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Speaker 1: You're listening to the Sportsman's Nation podcast network brought to

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Speaker 1: you by Interstate Batteries. Interstate Batteries has been a proud

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Speaker 1: visit their website Interstate Batteries dot com. Interstate Batteries Outrageously Dependable.

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Speaker 1: My name is Clay Nukeolman. I'm the host of the

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Speaker 1: Bear Hunting Magazine podcast. I'll also be your host into

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Speaker 1: the world of hunting the icon of the North American

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Speaker 1: Wilderness Fair. We'll talk about tactics, gear conservation. We will

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Speaker 1: also bring you into some of the wildest country on

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Speaker 1: the planet. Chasing bar Colby and I traveled up to Springfield,

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Speaker 1: Missouri to meet with Laura Connolly, who is the furbear

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Speaker 1: biologists for the Missouri Department of Conservation and Missouri Department

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Speaker 1: of Conservation biologists Josh Wisdom, and we talked about Missouri

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Speaker 1: black bears there right now in consideration of developing a

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Speaker 1: very limited hunting season in Missouri. We talked about all

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Speaker 1: the nuts and bolts and absolutely nerd out nerd out

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Speaker 1: on far biology in a very interesting conversation. And I

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Speaker 1: want to say, just off the off the get go.

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Speaker 1: We say this in the podcast, but for fear of

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Speaker 1: it getting lost inside all the incredib dorble details of

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Speaker 1: bar biology, is that really wants to be celebrated inside

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Speaker 1: of this is that there are bears in the Missouri

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Speaker 1: Ozarks and they haven't been there in a in a

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Speaker 1: long time, or there was there was a stretch of

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Speaker 1: time when they were basically extirpated, and so as hunters

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Speaker 1: were not just celebrating or even primarily celebrating that they

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Speaker 1: are considering allowing people to hunt them. What we're celebrating

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Speaker 1: is that they're there. And I think that would be

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Speaker 1: the heart of most people that are hunters, is that

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Speaker 1: it's a celebration of a wild animal living in a

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Speaker 1: place in a time when you know, the habitat is

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Speaker 1: under assault by civilization essentially, and um so that's the celebration.

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Speaker 1: Really great podcast with Laura Connolly and John Wisdom. Be

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Speaker 1: sure to check out Northwoods Bear Products. These guys have,

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Speaker 1: We've they've been with us for a long time in

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Speaker 1: Bear Hunting Magazine and we've used their products all over

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Speaker 1: North America. And if you're gonna be baiting bears, it

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Speaker 1: only makes sense to be using some commercial sense, and

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Speaker 1: uh check them out, check them out. Hey, it's the bear.

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Speaker 1: The spring bear season is essentially over in most places

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Speaker 1: right now, and so we're already looking forward to fall

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Speaker 1: bear baiting and uh so check out north Woods Bear

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Speaker 1: Products and check out W Hunting Supply for all your

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Speaker 1: hound related needs, garment related needs. And these guys also

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Speaker 1: have a podcast. Check out the W Hunting Supply podcast

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Speaker 1: which is primarily about hound hunting. And lastly, our buddies

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Speaker 1: at the Western Bear Foundation based out of Cody, Wyoming.

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Speaker 1: These guys are nonprofit hunting conservation organization being a voice

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Speaker 1: for fare conservationists bared lovers all over North America. We

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Speaker 1: are also hunters, So check out our buddies and enjoy

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Speaker 1: this podcast with some professional biologists out of Missouri, we're

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Speaker 1: recording Better Honey magazine podcast. Hey, we're in uh, we're

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Speaker 1: in Springfield, Missouri, and uh, I've got Laura Conley and

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Speaker 1: Josh Wisdom. Man, it's great that you guys have your

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Speaker 1: names on your shirts. I forget sometimes myself. Uh, and

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Speaker 1: I've got Colbe moorehead the baron Tech. Yeah yeah, now

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Speaker 1: this is uh, thank you guys so much for driving down. So, Laura,

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Speaker 1: you are based out of Columbia, Missouri, which is two

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Speaker 1: and a half hours from here, just about yep. Yeah,

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Speaker 1: smack in the middle of the state. Yeah. Yeah, yeah.

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Speaker 1: And Josh you're at home. Yep, yep. We're here in

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Speaker 1: our in my office here in Springfield. So I'm usually

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Speaker 1: here about every day. Yeah, okay. So what we're gonna

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Speaker 1: be talking about is Missouri black bears, which is so Laura,

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Speaker 1: just you are what is your title with the Missouri Department?

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Speaker 1: So I am the furbear biologist for the Missouri Yeah, yeah,

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Speaker 1: for for MDC here and so, bears are one of

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Speaker 1: the species that I work with, and so I work

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Speaker 1: with coyotes, fox, you know, raccoons, all the other fur

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Speaker 1: bears also, um, but as of late, bears typically take

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Speaker 1: up a substantial portion of my time just with the

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Speaker 1: research project that we've got going on, and just everything

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Speaker 1: that's going on with bears right now here. So do

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Speaker 1: you have so you're biologists? I mean you you have

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Speaker 1: a degree in wild bology. I do. Yeah. So I

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Speaker 1: I got my bachelor's degree from Northern Illinois University and

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Speaker 1: then my master's degree from Southern Illinois University, where I

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Speaker 1: studied long tailed weasels. So I started out at the

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Speaker 1: tiniest end of the carnivore spectrum and and now here

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Speaker 1: I am working there at the top. Yeah. I think

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Speaker 1: there's a few songs about that, starting at the bottom end. Um.

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Speaker 1: So your history with fur bears? Um? Are you a trapper?

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Speaker 1: You know? I know I'm not. And I did not

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Speaker 1: grow up in a hunting family or anything like that.

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Speaker 1: I had always had an interest in the outdoors and

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Speaker 1: and all through I would say, like, you know, junior

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Speaker 1: high in high school, my friends would just tease me

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Speaker 1: to no end that I was going to be a

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Speaker 1: park ranger, tan uniform, tan hat, and you know, they'd

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Speaker 1: find pictures in books and they'd write my name on

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Speaker 1: it and everything, and um, and so, I mean I

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Speaker 1: always had an interest in getting into some kind of

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Speaker 1: natural resource field, and then kind of through college kind

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Speaker 1: of honed in that interest on wanting to work with

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Speaker 1: carnivores and and really became interested in wildlife management and

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Speaker 1: how research informs management decisions and things like that and so. UM.

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Speaker 1: The weasel project that I worked on was State of

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Speaker 1: Illinois funded project, and so it was one of those

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Speaker 1: things that kind of tied into the work that they

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Speaker 1: were doing for the state. And then from graduate school,

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Speaker 1: I ended up taking a job in Massachusetts as the

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Speaker 1: fur bear biole just there. So I was out east

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Speaker 1: for about eight and a half years, UM working on

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Speaker 1: a very similar, very similar job, so coyotes, raccoons, all

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Speaker 1: all the fur bears that they had out there, um,

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Speaker 1: and then inherited their bear project out there. Somebody retired

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Speaker 1: and I was able to kind of move into the

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Speaker 1: bear project. So um, I've been working with bears at

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Speaker 1: this point for just a little over ten years. That's

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Speaker 1: pretty cool. So you're you're like it. I think it's

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Speaker 1: an interesting transition going from a non hunting family with

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Speaker 1: an just a general interest in outdoors and animals and

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Speaker 1: then moving into uh a place where you're making significant

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Speaker 1: you know, at least contributing significantly to wildlife management decisions

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Speaker 1: and being based in the hunting world. Like what was

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Speaker 1: that transition like for you? You know, there was I

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Speaker 1: mean there was a learning curve there and and during

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Speaker 1: my whole you know, graduate schooling, I was really lucky

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Speaker 1: that I had a lot of friends who were very

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Speaker 1: willing to take me out, show me the ropes, take

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Speaker 1: me hunting and stuff like that. And then, um, you know,

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Speaker 1: my my husband now basically introduced me to all of

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Speaker 1: big big deer hunter, big turkey hunter. Um. Where he

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Speaker 1: grew up in northern Illinois also kind of um, a

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Speaker 1: little bit more rural area than where I had come from.

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Speaker 1: And so um, he came out to Massachusetts with me

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Speaker 1: and adjusted to hunting public land out there where you know,

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Speaker 1: it's limited availability and a lot of people packed into

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Speaker 1: a little bit of area and stuff like that, and

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Speaker 1: so um, we'd always wanted to get back to the Midwest,

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Speaker 1: all of our families in the Midwest, and so we

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Speaker 1: were able to move our family to Missouri. And so

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Speaker 1: you went from Massachusetts to this jomb this and this

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Speaker 1: was the furbear biologist. That's the state of Missouri, that's right.

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Speaker 1: So you know, the this is this is a narrative

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Speaker 1: that I've heard, which I think it's probably true, is

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Speaker 1: that in wildlife management sometimes we are finding people getting

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Speaker 1: into wildlife management for the states that don't have a

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Speaker 1: background in hunting, and that can sometimes negatively if they're

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Speaker 1: anti hunting, if they're I don't know how to say that. Uh,

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Speaker 1: you know, like some people are getting into wildlife management

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Speaker 1: that have negative connotations of hunting. Maybe that's a simple

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Speaker 1: way to say that. Have you heard that before? I mean,

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Speaker 1: I think that's one of those ideas that some folks have.

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Speaker 1: Whether it's grounded in truth, I don't know. I mean,

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Speaker 1: that's not something that that I've run into in in

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Speaker 1: my career. I mean and for me, yeah, and and

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Speaker 1: for me, I mean in the fur bearer world, Um,

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Speaker 1: that was least something that was um, I wouldn't say

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Speaker 1: a challenge, but an adjustment for working with the Trappers

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Speaker 1: Association and not being a trapper myself. I think they

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Speaker 1: had a lot of questions as to you, well, well

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Speaker 1: how do you feel about trapping and for barrow management

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Speaker 1: and things like that, and so um. I mean I think,

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Speaker 1: you know, I've relied on on a lot of fellow

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Speaker 1: biologists and you know, hunters and trappers to help, you know,

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Speaker 1: build up that knowledge base and that background and things

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Speaker 1: like that. And and for me, you know, my interest

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Speaker 1: is really understanding how you know best to manage the

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Speaker 1: resources and so use use, use the research and monitoring

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Speaker 1: that we have available to us, and then make informed

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Speaker 1: management decisions through that. So, yeah, that's an incredible story.

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Speaker 1: That's great. Uh, that is that's really cool. Josh. Yes,

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Speaker 1: tell us about yourself, ma'am, what you do and well,

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Speaker 1: So I am one Missouri native. I'm originally from what

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Speaker 1: folks call the Booth Hill, so the southeast Cortera Missouri.

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Speaker 1: Been hunting all my life, started out when I was

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Speaker 1: little bitty, doing doves and squirrel hunts and public land

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Speaker 1: hunter my whole life. We don't own any property, so

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Speaker 1: we used to go to where I know you've been recently,

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Speaker 1: the Van Buren Current River area. So that was where

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Speaker 1: we would go through deer season hunting. So, I mean

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Speaker 1: that was about an hour and a half two hour

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Speaker 1: drive for us. Uh so, so a local guy. But

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Speaker 1: I went to school at the University of Missouri in Columbia.

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Speaker 1: I've got a four year degree wildlife management degree. I

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Speaker 1: don't have my master's. I worked for a federal agency

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Speaker 1: that does wildlife uh, we might call it damage control,

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Speaker 1: USDA Wildlife Services. I worked for them for eight years

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Speaker 1: before I came to the department. So during that time,

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Speaker 1: I worked as an airport biologist at Chicago Hair. I

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Speaker 1: did that for three years. I did a lot of

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Speaker 1: work with urban deer, uh I did. I've done work

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Speaker 1: with Farrellhall Control full time. I've done industrial bird work

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Speaker 1: and so kind of the opposite side of the coin.

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Speaker 1: If what Laura was kind of talking about, you've got

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Speaker 1: wildlife management as a as a rule when you go

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Speaker 1: to typical school, you know, how can we make more

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Speaker 1: We need to make more habitat, We need to make

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Speaker 1: the populations grow well doing the type of work that

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Speaker 1: I used to do, especially uh, you're looking at the opposite, Well,

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Speaker 1: what can I do to make this shrink? What can

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Speaker 1: we make this less inviting? And like so airport environments

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Speaker 1: that kind of thing. You know, it's you don't want

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Speaker 1: a bunch of You're trying to get them away. Yeah,

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Speaker 1: you don't want a bunch of private land biologists. I

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Speaker 1: want coming to my plan. But yeah, so I did

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Speaker 1: that for a long time, and so now with the department,

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Speaker 1: I'm my job titles. I'm a wildlife damage biologist, and

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Speaker 1: uh you know, so I don't do law enforcement, but

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Speaker 1: I helped private landowners a lot, especially I'm not tied

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Speaker 1: to an area. I don't do food plots. I don't

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Speaker 1: work on your pond. People generally call me when they

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Speaker 1: have a problem with In this case, we're gonna talk

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Speaker 1: about bears or you've got crop damage Missouri. Farrell hogs

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Speaker 1: aren't wildlife, but Farrell hog damage that kind of falls

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Speaker 1: in my range. Uh So, so things like that all

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Speaker 1: the way up to hey, you know, we've got a

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Speaker 1: bunch of geese on our golf course here in town.

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Speaker 1: What can we do about it? You know, they're closing

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Speaker 1: our swim beach, that kind of thing. So so I'm

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Speaker 1: kind of the opposite out of the coin. But but yeah,

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Speaker 1: I mean wildlife damage, whether it's you know, actual financial losses. Yeah,

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Speaker 1: sometimes people just need some some talking to, just some

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Speaker 1: education about you know, that's really not that big of

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Speaker 1: a deal to have a black snaking or driveway or whatever.

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Speaker 1: That's not gonna hurt anybody. So kind of runs the

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Speaker 1: whole gamut of some serious problems to just people need

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Speaker 1: some education. Yeah, that's great. You know, coming from Arkansas,

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Speaker 1: we have always had a very high reputation of the

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Speaker 1: Missouri Department of Conservation. I mean, like for no bias.

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Speaker 1: What I mean, when I was a teenager and I

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Speaker 1: remember my dad took me to Missouri turkey hunting, and

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Speaker 1: I remember him telling me, he's like, Missouri is really good.

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Speaker 1: They they they managed their wildlife well. And I mean

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Speaker 1: this was long before media or I had any reason

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Speaker 1: to think that. But so, yeah, the Missouri Department of

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Speaker 1: Conservation has a very good national reputation, which you guys

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Speaker 1: would know. I mean just for seven I've I've lived

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Speaker 1: all over the Midwest with different jobs, Iowa, Illinois, Indiana,

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Speaker 1: and I mean so even as when I was a

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Speaker 1: normal person quote unquote, I agree. I think Missouri has

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Speaker 1: got a good setup when you lived in other states,

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Speaker 1: it's it's got a lot of going for it. Yeah,

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Speaker 1: national leader, right, I mean, that's that's what you think

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Speaker 1: of in a lot of cases when you think of

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Speaker 1: m d C and conservation and stuff. So that's that's good, um, cold,

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Speaker 1: But any any questions for him personal I'm just wondering

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Speaker 1: why I rolling you on one podcast. Yeah, I know

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Speaker 1: about furbears. Then where I hear. Okay, so when we

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Speaker 1: drove up here, Shepard said there's a con and he

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Speaker 1: was talking about a con on a sign and I said,

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Speaker 1: I breaked, and I said, Sheppard, you gotta be more clear.

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Speaker 1: I said, if you see a con on a sign,

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Speaker 1: you gotta say I see a coon on a sign,

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Speaker 1: because I'll slam the brakes on this truck and we'll

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Speaker 1: have a wreck in the downtown Spring for the salon

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Speaker 1: with three cubs in the middle of the day yesterday,

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Speaker 1: walking up we had one climb up our tree in

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Speaker 1: our backyard and my daughter was just like all right.

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Speaker 1: We sat there and watched it for a while. So yeah, yeah,

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Speaker 1: pretty incredible animals. Um black bears, Laura, give me, give

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Speaker 1: me a history, like so starting from scratch, like nobody

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Speaker 1: like just assuming that. Well, let me back up. People

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Speaker 1: don't have a context for bears in the Mid South.

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Speaker 1: I guess we could call this the Mid South like

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Speaker 1: on a national scale, and especially several years ago, when

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Speaker 1: people would hear that I was from Arkansas, was bear

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Speaker 1: hunting blow their mind? And then when I started, you know,

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Speaker 1: when Oklahoma started hunting bears and and having robust bear populations.

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Speaker 1: People were shocked, and uh, I would imagine it's kind

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Speaker 1: of the will be the same thing when people start

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Speaker 1: hearing about Missouri bears. But I mean historic range of

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Speaker 1: the black bear. This is the premo historic range black bear.

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Speaker 1: But so so take us back to um, just just

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Speaker 1: your your story of or what you know of when

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Speaker 1: they had them, how they lost them, and now we

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Speaker 1: got them back. So I think, you know the story

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Speaker 1: of bears in Missouri is similar to a lot of

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Speaker 1: other places that um, you know, a lot of it

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Speaker 1: stemmed from habitat loss and unregulated harvest and things like that.

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Speaker 1: But for us here, um, you know, bears were found

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Speaker 1: throughout the state. You know, you read early settlers journals

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Speaker 1: and things like that, and and they were found throughout

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Speaker 1: forested areas of the state. Um, but by the early

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Speaker 1: nineteen hundreds, I mean, their numbers were driven really low.

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Speaker 1: And at that point, you know, the Ozark Forest had

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Speaker 1: been logged and there was just large scale habitat changes

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Speaker 1: and then unregulated harvest on the animals. And so basically

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Speaker 1: here in Missouri. Uh, really, by the early nineteen hundreds,

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Speaker 1: it was thought that bears had been extirpated from the state,

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Speaker 1: you know, so that's right, yeah, locally extincted, and there

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Speaker 1: were still rumors of bears, and you know, you'd hear

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Speaker 1: a few reports in the fifties we had and you know,

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Speaker 1: an instance that I think there was a bear here,

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Speaker 1: you know, killed and then another one that was killed.

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Speaker 1: The question was, are these captive bears that got out,

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Speaker 1: you know, right where where did they come from? Um?

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Speaker 1: And so for a long time we really did think

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Speaker 1: that our bear population had been extirpated. And then you know,

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Speaker 1: as you know, Arkansas Game and Fish had conducted reintroductions

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Speaker 1: in the nineteen fifties and nineteen sixties, and not surprising,

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Speaker 1: some of those bears made their way up this way.

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Speaker 1: And as Arkansas population grew, we started seeing, you know,

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Speaker 1: an increased number of sightings and stuff like that, and

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Speaker 1: and really that started to pick up around the seventies

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Speaker 1: and eighties. We're bear numbers here, so they were they

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Speaker 1: were confirmed bear sightings in Missouri in the seventies, absolutely,

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Speaker 1: and and even even post reintroduction, so even in in

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Speaker 1: the sixties and the late fifties, we did have confirmed

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Speaker 1: bear sightings there. And the thought was that, well, some

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Speaker 1: of these bears probably just came in, just came in

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Speaker 1: from Arkansas, came in from that room. Wasn't a reproducing

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Speaker 1: population or that's probably what they would have said, that's right. Yeah,

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Speaker 1: then that was the thought at the time, right, that

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Speaker 1: any of the bears that we were seeing were coming

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Speaker 1: in from Arkansas. And so um, over time, you know,

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Speaker 1: bear numbers just tinue to expand. And so we went

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Speaker 1: through a series of um kind of you know, concerted

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Speaker 1: efforts to collect sightings on bears and figure out, you know,

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Speaker 1: where where were the counties that we were seeing bears.

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Speaker 1: Are we seeing cows, stals with cubs and stuff like that, um,

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Speaker 1: to really decide are these just bears that use Missouri

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Speaker 1: as part of their range, they wandering from markets? Are

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Speaker 1: they just young, dispersing males that are showing up and

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Speaker 1: and over time it became apparent that we did have,

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Speaker 1: you know, bears that were established in the state of Missouri,

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Speaker 1: their home range was in Missouri, that reproducing in Missouri,

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Speaker 1: and so um, you know, as we looked to the

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Speaker 1: early nineties and things like that, bear numbers were steadily

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Speaker 1: increasing at that point, and by I would say the

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Speaker 1: mid two thousands, we got to the point where like, yes,

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Speaker 1: we we have a bear population here. We've got a

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Speaker 1: bear yeah, I mean, and it was in the nineties

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Speaker 1: that was kind of the thought at that point too.

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Speaker 1: You know, we we we we get reports of stals

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Speaker 1: with cubs, and so it seems it seems that that's

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Speaker 1: the case. UM. But as as time went on, you know,

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Speaker 1: into the into the early two thousands especially, the question

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Speaker 1: was just how many right and what what habitat requirements

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Speaker 1: do they have here? What what types of habitats are

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Speaker 1: they using, and things like that. So we really didn't

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Speaker 1: have a lot of that information and we were relying

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Speaker 1: UM a lot on sighting reports from the public. That's

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Speaker 1: the best way that you can collect some of this

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Speaker 1: information on a large scale. And so, you know, we

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Speaker 1: looked to those sighting reports, looked at that kind of range,

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Speaker 1: and then UM updated a bear management plan in two

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Speaker 1: thousand eight, and that really outlined some of the key

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Speaker 1: research questions that we had about our our bear population. Yeah,

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Speaker 1: what what is our population level, where do we see bears,

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Speaker 1: what does their range look like? And um, what's the

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Speaker 1: ecology of bears in this state? And that's kind of

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Speaker 1: the jumping off point from for where we are today basically,

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Speaker 1: So that started, y'all. You guys officially started doing research

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Speaker 1: in two thousand and eight. The research projects started in

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Speaker 1: two thousand ten, so so the management plan was updated. Yeah. Yeah,

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Speaker 1: we've been studying them for ten years. Let me let

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Speaker 1: me back up and ask you a question. Were so

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Speaker 1: for people who wouldn't be familiar with the topography and

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Speaker 1: kind of the vegetation, I guess uh of Missouri, Northern

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Speaker 1: Missouri is going to be like Midwest, I mean, classic

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Speaker 1: open space, yeah, fragmented forests that's not detected, a lot

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Speaker 1: of agriculture. And then southern Missouri is going to be

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Speaker 1: Ozark mountains. You know, probably elevations under two thousand feet

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Speaker 1: that kars topography, thick eastern inciduous forest. Um did black

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Speaker 1: bears range all the way up into the prairie portions

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Speaker 1: of Missouri? So we did get reports through forested areas,

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Speaker 1: So they probably weren't residing in the prairie portions of

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Speaker 1: the state, but where those forested areas stayed connected, it

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Speaker 1: seems that they would have been. There, probably would have

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Speaker 1: been bears like using the river drainages and stuff like

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Speaker 1: waving up north absolutely, but the but the core would

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Speaker 1: have been in those that really heavily forested area for sure.

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Speaker 1: Um So let me let me, let me think about

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Speaker 1: where I want to go from so many, so many

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Speaker 1: possibilities here. First of all, let me just say the

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Speaker 1: the idea that there's bears in Missouri is incredible. I mean, like,

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Speaker 1: when you think about on a macro scale, the population

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Speaker 1: of the earth increasing, the the the wide spread spawn

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Speaker 1: of civilization taking over places, the fact that we've got

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Speaker 1: these large carnivores that are increasing their range, increasing their numbers,

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Speaker 1: it's pretty incredible. And I mean so to me, like

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Speaker 1: I had heard for several years that Missouri was considering

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Speaker 1: a bear hunting season. They've been doing recent I knew that,

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Speaker 1: but I honestly wasn't expecting it to become a topic

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Speaker 1: of conversation so quickly. But when it did, I was like,

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Speaker 1: this is this is awesome news for conservation and in

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Speaker 1: our century. Really, Oh yeah, absolutely. And you look at

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Speaker 1: black bear nationally, I mean, they are one of the

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Speaker 1: great conservation success stories in so many locations, and so Missouri,

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Speaker 1: you know, we're kind of hitting that high point right

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Speaker 1: now where this is this is the time that, you know,

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Speaker 1: our bear population is rebounded and it's growing steadily expanding

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Speaker 1: in range. I mean, all in all, this is this

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Speaker 1: is a huge conservation success story. And when you look

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Speaker 1: to you know, black bear distribution nationally, you know their

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Speaker 1: range had been restricted again due to habitat changes and

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Speaker 1: unregulated harvests and things like that. And then over time,

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Speaker 1: you know, throughout the eastern US, you know, the southeastern US,

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Speaker 1: the western bear numbers rebounded, and so you know, we've

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Speaker 1: got this these you know, bear populations that in many

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Speaker 1: places are growing, and like you said, at the same

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Speaker 1: time that the human population is growing too, So that

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Speaker 1: in and of itself presents some challenges, right, you know,

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Speaker 1: but but it's it's that's the reason we have to

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Speaker 1: manage them. And I want to talk to Josh about

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Speaker 1: some new nuisance stuff later, but you know, when you

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Speaker 1: I can. I asked Myron Means if he thought this

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Speaker 1: number was legitimate. This was totally out off the wall number.

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Speaker 1: But like you know, I mean, bears don't know. There's

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Speaker 1: a border twenty miles south of here that separates Arkansas

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Speaker 1: from Missouri. But what I was thinking about was like this,

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Speaker 1: and I don't know if I'll call it mid South

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Speaker 1: populations of bears, but basically Missouri, Arkansas, Oklahoma. I mean

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Speaker 1: there's bears in northern Louisiana. You know, they confirmed bears

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Speaker 1: in East Texas like this big spot on the map. UH.

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Speaker 1: I think would be safe to say, you tell me

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Speaker 1: what you think ten thousand bears. I mean my Myron

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Speaker 1: means says Arkansas Game and Fishes now saying I think

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Speaker 1: that we have six thousand bears, which I told him

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Speaker 1: on the podcast. I knew that he was kind of

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Speaker 1: holding the cards load in UH, Oklahoma, I want to say,

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Speaker 1: says they have fifteen hundred to two thousand bears, something

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Speaker 1: in that range. So I mean there's eight thousand bears

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Speaker 1: and then you're not even talking about um, well you're not.

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Speaker 1: That doesn't include Missouri. And I mean bears are crossing

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Speaker 1: the Mississippi River going over to Mississippi. I've got I've

425
00:24:33,960 --> 00:24:37,040
Speaker 1: got a buddy that has a that hunts on a

426
00:24:37,160 --> 00:24:40,359
Speaker 1: lease on the east side of the Mississippi River that

427
00:24:40,440 --> 00:24:43,280
Speaker 1: gets bear pictures on its trail cameras. You know, bears

428
00:24:43,280 --> 00:24:46,560
Speaker 1: that are we're coming back. And there's Illinois before reported

429
00:24:46,560 --> 00:24:48,880
Speaker 1: to us, haven't we in so othern Illinois, So that's

430
00:24:48,880 --> 00:24:51,720
Speaker 1: on the other side of that would be you guys,

431
00:24:51,800 --> 00:24:54,800
Speaker 1: bears going over there. Is that right? We think it's possible.

432
00:24:55,160 --> 00:24:56,760
Speaker 1: It's possible, I mean, and that and I don't know

433
00:24:56,840 --> 00:25:00,480
Speaker 1: that they get a huge number of reports, but but

434
00:25:00,520 --> 00:25:02,359
Speaker 1: it has happened. I mean, and I mean if you

435
00:25:02,359 --> 00:25:05,440
Speaker 1: just look to Missouri, though, we get bear reports north

436
00:25:05,480 --> 00:25:08,080
Speaker 1: of Interstate seventy. So so when you're talking about, you know,

437
00:25:08,280 --> 00:25:10,880
Speaker 1: the dividing line between the state, basically, take the Missouri

438
00:25:11,000 --> 00:25:13,000
Speaker 1: River and it cuts the state in half and it

439
00:25:13,080 --> 00:25:16,560
Speaker 1: kind of separates, you know, that southern Ozark part of

440
00:25:16,600 --> 00:25:18,760
Speaker 1: the state and then that more I mean, and there's

441
00:25:18,800 --> 00:25:21,199
Speaker 1: a transition in between obviously, but that and then that

442
00:25:21,280 --> 00:25:24,800
Speaker 1: agricultural northern part of the state. Um, we get bear

443
00:25:24,840 --> 00:25:27,720
Speaker 1: reports north of the river. I mean, we're getting bear

444
00:25:27,760 --> 00:25:31,600
Speaker 1: reports um every year frequently from kind of the suburbs

445
00:25:31,600 --> 00:25:33,760
Speaker 1: of St. Louis, south of St. Louis. And then we've

446
00:25:33,800 --> 00:25:36,719
Speaker 1: got this tract of woods that kind of crosses the river,

447
00:25:36,840 --> 00:25:39,439
Speaker 1: crosses Interstate seventy, that goes into a couple of the

448
00:25:39,440 --> 00:25:42,760
Speaker 1: counties you know, north of the Highway. Uh, and we've

449
00:25:42,800 --> 00:25:45,080
Speaker 1: gotten bear reports in there. And you can almost track

450
00:25:45,160 --> 00:25:47,000
Speaker 1: that bear movement. You know that it's it's a it's

451
00:25:47,000 --> 00:25:49,760
Speaker 1: a young dispersing bear and boom. So they are I

452
00:25:49,760 --> 00:25:51,399
Speaker 1: mean they can they can get across those things. I

453
00:25:51,400 --> 00:25:53,159
Speaker 1: mean when I was out east, we'd see them a

454
00:25:53,160 --> 00:25:56,520
Speaker 1: cross major highways and the Connecticut River and things like that. So, yeah,

455
00:25:56,520 --> 00:26:03,800
Speaker 1: they're there. Their capabilities for dispersal are pretty incredible. Yeah. Yeah, UM,

456
00:26:03,960 --> 00:26:07,040
Speaker 1: tell me about some of the research, like what were

457
00:26:07,080 --> 00:26:10,359
Speaker 1: the what was the basic research and the questions that

458
00:26:10,400 --> 00:26:12,560
Speaker 1: you guys were trying to answer in the beginning here

459
00:26:12,640 --> 00:26:15,520
Speaker 1: still are yeah, yeah, so yeah, so right, we still

460
00:26:15,520 --> 00:26:18,560
Speaker 1: are in in the midst of our research project. UM,

461
00:26:18,600 --> 00:26:20,440
Speaker 1: it's getting to the point where we're wrapping up the

462
00:26:20,680 --> 00:26:22,760
Speaker 1: project that we're in right now. We've got another year

463
00:26:22,800 --> 00:26:25,360
Speaker 1: on that project. UM. But back in two thousand ten,

464
00:26:25,680 --> 00:26:28,080
Speaker 1: you know, really that initial question was, Okay, we know

465
00:26:28,160 --> 00:26:30,159
Speaker 1: we have a bear population here, but how big is it?

466
00:26:30,240 --> 00:26:32,280
Speaker 1: What is that? How many bears do we have? Because

467
00:26:32,359 --> 00:26:35,040
Speaker 1: ultimately that's what that's what everybody wants to know, right,

468
00:26:35,040 --> 00:26:37,600
Speaker 1: how many bears do you have? And so UM, we

469
00:26:37,720 --> 00:26:41,200
Speaker 1: started that work in two thousand ten, UM collaring bears

470
00:26:41,240 --> 00:26:44,679
Speaker 1: looking at home range size. UM did a genetic capture

471
00:26:44,720 --> 00:26:47,760
Speaker 1: recapture study with hair snares to get at that population

472
00:26:47,960 --> 00:26:50,200
Speaker 1: estimate UM, and so we did that for a couple

473
00:26:50,280 --> 00:26:53,560
Speaker 1: of years. UM. That's where we we got the baseline

474
00:26:53,600 --> 00:26:57,080
Speaker 1: population estimate that UM. If you had listened to communications,

475
00:26:57,240 --> 00:27:00,240
Speaker 1: you know, up until twenty nineteen, basically you'd hear about

476
00:27:00,240 --> 00:27:02,480
Speaker 1: three hundred bears. Missouri has got about three hundred bears.

477
00:27:02,520 --> 00:27:07,720
Speaker 1: And that's based on this estimate that was conducted from UM.

478
00:27:07,760 --> 00:27:10,800
Speaker 1: But with a baseline population estimate, you can't tell how

479
00:27:10,840 --> 00:27:12,880
Speaker 1: fast it's growing, right, It just gives you that kind

480
00:27:12,880 --> 00:27:14,880
Speaker 1: of point estimate in time. And so then the next

481
00:27:14,920 --> 00:27:19,040
Speaker 1: question was, well it it seems that we're seeing this

482
00:27:19,160 --> 00:27:21,959
Speaker 1: range expansion. It seems that from you know what we

483
00:27:22,000 --> 00:27:25,159
Speaker 1: can see here that the population is growing UM, but

484
00:27:25,200 --> 00:27:27,560
Speaker 1: at what rate? How quickly is it growing? So that

485
00:27:27,640 --> 00:27:30,240
Speaker 1: kind of kind of moved us into the next phase

486
00:27:30,280 --> 00:27:34,360
Speaker 1: of our research project. And so we've been visiting bear

487
00:27:34,400 --> 00:27:40,640
Speaker 1: Den's basically since UM trying to get survival estimates, reproductive

488
00:27:40,760 --> 00:27:43,880
Speaker 1: estimates UM, looking at UH, you know, what's the sex

489
00:27:44,000 --> 00:27:48,199
Speaker 1: ratio of our litters, how many cubs survived to age one, UM,

490
00:27:48,280 --> 00:27:50,399
Speaker 1: what's the breeding interval that we're seeing, is that what

491
00:27:50,480 --> 00:27:53,120
Speaker 1: we expect to see. And all of that has been

492
00:27:53,280 --> 00:27:56,159
Speaker 1: used to develop a population model and feed into that

493
00:27:56,200 --> 00:27:58,480
Speaker 1: population model. And so last year we were able to,

494
00:27:58,960 --> 00:28:00,560
Speaker 1: you know, based on all of the data that we've

495
00:28:00,560 --> 00:28:04,080
Speaker 1: collected essentially since, get to the point where we can

496
00:28:04,080 --> 00:28:07,680
Speaker 1: say our bare population is growing at about nine percent annually.

497
00:28:08,400 --> 00:28:11,280
Speaker 1: That is um. It's a it's a high growth rate.

498
00:28:11,400 --> 00:28:14,720
Speaker 1: It's not something that is out of norm for bare

499
00:28:14,800 --> 00:28:18,280
Speaker 1: populations or anything like that. UM. And and that's where

500
00:28:18,280 --> 00:28:20,960
Speaker 1: we get to the estimate of between five eight hundred

501
00:28:21,040 --> 00:28:24,840
Speaker 1: forty bears within the state. Guys and gals. Sorry to

502
00:28:24,840 --> 00:28:29,240
Speaker 1: interrupt the podcast, but we would like for you, if

503
00:28:29,280 --> 00:28:33,399
Speaker 1: you're not a subscriber to beare Hunting Magazine consider subscribing

504
00:28:33,440 --> 00:28:36,159
Speaker 1: to our print magazine is saying we'll get mailed to

505
00:28:36,200 --> 00:28:38,600
Speaker 1: your door six times a year. You get to hold

506
00:28:38,640 --> 00:28:40,520
Speaker 1: it in your hand, you'll get to keep it, You'll

507
00:28:40,560 --> 00:28:43,200
Speaker 1: get to read it and give it away. You could

508
00:28:43,280 --> 00:28:47,040
Speaker 1: read it and use it as kindeling, this fall for

509
00:28:47,320 --> 00:28:49,680
Speaker 1: starting fires, whatever you want to do. This is a

510
00:28:49,720 --> 00:28:55,240
Speaker 1: real product. And most of the of the content that's

511
00:28:55,240 --> 00:28:58,400
Speaker 1: in our magazine is found nowhere else, meaning it's not

512
00:28:58,440 --> 00:29:02,800
Speaker 1: on our website, it's not anywhere. We have monthly columns

513
00:29:02,840 --> 00:29:06,560
Speaker 1: that cover all aspects of bear hunting in North America.

514
00:29:06,760 --> 00:29:09,280
Speaker 1: There's no way you could read this magazine or get

515
00:29:09,280 --> 00:29:11,640
Speaker 1: it for a year and not say that you learn

516
00:29:11,840 --> 00:29:16,760
Speaker 1: something from it. So Bear Hunting Magazine, subscribe, check it out,

517
00:29:16,880 --> 00:29:20,600
Speaker 1: and also check out all our merchandise. We just got

518
00:29:20,640 --> 00:29:22,880
Speaker 1: back in. Colby wanted me to tell you we got

519
00:29:22,920 --> 00:29:27,920
Speaker 1: back in our very popular what is it, Kobe, it's

520
00:29:28,040 --> 00:29:32,880
Speaker 1: the Tan what do we call it? The v h

521
00:29:33,040 --> 00:29:35,800
Speaker 1: M Tan Trucker hat, and we have one in realtory

522
00:29:35,800 --> 00:29:40,760
Speaker 1: Advantage and the the retrobe bear hunter hat. We haven't

523
00:29:40,760 --> 00:29:44,600
Speaker 1: stocked as well. Let me let me go back. I

524
00:29:44,880 --> 00:29:47,760
Speaker 1: wanted to ask you about the different segments, Like I've

525
00:29:47,800 --> 00:29:55,160
Speaker 1: got some questions about bear hair DNA research, um so

526
00:29:55,240 --> 00:29:57,200
Speaker 1: I want I want people to understand how that works

527
00:29:57,280 --> 00:30:00,760
Speaker 1: because it's super difficult to get population umbers on a bear.

528
00:30:00,880 --> 00:30:04,080
Speaker 1: Absolutely yeah, because it's a it's a it's a low

529
00:30:04,160 --> 00:30:06,760
Speaker 1: density animals. I talked about that a lot because people,

530
00:30:07,160 --> 00:30:10,640
Speaker 1: especially new bear hunters, like hot in. This is the

531
00:30:10,800 --> 00:30:12,440
Speaker 1: simplest way I know to describe it as a high

532
00:30:12,480 --> 00:30:15,040
Speaker 1: density of deer might be forty deer per square mile.

533
00:30:15,120 --> 00:30:18,000
Speaker 1: A high density of bear might be a bear per

534
00:30:18,040 --> 00:30:22,800
Speaker 1: square mile. And yeah, so so so first of all,

535
00:30:22,800 --> 00:30:25,360
Speaker 1: it's a low density animal. It's an animal that wants

536
00:30:25,400 --> 00:30:27,200
Speaker 1: to you know, he's not gonna be feeding out on

537
00:30:27,240 --> 00:30:30,200
Speaker 1: the edge of the field in the back behind your house.

538
00:30:30,200 --> 00:30:32,600
Speaker 1: I mean, usually they're in dense cover and stuff. So

539
00:30:32,640 --> 00:30:34,920
Speaker 1: it's a hard animal to get a population number on.

540
00:30:35,320 --> 00:30:39,920
Speaker 1: So these bear bear snare DNA samples. So you're setting

541
00:30:40,000 --> 00:30:43,240
Speaker 1: up basically bait sites that's right with with barbed wire

542
00:30:43,360 --> 00:30:46,680
Speaker 1: around it. And so there's barbed wire like two feet

543
00:30:46,720 --> 00:30:48,920
Speaker 1: off the ground. Yeah, it's basically so that if the bear,

544
00:30:49,080 --> 00:30:51,480
Speaker 1: if the bear crawls under or over it, it's gonna

545
00:30:51,560 --> 00:30:55,520
Speaker 1: collect hair and and so there's a small scent attractant

546
00:30:55,640 --> 00:30:58,200
Speaker 1: that's set in the middle. And then um, when you're

547
00:30:58,200 --> 00:31:00,480
Speaker 1: doing it, you've got folks that check these pure biodically

548
00:31:00,640 --> 00:31:02,680
Speaker 1: and then just collect all of the hair samples and

549
00:31:02,680 --> 00:31:05,120
Speaker 1: then they send it off and get okay, there were

550
00:31:05,440 --> 00:31:09,560
Speaker 1: nine individual animals that came to this space. And then

551
00:31:09,560 --> 00:31:11,720
Speaker 1: the other thing that they're looking at with that is

552
00:31:11,800 --> 00:31:14,560
Speaker 1: how many times do you see those individuals too? So

553
00:31:14,560 --> 00:31:18,080
Speaker 1: so there's that capture part of it. So identifying the

554
00:31:18,120 --> 00:31:21,200
Speaker 1: animal once and then how many times do you recapture

555
00:31:21,240 --> 00:31:24,560
Speaker 1: that animal and so different places, in different places or

556
00:31:24,600 --> 00:31:27,680
Speaker 1: at the same place, and and that helps you Basically

557
00:31:27,720 --> 00:31:30,480
Speaker 1: there's there's some statistical models that you would feed that

558
00:31:30,520 --> 00:31:34,600
Speaker 1: information into to get you to that kind of overarching

559
00:31:34,640 --> 00:31:37,960
Speaker 1: population there and and here is my question, and I

560
00:31:38,080 --> 00:31:40,640
Speaker 1: kind of want to see if I'm understanding it right. Okay,

561
00:31:40,840 --> 00:31:42,720
Speaker 1: So I want to tell you the way that I

562
00:31:42,800 --> 00:31:44,560
Speaker 1: understand it, and you tell you guys, tell me if

563
00:31:44,560 --> 00:31:49,120
Speaker 1: I'm right. So, you can't put up bear snare capture

564
00:31:49,280 --> 00:31:55,280
Speaker 1: sites over every square mile of so you would you

565
00:31:55,320 --> 00:32:01,239
Speaker 1: would be doing uh, topographic analysis of habit at like

566
00:32:01,360 --> 00:32:05,560
Speaker 1: so you let's say maybe you had fifty bear hairschnite

567
00:32:05,800 --> 00:32:08,600
Speaker 1: sites across the state of Missouri. I'm just making this up,

568
00:32:08,800 --> 00:32:12,080
Speaker 1: and then you would analyze the data to the hilt,

569
00:32:13,080 --> 00:32:16,240
Speaker 1: doing all your statistical data, and then you would say, Okay,

570
00:32:16,240 --> 00:32:20,800
Speaker 1: in that type of habitat, we have this many bears,

571
00:32:20,840 --> 00:32:24,560
Speaker 1: we know for sure. And so are you taking an

572
00:32:24,600 --> 00:32:30,920
Speaker 1: analysis of the topography the land and saying, well, we

573
00:32:31,040 --> 00:32:36,360
Speaker 1: have thirty times that much good habitat, So we can

574
00:32:36,400 --> 00:32:39,600
Speaker 1: assume that there's that many bears in this spot. Yeah,

575
00:32:39,640 --> 00:32:42,920
Speaker 1: so that that that's that's the the idea behind it. Yeah.

576
00:32:42,960 --> 00:32:45,240
Speaker 1: So so the part that you look at it's it's

577
00:32:45,360 --> 00:32:49,640
Speaker 1: a spatially explicit model. So you identify the geographic area

578
00:32:50,080 --> 00:32:53,640
Speaker 1: that you are extrapolating across and so so that's the thing.

579
00:32:53,760 --> 00:32:57,160
Speaker 1: So you set up the hair snares and there's different

580
00:32:57,200 --> 00:32:59,760
Speaker 1: sampling methods that you can use on on how you

581
00:33:00,000 --> 00:33:02,080
Speaker 1: at up the hair snares and UM. Part of the

582
00:33:02,080 --> 00:33:04,240
Speaker 1: reason we had collars on those bears was to see

583
00:33:04,720 --> 00:33:07,560
Speaker 1: how these bears are interacting with those hair snares within

584
00:33:08,000 --> 00:33:10,560
Speaker 1: their home range. You know what what is an appropriate

585
00:33:10,640 --> 00:33:14,040
Speaker 1: home range size to think about setting up these hair

586
00:33:14,080 --> 00:33:16,720
Speaker 1: snares within, because that's the thing. You don't want to

587
00:33:16,760 --> 00:33:20,800
Speaker 1: put all your hair snares into one basket basically, right,

588
00:33:20,800 --> 00:33:23,640
Speaker 1: You're not putting it all in just one geographic location.

589
00:33:23,680 --> 00:33:25,760
Speaker 1: You are spreading it out to kind of get that

590
00:33:25,880 --> 00:33:28,680
Speaker 1: variability that you would see and it shows you kind

591
00:33:28,680 --> 00:33:31,120
Speaker 1: of the range in densities that you would see and

592
00:33:31,160 --> 00:33:34,080
Speaker 1: then UM and then through the modeling technique, after you've

593
00:33:34,120 --> 00:33:36,920
Speaker 1: defined that geographic area that, yeah, it projects it out

594
00:33:36,960 --> 00:33:40,080
Speaker 1: to UM the area that you've you've set it to

595
00:33:40,520 --> 00:33:43,400
Speaker 1: essentially um. And one of the things that the hair

596
00:33:43,400 --> 00:33:45,800
Speaker 1: snare stuff also does, I mean, it's allowing you to

597
00:33:45,920 --> 00:33:50,280
Speaker 1: get at that genetic information, so that individual information. And

598
00:33:50,440 --> 00:33:53,440
Speaker 1: we were part of a project that had you know,

599
00:33:53,760 --> 00:33:57,480
Speaker 1: hair samples collected in Oklahoma, hair samples collected in Arkansas,

600
00:33:57,520 --> 00:34:00,560
Speaker 1: both in the Ozarks and the Washitas, and so looking

601
00:34:00,680 --> 00:34:05,040
Speaker 1: at you know, how do um how did how did

602
00:34:05,040 --> 00:34:08,120
Speaker 1: those lineages link up? How are they changed? And one

603
00:34:08,120 --> 00:34:10,560
Speaker 1: of the things that we found was that it seems

604
00:34:10,560 --> 00:34:13,399
Speaker 1: that Missouri did have a small remnant bear population. Yeah.

605
00:34:13,520 --> 00:34:17,000
Speaker 1: So so so that genetic work indicates, you know that

606
00:34:17,040 --> 00:34:20,919
Speaker 1: there was a small population here that he must hung

607
00:34:20,920 --> 00:34:23,960
Speaker 1: on in the most room one parts of the and

608
00:34:24,040 --> 00:34:27,279
Speaker 1: just lived at just really low numbers for for a

609
00:34:27,320 --> 00:34:31,719
Speaker 1: long time. And then as that Arkansas population increased, now

610
00:34:31,800 --> 00:34:33,920
Speaker 1: you've got that kind of that would you would be

611
00:34:33,920 --> 00:34:37,760
Speaker 1: able to differentiate that because the reintroduction of the fifties

612
00:34:37,760 --> 00:34:40,759
Speaker 1: and sixty bears that came out of Canada in Minnesota,

613
00:34:41,000 --> 00:34:43,040
Speaker 1: so they had a different So there was new stuff.

614
00:34:43,560 --> 00:34:46,359
Speaker 1: I mean, you were you were finding new it was right,

615
00:34:46,400 --> 00:34:50,080
Speaker 1: it was a distinct signature basically significant. Yeah, it is.

616
00:34:50,120 --> 00:34:51,960
Speaker 1: It is and I mean I think that you know,

617
00:34:52,000 --> 00:34:55,240
Speaker 1: it's one of those things that it kind of falls

618
00:34:55,280 --> 00:34:58,120
Speaker 1: back onto that secretive nature of those of these animals,

619
00:34:58,120 --> 00:35:00,359
Speaker 1: you know when you talk about I mean they're they Yeah,

620
00:35:00,360 --> 00:35:03,319
Speaker 1: we get a lot of bear sightings, Um, but does

621
00:35:03,360 --> 00:35:06,440
Speaker 1: that equate to population numbers? Know, And that's why we

622
00:35:06,480 --> 00:35:10,200
Speaker 1: don't use bear sightings to estimate the population because you know,

623
00:35:10,239 --> 00:35:13,560
Speaker 1: bear sightings typically occur closer to where humans are going

624
00:35:13,600 --> 00:35:16,400
Speaker 1: to be. It's not in the deepest parts of the

625
00:35:16,400 --> 00:35:19,560
Speaker 1: woods where we know we also have bears and um,

626
00:35:19,560 --> 00:35:22,120
Speaker 1: but we can look at that information to see how

627
00:35:22,160 --> 00:35:25,040
Speaker 1: that range is expanding, because one of the challenges here

628
00:35:25,719 --> 00:35:28,360
Speaker 1: is that, you know, we've got this growing bear population

629
00:35:28,400 --> 00:35:31,799
Speaker 1: where we haven't had bears in in any number in

630
00:35:31,880 --> 00:35:35,840
Speaker 1: decades and and for sometimes in folks lifetime, they've never

631
00:35:35,920 --> 00:35:39,680
Speaker 1: had to think about bears occurring where they live. And

632
00:35:39,680 --> 00:35:42,680
Speaker 1: and now that's that's what we're running into. Bears expanding

633
00:35:42,719 --> 00:35:44,759
Speaker 1: into areas you know, around Lake of the Ozarks and

634
00:35:44,800 --> 00:35:47,400
Speaker 1: south of St. Louis and things like that. So, um,

635
00:35:47,480 --> 00:35:49,239
Speaker 1: you know, we've got a lot of good habitat here,

636
00:35:49,239 --> 00:35:51,600
Speaker 1: so there's a lot of room for them. You know,

637
00:35:51,719 --> 00:35:55,080
Speaker 1: I think there's a This is what I experienced in

638
00:35:55,160 --> 00:35:58,200
Speaker 1: Arkansas is that, especially in the hunting culture, is that

639
00:35:58,239 --> 00:36:02,960
Speaker 1: there was a cultural disconnect from hunting bears because they

640
00:36:02,960 --> 00:36:06,160
Speaker 1: just weren't here. Like you go over into the Appalachian

641
00:36:06,160 --> 00:36:09,560
Speaker 1: Mountains East Tennessee and those guys have been hunting bears

642
00:36:10,400 --> 00:36:14,239
Speaker 1: NonStop since a long time ago, and then like in

643
00:36:14,360 --> 00:36:16,160
Speaker 1: Arkansas would have been here, I mean, like we would

644
00:36:16,160 --> 00:36:19,040
Speaker 1: have had this like rich hunting history. I mean the

645
00:36:19,080 --> 00:36:21,279
Speaker 1: literature in Arkansas, and I'm sure it's the same way

646
00:36:21,280 --> 00:36:24,200
Speaker 1: in Missouri. I mean, there's all this incredible stuff about

647
00:36:24,239 --> 00:36:27,360
Speaker 1: these bear hunters and and some of it not so incredible,

648
00:36:27,360 --> 00:36:29,400
Speaker 1: and that they were market hunting and you know, like

649
00:36:30,400 --> 00:36:33,799
Speaker 1: not wisely using the resource. But aside from that, you know,

650
00:36:33,840 --> 00:36:37,640
Speaker 1: all these incredible bear hunting stories. And then it quit

651
00:36:38,160 --> 00:36:41,360
Speaker 1: because it killed all the bears out landscape level logging,

652
00:36:41,400 --> 00:36:43,960
Speaker 1: all this, and then so there was like the seventy

653
00:36:44,040 --> 00:36:45,800
Speaker 1: year period where there was nothing and then all of

654
00:36:45,840 --> 00:36:48,359
Speaker 1: a sudden, there's bears. And so what I feel like

655
00:36:48,520 --> 00:36:51,640
Speaker 1: has happened in Arkansas, and it's it hopefully happens here

656
00:36:52,120 --> 00:36:56,280
Speaker 1: is there's a resurgence and kind of of bear hunting.

657
00:36:56,680 --> 00:37:00,800
Speaker 1: But also kind of that fitting into the the hunting culture.

658
00:37:01,080 --> 00:37:04,200
Speaker 1: And what I saw in Arkansas was as bear numbers

659
00:37:04,200 --> 00:37:08,560
Speaker 1: started to increase, there was the deer hunters didn't like

660
00:37:08,640 --> 00:37:12,600
Speaker 1: them necessarily sometimes and I saw that as and I mean,

661
00:37:13,440 --> 00:37:16,680
Speaker 1: I was like, man, this is an incredible wildlife resource.

662
00:37:17,760 --> 00:37:20,960
Speaker 1: What's the disconnect here? Like? And and I think it

663
00:37:21,000 --> 00:37:24,279
Speaker 1: was because there was this long gap, but they weren't there,

664
00:37:25,120 --> 00:37:28,200
Speaker 1: and so there was no value placed on them. And

665
00:37:28,200 --> 00:37:30,640
Speaker 1: and I don't think that I feel like we've moved

666
00:37:30,680 --> 00:37:33,359
Speaker 1: past that. Even as a honey, I don't think you're

667
00:37:33,360 --> 00:37:35,440
Speaker 1: gonna experience That's not I'm not saying you're gonna experience

668
00:37:35,480 --> 00:37:39,319
Speaker 1: that here. But it's just an interesting kind of I

669
00:37:39,400 --> 00:37:42,640
Speaker 1: like to talk. I like to understand the hunting culture

670
00:37:42,640 --> 00:37:44,640
Speaker 1: and how things, you know, kind of want to get

671
00:37:44,640 --> 00:37:47,040
Speaker 1: ahead of ourselves. Laura's got a lot to say about

672
00:37:47,040 --> 00:37:50,000
Speaker 1: the research stuff, but exactly what you're talking about. In Missouri,

673
00:37:50,280 --> 00:37:52,680
Speaker 1: my dad didn't bear hunt, my grandpa didn't bear hunt,

674
00:37:52,719 --> 00:37:55,160
Speaker 1: my great grandpa didn't bear hunt. There's a deep deer

675
00:37:55,239 --> 00:37:58,319
Speaker 1: hunting culture. Everybody knows that. So in Missouri, a state

676
00:37:58,360 --> 00:38:00,480
Speaker 1: that doesn't have a bear season, you've got guys that

677
00:38:00,560 --> 00:38:02,840
Speaker 1: well they eat deer fonds, or well they hurt my

678
00:38:02,880 --> 00:38:04,600
Speaker 1: dear feeders, and so it's like it's a big thing

679
00:38:04,640 --> 00:38:07,040
Speaker 1: out there that I can't huh, it breaks my stuff.

680
00:38:07,239 --> 00:38:10,720
Speaker 1: And yeah, and so that's part of the whole culture.

681
00:38:10,760 --> 00:38:12,640
Speaker 1: It's like what, you know, what what good is it for? Then?

682
00:38:12,760 --> 00:38:15,480
Speaker 1: Right now, it's just a liability, which people I don't

683
00:38:15,600 --> 00:38:17,080
Speaker 1: I'm not saying I see it that way, but people

684
00:38:17,120 --> 00:38:19,520
Speaker 1: see that way and it's understandable. But yeah, there's definitely

685
00:38:20,239 --> 00:38:23,160
Speaker 1: an education that needs to occur. There is. And bears

686
00:38:23,200 --> 00:38:25,080
Speaker 1: are one of those species too. You know we talk

687
00:38:25,160 --> 00:38:27,840
Speaker 1: about and being charismatic mega font are right, they're big

688
00:38:27,960 --> 00:38:32,239
Speaker 1: and they are oftentimes symbolic for people and so, uh,

689
00:38:32,360 --> 00:38:35,520
Speaker 1: there's a whole you know, different set of values that

690
00:38:35,560 --> 00:38:38,240
Speaker 1: get placed on them by different individuals. Right, there's this

691
00:38:38,239 --> 00:38:41,960
Speaker 1: this you see, this whole spectrum of emotion when when

692
00:38:42,000 --> 00:38:44,880
Speaker 1: we talk about bears and um, you know, some of

693
00:38:44,920 --> 00:38:47,839
Speaker 1: it is like Josh said that, you know, the uh,

694
00:38:48,120 --> 00:38:51,359
Speaker 1: the kind of disconnected. I don't want them here. I'm

695
00:38:51,760 --> 00:38:53,400
Speaker 1: there's a lot of people that are afraid of them. Right,

696
00:38:53,440 --> 00:38:55,360
Speaker 1: It's a big animal and they just don't have that

697
00:38:55,440 --> 00:38:58,319
Speaker 1: understanding of what the animals doing and so so there's

698
00:38:58,360 --> 00:39:01,040
Speaker 1: that fear all the way to you know, for a

699
00:39:01,080 --> 00:39:04,120
Speaker 1: lot of folks, Uh, there's that intrinsic value just the

700
00:39:04,160 --> 00:39:06,959
Speaker 1: fact that they like to know that there's this wild

701
00:39:07,000 --> 00:39:09,560
Speaker 1: anim even if it doesn't occur where they live. Hey,

702
00:39:09,640 --> 00:39:12,239
Speaker 1: it's part of the woods there. And and so yeah,

703
00:39:12,280 --> 00:39:15,000
Speaker 1: I mean I think that that's that that also is

704
00:39:15,040 --> 00:39:19,400
Speaker 1: one of those big challenges with a recolonizing bear population, right,

705
00:39:19,440 --> 00:39:22,399
Speaker 1: you haven't it's it's not ingrained in folks to think

706
00:39:22,400 --> 00:39:24,799
Speaker 1: about bears and to think about the value they have

707
00:39:24,840 --> 00:39:28,320
Speaker 1: in the ecosystem and the fact that sometimes that means

708
00:39:28,480 --> 00:39:31,799
Speaker 1: changing your own behaviors so that you're not creating these

709
00:39:31,840 --> 00:39:35,160
Speaker 1: situations with human bear conflicts and stuff like that. So, uh,

710
00:39:35,400 --> 00:39:38,040
Speaker 1: it's you know, I mean here in Missouri, like we

711
00:39:38,080 --> 00:39:40,640
Speaker 1: talked about, this is a huge conservation success story, but

712
00:39:40,680 --> 00:39:43,360
Speaker 1: that doesn't mean that it's without challenges, right, It's you know,

713
00:39:43,400 --> 00:39:46,920
Speaker 1: there's there's always challenges with that, and and bears are

714
00:39:46,960 --> 00:39:50,160
Speaker 1: a large species and so you know, the management program

715
00:39:50,280 --> 00:39:53,480
Speaker 1: here it's multifaceted and it aims to address all of

716
00:39:53,560 --> 00:39:55,600
Speaker 1: those different components that you can you know, you can

717
00:39:55,600 --> 00:39:58,719
Speaker 1: talk about when it comes to bears. Yeah, well, you know,

718
00:39:58,800 --> 00:40:03,680
Speaker 1: I think I think the main what I've seen with

719
00:40:03,680 --> 00:40:06,080
Speaker 1: with the hunting seasons in Oklahoma and in Arkansas is

720
00:40:06,120 --> 00:40:11,600
Speaker 1: it it It gave people a vested interest in a

721
00:40:11,680 --> 00:40:14,920
Speaker 1: resource and then it added value to it. And inside

722
00:40:14,920 --> 00:40:17,719
Speaker 1: the North American miile of wildlife conservation, that has been

723
00:40:17,800 --> 00:40:22,560
Speaker 1: the keys too. It's been that, oh wait a minute,

724
00:40:22,640 --> 00:40:25,520
Speaker 1: this is our resource, and we're gonna be able to

725
00:40:25,880 --> 00:40:29,839
Speaker 1: with back scientific research and management, we're gonna be able

726
00:40:29,880 --> 00:40:32,480
Speaker 1: to utilize that resource to some degree. And all of

727
00:40:32,520 --> 00:40:34,880
Speaker 1: a sudden, that creates values. And that's a that's a

728
00:40:34,960 --> 00:40:37,760
Speaker 1: hard thing for some people to understand that don't understand

729
00:40:37,880 --> 00:40:42,080
Speaker 1: hunting and don't understand North America, uh in our hunting.

730
00:40:42,480 --> 00:40:44,839
Speaker 1: But it's so true. I mean it really is. If

731
00:40:44,920 --> 00:40:47,800
Speaker 1: if something is valued, if somebody has a reason to

732
00:40:47,920 --> 00:40:50,400
Speaker 1: value it. And the thing about a bear is nobody

733
00:40:50,480 --> 00:40:54,719
Speaker 1: sees Nobody sees them unless you're looking for looking for him,

734
00:40:55,520 --> 00:40:58,480
Speaker 1: or you've got one that's causing your treul. I mean

735
00:40:59,080 --> 00:41:01,200
Speaker 1: they're causing you. Are you looking for him? That's the

736
00:41:01,200 --> 00:41:03,000
Speaker 1: way you see them, right, And that's what we tell folks.

737
00:41:03,080 --> 00:41:06,160
Speaker 1: You know, sometimes we'll get reports of it's like I

738
00:41:06,239 --> 00:41:08,480
Speaker 1: saw I was hiking and I saw this bear across

739
00:41:08,520 --> 00:41:10,280
Speaker 1: the road, and oh my gosh, this was the coolest

740
00:41:10,320 --> 00:41:13,160
Speaker 1: thing I've ever seen. And we're like, yes, yeah, enjoy

741
00:41:13,280 --> 00:41:16,560
Speaker 1: that sighting, right, and and enjoy it because honestly, you

742
00:41:16,640 --> 00:41:19,279
Speaker 1: may never see one again. And it's just sometimes it's

743
00:41:19,360 --> 00:41:21,319
Speaker 1: just you're in the right place at the right time

744
00:41:21,440 --> 00:41:24,880
Speaker 1: for that, and and it is it's trying to show

745
00:41:25,440 --> 00:41:28,359
Speaker 1: the value of that species being here in the state.

746
00:41:28,560 --> 00:41:30,640
Speaker 1: Let me ask you a question related to that. I

747
00:41:30,800 --> 00:41:32,920
Speaker 1: like it. This is a this is a fun question.

748
00:41:33,080 --> 00:41:35,879
Speaker 1: You've been in Missouri three years. How many bears would

749
00:41:35,920 --> 00:41:40,640
Speaker 1: you have seen? Without oh, without the research project with you,

750
00:41:40,800 --> 00:41:43,400
Speaker 1: just like driving around the back roads, would you have

751
00:41:43,440 --> 00:41:47,200
Speaker 1: seen any? No? Probably, not, especially not where that's right.

752
00:41:47,200 --> 00:41:48,840
Speaker 1: I mean I live in the central part of the state, right,

753
00:41:48,920 --> 00:41:52,120
Speaker 1: so we we we don't have very many up that way.

754
00:41:52,160 --> 00:41:56,400
Speaker 1: But I mean, even just in all the driving around

755
00:41:56,600 --> 00:41:58,759
Speaker 1: the back roads of the Ozarks that we do for

756
00:41:58,880 --> 00:42:02,400
Speaker 1: the research project, I think I've seen one that has

757
00:42:02,640 --> 00:42:05,920
Speaker 1: gone across the road and we're like, oh, hey, there

758
00:42:06,000 --> 00:42:07,759
Speaker 1: it goes. I mean, And and it's the same thing

759
00:42:07,800 --> 00:42:10,120
Speaker 1: even when I was out in Massachusetts. You know that

760
00:42:10,239 --> 00:42:13,960
Speaker 1: bear population out there. It's a dense bear population. It's

761
00:42:13,960 --> 00:42:16,120
Speaker 1: about you know, I think that's when I was out

762
00:42:16,160 --> 00:42:18,440
Speaker 1: there was just over four thousand bears, and so it

763
00:42:18,560 --> 00:42:22,799
Speaker 1: was a very densely populated bear population. And I would

764
00:42:22,840 --> 00:42:26,000
Speaker 1: say I probably had one or two instances, but I

765
00:42:26,160 --> 00:42:28,520
Speaker 1: was out doing field work where I would expect to

766
00:42:28,680 --> 00:42:31,399
Speaker 1: see them, and then all the other times where oh yeah,

767
00:42:31,400 --> 00:42:32,719
Speaker 1: I mean it was it was when I was looking

768
00:42:32,760 --> 00:42:34,320
Speaker 1: for the bear that I found it. So it is.

769
00:42:34,360 --> 00:42:36,480
Speaker 1: I mean, it just gets to that kind of secretive nature.

770
00:42:36,600 --> 00:42:39,360
Speaker 1: Always say that if I wasn't looking for bears and

771
00:42:39,560 --> 00:42:43,520
Speaker 1: just we're just in my natural wanderings, I probably would

772
00:42:43,520 --> 00:42:46,680
Speaker 1: have seen five or six bears, just like crossing the highway,

773
00:42:46,719 --> 00:42:51,120
Speaker 1: crossing the road, bumping into four. I worked on bears

774
00:42:51,320 --> 00:42:53,160
Speaker 1: I saw, but I was doing full time pig work

775
00:42:53,760 --> 00:42:55,840
Speaker 1: trapping ferrell hawks, and so again I was in a

776
00:42:55,880 --> 00:42:57,239
Speaker 1: lot of places people have spent a lot of time.

777
00:42:57,280 --> 00:42:59,000
Speaker 1: But I saw one across the road on my way

778
00:42:59,040 --> 00:43:00,880
Speaker 1: to Petemont and I got a picture with it. All

779
00:43:01,160 --> 00:43:03,320
Speaker 1: something that that yeah, I've seen one. It's just a

780
00:43:03,400 --> 00:43:05,839
Speaker 1: crossing the road being a person in Missouri, and that's

781
00:43:05,880 --> 00:43:08,319
Speaker 1: why it's hard for people to understand. It's like, well,

782
00:43:08,360 --> 00:43:10,600
Speaker 1: if we've got all these bears, why don't we see them?

783
00:43:10,920 --> 00:43:13,000
Speaker 1: You know, they're just they're just a different kind of

784
00:43:13,000 --> 00:43:15,960
Speaker 1: animal and that's what makes them cool. I think, Um,

785
00:43:17,200 --> 00:43:19,960
Speaker 1: your den research. Tell me about your den research. How

786
00:43:20,040 --> 00:43:22,640
Speaker 1: many seals do you have? So so right now, I

787
00:43:22,719 --> 00:43:26,680
Speaker 1: think we're probably at about twenty eight sous thirty sous

788
00:43:26,800 --> 00:43:29,680
Speaker 1: something like that. Um, And so yes, we are you

789
00:43:29,760 --> 00:43:31,880
Speaker 1: in charge of all that? Ye? So I I oversee

790
00:43:31,920 --> 00:43:35,800
Speaker 1: the research project and then work with a huge number

791
00:43:35,960 --> 00:43:38,920
Speaker 1: of other MDC staff that you know, participate in the

792
00:43:38,960 --> 00:43:41,239
Speaker 1: research projects. So you know, Josh is one of those

793
00:43:41,560 --> 00:43:43,920
Speaker 1: who helps during the trapping season, he helps during the

794
00:43:43,960 --> 00:43:47,239
Speaker 1: den work. Um, We've got regional staff down here that

795
00:43:47,600 --> 00:43:50,760
Speaker 1: that put in tons of effort on the research projects.

796
00:43:50,800 --> 00:43:53,960
Speaker 1: So it's it's really is it's lead out of Columbia,

797
00:43:54,040 --> 00:43:56,279
Speaker 1: but it's a team effort and and most of our

798
00:43:56,320 --> 00:43:58,800
Speaker 1: work is down here in Southwest region, in the Ozark

799
00:43:58,880 --> 00:44:02,279
Speaker 1: region of our states. So um, but we've got I

800
00:44:02,320 --> 00:44:05,160
Speaker 1: would say, yeah, probably about thirty bears that are collared. Um,

801
00:44:05,200 --> 00:44:07,719
Speaker 1: and we kind of have them distributed across the southern

802
00:44:07,800 --> 00:44:10,680
Speaker 1: part of the state. So we've got bears essentially just

803
00:44:10,800 --> 00:44:13,839
Speaker 1: a little bit east of here where we're at in Springfield, UM.

804
00:44:13,960 --> 00:44:15,920
Speaker 1: And then bears that kind of go all the way

805
00:44:16,000 --> 00:44:18,880
Speaker 1: almost up to the current river uh in in the

806
00:44:18,960 --> 00:44:21,840
Speaker 1: eastern part of the Ozark. So so a pretty wide range.

807
00:44:21,880 --> 00:44:23,880
Speaker 1: And and in doing that, you know, we cover a

808
00:44:23,960 --> 00:44:26,239
Speaker 1: lot of different habitat types, We cover a lot of

809
00:44:26,280 --> 00:44:30,840
Speaker 1: different levels of force fragmentation and sizes of these forest

810
00:44:30,880 --> 00:44:33,960
Speaker 1: tracks that the bears occur in UM. And so so

811
00:44:34,320 --> 00:44:37,600
Speaker 1: each year we go out and we pinned down their

812
00:44:37,680 --> 00:44:41,160
Speaker 1: dens based on the collar signal uh when we can

813
00:44:41,200 --> 00:44:45,040
Speaker 1: find them, right. So again you know, bears are secretive

814
00:44:45,080 --> 00:44:49,440
Speaker 1: and when they then they're even more secretive as much.

815
00:44:50,440 --> 00:44:53,120
Speaker 1: That's right, yeah. So so so the collars that we

816
00:44:53,280 --> 00:44:56,799
Speaker 1: have used historically have been GPS collars where they store

817
00:44:56,880 --> 00:44:59,239
Speaker 1: the points on board, and so we have to find

818
00:44:59,320 --> 00:45:02,320
Speaker 1: the collar to get you know, with an aircraft to

819
00:45:02,520 --> 00:45:05,360
Speaker 1: get the points from it. UM. And then we do

820
00:45:05,520 --> 00:45:08,279
Speaker 1: have some satellite collars, so those transmit the locations back

821
00:45:08,320 --> 00:45:10,560
Speaker 1: to the satellite and then we can see them, you know,

822
00:45:11,360 --> 00:45:13,759
Speaker 1: with the lag time, we can see where that bear was. UM.

823
00:45:13,920 --> 00:45:15,880
Speaker 1: But yeah, when you get a bear that goes into

824
00:45:16,080 --> 00:45:19,279
Speaker 1: I mean as you mentioned, you know Ozark's cars topography,

825
00:45:20,000 --> 00:45:21,680
Speaker 1: we had a lot of holes in the ground and

826
00:45:21,920 --> 00:45:24,319
Speaker 1: a lot of caves and then I mean a lot

827
00:45:24,360 --> 00:45:27,480
Speaker 1: of big brush piles and down trees and stuff like that.

828
00:45:27,600 --> 00:45:30,840
Speaker 1: So when they're in any substantial amount of cover, the

829
00:45:30,920 --> 00:45:33,880
Speaker 1: signal is just not that great sometimes, so we do

830
00:45:35,120 --> 00:45:37,000
Speaker 1: we don't always find them now and and we we

831
00:45:37,400 --> 00:45:39,640
Speaker 1: we do spend quite a bit of time looking for

832
00:45:39,719 --> 00:45:41,279
Speaker 1: them so that we can find them in the dawn

833
00:45:41,400 --> 00:45:43,520
Speaker 1: and um and and a lot of times we chalk

834
00:45:43,560 --> 00:45:44,920
Speaker 1: it up to Okay, they must have gone in a

835
00:45:44,960 --> 00:45:47,200
Speaker 1: little bit before we were looking, or we just weren't

836
00:45:47,239 --> 00:45:49,400
Speaker 1: looking in the right spot. And you know it, it

837
00:45:49,480 --> 00:45:51,239
Speaker 1: gets tricky. I mean, there's a lot of areas that

838
00:45:51,320 --> 00:45:54,520
Speaker 1: don't have substantial road access and so you know, that's

839
00:45:54,560 --> 00:45:56,839
Speaker 1: areas that bears like to use. And when they're down

840
00:45:56,960 --> 00:45:59,640
Speaker 1: in those deep draws, if you're not in that draw

841
00:45:59,760 --> 00:46:02,080
Speaker 1: just right, you don't pick up the frequency and stuff.

842
00:46:02,160 --> 00:46:04,320
Speaker 1: So UM, So we try to den as many of

843
00:46:04,360 --> 00:46:06,400
Speaker 1: them as we can, visit as many of those dens

844
00:46:06,480 --> 00:46:09,920
Speaker 1: as we can UM and we'll go in, we'll immobilize

845
00:46:10,000 --> 00:46:13,279
Speaker 1: the sow. So we use UM. Primarily we use a

846
00:46:13,360 --> 00:46:17,440
Speaker 1: jab stick. So it goes up to twelve feet long. Um,

847
00:46:17,680 --> 00:46:20,680
Speaker 1: and we have you know, the tranquilizing drug at the

848
00:46:20,800 --> 00:46:22,600
Speaker 1: end of it in a needle. And so we'll walk

849
00:46:22,680 --> 00:46:25,320
Speaker 1: up to the den um jab the bear, get the

850
00:46:25,360 --> 00:46:28,240
Speaker 1: sow down. Um. For some of our more open dens,

851
00:46:28,719 --> 00:46:31,960
Speaker 1: we have to dart them. And Josh has a really

852
00:46:32,080 --> 00:46:35,200
Speaker 1: good darting story of a bear. I mean, you don't

853
00:46:35,239 --> 00:46:38,359
Speaker 1: think of bears and ground nests, right, We do find

854
00:46:38,400 --> 00:46:40,359
Speaker 1: them in that where basically, I mean they've just made

855
00:46:40,400 --> 00:46:43,680
Speaker 1: a bowl leaves and that's what they sit in. They

856
00:46:43,760 --> 00:46:47,320
Speaker 1: all winter long and and so those bears they're challenging

857
00:46:47,640 --> 00:46:49,640
Speaker 1: to get because you you can't walk up to them

858
00:46:49,680 --> 00:46:51,759
Speaker 1: and that you know they're they're awake enough that they

859
00:46:51,840 --> 00:46:54,799
Speaker 1: know you're there and everything. So so in those instances

860
00:46:55,000 --> 00:46:57,920
Speaker 1: we we dart them. And um, Josh was one that

861
00:46:58,200 --> 00:47:01,040
Speaker 1: belly crawled for. You're not talking about the one I did.

862
00:47:01,080 --> 00:47:04,600
Speaker 1: This winner the one last. So we have two stories.

863
00:47:05,680 --> 00:47:07,960
Speaker 1: There's a couple of them. I thought you're gonna say,

864
00:47:08,000 --> 00:47:11,680
Speaker 1: you put up a tree stand. I barely crawled what

865
00:47:11,800 --> 00:47:16,440
Speaker 1: it was at. I mean, like this is not really relevant,

866
00:47:16,520 --> 00:47:18,480
Speaker 1: but uh, there was a bear in an opened in

867
00:47:18,920 --> 00:47:21,560
Speaker 1: and she knows you're there. She can see you, and

868
00:47:21,640 --> 00:47:24,239
Speaker 1: so I barely crawled just to not make a much disturbance,

869
00:47:24,280 --> 00:47:25,960
Speaker 1: and she watches you the whole way, and so I

870
00:47:26,040 --> 00:47:28,200
Speaker 1: finally just kept putting like a big oak tree. It

871
00:47:28,280 --> 00:47:31,080
Speaker 1: was like, why is she up? And look at it

872
00:47:31,160 --> 00:47:32,960
Speaker 1: and then kind of turned around and sit back down,

873
00:47:32,960 --> 00:47:35,839
Speaker 1: and then she'd look back over her shoulder like yeah,

874
00:47:37,160 --> 00:47:38,480
Speaker 1: it's like, you know, it's like how much am I

875
00:47:38,520 --> 00:47:40,320
Speaker 1: going to tolerate? Am I gonna put on with? And

876
00:47:40,400 --> 00:47:42,439
Speaker 1: so finally I got us close, which I think ended

877
00:47:42,480 --> 00:47:44,520
Speaker 1: up being about twenty two yards, and that's important for

878
00:47:45,120 --> 00:47:48,120
Speaker 1: the trajectory of the dart and so so I keep

879
00:47:48,239 --> 00:47:50,080
Speaker 1: arrange finder and all that. But anyway, so I find

880
00:47:50,120 --> 00:47:51,560
Speaker 1: that pushed her as close as I could get, and

881
00:47:51,600 --> 00:47:53,640
Speaker 1: then she finally stood up, which was perfect because it

882
00:47:53,680 --> 00:47:55,480
Speaker 1: gave me that front shoulder shot. We like to put

883
00:47:55,560 --> 00:47:58,640
Speaker 1: them the darts in muscular so either basically their rump

884
00:47:58,760 --> 00:48:00,960
Speaker 1: the backside of them were like the shoulders. So yeah,

885
00:48:01,040 --> 00:48:02,680
Speaker 1: so anyway, we darted her and she ran off and

886
00:48:03,080 --> 00:48:07,120
Speaker 1: cubs she did, yeah, and an open den like that. Yeah. Yeah,

887
00:48:07,320 --> 00:48:08,719
Speaker 1: The bad part is you got to bring them back.

888
00:48:08,840 --> 00:48:12,240
Speaker 1: So she gets started, then she runs away to carry

889
00:48:12,280 --> 00:48:17,759
Speaker 1: her like like a wounded soldier get away from she

890
00:48:17,880 --> 00:48:20,239
Speaker 1: left the cubs. Yeah, and they'll do that sometimes. So

891
00:48:20,320 --> 00:48:22,080
Speaker 1: a lot of it is is kind of there's this

892
00:48:22,239 --> 00:48:24,400
Speaker 1: idea I think that you know, they're they're drawing the

893
00:48:24,520 --> 00:48:28,279
Speaker 1: danger away from those cubs. And and so've I've had

894
00:48:28,360 --> 00:48:30,000
Speaker 1: it where I mean, I've had bears get up and

895
00:48:30,120 --> 00:48:33,000
Speaker 1: walk around the den and they're hoping that you know

896
00:48:34,000 --> 00:48:35,719
Speaker 1: that that's enough for you. You don't want to be

897
00:48:35,840 --> 00:48:37,520
Speaker 1: by them, right, and they're hoping that you move off

898
00:48:37,600 --> 00:48:40,080
Speaker 1: and everything. Um, And then I mean, and then you

899
00:48:40,200 --> 00:48:42,359
Speaker 1: have others that just stay put and they don't move.

900
00:48:42,440 --> 00:48:45,200
Speaker 1: And I mean you see every every level of tolerance

901
00:48:45,440 --> 00:48:46,920
Speaker 1: with with the bear, and I think a lot of

902
00:48:46,960 --> 00:48:49,600
Speaker 1: it just depends on, um, you know, the type of

903
00:48:49,920 --> 00:48:55,279
Speaker 1: individual bear all of that, so different strategy. UM. So

904
00:48:56,200 --> 00:49:01,480
Speaker 1: describe for somebody that wouldn't know about how a bear

905
00:49:01,520 --> 00:49:03,280
Speaker 1: would react, because a lot of people would be surprised

906
00:49:03,320 --> 00:49:05,239
Speaker 1: to hear that a bear would be awaken a den

907
00:49:05,760 --> 00:49:08,359
Speaker 1: because you know, like I spend half of my life

908
00:49:08,520 --> 00:49:12,160
Speaker 1: talking to people about how bears don't hybridate, but I

909
00:49:12,239 --> 00:49:14,880
Speaker 1: want to hear and Laura's about five foot tall and

910
00:49:14,960 --> 00:49:17,520
Speaker 1: she crawls in there and with that three ftsticks. People

911
00:49:17,560 --> 00:49:20,719
Speaker 1: don't believe that when it's usually longer than a three footstick,

912
00:49:20,760 --> 00:49:22,520
Speaker 1: but no, I mean it it is. So Yeah, so

913
00:49:22,680 --> 00:49:25,000
Speaker 1: everybody thinks, you know, you have this picture in your

914
00:49:25,040 --> 00:49:26,960
Speaker 1: mind from what you were told as a kid. Right,

915
00:49:27,080 --> 00:49:30,279
Speaker 1: you know, you read all these stories about bear goes

916
00:49:30,320 --> 00:49:32,359
Speaker 1: into a cave and then they just sleep all winter

917
00:49:32,440 --> 00:49:34,560
Speaker 1: and they hibernate and things like that, and so, right,

918
00:49:34,640 --> 00:49:38,239
Speaker 1: bears aren't true hibernators. So they do go through like

919
00:49:38,520 --> 00:49:42,399
Speaker 1: a huge amount of physiological changes. So so when they're

920
00:49:42,400 --> 00:49:44,600
Speaker 1: getting ready to go into the den, you know, during

921
00:49:44,640 --> 00:49:46,719
Speaker 1: the fall, I mean, obviously they're packing on as many

922
00:49:46,760 --> 00:49:49,160
Speaker 1: pounds as they can get there in that period of

923
00:49:49,239 --> 00:49:52,279
Speaker 1: hyperphagia or there, I mean, they're literally spending all the

924
00:49:52,400 --> 00:49:55,239
Speaker 1: hours that they're active feeding, that's basically what they're doing,

925
00:49:55,800 --> 00:49:59,040
Speaker 1: um and and that enables them to go through an

926
00:49:59,239 --> 00:50:03,680
Speaker 1: entire winter without eating. But they're not in the same

927
00:50:04,000 --> 00:50:06,719
Speaker 1: kind of body condition that a true hibernator would be.

928
00:50:06,760 --> 00:50:09,120
Speaker 1: And so we have true hibernators here. There's chipmunks and

929
00:50:09,200 --> 00:50:12,520
Speaker 1: wood chucks and types of ground squirrels that are true hibernators,

930
00:50:12,520 --> 00:50:15,200
Speaker 1: and so that they would just be totally out body

931
00:50:15,239 --> 00:50:18,040
Speaker 1: temperature drop, I mean, there's a definition that's right. Yeah,

932
00:50:18,080 --> 00:50:21,160
Speaker 1: the body temperature of a true hibernator drops very close

933
00:50:21,239 --> 00:50:25,319
Speaker 1: to the ambient temperature, which is pretty incredible. Heart rate

934
00:50:25,400 --> 00:50:28,759
Speaker 1: drops significantly down. But those true hibernators they go through

935
00:50:28,840 --> 00:50:31,480
Speaker 1: these periods of wakefulness and then they eat a little

936
00:50:31,520 --> 00:50:34,560
Speaker 1: bit and then they go back into that that hibernati state.

937
00:50:34,640 --> 00:50:36,640
Speaker 1: And so it's very different than what bears do. And

938
00:50:36,719 --> 00:50:38,440
Speaker 1: so bears, you know, as they're preparing to go into

939
00:50:38,480 --> 00:50:40,400
Speaker 1: the winter den, they pack on as many pounds that

940
00:50:40,480 --> 00:50:42,760
Speaker 1: they can get, and then when food starts to become short,

941
00:50:43,160 --> 00:50:48,120
Speaker 1: they'll consume roughige and hair and create the fecal plug

942
00:50:48,280 --> 00:50:51,480
Speaker 1: that's basically gonna stop. Never heard that they eat their

943
00:50:51,480 --> 00:50:53,600
Speaker 1: own hair, Yeah, yeah, I mean it's I don't know

944
00:50:53,760 --> 00:50:56,000
Speaker 1: that it's something that has done a ton, but it's

945
00:50:56,040 --> 00:50:58,000
Speaker 1: it's basically, I mean, they think they're grooming themselves a

946
00:50:58,040 --> 00:51:00,320
Speaker 1: little bit. They're eating all that roughage, and when we

947
00:51:00,400 --> 00:51:02,560
Speaker 1: find those fecal plugs, I mean it is just a

948
00:51:02,680 --> 00:51:06,600
Speaker 1: hard mass of stuff, you know, and it's it's I

949
00:51:06,680 --> 00:51:08,960
Speaker 1: think whatever they can come across that's going to do

950
00:51:09,040 --> 00:51:11,520
Speaker 1: the job for that. And and so you know, they

951
00:51:11,560 --> 00:51:16,120
Speaker 1: go into that winter den and they become inactive, but

952
00:51:16,280 --> 00:51:20,960
Speaker 1: their body temperature really doesn't drop. It stays pretty stable.

953
00:51:21,160 --> 00:51:25,400
Speaker 1: Their heart rate slows down, um, but it doesn't go

954
00:51:25,600 --> 00:51:27,879
Speaker 1: down to next to nothing, but it does slow down

955
00:51:27,920 --> 00:51:29,319
Speaker 1: a lot. So I think it's like eight beats per

956
00:51:29,400 --> 00:51:31,719
Speaker 1: minute that they haven't in the den. So it goes down,

957
00:51:32,200 --> 00:51:36,000
Speaker 1: it goes down a lot um. But they can rouse instantly.

958
00:51:36,320 --> 00:51:38,600
Speaker 1: So with a true hibernator, if you catch them in

959
00:51:38,840 --> 00:51:42,120
Speaker 1: that deep hibernation state, you can't wake them up. They

960
00:51:42,440 --> 00:51:44,440
Speaker 1: have to basically warm their own body up and go

961
00:51:44,560 --> 00:51:47,520
Speaker 1: through certain processes and stuff. Bears, on the other hand,

962
00:51:47,560 --> 00:51:50,080
Speaker 1: I mean we see it with experience with the den work.

963
00:51:50,239 --> 00:51:52,719
Speaker 1: You walk up to the den and they're looking at you,

964
00:51:52,840 --> 00:51:54,440
Speaker 1: and they can get up and leave it anytime they want,

965
00:51:54,480 --> 00:51:56,560
Speaker 1: and sometimes they do it at full speed, you know,

966
00:51:56,760 --> 00:51:59,320
Speaker 1: so so they can they can be active right away.

967
00:51:59,360 --> 00:52:03,719
Speaker 1: And bears aren't obligate dinners. I mean, the only one

968
00:52:03,760 --> 00:52:06,400
Speaker 1: that's an obligate dinner would be a souath cubs like

969
00:52:07,280 --> 00:52:09,880
Speaker 1: they are going to den. But I say that to

970
00:52:09,960 --> 00:52:14,319
Speaker 1: say bears are not dinning based upon cold temperature. They're

971
00:52:14,360 --> 00:52:18,719
Speaker 1: dinning based upon food. Mean basically, eat until they run

972
00:52:18,760 --> 00:52:21,800
Speaker 1: out of food and then go dinn And so years

973
00:52:21,880 --> 00:52:25,680
Speaker 1: with good mass crop, they're gonna stay out longer. Yeah, absolutely,

974
00:52:25,920 --> 00:52:28,200
Speaker 1: get up more so you know, I mean, like out

975
00:52:28,239 --> 00:52:30,520
Speaker 1: of the den and maybe go wander around on a

976
00:52:30,600 --> 00:52:33,680
Speaker 1: sunny day in January. Yeah, And so that's the thing,

977
00:52:33,760 --> 00:52:36,880
Speaker 1: It's right. The females give birth in the den, and

978
00:52:36,960 --> 00:52:39,080
Speaker 1: so those are the only ones that have to den.

979
00:52:39,239 --> 00:52:40,880
Speaker 1: If they're going to give birth, they have to be

980
00:52:41,000 --> 00:52:43,520
Speaker 1: in that winter den. And so they give birth in

981
00:52:43,560 --> 00:52:45,960
Speaker 1: the den. But females with yearlings, females that are by

982
00:52:46,040 --> 00:52:49,160
Speaker 1: themselves so they didn't reproduce or they're too young to reproduce,

983
00:52:49,800 --> 00:52:52,640
Speaker 1: or males, they can stay active for a really long time.

984
00:52:52,800 --> 00:52:55,759
Speaker 1: And I mean and eventually in most places you get

985
00:52:55,800 --> 00:52:58,040
Speaker 1: to the dead winner and food just becomes too short

986
00:52:58,080 --> 00:53:00,920
Speaker 1: and it's not worth the energy cost to keep searching.

987
00:53:01,600 --> 00:53:04,640
Speaker 1: But in in warmer climates that period can be really short.

988
00:53:04,760 --> 00:53:08,080
Speaker 1: And then if you have bears that live around you know,

989
00:53:08,320 --> 00:53:12,240
Speaker 1: urban areas or suburban areas, they don't necessarily need natural foods.

990
00:53:12,320 --> 00:53:15,080
Speaker 1: They will rely on you know, bird feeders, and trash

991
00:53:15,160 --> 00:53:17,080
Speaker 1: and things like that, and that helps them even stay

992
00:53:17,120 --> 00:53:20,040
Speaker 1: active longer than maybe they would have otherwise. But um,

993
00:53:20,200 --> 00:53:22,759
Speaker 1: but when they go into that den uh, their body

994
00:53:22,920 --> 00:53:25,879
Speaker 1: is basically like a recycling system and it is it's

995
00:53:26,120 --> 00:53:29,279
Speaker 1: pretty incredible to think that they can go in this

996
00:53:29,440 --> 00:53:31,920
Speaker 1: den and especially when you think about the females um

997
00:53:32,239 --> 00:53:34,160
Speaker 1: that are going to give birth in the den um

998
00:53:34,239 --> 00:53:37,080
Speaker 1: and especially in more northern climates where they might den

999
00:53:37,280 --> 00:53:41,040
Speaker 1: upwards of six months. They they're not eating and they're

1000
00:53:41,080 --> 00:53:43,160
Speaker 1: not drinking that entire time, and so they have a

1001
00:53:43,239 --> 00:53:46,319
Speaker 1: certain type of fat in their body that they burn

1002
00:53:46,480 --> 00:53:49,120
Speaker 1: and that's what gives them the energy to basically maintain

1003
00:53:49,440 --> 00:53:51,720
Speaker 1: their bodily functions, you know, the heart and the breathing

1004
00:53:51,840 --> 00:53:54,360
Speaker 1: and their brain functions and things like that. Um. But

1005
00:53:54,440 --> 00:53:58,040
Speaker 1: as they burn that fat, any waste products that are created.

1006
00:53:58,120 --> 00:54:00,120
Speaker 1: You know, they're not urinating and they're not defecating in

1007
00:54:00,160 --> 00:54:03,239
Speaker 1: the den, so those waste products are recycled and it's

1008
00:54:03,280 --> 00:54:06,200
Speaker 1: thought that that's what replenishes their muscles and their bones

1009
00:54:06,320 --> 00:54:08,200
Speaker 1: because when they come out of the den. I mean,

1010
00:54:08,280 --> 00:54:12,000
Speaker 1: if if you or I laid inactive for even a

1011
00:54:12,080 --> 00:54:15,840
Speaker 1: weak our muscles would atrophy, your bones become weak, you know,

1012
00:54:15,960 --> 00:54:18,600
Speaker 1: and for any more extended periods of time. That's the

1013
00:54:18,680 --> 00:54:21,160
Speaker 1: challenges that people face, you know, when they're hospitalized for

1014
00:54:21,239 --> 00:54:25,120
Speaker 1: extended periods and stuff. Bears don't see a weakness in

1015
00:54:25,239 --> 00:54:28,000
Speaker 1: bones or a decrease in muscle strength and things like that,

1016
00:54:28,080 --> 00:54:30,440
Speaker 1: and it's because they've basically got There are other mammals

1017
00:54:30,520 --> 00:54:35,440
Speaker 1: that have similar that go into it. Yeah, yes, there

1018
00:54:35,480 --> 00:54:38,160
Speaker 1: are some other mammals that do that. There there are, so,

1019
00:54:38,440 --> 00:54:40,399
Speaker 1: I mean some of the other fur bearers, you think,

1020
00:54:40,440 --> 00:54:42,960
Speaker 1: you know, they go into these periods of winter in activity, right,

1021
00:54:43,120 --> 00:54:48,759
Speaker 1: But it's not necessarily to the same degree as very

1022
00:54:48,800 --> 00:54:54,040
Speaker 1: specific thing that the recycling of waste and stuff. Yeah, yeah, yeah,

1023
00:54:54,040 --> 00:54:55,359
Speaker 1: and it's and it's one of those things. I mean,

1024
00:54:55,400 --> 00:54:57,759
Speaker 1: there are there are other species that can be inactive

1025
00:54:57,840 --> 00:55:00,719
Speaker 1: for extended periods of time, and they ones that can

1026
00:55:00,800 --> 00:55:04,880
Speaker 1: go for that extent, right, And and they're adapted to

1027
00:55:05,000 --> 00:55:07,040
Speaker 1: give birth in the dent too, so when you think

1028
00:55:07,080 --> 00:55:09,480
Speaker 1: about that, you know, they've got um. They go through

1029
00:55:09,520 --> 00:55:13,120
Speaker 1: delayed implantation, right. The breeding season occurs in June and July.

1030
00:55:16,480 --> 00:55:19,719
Speaker 1: It's our go to any awkward moment in any conversation

1031
00:55:19,760 --> 00:55:21,879
Speaker 1: in my life, I go. Do you know about delight

1032
00:55:21,960 --> 00:55:26,799
Speaker 1: in plantation? You know, but it's one of those things

1033
00:55:26,840 --> 00:55:31,560
Speaker 1: I mean trying. It's all good, but I mean, but

1034
00:55:31,680 --> 00:55:35,040
Speaker 1: that's that's basically you know, they've got this process. And

1035
00:55:35,080 --> 00:55:38,440
Speaker 1: there are other species that have delayed implantation, so weasels

1036
00:55:38,480 --> 00:55:42,759
Speaker 1: are one of them. Apparently that's my connection weasels and

1037
00:55:42,800 --> 00:55:46,799
Speaker 1: bears right there. But because they are a low yeah,

1038
00:55:46,840 --> 00:55:48,440
Speaker 1: they're a load innst of the animal. And I think

1039
00:55:48,480 --> 00:55:50,480
Speaker 1: it's in a lot of cases it's animals that might

1040
00:55:50,520 --> 00:55:54,120
Speaker 1: experience food food shortages. And so for bears, you know,

1041
00:55:54,600 --> 00:55:57,799
Speaker 1: basically if they don't go into the dent in good

1042
00:55:57,880 --> 00:56:03,040
Speaker 1: body condition, that embryo doesn't implant, the pregnancy doesn't continue.

1043
00:56:03,239 --> 00:56:05,960
Speaker 1: And and part of that is that adaptation basically to

1044
00:56:06,040 --> 00:56:08,440
Speaker 1: make it through those six months. Because you know, if

1045
00:56:08,560 --> 00:56:12,400
Speaker 1: you have a sow that's expending the energy giving birth

1046
00:56:12,640 --> 00:56:15,719
Speaker 1: and rearing the cubs and and nursing them in the

1047
00:56:15,800 --> 00:56:18,799
Speaker 1: den while she's not consuming anything. Um, if she went

1048
00:56:18,880 --> 00:56:21,839
Speaker 1: in and really poor body condition, there's gonna be kind

1049
00:56:21,840 --> 00:56:23,480
Speaker 1: of a trade off. Something's gonna have to get. I

1050
00:56:23,600 --> 00:56:26,800
Speaker 1: just learned something that I'm adding to my repertoive knowledge

1051
00:56:26,840 --> 00:56:30,560
Speaker 1: of delayed implantation, food shortage. See, I I thought it

1052
00:56:30,800 --> 00:56:35,160
Speaker 1: was just that well, I mean I knew that their

1053
00:56:35,200 --> 00:56:38,320
Speaker 1: body didn't decide that they you know, just stated until

1054
00:56:38,600 --> 00:56:41,880
Speaker 1: there understood all that. But I thought it was also

1055
00:56:42,440 --> 00:56:46,120
Speaker 1: or primarily a function of them just needing to um

1056
00:56:47,840 --> 00:56:50,319
Speaker 1: breed when they could, because I've got such a big

1057
00:56:50,440 --> 00:56:54,239
Speaker 1: window of breeding and usually breeding determined conception date. But

1058
00:56:54,320 --> 00:56:56,560
Speaker 1: with a bear, it doesn't matter to have this big window.

1059
00:56:57,239 --> 00:57:00,640
Speaker 1: So that's good. I like that the food it's animals

1060
00:57:00,719 --> 00:57:04,719
Speaker 1: with potential major food shorter than Yeah, it's that that

1061
00:57:04,840 --> 00:57:07,279
Speaker 1: adaptation to kind of get through that. And I think too,

1062
00:57:07,360 --> 00:57:10,600
Speaker 1: you know, with delayed plantation, you know, there's not I

1063
00:57:10,680 --> 00:57:12,560
Speaker 1: don't know what the trigger is. I think that's one

1064
00:57:12,600 --> 00:57:14,239
Speaker 1: of those questions as to like, well, what is the

1065
00:57:14,440 --> 00:57:17,800
Speaker 1: trigger itself that you know, the body signal that the

1066
00:57:17,840 --> 00:57:21,200
Speaker 1: embryo can implant and you know, who knows if it's

1067
00:57:21,240 --> 00:57:25,000
Speaker 1: hormone related or you know, something along those lines. But um,

1068
00:57:25,120 --> 00:57:28,439
Speaker 1: but I mean just just the bear's physiology is something

1069
00:57:28,520 --> 00:57:31,760
Speaker 1: that's a really fascinating system. And so but that is

1070
00:57:31,840 --> 00:57:34,720
Speaker 1: the common misconception that everybody thinks, well, like, yeah, I

1071
00:57:34,760 --> 00:57:36,360
Speaker 1: mean you're gonna walk up to a bear den, but

1072
00:57:36,920 --> 00:57:42,480
Speaker 1: they're sound asleep, big deal, rights Like, well, not exactly,

1073
00:57:42,640 --> 00:57:46,000
Speaker 1: they generally aren't asleep. I mean, I've I've worked bears

1074
00:57:46,200 --> 00:57:50,120
Speaker 1: in deep snow cover on really really cold days where

1075
00:57:50,200 --> 00:57:53,560
Speaker 1: they are a little they're they're they're out, you know,

1076
00:57:53,640 --> 00:57:57,080
Speaker 1: and they're not really paying attention. Um. But then you know,

1077
00:57:57,200 --> 00:57:59,560
Speaker 1: on warm days, we could come up to the den

1078
00:57:59,640 --> 00:58:01,920
Speaker 1: and the bear is raking leaves into the den to

1079
00:58:02,080 --> 00:58:04,000
Speaker 1: build up the nest again, you know. So, I mean

1080
00:58:04,080 --> 00:58:07,400
Speaker 1: it it just it just depends on you know, the day.

1081
00:58:07,560 --> 00:58:10,840
Speaker 1: But especially here in Missouri, I mean, our bears are

1082
00:58:11,200 --> 00:58:14,240
Speaker 1: generally very well aware of the fact that we're walking

1083
00:58:14,320 --> 00:58:16,640
Speaker 1: up to them. Have you had any close calls with

1084
00:58:16,720 --> 00:58:20,640
Speaker 1: a bear on a din den study? I mean, like nothing,

1085
00:58:20,640 --> 00:58:22,920
Speaker 1: I mean nothing that I would say close. Well then

1086
00:58:24,600 --> 00:58:27,480
Speaker 1: Josh is laughing. Uh this year I got bluff charged

1087
00:58:27,520 --> 00:58:30,160
Speaker 1: at in the entrance of one and um. I mean,

1088
00:58:30,200 --> 00:58:34,040
Speaker 1: and and it does happen occasionally that they do that.

1089
00:58:34,160 --> 00:58:36,400
Speaker 1: I mean, it's it's not uncommon for them to swap

1090
00:58:36,480 --> 00:58:38,720
Speaker 1: the jab pull away, which is why in a lot

1091
00:58:38,760 --> 00:58:41,360
Speaker 1: of cases, you know, we weigh the do we dart

1092
00:58:41,440 --> 00:58:43,240
Speaker 1: the bear or do we jab the bear? If it's

1093
00:58:43,280 --> 00:58:45,760
Speaker 1: something where I think I'm going to make the bear

1094
00:58:45,920 --> 00:58:48,960
Speaker 1: stand up and move because I'm walking up to it.

1095
00:58:49,080 --> 00:58:51,120
Speaker 1: Then those are the instances where we think about, okay,

1096
00:58:51,200 --> 00:58:53,400
Speaker 1: is it a clear dart shot? And you know, I mean,

1097
00:58:53,680 --> 00:58:56,040
Speaker 1: you know, many of the areas in the Missouri's are

1098
00:58:56,200 --> 00:58:59,600
Speaker 1: are thick cover and BlackBerry patches and things like that,

1099
00:58:59,800 --> 00:59:02,920
Speaker 1: and so in those instances, not necessarily the best darting

1100
00:59:02,960 --> 00:59:05,440
Speaker 1: location because the cover is so thick and there's just

1101
00:59:05,520 --> 00:59:07,840
Speaker 1: not a clear shot and stuff. Um, So we kind

1102
00:59:07,880 --> 00:59:10,040
Speaker 1: of weigh all of that as we're approaching the dens.

1103
00:59:10,120 --> 00:59:12,920
Speaker 1: But um, but you know, we've had them where they

1104
00:59:13,080 --> 00:59:15,480
Speaker 1: swat the jab pole and in a lot of cases

1105
00:59:15,840 --> 00:59:17,960
Speaker 1: they just turn away from you and it's you know,

1106
00:59:18,040 --> 00:59:19,720
Speaker 1: they're kind of giving you the rear end. They don't

1107
00:59:19,760 --> 00:59:21,959
Speaker 1: they're not looking at you. They're not they're not wanting

1108
00:59:22,000 --> 00:59:24,520
Speaker 1: to pay attention to what you're doing. Right, And then

1109
00:59:24,600 --> 00:59:26,560
Speaker 1: in that case, yeah, it makes it It makes it

1110
00:59:26,880 --> 00:59:31,040
Speaker 1: easier to to jab them in that instance. Um. And

1111
00:59:31,120 --> 00:59:34,120
Speaker 1: then we run into some dens where they're so far

1112
00:59:34,200 --> 00:59:37,360
Speaker 1: back in a cave we can't reach it. It's one

1113
00:59:37,400 --> 00:59:39,400
Speaker 1: of those things where a lot of these caves lead

1114
00:59:39,520 --> 00:59:43,760
Speaker 1: to underwater areas or you know, an underground water reservoirs

1115
00:59:43,800 --> 00:59:45,360
Speaker 1: and stuff like that. So we're not going to take

1116
00:59:45,400 --> 00:59:47,560
Speaker 1: a chance and to mobilize a bear where there's a

1117
00:59:47,600 --> 00:59:49,320
Speaker 1: chance that it could go further into the cave where

1118
00:59:49,360 --> 00:59:52,040
Speaker 1: we can't watch it and stuff like That's an important

1119
00:59:52,040 --> 00:59:55,080
Speaker 1: thing to add though. This this will this this get

1120
00:59:55,160 --> 00:59:57,280
Speaker 1: rid of some rumors people see on TV. If we

1121
00:59:57,400 --> 00:59:59,880
Speaker 1: inject drugs into a bear, it might take twenty minutes,

1122
01:00:00,000 --> 01:00:02,080
Speaker 1: that's right, Yeah, especially in the winter. So so that's

1123
01:00:02,120 --> 01:00:03,680
Speaker 1: one of the things where, yeah, if if the bear

1124
01:00:03,760 --> 01:00:05,600
Speaker 1: is in a cave and you know, we can only

1125
01:00:05,640 --> 01:00:07,480
Speaker 1: see ten feet in it, well we can jab that

1126
01:00:07,560 --> 01:00:10,240
Speaker 1: bear with the drug. It can be awake for twenty minutes.

1127
01:00:10,280 --> 01:00:12,600
Speaker 1: It might walk a hundred yards down into the earth

1128
01:00:12,800 --> 01:00:14,600
Speaker 1: and then so it's not good for the bear, it's

1129
01:00:14,600 --> 01:00:16,440
Speaker 1: not good for us. And so situations like that you

1130
01:00:16,520 --> 01:00:19,800
Speaker 1: gotta pas R. Yeah. Yeah, But the one that Josh

1131
01:00:19,880 --> 01:00:21,520
Speaker 1: was talking about this year, we had a bear that

1132
01:00:21,720 --> 01:00:24,800
Speaker 1: was in an old slash pile. I mean, but you know,

1133
01:00:24,880 --> 01:00:27,640
Speaker 1: the the land had been cleared for pasture and there

1134
01:00:27,800 --> 01:00:29,720
Speaker 1: was a big kind of dozer deck and it was

1135
01:00:29,840 --> 01:00:33,520
Speaker 1: really old and so pretty unstable. In some spots, and

1136
01:00:33,600 --> 01:00:35,400
Speaker 1: it took us a really long time to just figure

1137
01:00:35,440 --> 01:00:38,200
Speaker 1: out within this huge pile of I mean what we're

1138
01:00:38,480 --> 01:00:42,240
Speaker 1: standing trees at one point where the bear had created

1139
01:00:42,360 --> 01:00:47,040
Speaker 1: kind of this den within Oh yeah, I mean we

1140
01:00:47,280 --> 01:00:49,480
Speaker 1: we for the longest time we figured okay, we could

1141
01:00:49,560 --> 01:00:53,960
Speaker 1: pinpoint like where I guess geo spatially within the pile

1142
01:00:54,120 --> 01:00:57,360
Speaker 1: she was, but how she was getting into the pile.

1143
01:00:57,800 --> 01:00:59,680
Speaker 1: I mean, it was like detective work. We're like, okay,

1144
01:00:59,680 --> 01:01:03,160
Speaker 1: I see grass clippings over here, because they'll they'll bring

1145
01:01:03,280 --> 01:01:05,000
Speaker 1: leaves in and when there's no leaves, I mean, if

1146
01:01:05,000 --> 01:01:06,560
Speaker 1: we have bears that are in this instance, it was

1147
01:01:06,560 --> 01:01:09,120
Speaker 1: surrounded by pasture, they bring in pasture grass and that's

1148
01:01:09,120 --> 01:01:12,520
Speaker 1: what they make their nest out of, so they'll move

1149
01:01:12,560 --> 01:01:14,560
Speaker 1: it so we can see. We could see some clumps

1150
01:01:14,600 --> 01:01:17,920
Speaker 1: that kind of lead to the area where we suspected

1151
01:01:18,000 --> 01:01:21,520
Speaker 1: she was, and so um, we we got up to her,

1152
01:01:22,000 --> 01:01:24,960
Speaker 1: finally figured out where she was, realized that the way

1153
01:01:25,040 --> 01:01:27,880
Speaker 1: she was coming in, just with the stability of the pile,

1154
01:01:27,920 --> 01:01:29,720
Speaker 1: probably wasn't safe for us to walk in that way.

1155
01:01:29,800 --> 01:01:31,440
Speaker 1: So I kind of said, okay, if we're gonna if

1156
01:01:31,440 --> 01:01:32,720
Speaker 1: we're gonna try to get at her. We have to

1157
01:01:32,760 --> 01:01:35,720
Speaker 1: get her the other way. That's gonna require some saws.

1158
01:01:35,760 --> 01:01:37,840
Speaker 1: We're gonna have to cut some of these logs just

1159
01:01:37,920 --> 01:01:41,000
Speaker 1: to be able for me to squeeze in. And so, um,

1160
01:01:41,480 --> 01:01:43,440
Speaker 1: we got to the point and you know, you know,

1161
01:01:43,520 --> 01:01:46,240
Speaker 1: bears popped their jaws when they're uncomfortable, right, and so

1162
01:01:46,640 --> 01:01:50,160
Speaker 1: in some dens, they'll hear us come in fifteen, you know,

1163
01:01:50,360 --> 01:01:53,240
Speaker 1: thirty yards away and they're already popping their jaws because

1164
01:01:53,320 --> 01:01:55,320
Speaker 1: they're just they're just letting us know they're not happy

1165
01:01:55,360 --> 01:01:58,200
Speaker 1: about it. Others never pop their jaws. The entire time

1166
01:01:58,240 --> 01:02:01,160
Speaker 1: that we're there just kind of depends. Um, but this bear,

1167
01:02:01,320 --> 01:02:04,360
Speaker 1: we we kind of cut out the logs away. I

1168
01:02:04,480 --> 01:02:07,480
Speaker 1: weaved the jab pole into the opening, and she basically

1169
01:02:07,560 --> 01:02:10,440
Speaker 1: had within this brush pile. There was an earth platform

1170
01:02:10,600 --> 01:02:13,040
Speaker 1: that she was on, but it was a long tube

1171
01:02:13,320 --> 01:02:16,600
Speaker 1: that led to where she was. So so she kind

1172
01:02:16,600 --> 01:02:18,959
Speaker 1: of had this just hollowed out area within this brush pile.

1173
01:02:19,440 --> 01:02:22,280
Speaker 1: Um that was basically the length of our jab pole,

1174
01:02:22,560 --> 01:02:27,040
Speaker 1: And so I kind of hung in upside down, had

1175
01:02:27,080 --> 01:02:31,600
Speaker 1: the jab pole kind of swinging above my head, and um,

1176
01:02:32,280 --> 01:02:34,480
Speaker 1: and you know, tried to get everything ready laid the

1177
01:02:34,520 --> 01:02:36,880
Speaker 1: flashlight on the bottom, so I can, you know, identify

1178
01:02:37,000 --> 01:02:39,200
Speaker 1: my target, make sure i'm jabbing where I'm you know,

1179
01:02:39,240 --> 01:02:41,360
Speaker 1: I'm comfortable jabbing and everything like that. And I could

1180
01:02:41,360 --> 01:02:43,000
Speaker 1: see her cubs, you know, where she was at, and

1181
01:02:43,520 --> 01:02:45,840
Speaker 1: she kind of turned her body and squared up a

1182
01:02:45,880 --> 01:02:47,880
Speaker 1: little bit with the opening, which is what they do.

1183
01:02:48,000 --> 01:02:49,840
Speaker 1: I mean, odd times they'll do that. And then that's

1184
01:02:49,840 --> 01:02:51,480
Speaker 1: when we jab him in the front shoulder. We can

1185
01:02:51,520 --> 01:02:53,400
Speaker 1: get him in the pectoral muscles if we have to,

1186
01:02:53,640 --> 01:02:56,800
Speaker 1: and um. And so I remember looking at Josh and

1187
01:02:56,840 --> 01:02:58,840
Speaker 1: and like I think she she's she's squaring up at

1188
01:02:58,880 --> 01:03:01,080
Speaker 1: the entrance, and I was like, all right, I'm gonna

1189
01:03:01,160 --> 01:03:03,320
Speaker 1: go for this, and I'm I'm hanging in and I'm

1190
01:03:03,400 --> 01:03:05,840
Speaker 1: like I'm dangling at my waist upside down, you know,

1191
01:03:05,960 --> 01:03:09,160
Speaker 1: looking at this bear. And right when I went to

1192
01:03:09,320 --> 01:03:12,760
Speaker 1: jab her the second the needle just brushed her. For

1193
01:03:13,280 --> 01:03:15,520
Speaker 1: she came straight for the opening, and there was a

1194
01:03:15,680 --> 01:03:18,840
Speaker 1: log there that she stopped at, and I just remember

1195
01:03:19,080 --> 01:03:21,040
Speaker 1: like chucking the jab pull back as far as I

1196
01:03:21,080 --> 01:03:24,200
Speaker 1: couldn't coming out, and and he was standing there and

1197
01:03:24,400 --> 01:03:27,600
Speaker 1: I was like, huh, she just bluff charged the entrance.

1198
01:03:27,640 --> 01:03:30,480
Speaker 1: But that log stopped her and and and so I

1199
01:03:30,600 --> 01:03:32,960
Speaker 1: kind of looked back in and the way she was

1200
01:03:33,080 --> 01:03:35,240
Speaker 1: she was squared up again, like there's you know, there's

1201
01:03:35,240 --> 01:03:37,000
Speaker 1: no way, there's no way that I'm gonna be able

1202
01:03:37,000 --> 01:03:38,919
Speaker 1: to jab this bear. At this point, We're just gonna

1203
01:03:39,000 --> 01:03:41,560
Speaker 1: have to let her be and we'll we'll try to

1204
01:03:41,640 --> 01:03:43,600
Speaker 1: trap her if she needs her collar and stuff like that.

1205
01:03:43,800 --> 01:03:48,400
Speaker 1: But that was probably my most Yeah, told Laura I

1206
01:03:48,480 --> 01:03:52,240
Speaker 1: was going to dart her. I'll just I'll just put

1207
01:03:54,280 --> 01:03:55,880
Speaker 1: that was one of those where I went home and

1208
01:03:56,080 --> 01:03:58,480
Speaker 1: and and told my husband, I'm like, but we had

1209
01:03:58,520 --> 01:04:03,680
Speaker 1: everything under control, and we did not for them stuff. Now,

1210
01:04:03,720 --> 01:04:06,080
Speaker 1: I mean we occasionally will when we're trapping. Uh you

1211
01:04:06,120 --> 01:04:09,960
Speaker 1: know sometimes when we're trapping, you know, we're primarily targeting females,

1212
01:04:10,320 --> 01:04:13,480
Speaker 1: so so we still get males that come into the trap,

1213
01:04:13,600 --> 01:04:16,120
Speaker 1: and especially during the breeding season, some of those males

1214
01:04:16,160 --> 01:04:19,080
Speaker 1: are really persistent, especially the big breeding age males you

1215
01:04:19,160 --> 01:04:23,400
Speaker 1: know are three four fifty pound males. Um. So we

1216
01:04:23,480 --> 01:04:26,120
Speaker 1: will occasionally carry bear spray when when we know we've

1217
01:04:26,160 --> 01:04:28,520
Speaker 1: got one of those that's just constantly coming into the

1218
01:04:28,520 --> 01:04:30,960
Speaker 1: trap site and stuff like that. But um, but for

1219
01:04:31,080 --> 01:04:33,920
Speaker 1: the den work, we don't. And and in that instance,

1220
01:04:34,200 --> 01:04:36,720
Speaker 1: I most definitely would have sprayed myself if if I

1221
01:04:36,880 --> 01:04:39,240
Speaker 1: even if I even tried, you know. And so so

1222
01:04:39,400 --> 01:04:43,000
Speaker 1: that that's where it comes into this, like it's that

1223
01:04:43,080 --> 01:04:45,600
Speaker 1: cost benefit just weighing the pros and cons of working

1224
01:04:45,640 --> 01:04:47,360
Speaker 1: the den. So everything that we do, you know, we're

1225
01:04:47,400 --> 01:04:49,680
Speaker 1: not going to do anything that's going to be detrimental

1226
01:04:49,800 --> 01:04:52,280
Speaker 1: to the bear. We're doing everything with the bear safety

1227
01:04:52,360 --> 01:04:55,160
Speaker 1: in mind. Um, when we handle them, you know, we

1228
01:04:55,520 --> 01:04:59,080
Speaker 1: were constantly checking their condition and making sure that they're

1229
01:04:59,120 --> 01:05:01,080
Speaker 1: not having any ill effect from the drugs and things

1230
01:05:01,160 --> 01:05:04,280
Speaker 1: like that. Um, but even within those dens, then and

1231
01:05:04,360 --> 01:05:06,080
Speaker 1: then and then the second part of it is okay,

1232
01:05:06,720 --> 01:05:09,360
Speaker 1: our safety, you know, is it is it a pile

1233
01:05:09,400 --> 01:05:11,760
Speaker 1: that we can climb onto when they're in rocket Your safety,

1234
01:05:11,800 --> 01:05:15,560
Speaker 1: not Josh, I'm just gonna grab her ankles and pull

1235
01:05:15,600 --> 01:05:17,000
Speaker 1: her back. One thing I want to say, that's what

1236
01:05:17,120 --> 01:05:20,919
Speaker 1: you're gonna say about feet. We've we've had like grab

1237
01:05:21,000 --> 01:05:22,840
Speaker 1: belt loops and stuff for But I was gonna say

1238
01:05:22,840 --> 01:05:25,760
Speaker 1: a caveat to our listeners here, Uh, don't go into

1239
01:05:25,800 --> 01:05:28,360
Speaker 1: bear Den's. Well, even if you know where bear Den's are,

1240
01:05:28,560 --> 01:05:30,840
Speaker 1: we have a lot of people besides me and Laura,

1241
01:05:30,960 --> 01:05:32,640
Speaker 1: let's say, are in the hole. We've got ten people

1242
01:05:32,720 --> 01:05:35,160
Speaker 1: behind us that are carrying things. And we have between

1243
01:05:35,160 --> 01:05:37,360
Speaker 1: all of us years of experience of what's normal, what's

1244
01:05:37,400 --> 01:05:41,120
Speaker 1: not normal, that's not normal behavior, And this one incident,

1245
01:05:41,240 --> 01:05:44,000
Speaker 1: we've done a hundred that I've been completely boring, and

1246
01:05:44,320 --> 01:05:46,240
Speaker 1: then you had this one. But but again, don't mess

1247
01:05:46,280 --> 01:05:48,640
Speaker 1: with bears that you know, don't mess with cubs, don't

1248
01:05:48,680 --> 01:05:51,040
Speaker 1: go in the dens, even though it's the thing people

1249
01:05:51,120 --> 01:05:55,240
Speaker 1: can do that our wildlife professionals, don't mess with bears. Yeah, exactly. Yeah,

1250
01:05:55,280 --> 01:05:56,840
Speaker 1: And and and that's one of those things too. You know,

1251
01:05:57,240 --> 01:06:00,520
Speaker 1: when you think about disturbance, you know, those those bears

1252
01:06:00,600 --> 01:06:03,880
Speaker 1: they tolerate a certain level of disturbance and then beyond that,

1253
01:06:04,560 --> 01:06:07,480
Speaker 1: some of them have a lower threshold than others. And

1254
01:06:07,800 --> 01:06:09,840
Speaker 1: and you don't want to be the reason. You know,

1255
01:06:10,160 --> 01:06:13,600
Speaker 1: you're making them move in the winter when they shouldn't

1256
01:06:13,600 --> 01:06:16,240
Speaker 1: normally be moving, and things like that. And and we

1257
01:06:16,360 --> 01:06:18,920
Speaker 1: do get the question in terms of our research, um

1258
01:06:19,160 --> 01:06:21,800
Speaker 1: if if this disturbance is bad for them? And the

1259
01:06:21,880 --> 01:06:24,200
Speaker 1: one thing this type of den work has been going

1260
01:06:24,320 --> 01:06:29,360
Speaker 1: on since bear research has been going that's right alive

1261
01:06:29,440 --> 01:06:32,760
Speaker 1: the next year if our cubs survives. Yeah. Yeah, so

1262
01:06:32,920 --> 01:06:35,280
Speaker 1: you know you know that you're not hurting, that's right. Yeah,

1263
01:06:35,320 --> 01:06:37,440
Speaker 1: And and we have you know, there's when you think

1264
01:06:37,480 --> 01:06:40,600
Speaker 1: about just bear researchers across the country, you know, kind

1265
01:06:40,600 --> 01:06:42,880
Speaker 1: of the collective knowledge of all the bear biologists that

1266
01:06:42,960 --> 01:06:46,120
Speaker 1: have done research projects like this, in all the university

1267
01:06:46,240 --> 01:06:49,280
Speaker 1: researchers that have done research like this. Um, you can

1268
01:06:49,320 --> 01:06:51,840
Speaker 1: look to a lot of other states and and this

1269
01:06:52,120 --> 01:06:55,480
Speaker 1: is a very common way of monitoring the population. So

1270
01:06:55,640 --> 01:06:58,680
Speaker 1: it's it's one of those and it's it's incredible that

1271
01:06:58,760 --> 01:07:00,680
Speaker 1: bears will let you do it. I mean, if you

1272
01:07:00,720 --> 01:07:03,400
Speaker 1: think about it, I mean like there's there's a there's

1273
01:07:03,400 --> 01:07:06,120
Speaker 1: a lot of small things that could be different that

1274
01:07:06,160 --> 01:07:09,280
Speaker 1: would make that totally un people don't do didn't work

1275
01:07:09,320 --> 01:07:12,960
Speaker 1: with grizzly bears. Yeah, that's a great example. I mean,

1276
01:07:13,000 --> 01:07:17,120
Speaker 1: you said, a bears, black bears, semi docile. We'll let

1277
01:07:17,200 --> 01:07:19,640
Speaker 1: you come up to it. What's the I want it?

1278
01:07:19,760 --> 01:07:23,880
Speaker 1: So I want to get to uh, Missouri's the management

1279
01:07:23,960 --> 01:07:25,880
Speaker 1: stuff that you guys are talking about. I saw the

1280
01:07:26,000 --> 01:07:28,720
Speaker 1: survey the other day that you guys put out. I

1281
01:07:28,800 --> 01:07:30,800
Speaker 1: thought was really good. Um, so I want to get

1282
01:07:30,840 --> 01:07:33,479
Speaker 1: to that. But before that, Uh, what's the biggest bear,

1283
01:07:34,000 --> 01:07:37,080
Speaker 1: legitimate bear that you guys have weighed in Missouri. It

1284
01:07:37,200 --> 01:07:39,240
Speaker 1: wasn't while I was here, so it was before I started,

1285
01:07:39,280 --> 01:07:42,000
Speaker 1: and I want to say it was around five forty

1286
01:07:42,040 --> 01:07:45,720
Speaker 1: five pounds or something like that. It was just it

1287
01:07:45,880 --> 01:07:48,520
Speaker 1: was just over that five mark. But remember, you know,

1288
01:07:48,880 --> 01:07:52,800
Speaker 1: we're trapping. It was a summer, so we're trapping these

1289
01:07:52,880 --> 01:07:56,160
Speaker 1: males in the in basically when they are probably at

1290
01:07:56,200 --> 01:07:58,840
Speaker 1: their lowest weight. So so this time of year right now,

1291
01:07:58,920 --> 01:08:01,880
Speaker 1: we're doing our bear trapping and we've had you know,

1292
01:08:02,040 --> 01:08:04,800
Speaker 1: in our traps, we use big their trailer traps. They're

1293
01:08:04,840 --> 01:08:10,000
Speaker 1: basically giant welded boxes and uh and and our big males,

1294
01:08:10,080 --> 01:08:11,640
Speaker 1: Like when we get up there, you know, one of

1295
01:08:11,720 --> 01:08:13,400
Speaker 1: the reasons, you know, we have to kind of assess

1296
01:08:13,440 --> 01:08:15,160
Speaker 1: the weight to figure out how much drug to give

1297
01:08:15,200 --> 01:08:18,000
Speaker 1: the animal, and and a lot of that comes with experience.

1298
01:08:18,040 --> 01:08:19,519
Speaker 1: We've worked a lot of bears, so we can we

1299
01:08:19,560 --> 01:08:21,040
Speaker 1: can look at them. But when we get these big

1300
01:08:21,120 --> 01:08:22,760
Speaker 1: males in the trap, you kind of look at like

1301
01:08:22,960 --> 01:08:26,080
Speaker 1: from okay, are his shoulders touching the top? And those

1302
01:08:26,200 --> 01:08:29,160
Speaker 1: really big boars their shoulders touched the top and then

1303
01:08:29,200 --> 01:08:31,160
Speaker 1: how low is his belly to the ground, right, Like

1304
01:08:31,200 --> 01:08:34,040
Speaker 1: how much light can I see underneath his belly? Because

1305
01:08:34,320 --> 01:08:37,240
Speaker 1: you know, a four year old male can be really lanky,

1306
01:08:37,560 --> 01:08:39,439
Speaker 1: really tall, but they just don't have the meat on them.

1307
01:08:39,479 --> 01:08:41,439
Speaker 1: But those those big boars, I mean, and we've worked

1308
01:08:41,560 --> 01:08:44,759
Speaker 1: some that are between that three fifty and four hundred

1309
01:08:44,800 --> 01:08:48,120
Speaker 1: pounds in June, you know, before the Barry cross has

1310
01:08:48,160 --> 01:08:50,200
Speaker 1: really kicked in. So those bears are going to be

1311
01:08:50,280 --> 01:08:55,280
Speaker 1: big in the fall. Yeah. With the the din study,

1312
01:08:55,360 --> 01:08:57,160
Speaker 1: how often does a female go back to the same

1313
01:08:57,240 --> 01:09:00,479
Speaker 1: dn or did they hop around? It's very able, but

1314
01:09:00,840 --> 01:09:03,559
Speaker 1: um so we have We've had one bear in our

1315
01:09:03,640 --> 01:09:07,240
Speaker 1: study that used the same den three years in a row.

1316
01:09:07,479 --> 01:09:11,320
Speaker 1: And she was actually an even more interesting story. Um

1317
01:09:11,800 --> 01:09:14,320
Speaker 1: we we had her with newborns one year, we had

1318
01:09:14,360 --> 01:09:18,120
Speaker 1: her with yearlings another year, and then um we we

1319
01:09:18,200 --> 01:09:19,840
Speaker 1: can't work the den it's in a cave, so we

1320
01:09:19,960 --> 01:09:22,439
Speaker 1: just put up cameras. She actually had what appeared to

1321
01:09:22,479 --> 01:09:24,600
Speaker 1: be her two year olds with their with her in

1322
01:09:24,720 --> 01:09:29,519
Speaker 1: that den, which is not something that is very Yeah,

1323
01:09:29,560 --> 01:09:31,080
Speaker 1: so she gave birth in the den and then when

1324
01:09:31,120 --> 01:09:33,080
Speaker 1: they were one, and then when they were too, So

1325
01:09:33,200 --> 01:09:35,360
Speaker 1: we had three times and and I kind of it

1326
01:09:35,479 --> 01:09:37,360
Speaker 1: wasn't something I had seen before and in the work

1327
01:09:37,439 --> 01:09:39,679
Speaker 1: that I've done, and so I kind of inquired around

1328
01:09:39,800 --> 01:09:41,720
Speaker 1: and and it was seen. It's been seen in a

1329
01:09:41,840 --> 01:09:44,800
Speaker 1: couple of other states, but it's definitely not something that

1330
01:09:45,080 --> 01:09:48,320
Speaker 1: is is very common. And so for for whatever reason,

1331
01:09:48,680 --> 01:09:50,439
Speaker 1: she didn't run them off like she normally would in

1332
01:09:50,479 --> 01:09:53,280
Speaker 1: the spring, or she didn't breed, and then she was

1333
01:09:53,360 --> 01:09:55,920
Speaker 1: just tolerant of them. I mean, I've had I've had

1334
01:09:56,000 --> 01:10:00,800
Speaker 1: sALS where they have newborns and then two year old

1335
01:10:00,960 --> 01:10:03,679
Speaker 1: is in relatively close proximity. That's why I was gonna

1336
01:10:03,680 --> 01:10:06,640
Speaker 1: ask if you've ever seen a year lying in and

1337
01:10:06,760 --> 01:10:10,599
Speaker 1: then with a newborn cub. I think it does happen. Yeah,

1338
01:10:10,680 --> 01:10:13,080
Speaker 1: we I don't not since I've been here, and I

1339
01:10:13,080 --> 01:10:14,840
Speaker 1: don't think that's something that we've seen here. But the

1340
01:10:14,960 --> 01:10:18,240
Speaker 1: idea behind that is that, um, you know, if if

1341
01:10:18,280 --> 01:10:21,519
Speaker 1: a sound loses her cubs during the breeding season, she'll

1342
01:10:21,520 --> 01:10:23,840
Speaker 1: go an asterisk and she'll breed again. And so the

1343
01:10:23,960 --> 01:10:26,720
Speaker 1: thought is that in some cases it might be that

1344
01:10:27,080 --> 01:10:30,600
Speaker 1: for whatever reason, the sound cub got separated for a

1345
01:10:30,760 --> 01:10:33,439
Speaker 1: long enough time period she got bread and then they

1346
01:10:33,479 --> 01:10:37,560
Speaker 1: connected back up and then now you've got that reuniting,

1347
01:10:40,280 --> 01:10:42,519
Speaker 1: you know. But it's it's definitely not something that happens

1348
01:10:42,800 --> 01:10:46,720
Speaker 1: very frequently, you know. Um, before we get to really

1349
01:10:46,760 --> 01:10:49,880
Speaker 1: what we want to talk to about nuisance spars like, um,

1350
01:10:51,320 --> 01:10:54,280
Speaker 1: what what's what's the temperature of NUIs and spars? And

1351
01:10:54,360 --> 01:10:57,080
Speaker 1: Missouri So beauties in the eye of the beholder, We'll

1352
01:10:57,080 --> 01:10:59,759
Speaker 1: put it that way. We get everything from people calling

1353
01:10:59,840 --> 01:11:01,760
Speaker 1: to because I saw a bear in my backyard and

1354
01:11:01,800 --> 01:11:03,960
Speaker 1: you need to come get it. Well, that's not gonna

1355
01:11:04,000 --> 01:11:06,640
Speaker 1: happen all the way to I've worked to been on

1356
01:11:06,720 --> 01:11:09,559
Speaker 1: two landowners properties this week that I've had bee hives

1357
01:11:09,640 --> 01:11:13,719
Speaker 1: that have been fut and demolished, eaten by bears. Classic, yep, classic,

1358
01:11:13,800 --> 01:11:15,719
Speaker 1: And it's the same thing that we've talked about before,

1359
01:11:15,840 --> 01:11:17,800
Speaker 1: people that have I've lived on this property in such

1360
01:11:17,840 --> 01:11:20,040
Speaker 1: and such counties since nineteen seventy two, and I've had

1361
01:11:20,080 --> 01:11:21,760
Speaker 1: bees the whole time, and I've never had to put

1362
01:11:21,800 --> 01:11:24,880
Speaker 1: electric fence up. Well today you do. And you know

1363
01:11:24,960 --> 01:11:26,800
Speaker 1: there's gonna be more bears next year than there are

1364
01:11:26,880 --> 01:11:29,280
Speaker 1: this year. And so it's especially if you keep feeding honey,

1365
01:11:29,360 --> 01:11:30,880
Speaker 1: if you keep feeding money and you know, and as

1366
01:11:30,920 --> 01:11:33,080
Speaker 1: you know, they like the they like the larvae, they

1367
01:11:33,120 --> 01:11:34,800
Speaker 1: like the broods. There's more than just the honey. So

1368
01:11:34,920 --> 01:11:38,639
Speaker 1: there's that, uh, we get I mean literally everything under

1369
01:11:38,640 --> 01:11:41,320
Speaker 1: the sun. We get your common bird feeder calls, garbage

1370
01:11:41,400 --> 01:11:46,559
Speaker 1: calls all across the state. We get chicken coops sometimes,

1371
01:11:46,720 --> 01:11:50,679
Speaker 1: people that still feed pets outside. When's the prime time

1372
01:11:50,760 --> 01:11:53,600
Speaker 1: for nuisance calls? Right now? The earliest so there no

1373
01:11:53,760 --> 01:11:57,000
Speaker 1: berries are right, Yeah, So the earliest I personally have

1374
01:11:57,080 --> 01:11:59,280
Speaker 1: had is April first, April fools Day. I've had nuisance

1375
01:11:59,360 --> 01:12:02,360
Speaker 1: calls all the way from April Fool's Day through like October. Yeah,

1376
01:12:03,160 --> 01:12:04,920
Speaker 1: we see in a lot of places, you know, you'll

1377
01:12:04,960 --> 01:12:07,280
Speaker 1: see especially if you've got a dry summer where you

1378
01:12:07,400 --> 01:12:09,759
Speaker 1: don't have a good berry crop, then you've got bears

1379
01:12:09,800 --> 01:12:12,160
Speaker 1: that are switching to alternate foods. I mean, we had

1380
01:12:12,200 --> 01:12:14,600
Speaker 1: a bear that was grazing wheat at one of our

1381
01:12:14,680 --> 01:12:17,160
Speaker 1: areas that was a very popular hiking trail, so we

1382
01:12:17,240 --> 01:12:19,560
Speaker 1: got a lot of that, a lot of calls. It

1383
01:12:19,640 --> 01:12:21,479
Speaker 1: was sitting in a wheat field, a food plot that

1384
01:12:21,560 --> 01:12:24,080
Speaker 1: we had planted, eating the heads off a wheat, sitting

1385
01:12:24,120 --> 01:12:26,360
Speaker 1: on its back, on its belly, you know, raking it

1386
01:12:26,439 --> 01:12:29,479
Speaker 1: in and everybody pushing literally pushing strollers walking by looking

1387
01:12:29,479 --> 01:12:31,479
Speaker 1: at this bear eating the heads off a wheat. But

1388
01:12:31,560 --> 01:12:33,680
Speaker 1: it was a very dry summer that year, and so

1389
01:12:33,840 --> 01:12:35,800
Speaker 1: he was really not wanting to leave them, and that

1390
01:12:35,960 --> 01:12:37,880
Speaker 1: in that summer, you know, we saw an increase in

1391
01:12:38,439 --> 01:12:41,000
Speaker 1: complaints of bear showing up bird feeders, bear showing up

1392
01:12:41,040 --> 01:12:43,040
Speaker 1: a trash and things like that. I mean, so so

1393
01:12:43,400 --> 01:12:46,559
Speaker 1: we we see, you know, that kind of fluctuation between

1394
01:12:46,720 --> 01:12:49,720
Speaker 1: years and then and then within seasons. And the other

1395
01:12:49,840 --> 01:12:51,720
Speaker 1: part of it too is you know, right now, this

1396
01:12:51,960 --> 01:12:56,000
Speaker 1: is dispersal time. So those eighteen month olds, Yeah, those

1397
01:12:56,080 --> 01:12:58,960
Speaker 1: young ones are set off on their own, and the

1398
01:12:59,040 --> 01:13:01,479
Speaker 1: young males, they wander huge distances. And so these are

1399
01:13:01,520 --> 01:13:03,320
Speaker 1: the bears that show up south to St. Louis, and

1400
01:13:03,720 --> 01:13:06,200
Speaker 1: in general they don't stay in one place for very long.

1401
01:13:06,320 --> 01:13:08,760
Speaker 1: But when they moved through, boy, they generate a lot

1402
01:13:08,800 --> 01:13:11,960
Speaker 1: of phone calls because it's like they're in neighborhoods or

1403
01:13:12,439 --> 01:13:14,760
Speaker 1: or they're just really in areas where folks are like, wait,

1404
01:13:14,800 --> 01:13:17,120
Speaker 1: there's a that can't be a bear, right, and no,

1405
01:13:17,280 --> 01:13:19,280
Speaker 1: it is a bear, and then it's like okay, and

1406
01:13:19,360 --> 01:13:21,160
Speaker 1: then you know, and as it moves through you can

1407
01:13:21,240 --> 01:13:23,120
Speaker 1: kind of track just that one bear. Okay, I think

1408
01:13:23,160 --> 01:13:25,000
Speaker 1: it's I think it's over here now, right now, it's

1409
01:13:25,000 --> 01:13:27,360
Speaker 1: switched counties, it's over here, and it's moved on. Um.

1410
01:13:27,680 --> 01:13:29,400
Speaker 1: And then you couple this time of year with the

1411
01:13:29,439 --> 01:13:32,960
Speaker 1: breeding season and those breeding age males, you know, they

1412
01:13:33,080 --> 01:13:36,880
Speaker 1: just cover huge ground. So the more something's moving, the

1413
01:13:37,000 --> 01:13:39,120
Speaker 1: more likely it is that maybe it's going to cross

1414
01:13:39,120 --> 01:13:42,120
Speaker 1: the road and get seen and stuff like that. So um,

1415
01:13:42,200 --> 01:13:44,840
Speaker 1: our our bear reports are just you know, they're rolling

1416
01:13:44,880 --> 01:13:48,240
Speaker 1: in daily, you know, and the vast majority of reports

1417
01:13:48,320 --> 01:13:50,280
Speaker 1: that we get from the public are just sightings. You know,

1418
01:13:50,360 --> 01:13:53,200
Speaker 1: they're not they're not all nuisance issues, right, and and

1419
01:13:53,280 --> 01:13:56,200
Speaker 1: a lot of them are just you know, folks excited

1420
01:13:56,400 --> 01:13:59,719
Speaker 1: about what they saw or seeking more information like, Okay,

1421
01:13:59,760 --> 01:14:01,639
Speaker 1: this is the first time I've ever seen a bear.

1422
01:14:02,080 --> 01:14:04,000
Speaker 1: What in the world am I supposed to do about that?

1423
01:14:04,040 --> 01:14:06,760
Speaker 1: What do I do? What's your advice? Kind of stuff? Um.

1424
01:14:06,920 --> 01:14:08,760
Speaker 1: And then and then, as Josh said, we do get

1425
01:14:08,840 --> 01:14:11,639
Speaker 1: those instances where you know, the bear is seeking out

1426
01:14:11,720 --> 01:14:14,120
Speaker 1: those easy food sources and causing damage. And when we

1427
01:14:14,240 --> 01:14:18,320
Speaker 1: look at our you know, human bear conflicts, the vast

1428
01:14:18,360 --> 01:14:20,360
Speaker 1: majority of them are centered around food, right, It's it's

1429
01:14:20,439 --> 01:14:22,680
Speaker 1: those bee hives, it's the chicken coops and things like that.

1430
01:14:22,880 --> 01:14:25,920
Speaker 1: And then every year we we get the occasional bear

1431
01:14:26,040 --> 01:14:29,880
Speaker 1: that will wander into town. Believe I hadn't talked about that,

1432
01:14:30,000 --> 01:14:32,320
Speaker 1: like the big thing that the probably the most famous

1433
01:14:32,400 --> 01:14:34,840
Speaker 1: one is we have. I have a counterpart in St. Louis,

1434
01:14:34,960 --> 01:14:37,400
Speaker 1: tom we had a bear walk inside a church that

1435
01:14:37,479 --> 01:14:40,040
Speaker 1: had the doors open that they have I think it's

1436
01:14:40,040 --> 01:14:42,840
Speaker 1: a parochial school or something, so they have there's people there,

1437
01:14:43,080 --> 01:14:45,200
Speaker 1: so the doors are open for the breeze, and long

1438
01:14:45,280 --> 01:14:47,000
Speaker 1: story shot at the bear ended up in the boy's

1439
01:14:47,040 --> 01:14:50,280
Speaker 1: bathroom and couldn't get out because the doorship. And so

1440
01:14:50,400 --> 01:14:52,560
Speaker 1: that my counterpart went in there and darted it in

1441
01:14:52,640 --> 01:14:55,120
Speaker 1: a stall and we had to I say, we the department.

1442
01:14:55,160 --> 01:14:57,080
Speaker 1: We had to carry it out. But but yes, that's

1443
01:14:57,120 --> 01:14:59,360
Speaker 1: part of the whole culture thing is I've done a

1444
01:14:59,400 --> 01:15:01,720
Speaker 1: bunch of the where literally a bear walks into town

1445
01:15:01,760 --> 01:15:03,880
Speaker 1: at night following his nose. Usually it's a two year

1446
01:15:03,920 --> 01:15:07,000
Speaker 1: old male. As the city starts to come alive at

1447
01:15:07,040 --> 01:15:09,120
Speaker 1: eight o'clock traffic people are going to work. Well, then

1448
01:15:09,120 --> 01:15:10,840
Speaker 1: he runs up a tree because he's scared. Well, the

1449
01:15:10,920 --> 01:15:14,439
Speaker 1: tree might be the courthouse square, a playground. Well, now

1450
01:15:14,560 --> 01:15:16,640
Speaker 1: there's news involved because we haven't had a bear in

1451
01:15:16,680 --> 01:15:19,640
Speaker 1: Missouri and two hundred years people, and now it's up

1452
01:15:19,680 --> 01:15:21,559
Speaker 1: a tree, and and so you know, it ends up

1453
01:15:21,600 --> 01:15:24,080
Speaker 1: being you know, almost a state of emergency depending on

1454
01:15:24,200 --> 01:15:26,559
Speaker 1: the type of people involved. And so that always ends

1455
01:15:26,600 --> 01:15:28,240
Speaker 1: up being its own deal. And sometimes you can just

1456
01:15:28,400 --> 01:15:30,040
Speaker 1: wait till night and it comes down the tree and

1457
01:15:30,080 --> 01:15:32,640
Speaker 1: it walks away. That's the best thing. Every once in

1458
01:15:32,680 --> 01:15:34,519
Speaker 1: a while, we'll get in a situation where it is

1459
01:15:34,600 --> 01:15:37,320
Speaker 1: such an urban center where we'll try very hard to

1460
01:15:37,400 --> 01:15:39,760
Speaker 1: grab that bear and not that we're gonna relocate him,

1461
01:15:39,760 --> 01:15:41,360
Speaker 1: but I'm gonna move him outside of town so he

1462
01:15:41,400 --> 01:15:43,639
Speaker 1: didn't get hit by traffic. He doesn't. We're not making

1463
01:15:43,680 --> 01:15:45,639
Speaker 1: this problem prolonged. And so we do some of those

1464
01:15:45,720 --> 01:15:48,280
Speaker 1: two yeah, and and we do a lot of discussion

1465
01:15:48,320 --> 01:15:50,200
Speaker 1: to you know, about the fed bears, a dead bear

1466
01:15:50,280 --> 01:15:53,080
Speaker 1: and stuff like that, because i mean, you know, even

1467
01:15:53,120 --> 01:15:55,439
Speaker 1: though we have a low density population, we still have

1468
01:15:55,600 --> 01:15:57,760
Speaker 1: bears that that show up in town. And we have

1469
01:15:57,920 --> 01:16:01,240
Speaker 1: sun bears that get to be very assistant with the food.

1470
01:16:01,320 --> 01:16:04,920
Speaker 1: Whether it's bears that are a bear that's continually busting

1471
01:16:04,960 --> 01:16:06,800
Speaker 1: through electric fence to get at bees, you know, and

1472
01:16:06,920 --> 01:16:10,040
Speaker 1: once they start doing that, it's really hard to to

1473
01:16:10,240 --> 01:16:13,000
Speaker 1: push them off doing it. And or or the bears

1474
01:16:13,040 --> 01:16:15,640
Speaker 1: that are getting more bold and breaking into porches and

1475
01:16:15,680 --> 01:16:18,280
Speaker 1: stuff like that, And it doesn't happen all the time,

1476
01:16:19,120 --> 01:16:21,920
Speaker 1: but it does, and so it just goes all the way.

1477
01:16:21,920 --> 01:16:24,040
Speaker 1: You know, it's that continuous look of loop loop of

1478
01:16:24,280 --> 01:16:27,680
Speaker 1: education because it's you know, these things are preventable, but

1479
01:16:27,800 --> 01:16:29,960
Speaker 1: once the bear goes down that road. Sometimes we get

1480
01:16:30,040 --> 01:16:32,800
Speaker 1: to the situation and you know, it's not a situation

1481
01:16:32,880 --> 01:16:34,760
Speaker 1: that we're happy about where we have to go in

1482
01:16:34,880 --> 01:16:36,519
Speaker 1: and you know, or Josh would have to go in

1483
01:16:36,960 --> 01:16:40,280
Speaker 1: and euthanize a bear. But it does happen. It's unfortunate

1484
01:16:40,360 --> 01:16:43,519
Speaker 1: when it does. But you know, are there times you

1485
01:16:43,600 --> 01:16:45,400
Speaker 1: have to get really creative where you can't get a

1486
01:16:45,439 --> 01:16:48,640
Speaker 1: trapped in or the bear just isn't there too. So

1487
01:16:48,760 --> 01:16:51,680
Speaker 1: I mean, yes and no. We as a department, you know,

1488
01:16:51,720 --> 01:16:54,240
Speaker 1: we do a lot well I I personally, and and

1489
01:16:54,360 --> 01:16:56,200
Speaker 1: the other we there's six guys that have my job

1490
01:16:56,280 --> 01:16:58,240
Speaker 1: title in the state, and we all try very hard

1491
01:16:58,280 --> 01:17:00,519
Speaker 1: to help the public with these because exactly. It's like

1492
01:17:00,800 --> 01:17:02,479
Speaker 1: most of the public, it's like you drop these things

1493
01:17:02,520 --> 01:17:04,719
Speaker 1: off from matter space have no idea what to expect.

1494
01:17:05,000 --> 01:17:06,720
Speaker 1: People don't even know they climb trees, you know, and

1495
01:17:06,760 --> 01:17:08,680
Speaker 1: they just don't know what to expect. So we loan

1496
01:17:08,760 --> 01:17:14,080
Speaker 1: out electrical fences. Sometimes I've used rubber buckshot, I've used pyrotechnics.

1497
01:17:14,160 --> 01:17:16,960
Speaker 1: I even have an electric doormat. So if you had

1498
01:17:17,120 --> 01:17:19,360
Speaker 1: a bear that was getting on your porch, obviously he's

1499
01:17:19,439 --> 01:17:21,760
Speaker 1: climbing up the stairs, we can maybe stop that before

1500
01:17:21,760 --> 01:17:23,479
Speaker 1: he even gets up the stairs. I could use that

1501
01:17:24,080 --> 01:17:29,679
Speaker 1: sometimes possibility possibility, say I didn't invent it, there's these problems,

1502
01:17:32,160 --> 01:17:34,960
Speaker 1: say it's actually there's some outfits out in Tahoe. You know,

1503
01:17:35,040 --> 01:17:37,879
Speaker 1: this is a lot more common problems. And so I've

1504
01:17:37,960 --> 01:17:39,800
Speaker 1: dealt with some of those people out there. But but yeah,

1505
01:17:39,840 --> 01:17:42,000
Speaker 1: so sometimes you gotta get you know, kind of figure

1506
01:17:42,040 --> 01:17:45,280
Speaker 1: it out. I use a device. Actually I'm not really

1507
01:17:45,320 --> 01:17:46,920
Speaker 1: like trying to sell them, but critter getter. It's a

1508
01:17:46,960 --> 01:17:49,320
Speaker 1: noisemaker device that has a motion sensor. You can put

1509
01:17:49,360 --> 01:17:52,240
Speaker 1: that over a dumpster, so that generally will scare the

1510
01:17:52,280 --> 01:17:54,439
Speaker 1: bear away or it'll let the landowner no that. Now

1511
01:17:54,479 --> 01:17:56,519
Speaker 1: you can come outside and use these noisemakers that we

1512
01:17:56,640 --> 01:17:59,400
Speaker 1: lent you or whatever. So we really try because because yeah,

1513
01:17:59,400 --> 01:18:01,719
Speaker 1: I kind of reaching back to what we talked about before.

1514
01:18:02,040 --> 01:18:04,360
Speaker 1: If it's just a liability and and nobody will even

1515
01:18:04,400 --> 01:18:05,880
Speaker 1: help me with it, it's like, then what's the point

1516
01:18:05,920 --> 01:18:08,400
Speaker 1: of having in here. So we really try hard to

1517
01:18:08,479 --> 01:18:11,200
Speaker 1: make everybody have a positive react interaction as well as

1518
01:18:11,240 --> 01:18:12,800
Speaker 1: we don't want to put any more bears down than

1519
01:18:13,160 --> 01:18:15,040
Speaker 1: we don't put any down. But but yeah, you know,

1520
01:18:15,080 --> 01:18:17,720
Speaker 1: we really try to to fix that problem with when

1521
01:18:17,800 --> 01:18:20,640
Speaker 1: we can. Yeah, I think that no, no ahead, I

1522
01:18:20,720 --> 01:18:22,800
Speaker 1: think that kind of shapes gives more shape to what

1523
01:18:22,960 --> 01:18:24,640
Speaker 1: it is you actually do, because it's really teaching the

1524
01:18:24,680 --> 01:18:28,519
Speaker 1: public to or private or civilians, I guess because it

1525
01:18:28,600 --> 01:18:31,200
Speaker 1: seems like you could be so you can go mility

1526
01:18:31,200 --> 01:18:34,439
Speaker 1: in view. I'm just kidding, but no, uh, but just

1527
01:18:34,760 --> 01:18:37,320
Speaker 1: being able to go in and really education is the

1528
01:18:37,479 --> 01:18:39,840
Speaker 1: main thing that you do outside of and like the

1529
01:18:40,320 --> 01:18:42,840
Speaker 1: like nuisance and trapping is just kind of the small

1530
01:18:42,920 --> 01:18:46,360
Speaker 1: percentage of And so I think that would have been

1531
01:18:46,400 --> 01:18:48,720
Speaker 1: a disconnect sometimes inside of my mind, you know, it's

1532
01:18:48,760 --> 01:18:51,560
Speaker 1: like I'm so busy just relocating bears rather than oh, no,

1533
01:18:51,640 --> 01:18:53,720
Speaker 1: I'm going and I'm teaching these people how to do this,

1534
01:18:54,000 --> 01:18:57,080
Speaker 1: do that and equipping them to coexist. Well. And that's

1535
01:18:57,120 --> 01:18:59,480
Speaker 1: the thing, you know, And you'll talk to any wildlife

1536
01:18:59,520 --> 01:19:03,600
Speaker 1: management person. Wildlife management is people management. It's easy to

1537
01:19:03,680 --> 01:19:05,680
Speaker 1: plant seeds, it's easy to let them breed and do

1538
01:19:05,720 --> 01:19:07,559
Speaker 1: what they're gonna do. But getting the public to change,

1539
01:19:07,600 --> 01:19:11,040
Speaker 1: whether it's dear bear turkey, whatever, getting them to appreciate

1540
01:19:11,120 --> 01:19:14,080
Speaker 1: it or change their way of doing business, it's all.

1541
01:19:14,800 --> 01:19:16,800
Speaker 1: Darryl is another gentleman that works with me. You know.

1542
01:19:16,880 --> 01:19:19,000
Speaker 1: He said my time in college as a bartender helped

1543
01:19:19,000 --> 01:19:21,639
Speaker 1: me more than some of my classes because it's learning

1544
01:19:21,640 --> 01:19:23,280
Speaker 1: how to you know, how to relate to people, how

1545
01:19:23,280 --> 01:19:25,960
Speaker 1: to talk to people and get them to understand uh

1546
01:19:26,200 --> 01:19:27,800
Speaker 1: and and so yeah, that is a big part of

1547
01:19:27,840 --> 01:19:30,519
Speaker 1: what we do. And and you know, again, I think

1548
01:19:30,560 --> 01:19:32,400
Speaker 1: it helps that I'm that I'm a local guy, you know,

1549
01:19:32,520 --> 01:19:34,360
Speaker 1: I'm a Missourian. But you've got to be able to

1550
01:19:34,600 --> 01:19:36,439
Speaker 1: relate to people to understand that if I lost a

1551
01:19:36,479 --> 01:19:39,160
Speaker 1: five beehive and I've lived here for thirty years, I'm

1552
01:19:39,160 --> 01:19:42,280
Speaker 1: a little upset about it, and and rightly so, you know,

1553
01:19:42,439 --> 01:19:44,880
Speaker 1: And so again we we really try to help and

1554
01:19:45,120 --> 01:19:47,160
Speaker 1: and part of that ties back into the research. And

1555
01:19:47,320 --> 01:19:49,519
Speaker 1: you know, I've literally printed off maps from our data

1556
01:19:49,560 --> 01:19:52,080
Speaker 1: and been like, look, I let's say I came and

1557
01:19:52,240 --> 01:19:55,160
Speaker 1: killed this bear that's causing you problems. There's not one

1558
01:19:55,200 --> 01:19:57,519
Speaker 1: bear here. Look at this data. There's five more bears

1559
01:19:57,560 --> 01:19:59,640
Speaker 1: that you don't know about. They're literally walking down this

1560
01:19:59,800 --> 01:20:02,400
Speaker 1: rid that you've never seen before. We had an incident,

1561
01:20:02,760 --> 01:20:04,680
Speaker 1: it's not important where. We had an incident where we

1562
01:20:04,720 --> 01:20:06,600
Speaker 1: had an issue with a bear and I trapped it.

1563
01:20:06,960 --> 01:20:09,000
Speaker 1: And that same week, while I had this trap, said

1564
01:20:09,000 --> 01:20:11,040
Speaker 1: I had a bear run over on the road that

1565
01:20:11,200 --> 01:20:13,280
Speaker 1: was physical description was the same. I was like, well,

1566
01:20:13,280 --> 01:20:15,960
Speaker 1: there's that probably fixed my problem. It didn't. I had

1567
01:20:16,000 --> 01:20:18,280
Speaker 1: a trail camera from the neighbor across the road that

1568
01:20:18,360 --> 01:20:21,040
Speaker 1: had a bear picture that was that's probably him over there.

1569
01:20:21,479 --> 01:20:23,200
Speaker 1: I already had the bear in the trap while all

1570
01:20:23,240 --> 01:20:24,680
Speaker 1: three of these things happened, and so I took that

1571
01:20:24,760 --> 01:20:26,960
Speaker 1: to the landowner. I was looked, there was three bears

1572
01:20:27,000 --> 01:20:29,360
Speaker 1: that were two hundred fifty pounds within a half mile

1573
01:20:29,439 --> 01:20:31,400
Speaker 1: of your house, all at the same time. So so

1574
01:20:31,600 --> 01:20:33,120
Speaker 1: you need to you know, you need to change the

1575
01:20:33,160 --> 01:20:35,080
Speaker 1: way you do business. It's not that I'm gonna kill

1576
01:20:35,439 --> 01:20:38,320
Speaker 1: that bear. I'm gonna move that bear. And I said, Missouri,

1577
01:20:38,400 --> 01:20:40,320
Speaker 1: we don't really have a relocation thing. You know. It's

1578
01:20:40,320 --> 01:20:42,320
Speaker 1: not like Montana. I can't take them two hundred miles

1579
01:20:42,320 --> 01:20:44,080
Speaker 1: away and dumblin. I could take him to Clay's place

1580
01:20:44,080 --> 01:20:46,160
Speaker 1: and let him go. But he may, he may may.

1581
01:20:47,720 --> 01:20:49,599
Speaker 1: But you know that's the thing. Most people they say, well,

1582
01:20:49,640 --> 01:20:51,880
Speaker 1: you need to take that move it somewhere, and it's like, well, again,

1583
01:20:52,040 --> 01:20:54,479
Speaker 1: I can take it. I can take it to Branson,

1584
01:20:54,560 --> 01:20:56,679
Speaker 1: you know, I can take it to Springfield. Those people

1585
01:20:56,720 --> 01:20:59,479
Speaker 1: don't like that idea either, And so again it's gonna

1586
01:20:59,520 --> 01:21:01,639
Speaker 1: have to be a populace is going to have to understand.

1587
01:21:01,920 --> 01:21:03,680
Speaker 1: And that brings us to a good point here. And

1588
01:21:03,760 --> 01:21:05,160
Speaker 1: before I get to this point, I do want to

1589
01:21:05,200 --> 01:21:09,720
Speaker 1: talk about bear home ranges. But the nuisance stuff is

1590
01:21:10,160 --> 01:21:14,879
Speaker 1: essentially a big component of why we have to manage

1591
01:21:14,920 --> 01:21:18,000
Speaker 1: these animals through regulated hunting, you know, because that's that's

1592
01:21:18,040 --> 01:21:19,479
Speaker 1: a big question a lot of people have, is you know,

1593
01:21:19,560 --> 01:21:23,880
Speaker 1: why do we hunt bears? Uh? Number one, bears have

1594
01:21:24,040 --> 01:21:28,920
Speaker 1: been used historically in this country for forever, and they're

1595
01:21:29,000 --> 01:21:32,000
Speaker 1: great meat. It's a great animal I mean, it's so

1596
01:21:32,200 --> 01:21:36,160
Speaker 1: from the wildlife utilization standpoint, it's a sustainable resource. All

1597
01:21:36,200 --> 01:21:38,759
Speaker 1: these things that we know, like us hunting these bears

1598
01:21:38,880 --> 01:21:43,599
Speaker 1: is actually helping their populations in many cases. But the way,

1599
01:21:44,120 --> 01:21:46,680
Speaker 1: the way I describe it is there's only so much

1600
01:21:46,760 --> 01:21:50,040
Speaker 1: suitable bear habitat in Missouri or in Arkansas, or in

1601
01:21:50,120 --> 01:21:54,559
Speaker 1: Oklahoma or in Montana. There's only so much habitat, only

1602
01:21:54,680 --> 01:21:57,360
Speaker 1: so many bears can live in that habitat and maintain

1603
01:21:57,479 --> 01:22:00,719
Speaker 1: their health and fitness and have enough food, have enough space,

1604
01:22:00,800 --> 01:22:03,880
Speaker 1: have enough holes in the ground to then and bare

1605
01:22:03,960 --> 01:22:09,160
Speaker 1: populations increased by nine per year in in in this state.

1606
01:22:09,400 --> 01:22:12,880
Speaker 1: I did the math on the Arkansas population the other

1607
01:22:13,040 --> 01:22:17,120
Speaker 1: day at like basically, a population that's increasing by ten

1608
01:22:17,160 --> 01:22:20,840
Speaker 1: percent per year will double in twelve years something like that.

1609
01:22:21,439 --> 01:22:24,560
Speaker 1: So like so if you so, but you've got this

1610
01:22:24,640 --> 01:22:28,240
Speaker 1: fixed amount of habitat that's not growing, that's actually decreasing probably,

1611
01:22:28,640 --> 01:22:31,360
Speaker 1: I mean, if you're talking about private land stuff habitat,

1612
01:22:31,680 --> 01:22:35,880
Speaker 1: and so you've got this large carnivore that's naturally increasing.

1613
01:22:37,040 --> 01:22:42,000
Speaker 1: We need wildlife management through hunting. That stimulates so many

1614
01:22:42,120 --> 01:22:45,840
Speaker 1: positive things. I mean, it stimulates families getting out and

1615
01:22:45,880 --> 01:22:51,200
Speaker 1: hunting people, gathering wild protein. It uh stimulates the economy,

1616
01:22:51,840 --> 01:22:57,320
Speaker 1: it but it you know, the in these nuisance issues

1617
01:22:57,720 --> 01:23:01,760
Speaker 1: show us places where these cares are essentially I mean

1618
01:23:01,800 --> 01:23:05,240
Speaker 1: not always running out of habitat, but I mean bears dispersing,

1619
01:23:05,360 --> 01:23:09,240
Speaker 1: bears going into places that really they can't. We can't

1620
01:23:09,280 --> 01:23:11,400
Speaker 1: sustain a bear there. I mean there's a little block

1621
01:23:11,400 --> 01:23:14,160
Speaker 1: of wood rut over there. A bear probably can't live

1622
01:23:14,200 --> 01:23:17,599
Speaker 1: there his whole life. And so that's you know, that's

1623
01:23:17,600 --> 01:23:19,400
Speaker 1: why we need to hunt these bears, right, and you

1624
01:23:19,439 --> 01:23:22,080
Speaker 1: think about, you know, the biological carrying capacity of the landscape,

1625
01:23:22,160 --> 01:23:24,080
Speaker 1: right what what can the landscape hold? And then the

1626
01:23:24,160 --> 01:23:27,720
Speaker 1: social caring capacity what can people tolerate? And and so

1627
01:23:28,000 --> 01:23:29,800
Speaker 1: you know, we see this with a lot of different

1628
01:23:29,840 --> 01:23:32,200
Speaker 1: wildlife species. You know, with deer, I mean you can

1629
01:23:32,560 --> 01:23:35,519
Speaker 1: you can have deer increase and increase and increase, but

1630
01:23:35,640 --> 01:23:37,920
Speaker 1: you get to a point where people say, okay, this

1631
01:23:38,080 --> 01:23:40,880
Speaker 1: is this is too much um And so for bear, yeah,

1632
01:23:40,920 --> 01:23:43,920
Speaker 1: the biological carrying capacity of the land is one thing.

1633
01:23:44,000 --> 01:23:45,720
Speaker 1: And here in Missouri, we we've got a lot of

1634
01:23:45,760 --> 01:23:48,760
Speaker 1: bear habitat. We've got you know, our bears right now,

1635
01:23:49,000 --> 01:23:52,479
Speaker 1: from our our research, they're pretty choosy. They select like

1636
01:23:52,600 --> 01:23:55,880
Speaker 1: the highest quality habitat because they can, right they live

1637
01:23:55,960 --> 01:23:58,920
Speaker 1: at low densities right now, so there's not that competition

1638
01:23:59,360 --> 01:24:02,599
Speaker 1: to you know, to to get to that high quality habitat.

1639
01:24:02,640 --> 01:24:05,080
Speaker 1: They that's what they're selecting for. But we can look

1640
01:24:05,160 --> 01:24:08,080
Speaker 1: to other parts of the country and recognize that bears

1641
01:24:08,120 --> 01:24:12,479
Speaker 1: are super adaptable and as they continue to grow, they'll

1642
01:24:12,560 --> 01:24:15,000
Speaker 1: use those more marginal habitats. And you could be talking

1643
01:24:15,080 --> 01:24:19,320
Speaker 1: about fragmented forests where you have bears crossing roads really frequently,

1644
01:24:20,040 --> 01:24:22,720
Speaker 1: or or that type of fragmented forests where it's you know,

1645
01:24:23,120 --> 01:24:26,280
Speaker 1: human development and or agricultural development and things like that,

1646
01:24:26,880 --> 01:24:31,120
Speaker 1: and so that social social carying capacity tends to be

1647
01:24:31,720 --> 01:24:34,920
Speaker 1: lower than what the landscape could support. And it's and

1648
01:24:35,000 --> 01:24:38,800
Speaker 1: it's just because you know, there's that possibility of those

1649
01:24:38,880 --> 01:24:41,840
Speaker 1: nuisance issues or the perception of the animals being in

1650
01:24:41,960 --> 01:24:44,640
Speaker 1: close proximity to homes and things like that, and so,

1651
01:24:45,160 --> 01:24:46,439
Speaker 1: you know, I mean, I think when you you know,

1652
01:24:46,560 --> 01:24:49,560
Speaker 1: talk about hunting and the ability to provide that opportunity,

1653
01:24:49,640 --> 01:24:52,200
Speaker 1: and so you know, we were at this point with

1654
01:24:52,280 --> 01:24:55,799
Speaker 1: our bear population where we can look to um proposing

1655
01:24:55,840 --> 01:24:58,479
Speaker 1: a hunting season, right this is a really exciting time

1656
01:24:58,560 --> 01:25:01,400
Speaker 1: for the state of Missouri where year and we we

1657
01:25:01,520 --> 01:25:04,160
Speaker 1: have a bear population where we can say, yep, we're

1658
01:25:04,280 --> 01:25:06,160
Speaker 1: at this stage now where we can look to that.

1659
01:25:06,280 --> 01:25:10,320
Speaker 1: And so we've established, you know, this proposed hunting season framework,

1660
01:25:10,600 --> 01:25:13,920
Speaker 1: and it's really to provide opportunity our our population can

1661
01:25:14,000 --> 01:25:18,280
Speaker 1: sustain harvest, and so we can provide Missourian's that opportunity

1662
01:25:18,320 --> 01:25:22,400
Speaker 1: to utilize this incredible resource that they haven't had that

1663
01:25:22,479 --> 01:25:32,880
Speaker 1: opportunity before in that's right, So you know, so it's

1664
01:25:32,920 --> 01:25:35,280
Speaker 1: it's like this incredible just you know, we talked about

1665
01:25:35,280 --> 01:25:37,560
Speaker 1: it being this conservation success story and that kind of

1666
01:25:37,720 --> 01:25:39,479
Speaker 1: gets you to that. And then and then for us,

1667
01:25:39,560 --> 01:25:42,599
Speaker 1: we have a bear management plan that really identifies kind

1668
01:25:42,600 --> 01:25:46,400
Speaker 1: of the multifaceted nature of bear management, right, I mean,

1669
01:25:46,640 --> 01:25:48,920
Speaker 1: all the things we've already talked about, we've covered basically

1670
01:25:49,000 --> 01:25:52,559
Speaker 1: everything that you would discuss with our plan. It's education,

1671
01:25:52,800 --> 01:25:55,519
Speaker 1: it's minimizing and addressing those conflicts when they occur. It's

1672
01:25:55,840 --> 01:25:59,519
Speaker 1: the research used to inform those management decisions. Um and

1673
01:25:59,600 --> 01:26:02,200
Speaker 1: then and for us here, as our population continues to grow,

1674
01:26:02,240 --> 01:26:05,280
Speaker 1: we'll look to establish those population benchmarks and hunting will

1675
01:26:05,320 --> 01:26:08,720
Speaker 1: be an essential component of that management program. So I

1676
01:26:08,800 --> 01:26:12,360
Speaker 1: mean it all, what's the general framework for the proposal?

1677
01:26:12,640 --> 01:26:15,519
Speaker 1: So yes, so for our bear hunting season, the proposal

1678
01:26:15,600 --> 01:26:17,280
Speaker 1: that we have so right now, you know, we don't

1679
01:26:17,360 --> 01:26:20,160
Speaker 1: have a season. This is kind of our initial public

1680
01:26:20,280 --> 01:26:24,879
Speaker 1: input phase, so so Department of Conservation. UH. In many cases,

1681
01:26:25,000 --> 01:26:27,760
Speaker 1: especially with these types of big changes, this is you know,

1682
01:26:27,840 --> 01:26:29,639
Speaker 1: this is a big deal, right, this is brand new

1683
01:26:29,760 --> 01:26:33,120
Speaker 1: for us. UH. So we we create this proposed framework,

1684
01:26:33,200 --> 01:26:36,320
Speaker 1: take it out for initial public comment, will make refinements

1685
01:26:36,400 --> 01:26:38,320
Speaker 1: to it, and then and then send it down for

1686
01:26:38,600 --> 01:26:40,640
Speaker 1: kind of that approval chain that it would need to

1687
01:26:40,680 --> 01:26:43,559
Speaker 1: go through. UM. But kind of the gist of it is, UM,

1688
01:26:43,600 --> 01:26:46,360
Speaker 1: we're proposing a ten day season that would start the

1689
01:26:46,439 --> 01:26:50,599
Speaker 1: third Monday in October. UM we are proposing zone specific

1690
01:26:50,680 --> 01:26:53,080
Speaker 1: harvest quotas. So we have kind of proposed three bear

1691
01:26:53,160 --> 01:26:56,560
Speaker 1: management zones UM zone specific harvest quotas, and so the

1692
01:26:56,640 --> 01:27:00,400
Speaker 1: season would close either when the zone specific quota reached

1693
01:27:00,479 --> 01:27:04,400
Speaker 1: or we don't have that established yet, so so the

1694
01:27:04,479 --> 01:27:07,000
Speaker 1: other assume it would be pretty low. So what we're

1695
01:27:07,000 --> 01:27:09,560
Speaker 1: talking about is a limited and highly regulated harvest. So

1696
01:27:09,680 --> 01:27:12,960
Speaker 1: this is this is US you know, basically establishing this

1697
01:27:13,120 --> 01:27:18,200
Speaker 1: hunting season. So thirty bear quote of the first year,

1698
01:27:18,360 --> 01:27:21,599
Speaker 1: the first several years, and they started killing like forty

1699
01:27:21,640 --> 01:27:24,639
Speaker 1: bears on the first day, you know, before they could

1700
01:27:24,640 --> 01:27:26,640
Speaker 1: close the season. But no. Yeah, and one of the

1701
01:27:26,680 --> 01:27:29,640
Speaker 1: things that we're looking at too is allocating permits for

1702
01:27:29,720 --> 01:27:32,280
Speaker 1: those bear management zones. So you know, we we know

1703
01:27:32,760 --> 01:27:35,200
Speaker 1: with bear hunting, success rates tend to be low, right

1704
01:27:35,280 --> 01:27:37,920
Speaker 1: and and I think that in and of itself is

1705
01:27:37,960 --> 01:27:40,840
Speaker 1: an adjustment for folks that have never bear hunted, you know,

1706
01:27:41,040 --> 01:27:45,120
Speaker 1: it is one of those things that's right. You got

1707
01:27:45,240 --> 01:27:48,880
Speaker 1: to understand that that success rates for for for bear

1708
01:27:48,960 --> 01:27:51,880
Speaker 1: hunters are typically low. And you know, right now we're

1709
01:27:51,920 --> 01:27:54,760
Speaker 1: proposing no baiting and no dogs, and so in that case,

1710
01:27:54,840 --> 01:27:57,160
Speaker 1: success rates will be low. We know that, and we

1711
01:27:57,240 --> 01:27:59,519
Speaker 1: can look to other states and and see that you know,

1712
01:27:59,600 --> 01:28:02,320
Speaker 1: in those since as you're talking about, typically a below

1713
01:28:02,400 --> 01:28:05,560
Speaker 1: ten percent success rate in most cases. Um you know,

1714
01:28:05,680 --> 01:28:08,120
Speaker 1: some states have seen kind of some variability around it.

1715
01:28:08,240 --> 01:28:10,559
Speaker 1: But but it's not what you're going to think about

1716
01:28:10,680 --> 01:28:12,920
Speaker 1: for for other species that that folks might be a

1717
01:28:13,000 --> 01:28:16,760
Speaker 1: little bit you know, more common you know, commonplace to them. Um. So,

1718
01:28:17,160 --> 01:28:20,200
Speaker 1: so thinking about that permit allocation by zone UM. Those

1719
01:28:20,280 --> 01:28:23,160
Speaker 1: zones specific harvest quotas, and our zones are set up

1720
01:28:23,200 --> 01:28:26,840
Speaker 1: to kind of delineate regions of the state UM that

1721
01:28:26,920 --> 01:28:30,320
Speaker 1: are kind of separated by major highways. So they kind

1722
01:28:30,320 --> 01:28:33,839
Speaker 1: of take these these bear habitat areas that are already

1723
01:28:34,080 --> 01:28:36,880
Speaker 1: kind of separated by these by these major roadways. UM.

1724
01:28:36,960 --> 01:28:39,840
Speaker 1: And so are our Bear Management Zone that is our

1725
01:28:39,880 --> 01:28:43,599
Speaker 1: southwestern zone, so that would be here where we're at Springfield. UM.

1726
01:28:43,800 --> 01:28:45,800
Speaker 1: That one is an area where it's got a lot

1727
01:28:45,840 --> 01:28:48,640
Speaker 1: of really suitable bear habitat. We've had bear reports and

1728
01:28:48,720 --> 01:28:50,479
Speaker 1: a number of the counties within the zone for the

1729
01:28:50,560 --> 01:28:53,400
Speaker 1: longest time period sores have been established in in Zone

1730
01:28:53,479 --> 01:28:55,560
Speaker 1: one for for a long time UM. And there's some

1731
01:28:55,680 --> 01:28:58,479
Speaker 1: variability within that zone obviously because it's dependent on that

1732
01:28:58,640 --> 01:29:02,080
Speaker 1: forest cover. UM zone too kind of encompasses the largest

1733
01:29:02,120 --> 01:29:04,400
Speaker 1: tracts of Mark Twain National Forest and some of our

1734
01:29:04,720 --> 01:29:10,240
Speaker 1: our larger less fragmented habitat blocks and the current river

1735
01:29:10,840 --> 01:29:13,639
Speaker 1: over there that's right, yep, yep. And then Zone three

1736
01:29:14,160 --> 01:29:16,000
Speaker 1: is an area that kind of surrounds Lake of the

1737
01:29:16,040 --> 01:29:18,160
Speaker 1: Ozarks and Truman Reservoir. And so when you think about

1738
01:29:18,200 --> 01:29:20,320
Speaker 1: that zone, you know that area there's a lot of

1739
01:29:20,360 --> 01:29:23,400
Speaker 1: suitable bear habitat there. Um, but bear numbers are low,

1740
01:29:23,439 --> 01:29:25,720
Speaker 1: and so we know that areas an expansion area. We

1741
01:29:25,920 --> 01:29:28,360
Speaker 1: we have sous in the area, we have you know,

1742
01:29:28,439 --> 01:29:31,240
Speaker 1: we get bear reports regularly. Um, you know, but in

1743
01:29:31,560 --> 01:29:34,559
Speaker 1: in those look in that in that zone. Um, there,

1744
01:29:34,640 --> 01:29:38,040
Speaker 1: it's just a lower density of bears just by default

1745
01:29:38,120 --> 01:29:41,000
Speaker 1: that that's kind of that expansion zone. So kind of

1746
01:29:41,120 --> 01:29:44,439
Speaker 1: dividing it up that way. Um, when would the proposed

1747
01:29:44,479 --> 01:29:47,880
Speaker 1: season be So if it moves through in terms of

1748
01:29:48,000 --> 01:29:51,479
Speaker 1: the MDC process, Um, the earliest we could have it

1749
01:29:51,520 --> 01:29:56,240
Speaker 1: would be October and potentially next year. That's right, yep, man,

1750
01:29:56,360 --> 01:30:04,320
Speaker 1: that's exciting, that's very exciting. Um. The uh, yeah, the

1751
01:30:04,800 --> 01:30:09,599
Speaker 1: in Arkansas, the way all this went down was for years,

1752
01:30:10,280 --> 01:30:12,400
Speaker 1: the you know, we managed we had a we had

1753
01:30:12,400 --> 01:30:14,920
Speaker 1: a season since nineteen eighty. I'm not telling you something

1754
01:30:14,920 --> 01:30:18,160
Speaker 1: you don't know. I'm just kind of giving a context.

1755
01:30:18,760 --> 01:30:21,000
Speaker 1: We had a season from nineteen eighty and then in

1756
01:30:21,080 --> 01:30:24,240
Speaker 1: two thousand one they opened up baiting on private land

1757
01:30:24,280 --> 01:30:29,120
Speaker 1: because the bear population began to expand beyond what uh

1758
01:30:29,640 --> 01:30:32,640
Speaker 1: the still hunters will call them could harvest. So that

1759
01:30:32,760 --> 01:30:34,559
Speaker 1: you know, we need to we need to take out

1760
01:30:34,560 --> 01:30:36,880
Speaker 1: more bear. So you know, they said, well, we're gonna

1761
01:30:37,080 --> 01:30:39,719
Speaker 1: we're gonna allow bait on private land in certain areas.

1762
01:30:39,880 --> 01:30:43,040
Speaker 1: But what we're seeing now is guy's going back to

1763
01:30:44,040 --> 01:30:50,120
Speaker 1: this uh harder way. Yeah. Yeah, I'm giving him if

1764
01:30:50,200 --> 01:30:56,639
Speaker 1: he knows that phrase to wash our hands not Yeah yeah,

1765
01:30:56,800 --> 01:31:00,240
Speaker 1: if we coined this deep deep metaphor of sheep hunt

1766
01:31:00,240 --> 01:31:02,880
Speaker 1: of the south. Uh. But yeah, it's a super tough hunt.

1767
01:31:02,960 --> 01:31:05,880
Speaker 1: But so I'm so excited to see how people do.

1768
01:31:06,400 --> 01:31:10,800
Speaker 1: And I think in an unhunted population it will be easier. Josh,

1769
01:31:10,960 --> 01:31:13,800
Speaker 1: So this is your year, man, I'm hoping, yeah, this

1770
01:31:13,920 --> 01:31:16,240
Speaker 1: is there. Next year, I shoot a recurse something too.

1771
01:31:16,320 --> 01:31:17,640
Speaker 1: I don't know if I'm gonna go with. You know,

1772
01:31:17,840 --> 01:31:26,720
Speaker 1: I'm not taking as well. No, Um, no, such great information. Um.

1773
01:31:27,720 --> 01:31:31,800
Speaker 1: Is there anything we've We've bounced around a lot, talked

1774
01:31:31,800 --> 01:31:34,759
Speaker 1: about research, talked about the season framework. Is there anything

1775
01:31:34,840 --> 01:31:36,760
Speaker 1: else you'd like to I do want to hear you

1776
01:31:36,800 --> 01:31:40,800
Speaker 1: talk about home ranges, like, because that's always fascinating to me.

1777
01:31:41,479 --> 01:31:43,240
Speaker 1: Uh So let me back up. Let me talk to

1778
01:31:43,280 --> 01:31:44,960
Speaker 1: you about home ranges, and then I'll say you can

1779
01:31:45,000 --> 01:31:47,639
Speaker 1: say whatever you want. You two, Josh, you two, Josh,

1780
01:31:49,920 --> 01:31:53,599
Speaker 1: what's the first okay, too simple questions, what's the furthest

1781
01:31:53,720 --> 01:31:56,240
Speaker 1: you've seen a bear go like a GPS collared fair

1782
01:31:56,320 --> 01:31:59,360
Speaker 1: and all your research go. And then the question is

1783
01:31:59,600 --> 01:32:06,080
Speaker 1: what an average for a sal home range? So so

1784
01:32:06,320 --> 01:32:10,719
Speaker 1: we have we are really lucky in that we've picked

1785
01:32:10,800 --> 01:32:14,519
Speaker 1: up a few really cool dispersal movements with our collar data.

1786
01:32:14,600 --> 01:32:17,679
Speaker 1: So you know, I mean males you think of mails

1787
01:32:17,840 --> 01:32:22,040
Speaker 1: move huge distances, right, so so they move really large distances. Um,

1788
01:32:22,200 --> 01:32:26,160
Speaker 1: we have one that was initially trapped kind of in

1789
01:32:26,240 --> 01:32:28,280
Speaker 1: the Springfield. It was not far from here, It wasn't

1790
01:32:28,320 --> 01:32:31,040
Speaker 1: in Springfield. It was just a little bit northeast of here,

1791
01:32:31,160 --> 01:32:33,960
Speaker 1: but um, kind of in this area. And um, that

1792
01:32:34,080 --> 01:32:37,439
Speaker 1: bear he ended up in Warren County, Missouri, which is

1793
01:32:37,680 --> 01:32:47,880
Speaker 1: north of Interstate seventy, north of the Missouri River. Basically, yeah,

1794
01:32:47,960 --> 01:32:50,479
Speaker 1: and so and and it wasn't just a long linear

1795
01:32:50,560 --> 01:32:53,760
Speaker 1: movement he he basically he kind of wandered around. And

1796
01:32:53,920 --> 01:32:56,400
Speaker 1: so we we put a new collar on him up

1797
01:32:56,479 --> 01:33:00,200
Speaker 1: there and kind of tracked his moses back up there. Yep,

1798
01:33:00,240 --> 01:33:02,120
Speaker 1: he didn't bring him back down here, no, because we

1799
01:33:02,200 --> 01:33:04,280
Speaker 1: don't relocate him. And and and that instant, you know,

1800
01:33:04,439 --> 01:33:07,280
Speaker 1: he's that he's that dispersing bear, and so his thing,

1801
01:33:07,400 --> 01:33:09,479
Speaker 1: he's just gonna keep moving, right, and you know, there's

1802
01:33:09,479 --> 01:33:11,880
Speaker 1: nowhere that we could put him where he's not gonna move. So,

1803
01:33:12,640 --> 01:33:15,840
Speaker 1: so so he went about his business. Um, we had

1804
01:33:15,920 --> 01:33:18,360
Speaker 1: locations of him almost all the way to Cape Girardos,

1805
01:33:18,360 --> 01:33:21,320
Speaker 1: So now you're talking almost to the Mississippi River. That

1806
01:33:21,520 --> 01:33:23,080
Speaker 1: he went. He kind of stopped at the edge of

1807
01:33:23,120 --> 01:33:26,720
Speaker 1: the forest at habitat there, turned around. We recaptured him

1808
01:33:27,000 --> 01:33:31,400
Speaker 1: um down in the birch Tree area, So Shannon County,

1809
01:33:31,479 --> 01:33:34,360
Speaker 1: not too far from current river. Youre in that that location,

1810
01:33:34,560 --> 01:33:37,599
Speaker 1: that's a good place for him, yeah, yeah. And then

1811
01:33:37,680 --> 01:33:39,559
Speaker 1: and then he denned a little bit north of there.

1812
01:33:39,560 --> 01:33:41,120
Speaker 1: So I mean when we look at his movements there,

1813
01:33:41,160 --> 01:33:44,320
Speaker 1: this just this this crazy hundreds of miles. Oh yeah,

1814
01:33:44,320 --> 01:33:47,040
Speaker 1: I mean I I basically just did like a quick

1815
01:33:47,080 --> 01:33:49,720
Speaker 1: measure on Google Maps that if if this is from

1816
01:33:49,760 --> 01:33:51,640
Speaker 1: point A to point B two C two D, this

1817
01:33:51,840 --> 01:33:53,840
Speaker 1: it was like four fifty miles and you know there's

1818
01:33:53,880 --> 01:33:56,960
Speaker 1: more in between, right, because it's not just I wonder

1819
01:33:57,080 --> 01:34:03,080
Speaker 1: how many Missouri citizens bearing called and so so interestingly,

1820
01:34:03,160 --> 01:34:04,960
Speaker 1: we can look at our sighting reports. So when he

1821
01:34:05,080 --> 01:34:06,840
Speaker 1: was in that Warren County area. If you if you

1822
01:34:06,920 --> 01:34:10,000
Speaker 1: look on our sightings map um, I think it's like

1823
01:34:10,160 --> 01:34:12,920
Speaker 1: yellow dots right now that we're two thousand eleven, and

1824
01:34:13,960 --> 01:34:16,479
Speaker 1: oh my gosh, yeah, there are these all these reports

1825
01:34:16,520 --> 01:34:18,960
Speaker 1: of this, you know, of one individual bear and stuff.

1826
01:34:19,000 --> 01:34:21,280
Speaker 1: So so they do, I mean, they move these huge distances.

1827
01:34:21,439 --> 01:34:24,880
Speaker 1: But you know, the thought with females is that females

1828
01:34:24,960 --> 01:34:28,200
Speaker 1: don't disperse very far, right, they stick around their mother

1829
01:34:28,320 --> 01:34:30,479
Speaker 1: and that's kind of their typical dispersal pattern. And so

1830
01:34:30,720 --> 01:34:32,960
Speaker 1: basically what they do is, you know, it's it's very

1831
01:34:33,000 --> 01:34:35,400
Speaker 1: similar to dear. It's that rose pedal hypothesis. So you

1832
01:34:35,479 --> 01:34:37,840
Speaker 1: have a sou if she has a female cub, that

1833
01:34:37,960 --> 01:34:40,720
Speaker 1: female cubs sets up a home range that overlaps some

1834
01:34:41,320 --> 01:34:43,920
Speaker 1: with the mothers, and then her female cubs will do

1835
01:34:44,040 --> 01:34:46,360
Speaker 1: the same thing. And so the female component of a

1836
01:34:46,400 --> 01:34:51,280
Speaker 1: population is a lot slower to expand than the male component,

1837
01:34:51,479 --> 01:34:54,040
Speaker 1: which is why we see males south of St. Louis,

1838
01:34:54,080 --> 01:34:56,360
Speaker 1: why we see more males around the Lake of the Ozarks.

1839
01:34:56,640 --> 01:34:59,479
Speaker 1: It's just because that male subset, you know, is the

1840
01:34:59,520 --> 01:35:03,080
Speaker 1: one that spans a lot quicker um. But we've had

1841
01:35:03,160 --> 01:35:06,080
Speaker 1: a couple of long range female dispersals. So we had

1842
01:35:06,240 --> 01:35:09,320
Speaker 1: one where we were able to see this this female,

1843
01:35:09,400 --> 01:35:11,960
Speaker 1: she's collared UM and and she was kind of I

1844
01:35:12,000 --> 01:35:14,680
Speaker 1: think she was four when we had her collard and

1845
01:35:14,880 --> 01:35:19,320
Speaker 1: she moved basically it was like eight miles something like that,

1846
01:35:19,600 --> 01:35:22,040
Speaker 1: and and and then kind of hung around the Houston,

1847
01:35:22,120 --> 01:35:25,680
Speaker 1: Missouri area, um, and then even went further east from there.

1848
01:35:25,760 --> 01:35:27,439
Speaker 1: So she was another one of these bears from the

1849
01:35:27,520 --> 01:35:30,360
Speaker 1: southwestern region and kind of went went that direction. That's

1850
01:35:30,439 --> 01:35:34,960
Speaker 1: probably a phenomena too, of an expanding population, absolutely, because

1851
01:35:35,040 --> 01:35:38,400
Speaker 1: if she had went five miles and bumped into some

1852
01:35:38,640 --> 01:35:42,000
Speaker 1: kind of bear conflict, it might have turned or I mean,

1853
01:35:42,040 --> 01:35:44,720
Speaker 1: these bears are just like heading north and nothing to

1854
01:35:44,760 --> 01:35:48,519
Speaker 1: stop him, nothing in terms of bear bear stuff, right,

1855
01:35:49,560 --> 01:35:52,280
Speaker 1: exactly right, exactly other bears, right, yeah, But but that's it,

1856
01:35:52,360 --> 01:35:55,560
Speaker 1: I mean. And so so those types of female dispersals,

1857
01:35:55,640 --> 01:35:57,640
Speaker 1: but like those are the little sparks, right that are

1858
01:35:57,680 --> 01:36:01,560
Speaker 1: gonna ignite kind of those local breedinging populations there. So

1859
01:36:02,120 --> 01:36:05,000
Speaker 1: so if we have these longer female dispersals, we may

1860
01:36:05,080 --> 01:36:07,400
Speaker 1: get females that show up in some of these areas

1861
01:36:07,479 --> 01:36:10,000
Speaker 1: where if it was just that kind of typical that

1862
01:36:10,080 --> 01:36:12,960
Speaker 1: you would think of population expansion, uh that you know,

1863
01:36:13,000 --> 01:36:15,559
Speaker 1: you wouldn't see for for a little bit longer, um

1864
01:36:15,680 --> 01:36:17,160
Speaker 1: and so and so we we kind of see it.

1865
01:36:17,240 --> 01:36:19,559
Speaker 1: So for all the cubs that we handle, we pit

1866
01:36:19,680 --> 01:36:23,880
Speaker 1: tag them so little microchips like you do. Exactly. Yeah,

1867
01:36:23,960 --> 01:36:26,240
Speaker 1: And we just caught one that we had handled in

1868
01:36:27,320 --> 01:36:30,760
Speaker 1: as a cub. We just trapped her fifty miles away. Yeah,

1869
01:36:30,840 --> 01:36:34,280
Speaker 1: totally different area than female. Yeah, So so it does happen.

1870
01:36:34,400 --> 01:36:37,599
Speaker 1: And so we're seeing that kind of expansion of ranges.

1871
01:36:38,800 --> 01:36:40,639
Speaker 1: I guess we'd have to get into definition home range.

1872
01:36:40,720 --> 01:36:43,720
Speaker 1: But what would be just like a general statement for

1873
01:36:44,160 --> 01:36:48,200
Speaker 1: ozark bears like square mile and I and I realized

1874
01:36:48,360 --> 01:36:50,479
Speaker 1: we can't really talk about home ranges and square miles,

1875
01:36:50,880 --> 01:36:54,719
Speaker 1: but do it? Yeah, so we say, like square miles

1876
01:36:54,840 --> 01:36:57,000
Speaker 1: is what you think of as a typical female size

1877
01:36:57,080 --> 01:37:00,960
Speaker 1: average home range and then recognizing there's that variability, right,

1878
01:37:01,080 --> 01:37:06,639
Speaker 1: so exactly, Yeah, it could be oblong along the whole

1879
01:37:06,760 --> 01:37:09,000
Speaker 1: ridge that and that's that bears that bears home range

1880
01:37:09,040 --> 01:37:11,679
Speaker 1: for sure, and so uh so, yeah, so about twenty

1881
01:37:11,880 --> 01:37:15,880
Speaker 1: square miles for the females, um and in some areas, Yeah,

1882
01:37:16,000 --> 01:37:17,840
Speaker 1: but it can be a lot smaller, right, So, so

1883
01:37:17,960 --> 01:37:19,960
Speaker 1: they can get down even lower than that. I mean

1884
01:37:20,040 --> 01:37:21,680
Speaker 1: when I when I worked on the East Coast, we

1885
01:37:21,800 --> 01:37:24,240
Speaker 1: had bears that had much smaller home ranges and mean

1886
01:37:24,280 --> 01:37:27,320
Speaker 1: and they were denser population. And a lot of those

1887
01:37:27,360 --> 01:37:29,599
Speaker 1: bears with really tight home ranges. A lot of it's

1888
01:37:29,600 --> 01:37:32,280
Speaker 1: based on food. So they're gonna go where they can

1889
01:37:32,320 --> 01:37:34,840
Speaker 1: find food. So if they're in an area with lots

1890
01:37:34,920 --> 01:37:37,320
Speaker 1: of you know, human associated foods, they don't have to

1891
01:37:37,360 --> 01:37:40,080
Speaker 1: go as far to meet their energetic needs and stuff

1892
01:37:40,080 --> 01:37:42,200
Speaker 1: like that. If you're talking about big tracks of forest,

1893
01:37:42,560 --> 01:37:45,080
Speaker 1: sometimes they do need to travel a little bit longer

1894
01:37:45,160 --> 01:37:47,760
Speaker 1: distances to get to you know, the good patches of

1895
01:37:47,800 --> 01:37:50,800
Speaker 1: acorns and stuff like that, with the bear patches and everything. Um,

1896
01:37:50,920 --> 01:37:53,479
Speaker 1: So we we do see some variability around that. And

1897
01:37:53,520 --> 01:37:56,000
Speaker 1: then and we did have a young female that was

1898
01:37:56,200 --> 01:37:59,200
Speaker 1: collared around the Lake of the Ozarks area, and her

1899
01:37:59,240 --> 01:38:00,880
Speaker 1: home range was a lot bigger, you know, it was

1900
01:38:01,160 --> 01:38:02,840
Speaker 1: you'd look at it on a map and it would

1901
01:38:02,880 --> 01:38:04,479
Speaker 1: look like what you would think of as a males

1902
01:38:04,520 --> 01:38:06,679
Speaker 1: home range. And it's just she was in an area where,

1903
01:38:07,240 --> 01:38:09,080
Speaker 1: like you said, probably not a lot of bears, not

1904
01:38:09,200 --> 01:38:11,240
Speaker 1: as not as many bears, and so she really wasn't

1905
01:38:11,280 --> 01:38:13,679
Speaker 1: restricted in her movements and things like that about males.

1906
01:38:14,320 --> 01:38:17,640
Speaker 1: So males at varies, Yeah, males varies from year, you know,

1907
01:38:17,920 --> 01:38:20,400
Speaker 1: during the time of year. But at the biggest you're

1908
01:38:20,400 --> 01:38:23,320
Speaker 1: talking about a hundred square miles, so just like huge,

1909
01:38:23,760 --> 01:38:28,519
Speaker 1: huge areas. Yeah yeah yeah. So so males during the

1910
01:38:28,560 --> 01:38:32,080
Speaker 1: breeding season, I mean they'll move really big distances. Yeah.

1911
01:38:32,120 --> 01:38:34,160
Speaker 1: I wonder how different that would be. I mean it's

1912
01:38:34,200 --> 01:38:37,880
Speaker 1: been years. Like the research that is in my file

1913
01:38:37,960 --> 01:38:41,839
Speaker 1: cabinet in my head is from the early nine in Arkansas,

1914
01:38:42,640 --> 01:38:45,800
Speaker 1: UM and just from what I've heard biologists kind of

1915
01:38:45,880 --> 01:38:48,040
Speaker 1: just say off the cuff. So, I mean, this isn't

1916
01:38:48,080 --> 01:38:51,920
Speaker 1: like hard science, but like I was, I was thinking that,

1917
01:38:52,120 --> 01:38:55,479
Speaker 1: you know, like a bear, male bear in Arkansas to

1918
01:38:55,560 --> 01:38:57,599
Speaker 1: have like a twenty square mile home range, and it's

1919
01:38:57,640 --> 01:39:00,880
Speaker 1: totally possible. And so with Dancer pop, Yeah, you see

1920
01:39:00,920 --> 01:39:02,880
Speaker 1: you see variability and and a lot of it is

1921
01:39:02,920 --> 01:39:05,719
Speaker 1: food dependent. So if there's very ability in the habitat

1922
01:39:05,800 --> 01:39:08,080
Speaker 1: and there's you know, different types of food resources and

1923
01:39:08,200 --> 01:39:11,160
Speaker 1: things like that, you'll definitely see that variability. And males

1924
01:39:11,200 --> 01:39:13,400
Speaker 1: shrink their home ranges down a lot when it's not

1925
01:39:13,520 --> 01:39:16,080
Speaker 1: the breeding season. You know, we like to describe it

1926
01:39:16,200 --> 01:39:19,120
Speaker 1: for folks, especially this time of year. This is the

1927
01:39:19,280 --> 01:39:22,120
Speaker 1: biggest they could cover because it helps explain why they

1928
01:39:22,200 --> 01:39:24,320
Speaker 1: might see them where they're seeing them. And then and

1929
01:39:24,560 --> 01:39:27,439
Speaker 1: then why you know, if you see a bear here

1930
01:39:27,960 --> 01:39:31,200
Speaker 1: and then we get a report way the heck over here,

1931
01:39:31,240 --> 01:39:33,080
Speaker 1: it could be the same bear because they can move

1932
01:39:33,160 --> 01:39:35,559
Speaker 1: such big distances. And so yeah, I mean we've been

1933
01:39:35,600 --> 01:39:37,400
Speaker 1: we've been really lucky and kind of catching some of

1934
01:39:37,439 --> 01:39:40,000
Speaker 1: those more unique dispersal movements and stuff like that to

1935
01:39:40,080 --> 01:39:43,720
Speaker 1: see that. So that's that's the longest bear dispersal that

1936
01:39:43,880 --> 01:39:47,639
Speaker 1: I've heard of. Just described. He was like a meander,

1937
01:39:48,040 --> 01:39:50,320
Speaker 1: you know, just just he wandered. Basically, he was just

1938
01:39:50,400 --> 01:39:53,280
Speaker 1: a wandering bear. And and and he he ended up

1939
01:39:53,320 --> 01:39:55,560
Speaker 1: dropping his collar before we got to where he was

1940
01:39:55,600 --> 01:39:58,760
Speaker 1: like in an established home range. Now we don't know

1941
01:39:58,760 --> 01:40:01,280
Speaker 1: where he's at now, but but from Josh probably does.

1942
01:40:03,320 --> 01:40:05,240
Speaker 1: But from the later years, it did seem like he

1943
01:40:05,320 --> 01:40:07,400
Speaker 1: was kind of settling down right, So we started kind

1944
01:40:07,400 --> 01:40:10,280
Speaker 1: of to pick him up between and and he may

1945
01:40:10,400 --> 01:40:12,479
Speaker 1: end up being this was several years ago, we're still

1946
01:40:12,520 --> 01:40:15,040
Speaker 1: trapping in this area. He's probably got your text still,

1947
01:40:15,080 --> 01:40:17,599
Speaker 1: and and we manned up. Yeah, we may end up

1948
01:40:17,600 --> 01:40:19,400
Speaker 1: getting him as you know, one of those three pound

1949
01:40:19,439 --> 01:40:21,880
Speaker 1: breeding age males now because he's kind of reached that

1950
01:40:21,960 --> 01:40:28,519
Speaker 1: age class. So yeah, Jeff Ford in Oklahoma talks about

1951
01:40:28,560 --> 01:40:32,120
Speaker 1: a bear that was going seventy miles in between its

1952
01:40:32,160 --> 01:40:35,439
Speaker 1: summer and fall ranges in Oklahoma, and it's same story.

1953
01:40:35,479 --> 01:40:38,680
Speaker 1: It lost its collar and uh, the last time they

1954
01:40:38,760 --> 01:40:42,879
Speaker 1: had GPS on it, it was like ten miles into Arkansas.

1955
01:40:43,080 --> 01:40:46,800
Speaker 1: The other way it was going into like this like

1956
01:40:47,160 --> 01:40:51,840
Speaker 1: fringy agricultural area in Oklahoma, coming out of kind of

1957
01:40:51,920 --> 01:40:55,080
Speaker 1: this big national forest like core bear area, and it

1958
01:40:55,240 --> 01:40:59,200
Speaker 1: was going seventy miles. I can't remember that. It was

1959
01:40:59,240 --> 01:41:01,240
Speaker 1: probably doing that the summer and coming back to den

1960
01:41:01,320 --> 01:41:03,600
Speaker 1: in the mountains, but may have been different, but just

1961
01:41:04,120 --> 01:41:06,760
Speaker 1: bizarre stuff. It's yeah, it's incredible, I mean, and I

1962
01:41:06,800 --> 01:41:08,840
Speaker 1: mean and you you know, like when when you collar

1963
01:41:08,960 --> 01:41:12,400
Speaker 1: these animals, you kind of get this insight into stuff

1964
01:41:12,439 --> 01:41:15,320
Speaker 1: that you really wouldn't have noticed otherwise. And and then

1965
01:41:15,439 --> 01:41:19,000
Speaker 1: and the collar technology right now, you know, when we

1966
01:41:19,080 --> 01:41:22,120
Speaker 1: think about you know, historical studies and things like that,

1967
01:41:22,200 --> 01:41:25,439
Speaker 1: when you're just using VHF collars, all that collar does

1968
01:41:25,560 --> 01:41:28,320
Speaker 1: is put out a beep and it's dependent on you

1969
01:41:28,560 --> 01:41:32,320
Speaker 1: finding it and triangulating its location and so so realistic.

1970
01:41:32,320 --> 01:41:34,200
Speaker 1: You know, how many times can you find it each day?

1971
01:41:34,479 --> 01:41:37,240
Speaker 1: How many consecutive days can you find it for? How long?

1972
01:41:37,400 --> 01:41:39,800
Speaker 1: And especially you know, when you think about bears and

1973
01:41:39,800 --> 01:41:42,200
Speaker 1: the huge ranges they cover and then the topography that

1974
01:41:42,240 --> 01:41:44,439
Speaker 1: they're in, there's so many challenges there, right, It's it's

1975
01:41:44,520 --> 01:41:47,160
Speaker 1: hard to do that. The collars now, I mean they're

1976
01:41:47,200 --> 01:41:51,200
Speaker 1: like a handheld GPS unit that is basically logging locations,

1977
01:41:51,280 --> 01:41:54,160
Speaker 1: and so our GPS collars, most of them take locations

1978
01:41:54,200 --> 01:41:55,880
Speaker 1: every two and a half hours. We have something are

1979
01:41:55,920 --> 01:41:59,200
Speaker 1: doing it every yeah, yeah, I mean, and and really

1980
01:41:59,280 --> 01:42:01,480
Speaker 1: thick cover. Some times they don't connect with the satellite

1981
01:42:01,479 --> 01:42:03,160
Speaker 1: and so you know you can't see see some of

1982
01:42:03,240 --> 01:42:06,879
Speaker 1: those things, but you get this incredible just detailed habitat

1983
01:42:07,000 --> 01:42:09,040
Speaker 1: use and and there's times where you know, you may

1984
01:42:09,120 --> 01:42:11,800
Speaker 1: have a bear that oh we usually see her over here,

1985
01:42:11,840 --> 01:42:13,600
Speaker 1: but she's been gone for like a month, and so

1986
01:42:13,720 --> 01:42:16,840
Speaker 1: the question is did she drop her collar and we're

1987
01:42:16,880 --> 01:42:19,400
Speaker 1: just not, you know, not picking it up. Did she

1988
01:42:19,520 --> 01:42:22,200
Speaker 1: die or did she disperse or you know, she had

1989
01:42:22,240 --> 01:42:24,160
Speaker 1: a walk about. And so we've had some bears that

1990
01:42:24,200 --> 01:42:26,960
Speaker 1: are down near the Arkansas border that make these huge

1991
01:42:27,000 --> 01:42:29,920
Speaker 1: forays down into Arkansas. And she's gone for the better

1992
01:42:29,960 --> 01:42:31,200
Speaker 1: part of a couple of weeks and then and then

1993
01:42:31,280 --> 01:42:34,000
Speaker 1: comes back up and is right back to their core range.

1994
01:42:34,040 --> 01:42:36,080
Speaker 1: And you know, we've seen that with with other bears,

1995
01:42:36,120 --> 01:42:37,680
Speaker 1: and so you know, I mean, and it kind of

1996
01:42:37,760 --> 01:42:40,600
Speaker 1: shows you just that connectivity of the population. Right, Like

1997
01:42:40,640 --> 01:42:43,680
Speaker 1: you said, bears don't know political boundaries here. So you know,

1998
01:42:43,960 --> 01:42:47,040
Speaker 1: we talk about five hundred forty bears here in Missouri,

1999
01:42:47,160 --> 01:42:52,920
Speaker 1: but they're part of this larger population. Their ranges are

2000
01:42:53,000 --> 01:42:59,599
Speaker 1: overlapping and the most absolutely wow, that incredible. Um. Okay,

2001
01:42:59,680 --> 01:43:04,720
Speaker 1: So back to the ending questions, Yeah, do you have it?

2002
01:43:04,800 --> 01:43:07,519
Speaker 1: We'll start with Josh, do we do? Is there anything

2003
01:43:07,600 --> 01:43:09,600
Speaker 1: we haven't covered that people need to know that you

2004
01:43:09,680 --> 01:43:12,840
Speaker 1: guys would like to say to people? M hmm, well,

2005
01:43:12,960 --> 01:43:14,960
Speaker 1: I mean, just anything fun you want to say, Josh,

2006
01:43:15,479 --> 01:43:19,040
Speaker 1: I'll talk all day, man, a couple of things, and

2007
01:43:19,040 --> 01:43:20,679
Speaker 1: we're probably gonna be kind of preaching to the choir

2008
01:43:21,000 --> 01:43:23,040
Speaker 1: in this outfit. But you know, a big thing that

2009
01:43:23,120 --> 01:43:26,479
Speaker 1: I like to stress to people is that when I

2010
01:43:26,520 --> 01:43:29,479
Speaker 1: get calls from the public, it's usually people think bears

2011
01:43:29,560 --> 01:43:31,599
Speaker 1: are Winnie the Pooh or they think it's the grizzly

2012
01:43:31,600 --> 01:43:35,120
Speaker 1: Bear from the revenue. There's no it rips off children's

2013
01:43:35,160 --> 01:43:37,800
Speaker 1: faces or or it's a it's a love toy, you know.

2014
01:43:38,720 --> 01:43:40,880
Speaker 1: So bears are neither one of those, you know bears.

2015
01:43:40,920 --> 01:43:42,840
Speaker 1: But bears aren't fuzzy people either. They don't want to

2016
01:43:42,880 --> 01:43:45,439
Speaker 1: be your friend. That they have a different life than

2017
01:43:45,479 --> 01:43:47,240
Speaker 1: a human does. I realized they take care of their

2018
01:43:47,280 --> 01:43:49,320
Speaker 1: young just like dear dude, just like turkey do. And

2019
01:43:49,360 --> 01:43:52,400
Speaker 1: it's just really important for people to understand that bears

2020
01:43:52,520 --> 01:43:55,920
Speaker 1: need respect, not necessarily fear. You know, they are a

2021
01:43:56,000 --> 01:43:58,719
Speaker 1: valuable resource. It's it's a good time to be alive.

2022
01:43:58,800 --> 01:44:00,880
Speaker 1: It's a great time from Misser eight to have bears.

2023
01:44:00,960 --> 01:44:03,360
Speaker 1: You know, we just open an Elk season now we've

2024
01:44:03,400 --> 01:44:05,760
Speaker 1: got black bears, and Laura talked a little bit about

2025
01:44:05,760 --> 01:44:08,360
Speaker 1: intrinsic value. For me, it's neat to know that. Yeah,

2026
01:44:08,400 --> 01:44:10,040
Speaker 1: I mean, I can tell you the place that we're

2027
01:44:10,040 --> 01:44:12,200
Speaker 1: sitting right now, I've had bears ten minutes. That way,

2028
01:44:12,479 --> 01:44:13,800
Speaker 1: if a bear walk through this park a lot, I

2029
01:44:13,840 --> 01:44:16,760
Speaker 1: wouldn't be surprised. And so it's cool from a guy

2030
01:44:16,920 --> 01:44:19,920
Speaker 1: that's that's a Missourian that grew up and they actually

2031
01:44:19,960 --> 01:44:21,960
Speaker 1: grow cotton where I'm from, but you know, just a

2032
01:44:22,000 --> 01:44:24,760
Speaker 1: few hours away, it's like we have wilderness, which we

2033
01:44:24,800 --> 01:44:26,479
Speaker 1: do have some wilderness areas here, but you know, we've

2034
01:44:26,479 --> 01:44:28,200
Speaker 1: got black bears and we've got an elk hunt. And

2035
01:44:28,280 --> 01:44:29,920
Speaker 1: it's like, man, that's impressive. It's like, I don't I

2036
01:44:29,960 --> 01:44:32,640
Speaker 1: don't have to drive to Montana or Wyoming anymore. It's like,

2037
01:44:32,720 --> 01:44:34,560
Speaker 1: it's just as wooly here as it is there, and

2038
01:44:35,200 --> 01:44:37,519
Speaker 1: you can literally drive twenty minutes from your house where

2039
01:44:37,520 --> 01:44:38,800
Speaker 1: I live and be right in the middle of it.

2040
01:44:39,040 --> 01:44:41,360
Speaker 1: I just think that's a it's something people need to appreciate,

2041
01:44:41,479 --> 01:44:43,320
Speaker 1: and it's it's it's a good time. It's a good thing.

2042
01:44:43,520 --> 01:44:45,600
Speaker 1: And I think to add to that too. You know,

2043
01:44:45,640 --> 01:44:48,080
Speaker 1: when you think about that, it just it highlights again,

2044
01:44:48,120 --> 01:44:50,160
Speaker 1: you know, those conservation success stories. And one of the

2045
01:44:50,160 --> 01:44:52,360
Speaker 1: things when you think about, you know, you talk about MDC,

2046
01:44:52,520 --> 01:44:54,960
Speaker 1: you know, the Department Conservation here being a national leader,

2047
01:44:55,080 --> 01:44:58,080
Speaker 1: and that is only because we have the support of

2048
01:44:58,439 --> 01:45:00,240
Speaker 1: individuals in this state. You know, we have of the

2049
01:45:00,280 --> 01:45:05,240
Speaker 1: support of Missouri residents and the people exactly exactly, and

2050
01:45:05,360 --> 01:45:08,720
Speaker 1: so so in looking at you know, how you have, um,

2051
01:45:09,000 --> 01:45:13,640
Speaker 1: kind of this strong conservation foundation here. It's it's in

2052
01:45:13,760 --> 01:45:17,400
Speaker 1: the values of individual Missourians that they value conservation. And

2053
01:45:17,560 --> 01:45:19,640
Speaker 1: so you know, when we think about kind of the

2054
01:45:19,720 --> 01:45:24,800
Speaker 1: resurgence in the bear population and um, the habitat improvements

2055
01:45:24,840 --> 01:45:27,040
Speaker 1: that have been made. So I mean, you're talking a

2056
01:45:27,160 --> 01:45:31,639
Speaker 1: hundred years ago, the Ozark Forest looked substantially different, right,

2057
01:45:31,800 --> 01:45:34,120
Speaker 1: you know. So, I mean so just in that time period,

2058
01:45:34,240 --> 01:45:36,600
Speaker 1: there's been you know, so many substantial changes in just

2059
01:45:36,680 --> 01:45:39,280
Speaker 1: the level of support that Missouri residents give to the

2060
01:45:39,360 --> 01:45:42,519
Speaker 1: Department of Conservation. You know, all of those It is

2061
01:45:42,600 --> 01:45:45,320
Speaker 1: it's an exciting time. You know, it's an exciting time

2062
01:45:45,400 --> 01:45:47,840
Speaker 1: for me as the bare Bile just in the state

2063
01:45:47,920 --> 01:45:51,280
Speaker 1: to be part of this incredible program, in this incredible organization,

2064
01:45:51,680 --> 01:45:55,880
Speaker 1: but to also just recognize, you know, the the long

2065
01:45:56,240 --> 01:45:59,200
Speaker 1: and you know, very important history that the Department of

2066
01:45:59,240 --> 01:46:01,960
Speaker 1: Conservations had for the state and and and how that

2067
01:46:02,200 --> 01:46:05,240
Speaker 1: has come up from you know, the residents within this

2068
01:46:05,400 --> 01:46:09,120
Speaker 1: state's supporting especially conservation project. Most of our dens usually

2069
01:46:09,160 --> 01:46:11,599
Speaker 1: end up being on private so we have to get

2070
01:46:11,640 --> 01:46:13,720
Speaker 1: permission and they sometimes they might tell you know, and

2071
01:46:13,760 --> 01:46:15,519
Speaker 1: that's their right to do it, but we generally get

2072
01:46:15,600 --> 01:46:19,360
Speaker 1: really good cooperations. Absolutely, yeah, and so there's yeah, that's

2073
01:46:19,400 --> 01:46:21,479
Speaker 1: something I didn't talk to you about. Maybe you could

2074
01:46:21,520 --> 01:46:24,760
Speaker 1: just like talk on it for like thirty seconds. Public land,

2075
01:46:24,800 --> 01:46:27,760
Speaker 1: private land. Like in Arkansas, our core bear populations are

2076
01:46:27,800 --> 01:46:31,479
Speaker 1: on public land. You know, we've got pretty big blocks

2077
01:46:31,479 --> 01:46:33,720
Speaker 1: of national forest. Is that so we so we do

2078
01:46:33,920 --> 01:46:36,760
Speaker 1: see we see both, right, So so really the core

2079
01:46:36,840 --> 01:46:39,479
Speaker 1: of our population is a nice healthy mix of public

2080
01:46:39,520 --> 01:46:42,920
Speaker 1: and private land, and and so we have those. Really

2081
01:46:43,120 --> 01:46:46,120
Speaker 1: we've got large tracts of public land they certainly have bears,

2082
01:46:46,640 --> 01:46:48,840
Speaker 1: but we also have some areas, I mean, especially when

2083
01:46:48,840 --> 01:46:51,080
Speaker 1: you're thinking about kind of you know, some of the

2084
01:46:51,160 --> 01:46:54,880
Speaker 1: locations around here where it's more private land interspersed that

2085
01:46:55,720 --> 01:46:59,479
Speaker 1: core areas wouldn't necessarily be hubbed around big blocks of

2086
01:46:59,520 --> 01:47:01,760
Speaker 1: public land, and like Mark Twain and stuff, they still

2087
01:47:01,800 --> 01:47:03,479
Speaker 1: I mean many of the cases they still are. It's

2088
01:47:03,479 --> 01:47:05,760
Speaker 1: probably half and half. Yeah. So but when when we

2089
01:47:05,840 --> 01:47:08,360
Speaker 1: think about like the Mark Twain National Forest compared to

2090
01:47:08,600 --> 01:47:11,040
Speaker 1: Ozark National Force and Washington Force, I think that you know,

2091
01:47:11,160 --> 01:47:15,200
Speaker 1: Mark Twain is kind of separated into these segments, right,

2092
01:47:15,280 --> 01:47:17,519
Speaker 1: So they're they're big segments, and it makes up this

2093
01:47:18,040 --> 01:47:21,680
Speaker 1: there's private and stuff. Yeah, okay, so they could be

2094
01:47:22,240 --> 01:47:26,439
Speaker 1: really living in the mark Twain but beyond private lands. Ye. Yeah.

2095
01:47:26,479 --> 01:47:28,839
Speaker 1: And and in some of the areas where we've found

2096
01:47:29,360 --> 01:47:31,960
Speaker 1: um kind of that remnant d n A, A lot

2097
01:47:32,040 --> 01:47:34,040
Speaker 1: of that was on private land. A lot of you know,

2098
01:47:34,120 --> 01:47:36,080
Speaker 1: the hair snares that were run on private land and

2099
01:47:36,160 --> 01:47:38,320
Speaker 1: things like that. And we've you know, in some of

2100
01:47:38,360 --> 01:47:41,439
Speaker 1: the areas, um kind of in the south central part

2101
01:47:41,479 --> 01:47:43,840
Speaker 1: of the state of South Highway sixty but kind of

2102
01:47:43,920 --> 01:47:46,200
Speaker 1: centered in the part of central part of the state. UM,

2103
01:47:46,479 --> 01:47:48,560
Speaker 1: A lot of our trapping occurs on private land. We

2104
01:47:48,600 --> 01:47:53,640
Speaker 1: have tons of landowner cooperators absolutely, yeah, and and and realistically,

2105
01:47:53,720 --> 01:47:55,439
Speaker 1: like Josh that and we couldn't do the bear project

2106
01:47:55,479 --> 01:47:57,880
Speaker 1: without it because bears don't know fence rows, and they

2107
01:47:57,920 --> 01:48:00,280
Speaker 1: don't know boundaries and stuff like that, you know, so

2108
01:48:00,360 --> 01:48:02,519
Speaker 1: they don't only occur on the Forest Service. So if

2109
01:48:02,520 --> 01:48:04,880
Speaker 1: we've got a drop collar that's on private land, we

2110
01:48:04,920 --> 01:48:07,040
Speaker 1: need to go pick that up. We we always you know,

2111
01:48:07,120 --> 01:48:09,240
Speaker 1: we we don't go on that property without the permission

2112
01:48:09,280 --> 01:48:11,760
Speaker 1: of the landowner. And um, and we have so many

2113
01:48:11,840 --> 01:48:13,960
Speaker 1: folks that like, hey, I've got bears here, you want

2114
01:48:14,000 --> 01:48:15,360
Speaker 1: to set up a trap, you know, I know, your

2115
01:48:15,400 --> 01:48:17,040
Speaker 1: research project. Do you want to set up a trap

2116
01:48:17,120 --> 01:48:19,759
Speaker 1: and stuff like that. I mean, there's there's people are excited.

2117
01:48:19,840 --> 01:48:22,840
Speaker 1: Oh yeah, yeah, absolutely. Where are the where are the core?

2118
01:48:23,400 --> 01:48:26,240
Speaker 1: Like if you could like where are where are the

2119
01:48:26,400 --> 01:48:30,080
Speaker 1: main populations? So so we would say that our main

2120
01:48:30,200 --> 01:48:34,320
Speaker 1: population is really south of Highway sixty here in Missouri,

2121
01:48:34,560 --> 01:48:36,639
Speaker 1: and it's kind of spread across all of those southern

2122
01:48:36,720 --> 01:48:39,400
Speaker 1: counties and so like that's the that's the real core,

2123
01:48:40,200 --> 01:48:43,080
Speaker 1: all the way over to the Mississippi River. Probably not

2124
01:48:43,240 --> 01:48:46,320
Speaker 1: that far so Poplar Bluff area, yeah, I mean and

2125
01:48:46,360 --> 01:48:49,800
Speaker 1: if you from like Joplin, the Poplar Bluff Choplin is

2126
01:48:49,800 --> 01:48:51,439
Speaker 1: a little bit of a stretch, but really okay, so

2127
01:48:51,520 --> 01:48:53,760
Speaker 1: they're not going that far west. There are some there,

2128
01:48:53,960 --> 01:48:58,479
Speaker 1: but again it's definitely outside Springfield to there. Yeah. And

2129
01:48:58,960 --> 01:49:00,720
Speaker 1: when you when you look at the map of kind

2130
01:49:00,720 --> 01:49:02,840
Speaker 1: of the forested areas of Missouri, when you look at

2131
01:49:03,200 --> 01:49:05,840
Speaker 1: kind of those southern counties, you can pick out those

2132
01:49:05,880 --> 01:49:08,559
Speaker 1: big blocks of forests and it's those really connected patches

2133
01:49:08,640 --> 01:49:11,200
Speaker 1: and and so we say, you know, primary range is

2134
01:49:11,240 --> 01:49:13,320
Speaker 1: south of Highway forty four, and that's a really easy

2135
01:49:13,360 --> 01:49:15,800
Speaker 1: interstate for people to think about. It kind of cuts

2136
01:49:15,880 --> 01:49:19,200
Speaker 1: the state diagonally and then you know, recognizing what that

2137
01:49:19,320 --> 01:49:21,960
Speaker 1: within that primary range, there's a lot of variability in

2138
01:49:22,080 --> 01:49:23,920
Speaker 1: terms of the density of bears and how many bear

2139
01:49:23,960 --> 01:49:26,599
Speaker 1: reports we get from certain counties and things like that. UM.

2140
01:49:26,720 --> 01:49:28,960
Speaker 1: And then as you go north of that and closer

2141
01:49:29,000 --> 01:49:31,360
Speaker 1: to St. Louis, we kind of hit these expansion areas

2142
01:49:31,400 --> 01:49:35,240
Speaker 1: where it's year after year dispersing mail showing up and um,

2143
01:49:35,439 --> 01:49:38,439
Speaker 1: there's high quality habitat there and it's connected. But it's

2144
01:49:38,439 --> 01:49:41,040
Speaker 1: also these areas that are surrounded by human populations and

2145
01:49:41,160 --> 01:49:45,040
Speaker 1: so there's that kind of um, you know, education factor

2146
01:49:45,120 --> 01:49:47,160
Speaker 1: that goes into it and UM. And in terms of

2147
01:49:47,200 --> 01:49:49,360
Speaker 1: our research, it's actually one of the things that we're

2148
01:49:49,400 --> 01:49:51,800
Speaker 1: looking at. So so you know, we we estimate the

2149
01:49:51,840 --> 01:49:54,400
Speaker 1: population and monitor that population growth. We can look at

2150
01:49:54,439 --> 01:49:56,519
Speaker 1: the home ranges and and you know, we know our

2151
01:49:56,560 --> 01:49:59,240
Speaker 1: bears are choosy and they're selecting the highest quality habitat

2152
01:49:59,280 --> 01:50:02,040
Speaker 1: and things like that. UM. But we can think to

2153
01:50:02,120 --> 01:50:05,479
Speaker 1: the future, right, and we can look at based on

2154
01:50:05,600 --> 01:50:08,280
Speaker 1: how bears use the landscape here and what habitat you know,

2155
01:50:08,360 --> 01:50:11,439
Speaker 1: components are important to them. What are some of the

2156
01:50:11,520 --> 01:50:14,160
Speaker 1: towns that are likely to have conflicts in the future.

2157
01:50:14,520 --> 01:50:16,680
Speaker 1: And so you know, Josh deals a ton with the

2158
01:50:16,760 --> 01:50:19,519
Speaker 1: Brandson area and you know some of the suburbs of

2159
01:50:19,600 --> 01:50:22,439
Speaker 1: Springfield and in between the two and and like this

2160
01:50:22,640 --> 01:50:25,120
Speaker 1: is you know, right around the core core bear range, right,

2161
01:50:25,160 --> 01:50:27,720
Speaker 1: So it's not surprising. But then we can look down

2162
01:50:27,800 --> 01:50:32,480
Speaker 1: the road and rather than it being reactive exactly exactly,

2163
01:50:32,800 --> 01:50:34,760
Speaker 1: and we've done a lot of corridor work looking at

2164
01:50:34,840 --> 01:50:36,960
Speaker 1: like what are the most likely travel corridors that are

2165
01:50:37,000 --> 01:50:39,640
Speaker 1: bears would have and then um kind of identifying what

2166
01:50:39,760 --> 01:50:42,920
Speaker 1: are barriers to movement and recognizing that you know, maybe

2167
01:50:42,960 --> 01:50:45,639
Speaker 1: those barriers could use mitigation in the future, if that's

2168
01:50:45,680 --> 01:50:49,920
Speaker 1: something that is a possibility, that's right, yeah, yeah exactly,

2169
01:50:50,080 --> 01:50:52,719
Speaker 1: or you know, just maintaining that connectivity and and looking

2170
01:50:52,800 --> 01:50:55,040
Speaker 1: at how we can keep that forest connected and stuff

2171
01:50:55,040 --> 01:50:56,840
Speaker 1: so that we have that continued bear movement, but then

2172
01:50:56,960 --> 01:51:00,840
Speaker 1: also looking at how those corridors might funnel bears to

2173
01:51:00,880 --> 01:51:02,880
Speaker 1: certain areas where now it's going to be a challenge

2174
01:51:03,080 --> 01:51:05,800
Speaker 1: es you're doing some predictive work. You know, they say

2175
01:51:05,840 --> 01:51:09,640
Speaker 1: the wash dolls and ozark bears are alapatrick populations for

2176
01:51:09,720 --> 01:51:12,840
Speaker 1: the most part because the Arkansas River and then I

2177
01:51:13,040 --> 01:51:16,479
Speaker 1: forty and I mean for the most part, bears aren't

2178
01:51:16,640 --> 01:51:19,240
Speaker 1: crossing that that much. But I mean, so that's what

2179
01:51:19,320 --> 01:51:23,120
Speaker 1: you're talking about. It's like physical barriers that are dividing populations.

2180
01:51:23,720 --> 01:51:28,560
Speaker 1: But yeah, that's fascinating, that's cool, cool stuff. Well, we

2181
01:51:28,680 --> 01:51:32,680
Speaker 1: have gone a while here, and that's perfect. Um how far?

2182
01:51:32,720 --> 01:51:38,080
Speaker 1: How long have we going? Long time? Josh is just

2183
01:51:38,280 --> 01:51:41,720
Speaker 1: really he just loves to talk. I could talk to

2184
01:51:41,760 --> 01:51:44,719
Speaker 1: you for another two hours. I really could. Closing closing,

2185
01:51:45,000 --> 01:51:47,479
Speaker 1: closing comment. You know, I think I think it's an

2186
01:51:47,520 --> 01:51:49,720
Speaker 1: exciting time for bears in the state here. I mean,

2187
01:51:49,760 --> 01:51:51,680
Speaker 1: it just just bears in general. You know, if you're

2188
01:51:51,720 --> 01:51:54,320
Speaker 1: interested in bear management, regardless of what state you live in,

2189
01:51:54,640 --> 01:51:57,120
Speaker 1: it's an exciting time here. And I would say, you know,

2190
01:51:57,240 --> 01:51:58,880
Speaker 1: just kind of keep an eye out. We're we're in

2191
01:51:58,960 --> 01:52:03,280
Speaker 1: this you know, phase of looking at that potential hunting season,

2192
01:52:03,800 --> 01:52:06,640
Speaker 1: thinking about how that might how that might look. Um.

2193
01:52:06,840 --> 01:52:09,479
Speaker 1: But also just with this growing and expanding and expanding

2194
01:52:09,520 --> 01:52:12,120
Speaker 1: population here, you know, we're in we're in a really

2195
01:52:12,640 --> 01:52:15,439
Speaker 1: active management that involves a whole lot of different things.

2196
01:52:15,520 --> 01:52:17,960
Speaker 1: You know. It's you know, it's not it's not just hunting.

2197
01:52:18,000 --> 01:52:21,320
Speaker 1: It's not just education, it's not just nuisance issues, it's

2198
01:52:21,600 --> 01:52:24,400
Speaker 1: how all of those kind of combined into one copies

2199
01:52:24,439 --> 01:52:27,680
Speaker 1: of management program. So yeah, i'd say, you know, keep

2200
01:52:27,680 --> 01:52:29,559
Speaker 1: an eye on and stay tuned, and then if if

2201
01:52:29,760 --> 01:52:32,519
Speaker 1: anyone's interested in the research project we do on the

2202
01:52:32,680 --> 01:52:36,000
Speaker 1: MDC web page, have a research page and we have

2203
01:52:36,160 --> 01:52:38,519
Speaker 1: a bare Story map that we have on there that

2204
01:52:38,720 --> 01:52:41,720
Speaker 1: we update once a year and it's kind of a

2205
01:52:42,080 --> 01:52:45,000
Speaker 1: fun interactive way. So folks haven't seen bare Den's We've

2206
01:52:45,040 --> 01:52:47,720
Speaker 1: got some really cool like bare Den videos and like

2207
01:52:48,120 --> 01:52:50,040
Speaker 1: a bear in a hollow tree, you know, putting a

2208
01:52:50,120 --> 01:52:52,519
Speaker 1: go pro in and looking at her from above and

2209
01:52:52,640 --> 01:52:54,479
Speaker 1: stuff like that, and the pairs coming out of caves

2210
01:52:54,560 --> 01:52:57,240
Speaker 1: and everything. So I'd say check it out if there's

2211
01:52:57,240 --> 01:52:59,799
Speaker 1: any interest there. What's it, what's it called? What's that website?

2212
01:53:00,200 --> 01:53:01,960
Speaker 1: So so you can just get to it at MDC

2213
01:53:02,360 --> 01:53:05,439
Speaker 1: dot MO dot gov slash bears and then there's a

2214
01:53:05,520 --> 01:53:08,240
Speaker 1: link to all of the research, all the management stuff,

2215
01:53:08,280 --> 01:53:12,280
Speaker 1: our management plan and everything. It's all all right there, perfect,

2216
01:53:12,560 --> 01:53:16,320
Speaker 1: and the potential hunt is just for residents as well,

2217
01:53:16,479 --> 01:53:19,120
Speaker 1: that's right. Yeah, So I think that's great. I think

2218
01:53:19,160 --> 01:53:21,640
Speaker 1: that I just wanted to say that because you know,

2219
01:53:21,680 --> 01:53:23,960
Speaker 1: if somebody was like, oh, I can go to Missouri

2220
01:53:24,840 --> 01:53:27,559
Speaker 1: for bread for Missouri residents only, right, I think there

2221
01:53:27,600 --> 01:53:31,400
Speaker 1: should be perks for state residents. We didn't talk about

2222
01:53:31,439 --> 01:53:33,519
Speaker 1: as part of the plan kind of the allotment with

2223
01:53:33,680 --> 01:53:37,040
Speaker 1: landowners versus general ottery either. Okay, I saw that. Yeah,

2224
01:53:37,080 --> 01:53:39,080
Speaker 1: so that is that's a that's a part of the proposal.

2225
01:53:39,200 --> 01:53:43,559
Speaker 1: So so essentially allocating the first ten percent of permits

2226
01:53:43,640 --> 01:53:47,720
Speaker 1: to landowners that that have twenty contiguous acres within the

2227
01:53:47,760 --> 01:53:51,200
Speaker 1: bear management zone for which they're applying. So so trying

2228
01:53:51,320 --> 01:53:54,920
Speaker 1: to get to, you know, where that we can encourage

2229
01:53:54,920 --> 01:53:58,080
Speaker 1: that landowner participation that way and recognizing, you know, we're

2230
01:53:58,080 --> 01:54:01,840
Speaker 1: still talking about a limited a limited hunting season right now.

2231
01:54:02,200 --> 01:54:05,320
Speaker 1: Would part of that be some type of thing where

2232
01:54:05,320 --> 01:54:07,840
Speaker 1: they would have to report back at the end with

2233
01:54:07,960 --> 01:54:10,559
Speaker 1: waterfowl and stuff like that. Yeah, so we so we will.

2234
01:54:10,840 --> 01:54:13,800
Speaker 1: We'll have a TeleCheck requirement for any harvested bears and

2235
01:54:13,880 --> 01:54:17,160
Speaker 1: then and then there's been discussions about post harvest surveys

2236
01:54:17,240 --> 01:54:19,479
Speaker 1: off the season were to move forward and things like that,

2237
01:54:19,600 --> 01:54:21,400
Speaker 1: and that's something that we do for a variety of

2238
01:54:21,479 --> 01:54:24,840
Speaker 1: other species. So, um, looking at you know, gaining that

2239
01:54:24,960 --> 01:54:27,920
Speaker 1: information for harvested bears, we would require a tooth so

2240
01:54:28,000 --> 01:54:30,360
Speaker 1: that we could get that age, age, structure of the

2241
01:54:30,479 --> 01:54:33,720
Speaker 1: of the harvest and stuff. So yeah, great shepherd. Do

2242
01:54:33,760 --> 01:54:37,120
Speaker 1: you have any questions? None? You learned something though, didn't

2243
01:54:37,120 --> 01:54:45,080
Speaker 1: you what you learn there's you can go Yep, that's right,

2244
01:54:45,240 --> 01:54:48,920
Speaker 1: that one bear went that far. Yep. Great, Well, thank

2245
01:54:48,960 --> 01:54:54,040
Speaker 1: you guys, And yeah, well I get quick, I just

2246
01:54:54,160 --> 01:55:01,120
Speaker 1: have I have more questions. You can start your own podcast. Yeah,

2247
01:55:01,560 --> 01:55:03,240
Speaker 1: I don't know, I guess this would probably be a

2248
01:55:03,360 --> 01:55:05,440
Speaker 1: quick question. But what would be the thing that would

2249
01:55:05,520 --> 01:55:08,040
Speaker 1: help you guys with your research more like with public

2250
01:55:08,120 --> 01:55:11,760
Speaker 1: interaction or or just if if somebody wanted to help

2251
01:55:11,880 --> 01:55:14,400
Speaker 1: just bology us in their own state, what would be

2252
01:55:14,520 --> 01:55:16,800
Speaker 1: a way to think about how to interact with that,

2253
01:55:17,240 --> 01:55:19,760
Speaker 1: you know, I think if if there's interest there, you know,

2254
01:55:19,960 --> 01:55:22,720
Speaker 1: look look to the website, see if there's any guidance there.

2255
01:55:22,760 --> 01:55:24,440
Speaker 1: I mean, one of the big things that we encourage

2256
01:55:24,440 --> 01:55:26,920
Speaker 1: the public due to report bear sightings. And so that's

2257
01:55:26,920 --> 01:55:29,400
Speaker 1: not something that every state does, especially states with you know,

2258
01:55:29,640 --> 01:55:32,720
Speaker 1: huge burgeoning populations and stuff, but but for us here

2259
01:55:32,840 --> 01:55:36,720
Speaker 1: that's a really critical component and in some cases, it's

2260
01:55:36,840 --> 01:55:40,160
Speaker 1: that one sighting report that leads to us trapping on

2261
01:55:40,400 --> 01:55:43,040
Speaker 1: a property because there's a collar bear there, or because

2262
01:55:43,440 --> 01:55:45,120
Speaker 1: you know, they've got a female in an area where

2263
01:55:45,120 --> 01:55:46,960
Speaker 1: we'd like to call her a female and stuff like that,

2264
01:55:47,120 --> 01:55:49,160
Speaker 1: and so I mean I think I would say, you know,

2265
01:55:49,240 --> 01:55:52,120
Speaker 1: you could reach out in that instance. Um. And for me,

2266
01:55:52,240 --> 01:55:54,760
Speaker 1: I mean I I always get questions from the public

2267
01:55:54,800 --> 01:55:57,800
Speaker 1: about the project and and interest, you know, and find

2268
01:55:57,840 --> 01:56:02,120
Speaker 1: their email and send an email kind of thing. Yeah, yeah, cool, good,

2269
01:56:03,040 --> 01:56:05,960
Speaker 1: Well think the wild wise wild because that's real bear's names.

2270
01:56:06,840 --> 01:56:08,960
Speaker 1: Thank you for good h