> 01:46:48,760
Speaker 1: this guy, he'll he'll die in a year, but he's

1793
01:46:48,800 --> 01:46:51,000
Speaker 1: got typhoid the whole time. We'll send them over to

1794
01:46:51,040 --> 01:46:54,880
Speaker 1: your area for for decades. It does seem like someone

1795
01:46:54,880 --> 01:46:55,719
Speaker 1: would be like, wow.

1796
01:46:56,160 --> 01:47:01,080
Speaker 2: Yeah, for decades. To your point, the whole focus of

1797
01:47:01,360 --> 01:47:05,200
Speaker 2: you know, the from from USDA state agriculture agencies and

1798
01:47:05,240 --> 01:47:09,720
Speaker 2: state wildlife agencies has been separation of captive serviands and

1799
01:47:09,800 --> 01:47:14,080
Speaker 2: wild servants. Right, we need separation of these two populations

1800
01:47:14,120 --> 01:47:18,200
Speaker 2: for disease purposes. So to start suddenly talking about the

1801
01:47:18,280 --> 01:47:23,080
Speaker 2: idea of opening the fence and releasing captive bread animals

1802
01:47:23,120 --> 01:47:27,479
Speaker 2: that are selectively bred for the traits that humans think

1803
01:47:27,520 --> 01:47:30,880
Speaker 2: are favorable, not for what mother nature thinks is favorable.

1804
01:47:31,560 --> 01:47:33,960
Speaker 2: Is you know, there's no place for that in my

1805
01:47:34,040 --> 01:47:38,080
Speaker 2: opinion right now, it's just there's we live in a

1806
01:47:38,120 --> 01:47:43,240
Speaker 2: world with wildlife disease of unintended consequences. There's always unintended

1807
01:47:43,280 --> 01:47:46,800
Speaker 2: consequences that are hard to predict, and it's it'd be

1808
01:47:46,880 --> 01:47:48,320
Speaker 2: super challenging to to.

1809
01:47:49,640 --> 01:47:50,000
Speaker 1: Have a.

1810
01:47:51,720 --> 01:47:57,760
Speaker 2: Have enough assurances that that that those animals are, you know,

1811
01:47:57,800 --> 01:47:59,200
Speaker 2: not going to put the populations.

1812
01:47:59,760 --> 01:48:03,679
Speaker 4: Is a plausible that you're releasing something else into the environment?

1813
01:48:03,960 --> 01:48:05,439
Speaker 5: Oh yeah, I mean listen to that.

1814
01:48:06,280 --> 01:48:08,320
Speaker 1: You hear that Kell's Wildlife Disease Book.

1815
01:48:08,680 --> 01:48:12,960
Speaker 5: That's that's a whole book of wildlife diseases just found

1816
01:48:12,960 --> 01:48:15,240
Speaker 5: in the southeast. We're only talking about one.

1817
01:48:15,600 --> 01:48:18,960
Speaker 1: All right, let's go. Let let's take northwest is it?

1818
01:48:19,000 --> 01:48:27,760
Speaker 1: Northwest Arkansas? Okay? Northwest Arkansas, southwest Wisconsin. Here you got prevalency.

1819
01:48:28,880 --> 01:48:31,320
Speaker 1: You know, hunters, they're the forty percent of the deer

1820
01:48:31,360 --> 01:48:33,599
Speaker 1: they kill fifty percent of the deer they kill. Have

1821
01:48:33,640 --> 01:48:40,600
Speaker 1: some CWD deer populations had a new form of mortality.

1822
01:48:40,760 --> 01:48:44,080
Speaker 1: Used to be hunting and predation. Now it's hunting predation

1823
01:48:44,280 --> 01:48:47,640
Speaker 1: c w D. CWD is killing twenty percent of the

1824
01:48:47,640 --> 01:48:50,519
Speaker 1: deer herd. The deer herd is going down, down, down,

1825
01:48:50,520 --> 01:48:55,040
Speaker 1: down down. What is the recommendation? I mean, like, like,

1826
01:48:55,200 --> 01:48:58,680
Speaker 1: what do you wind up doing with that information? I mean,

1827
01:48:58,760 --> 01:49:02,880
Speaker 1: do you say no more hunt, uh, because we're going

1828
01:49:02,960 --> 01:49:04,880
Speaker 1: to run out of deer. Do you say, hey, kill

1829
01:49:04,920 --> 01:49:09,120
Speaker 1: more deer because somehow that'll fix the problem. Like, what

1830
01:49:09,160 --> 01:49:09,960
Speaker 1: do you tell people?

1831
01:49:10,040 --> 01:49:13,559
Speaker 4: Well, as a scientist, what we told the agency is

1832
01:49:14,720 --> 01:49:16,840
Speaker 4: we don't design regulations or.

1833
01:49:16,840 --> 01:49:19,040
Speaker 1: To I know, but I'm asking you outside of that.

1834
01:49:19,160 --> 01:49:22,080
Speaker 4: Yeah, but what what we did is we told the

1835
01:49:22,120 --> 01:49:25,000
Speaker 4: agency this is where you are, you know, this is

1836
01:49:25,000 --> 01:49:29,320
Speaker 4: where you're headed, and this is how many deer per

1837
01:49:29,360 --> 01:49:32,080
Speaker 4: square mile you have, we think, and this is what

1838
01:49:32,120 --> 01:49:33,000
Speaker 4: the future looks like.

1839
01:49:33,400 --> 01:49:34,960
Speaker 1: You know how many you figured had? How many per

1840
01:49:34,960 --> 01:49:38,640
Speaker 1: square mile? About one to five depending on unbelievable. And

1841
01:49:38,640 --> 01:49:41,519
Speaker 1: then you think they're headed where It.

1842
01:49:41,600 --> 01:49:45,760
Speaker 4: Really depends on you know, various factors.

1843
01:49:45,320 --> 01:49:47,680
Speaker 1: But I think essentially lower than that.

1844
01:49:48,080 --> 01:49:52,000
Speaker 4: Well, I mean right now in in the one the

1845
01:49:52,080 --> 01:49:54,479
Speaker 4: highest prevalence area of Mark and I talked about this

1846
01:49:54,880 --> 01:49:58,719
Speaker 4: over coffee this morning. From spending time there, you can't

1847
01:49:58,880 --> 01:50:02,040
Speaker 4: you can't find deer. They're like, you can drive around

1848
01:50:02,080 --> 01:50:04,599
Speaker 4: at night, you don't see deer. You can drive around

1849
01:50:04,640 --> 01:50:08,320
Speaker 4: looking for deer and you you don't see deer. And

1850
01:50:08,400 --> 01:50:12,760
Speaker 4: so you know what Mark alluded to this earlier. I mean,

1851
01:50:12,800 --> 01:50:15,360
Speaker 4: you're going to get to some point where the population

1852
01:50:15,520 --> 01:50:19,160
Speaker 4: is going to stabilize and it's going to increase, but

1853
01:50:19,200 --> 01:50:22,680
Speaker 4: it's not going back to where it was, and so

1854
01:50:23,960 --> 01:50:28,000
Speaker 4: where it goes and how quickly it gets there could

1855
01:50:28,080 --> 01:50:32,200
Speaker 4: be influenced by regulations. So to your question, you know,

1856
01:50:33,200 --> 01:50:36,560
Speaker 4: should the agency I'm not going to tell the agency,

1857
01:50:36,600 --> 01:50:41,800
Speaker 4: but could the agency consider basically taking the foot off

1858
01:50:41,840 --> 01:50:46,760
Speaker 4: harvest and instead of liberalizing harvests like many agencies do

1859
01:50:47,160 --> 01:50:49,880
Speaker 4: thinking they're low on the curve, now when they're up

1860
01:50:49,920 --> 01:50:51,880
Speaker 4: high on the curve, do we take our foot off

1861
01:50:51,880 --> 01:50:55,639
Speaker 4: the gas? Do we reduce dough harvest? Do we you know,

1862
01:50:55,840 --> 01:50:58,479
Speaker 4: do we change our behavior because now we're in a

1863
01:50:58,520 --> 01:51:03,280
Speaker 4: new normal. And I think the answers yes that because

1864
01:51:03,760 --> 01:51:08,160
Speaker 4: you're going to try at that point, the agency's goal,

1865
01:51:08,680 --> 01:51:13,280
Speaker 4: I would think logically would be recovery. Now, what's this

1866
01:51:13,360 --> 01:51:15,880
Speaker 4: going to look like in the next few decades, And

1867
01:51:17,000 --> 01:51:19,479
Speaker 4: we know we're not going back to where we were

1868
01:51:19,520 --> 01:51:24,040
Speaker 4: forty years ago, but we have to get this population sustainable.

1869
01:51:24,880 --> 01:51:27,719
Speaker 4: And from the standpoint of you know, I'm thinking about

1870
01:51:27,760 --> 01:51:29,360
Speaker 4: this as a deer hunter. I grew up in an

1871
01:51:29,400 --> 01:51:32,320
Speaker 4: area of Virginia when at the time, if you saw

1872
01:51:32,360 --> 01:51:34,880
Speaker 4: a deer you had that was a great hunt. If

1873
01:51:34,920 --> 01:51:37,960
Speaker 4: you killed a deer. I was telling Mark, we would

1874
01:51:37,960 --> 01:51:41,920
Speaker 4: take polaroids brown deer. We shot brown deer. We would

1875
01:51:41,960 --> 01:51:44,840
Speaker 4: take a polaroid and go to school on Monday and

1876
01:51:44,960 --> 01:51:48,040
Speaker 4: show it. And it was like you you had struck

1877
01:51:48,040 --> 01:51:51,960
Speaker 4: the lottery, you know. And then I fast forward to

1878
01:51:52,760 --> 01:51:56,240
Speaker 4: where I am now and trying to raise kids and

1879
01:51:56,360 --> 01:52:00,600
Speaker 4: mentor young people through becoming deer hunters. They have to

1880
01:52:00,680 --> 01:52:03,080
Speaker 4: be successful, They have to see animals. They have to

1881
01:52:03,080 --> 01:52:06,400
Speaker 4: be able to grasp the fraternity of what you're doing

1882
01:52:06,520 --> 01:52:10,080
Speaker 4: and the success, and you build off of that, and

1883
01:52:09,520 --> 01:52:12,799
Speaker 4: then they want to learn about the process of managing

1884
01:52:12,840 --> 01:52:15,960
Speaker 4: for deer and all this that goes away if you

1885
01:52:16,000 --> 01:52:19,920
Speaker 4: can't see animals and you can't harvest animals. So as

1886
01:52:19,960 --> 01:52:23,599
Speaker 4: a deer hunter, I would look at the agency and say,

1887
01:52:24,320 --> 01:52:27,160
Speaker 4: I need you as an agency to think about how

1888
01:52:27,200 --> 01:52:30,120
Speaker 4: to get what does the future need to look like

1889
01:52:30,360 --> 01:52:33,400
Speaker 4: to recover this population to the point where I can

1890
01:52:33,680 --> 01:52:37,760
Speaker 4: I can see animals, I can harvest animals, and we

1891
01:52:37,920 --> 01:52:40,200
Speaker 4: know that prevalence is not going to stay at that

1892
01:52:40,360 --> 01:52:43,240
Speaker 4: super super high level. It's going to it's going to

1893
01:52:44,400 --> 01:52:49,040
Speaker 4: reduce through time. So yes, and we hope to get it.

1894
01:52:49,320 --> 01:52:54,120
Speaker 4: You know, it's some something where you're you're not dealing

1895
01:52:54,200 --> 01:52:56,559
Speaker 4: with what you're dealing with now, which is you know,

1896
01:52:56,680 --> 01:53:00,799
Speaker 4: every every other animal in most bucks are to positive.

1897
01:53:01,280 --> 01:53:03,320
Speaker 1: You think it will go You think it has the

1898
01:53:03,320 --> 01:53:06,679
Speaker 1: capacity to then go the other direction, to climb, climb,

1899
01:53:06,720 --> 01:53:10,080
Speaker 1: climb to fifty sixty seventy percent, and then it hit

1900
01:53:10,160 --> 01:53:12,320
Speaker 1: some point when prevalency goes down.

1901
01:53:13,280 --> 01:53:16,840
Speaker 2: I don't think it would go back down to it

1902
01:53:16,880 --> 01:53:19,360
Speaker 2: will still it'll be chronically high. You know, it might

1903
01:53:19,400 --> 01:53:21,200
Speaker 2: come up and then just kind of level out and

1904
01:53:21,240 --> 01:53:24,240
Speaker 2: then wobble back and forth as you get recruitment and whatnot.

1905
01:53:24,360 --> 01:53:25,080
Speaker 2: And that would happen.

1906
01:53:25,560 --> 01:53:30,760
Speaker 5: But the effect there, Michael, to your point is like

1907
01:53:31,360 --> 01:53:33,479
Speaker 5: people aren't gonna want to hunt in that area, and

1908
01:53:33,560 --> 01:53:37,600
Speaker 5: so like the hunting participation in that zone and the

1909
01:53:37,640 --> 01:53:43,480
Speaker 5: culture around hunting is going to suffer alongside the low population.

1910
01:53:44,360 --> 01:53:46,760
Speaker 2: And this is this is the challenge with CWD as

1911
01:53:46,800 --> 01:53:50,280
Speaker 2: you hit that that chronic, steady state of this is

1912
01:53:50,320 --> 01:53:53,840
Speaker 2: the new normal. Right. We hear a lot about EHD, right,

1913
01:53:53,880 --> 01:53:57,400
Speaker 2: and so we've had multiple large scale EHD outbreaks where

1914
01:53:57,479 --> 01:54:00,519
Speaker 2: like even in a given county thousands of deer like

1915
01:54:00,560 --> 01:54:03,719
Speaker 2: that right, in one transmission season, you might kill thousands

1916
01:54:03,720 --> 01:54:10,240
Speaker 2: of deer indiscriminately right the sky's falling, people back off

1917
01:54:10,240 --> 01:54:13,559
Speaker 2: a hunting that year. We've got multiple examples though through

1918
01:54:13,640 --> 01:54:17,679
Speaker 2: time of within a few years that population is right

1919
01:54:17,720 --> 01:54:20,880
Speaker 2: back to where it was, or even beyond where it was.

1920
01:54:21,400 --> 01:54:24,439
Speaker 1: Yeah, I'd like personally, yeah, I'm old enough where I

1921
01:54:24,479 --> 01:54:26,839
Speaker 1: personally lived through the cycle, right.

1922
01:54:27,000 --> 01:54:29,720
Speaker 2: And that's where this is so different, right, And this

1923
01:54:29,800 --> 01:54:32,160
Speaker 2: is why this matters. Is like with EHD, you can

1924
01:54:32,200 --> 01:54:33,600
Speaker 2: get on the other side of it and get back

1925
01:54:33,640 --> 01:54:37,160
Speaker 2: to the normal state. With CWD, you don't. You just

1926
01:54:37,400 --> 01:54:40,160
Speaker 2: go to this new state of normal. And that's what

1927
01:54:40,200 --> 01:54:42,520
Speaker 2: we're trying to define of what that is. And that's where,

1928
01:54:42,720 --> 01:54:46,840
Speaker 2: like you know, in Wisconsin, parts of Wisconsin, parts of Arkansas, Colorado, Wyoming,

1929
01:54:47,200 --> 01:54:49,600
Speaker 2: part of West Virginia, like trying to figure out what

1930
01:54:49,640 --> 01:54:52,640
Speaker 2: that new normal state looks like. And I do think

1931
01:54:52,640 --> 01:54:55,480
Speaker 2: it's important too to mention, like you mentioned backing off

1932
01:54:55,480 --> 01:54:59,080
Speaker 2: a doze for instance, I think it's a confusing point

1933
01:54:59,120 --> 01:55:05,400
Speaker 2: to hunters that that don't have the misfortune or pleasure,

1934
01:55:05,440 --> 01:55:08,280
Speaker 2: whatever the case may be, of of of seeing the

1935
01:55:08,320 --> 01:55:12,600
Speaker 2: bad spots and the not so bad spots if because

1936
01:55:12,600 --> 01:55:14,720
Speaker 2: you might be in an area and your interaction with

1937
01:55:14,760 --> 01:55:17,440
Speaker 2: C TOBD is very early in that scale, Right, there's

1938
01:55:17,480 --> 01:55:19,160
Speaker 2: just a couple of detections in the state or in

1939
01:55:19,160 --> 01:55:22,840
Speaker 2: a county, and what do they do. They liberalize most

1940
01:55:23,200 --> 01:55:25,760
Speaker 2: take right, And so they're they're doing the opposite. And

1941
01:55:25,840 --> 01:55:29,680
Speaker 2: I think I think many folks that's a little bit

1942
01:55:29,720 --> 01:55:34,080
Speaker 2: confusing based on you know, what phase of the disease

1943
01:55:34,200 --> 01:55:37,560
Speaker 2: you are in the management agency seemingly from like on

1944
01:55:37,600 --> 01:55:40,680
Speaker 2: the surface level doing completely different things. They're telling me

1945
01:55:40,720 --> 01:55:42,560
Speaker 2: not to shoot those, they're telling me to shoot those.

1946
01:55:43,000 --> 01:55:44,840
Speaker 2: It can be a little bit confusing, but it's all

1947
01:55:44,880 --> 01:55:47,600
Speaker 2: relative to that long protracted time scale, and in the

1948
01:55:47,680 --> 01:55:50,320
Speaker 2: early phase you're trying to prevent from getting to that

1949
01:55:50,360 --> 01:55:52,560
Speaker 2: bad phase. And that's what all those actions are doing.

1950
01:55:52,600 --> 01:55:55,800
Speaker 1: And actually, like if this place in Arkansas it's got

1951
01:55:55,960 --> 01:55:58,839
Speaker 1: one to five per square mile, I just can't picture

1952
01:55:59,400 --> 01:56:01,560
Speaker 1: that they'd still be in the mind frame of we're

1953
01:56:01,560 --> 01:56:03,960
Speaker 1: going to do earn a buck. We're going to do

1954
01:56:05,520 --> 01:56:08,920
Speaker 1: you can hunt deer through February, right, right, like, because

1955
01:56:08,920 --> 01:56:10,560
Speaker 1: you're playing with fire at that point.

1956
01:56:10,360 --> 01:56:13,440
Speaker 4: Right, and we don't know, I mean, we tried to

1957
01:56:13,440 --> 01:56:17,640
Speaker 4: simulate what prevalence would look like, you know, through time.

1958
01:56:18,080 --> 01:56:22,520
Speaker 4: But again, we we capture a five year snapshot of

1959
01:56:22,560 --> 01:56:27,000
Speaker 4: this population in Arkansas, and it was extremely well done.

1960
01:56:27,080 --> 01:56:30,040
Speaker 4: Science is rigorous, but it's five years of data and

1961
01:56:29,480 --> 01:56:34,280
Speaker 4: we're trying to predict out, you know, to Mark's point,

1962
01:56:35,640 --> 01:56:40,200
Speaker 4: prevalence gets to some level it's fifty percent right here,

1963
01:56:40,240 --> 01:56:42,680
Speaker 4: and then in the next county over it's thirty percent

1964
01:56:42,800 --> 01:56:46,200
Speaker 4: or whatever. You know, So you've already got some complexity there.

1965
01:56:46,280 --> 01:56:49,800
Speaker 4: So we're trying to inform the agency on where are

1966
01:56:49,800 --> 01:56:52,640
Speaker 4: you going to be. It's not going to disappear, but

1967
01:56:52,680 --> 01:56:55,280
Speaker 4: where are you going to be? Its prevalence going to

1968
01:56:55,320 --> 01:56:59,960
Speaker 4: remain high in parts of the landscape, It's probably going

1969
01:57:00,120 --> 01:57:03,400
Speaker 4: to remain high in other parts of the landscape. When

1970
01:57:03,440 --> 01:57:06,600
Speaker 4: it kind of starts oscillating to Mark's point and going

1971
01:57:06,680 --> 01:57:10,840
Speaker 4: up and down slightly, it very likely will remain at

1972
01:57:10,880 --> 01:57:16,400
Speaker 4: a prevalence that is at least palatable. Moving forward. You're

1973
01:57:16,440 --> 01:57:18,960
Speaker 4: still going to have situations where you're going to have

1974
01:57:19,000 --> 01:57:21,120
Speaker 4: a deer that you harvest a test positive, but it's

1975
01:57:21,160 --> 01:57:24,280
Speaker 4: not going to be at the scale at which it

1976
01:57:24,360 --> 01:57:28,080
Speaker 4: is now, which is most are prevalent.

1977
01:57:28,600 --> 01:57:31,640
Speaker 1: Do you think there's a way that you could have

1978
01:57:31,840 --> 01:57:32,960
Speaker 1: Do you think there's a way you could have a

1979
01:57:33,000 --> 01:57:36,320
Speaker 1: county Texas, Illinois? Where ever? To help, we'll say there's

1980
01:57:36,320 --> 01:57:43,360
Speaker 1: a county in Texas that has one percent prevalency today, Okay,

1981
01:57:44,800 --> 01:57:50,280
Speaker 1: is there a way that in forty years that county

1982
01:57:50,320 --> 01:57:54,320
Speaker 1: will have the same deer density and one percent prevalency.

1983
01:57:57,720 --> 01:57:59,880
Speaker 4: Let's see, that's part of why we're having this conversation.

1984
01:58:00,240 --> 01:58:05,480
Speaker 4: Those questions are incredibly difficult, almost impossible to answer because

1985
01:58:05,480 --> 01:58:10,520
Speaker 4: there's so many factors that influence the transmission and accumulation.

1986
01:58:11,280 --> 01:58:16,080
Speaker 4: I mean, we know vegetative communities, soil types, deer density,

1987
01:58:16,680 --> 01:58:22,920
Speaker 4: social behaviors, there's so many factors that influence how this

1988
01:58:23,000 --> 01:58:28,040
Speaker 4: disease is operating on the landscape that there could literally

1989
01:58:28,120 --> 01:58:31,960
Speaker 4: be a thousand different scenarios. And that's part of why

1990
01:58:32,000 --> 01:58:35,040
Speaker 4: it's so difficult to have these conversations with hunters. To

1991
01:58:35,080 --> 01:58:37,400
Speaker 4: march point is like, well, I see that this is

1992
01:58:37,880 --> 01:58:40,919
Speaker 4: occurring over here, and I see that this is occurring

1993
01:58:40,960 --> 01:58:43,720
Speaker 4: over here, and that doesn't make any sense to me.

1994
01:58:43,760 --> 01:58:47,240
Speaker 4: They should be doing the same thing. And so to

1995
01:58:47,720 --> 01:58:52,320
Speaker 4: Mark's point, you know northwest Arkansas, that the context needs

1996
01:58:52,360 --> 01:58:55,160
Speaker 4: to be that this population is so far along on

1997
01:58:55,200 --> 01:58:58,120
Speaker 4: this curve, and the disease has progressed the way it

1998
01:58:58,200 --> 01:59:01,520
Speaker 4: has here, but it's not going to operate like that everywhere.

1999
01:59:02,280 --> 01:59:04,879
Speaker 4: There's going to be situations where it's going to operate

2000
01:59:05,000 --> 01:59:08,720
Speaker 4: very differently. And then so that context is lost on

2001
01:59:08,800 --> 01:59:12,080
Speaker 4: us as hunters. I see the frustration as a hunter,

2002
01:59:12,840 --> 01:59:13,720
Speaker 4: and you see.

2003
01:59:13,560 --> 01:59:15,040
Speaker 1: If you getting frustrated over here.

2004
01:59:16,480 --> 01:59:19,600
Speaker 4: As a scientist. As a scientist, damn it. I want

2005
01:59:19,600 --> 01:59:22,280
Speaker 4: to solve I want this to be solved, and as

2006
01:59:22,280 --> 01:59:23,920
Speaker 4: a deer hunter, I don't want to deal with this.

2007
01:59:24,640 --> 01:59:26,720
Speaker 4: I don't want to deal with this. I don't want

2008
01:59:27,080 --> 01:59:29,360
Speaker 4: you to tell me that I have to behave differently.

2009
01:59:29,600 --> 01:59:32,320
Speaker 4: I don't want you to tell me that this thing

2010
01:59:32,360 --> 01:59:35,680
Speaker 4: that I've worked let's say fifty years to groom this

2011
01:59:35,760 --> 01:59:41,120
Speaker 4: piece of property suddenly is is all undermined by the yeah.

2012
01:59:41,160 --> 01:59:44,240
Speaker 4: And I don't want I don't want there to be

2013
01:59:44,280 --> 01:59:49,000
Speaker 4: conversations where there are people that are telling the public

2014
01:59:49,040 --> 01:59:52,520
Speaker 4: that the science is a lie. Don't I don't want

2015
01:59:52,560 --> 01:59:55,520
Speaker 4: to be in that discussion either. But that's where we

2016
01:59:55,560 --> 01:59:59,160
Speaker 4: are with this disease, and all of this creates confusion,

2017
01:59:59,320 --> 02:00:04,480
Speaker 4: and the confus usion creates nihilistic kind of attitudes. Nothing's worked.

2018
02:00:04,560 --> 02:00:08,040
Speaker 4: The hell with it, let's just quit. And I just

2019
02:00:08,240 --> 02:00:11,400
Speaker 4: I don't see that looking through the two lenses I'm

2020
02:00:11,440 --> 02:00:12,720
Speaker 4: looking through as an option.

2021
02:00:13,360 --> 02:00:16,480
Speaker 2: And to your one percent question, my wheels had to

2022
02:00:16,480 --> 02:00:19,760
Speaker 2: turn for a minute on that. I'm a thinker. No,

2023
02:00:20,320 --> 02:00:22,520
Speaker 2: it's not going to stay the same. You know, if

2024
02:00:22,520 --> 02:00:25,120
Speaker 2: you mother nature has done that experiment for us, right,

2025
02:00:25,840 --> 02:00:30,760
Speaker 2: you know if because it's operated you know, cryptically underneath

2026
02:00:31,040 --> 02:00:33,120
Speaker 2: hiding in plain sight, right in front of us. Right,

2027
02:00:33,200 --> 02:00:40,360
Speaker 2: no interventions, status quo, Right, what did it do? It climbs?

2028
02:00:40,600 --> 02:00:43,839
Speaker 2: I mean, you know, there's just nothing, you know, without

2029
02:00:43,920 --> 02:00:48,360
Speaker 2: without intervention, CWD has proven to us over time that

2030
02:00:48,480 --> 02:00:51,840
Speaker 2: it will do two things. It will the percentage of

2031
02:00:51,880 --> 02:00:54,680
Speaker 2: deer in that population that are infected with CWD it's

2032
02:00:54,680 --> 02:00:58,080
Speaker 2: going to increase. And then the geographic footprint of where

2033
02:00:58,120 --> 02:01:01,240
Speaker 2: it is on the landscape that's also and I increase. Like,

2034
02:01:01,280 --> 02:01:04,360
Speaker 2: those are the two things that we know with absolute

2035
02:01:04,400 --> 02:01:07,800
Speaker 2: certainty are going to happen, and that expansion.

2036
02:01:07,320 --> 02:01:08,280
Speaker 4: Is going to take time.

2037
02:01:11,160 --> 02:01:14,800
Speaker 1: So in your professional opinions, if you're in a like

2038
02:01:14,880 --> 02:01:17,760
Speaker 1: an area that has very low prevalence here they just

2039
02:01:17,760 --> 02:01:20,680
Speaker 1: found their first case, and your professional opinions is if

2040
02:01:20,920 --> 02:01:24,480
Speaker 1: your option, if you choose the option of ignore it

2041
02:01:24,560 --> 02:01:29,520
Speaker 1: and do nothing in your professional opinion, decades down the road,

2042
02:01:30,920 --> 02:01:33,920
Speaker 1: you will be living under a new normal and it

2043
02:01:33,920 --> 02:01:35,440
Speaker 1: won't just be that you wished it away.

2044
02:01:37,680 --> 02:01:40,520
Speaker 2: Correct, Yes, I mean yeah, I don't see. I don't

2045
02:01:40,560 --> 02:01:45,280
Speaker 2: see a scenario where, you know, if it's just one

2046
02:01:45,480 --> 02:01:48,480
Speaker 2: deer on the landscape right and it it dies, it's

2047
02:01:48,520 --> 02:01:51,120
Speaker 2: not consumed, and you know, somebody covers it up with

2048
02:01:51,120 --> 02:01:53,640
Speaker 2: a driveway. Okay, maybe it's sealed in there, it's not

2049
02:01:53,680 --> 02:01:56,360
Speaker 2: coming anywhere, but like, but other than that, you know,

2050
02:01:56,440 --> 02:02:00,839
Speaker 2: these will will fester, It will smolder till it's visible,

2051
02:02:01,120 --> 02:02:02,400
Speaker 2: you know, years down the road.

2052
02:02:02,880 --> 02:02:08,320
Speaker 1: Can you guys? Is it what blocks someone what prevents

2053
02:02:08,320 --> 02:02:14,840
Speaker 1: the researcher from getting some white tailed deer in captivity

2054
02:02:15,920 --> 02:02:22,200
Speaker 1: and experimenting with different transmission things, Meaning it's only you

2055
02:02:22,240 --> 02:02:24,400
Speaker 1: take a deer and it never comes in contact with

2056
02:02:24,480 --> 02:02:32,040
Speaker 1: another deer. You allow an affected deer to graze a

2057
02:02:32,720 --> 02:02:36,960
Speaker 1: one acre pasture for a week, pull that deer away

2058
02:02:36,960 --> 02:02:40,520
Speaker 1: and kill it. Then you take a known, clean deer

2059
02:02:43,760 --> 02:02:45,800
Speaker 1: that doesn't have interaction in there deer and you let

2060
02:02:45,840 --> 02:02:49,160
Speaker 1: it go graze on that pasture. And then you see

2061
02:02:49,520 --> 02:02:52,720
Speaker 1: does it get CWD from grazing on the pasture? Like,

2062
02:02:52,840 --> 02:02:54,240
Speaker 1: did it happen that way?

2063
02:02:54,920 --> 02:02:58,320
Speaker 2: That's been done, that that kind of work gets done?

2064
02:02:58,000 --> 02:03:01,720
Speaker 1: And is it? Because do you remember a few years

2065
02:03:01,720 --> 02:03:04,280
Speaker 1: ago all this hysteria came out, like if you took

2066
02:03:04,320 --> 02:03:07,280
Speaker 1: stainless steel and you like cut a deer up on

2067
02:03:07,400 --> 02:03:10,160
Speaker 1: stainless steel and then scrubbed it and bleached it, it

2068
02:03:10,200 --> 02:03:13,120
Speaker 1: could still I'm like a bullshit, do you know what

2069
02:03:13,120 --> 02:03:15,760
Speaker 1: I mean? Like theoretically sure, but like people aren't getting

2070
02:03:15,800 --> 02:03:20,120
Speaker 1: it that way or like deer aren't getting it yeah

2071
02:03:20,880 --> 02:03:24,280
Speaker 1: off stainless steel, right, like like how are they getting it?

2072
02:03:24,640 --> 02:03:26,800
Speaker 2: I mean that's a it's a you know, for as

2073
02:03:26,880 --> 02:03:29,400
Speaker 2: much as we know about chronic waste and disease, there's

2074
02:03:29,440 --> 02:03:31,840
Speaker 2: a lot we don't know about.

2075
02:03:31,440 --> 02:03:33,560
Speaker 1: Does the does the deer get it? Who only goes

2076
02:03:33,560 --> 02:03:34,720
Speaker 1: and grazes on the pasture?

2077
02:03:36,600 --> 02:03:40,480
Speaker 2: Well, well that's one possibility and it's been shown so

2078
02:03:40,480 --> 02:03:44,560
Speaker 2: so Colorado Parks and Wildlife they did a study where

2079
02:03:44,600 --> 02:03:48,440
Speaker 2: they had, you know, a decomposed carcass from a clinical

2080
02:03:48,440 --> 02:03:51,960
Speaker 2: CWD animal, Like by decomposed, I mean bleach, white bones

2081
02:03:52,440 --> 02:03:55,680
Speaker 2: gone yours put deer in there and they get infected.

2082
02:03:55,800 --> 02:03:56,120
Speaker 4: They do.

2083
02:03:56,320 --> 02:03:59,000
Speaker 2: They do, just not other deer in there. Just go

2084
02:03:59,080 --> 02:04:01,840
Speaker 2: into that clean deer in clean deer in dirty deer

2085
02:04:01,880 --> 02:04:02,240
Speaker 2: come out.

2086
02:04:02,480 --> 02:04:04,600
Speaker 1: Yeah, that's what That's what I'm saying. So this has

2087
02:04:04,640 --> 02:04:05,800
Speaker 1: been demonstrating, that has been done.

2088
02:04:05,840 --> 02:04:09,480
Speaker 2: But the exact mechanisms, right, is it eating soil, is

2089
02:04:09,480 --> 02:04:11,760
Speaker 2: it chewing on a bone? Is it getting in a plant?

2090
02:04:12,000 --> 02:04:15,400
Speaker 2: The exactly how it gets in there they don't understand yet,

2091
02:04:15,440 --> 02:04:19,480
Speaker 2: but most of the evidence suggests that it's like oor nasal.

2092
02:04:19,960 --> 02:04:21,920
Speaker 1: So, but the highest chance is oral.

2093
02:04:21,960 --> 02:04:24,640
Speaker 2: Nay, through the nose, through the mouth is the highest chance.

2094
02:04:24,640 --> 02:04:29,400
Speaker 2: But there's multiple modes of transmission, you know, potentially and

2095
02:04:29,480 --> 02:04:32,200
Speaker 2: so you know, so deer can get it through their

2096
02:04:32,240 --> 02:04:35,920
Speaker 2: social direct contacts with one another, which obvious. You know,

2097
02:04:35,920 --> 02:04:38,760
Speaker 2: a lot of transmissible diseases are like that. The thing

2098
02:04:38,880 --> 02:04:41,320
Speaker 2: the curve, one of the curveballs is that CWD has

2099
02:04:41,520 --> 02:04:45,400
Speaker 2: is exactly what we just talked about. The environment, the habitat, right,

2100
02:04:45,480 --> 02:04:49,400
Speaker 2: and that's where you know, if if you can become

2101
02:04:49,640 --> 02:04:55,800
Speaker 2: sick or infected just from the habitat, which almost acts

2102
02:04:55,840 --> 02:04:58,480
Speaker 2: like a host. When I look at through my lenses,

2103
02:04:58,560 --> 02:05:02,000
Speaker 2: I look at the landscape, I look at the habitat

2104
02:05:02,040 --> 02:05:03,960
Speaker 2: as a host, just like I look at a deer

2105
02:05:03,960 --> 02:05:07,120
Speaker 2: as a host, and the importance of that host based

2106
02:05:07,120 --> 02:05:10,520
Speaker 2: on you know, what we've seen so far in some

2107
02:05:10,600 --> 02:05:14,600
Speaker 2: literature is that the importance of that habitat as a

2108
02:05:14,600 --> 02:05:19,240
Speaker 2: as a source of infection for deer becomes greater the

2109
02:05:19,280 --> 02:05:21,960
Speaker 2: farther up that curve and the time scale you get.

2110
02:05:22,160 --> 02:05:24,280
Speaker 2: The more deer die, the more deer p and poop

2111
02:05:24,320 --> 02:05:26,960
Speaker 2: and just you know, live on the landscape, the more

2112
02:05:27,640 --> 02:05:29,880
Speaker 2: of those CBD prions are going to be put into

2113
02:05:29,880 --> 02:05:33,480
Speaker 2: that environment. And so as you get those prevalentce you know,

2114
02:05:33,800 --> 02:05:38,160
Speaker 2: of of the deer, that's a lot of it's a

2115
02:05:38,200 --> 02:05:39,680
Speaker 2: lot of p that's a lot of poop, that's a

2116
02:05:39,680 --> 02:05:42,120
Speaker 2: lot of saliva, that's a lot of flesh that goes

2117
02:05:42,120 --> 02:05:44,880
Speaker 2: onto the landscape, and those preons just stick around. And

2118
02:05:44,920 --> 02:05:48,640
Speaker 2: so trying to control prevalence, right, trying to keep lower

2119
02:05:48,720 --> 02:05:52,520
Speaker 2: down that scale will will in theory hopefully help minimize

2120
02:05:52,520 --> 02:05:53,760
Speaker 2: that environmental contamination.

2121
02:05:54,080 --> 02:05:54,360
Speaker 4: Right.

2122
02:05:54,640 --> 02:05:58,440
Speaker 2: And so, like Mike mentioned earlier, feeding and baiting, right,

2123
02:05:59,160 --> 02:06:03,120
Speaker 2: those a focal spot on the landscape put a lot

2124
02:06:03,120 --> 02:06:07,160
Speaker 2: of deer which also pee and poop and other things.

2125
02:06:07,160 --> 02:06:11,760
Speaker 2: So you're potentially depositing like sort of a hyper focused

2126
02:06:11,840 --> 02:06:15,160
Speaker 2: area of prions on the landscape that would put a

2127
02:06:15,200 --> 02:06:18,680
Speaker 2: deer at greater risk of infection if it forages there.

2128
02:06:19,520 --> 02:06:22,480
Speaker 2: That's what all those regulations try to sort of get at,

2129
02:06:22,720 --> 02:06:24,880
Speaker 2: is like, Okay, let's try to lower that risk. And

2130
02:06:24,920 --> 02:06:27,760
Speaker 2: that's why baiting and feeding are a common, you know,

2131
02:06:27,960 --> 02:06:31,440
Speaker 2: a common point of intervention for the state, because you know,

2132
02:06:31,480 --> 02:06:34,080
Speaker 2: you're just trying to break the chain of infection, right, Like,

2133
02:06:34,160 --> 02:06:37,880
Speaker 2: what can we do that will try to lower risk

2134
02:06:38,000 --> 02:06:41,600
Speaker 2: on the landscape for deer encountering CWD, whether it's from

2135
02:06:41,640 --> 02:06:43,320
Speaker 2: another deer or from its habitat.

2136
02:06:44,040 --> 02:06:47,160
Speaker 1: So much would make a handy chart. The chart would

2137
02:06:47,200 --> 02:06:50,040
Speaker 1: be zero to five, here's what you do. Try this

2138
02:06:51,640 --> 02:06:55,360
Speaker 1: five to ten or like zero to three, try this right,

2139
02:06:55,960 --> 02:07:00,320
Speaker 1: and when you get to thirty or forty, guess that's

2140
02:07:00,320 --> 02:07:02,440
Speaker 1: where I'm like, I find my confusion. Is that thirty

2141
02:07:02,520 --> 02:07:05,240
Speaker 1: or forty Is it just say like, try to enjoy

2142
02:07:06,120 --> 02:07:09,200
Speaker 1: your last bit of great deer hunting well?

2143
02:07:09,520 --> 02:07:12,840
Speaker 2: And I think that i'd say more to come soon.

2144
02:07:13,040 --> 02:07:14,560
Speaker 1: The suggestions kind of run.

2145
02:07:14,440 --> 02:07:18,240
Speaker 4: Out well, and I think that's I mean, that's part

2146
02:07:18,280 --> 02:07:21,120
Speaker 4: of why we wanted to have this conversation is that

2147
02:07:21,520 --> 02:07:26,680
Speaker 4: there is no blanket prescription for this, and that just

2148
02:07:26,800 --> 02:07:31,240
Speaker 4: creates complexity and confusion. And so that's part of why

2149
02:07:31,320 --> 02:07:34,800
Speaker 4: we wanted to have this conversation is where you're at

2150
02:07:34,920 --> 02:07:39,040
Speaker 4: on the curve matters. And some of these prescriptions that

2151
02:07:39,120 --> 02:07:42,879
Speaker 4: agencies are taking, like the banning feeding and liberalizing harvest,

2152
02:07:43,120 --> 02:07:46,280
Speaker 4: those are applicable at the bottom of the curve. But

2153
02:07:46,320 --> 02:07:48,000
Speaker 4: when you get up to the top of the curve,

2154
02:07:49,760 --> 02:07:53,280
Speaker 4: as we now see that because we the data are

2155
02:07:53,320 --> 02:07:56,200
Speaker 4: emerging from these populations that are high up the curve,

2156
02:07:56,280 --> 02:07:59,040
Speaker 4: now it's taken some time to get those fields down.

2157
02:07:59,040 --> 02:08:01,240
Speaker 5: That's an unfortunate take away from some of our nas

2158
02:08:01,360 --> 02:08:05,040
Speaker 5: air crowd. Yeah, right, like, well, you better be testing

2159
02:08:05,040 --> 02:08:07,720
Speaker 5: and turning in your deer because that's your best shot

2160
02:08:07,800 --> 02:08:11,280
Speaker 5: at being able debate again, well as if the prevalence,

2161
02:08:11,560 --> 02:08:12,640
Speaker 5: if you show the.

2162
02:08:12,560 --> 02:08:14,720
Speaker 4: Prevalence is and the bottom line is, you know, there

2163
02:08:14,760 --> 02:08:18,440
Speaker 4: was a recent summary National Academy of Science has put

2164
02:08:18,480 --> 02:08:21,400
Speaker 4: this kind of state of the state of where we

2165
02:08:21,440 --> 02:08:25,839
Speaker 4: are with CWD, and then in the preface it says,

2166
02:08:25,880 --> 02:08:32,400
Speaker 4: basically to paraphrase, albeit not perfect, efforts to manage the disease,

2167
02:08:32,560 --> 02:08:36,920
Speaker 4: the progression and spread of this disease are our option

2168
02:08:37,360 --> 02:08:40,680
Speaker 4: right now. So you have this group of scientists that

2169
02:08:41,320 --> 02:08:45,080
Speaker 4: come from all these different perspectives that collectively agree that

2170
02:08:45,200 --> 02:08:49,560
Speaker 4: it's not perfect. The management strategies that agencies are implementing,

2171
02:08:49,760 --> 02:08:52,920
Speaker 4: they're not perfect, but they are where we need to

2172
02:08:53,000 --> 02:08:57,320
Speaker 4: be right now, given how much we don't know about

2173
02:08:57,320 --> 02:08:59,440
Speaker 4: this disease, and there's just so much we don't know

2174
02:09:00,280 --> 02:09:00,960
Speaker 4: so much time.

2175
02:09:01,040 --> 02:09:04,240
Speaker 5: Yeah, because I mean, the blue Sky scenario really could

2176
02:09:04,280 --> 02:09:11,480
Speaker 5: be to be able to manipulate the new normal, right,

2177
02:09:11,520 --> 02:09:13,560
Speaker 5: So like right now you're like, yeah, we probably if

2178
02:09:13,600 --> 02:09:17,520
Speaker 5: it if the new normal levels out at forty percent prevalence,

2179
02:09:18,040 --> 02:09:20,400
Speaker 5: we're probably not going to get lower than that. But

2180
02:09:20,720 --> 02:09:24,000
Speaker 5: maybe that is the the ultimate goal is to be

2181
02:09:24,040 --> 02:09:27,480
Speaker 5: able to reduce those new normals or be able to

2182
02:09:27,600 --> 02:09:34,000
Speaker 5: manipulate them to some degree. Ideally, right if you, through

2183
02:09:34,320 --> 02:09:40,360
Speaker 5: people turning, in voluntary testing and good communication, you establish

2184
02:09:40,480 --> 02:09:44,000
Speaker 5: that new normal at five to ten percent prevalence.

2185
02:09:45,320 --> 02:09:46,160
Speaker 4: Is that yeah?

2186
02:09:46,480 --> 02:09:47,440
Speaker 5: Realistic sounding?

2187
02:09:48,080 --> 02:09:50,080
Speaker 2: I mean it all, It all sort of depends on

2188
02:09:50,120 --> 02:09:52,600
Speaker 2: where you're at in the in the scale. I think

2189
02:09:52,640 --> 02:09:55,680
Speaker 2: some of those sort of real world experiments you know,

2190
02:09:55,840 --> 02:09:59,080
Speaker 2: can can be happening, especially sort of in you know,

2191
02:09:59,200 --> 02:10:00,840
Speaker 2: in parts of the web with some of the oldier

2192
02:10:00,880 --> 02:10:04,040
Speaker 2: populations where you have okay, you're at this high prevalence.

2193
02:10:04,160 --> 02:10:08,720
Speaker 2: Now what you know, what management actions or harvest you know,

2194
02:10:09,120 --> 02:10:11,320
Speaker 2: sort of quotas, could we could we get to try

2195
02:10:11,320 --> 02:10:14,320
Speaker 2: to drop this back down? A lot of like where

2196
02:10:14,360 --> 02:10:17,000
Speaker 2: that intervention happens a little bit that the goal would

2197
02:10:17,000 --> 02:10:20,080
Speaker 2: be happened earlier, right before you get to this sort

2198
02:10:20,120 --> 02:10:24,640
Speaker 2: of thirty forty, like you're up at the five, eight, ten, twelve,

2199
02:10:24,720 --> 02:10:27,480
Speaker 2: Like okay, let's let's you know, be aggressive and try

2200
02:10:27,520 --> 02:10:30,080
Speaker 2: to knock this see if we can through harvest, through

2201
02:10:30,080 --> 02:10:35,240
Speaker 2: our hunters, you know, decrease prevalence and stabilize prevalence, right

2202
02:10:35,320 --> 02:10:37,440
Speaker 2: and and so that's where a lot of the effort

2203
02:10:37,560 --> 02:10:40,880
Speaker 2: comes in is again trying to trying to prevent the

2204
02:10:40,920 --> 02:10:43,960
Speaker 2: climb up, you know, and I think now there'll be

2205
02:10:44,040 --> 02:10:46,640
Speaker 2: like once we get to that mountaintop, I guess, and

2206
02:10:46,800 --> 02:10:49,400
Speaker 2: trying to understand the new norm. Then it's like what

2207
02:10:49,440 --> 02:10:53,040
Speaker 2: triggers are there? What levers can be pulled to manipulate that?

2208
02:10:53,440 --> 02:10:55,560
Speaker 2: Are there some you know, can we bring it back down?

2209
02:10:56,000 --> 02:10:57,880
Speaker 1: I got two yes, no questions for you guys, But

2210
02:10:57,880 --> 02:11:01,320
Speaker 1: you can only do. Yes, No, No, we don't. That's

2211
02:11:01,360 --> 02:11:04,440
Speaker 1: tough for our scientists. It always depends because it's guessing.

2212
02:11:04,560 --> 02:11:06,520
Speaker 1: It's just guessing. No one's going to hold you to this.

2213
02:11:06,960 --> 02:11:08,480
Speaker 1: It's just crystal ball. Guests.

2214
02:11:08,600 --> 02:11:10,920
Speaker 4: We both know that that is fundamentally a lie.

2215
02:11:11,560 --> 02:11:16,920
Speaker 1: In twenty five years. In twenty five years, will there

2216
02:11:17,000 --> 02:11:21,280
Speaker 1: be counties in the eastern half of the United States

2217
02:11:22,040 --> 02:11:24,200
Speaker 1: where CWD has not been detected?

2218
02:11:24,760 --> 02:11:27,839
Speaker 4: Yes, I agree, that was fast.

2219
02:11:28,440 --> 02:11:31,720
Speaker 1: If I made you a hamburger, I keep wanting to

2220
02:11:31,720 --> 02:11:37,200
Speaker 1: do this. I'm gonna I have five CWD positive deer,

2221
02:11:38,840 --> 02:11:41,280
Speaker 1: now handle them just like normal. I bone them ount

2222
02:11:41,720 --> 02:11:42,800
Speaker 1: I make burger.

2223
02:11:44,200 --> 02:11:45,560
Speaker 5: Which is a mix between the five.

2224
02:11:45,760 --> 02:11:48,760
Speaker 1: I got five CWD positives, me a burger. This is

2225
02:11:48,800 --> 02:11:51,640
Speaker 1: my this is my thing for whiles like. The only

2226
02:11:51,760 --> 02:11:56,080
Speaker 1: CWD deniers I'm interested in talking to are the ones

2227
02:11:56,640 --> 02:12:00,920
Speaker 1: that eat this burger. I take five CWD, I grind

2228
02:12:00,920 --> 02:12:03,720
Speaker 1: it all up and make a normal old burger. I

2229
02:12:03,760 --> 02:12:08,560
Speaker 1: grill that burger to medium. I know it doesn't matter

2230
02:12:08,600 --> 02:12:11,800
Speaker 1: by a girl to medium, And I'm like, would you

2231
02:12:11,840 --> 02:12:15,120
Speaker 1: like a bite of that burger? The ones that eat

2232
02:12:15,160 --> 02:12:17,800
Speaker 1: the burger, I'm like, I'd like to hear what you

2233
02:12:17,840 --> 02:12:21,960
Speaker 1: think about c w D. The ones that don't eat

2234
02:12:21,960 --> 02:12:26,120
Speaker 1: the burger, I understand how you feel, right, But the

2235
02:12:26,120 --> 02:12:27,880
Speaker 1: ones that are like, it's no big deal, I'm like,

2236
02:12:27,960 --> 02:12:31,160
Speaker 1: you eat that burger and tell me it's no big deal. Okay.

2237
02:12:31,840 --> 02:12:34,760
Speaker 1: If I made said burger, would you take a bite?

2238
02:12:36,280 --> 02:12:37,320
Speaker 2: No?

2239
02:12:37,320 --> 02:12:43,040
Speaker 1: No, you wouldn't me neither, so kills me. Would you

2240
02:12:43,040 --> 02:12:43,560
Speaker 1: eat it? Phil?

2241
02:12:44,480 --> 02:12:45,960
Speaker 4: Oh no, I don't think so.

2242
02:12:46,760 --> 02:12:52,360
Speaker 7: Cat they eat the biggest burger London five quid. It's

2243
02:12:52,360 --> 02:12:57,760
Speaker 7: so funny though, because c w D burger in London.

2244
02:12:57,480 --> 02:13:01,840
Speaker 5: Meat saying a thing like the it's in a direct

2245
02:13:02,080 --> 02:13:06,360
Speaker 5: attack on my ability to make stock, which is horrible.

2246
02:13:06,400 --> 02:13:08,320
Speaker 1: Right, you do all the ship you're not supposed to do.

2247
02:13:08,480 --> 02:13:11,160
Speaker 1: You like got the backbone and air and everything. Oh yeah,

2248
02:13:11,640 --> 02:13:12,880
Speaker 1: spine turns all why.

2249
02:13:12,840 --> 02:13:18,200
Speaker 5: And for the longest time, like all everything I did

2250
02:13:18,360 --> 02:13:21,200
Speaker 5: came out of the woods on my back, typically a

2251
02:13:21,240 --> 02:13:23,920
Speaker 5: long way, so some of this you'd be like, oh yeah,

2252
02:13:23,960 --> 02:13:27,160
Speaker 5: no bones, no problem. But then like you get that

2253
02:13:27,240 --> 02:13:30,040
Speaker 5: big bull elk and a CWD management zone right on

2254
02:13:30,080 --> 02:13:32,920
Speaker 5: the side of the road. Magically you're like, oh my god.

2255
02:13:33,960 --> 02:13:36,160
Speaker 1: I'm making like t bones and ship, you know, and

2256
02:13:36,200 --> 02:13:41,160
Speaker 1: then you get all scared about it. That's what continues

2257
02:13:41,200 --> 02:13:41,680
Speaker 1: to kill me.

2258
02:13:41,840 --> 02:13:43,880
Speaker 4: Yeeah, I totally understand that it.

2259
02:13:43,800 --> 02:13:45,840
Speaker 1: Continues to kill me. And I know that's not what

2260
02:13:45,920 --> 02:13:47,760
Speaker 1: you guys are here to talk about. But like I

2261
02:13:47,920 --> 02:13:51,920
Speaker 1: worry about, like I've proposed the two bunch of people,

2262
02:13:52,800 --> 02:13:54,360
Speaker 1: I don't know if if there's a good way to

2263
02:13:54,400 --> 02:13:56,240
Speaker 1: do it, it'd be like I wish someone would have

2264
02:13:56,240 --> 02:13:59,880
Speaker 1: started a long time ago. Go to Buffalo County, Wisconsin, Okay,

2265
02:14:01,080 --> 02:14:02,920
Speaker 1: used to be like for a while that was like

2266
02:14:02,960 --> 02:14:05,240
Speaker 1: big Bucks. You know what, big Buck Central moves around

2267
02:14:05,320 --> 02:14:08,840
Speaker 1: the country, Like big Buck Central was Alberta, big Buck

2268
02:14:08,920 --> 02:14:12,080
Speaker 1: Central was whatever, Illinois, big Buck Central Kansas. You know,

2269
02:14:12,240 --> 02:14:15,520
Speaker 1: just it hops around. There's multiple big Buck Centrals at

2270
02:14:15,520 --> 02:14:18,880
Speaker 1: any given time, but they move the places people are

2271
02:14:18,920 --> 02:14:22,280
Speaker 1: excited about move. Buffalo County had like a for a

2272
02:14:22,280 --> 02:14:26,600
Speaker 1: while they were big Buck Central, Like go into areas.

2273
02:14:26,680 --> 02:14:28,440
Speaker 1: I wish he'd done it ten years ago and start

2274
02:14:28,480 --> 02:14:33,640
Speaker 1: being like, man, let's track like Boone and Crockett Entries

2275
02:14:35,080 --> 02:14:39,640
Speaker 1: and overlay Boone and Crockett Entries county wide, statewide whatever

2276
02:14:40,120 --> 02:14:45,000
Speaker 1: with CWD prevalency and be like or some way like

2277
02:14:45,360 --> 02:14:47,280
Speaker 1: is if you just like to hunt big Bucks and

2278
02:14:47,320 --> 02:14:49,880
Speaker 1: you're an antler guy, and I'm like fifty percent antler guy.

2279
02:14:49,920 --> 02:14:54,040
Speaker 1: I'm fifty percent a burger guy. But like, are we

2280
02:14:54,160 --> 02:14:59,440
Speaker 1: seeing that, like antlers are going away from CWD. If

2281
02:14:59,440 --> 02:15:01,800
Speaker 1: someone imustrated that, it would change a lot of the

2282
02:15:01,840 --> 02:15:04,600
Speaker 1: conversation people were having. But it would need to be

2283
02:15:04,840 --> 02:15:12,320
Speaker 1: like not need to be that would that would impact

2284
02:15:12,400 --> 02:15:19,800
Speaker 1: people's behaviors, It would impact people's perspectives to see where

2285
02:15:19,800 --> 02:15:22,040
Speaker 1: it's headed. But just the uncertainty, it's just like it

2286
02:15:22,160 --> 02:15:24,040
Speaker 1: just kills me. But you know, it's been killing me

2287
02:15:24,080 --> 02:15:26,280
Speaker 1: now for how many years? Has been killing me? It's

2288
02:15:26,320 --> 02:15:28,240
Speaker 1: been killing me for my entire adult life.

2289
02:15:28,760 --> 02:15:36,400
Speaker 4: The uncertainty exactly, and the fact that this disease is

2290
02:15:36,440 --> 02:15:42,280
Speaker 4: so complex. We want answers. We don't like working under

2291
02:15:42,680 --> 02:15:47,960
Speaker 4: uncertain conditions. We don't like being told, well, you can't

2292
02:15:48,000 --> 02:15:50,960
Speaker 4: do this the way you've been doing it. Well, why, well,

2293
02:15:53,360 --> 02:15:56,240
Speaker 4: we can't give you an answer, a precise answer for

2294
02:15:56,320 --> 02:15:59,520
Speaker 4: this question that you're asking, because we don't know. And

2295
02:15:59,560 --> 02:16:03,200
Speaker 4: when some body, particularly a scientist, says we don't know.

2296
02:16:03,360 --> 02:16:06,480
Speaker 4: I've said I don't know several times today. It's because

2297
02:16:06,520 --> 02:16:10,520
Speaker 4: we don't know. And if you, I mean, all we

2298
02:16:10,560 --> 02:16:12,800
Speaker 4: can do is acknowledge what we know and what we

2299
02:16:12,800 --> 02:16:15,680
Speaker 4: can demonstrate with with rigorous data. And if we don't

2300
02:16:15,720 --> 02:16:18,680
Speaker 4: have the data, we just have to say, don't we

2301
02:16:18,720 --> 02:16:21,240
Speaker 4: don't know the answer to that. That doesn't sit well

2302
02:16:21,280 --> 02:16:23,120
Speaker 4: with us as society.

2303
02:16:23,240 --> 02:16:30,320
Speaker 1: No, That's why the one certainty I have is whatever

2304
02:16:30,360 --> 02:16:35,520
Speaker 1: we're spending on research, I'd be like, let's quadruple it.

2305
02:16:35,560 --> 02:16:37,520
Speaker 1: I'll find the money somewhere. I'll find something dumb that

2306
02:16:37,600 --> 02:16:39,320
Speaker 1: we spend money out to make that go away, so

2307
02:16:39,360 --> 02:16:41,640
Speaker 1: we can spend four times as much money on research.

2308
02:16:42,320 --> 02:16:44,000
Speaker 1: So they're like, I don't know me and my kids

2309
02:16:44,000 --> 02:16:45,680
Speaker 1: don't have to be paranoid about this ship for their

2310
02:16:45,800 --> 02:16:46,600
Speaker 1: entire adult life.

2311
02:16:46,720 --> 02:16:49,360
Speaker 4: Yeah. And one thing that doesn't help with CWD at

2312
02:16:49,360 --> 02:16:54,840
Speaker 4: all counterproductive is you have narratives, You have myths, you

2313
02:16:54,959 --> 02:16:59,120
Speaker 4: have nonsense that that gets that can Mark and I

2314
02:16:59,120 --> 02:17:01,240
Speaker 4: were talking about this on the drive over here. That

2315
02:17:01,440 --> 02:17:06,720
Speaker 4: just consumes state agency personnel and resources and time. They

2316
02:17:06,760 --> 02:17:11,360
Speaker 4: spend more time dealing with bullshit than they do trying

2317
02:17:11,400 --> 02:17:15,160
Speaker 4: to actually do their job and try to understand what's

2318
02:17:15,200 --> 02:17:18,640
Speaker 4: going on. And you put all that you know in

2319
02:17:18,720 --> 02:17:22,800
Speaker 4: a hat, and you have something that's so complex that

2320
02:17:22,959 --> 02:17:25,640
Speaker 4: is cryptic to Mark's point that you don't see it

2321
02:17:26,040 --> 02:17:30,520
Speaker 4: that it takes generations to to kind of manifest itself

2322
02:17:30,560 --> 02:17:33,440
Speaker 4: and really get going. And you and I think in

2323
02:17:33,879 --> 02:17:37,480
Speaker 4: year to year, month to month terms, and now you're talking.

2324
02:17:37,560 --> 02:17:40,480
Speaker 4: You know, now you have COVID and the skepticism of

2325
02:17:40,520 --> 02:17:43,080
Speaker 4: science in general, and you put all of that together

2326
02:17:43,160 --> 02:17:47,160
Speaker 4: and you've got a soup of crap that surrounds this disease.

2327
02:17:48,040 --> 02:17:50,720
Speaker 4: And then that's what we work in. We work in

2328
02:17:50,760 --> 02:17:55,160
Speaker 4: that soup. We're trying to provide data to inform decisions

2329
02:17:55,200 --> 02:17:59,000
Speaker 4: and have conversations that are difficult to have. Nobody wants.

2330
02:17:59,000 --> 02:18:01,240
Speaker 4: I don't want to think about this in the future,

2331
02:18:01,600 --> 02:18:04,879
Speaker 4: but it's an unfortunate reality on the landscapes that I

2332
02:18:04,959 --> 02:18:08,840
Speaker 4: hunt and I that I do science on. And so

2333
02:18:09,080 --> 02:18:12,360
Speaker 4: you put all that together and it's it's it's it

2334
02:18:12,480 --> 02:18:15,760
Speaker 4: burns your energy. And that's what you see when you

2335
02:18:15,879 --> 02:18:18,960
Speaker 4: talk to state agency personnel in these states that have

2336
02:18:19,040 --> 02:18:22,200
Speaker 4: these high prevalence rates, it is a gut punch to them.

2337
02:18:22,840 --> 02:18:26,280
Speaker 4: I mean, the morale is down. They just are like,

2338
02:18:26,600 --> 02:18:31,240
Speaker 4: what do we do, Like, there's no answer that's going

2339
02:18:31,280 --> 02:18:35,800
Speaker 4: to work today, and the skeptical public wants an answer yesterday,

2340
02:18:36,160 --> 02:18:39,080
Speaker 4: and that's just not the way that this works. And

2341
02:18:39,160 --> 02:18:43,760
Speaker 4: that is a colleague to these agency biologists. That's frustrating

2342
02:18:44,000 --> 02:18:47,760
Speaker 4: to me because I see what they're going through, and

2343
02:18:47,920 --> 02:18:50,840
Speaker 4: I see that there are people in the public saying

2344
02:18:51,640 --> 02:18:55,680
Speaker 4: that the agencies, you know, this is a positive because

2345
02:18:55,720 --> 02:18:59,280
Speaker 4: they can get federal money. For God's sake. Oh give

2346
02:18:59,360 --> 02:19:00,760
Speaker 4: me a break. I don't know.

2347
02:19:00,959 --> 02:19:03,560
Speaker 1: Yeah, that that idea, Like, I know plenty of people

2348
02:19:03,560 --> 02:19:06,680
Speaker 1: that are in wildlife management. The fact that like that,

2349
02:19:06,720 --> 02:19:10,640
Speaker 1: there's this idea that someone that some biologists, some deer

2350
02:19:10,680 --> 02:19:14,640
Speaker 1: biologists sitting there and they get a positive in his region.

2351
02:19:15,040 --> 02:19:17,640
Speaker 1: He's like, oh goodie, Yeah, now I'll be able to

2352
02:19:17,640 --> 02:19:20,560
Speaker 1: buy that new car. It's like, are you kidding me? Shoulders,

2353
02:19:20,640 --> 02:19:24,119
Speaker 1: It's so it's it's like so cynical and grotesque.

2354
02:19:24,160 --> 02:19:28,720
Speaker 4: Yeah. Yeah, it's like they just found out that think

2355
02:19:28,760 --> 02:19:31,320
Speaker 4: about it like this, You're the director of a state

2356
02:19:31,360 --> 02:19:34,760
Speaker 4: agency that just discovered CWD in your state for the

2357
02:19:34,760 --> 02:19:38,720
Speaker 4: first time. Everything just changed everything. And he's like, oh good,

2358
02:19:38,840 --> 02:19:43,360
Speaker 4: everything just changed for that that man worship And and

2359
02:19:43,400 --> 02:19:43,879
Speaker 4: if you're.

2360
02:19:43,879 --> 02:19:46,560
Speaker 5: A director of a state agency, you're already well aware

2361
02:19:46,640 --> 02:19:51,600
Speaker 5: that the subtlest changes in your state regulations for anything. Yeah,

2362
02:19:51,680 --> 02:19:54,560
Speaker 5: because quite the public uproar.

2363
02:19:56,240 --> 02:19:56,560
Speaker 2: Dollars.

2364
02:19:56,720 --> 02:19:59,240
Speaker 5: Yeah yeah, Now they're doing what with snapping turtles? I

2365
02:19:59,240 --> 02:20:02,520
Speaker 5: don't I don't care, but I got an opinion on it.

2366
02:20:02,600 --> 02:20:07,040
Speaker 4: Now everything changes for these biologists and and it trickles

2367
02:20:07,080 --> 02:20:10,080
Speaker 4: down from the director all the way to the field staff.

2368
02:20:10,520 --> 02:20:13,440
Speaker 4: Everything changes about the way they do their jobs, The

2369
02:20:13,480 --> 02:20:17,640
Speaker 4: resource flow within the states change, everything changes, and the

2370
02:20:17,680 --> 02:20:21,440
Speaker 4: idea that that is a positive. The amount of federal

2371
02:20:21,480 --> 02:20:25,280
Speaker 4: money that's allocated to deal with CWD is literally pennies

2372
02:20:25,440 --> 02:20:29,080
Speaker 4: to what it costs state agencies to deal with the

2373
02:20:29,120 --> 02:20:33,280
Speaker 4: consequences of this disease. So this this this myth that

2374
02:20:33,360 --> 02:20:37,000
Speaker 4: it's a money grab. It's ludicrous. It's absolutely ludicrous. It's

2375
02:20:37,080 --> 02:20:39,680
Speaker 4: it's it's the exact opposite of that. It is a

2376
02:20:39,760 --> 02:20:44,360
Speaker 4: money loss. It's a morale killer. It causes these state

2377
02:20:44,400 --> 02:20:49,520
Speaker 4: agency biologists to put their hands up because particularly in

2378
02:20:49,600 --> 02:20:53,600
Speaker 4: states like you see in Arkansas, where you know you

2379
02:20:53,640 --> 02:20:56,879
Speaker 4: can you can feel it, like in the room, you

2380
02:20:56,920 --> 02:21:00,440
Speaker 4: can feel it, you can feel the conversations about how

2381
02:21:00,879 --> 02:21:05,160
Speaker 4: exasperated they are. It's like, my gosh, this is where

2382
02:21:05,200 --> 02:21:07,200
Speaker 4: we're at, and this is where we're headed. And it's

2383
02:21:07,280 --> 02:21:09,920
Speaker 4: just you can feel it sucked the air out of

2384
02:21:09,959 --> 02:21:10,320
Speaker 4: the room.

2385
02:21:10,520 --> 02:21:14,600
Speaker 5: Well, I mean, you're not uncontrollable timelines, right, And it's

2386
02:21:14,640 --> 02:21:17,800
Speaker 5: like the old gentleman that you talked about, like made

2387
02:21:17,800 --> 02:21:20,920
Speaker 5: his dream become a reality. He's been planning and scheming

2388
02:21:21,000 --> 02:21:25,800
Speaker 5: on this legacy white tail property or just family ranch. Right,

2389
02:21:26,200 --> 02:21:30,080
Speaker 5: It's like how much of the planning has been done

2390
02:21:30,080 --> 02:21:33,800
Speaker 5: in the absence of real nature and real conditions.

2391
02:21:33,879 --> 02:21:34,080
Speaker 4: Right.

2392
02:21:34,200 --> 02:21:35,640
Speaker 5: But it's like, yeah, this is the way it's going

2393
02:21:35,680 --> 02:21:37,039
Speaker 5: to be, and this is the way it's going to be,

2394
02:21:37,800 --> 02:21:41,480
Speaker 5: and it just takes time. It's not going to happen

2395
02:21:41,520 --> 02:21:42,840
Speaker 5: on our timeline, no matter what.

2396
02:21:42,879 --> 02:21:45,959
Speaker 4: I think about the other side. Because I have friends

2397
02:21:46,000 --> 02:21:47,720
Speaker 4: that are on the other side. Well then what do

2398
02:21:47,720 --> 02:21:51,400
Speaker 4: we do? Nothing's working fail with it. Let's just and

2399
02:21:52,440 --> 02:21:56,400
Speaker 4: the science shows that if you can keep prevalence to

2400
02:21:56,440 --> 02:22:00,360
Speaker 4: where CWD is not a relevant source of mortality, if

2401
02:22:00,400 --> 02:22:04,680
Speaker 4: you can keep prevalence low, then the future is not

2402
02:22:04,879 --> 02:22:07,280
Speaker 4: going to look like it's going to look if you

2403
02:22:07,320 --> 02:22:09,120
Speaker 4: put your hands up in the air and turn around

2404
02:22:09,120 --> 02:22:11,040
Speaker 4: and walk off. That's just the reality.

2405
02:22:11,120 --> 02:22:13,560
Speaker 1: Yeah, that's clear. And I guess what people are going

2406
02:22:13,640 --> 02:22:17,360
Speaker 1: to be waiting on is if you don't do that

2407
02:22:18,520 --> 02:22:24,720
Speaker 1: and things go to hell what you try, and maybe

2408
02:22:24,920 --> 02:22:29,400
Speaker 1: they're sometime down the road there'll be some clarity about that. Yeah,

2409
02:22:29,680 --> 02:22:31,600
Speaker 1: But I think if you're in the low area, I'd

2410
02:22:31,680 --> 02:22:32,600
Speaker 1: aim for low.

2411
02:22:33,160 --> 02:22:35,560
Speaker 5: Right, if you like the way things are right now, yeah,

2412
02:22:35,600 --> 02:22:38,640
Speaker 5: and your best chance of getting somewhere close.

2413
02:22:38,360 --> 02:22:42,360
Speaker 2: To that is yeah. And that's where, like, you know,

2414
02:22:42,400 --> 02:22:46,240
Speaker 2: across the landscape, you know, in these areas where you know,

2415
02:22:46,280 --> 02:22:49,520
Speaker 2: we don't think CWD exists, even if it's part of

2416
02:22:49,560 --> 02:22:53,160
Speaker 2: a state that has CWD, you know, all of the

2417
02:22:53,160 --> 02:22:56,080
Speaker 2: effort and energy should be at prevention still, you know,

2418
02:22:56,120 --> 02:22:59,680
Speaker 2: I think I think there's this other narrative out there.

2419
02:23:00,560 --> 02:23:01,960
Speaker 2: You know, we look at the states. What are we

2420
02:23:02,040 --> 02:23:05,000
Speaker 2: up to? Thirty five? I don't even remember because it's changes.

2421
02:23:05,520 --> 02:23:07,280
Speaker 2: But then it's like, okay, well.

2422
02:23:07,240 --> 02:23:10,080
Speaker 1: That's thirty five states where it's detect right.

2423
02:23:10,120 --> 02:23:10,360
Speaker 4: I guess.

2424
02:23:10,360 --> 02:23:13,600
Speaker 1: So it's like okay, yeah, it's been hard to follow

2425
02:23:13,640 --> 02:23:15,760
Speaker 1: because we keep almost getting new states.

2426
02:23:15,480 --> 02:23:19,920
Speaker 2: Right, right, right, right, But you know, like it's almost

2427
02:23:20,000 --> 02:23:21,760
Speaker 2: like you know, some some people are like, oh, that

2428
02:23:21,800 --> 02:23:24,080
Speaker 2: state's positive now whatever, it's done.

2429
02:23:24,120 --> 02:23:26,640
Speaker 1: Yeah, you one, it's a bad way of thinking.

2430
02:23:26,640 --> 02:23:28,160
Speaker 2: It's a bad way of thinking about it because to

2431
02:23:28,200 --> 02:23:30,520
Speaker 2: your question earlier, Steve, about in twenty five years is

2432
02:23:30,560 --> 02:23:33,000
Speaker 2: going to be a county that's not detected in the

2433
02:23:33,040 --> 02:23:36,520
Speaker 2: state or in the in the southeast right those places

2434
02:23:36,520 --> 02:23:40,960
Speaker 2: where we know it not exists, you know, the whole

2435
02:23:41,040 --> 02:23:45,879
Speaker 2: effort of people in that area should be to prevent

2436
02:23:45,959 --> 02:23:48,640
Speaker 2: it from coming. So we often throw prevention to the

2437
02:23:48,680 --> 02:23:50,680
Speaker 2: side because it's a pain in the ass and it's

2438
02:23:51,040 --> 02:23:54,120
Speaker 2: you know it, it interferes with our way of doing

2439
02:23:54,200 --> 02:23:56,440
Speaker 2: things and what we want to do and how we've

2440
02:23:56,440 --> 02:23:59,959
Speaker 2: done it in the past. But the alternative is not great.

2441
02:24:00,200 --> 02:24:02,720
Speaker 2: I would much rather live in a in a shroud

2442
02:24:02,760 --> 02:24:06,760
Speaker 2: of prevention than one of reaction and frustration and control.

2443
02:24:07,080 --> 02:24:09,760
Speaker 1: Meaning the fight shouldn't start when you find your first case.

2444
02:24:09,800 --> 02:24:11,880
Speaker 1: The fight should start before you find your first kiss.

2445
02:24:11,920 --> 02:24:13,920
Speaker 4: An excellent point, very good point.

2446
02:24:14,040 --> 02:24:16,960
Speaker 1: Yeah, all right, guys, we got to wrap up. Man.

2447
02:24:17,280 --> 02:24:19,800
Speaker 1: I appreciate you coming on, thank you for having me,

2448
02:24:19,920 --> 02:24:25,320
Speaker 1: and I appreciate just like the you're talking about wildlife

2449
02:24:25,320 --> 02:24:30,240
Speaker 1: managers being frustrated, you know, like, I appreciate you guys

2450
02:24:30,320 --> 02:24:34,600
Speaker 1: entertaining a conversation that just like is it's hard, It

2451
02:24:34,640 --> 02:24:36,840
Speaker 1: is like it is frustrating because like you're coming on,

2452
02:24:37,240 --> 02:24:41,400
Speaker 1: you know, you're coming on with with having done research

2453
02:24:41,440 --> 02:24:44,119
Speaker 1: and expert opinion, and you're just in a situation where

2454
02:24:44,160 --> 02:24:45,880
Speaker 1: you got to have a lot of like I don't know,

2455
02:24:46,320 --> 02:24:48,640
Speaker 1: I don't know, it's got to be feel a lot

2456
02:24:48,640 --> 02:24:52,440
Speaker 1: better when you come on and be like here's the deal, Yeah,

2457
02:24:52,760 --> 02:24:54,320
Speaker 1: do X do why we're gonna do Z.

2458
02:24:54,480 --> 02:24:55,200
Speaker 4: We're gonna fix this.

2459
02:24:55,560 --> 02:24:59,640
Speaker 5: But but what is like the at home takeaway right

2460
02:24:59,680 --> 02:25:02,000
Speaker 5: now for folks going into their deer season.

2461
02:25:02,640 --> 02:25:06,920
Speaker 2: I always say, I mean, and I appreciate you for

2462
02:25:07,280 --> 02:25:11,760
Speaker 2: entertaining this topic. Yeah, with you know, your audience, because

2463
02:25:11,760 --> 02:25:15,680
Speaker 2: I think I think as much as individuals can just

2464
02:25:15,920 --> 02:25:20,360
Speaker 2: be engaged care you know, and and understand sort of

2465
02:25:20,400 --> 02:25:23,560
Speaker 2: the the you know, it's not you know, some of

2466
02:25:23,600 --> 02:25:28,640
Speaker 2: these restrictions and quirky regulations and confusion around that. It's

2467
02:25:28,680 --> 02:25:31,360
Speaker 2: it's all from a place of trying to prevent a

2468
02:25:31,360 --> 02:25:34,600
Speaker 2: really big problem in the future and so trying to

2469
02:25:34,879 --> 02:25:37,600
Speaker 2: just you know, embrace that and you know, be an

2470
02:25:37,640 --> 02:25:42,440
Speaker 2: active participant in what the wildlife agencies need. That's one

2471
02:25:42,480 --> 02:25:44,039
Speaker 2: of the things I always lean into.

2472
02:25:44,720 --> 02:25:47,280
Speaker 4: And be willing to. I mean, from my perspective, I

2473
02:25:47,560 --> 02:25:51,760
Speaker 4: talk to hunters all the time that that have various

2474
02:25:51,840 --> 02:25:54,840
Speaker 4: narratives that we've talked about today, their minds, you know,

2475
02:25:54,879 --> 02:25:58,959
Speaker 4: their mindset is different than mine. I don't expect you

2476
02:25:59,000 --> 02:26:01,960
Speaker 4: to listen to this podcast, ask and change everything you

2477
02:26:02,040 --> 02:26:05,480
Speaker 4: think about CWD. But if you will just sit back

2478
02:26:05,720 --> 02:26:10,120
Speaker 4: and just think carefully about the issues we've talked about

2479
02:26:10,160 --> 02:26:13,360
Speaker 4: and recognize that there's no there's no answer, there's no

2480
02:26:13,480 --> 02:26:16,160
Speaker 4: clear answer right now. This is going to take time.

2481
02:26:16,280 --> 02:26:20,120
Speaker 4: There's always context involved, But if you're willing to at

2482
02:26:20,200 --> 02:26:24,120
Speaker 4: least entertain that there is work going on that's showing

2483
02:26:24,160 --> 02:26:26,200
Speaker 4: these things that we've talked about that this is a

2484
02:26:26,440 --> 02:26:29,120
Speaker 4: this is a problem that is not going to just

2485
02:26:29,200 --> 02:26:33,959
Speaker 4: go away. To Mark's point, you not getting it is

2486
02:26:34,680 --> 02:26:38,800
Speaker 4: in your area is important and so I kind of

2487
02:26:38,800 --> 02:26:41,039
Speaker 4: look at it from you know, the deer season framework

2488
02:26:41,160 --> 02:26:44,640
Speaker 4: is one I don't want CWD where I'm trying to hunt,

2489
02:26:45,280 --> 02:26:48,440
Speaker 4: and if I have it there, then I'm going to

2490
02:26:48,520 --> 02:26:51,680
Speaker 4: have to behave differently because the agency is going to

2491
02:26:51,720 --> 02:26:55,640
Speaker 4: implement changes to try to keep prevalence low, and that

2492
02:26:55,800 --> 02:26:59,720
Speaker 4: is key. Not getting it and keeping prevalence low if

2493
02:26:59,760 --> 02:27:02,440
Speaker 4: you have it, That's that's kind of where I see it.

2494
02:27:04,160 --> 02:27:06,560
Speaker 1: All right, man. Thanks again, guys, thank you well, thank

2495
02:27:06,600 --> 02:27:09,640
Speaker 1: you for the book Field Manual of Wildlife Diseases in

2496
02:27:09,680 --> 02:27:14,000
Speaker 1: the Southeastern United States, which my first response upon seeing

2497
02:27:14,040 --> 02:27:15,560
Speaker 1: it is it shouldn't be that thick.

2498
02:27:17,640 --> 02:27:18,680
Speaker 2: Unfortunately it is.

2499
02:27:19,280 --> 02:27:22,119
Speaker 1: Oh yeah, I'm gonna read this to my kids at night.

2500
02:27:22,440 --> 02:27:26,120
Speaker 4: I wouldn't recommend that. Yeah, oh, thanks man.

2501
02:27:26,640 --> 02:27:30,240
Speaker 1: Yeah, if you want a real uh real eyeburner, I

2502
02:27:30,280 --> 02:27:31,160
Speaker 1: don't know what you call this.

2503
02:27:32,600 --> 02:27:35,720
Speaker 5: Well, it's a professional level book based off the intensity

2504
02:27:35,720 --> 02:27:36,879
Speaker 5: of the pictures.

2505
02:27:36,879 --> 02:27:39,440
Speaker 1: Right, it's a professional book. When I'm taking a non

2506
02:27:39,480 --> 02:27:43,080
Speaker 1: professional gander through here, and it's an alarming collection of

2507
02:27:43,080 --> 02:27:45,240
Speaker 1: photo my kids would like.

2508
02:27:45,240 --> 02:27:49,080
Speaker 4: Yeah, we're song okay. I was actually gonna ask Marca,

2509
02:27:49,680 --> 02:27:53,640
Speaker 4: there's a there's a disease. There's something that causes wild

2510
02:27:53,680 --> 02:27:56,640
Speaker 4: turkey feathers to be like soaking wet with like an

2511
02:27:56,640 --> 02:27:57,920
Speaker 4: oil all over them.

2512
02:27:58,080 --> 02:28:00,640
Speaker 2: Whoa that I haven't seen that.

2513
02:28:00,680 --> 02:28:01,400
Speaker 1: It's not in this book.

2514
02:28:01,400 --> 02:28:03,760
Speaker 4: It's not in that book. And I'm certain this book

2515
02:28:03,840 --> 02:28:06,600
Speaker 4: isn't complete. You haven't said you haven't sent this one, mate. No,

2516
02:28:06,640 --> 02:28:08,760
Speaker 4: we caught we caught a hen in Louisiana in two

2517
02:28:08,800 --> 02:28:12,640
Speaker 4: thousand and eight, and she was soaking wet like not wet.

2518
02:28:13,200 --> 02:28:17,040
Speaker 4: She had this oil all over her to the point

2519
02:28:17,040 --> 02:28:21,320
Speaker 4: where she looked terrible, and I put her in a

2520
02:28:21,360 --> 02:28:24,240
Speaker 4: capture box and it was greasy on the inside of

2521
02:28:24,240 --> 02:28:26,560
Speaker 4: the box. She was part of a brouge. She had

2522
02:28:26,560 --> 02:28:30,039
Speaker 4: polts with her and I've searched for that, and I

2523
02:28:30,280 --> 02:28:32,080
Speaker 4: meant to ask you the other day about that.

2524
02:28:32,120 --> 02:28:33,360
Speaker 2: And is that your only encounter?

2525
02:28:33,600 --> 02:28:34,680
Speaker 4: Only encounter ever?

2526
02:28:35,160 --> 02:28:37,360
Speaker 2: Weird things happen. I mean, is there any chance she

2527
02:28:38,000 --> 02:28:38,800
Speaker 2: got into.

2528
02:28:38,560 --> 02:28:44,879
Speaker 4: A been a ben of oil whales? She was country,

2529
02:28:44,920 --> 02:28:47,520
Speaker 4: so she could have encountered anything, right, right, Yeah, she

2530
02:28:47,680 --> 02:28:48,320
Speaker 4: ran through.

2531
02:28:48,200 --> 02:28:51,760
Speaker 5: The defat Friar before she got right, yeah, yeah, anyway,

2532
02:28:51,879 --> 02:28:52,600
Speaker 5: good lord.

2533
02:28:52,760 --> 02:28:55,840
Speaker 2: This book, now we we make that for that's intended

2534
02:28:55,840 --> 02:28:58,400
Speaker 2: for field biologists, so those you know, most of our

2535
02:28:58,760 --> 02:29:02,160
Speaker 2: agency personnel in this southeast kind of refer to that.

2536
02:29:02,200 --> 02:29:05,520
Speaker 2: So it's written for biologists, but any hunter would enjoy it.

2537
02:29:05,520 --> 02:29:08,600
Speaker 5: I think put this in the camp or un take

2538
02:29:08,680 --> 02:29:13,000
Speaker 5: my buddies read kid hunting with us this year and

2539
02:29:13,040 --> 02:29:14,400
Speaker 5: be like, well, you just got to flip through that

2540
02:29:14,520 --> 02:29:16,439
Speaker 5: first before we But there's also.

2541
02:29:18,640 --> 02:29:21,360
Speaker 2: There's also some normal stuff in there, because disease is

2542
02:29:21,360 --> 02:29:24,120
Speaker 2: a part of life with wildlife, so you can have

2543
02:29:24,160 --> 02:29:26,039
Speaker 2: a healthy deer that also has a disease, and so

2544
02:29:26,080 --> 02:29:28,720
Speaker 2: there's lots of you know, parasites we've commonly seen in

2545
02:29:28,760 --> 02:29:31,480
Speaker 2: wildlife and other things that would be of interest for

2546
02:29:31,640 --> 02:29:33,080
Speaker 2: hunters when they're dressing an animal.

2547
02:29:33,120 --> 02:29:36,480
Speaker 1: I'm quite enjoying this book, man. All right, guys, thanks good,

2548
02:29:36,600 --> 02:29:37,960
Speaker 1: thank you, thank you, y'all.