1 00:00:08,920 --> 00:00:13,320 Speaker 1: This is the Meat Eater Podcast coming at you shirtless, severely, 2 00:00:13,440 --> 00:00:18,279 Speaker 1: bug bitten and in my case, underwear listening podcast. You 3 00:00:18,360 --> 00:00:27,720 Speaker 1: can't predict anything. Okay, Welcome to the Meat Eater. I 4 00:00:27,880 --> 00:00:31,840 Speaker 1: changed the name. It's now the Meat Eater Digital Radio Program. 5 00:00:31,880 --> 00:00:34,440 Speaker 1: I like that better. There's a bunch of people here. 6 00:00:34,440 --> 00:00:36,199 Speaker 1: I'm gonna introduce him like how if if I was 7 00:00:36,280 --> 00:00:41,199 Speaker 1: dealing poker by going clockwise? Yo, honestly tell us by 8 00:00:41,280 --> 00:00:44,720 Speaker 1: Janni is his new name? Garrett Smith, who has a 9 00:00:44,760 --> 00:00:46,920 Speaker 1: distended belly right now, and he's and he's got a 10 00:00:47,040 --> 00:00:50,960 Speaker 1: chew packed and somehow they're related like that chew is 11 00:00:50,960 --> 00:00:53,520 Speaker 1: gonna alleviate his distended belly. I think he was trying 12 00:00:53,520 --> 00:00:57,520 Speaker 1: to tell us in some kind of subtle way. Um, 13 00:00:57,600 --> 00:01:02,320 Speaker 1: Chris Gil like a fish, like a fish. Who's a 14 00:01:02,320 --> 00:01:04,399 Speaker 1: turkey man? Now you just heard your first turkey gowl? 15 00:01:04,520 --> 00:01:07,520 Speaker 1: I did? Is that true? I think it is? Yeah. 16 00:01:07,680 --> 00:01:10,080 Speaker 1: I can't remember hearing one before that, I mean, you know, 17 00:01:10,120 --> 00:01:16,160 Speaker 1: other than digitally. Yeah. And then Dr Carl Malcolm Carl 18 00:01:16,160 --> 00:01:21,320 Speaker 1: tell us about the Wisconsin supersow Man, the Wisconsin Supersou, 19 00:01:21,760 --> 00:01:25,080 Speaker 1: the wiscon This is the most this is it? Yeah? 20 00:01:25,200 --> 00:01:27,840 Speaker 1: Tell us about the Wisconsin supersou all right, so a 21 00:01:27,880 --> 00:01:31,640 Speaker 1: little backstory, lay it all out, lay it all out, 22 00:01:31,720 --> 00:01:34,520 Speaker 1: all right, I mean within reason. Okay, So so my 23 00:01:34,560 --> 00:01:40,840 Speaker 1: mom and my father. Yeah, so I'll began right around um. 24 00:01:40,880 --> 00:01:42,760 Speaker 1: All right, So I went to graduate school at the 25 00:01:42,800 --> 00:01:45,520 Speaker 1: University of Wisconsin Madison, which, by the way, was the 26 00:01:45,560 --> 00:01:49,160 Speaker 1: first wildlife management program anywhere in the world, founded by 27 00:01:49,160 --> 00:01:52,600 Speaker 1: Aldo Leopold after he left the Forest Service. That was 28 00:01:52,640 --> 00:01:54,320 Speaker 1: one of the draws for me and kind of a 29 00:01:54,360 --> 00:01:59,200 Speaker 1: Leopold junkie growing up. Um, but going to Madison, I 30 00:01:59,280 --> 00:02:04,160 Speaker 1: was in kind of the southern farm belt region of Wisconsin, 31 00:02:04,400 --> 00:02:07,680 Speaker 1: and as you travel north in the state of Wisconsin, 32 00:02:07,760 --> 00:02:12,440 Speaker 1: you increasingly get into more and more forested landscapes, to 33 00:02:12,480 --> 00:02:13,880 Speaker 1: the point where you get up into the northern part 34 00:02:13,880 --> 00:02:18,200 Speaker 1: of the state, and the northern third is predominantly forested. 35 00:02:19,120 --> 00:02:22,799 Speaker 1: So about halfway up you're in this interesting mix where 36 00:02:22,800 --> 00:02:26,200 Speaker 1: you've got about a fifty fifty ratio of row crops 37 00:02:26,400 --> 00:02:31,160 Speaker 1: like corn and soybeans and forest. And our good friend 38 00:02:31,240 --> 00:02:33,520 Speaker 1: Doug Durn and south of that line, yep, he's south 39 00:02:33,560 --> 00:02:36,480 Speaker 1: of that line. He's just like solid egg. No, well, 40 00:02:36,560 --> 00:02:39,880 Speaker 1: defining like the defining feature or how would you put it? 41 00:02:40,160 --> 00:02:42,280 Speaker 1: You know, So the Driftless area, the southwest part of 42 00:02:42,280 --> 00:02:46,200 Speaker 1: the state where dug Durn is located is is interesting 43 00:02:46,240 --> 00:02:50,000 Speaker 1: because it does have a major agricultural component, but there's 44 00:02:50,040 --> 00:02:52,680 Speaker 1: certainly a lot of forest land, and part of that 45 00:02:52,760 --> 00:02:55,520 Speaker 1: is because there's so much slope, which is unusual for 46 00:02:55,560 --> 00:02:58,600 Speaker 1: the rest of the state until Yeah, so there's there's 47 00:02:58,639 --> 00:03:01,160 Speaker 1: some untillable land, which is where you typically have forests 48 00:03:01,160 --> 00:03:03,560 Speaker 1: there in the Driftless area. And this relates to the 49 00:03:03,639 --> 00:03:07,200 Speaker 1: story because what's been happening for the last few decades 50 00:03:07,800 --> 00:03:11,520 Speaker 1: is that black bears throughout the Midwest are increasingly expanding 51 00:03:11,560 --> 00:03:14,120 Speaker 1: their range southward. So I don't know if Doug has 52 00:03:14,120 --> 00:03:16,320 Speaker 1: any stories about bears showing up in his property in 53 00:03:16,360 --> 00:03:19,240 Speaker 1: the Driftless area yet, not yet, because I feel like 54 00:03:19,240 --> 00:03:21,799 Speaker 1: if he did, I would have heard about it. Yeah, well, 55 00:03:22,280 --> 00:03:24,600 Speaker 1: because he'll tell you about everything down to a greener showing, 56 00:03:25,480 --> 00:03:28,040 Speaker 1: you know what I mean. I imagine he would, and 57 00:03:28,360 --> 00:03:31,079 Speaker 1: I predict that he will have that story before too 58 00:03:31,080 --> 00:03:34,519 Speaker 1: long because certainly bears, why why are bears mark him south? 59 00:03:34,639 --> 00:03:37,080 Speaker 1: Like my theory on it, and this is completely untested 60 00:03:37,080 --> 00:03:39,360 Speaker 1: and probably you probably i'd recommend you do not publish 61 00:03:39,440 --> 00:03:41,800 Speaker 1: the paper on this is it. It It just took him 62 00:03:41,800 --> 00:03:47,160 Speaker 1: a hundred fifty years to get used to people. That's 63 00:03:47,400 --> 00:03:51,880 Speaker 1: the case. So what I think it has to do 64 00:03:51,920 --> 00:03:58,880 Speaker 1: with is persecution. So black bears are extremely adaptable with 65 00:03:58,920 --> 00:04:01,480 Speaker 1: their diet, and everybody knows is there. Like the classic omnivore, 66 00:04:01,520 --> 00:04:06,280 Speaker 1: they'll eat anything. They can subsist on vegetation purely. They 67 00:04:06,280 --> 00:04:09,480 Speaker 1: can do very well chowing down on meat and typically speaking, 68 00:04:09,520 --> 00:04:13,320 Speaker 1: they're eating some combination of the two. So they can 69 00:04:13,400 --> 00:04:16,280 Speaker 1: exist just about anywhere where there's where there's food for him. 70 00:04:16,800 --> 00:04:19,720 Speaker 1: You know, my neighbor, uh, you'll at my last cabin. 71 00:04:20,600 --> 00:04:23,280 Speaker 1: He's telling about a guy that had a bear come 72 00:04:23,360 --> 00:04:28,520 Speaker 1: into his workshop and drink three gallons gear oil. That's unreal. 73 00:04:29,240 --> 00:04:34,159 Speaker 1: I wonder if you killed it. If it didn't, it 74 00:04:34,240 --> 00:04:42,640 Speaker 1: probably tore some gastro intestinal situation. Was debating whether or 75 00:04:42,720 --> 00:04:44,200 Speaker 1: not to go there. But I took the high road 76 00:04:44,200 --> 00:04:48,640 Speaker 1: and let you take it there. So thanks for being Yeah, 77 00:04:48,720 --> 00:04:51,680 Speaker 1: phenomenal omnivorse. So the point is they're they're really adaptable. 78 00:04:51,720 --> 00:04:54,200 Speaker 1: They can live just about anywhere as long as they're 79 00:04:54,240 --> 00:04:57,320 Speaker 1: not being shot to the point where it's not sustainable. 80 00:04:57,400 --> 00:04:59,360 Speaker 1: You know, if, like anything else, if you shoot enough 81 00:04:59,360 --> 00:05:02,640 Speaker 1: of them, or you know, trap enough of them, if 82 00:05:02,640 --> 00:05:06,560 Speaker 1: you eliminate enough from the from the population, they're not 83 00:05:06,600 --> 00:05:10,000 Speaker 1: going to exist in a particular part of the state anymore. So. 84 00:05:10,120 --> 00:05:13,440 Speaker 1: The bears, like many other species UM that are managed 85 00:05:13,960 --> 00:05:18,600 Speaker 1: by state agencies as hunted species, have been on an 86 00:05:18,720 --> 00:05:21,800 Speaker 1: upward trajectory since their low point when they weren't being 87 00:05:21,839 --> 00:05:26,360 Speaker 1: managed as such. So essentially, bears, like many other species, 88 00:05:26,400 --> 00:05:30,640 Speaker 1: were persecuted by unregulated hunting for a long time and 89 00:05:30,720 --> 00:05:34,440 Speaker 1: driven out. I mean, we're just like no rules about 90 00:05:34,520 --> 00:05:36,760 Speaker 1: take and it doesn't matter what time of year, saw 91 00:05:36,880 --> 00:05:39,440 Speaker 1: with cubs whatever. You could at a time shoot a 92 00:05:39,440 --> 00:05:41,920 Speaker 1: bear and there was no just like everything else, right, 93 00:05:41,960 --> 00:05:43,600 Speaker 1: I mean at a time, that's what it was for 94 00:05:43,640 --> 00:05:48,880 Speaker 1: all these species. But under managed under a management scenario 95 00:05:49,200 --> 00:05:52,440 Speaker 1: where we're tracking populations, were making sure that the number 96 00:05:52,440 --> 00:05:56,479 Speaker 1: of bears taken is sustainable. Um, they are showing that 97 00:05:56,520 --> 00:05:59,960 Speaker 1: they're capable of existing well outside of what people think 98 00:06:00,040 --> 00:06:03,120 Speaker 1: of as bear country, including places like southwest Wisconsin, which 99 00:06:03,160 --> 00:06:08,000 Speaker 1: historically certainly had bears and now increasingly has bears showing 100 00:06:08,040 --> 00:06:12,640 Speaker 1: up places like Richland County as an example. Yeah, right, 101 00:06:13,000 --> 00:06:15,240 Speaker 1: So I'm throwing it out there for you. Always feel 102 00:06:15,240 --> 00:06:19,039 Speaker 1: like calling Dug up right now if he if he 103 00:06:19,080 --> 00:06:21,599 Speaker 1: doesn't have a bear story about his property, he will 104 00:06:21,920 --> 00:06:25,200 Speaker 1: he'll have well he will soon, I think, and he'll 105 00:06:25,200 --> 00:06:29,480 Speaker 1: certainly have bear stories from other people's properties. So part 106 00:06:29,520 --> 00:06:32,920 Speaker 1: of the equation here with the expanding bear population is 107 00:06:34,120 --> 00:06:38,000 Speaker 1: the super Sal and bears like her. And the super 108 00:06:38,040 --> 00:06:40,839 Speaker 1: Sal was an individual bear that was part of my 109 00:06:40,920 --> 00:06:43,640 Speaker 1: research project and as a graduate student at the University Wisconsin. 110 00:06:44,560 --> 00:06:47,880 Speaker 1: Who but tell, tell, tell what you were doing? Okay, 111 00:06:47,920 --> 00:06:50,240 Speaker 1: So I was looking at that spatial expansion. So what 112 00:06:50,320 --> 00:06:53,719 Speaker 1: I was doing, I was I was specifically focused on 113 00:06:54,920 --> 00:06:59,159 Speaker 1: dispersing subadults. So black bears are really interesting and that 114 00:06:59,240 --> 00:07:02,560 Speaker 1: you know they're they're in the den. So they they 115 00:07:02,600 --> 00:07:06,640 Speaker 1: emerge into the world um with their mother in the 116 00:07:06,680 --> 00:07:10,240 Speaker 1: den and basically just latch on and nurse for the 117 00:07:10,240 --> 00:07:12,400 Speaker 1: first couple of months of their lives, and then the 118 00:07:12,440 --> 00:07:15,680 Speaker 1: family emerges from the den in the spring. I gotta 119 00:07:15,680 --> 00:07:18,640 Speaker 1: ask you the other question, bring it. What's the difference 120 00:07:18,640 --> 00:07:25,120 Speaker 1: between precocial. They're not precocial, they are altricial. Altricial. Yeah, 121 00:07:25,240 --> 00:07:30,000 Speaker 1: So they're born in a state where essentially um they're 122 00:07:30,080 --> 00:07:36,040 Speaker 1: relatively underdeveloped, they're tiny, their limbs are barely formed when 123 00:07:36,080 --> 00:07:39,640 Speaker 1: they're born, and they basically just navigate from the birth 124 00:07:39,720 --> 00:07:45,280 Speaker 1: canal to a nipple latch on. And bears in general, 125 00:07:45,400 --> 00:07:48,440 Speaker 1: including black bears, crank out some of the most calorie 126 00:07:49,040 --> 00:07:52,720 Speaker 1: dense milk anywhere in the animal kingdom. It's like liquid 127 00:07:52,840 --> 00:07:56,920 Speaker 1: butter coming from those nipples. So they grow really fast, 128 00:07:57,360 --> 00:08:02,240 Speaker 1: and they do after the wrong nipples. Yeah, I mean 129 00:08:02,280 --> 00:08:04,280 Speaker 1: it's amazing. So as an example, you know, I have 130 00:08:04,360 --> 00:08:07,520 Speaker 1: my hand on a lot of bears um during the 131 00:08:07,560 --> 00:08:09,920 Speaker 1: field work. And when you go to work up a 132 00:08:10,000 --> 00:08:13,520 Speaker 1: den that had a sow with cubs, the styles would 133 00:08:13,520 --> 00:08:17,080 Speaker 1: be lactating. And there were a number of times where 134 00:08:17,120 --> 00:08:19,800 Speaker 1: explaining working up a den. But use a checklist for you. 135 00:08:21,400 --> 00:08:23,000 Speaker 1: I want you to I want to do a quickie 136 00:08:23,480 --> 00:08:28,360 Speaker 1: pre precocial altricial. Do quickie on that. And then don't 137 00:08:28,400 --> 00:08:29,960 Speaker 1: just say work up a den, because no one's gonna 138 00:08:29,960 --> 00:08:32,640 Speaker 1: know what the hell that means. Okay, all right, precuecial altricial. 139 00:08:32,800 --> 00:08:37,480 Speaker 1: So species that are born precocial have the ability to 140 00:08:38,480 --> 00:08:43,319 Speaker 1: do things like evade predation. So, for example, like pronghorn fawns, 141 00:08:43,520 --> 00:08:46,520 Speaker 1: when they're born it's a matter of days before they're 142 00:08:46,559 --> 00:08:48,719 Speaker 1: up on their feet and able to cruise if a 143 00:08:48,800 --> 00:08:52,839 Speaker 1: predator shows up. Alright, altricial species are born in a 144 00:08:52,840 --> 00:08:54,599 Speaker 1: state where they still have a lot of development to go. 145 00:08:54,880 --> 00:08:57,599 Speaker 1: So we're humans are altricial. Yeah, man, Yeah, you know, 146 00:08:58,400 --> 00:09:00,520 Speaker 1: infant is not going to evade pre ation. It's got 147 00:09:00,600 --> 00:09:03,400 Speaker 1: to be protected, just like a bear cup all right. Now, 148 00:09:03,480 --> 00:09:05,760 Speaker 1: working up a den essentially, what I'm referring to is 149 00:09:05,880 --> 00:09:10,560 Speaker 1: going into a place where bears are hibernating. They've been 150 00:09:10,600 --> 00:09:12,920 Speaker 1: located either because they've got a radio collar or someone 151 00:09:13,000 --> 00:09:16,320 Speaker 1: from the public has encountered a den and contacted through 152 00:09:16,440 --> 00:09:22,640 Speaker 1: some avenue researchers like myself, and we go into the 153 00:09:22,720 --> 00:09:27,120 Speaker 1: den with typically a poll syringe or a jab stick, 154 00:09:27,360 --> 00:09:31,800 Speaker 1: which is basically envisioned like a broom handle with a 155 00:09:31,920 --> 00:09:35,040 Speaker 1: big syringe and a needle on the end. And the 156 00:09:35,120 --> 00:09:37,000 Speaker 1: goal is to be able to give the bear an 157 00:09:37,080 --> 00:09:41,520 Speaker 1: injection in some major muscle without putting yourself in harm's way. 158 00:09:42,559 --> 00:09:45,719 Speaker 1: So you're either trying to get an injection somewhere like 159 00:09:45,840 --> 00:09:48,240 Speaker 1: in the buttock or in the shoulder. Those are the 160 00:09:48,280 --> 00:09:51,480 Speaker 1: two best spots to try to get a stick, and 161 00:09:52,480 --> 00:09:54,560 Speaker 1: the den's. You know, when people think of a bear den, 162 00:09:54,640 --> 00:09:56,760 Speaker 1: most folks are thinking like a hole in the ground 163 00:09:56,800 --> 00:09:59,480 Speaker 1: with the bears piled up in it, a cave. But 164 00:09:59,840 --> 00:10:03,520 Speaker 1: and and sometimes that is the case. But I would say, man, 165 00:10:03,640 --> 00:10:06,880 Speaker 1: probably around half the time they're above ground, maybe in 166 00:10:07,000 --> 00:10:10,120 Speaker 1: like a a slash pile where they've kind of carved 167 00:10:10,120 --> 00:10:12,679 Speaker 1: out a little nest, or sometimes just laying on the 168 00:10:12,760 --> 00:10:14,960 Speaker 1: ground in the wide open. You were saying, you found 169 00:10:15,040 --> 00:10:17,760 Speaker 1: him dend up just under like some bows, over under 170 00:10:17,840 --> 00:10:21,200 Speaker 1: overhanging evergreen boughs. I found him, you know, I found 171 00:10:21,280 --> 00:10:24,160 Speaker 1: him dend up in places where they really have almost 172 00:10:24,200 --> 00:10:26,360 Speaker 1: no cover. They're just like laying there in the snow, 173 00:10:26,640 --> 00:10:29,160 Speaker 1: getting snowed on, and the cubs will be curled up 174 00:10:29,200 --> 00:10:32,840 Speaker 1: against their bellies. Um, and it doesn't look like they 175 00:10:32,920 --> 00:10:36,439 Speaker 1: put any effort at all into seeking like shelter of 176 00:10:36,480 --> 00:10:39,240 Speaker 1: any form, so highly variable, what these dens look like. 177 00:10:40,840 --> 00:10:42,959 Speaker 1: I was gonna just ask if you have like has 178 00:10:43,000 --> 00:10:46,400 Speaker 1: that always been like that, like when you read older papers, 179 00:10:46,679 --> 00:10:49,040 Speaker 1: did they have research that shows that as well? Or 180 00:10:49,080 --> 00:10:50,960 Speaker 1: do you feel do you have a hypothesis on maybe 181 00:10:51,000 --> 00:10:53,880 Speaker 1: why that's is it happening more now than it used to? 182 00:10:54,200 --> 00:10:57,079 Speaker 1: Like the expanding bears aren't finding good spots, you know, man, 183 00:10:57,280 --> 00:10:58,839 Speaker 1: or maybe they don't need to because the winner is 184 00:10:59,280 --> 00:11:01,959 Speaker 1: still In some places. They don't even hibernate, right, I 185 00:11:02,000 --> 00:11:05,079 Speaker 1: mean they in hibernation is a whole different subject. You know, 186 00:11:05,240 --> 00:11:07,959 Speaker 1: they're not technically true hibernators. They go into like a 187 00:11:08,080 --> 00:11:11,920 Speaker 1: seasonal sort of downturn in their metabolism, but they're not 188 00:11:11,960 --> 00:11:16,800 Speaker 1: a true hibernating species. Um So, I don't think it's 189 00:11:16,840 --> 00:11:18,679 Speaker 1: something that has changed. I think it's part of their 190 00:11:18,760 --> 00:11:21,800 Speaker 1: life history. Um So, No, I don't. I do not 191 00:11:22,040 --> 00:11:27,080 Speaker 1: think that the denning without a hole in the ground 192 00:11:27,200 --> 00:11:30,080 Speaker 1: is something that is new for black bears, like it's 193 00:11:30,120 --> 00:11:31,599 Speaker 1: part of their life history. It has been part of 194 00:11:31,640 --> 00:11:36,839 Speaker 1: their life history. They basically do what they need to 195 00:11:36,920 --> 00:11:41,079 Speaker 1: do to survive. Some bears one year will make it, 196 00:11:41,160 --> 00:11:44,160 Speaker 1: then the next year not. There doesn't seem to be 197 00:11:44,160 --> 00:11:48,120 Speaker 1: any rhyme or reason. One interesting pattern that was true 198 00:11:48,200 --> 00:11:51,240 Speaker 1: throughout my research and was conveyed to me by other 199 00:11:51,240 --> 00:11:53,520 Speaker 1: folks who have done a lot of bear handling, is 200 00:11:53,640 --> 00:11:57,319 Speaker 1: that an individual bear will not use the same den 201 00:11:57,440 --> 00:12:01,480 Speaker 1: location twice ever, and in some cases, and I thought 202 00:12:01,480 --> 00:12:04,240 Speaker 1: it was twice in a row but they'll alternate. I've 203 00:12:05,080 --> 00:12:07,160 Speaker 1: I've never seen a bear go back to the same place, 204 00:12:07,679 --> 00:12:10,000 Speaker 1: and the people with whom I have done my research 205 00:12:10,440 --> 00:12:13,200 Speaker 1: have never seen a den get reused. What it makes sense. 206 00:12:13,240 --> 00:12:20,800 Speaker 1: There's a guy I know in northern Wisconsin. Um, his 207 00:12:20,960 --> 00:12:25,559 Speaker 1: last name is Heart maybe Bill Hart. He owns a 208 00:12:25,640 --> 00:12:31,440 Speaker 1: T shirt shop. Where's Northland College something like that. There 209 00:12:31,520 --> 00:12:33,719 Speaker 1: is Northland College, I can't remember the town. They have 210 00:12:33,800 --> 00:12:37,440 Speaker 1: to think called the Secret f Olson Nature Writing Award. Yeah, 211 00:12:37,440 --> 00:12:39,640 Speaker 1: and I won that award and was hosted by this 212 00:12:39,760 --> 00:12:42,160 Speaker 1: man Bill Hart. He took me down and showed me 213 00:12:42,679 --> 00:12:47,880 Speaker 1: undercut Bank on his property where every other year there's 214 00:12:47,880 --> 00:12:50,760 Speaker 1: a black bear with cubs in there, and there's a 215 00:12:50,800 --> 00:12:54,600 Speaker 1: little hole he can even look in there. So maybe 216 00:12:54,640 --> 00:12:57,160 Speaker 1: it's different bears. It's just a SP's different bears. Maybe 217 00:12:57,200 --> 00:13:00,360 Speaker 1: it's the same bear disproving this pattern that I've served. 218 00:13:01,040 --> 00:13:03,800 Speaker 1: I'm sure he listen. I hate guys like I hate 219 00:13:03,800 --> 00:13:06,280 Speaker 1: people to do what I just did, because you're trying 220 00:13:06,280 --> 00:13:09,600 Speaker 1: to talk about like generally right, So generally it's bad 221 00:13:09,920 --> 00:13:12,960 Speaker 1: to smoke tons of cigarettes and then someone's like agreeable, 222 00:13:13,200 --> 00:13:18,040 Speaker 1: you know, so it's like, yeah, interesting side this fello 223 00:13:18,120 --> 00:13:19,880 Speaker 1: by the last name of Heart. I will go on 224 00:13:20,000 --> 00:13:22,760 Speaker 1: to say this, I guarantee you in the history of 225 00:13:22,800 --> 00:13:26,920 Speaker 1: American black bears, a bear has reused a den. That's 226 00:13:27,760 --> 00:13:31,160 Speaker 1: that's all I'm trying to say. Man, generally speaking, black 227 00:13:31,200 --> 00:13:33,640 Speaker 1: bears do not reuse den sights. And this the super 228 00:13:33,720 --> 00:13:36,000 Speaker 1: Saudi asked about is a really interesting example of this 229 00:13:36,160 --> 00:13:41,440 Speaker 1: because she denned in the same like hundred yard by 230 00:13:41,559 --> 00:13:46,080 Speaker 1: hundred yard area, but shows different locations within this small 231 00:13:46,200 --> 00:13:49,560 Speaker 1: footprint during the years that I found. You're worried about 232 00:13:49,720 --> 00:13:52,880 Speaker 1: disease transmission of some sort. I don't know. I don't know. 233 00:13:53,000 --> 00:13:55,920 Speaker 1: Maybe it's who knows. Man, Trying to get into the 234 00:13:55,960 --> 00:13:57,480 Speaker 1: mind of a bear is what we're doing here, and 235 00:13:57,559 --> 00:13:59,960 Speaker 1: I think it's But I don't like. Yeah, it's an 236 00:14:00,200 --> 00:14:03,120 Speaker 1: when you're talking about like why things do things, why 237 00:14:03,160 --> 00:14:05,640 Speaker 1: animals do things, A lot of people say, like, for instance, 238 00:14:05,679 --> 00:14:08,280 Speaker 1: the r day, my friend Heart, he's got a bear 239 00:14:08,440 --> 00:14:12,719 Speaker 1: that comes back to the same he's convinced it's the 240 00:14:12,800 --> 00:14:16,040 Speaker 1: same bear. Yeah, And I don't think I said, like, 241 00:14:16,360 --> 00:14:18,760 Speaker 1: never has a bear done this. I'm not taking your task. 242 00:14:18,800 --> 00:14:21,040 Speaker 1: I'm just I'm just asking a point. I like it. 243 00:14:21,200 --> 00:14:24,160 Speaker 1: I like it. Um And then knowing thing people do 244 00:14:24,560 --> 00:14:27,320 Speaker 1: and I do it all the time, is you'll say, 245 00:14:28,720 --> 00:14:32,000 Speaker 1: let me give an example. I was yesterday admiring some 246 00:14:32,160 --> 00:14:36,760 Speaker 1: turkeys that we shot on our turkey hunt. It's a 247 00:14:36,880 --> 00:14:39,800 Speaker 1: Miriam's turkey, and a Miriam's turkey has a lot of 248 00:14:39,960 --> 00:14:42,840 Speaker 1: white on the end of their feathers. I was saying, 249 00:14:42,920 --> 00:14:49,000 Speaker 1: I wonder if that has to do with heat reducing 250 00:14:49,160 --> 00:14:51,800 Speaker 1: how many how much radiant surface because it's a it's 251 00:14:51,800 --> 00:14:56,120 Speaker 1: an animal from the southwest, very intense sun. An Eastern 252 00:14:56,200 --> 00:14:58,760 Speaker 1: turkey has a lot of black on it. Maybe these 253 00:14:58,800 --> 00:15:02,000 Speaker 1: turkeys have a lot more white on them as an 254 00:15:02,040 --> 00:15:05,200 Speaker 1: adaptive advantage about radiant heat, Like maybe that's a problem 255 00:15:05,560 --> 00:15:09,440 Speaker 1: getting too hot. So I think that when you look 256 00:15:09,440 --> 00:15:12,920 Speaker 1: at stuff you be you'd say, like you, I can't 257 00:15:12,960 --> 00:15:16,720 Speaker 1: say that that's why those turkeys evolved that what you 258 00:15:16,760 --> 00:15:18,720 Speaker 1: could not pillage, But what would you call it? I'd 259 00:15:18,760 --> 00:15:21,120 Speaker 1: call it that. Okay, I can't say that's why those 260 00:15:21,160 --> 00:15:24,440 Speaker 1: turkeys evolved that pellage, but I could say that could 261 00:15:24,480 --> 00:15:27,520 Speaker 1: be something to do with it, or that it could 262 00:15:27,600 --> 00:15:31,760 Speaker 1: have that effect in reducing radiant heat. So, but I 263 00:15:31,840 --> 00:15:34,200 Speaker 1: find talking to scientists like yourself, I'll be like, oh, 264 00:15:34,360 --> 00:15:37,480 Speaker 1: do they do it. Do the bears not want to 265 00:15:37,560 --> 00:15:41,080 Speaker 1: go back, maybe because of mits or some kind of 266 00:15:41,120 --> 00:15:44,840 Speaker 1: thing like that. I know you don't know all the way, 267 00:15:45,360 --> 00:15:49,760 Speaker 1: but is that a reasonable Yes, it's a reasonable idea. 268 00:15:49,960 --> 00:15:53,160 Speaker 1: It's a reasonable idea. It will be another reasonable idea 269 00:15:54,320 --> 00:15:56,680 Speaker 1: maybe to be unpredictable. You know, if they've got a 270 00:15:56,760 --> 00:15:59,560 Speaker 1: den that has been there on the ground for X 271 00:15:59,680 --> 00:16:03,280 Speaker 1: number of months and a certain number of animals have 272 00:16:03,440 --> 00:16:06,240 Speaker 1: encountered that den and become aware of its existence, then 273 00:16:06,280 --> 00:16:10,560 Speaker 1: there might be some adaptive advantage to moving locations, you know, 274 00:16:11,120 --> 00:16:19,000 Speaker 1: especially if you have those extremely altricial cubs to look after. Um. 275 00:16:20,120 --> 00:16:23,960 Speaker 1: You know, basically the onus is entirely on a mother 276 00:16:24,040 --> 00:16:27,520 Speaker 1: bear to make sure those cubs get to the point 277 00:16:27,560 --> 00:16:30,400 Speaker 1: where they can climb a tree. And they've got a 278 00:16:30,480 --> 00:16:34,880 Speaker 1: long road to ho from the time they're born before 279 00:16:34,920 --> 00:16:36,680 Speaker 1: they're to that point, because they're born in the middle 280 00:16:36,680 --> 00:16:39,000 Speaker 1: of the winter, right, Yeah, that's right, like February March 281 00:16:39,120 --> 00:16:42,120 Speaker 1: or something like that. Yeah, late January, yep. And then 282 00:16:42,320 --> 00:16:43,960 Speaker 1: like I said, you know, when when they're born, they're 283 00:16:43,960 --> 00:16:46,480 Speaker 1: they're tiny, and by the time they're coming out of 284 00:16:46,520 --> 00:16:49,680 Speaker 1: the den, they've gone from being you know, like something 285 00:16:49,720 --> 00:16:51,480 Speaker 1: you hold in the palm in your hand to be 286 00:16:51,600 --> 00:16:55,160 Speaker 1: in something that's four or five, six, maybe seven pounds, 287 00:16:56,080 --> 00:17:00,720 Speaker 1: And so the mother has she's got to bring all 288 00:17:00,840 --> 00:17:05,280 Speaker 1: that all those calories, all that energy into the den 289 00:17:05,400 --> 00:17:09,760 Speaker 1: with her both to maintain that pregnancy, deliver the cubs, 290 00:17:10,400 --> 00:17:14,119 Speaker 1: and then provide enough nutrition through her milk to get 291 00:17:14,200 --> 00:17:16,280 Speaker 1: him to the point where when they emerge from the den, 292 00:17:17,440 --> 00:17:20,720 Speaker 1: she can wolf at them and they're ready to climb, 293 00:17:21,320 --> 00:17:24,400 Speaker 1: because once they leave the den, you know, she's she's 294 00:17:24,760 --> 00:17:29,400 Speaker 1: not in a position to just protect them the way 295 00:17:29,480 --> 00:17:32,240 Speaker 1: she can while they're they're all bawled up in a pilot, dogs, 296 00:17:32,240 --> 00:17:35,840 Speaker 1: other bears, all manner of things. Yeah, definitely. So that's 297 00:17:36,240 --> 00:17:39,920 Speaker 1: you covered on everything so far. No, man, I'm sharp, 298 00:17:40,280 --> 00:17:45,080 Speaker 1: I am sharp. I'm good. It is fascinating stuff. And 299 00:17:45,160 --> 00:17:47,320 Speaker 1: by the way, one of the highlights of this week 300 00:17:47,960 --> 00:17:50,040 Speaker 1: turkey hunting. Yea, you guys almost got killed by bear. No, 301 00:17:50,160 --> 00:17:55,240 Speaker 1: we didn't almost. We had to bear encounters this week though. Um. 302 00:17:56,000 --> 00:17:58,920 Speaker 1: The first one was going out trying to locate some 303 00:17:59,000 --> 00:18:02,080 Speaker 1: birds in the evening and I heard what sounded like 304 00:18:02,320 --> 00:18:06,000 Speaker 1: a cub kind of bowling down the hill from us, 305 00:18:06,560 --> 00:18:08,240 Speaker 1: and then a bunch of claw marks on a tree 306 00:18:09,000 --> 00:18:11,200 Speaker 1: and then what had to have been the sow popping 307 00:18:11,240 --> 00:18:15,080 Speaker 1: her teeth, and given how late it was in the day, 308 00:18:15,200 --> 00:18:17,240 Speaker 1: I decided not to take the shotgun with me. I 309 00:18:17,320 --> 00:18:18,639 Speaker 1: was just kind of strolling up the hill, and when 310 00:18:18,680 --> 00:18:20,080 Speaker 1: I heard that sow pop in her teeth, I was like, 311 00:18:20,280 --> 00:18:24,240 Speaker 1: let's let's take this other direction. And then, uh, what 312 00:18:24,440 --> 00:18:27,960 Speaker 1: was even a cooler sighting was um as yesterday morning 313 00:18:28,040 --> 00:18:30,680 Speaker 1: man saw that the biggest bear I've seen since coming 314 00:18:30,720 --> 00:18:34,400 Speaker 1: to New Mexico. And it was also the blondest bear, 315 00:18:34,600 --> 00:18:38,520 Speaker 1: this great big boar, and UH had him while I 316 00:18:38,560 --> 00:18:40,720 Speaker 1: was putting a decoy in the ground and heard a 317 00:18:40,760 --> 00:18:43,320 Speaker 1: twig pop and looked over and he was no more 318 00:18:43,359 --> 00:18:45,359 Speaker 1: than seventy yards away looking at me through the trees, 319 00:18:45,440 --> 00:18:47,520 Speaker 1: and he was just beautiful. And then we we set 320 00:18:47,600 --> 00:18:49,080 Speaker 1: up a couple more times, and he came back in 321 00:18:49,200 --> 00:18:50,639 Speaker 1: to check us out, and he was woofing at us 322 00:18:50,640 --> 00:18:52,840 Speaker 1: from up the hill, so we all got a good 323 00:18:52,840 --> 00:18:54,600 Speaker 1: look at him. Is just a beautiful animal man there, 324 00:18:54,640 --> 00:18:57,680 Speaker 1: And you're getting a lot of bear vocalizations, which is usual. Yeah, 325 00:18:58,480 --> 00:19:01,960 Speaker 1: that's true. You know, I was telling you I one 326 00:19:02,000 --> 00:19:06,280 Speaker 1: time was hand calling to a tom to a gobbler 327 00:19:06,880 --> 00:19:11,960 Speaker 1: and heard an exhale over my shoulder, like how someone 328 00:19:11,960 --> 00:19:13,400 Speaker 1: would do, like they're a little bit tired from walking 329 00:19:13,440 --> 00:19:16,000 Speaker 1: up a hill. And it was a bear, I mean 330 00:19:16,760 --> 00:19:20,760 Speaker 1: arms distance that that would be an exaggeration, extremely clear 331 00:19:20,880 --> 00:19:23,480 Speaker 1: enough where I could like, I could hear it breathe. 332 00:19:24,160 --> 00:19:26,919 Speaker 1: He's coming to kill that hand When I turned around, Man, 333 00:19:26,960 --> 00:19:32,640 Speaker 1: it's scared the ship out of him. Scared. He freaked out. Yeah, 334 00:19:33,040 --> 00:19:35,439 Speaker 1: he did not like that man. Yeah, and that big 335 00:19:35,480 --> 00:19:37,480 Speaker 1: one yesterday when he first saw me, he went part 336 00:19:37,560 --> 00:19:39,920 Speaker 1: way up a tree and decided that wasn't his best 337 00:19:40,160 --> 00:19:43,480 Speaker 1: course of defense. Came back down the tree, making so 338 00:19:43,680 --> 00:19:46,840 Speaker 1: much noise, breaking big branches, claws scraping on the side 339 00:19:46,880 --> 00:19:49,480 Speaker 1: of the tree, and then tore off up the mountain. 340 00:19:50,000 --> 00:19:51,920 Speaker 1: And it surprised me that he came back in to 341 00:19:52,040 --> 00:19:53,639 Speaker 1: check us out when we were calling again. So I 342 00:19:53,680 --> 00:19:55,639 Speaker 1: don't know if the turkey he went and got pumped up. 343 00:19:56,000 --> 00:19:59,000 Speaker 1: Maybe he's like, come on, dude, your whole life he's 344 00:19:59,040 --> 00:20:03,520 Speaker 1: been running, Go down there. You've got that guy. But 345 00:20:03,560 --> 00:20:06,560 Speaker 1: at least two and a half bills. It was an 346 00:20:06,560 --> 00:20:10,440 Speaker 1: awesome animal. Man Okay, Wisconsin, Supersouth, Okay, Wisconsin. Super south. 347 00:20:10,520 --> 00:20:13,119 Speaker 1: So aside from the fact that she came back to 348 00:20:13,280 --> 00:20:17,359 Speaker 1: the same general need, I needed more background. Okay, how 349 00:20:17,400 --> 00:20:19,960 Speaker 1: many bear dance have you dug up? I would have 350 00:20:20,040 --> 00:20:22,600 Speaker 1: to look at my notebook to give you an answer. 351 00:20:22,760 --> 00:20:30,440 Speaker 1: I would say, oh, gosh, in the neighborhood of lady 352 00:20:30,480 --> 00:20:34,160 Speaker 1: to fifty dans something like that that I've been or everybody. 353 00:20:34,960 --> 00:20:36,600 Speaker 1: So I should give you a little more context on 354 00:20:36,680 --> 00:20:40,640 Speaker 1: the research projects. We're interested in. This expansion of black 355 00:20:40,720 --> 00:20:44,639 Speaker 1: bears south in their range, so individuals moving farther and 356 00:20:44,720 --> 00:20:46,800 Speaker 1: farther south. And as you know from all the other 357 00:20:46,880 --> 00:20:50,359 Speaker 1: species that show up in crazy places like mountain lions 358 00:20:50,400 --> 00:20:53,560 Speaker 1: showing up in New York State. You know these critters 359 00:20:53,640 --> 00:20:59,040 Speaker 1: that go hundreds of miles. Typically it's these young males 360 00:20:59,600 --> 00:21:02,760 Speaker 1: disperse sing that go great distances. So I was really 361 00:21:02,800 --> 00:21:05,840 Speaker 1: interested in looking at the dispersal behavior of black bears. 362 00:21:06,280 --> 00:21:09,399 Speaker 1: So what I needed for that research project was to 363 00:21:09,520 --> 00:21:15,159 Speaker 1: get GPS collars on yearling bears and a little bit 364 00:21:15,240 --> 00:21:17,280 Speaker 1: more about the biology of the species. Got you, I 365 00:21:17,359 --> 00:21:21,359 Speaker 1: got you. So born in the den, they get up 366 00:21:21,400 --> 00:21:24,160 Speaker 1: to let's say five pounds, come out of the den 367 00:21:24,400 --> 00:21:28,320 Speaker 1: with mom in the spring, keep growing still really dependent 368 00:21:28,359 --> 00:21:33,000 Speaker 1: on mom for their defense. Spend that whole spring, summer, fall, 369 00:21:34,040 --> 00:21:38,200 Speaker 1: buy mom's side, side like insight of mom or in 370 00:21:38,359 --> 00:21:42,000 Speaker 1: sound range of mom. And if something's going wrong, all 371 00:21:42,080 --> 00:21:43,680 Speaker 1: that mother bear has to do is give a wolf, 372 00:21:44,560 --> 00:21:46,399 Speaker 1: and the cubs know they've got to get up the 373 00:21:46,440 --> 00:21:50,000 Speaker 1: nearest tree. So what a lot of people don't know 374 00:21:50,560 --> 00:21:54,840 Speaker 1: is that when that second winner comes around, now you've 375 00:21:54,880 --> 00:21:59,240 Speaker 1: got Mama bear and a bunch of you know, we 376 00:21:59,320 --> 00:22:01,240 Speaker 1: call them year things, but they're less than a year old. 377 00:22:01,480 --> 00:22:04,120 Speaker 1: They're just about to complete their first year. They all 378 00:22:04,280 --> 00:22:07,840 Speaker 1: den up together again, so you'll have a beared end 379 00:22:08,080 --> 00:22:11,320 Speaker 1: that might have let's say a sow that weighs two 380 00:22:11,800 --> 00:22:15,960 Speaker 1: thirty pounds, and then she's got x number of one 381 00:22:16,040 --> 00:22:19,359 Speaker 1: year old cubs, some of which might weigh as much 382 00:22:19,359 --> 00:22:23,399 Speaker 1: as a hundred pounds themselves, all piled up together. So 383 00:22:23,600 --> 00:22:28,080 Speaker 1: it could be a huge like biomass of bear in 384 00:22:28,160 --> 00:22:30,680 Speaker 1: a heap, and they're sorting it all out. And and 385 00:22:31,000 --> 00:22:33,600 Speaker 1: especially if they're underground, you know, so I mentioned I 386 00:22:33,720 --> 00:22:36,439 Speaker 1: described this this polsyringe that you used to sedate the bears. 387 00:22:37,480 --> 00:22:39,760 Speaker 1: And if they're underground, you know, you've got like a 388 00:22:39,840 --> 00:22:41,520 Speaker 1: head lamp and you're looking in there and it's a 389 00:22:41,600 --> 00:22:44,959 Speaker 1: dark hole and a dark animal and they're the way 390 00:22:45,000 --> 00:22:47,480 Speaker 1: that they're piled up, it's like super spooning. It's like 391 00:22:48,320 --> 00:22:52,600 Speaker 1: a tangled mass of limbs and heads and trying to 392 00:22:52,640 --> 00:22:55,359 Speaker 1: figure out where one bear ends and another bear begins. 393 00:22:55,440 --> 00:22:56,959 Speaker 1: And you don't even know how many bears there are 394 00:22:57,080 --> 00:22:59,159 Speaker 1: down in the hole. Like when our kids crawling with 395 00:22:59,240 --> 00:23:01,840 Speaker 1: me and my wife, man, yeah, just wake up. It's hard. 396 00:23:01,920 --> 00:23:03,760 Speaker 1: You can't get out. So you're like, is that is 397 00:23:03,840 --> 00:23:08,119 Speaker 1: that Steve's thigh or you know, you have no idea, 398 00:23:08,280 --> 00:23:11,880 Speaker 1: so it can. It was, and it is a nerve 399 00:23:12,000 --> 00:23:14,639 Speaker 1: racking thing at first to intentionally go up to a 400 00:23:14,720 --> 00:23:19,080 Speaker 1: den and try to sedate these animals. And you got 401 00:23:19,160 --> 00:23:21,560 Speaker 1: to sedate the cubs too. You have to sedate the 402 00:23:21,600 --> 00:23:26,480 Speaker 1: cubs when they're in that second winter when well, yeah, 403 00:23:26,840 --> 00:23:29,880 Speaker 1: and they're you know, hundred pounds, Yeah, and they don't 404 00:23:29,920 --> 00:23:32,040 Speaker 1: know what's going on. They want to get away, and 405 00:23:32,119 --> 00:23:33,960 Speaker 1: you don't want to. You don't want to fracture that 406 00:23:34,080 --> 00:23:36,159 Speaker 1: family in a prematurely either, So you want to get 407 00:23:36,200 --> 00:23:39,359 Speaker 1: everybody sedated and then you because you don't want one 408 00:23:39,400 --> 00:23:42,840 Speaker 1: to run off. Yeah, and yeah, and that can happen. 409 00:23:42,920 --> 00:23:45,280 Speaker 1: You can have individuals that you know, try to make 410 00:23:45,320 --> 00:23:50,119 Speaker 1: a getaway. So that's what I'm talking about when I 411 00:23:50,160 --> 00:23:52,320 Speaker 1: say working up a den, going into sedate um and 412 00:23:52,359 --> 00:23:57,720 Speaker 1: then you're getting measurements, you're taking um blood samples. You know, 413 00:23:57,760 --> 00:24:00,639 Speaker 1: there are other research projects people were looking at a 414 00:24:00,720 --> 00:24:04,000 Speaker 1: variety of other topics with respect of these bears, and 415 00:24:04,960 --> 00:24:08,119 Speaker 1: one of the projects they're interested in in milk. In 416 00:24:08,480 --> 00:24:10,600 Speaker 1: in the bare milk, And I mentioned to you the 417 00:24:10,680 --> 00:24:14,440 Speaker 1: fat content of bare milk, and we segued several different 418 00:24:14,480 --> 00:24:17,560 Speaker 1: times since then, but I wanted to mention on several 419 00:24:17,600 --> 00:24:21,160 Speaker 1: occasions I've had bare milk on my hands when I'm 420 00:24:21,160 --> 00:24:25,400 Speaker 1: doing this in the winter, and obviously it's gone from 421 00:24:25,760 --> 00:24:30,680 Speaker 1: bare body temperature out to wintertime temperature, and it's almost 422 00:24:30,800 --> 00:24:34,439 Speaker 1: instantaneous that it turns into a solid and you can 423 00:24:34,520 --> 00:24:37,159 Speaker 1: smear it between your fingers and it feels it feels 424 00:24:37,200 --> 00:24:39,480 Speaker 1: like butter. I mean it, it's so it's got so 425 00:24:39,640 --> 00:24:42,080 Speaker 1: much fat in it that the second you take it 426 00:24:42,119 --> 00:24:45,560 Speaker 1: away from that that body heat from the mother, it 427 00:24:45,640 --> 00:24:48,640 Speaker 1: turns into a solid. And obviously for the cubs, that's 428 00:24:48,640 --> 00:24:51,040 Speaker 1: just going straight from bare body temperature to bare body 429 00:24:51,080 --> 00:24:53,719 Speaker 1: temperature inside the cup's mouth while it's ingested, but if 430 00:24:53,760 --> 00:24:55,320 Speaker 1: it gets out in that winter air, it is like 431 00:24:55,400 --> 00:24:59,840 Speaker 1: a solid material, so pretty fascinating stuff. So those cubs 432 00:24:59,840 --> 00:25:03,480 Speaker 1: are not a ton of weight. And the number of 433 00:25:04,359 --> 00:25:07,320 Speaker 1: offspring that a single sow has in a given year 434 00:25:08,280 --> 00:25:11,320 Speaker 1: is linked directly to her body condition. So a bear 435 00:25:11,440 --> 00:25:14,680 Speaker 1: that goes into the den in good condition will have 436 00:25:14,920 --> 00:25:16,960 Speaker 1: more cubs than a bear that goes into a den 437 00:25:17,400 --> 00:25:19,119 Speaker 1: in poor condition. And one of the ways that this 438 00:25:19,280 --> 00:25:23,800 Speaker 1: is controlled is that black bears have what's called delayed implantation, 439 00:25:24,280 --> 00:25:27,440 Speaker 1: so they get pregnant and these little fertilized eggs just 440 00:25:27,520 --> 00:25:29,200 Speaker 1: kind of float around in the womb for a little 441 00:25:29,200 --> 00:25:33,800 Speaker 1: while and then when the time is right. The body 442 00:25:34,400 --> 00:25:37,200 Speaker 1: is communicating to the brain what kind of condition it's in. 443 00:25:37,440 --> 00:25:41,440 Speaker 1: And there are a variety of chemical uh interactions that 444 00:25:42,800 --> 00:25:45,879 Speaker 1: scientists believe drive this relationship. One of one of the 445 00:25:45,960 --> 00:25:51,680 Speaker 1: keys is likely to be uh lepton, which is in 446 00:25:51,840 --> 00:25:57,240 Speaker 1: circulation in a in an amount proportional to body fat. 447 00:25:58,240 --> 00:26:01,280 Speaker 1: So a really fat bear, it body is telling its brain, 448 00:26:01,800 --> 00:26:04,400 Speaker 1: I'm in really good shape. It's brains telling its body 449 00:26:04,600 --> 00:26:08,160 Speaker 1: we should be having more cubs than in a poor year, 450 00:26:09,240 --> 00:26:14,879 Speaker 1: and more of those fertilized embryos will implant into the 451 00:26:15,000 --> 00:26:17,800 Speaker 1: uterus wall and turn into cubs. You can you imagine 452 00:26:17,920 --> 00:26:22,879 Speaker 1: humans had delayed implantation, the implications at half I'm imagining it. 453 00:26:23,000 --> 00:26:25,479 Speaker 1: We still be My wife is still have three floating 454 00:26:25,480 --> 00:26:28,680 Speaker 1: in there. They're like no, not quite yet, Like no 455 00:26:28,720 --> 00:26:32,680 Speaker 1: one are there, but not quite Yeah, So it's pretty 456 00:26:32,720 --> 00:26:35,720 Speaker 1: It's it's amazing stuff, man, animal kingdom. What's the maximum? 457 00:26:36,680 --> 00:26:39,600 Speaker 1: When you say that, how many does she have in reserve? Like? 458 00:26:39,680 --> 00:26:42,040 Speaker 1: How many could she have? That's it's a great question, 459 00:26:42,119 --> 00:26:44,159 Speaker 1: and I don't know the answer to it, but I 460 00:26:44,200 --> 00:26:47,840 Speaker 1: can tell you that in the literature there are very 461 00:26:48,040 --> 00:26:51,919 Speaker 1: very few instances where six cubs have been documented. Being 462 00:26:51,960 --> 00:26:54,399 Speaker 1: born to a single mother in a given year seems 463 00:26:54,400 --> 00:26:56,840 Speaker 1: to be about the mass six is like, you know, 464 00:26:58,119 --> 00:27:00,760 Speaker 1: like the less than once in a blue moon number. 465 00:27:01,080 --> 00:27:04,119 Speaker 1: What's the national average? Two to three is really common? 466 00:27:04,760 --> 00:27:07,520 Speaker 1: Two to three is really common? And imagine you know, 467 00:27:07,560 --> 00:27:09,920 Speaker 1: you asked about a national average. Obviously, depending on where 468 00:27:09,920 --> 00:27:12,199 Speaker 1: you are on the map, you're gonna have different food resources, 469 00:27:12,600 --> 00:27:15,680 Speaker 1: and then even in a given location year to year, 470 00:27:15,720 --> 00:27:18,280 Speaker 1: it's highly variable. Think about you know, in a lot 471 00:27:18,320 --> 00:27:22,480 Speaker 1: of these systems acorn mast crop is a key driver. 472 00:27:23,359 --> 00:27:24,880 Speaker 1: So if you're in a place that's let's say, got 473 00:27:25,240 --> 00:27:27,080 Speaker 1: a lot of white oak and it's a massed year, 474 00:27:27,920 --> 00:27:30,960 Speaker 1: you should expect those Souths to have more fat and 475 00:27:31,080 --> 00:27:34,119 Speaker 1: more cubs. And when it's a massed poor year and 476 00:27:34,160 --> 00:27:38,760 Speaker 1: they're forced to some relatively inferior calorie, poor food source, 477 00:27:39,440 --> 00:27:43,440 Speaker 1: lower body condition for your cubs makes sense. Hold there 478 00:27:43,480 --> 00:27:47,280 Speaker 1: for a minute. Okay, Yehney, any questions. You're cool and 479 00:27:47,320 --> 00:27:49,479 Speaker 1: everything up to this point. I'm cool. I can tell 480 00:27:49,520 --> 00:27:51,040 Speaker 1: you that where there won't be a lot of cubs 481 00:27:51,080 --> 00:27:58,160 Speaker 1: come out of dentist here, and that's in Kentucky, Tennessee's straight. Yeah. 482 00:27:58,240 --> 00:28:02,480 Speaker 1: I am curious about the the hundred yard square, like 483 00:28:02,600 --> 00:28:05,840 Speaker 1: if that had a reason to it with the Superstown. 484 00:28:06,840 --> 00:28:08,960 Speaker 1: It's a it's like how many she dined? How many 485 00:28:09,000 --> 00:28:11,879 Speaker 1: times within a little chunker ground? Three times I visited 486 00:28:11,920 --> 00:28:14,439 Speaker 1: that sow in this little area. What were the three dens? 487 00:28:14,640 --> 00:28:17,280 Speaker 1: So two times? It was this interesting place. It was 488 00:28:17,359 --> 00:28:19,840 Speaker 1: on private property. The landowner gave his permission to do 489 00:28:19,880 --> 00:28:22,320 Speaker 1: the work. If I remember right, it was it was 490 00:28:23,800 --> 00:28:26,639 Speaker 1: the Pettis Farm was the name of this place. And 491 00:28:26,760 --> 00:28:29,360 Speaker 1: there were some stump piles there the farmer had cleared out, 492 00:28:29,600 --> 00:28:31,800 Speaker 1: you know, some egg fields and piled up a bunch 493 00:28:31,800 --> 00:28:34,480 Speaker 1: of stumps. So on two of those occasions, the sow 494 00:28:34,680 --> 00:28:35,960 Speaker 1: was in a stump pile, but it was not the 495 00:28:36,000 --> 00:28:38,600 Speaker 1: same stump pile, two separate stump piles. And then on 496 00:28:38,680 --> 00:28:41,480 Speaker 1: a third occasion occasion, she was above the ground and 497 00:28:41,880 --> 00:28:44,160 Speaker 1: close to those stump piles, just laying out, just laying 498 00:28:44,200 --> 00:28:47,400 Speaker 1: out with a pile of pile of yearlings. So how 499 00:28:47,480 --> 00:28:49,360 Speaker 1: in the world does that work? I don't know, man, 500 00:28:49,440 --> 00:28:51,920 Speaker 1: but I can tell you, like, like, how do they not? 501 00:28:52,520 --> 00:28:55,080 Speaker 1: So it's just laying there, like a dog could walk 502 00:28:55,200 --> 00:28:58,040 Speaker 1: up and start eating the young. If a dog walked 503 00:28:58,120 --> 00:29:00,440 Speaker 1: up and tried to start eating the young, it would 504 00:29:00,480 --> 00:29:02,800 Speaker 1: not go favorably for the day, even though she's in 505 00:29:02,880 --> 00:29:06,480 Speaker 1: a semi stupor state. Yes, and that's another sort of 506 00:29:06,560 --> 00:29:10,760 Speaker 1: misconception when you approach a den. And I should probably 507 00:29:11,720 --> 00:29:15,320 Speaker 1: have prefaced the conversation about so called working up den's 508 00:29:15,480 --> 00:29:19,040 Speaker 1: with a disclaimer like, no one if you find a 509 00:29:19,080 --> 00:29:21,160 Speaker 1: bear den should be messing with it. Just leave him alone. 510 00:29:21,240 --> 00:29:25,040 Speaker 1: Let them do their things. Now, when you come up 511 00:29:25,080 --> 00:29:27,200 Speaker 1: to a den, it's not like the bear is laying 512 00:29:27,240 --> 00:29:31,000 Speaker 1: there in suspended animation, oblivious to your presence. The vast 513 00:29:31,080 --> 00:29:33,440 Speaker 1: majority of the time when I would get to the 514 00:29:33,520 --> 00:29:36,239 Speaker 1: point of trying to figure out how many bears are 515 00:29:36,280 --> 00:29:38,239 Speaker 1: in the den, is it is, you know, the den 516 00:29:38,320 --> 00:29:41,400 Speaker 1: above ground or below ground. By the time I found 517 00:29:41,440 --> 00:29:43,960 Speaker 1: that the location and was looking at the bear, the 518 00:29:44,040 --> 00:29:46,320 Speaker 1: bear was aware of my presence and looking back at 519 00:29:46,400 --> 00:29:52,080 Speaker 1: me sometimes but aware. It's not like they're you know, 520 00:29:53,720 --> 00:29:58,040 Speaker 1: completely sedated already and you just walk up and give 521 00:29:58,080 --> 00:30:01,200 Speaker 1: a sleeping bear a shot. They know you're there. And 522 00:30:02,040 --> 00:30:05,200 Speaker 1: the speed at which they can go from being in 523 00:30:05,320 --> 00:30:11,560 Speaker 1: this metabolically um slow state to just being like with 524 00:30:11,760 --> 00:30:15,520 Speaker 1: it and running away, you know, it is remarkable. I 525 00:30:15,560 --> 00:30:18,360 Speaker 1: mean they can they can go from idol or sub 526 00:30:18,440 --> 00:30:21,480 Speaker 1: idol speed to full RPMs in a matter of minutes. 527 00:30:21,800 --> 00:30:24,200 Speaker 1: It's really an amazing thing that their bodies can do. 528 00:30:24,920 --> 00:30:27,400 Speaker 1: That's like me in the morning before tricky hunt. He's 529 00:30:27,400 --> 00:30:29,560 Speaker 1: noticed that as long he's got some of that great 530 00:30:29,680 --> 00:30:35,239 Speaker 1: camp coffee. Before I can even think about getting up, 531 00:30:35,400 --> 00:30:38,560 Speaker 1: he's got the jet boils round and everything's happening. You guys, run, 532 00:30:40,400 --> 00:30:42,200 Speaker 1: You guys are in a tight ship. Chris, are you cool? 533 00:30:42,240 --> 00:30:45,160 Speaker 1: And everything. Yeah, Actually I do have a question. Um, 534 00:30:46,280 --> 00:30:52,560 Speaker 1: so averages two to three cubs per per litter per letter? 535 00:30:53,200 --> 00:30:56,840 Speaker 1: How many cubs? Like, how many litters can a bear 536 00:30:56,960 --> 00:31:00,080 Speaker 1: have in her lifetime? Is it just one? Or is it? 537 00:31:00,600 --> 00:31:03,360 Speaker 1: That depends on one key variable, which is how long 538 00:31:03,480 --> 00:31:06,800 Speaker 1: she lives? So they can't. They don't do it every year, 539 00:31:06,840 --> 00:31:10,080 Speaker 1: though they do. That's exactly well typically, that's right. Yeah, 540 00:31:10,160 --> 00:31:13,440 Speaker 1: so bear in mind again those cubs are born. Let's 541 00:31:13,480 --> 00:31:16,680 Speaker 1: say year one, the cubs are born, mama's got that 542 00:31:16,800 --> 00:31:20,680 Speaker 1: responsibility for a year two, right, she's denning with them again, 543 00:31:21,480 --> 00:31:23,320 Speaker 1: so she can't give birth to a new letter and 544 00:31:23,520 --> 00:31:26,120 Speaker 1: care for last year's litter. So that's why there's this 545 00:31:26,680 --> 00:31:30,000 Speaker 1: cycle where it's a litter and then it's rearing last 546 00:31:30,080 --> 00:31:32,400 Speaker 1: year's litter and then they're gone, and then it's a 547 00:31:32,480 --> 00:31:35,400 Speaker 1: litter and it's rearing that litter and then they're gone. 548 00:31:35,480 --> 00:31:38,040 Speaker 1: How old are they when he becomes sextually mature. It 549 00:31:38,160 --> 00:31:40,880 Speaker 1: depends on diet, But you can have bears that are 550 00:31:40,920 --> 00:31:45,520 Speaker 1: reproducing at two years of age. Yep, So they're not 551 00:31:45,680 --> 00:31:49,000 Speaker 1: they're they're not doing is that many times? Well, he 552 00:31:49,040 --> 00:31:52,080 Speaker 1: could have a black bear boar one time they aged 553 00:31:52,120 --> 00:31:54,200 Speaker 1: at seventeen not accurate that they can get I mean 554 00:31:54,280 --> 00:31:56,240 Speaker 1: they can live into their twenties. It depends, you know. 555 00:31:56,320 --> 00:32:01,440 Speaker 1: The biggest thing is is uh, honestly, how how hard 556 00:32:01,520 --> 00:32:06,040 Speaker 1: hunted the population is. That's like the leading cause mortality. Ye, 557 00:32:06,560 --> 00:32:08,280 Speaker 1: but you could you could you know in a in 558 00:32:08,360 --> 00:32:14,480 Speaker 1: a situation where a sow has avoided predation and made 559 00:32:14,520 --> 00:32:17,760 Speaker 1: it to her twenties, she might have had eight litters 560 00:32:18,640 --> 00:32:21,800 Speaker 1: nine litters, so they can crank out a bunch. Now 561 00:32:21,880 --> 00:32:26,520 Speaker 1: this style that I'm talking about, the super I named 562 00:32:26,560 --> 00:32:34,160 Speaker 1: her that because she perfect perfect. I'm a fan of alliteration, 563 00:32:34,280 --> 00:32:36,800 Speaker 1: so it kind of has a ring to it. Um. 564 00:32:37,720 --> 00:32:41,560 Speaker 1: She really stood out because I mentioned that A visit 565 00:32:41,600 --> 00:32:44,960 Speaker 1: her three times. The first year I visited her, she 566 00:32:45,040 --> 00:32:47,320 Speaker 1: had five cups, which was noteworthy in and of itself. 567 00:32:47,400 --> 00:32:53,520 Speaker 1: She's the only bear during my research project with five cubs. Ever, 568 00:32:55,480 --> 00:32:57,000 Speaker 1: that's a good question. I'd have to look at my 569 00:32:57,040 --> 00:32:59,840 Speaker 1: notes again on that. But she wasn't She was not 570 00:33:00,080 --> 00:33:02,560 Speaker 1: not like a monster, but she was in the neighborhood 571 00:33:02,600 --> 00:33:05,600 Speaker 1: of two twenty somewhere in there, so not not like 572 00:33:05,760 --> 00:33:09,320 Speaker 1: holy cows. Would have read reread my paper on this 573 00:33:09,360 --> 00:33:10,960 Speaker 1: if I knew I was going to get all these questions, 574 00:33:11,040 --> 00:33:13,040 Speaker 1: but it's a it's a cool topic, for sure. So 575 00:33:13,600 --> 00:33:15,840 Speaker 1: let's say she was in the neighborhood of two pounds. 576 00:33:15,920 --> 00:33:19,280 Speaker 1: All right, she has five cups. That's big, but not extraordinary. 577 00:33:19,680 --> 00:33:22,840 Speaker 1: It's a good, a nice, big, sell healthy cell. So 578 00:33:22,920 --> 00:33:26,600 Speaker 1: she's got these five cups the first first time I've 579 00:33:26,640 --> 00:33:29,160 Speaker 1: seen that, really cool deal. And so I'm looking at 580 00:33:29,200 --> 00:33:30,960 Speaker 1: it from the standpoint of, all right, here are five 581 00:33:31,080 --> 00:33:33,880 Speaker 1: cubs now. But next year I can come back and 582 00:33:33,920 --> 00:33:37,640 Speaker 1: I'll have five year links for my research project. Because 583 00:33:37,680 --> 00:33:40,800 Speaker 1: then when their yearlings and they emerge from the den, 584 00:33:41,400 --> 00:33:44,800 Speaker 1: that's when the family unit splinters, all right, breaks up, 585 00:33:45,840 --> 00:33:49,360 Speaker 1: And oftentimes that coincides with the spring breeding season, so 586 00:33:49,440 --> 00:33:51,960 Speaker 1: the males are starting to chase mom around. The yearlings 587 00:33:52,000 --> 00:33:55,600 Speaker 1: don't want to be in the neighborhood anymore. Mom isn't 588 00:33:55,720 --> 00:33:58,840 Speaker 1: caring for him anymore, and the females will typically go 589 00:33:59,400 --> 00:34:02,600 Speaker 1: a relative short distance when they disperse. Sometimes their home 590 00:34:02,720 --> 00:34:04,880 Speaker 1: ranges as adults will even overlap a little bit with 591 00:34:04,920 --> 00:34:08,320 Speaker 1: the home range of their mothers, and those young males 592 00:34:08,640 --> 00:34:12,760 Speaker 1: can go phenomenal distances like on the order of tens 593 00:34:12,800 --> 00:34:15,279 Speaker 1: to hundreds of miles they'll cover and then set up 594 00:34:15,320 --> 00:34:21,920 Speaker 1: shop in a new place. So I've got five bears 595 00:34:22,160 --> 00:34:24,759 Speaker 1: that I'm hoping the following winter I'll be able to 596 00:34:24,800 --> 00:34:27,560 Speaker 1: put GPS colors on from my research probac slim that's 597 00:34:27,600 --> 00:34:30,399 Speaker 1: gonna happen. Yeah, she's good that they're all gonna live. Well, 598 00:34:30,640 --> 00:34:32,560 Speaker 1: I shouldn't say the odds are slim, because we actually 599 00:34:32,600 --> 00:34:37,680 Speaker 1: had pretty high survivorship of bears that we found as 600 00:34:37,760 --> 00:34:41,280 Speaker 1: cubs and then relocated as yearlings. Most of them survived, 601 00:34:42,200 --> 00:34:45,000 Speaker 1: but you know, you got your hands full with five 602 00:34:45,800 --> 00:34:48,600 Speaker 1: offspring to deal with. I come back to the den 603 00:34:48,719 --> 00:34:51,440 Speaker 1: the next year hoping to find five yearlings. There are 604 00:34:51,480 --> 00:34:53,560 Speaker 1: five yearlings. And not only are there five yearlings, but 605 00:34:53,600 --> 00:34:56,600 Speaker 1: they're big, like they've thrived. They've done really, really well. 606 00:34:57,600 --> 00:35:01,120 Speaker 1: What's big, like hundred pounds, So they've gone from five 607 00:35:01,160 --> 00:35:03,560 Speaker 1: pounds to hundred pounds in a year. And the males 608 00:35:03,560 --> 00:35:06,000 Speaker 1: were bigger than the females. The females, you know, seventy pounds. 609 00:35:06,640 --> 00:35:09,280 Speaker 1: So there's seven hundred pounds worth of bears. A pile 610 00:35:09,360 --> 00:35:12,879 Speaker 1: of bears, yes, seven hundred pound blob of black bears. 611 00:35:12,920 --> 00:35:15,000 Speaker 1: A heap of black bears, six of them yes, six 612 00:35:15,080 --> 00:35:18,520 Speaker 1: bears all piled up. That's incredible. So one of my 613 00:35:18,600 --> 00:35:23,320 Speaker 1: grad school colleagues, guy named Dave McFarland, who's a working 614 00:35:23,360 --> 00:35:26,640 Speaker 1: for the Wisconsin d NR now as a as an ecologist. 615 00:35:27,360 --> 00:35:32,600 Speaker 1: He and I were tasked with getting those bears handled 616 00:35:32,640 --> 00:35:37,880 Speaker 1: and collared, and those five became subjects of my research. 617 00:35:39,239 --> 00:35:42,799 Speaker 1: And then another year goes by and I go back 618 00:35:42,880 --> 00:35:46,359 Speaker 1: in to this same style. She's den in that same 619 00:35:46,400 --> 00:35:51,200 Speaker 1: general area, and she has five newborn cubs again, so 620 00:35:51,360 --> 00:35:58,279 Speaker 1: she has successive litters of quintuplets, and that's amazing in 621 00:35:58,400 --> 00:36:02,000 Speaker 1: and of itself. Furthermore, we weighed her that first year, 622 00:36:02,760 --> 00:36:06,000 Speaker 1: we waited the second year, we weighed her the third year, 623 00:36:06,600 --> 00:36:10,800 Speaker 1: and over the course of birthing and weaning those ten cubs, 624 00:36:11,960 --> 00:36:18,319 Speaker 1: she put on on the order of fifty pounds of weight, 625 00:36:18,800 --> 00:36:24,080 Speaker 1: gaining weight, gaining weight while cranking out calories like nobody's business. 626 00:36:24,840 --> 00:36:28,919 Speaker 1: So that's how she got the moniker of super cell. Yeah. 627 00:36:29,000 --> 00:36:31,640 Speaker 1: So back to back litters of quinn tuplets, I mean, 628 00:36:32,400 --> 00:36:35,440 Speaker 1: ten cubs over the span of three years. And then 629 00:36:35,560 --> 00:36:37,520 Speaker 1: I started getting stories to one of the one of 630 00:36:37,560 --> 00:36:41,359 Speaker 1: the coolest stories was from some Wisconsin Department of transportation 631 00:36:41,440 --> 00:36:46,480 Speaker 1: guys who had seen the sow with those five yearlings, 632 00:36:47,120 --> 00:36:49,759 Speaker 1: and they were going and scavenging deer carcasses that the 633 00:36:49,840 --> 00:36:52,840 Speaker 1: d O T guys had picked up and taken to 634 00:36:52,960 --> 00:36:55,440 Speaker 1: like a dump site. Secret. Well, that was part of 635 00:36:55,480 --> 00:36:57,239 Speaker 1: her secret. The other part of it was she was 636 00:36:57,360 --> 00:37:01,600 Speaker 1: living in this landscape where there's corn like corn and 637 00:37:02,320 --> 00:37:07,600 Speaker 1: oak forest and she's just translating all those calories into 638 00:37:07,680 --> 00:37:12,040 Speaker 1: bare biomass through her reproduction. But now did she do 639 00:37:12,120 --> 00:37:16,600 Speaker 1: it again? Though? So what she did again was rear 640 00:37:16,719 --> 00:37:19,800 Speaker 1: those five cubs to the point that they were yearlings 641 00:37:19,880 --> 00:37:23,640 Speaker 1: and dispersed, and at that point I was done tracking 642 00:37:24,040 --> 00:37:26,960 Speaker 1: that style. Did any of the ten that you watched 643 00:37:27,000 --> 00:37:33,600 Speaker 1: her bring to yearling hood? Did any go south? Yes? 644 00:37:34,360 --> 00:37:37,040 Speaker 1: What percent went south? So out of those out of 645 00:37:37,080 --> 00:37:39,560 Speaker 1: those ten specific cubs, I do not know the answer 646 00:37:39,640 --> 00:37:41,640 Speaker 1: to that, but I can tell you that there was 647 00:37:41,680 --> 00:37:47,520 Speaker 1: a statistically significant skewing of the data where the bears 648 00:37:47,600 --> 00:37:51,640 Speaker 1: were moving in a southerly and easterly direction from that 649 00:37:51,800 --> 00:37:55,480 Speaker 1: sort of central forest part of the state, like moving 650 00:37:55,880 --> 00:37:59,319 Speaker 1: initially or winding up, winding up, winding up, So they 651 00:37:59,360 --> 00:38:03,680 Speaker 1: were they were checking for territory and finding unoccupied locations. Yes, 652 00:38:03,880 --> 00:38:05,839 Speaker 1: that's certainly true. And I think one of the things 653 00:38:05,960 --> 00:38:08,440 Speaker 1: driving it was not only were they finding unoccupied locations, 654 00:38:09,080 --> 00:38:14,320 Speaker 1: but they were finding unoccupied locations with ad libitum, in 655 00:38:14,400 --> 00:38:20,000 Speaker 1: other words, unlimited food supply and no competition. And another 656 00:38:20,040 --> 00:38:22,560 Speaker 1: really cool thing that happened because these GPS collars, you know, 657 00:38:22,600 --> 00:38:25,879 Speaker 1: they've just revolutionized wildlife research because rather than going out 658 00:38:25,880 --> 00:38:27,840 Speaker 1: there with like an antenna and trying to locate the 659 00:38:27,960 --> 00:38:31,360 Speaker 1: radio signal, you're just getting thousands and thousands of locations. 660 00:38:32,200 --> 00:38:35,399 Speaker 1: And I had a handful of bears that made these 661 00:38:35,680 --> 00:38:40,000 Speaker 1: really interesting forays into totally new areas where they'd never 662 00:38:40,080 --> 00:38:45,040 Speaker 1: been before and distances of dozens, sometimes as much as 663 00:38:45,080 --> 00:38:47,759 Speaker 1: forty or fifty miles, And then they'd returned to the 664 00:38:47,800 --> 00:38:50,520 Speaker 1: area where they were born. And then they'd go back 665 00:38:50,560 --> 00:38:52,480 Speaker 1: to that place that they had explored and set up 666 00:38:52,480 --> 00:38:56,480 Speaker 1: shot there. Yeah, they come back to get their stuff. Well, 667 00:38:56,880 --> 00:38:58,600 Speaker 1: you know, I think it was like get their stuff 668 00:38:58,600 --> 00:39:01,200 Speaker 1: out of storage, you know, again trying to try to 669 00:39:01,280 --> 00:39:03,920 Speaker 1: get I got to go to store. You know, it's 670 00:39:03,920 --> 00:39:07,480 Speaker 1: try to find a spot if whatever he'son, come back 671 00:39:07,520 --> 00:39:10,359 Speaker 1: where they came from, and then go back to their spot. 672 00:39:10,560 --> 00:39:12,120 Speaker 1: Do you want to see some of these data points, 673 00:39:12,680 --> 00:39:14,879 Speaker 1: well I will buy me not right now, but i'd 674 00:39:14,920 --> 00:39:18,880 Speaker 1: love to. I looked at one time. We'll put some 675 00:39:19,040 --> 00:39:21,000 Speaker 1: if you want to share. We put somebody's up for 676 00:39:21,200 --> 00:39:23,480 Speaker 1: listeners to go check out. Because I also find this 677 00:39:23,600 --> 00:39:25,680 Speaker 1: link where I looked at one time how a wolverine 678 00:39:25,800 --> 00:39:28,640 Speaker 1: uses a mountain for a year, and it was just 679 00:39:28,920 --> 00:39:33,480 Speaker 1: his marks of all the places he went on a mountain, 680 00:39:33,920 --> 00:39:38,799 Speaker 1: which was looking at it. It seemed like very haphazard, 681 00:39:39,480 --> 00:39:41,520 Speaker 1: but probably made some kind of sense to him. Yeah, 682 00:39:41,760 --> 00:39:44,040 Speaker 1: you know, it's got to be a reason for it. Man. 683 00:39:44,120 --> 00:39:50,640 Speaker 1: So one pioneering bear, the Wisconsin super South, moves into 684 00:39:50,680 --> 00:39:54,000 Speaker 1: a new area semi new. Yeah, I mean she was 685 00:39:54,040 --> 00:39:56,000 Speaker 1: at the southern extent of what you consider like the 686 00:39:56,160 --> 00:39:58,240 Speaker 1: core bear range of the state, and in the course 687 00:39:58,480 --> 00:40:04,960 Speaker 1: of four years produces ten offspring weighing a hundred pounds. 688 00:40:06,640 --> 00:40:10,800 Speaker 1: Some of them move souphomore. So if you see a 689 00:40:10,840 --> 00:40:13,200 Speaker 1: bear your listeners show up in your neighborhood, think of Carl. 690 00:40:13,760 --> 00:40:18,640 Speaker 1: Yeah they're coming, Carl. You could go, you could do 691 00:40:18,760 --> 00:40:21,880 Speaker 1: your thoughts last Okay, yeah you can. Here's deal. You're 692 00:40:21,920 --> 00:40:24,080 Speaker 1: gonna have to come back on though. I'm down for that, 693 00:40:25,080 --> 00:40:27,000 Speaker 1: we don't even talk about what I was gonna talking about. 694 00:40:27,840 --> 00:40:35,920 Speaker 1: Let's we'll do it again, Johnny, I'll do my job here, 695 00:40:39,320 --> 00:40:49,680 Speaker 1: do you. Um yeah, it's kind of general broad but 696 00:40:50,239 --> 00:40:55,080 Speaker 1: I love the fact that we're doing like biology and 697 00:40:55,440 --> 00:40:59,239 Speaker 1: science equals hunting, Like that's just awesome for me. And 698 00:40:59,239 --> 00:41:00,560 Speaker 1: I hope we can can te you to do that 699 00:41:00,680 --> 00:41:03,680 Speaker 1: and have more biologists on but on the digital radio program, 700 00:41:03,800 --> 00:41:06,320 Speaker 1: on digital radio program. But yeah, man, I feel like 701 00:41:06,880 --> 00:41:12,160 Speaker 1: all hunters should be thinking, you know, with this mind frame, 702 00:41:12,239 --> 00:41:16,040 Speaker 1: you know, and and looking at it that way so advantageous. 703 00:41:16,080 --> 00:41:18,680 Speaker 1: I recently I gave a talk at a at a 704 00:41:18,800 --> 00:41:25,120 Speaker 1: thing and um, after I get this talk, well, as 705 00:41:25,160 --> 00:41:27,239 Speaker 1: I was preparing for my talk, I noticed my wife 706 00:41:27,320 --> 00:41:29,600 Speaker 1: for what she was doing. She was working on a project, 707 00:41:29,680 --> 00:41:31,839 Speaker 1: and she had a lot of unusual magazines around our house, 708 00:41:32,800 --> 00:41:34,680 Speaker 1: and I noticed that the big thing in magazine anyone 709 00:41:34,719 --> 00:41:37,120 Speaker 1: who stands in the checkout line, I'll see this. Everything's 710 00:41:37,200 --> 00:41:43,160 Speaker 1: like top you know, um, seven things to make for dinner, 711 00:41:44,040 --> 00:41:48,279 Speaker 1: or like forty nine ways to blow your man's mind 712 00:41:48,360 --> 00:41:50,640 Speaker 1: in bed, or like a hundred and one you know 713 00:41:50,680 --> 00:41:53,439 Speaker 1: what I mean. Like lists are big. And my wife 714 00:41:53,480 --> 00:41:56,839 Speaker 1: was even telling me that an odd numbered list does 715 00:41:56,960 --> 00:42:00,359 Speaker 1: better than an even numbered list. People when you say 716 00:42:00,400 --> 00:42:03,560 Speaker 1: top ten, people think they're being bullshitted. If you say eleven, 717 00:42:03,680 --> 00:42:09,640 Speaker 1: they're like, who, like why eleven? They want to read 718 00:42:09,680 --> 00:42:12,279 Speaker 1: it more so. Anyhow, at my end of my thing, 719 00:42:12,360 --> 00:42:15,000 Speaker 1: I had seven things that I think hunters should be doing, 720 00:42:16,000 --> 00:42:19,319 Speaker 1: and one of those seven was why not spend more 721 00:42:19,360 --> 00:42:24,120 Speaker 1: time learning about a college and biology, like from real places? 722 00:42:24,800 --> 00:42:27,200 Speaker 1: Do you know what I mean? Like, especially if you 723 00:42:27,280 --> 00:42:30,439 Speaker 1: can figure out how to read the abstracts of peer 724 00:42:30,520 --> 00:42:34,640 Speaker 1: reviewed wildlife journals, that if nothing else, you'd be a 725 00:42:34,680 --> 00:42:38,080 Speaker 1: better guy to talk to in the bar, because you'd 726 00:42:38,080 --> 00:42:39,440 Speaker 1: be like, you know what, you'd be you'd be the 727 00:42:39,520 --> 00:42:40,600 Speaker 1: kind of guy who gets to go like this. You'd 728 00:42:40,600 --> 00:42:42,120 Speaker 1: be saying, you know what, that's not how it works, 729 00:42:44,440 --> 00:42:47,680 Speaker 1: that's not exactly what happens. You're wrong. I read it 730 00:42:47,760 --> 00:42:51,120 Speaker 1: in a pure reviewed journal. Um is that if you're 731 00:42:51,120 --> 00:42:55,480 Speaker 1: concluding thought gret to Cotail that it was very enjoyable 732 00:42:55,560 --> 00:42:58,080 Speaker 1: to hunt and hike with Carl because of that fact, 733 00:42:58,239 --> 00:43:00,759 Speaker 1: like a little tidbits, you'd point out that you knew 734 00:43:00,800 --> 00:43:03,560 Speaker 1: because of your studies that otherwise you know what had 735 00:43:03,760 --> 00:43:06,279 Speaker 1: gone unnoticed by someone like me. So that dude to 736 00:43:06,360 --> 00:43:08,640 Speaker 1: wealth and knowledge. He introduced me to the word music 737 00:43:08,760 --> 00:43:12,920 Speaker 1: and then the opposite of music is zer. So Carl 738 00:43:13,000 --> 00:43:17,520 Speaker 1: was describing a ridge top as being music, meaning it 739 00:43:17,800 --> 00:43:22,160 Speaker 1: was relatively moist by Southwestern standards. Yeah, so this is 740 00:43:22,200 --> 00:43:24,279 Speaker 1: one of these we didn't get talked about. Carl is uh, 741 00:43:24,840 --> 00:43:26,160 Speaker 1: tell me what you I know what you do, but 742 00:43:26,280 --> 00:43:28,360 Speaker 1: just give me, give me to everybody what you do. 743 00:43:29,680 --> 00:43:32,560 Speaker 1: I work as the Southwestern Regional Wildlife Ecologist for the 744 00:43:32,600 --> 00:43:36,520 Speaker 1: Forest Service, so pretty much anything related to wildlife monitoring 745 00:43:37,520 --> 00:43:41,960 Speaker 1: and research type stuff in the Southwest Arizona, New Mexico 746 00:43:42,160 --> 00:43:45,800 Speaker 1: on the Forest Services, twenty point six million acres of 747 00:43:45,920 --> 00:43:49,680 Speaker 1: land is under the purview of my position. And by 748 00:43:49,719 --> 00:43:52,239 Speaker 1: those twenty point six million acres of four Service land, 749 00:43:52,800 --> 00:43:56,160 Speaker 1: I mean the land that belongs to all of your listeners, 750 00:43:57,000 --> 00:43:59,560 Speaker 1: to all the listeners, to everybody around this table. And 751 00:43:59,680 --> 00:44:03,160 Speaker 1: that's way the world's people. That's true, because if you're 752 00:44:03,160 --> 00:44:04,759 Speaker 1: a German and you come over here, they're not like 753 00:44:05,080 --> 00:44:11,560 Speaker 1: even a German can go out there. Chris Gotty concluding thoughts, Um, yeah, 754 00:44:11,640 --> 00:44:13,960 Speaker 1: I learned that you shouldn't go working up a bear 755 00:44:14,040 --> 00:44:19,440 Speaker 1: den without some sort of poking stick. He made a 756 00:44:19,520 --> 00:44:22,920 Speaker 1: personal note. I was like making a was like, you know, 757 00:44:24,120 --> 00:44:27,440 Speaker 1: excuse me minute, I gotta call my wife, tell her 758 00:44:27,440 --> 00:44:32,239 Speaker 1: to remind me of something. I get home. Carl concluding thoughts, 759 00:44:35,160 --> 00:44:39,480 Speaker 1: I agree wholeheartedly that you know, I think hunters. I 760 00:44:39,560 --> 00:44:43,640 Speaker 1: think hunters do innately have a desire to know more 761 00:44:43,840 --> 00:44:46,840 Speaker 1: about the places and the species that they hunt. So 762 00:44:47,000 --> 00:44:48,759 Speaker 1: they have the desire to know more. I think so. 763 00:44:49,000 --> 00:44:51,000 Speaker 1: I think it's a it's a natural thing, a natural 764 00:44:51,080 --> 00:44:57,080 Speaker 1: fascination and and um, that was what it was. It 765 00:44:57,200 --> 00:45:00,959 Speaker 1: was experiences as a hunter and fisherman, just kid grown 766 00:45:01,040 --> 00:45:04,000 Speaker 1: up outside that led me on this career track. And 767 00:45:04,120 --> 00:45:07,120 Speaker 1: this career track feeds directly back into how I appreciate 768 00:45:07,200 --> 00:45:11,120 Speaker 1: those activities even more now than I did then. It's 769 00:45:11,160 --> 00:45:14,600 Speaker 1: like a it's a a feedback loop of sorts. The 770 00:45:14,680 --> 00:45:16,480 Speaker 1: more I learned, the more I like to hunt. The 771 00:45:16,560 --> 00:45:18,680 Speaker 1: more I hunt, the more I want to learn, you know, 772 00:45:19,680 --> 00:45:24,040 Speaker 1: And if people feel that intrigue, if that's something that 773 00:45:24,120 --> 00:45:27,920 Speaker 1: resonates with folks, you should you should explore that when 774 00:45:27,920 --> 00:45:30,040 Speaker 1: you're out there. You should take the time to note 775 00:45:30,560 --> 00:45:34,719 Speaker 1: a question that you have and pursue additional information. And 776 00:45:35,880 --> 00:45:38,919 Speaker 1: you should be trying trying to find ways as individuals 777 00:45:39,840 --> 00:45:44,200 Speaker 1: to be more than takers from these places. If there's 778 00:45:44,200 --> 00:45:47,360 Speaker 1: a place from which you are taking a resource, you 779 00:45:47,440 --> 00:45:54,040 Speaker 1: should feel like you have a stewardship responsibility. Yes. Um, 780 00:45:54,400 --> 00:45:57,319 Speaker 1: my conclusion thought is I love it that I didn't 781 00:45:57,320 --> 00:45:59,799 Speaker 1: know about this. I knew roughly this about you. Better 782 00:45:59,840 --> 00:46:03,200 Speaker 1: know all the way about you did. Um, you got 783 00:46:03,239 --> 00:46:06,400 Speaker 1: your start on your own hunting squirrels. You're darn right. 784 00:46:07,280 --> 00:46:09,880 Speaker 1: Carl was telling me in Michigan, where Carls grew up 785 00:46:09,880 --> 00:46:12,920 Speaker 1: and I did too. Deer season openers November fift The 786 00:46:12,960 --> 00:46:15,239 Speaker 1: Carl's telling me about one time he went out on 787 00:46:15,320 --> 00:46:17,960 Speaker 1: a squirrel stroll on November fift that got a hollered 788 00:46:18,000 --> 00:46:19,920 Speaker 1: at by a deer hunter, which I kind of love. 789 00:46:20,719 --> 00:46:24,719 Speaker 1: But you turned a love of squirrel hunting into doing 790 00:46:24,880 --> 00:46:30,280 Speaker 1: like very important work and our understanding and preservation of wildlife. 791 00:46:31,040 --> 00:46:33,399 Speaker 1: I appreciate the kind words. But a squirrel hunter, debt 792 00:46:33,440 --> 00:46:37,040 Speaker 1: bared and digger, I would counter that squirrel hunting is 793 00:46:37,480 --> 00:46:41,919 Speaker 1: in and of itself important work. Yes, that that point 794 00:46:42,080 --> 00:46:46,399 Speaker 1: point well taken. There you have it, Wisconsin super sow 795 00:46:47,000 --> 00:46:50,120 Speaker 1: Dr Carl Malcolm. Can people look up your work online. 796 00:46:50,200 --> 00:46:52,160 Speaker 1: Is there? Do you think I go to J store 797 00:46:52,200 --> 00:46:53,719 Speaker 1: and pay for it? Can they find stuff? There's some 798 00:46:53,800 --> 00:46:55,880 Speaker 1: stuff on there for free, the best, find the abstract 799 00:46:55,920 --> 00:46:58,800 Speaker 1: of the super sal Yeah, the best, the best. Some 800 00:46:58,840 --> 00:47:01,279 Speaker 1: stuff online, you man. We'll put stuff online. We'll put 801 00:47:01,320 --> 00:47:03,600 Speaker 1: some of those some of those little maps showing these 802 00:47:03,640 --> 00:47:08,000 Speaker 1: bears roaming around. Let's do that all right. Next time, 803 00:47:08,080 --> 00:47:10,160 Speaker 1: Carl's gonna talk about stuff that he's been doing recently, 804 00:47:10,200 --> 00:47:13,280 Speaker 1: and that stuff you did a long time ago. Sounds good, buddy,