1 00:00:05,200 --> 00:00:08,640 Speaker 1: Welcome to This Country Life. I'm your host, Brent Reeves. 2 00:00:09,119 --> 00:00:12,680 Speaker 1: From coon hunting to trot lining and just general country living. 3 00:00:12,920 --> 00:00:14,680 Speaker 1: I want you to stay a while as I share 4 00:00:14,760 --> 00:00:19,200 Speaker 1: my experiences and life lessons. This Country Life is presented 5 00:00:19,239 --> 00:00:23,240 Speaker 1: by Case Knives on Meat Eaters Podcast Network, bringing you 6 00:00:23,280 --> 00:00:28,240 Speaker 1: the best outdoor podcast that Airwaves had off. All right, friends, 7 00:00:28,600 --> 00:00:31,760 Speaker 1: grab a chair or drop that tailgate. I've got some 8 00:00:31,840 --> 00:00:41,440 Speaker 1: stories to share. Welcome to Part two of This Country Life. 9 00:00:41,560 --> 00:00:45,720 Speaker 1: It's kind of a different podcast about where I'm talking 10 00:00:45,720 --> 00:00:49,159 Speaker 1: to somebody and I'm here talking with doctor Drew Ricketts 11 00:00:49,200 --> 00:00:52,040 Speaker 1: from Kansas State University. He was on last week, it's 12 00:00:52,040 --> 00:00:53,920 Speaker 1: going to be on this week. And because I am 13 00:00:54,000 --> 00:00:57,520 Speaker 1: absolutely intrigued and I hope you are too, about how 14 00:00:57,640 --> 00:01:01,279 Speaker 1: coats affect the landscape, Deer hunting is big. A lot 15 00:01:01,320 --> 00:01:04,400 Speaker 1: of the folks that listening to my show, large portion 16 00:01:04,560 --> 00:01:07,480 Speaker 1: of them are in South in the Southeast, and that 17 00:01:07,600 --> 00:01:12,959 Speaker 1: deer hunting is king down here. And forever you see 18 00:01:12,959 --> 00:01:16,160 Speaker 1: a coyote, he's got to go because I've got to 19 00:01:16,200 --> 00:01:20,679 Speaker 1: have He's killing my deer, He's ruining everything that I've 20 00:01:20,720 --> 00:01:24,280 Speaker 1: been working so hard with and manipulating my forest and 21 00:01:24,440 --> 00:01:28,000 Speaker 1: planting food plots and doing everything I can to grow 22 00:01:28,040 --> 00:01:31,160 Speaker 1: big and better deer. And I've got this thief out 23 00:01:31,200 --> 00:01:34,000 Speaker 1: there that is stealing my boon and Crockett and poping 24 00:01:34,080 --> 00:01:38,279 Speaker 1: young deer away from me. But doctor Drew Ricketts, Kansas 25 00:01:38,319 --> 00:01:40,520 Speaker 1: State University, and we're here and we're gonna talk. We're 26 00:01:40,520 --> 00:01:42,600 Speaker 1: gonna get to the stuff that you've been waiting for, 27 00:01:42,760 --> 00:01:46,240 Speaker 1: I hope, because I've been waiting for it about how 28 00:01:46,360 --> 00:01:52,600 Speaker 1: coyotes affect the white tailed deer here on the landscape. Doctor. 29 00:01:53,040 --> 00:01:56,400 Speaker 1: We met last month on a hunt up here in 30 00:01:56,480 --> 00:01:59,600 Speaker 1: Kansas with you, a decoy dog hunt with you and 31 00:01:59,680 --> 00:02:02,560 Speaker 1: Jeff that that's a film that'll be coming out on 32 00:02:02,760 --> 00:02:06,880 Speaker 1: them and next year in twenty twenty six. I learned 33 00:02:06,920 --> 00:02:10,880 Speaker 1: some stuff while I was there. Re learned some stuff 34 00:02:10,919 --> 00:02:14,200 Speaker 1: I was there that I thought was that was that 35 00:02:14,320 --> 00:02:17,120 Speaker 1: wasn't correct. And that's that's what I want to get 36 00:02:17,120 --> 00:02:18,600 Speaker 1: out there. And I think a lot of people will 37 00:02:18,600 --> 00:02:22,800 Speaker 1: get some stuff out of this. Tell me why and 38 00:02:22,919 --> 00:02:28,280 Speaker 1: how coyotes are affecting the landscape where we're hunting. 39 00:02:28,400 --> 00:02:33,200 Speaker 2: Sure, sure, So you know last time we briefly talked 40 00:02:33,200 --> 00:02:36,360 Speaker 2: about their diet and just to reiterate that you know, 41 00:02:36,400 --> 00:02:40,200 Speaker 2: their their diet in the Eastern US, where they're a newcomer, 42 00:02:40,360 --> 00:02:42,520 Speaker 2: is quite different than it is here in the Great 43 00:02:42,520 --> 00:02:46,280 Speaker 2: Plains where I'm at. So you know, here they're mainly 44 00:02:46,320 --> 00:02:50,160 Speaker 2: eating smaller stuff like rabbits and rodents. Out in the east, 45 00:02:50,720 --> 00:02:53,560 Speaker 2: ungulates like deer are a much bigger part of their 46 00:02:53,600 --> 00:02:59,359 Speaker 2: diet and they can have an impact on deer populations. 47 00:02:59,800 --> 00:03:03,600 Speaker 2: And that has led folks to think about coyotes the 48 00:03:03,639 --> 00:03:06,079 Speaker 2: way that you're talking. You know, they're they're a villain. 49 00:03:06,480 --> 00:03:09,520 Speaker 2: We got to remove them from the landscape, and I mean, 50 00:03:09,560 --> 00:03:13,080 Speaker 2: to be honest, when we had We've had armadillus come 51 00:03:13,120 --> 00:03:16,160 Speaker 2: into Kansas, right, it's a natural range expansion. It's not 52 00:03:16,280 --> 00:03:18,519 Speaker 2: something that people have done. But that's kind of how 53 00:03:18,560 --> 00:03:21,560 Speaker 2: I think about armadillus. You know, they're they're not supposed 54 00:03:21,600 --> 00:03:24,160 Speaker 2: to be here, they're tearing stuff up. They're new. Well, 55 00:03:24,360 --> 00:03:28,959 Speaker 2: coyotes in in your area are are kind of that 56 00:03:29,400 --> 00:03:33,240 Speaker 2: same sort of critter there. There have been a lot 57 00:03:33,280 --> 00:03:35,560 Speaker 2: of studies that have looked at whether or not we 58 00:03:35,600 --> 00:03:38,120 Speaker 2: can remove enough coyotes to have an impact on deer 59 00:03:38,160 --> 00:03:43,080 Speaker 2: survival and more specifically, fond survival. They do kill some 60 00:03:43,160 --> 00:03:46,600 Speaker 2: adult deer Uh, it's not super common for them too, 61 00:03:46,640 --> 00:03:50,160 Speaker 2: but in the eastern US it's more common for them too. 62 00:03:52,000 --> 00:03:58,640 Speaker 1: More common because of more codes, more deer, or the 63 00:03:58,760 --> 00:04:00,240 Speaker 1: terrain in which they're hunting. 64 00:04:00,520 --> 00:04:05,280 Speaker 2: More common because those coyotes have longer legs, they're bigger, 65 00:04:05,600 --> 00:04:09,320 Speaker 2: they're more social in their hunting strategies, so you might 66 00:04:09,320 --> 00:04:13,160 Speaker 2: get multiple coyotes hunting together more often. And then the 67 00:04:13,200 --> 00:04:15,600 Speaker 2: other things that it's correlated with that we don't think 68 00:04:15,640 --> 00:04:19,720 Speaker 2: about a lot of times, are as as your average 69 00:04:19,920 --> 00:04:23,160 Speaker 2: snow depths during the wintertime increases, then it becomes more 70 00:04:23,200 --> 00:04:25,320 Speaker 2: and more likely that coyotes are going to be preying 71 00:04:25,360 --> 00:04:28,799 Speaker 2: on larger deer because they can. When you've got deep snow, 72 00:04:29,200 --> 00:04:31,520 Speaker 2: those coyotes can chase down a deer more easily and 73 00:04:31,560 --> 00:04:32,240 Speaker 2: catch it and kill it. 74 00:04:32,320 --> 00:04:34,400 Speaker 1: Let mean something. Let me tell you about something that 75 00:04:34,440 --> 00:04:38,359 Speaker 1: I observed in central Arkansas where I live. It was 76 00:04:38,440 --> 00:04:42,760 Speaker 1: a spring evening, I believe, yes, it was. It was 77 00:04:43,000 --> 00:04:44,760 Speaker 1: just right after Turkey season, so this would have been 78 00:04:44,760 --> 00:04:48,600 Speaker 1: in May. And I have got a brand new thermal, 79 00:04:48,800 --> 00:04:50,520 Speaker 1: and I'm sitting out on my front porch and I'm 80 00:04:50,520 --> 00:04:52,880 Speaker 1: looking at a pasture field across in front of my 81 00:04:52,960 --> 00:04:56,359 Speaker 1: house and I see seven or eight deer out there feeding, 82 00:04:56,960 --> 00:04:58,840 Speaker 1: and then I catch a glimpse of a coat, and 83 00:04:58,839 --> 00:05:01,760 Speaker 1: then I see another one. I see another one, and 84 00:05:02,080 --> 00:05:04,040 Speaker 1: you got a picture. There's there's seven or eight deer 85 00:05:04,080 --> 00:05:07,839 Speaker 1: feeding and they're on the west side of the property, 86 00:05:08,160 --> 00:05:11,440 Speaker 1: and coming from the east is three coachs and they separated. 87 00:05:11,880 --> 00:05:14,320 Speaker 1: One went around one side of the herd of the deer, 88 00:05:14,400 --> 00:05:17,440 Speaker 1: one went around the far side, was on the ones 89 00:05:17,480 --> 00:05:19,599 Speaker 1: on the far side, ones on the near side, and 90 00:05:19,640 --> 00:05:21,880 Speaker 1: one's right in the middle. And I thought, holy cow, 91 00:05:22,279 --> 00:05:24,599 Speaker 1: I'm fixing the sea. I'm fixing to see it right here. 92 00:05:25,120 --> 00:05:28,599 Speaker 1: This is national geographic happening in my front yard, you know, 93 00:05:28,680 --> 00:05:31,640 Speaker 1: from my front porch. The deer all looked at them, 94 00:05:32,080 --> 00:05:36,000 Speaker 1: and the coyoats walked right past them on both sides. 95 00:05:36,080 --> 00:05:38,320 Speaker 1: The one in the middle split right down the middle, 96 00:05:38,360 --> 00:05:41,240 Speaker 1: and the deer never paid any attention to them other 97 00:05:41,279 --> 00:05:45,080 Speaker 1: than watching them walk away. And they were fifty yards 98 00:05:45,279 --> 00:05:47,400 Speaker 1: trotting away, and the deer went right back to feeding. 99 00:05:47,960 --> 00:05:50,040 Speaker 1: It did not happen like I thought it was going 100 00:05:50,120 --> 00:05:53,040 Speaker 1: to happen, And there were small deer out there with them. 101 00:05:53,760 --> 00:05:55,119 Speaker 1: Didn't Why didn't it happen? 102 00:05:55,360 --> 00:06:00,080 Speaker 2: Well, that those to the average coyote, an animal that 103 00:06:00,120 --> 00:06:04,320 Speaker 2: big is not a prey item. It's more risky in 104 00:06:04,440 --> 00:06:07,719 Speaker 2: terms of energy expended and the potential to get hurt 105 00:06:08,480 --> 00:06:12,600 Speaker 2: than it than the reward is and and so it's 106 00:06:12,680 --> 00:06:17,480 Speaker 2: just coyotes aren't aren't naturally hunters a big prey. It's 107 00:06:17,520 --> 00:06:22,359 Speaker 2: it's more of an acquired thing. And I hesitate to 108 00:06:22,400 --> 00:06:26,799 Speaker 2: say it's learned, but you know, it's it's a process 109 00:06:26,920 --> 00:06:30,360 Speaker 2: of getting up to gumption to try and kill something bigger, 110 00:06:30,360 --> 00:06:35,440 Speaker 2: whether it's deer, livestock, it's it's learning how to do 111 00:06:35,520 --> 00:06:37,400 Speaker 2: it in addition to that, and so there's lots of 112 00:06:37,440 --> 00:06:38,840 Speaker 2: different things that come into it. 113 00:06:39,440 --> 00:06:46,360 Speaker 1: I saw a deer on a decoy dog hunt one 114 00:06:46,400 --> 00:06:50,960 Speaker 1: time with Jeff. We did a fallen in distress call 115 00:06:52,160 --> 00:06:54,119 Speaker 1: and there was a dough deer that came in there 116 00:06:55,120 --> 00:06:59,200 Speaker 1: and about the same time that the kyote did. And 117 00:06:59,240 --> 00:07:02,160 Speaker 1: that I'm assuming, now you know, I'm not reading the 118 00:07:02,200 --> 00:07:04,960 Speaker 1: deer's line, but I'm assuming she's looking at that predator 119 00:07:05,000 --> 00:07:08,039 Speaker 1: over there and thinking he's causing the distress that she's hearing. Yeah, 120 00:07:08,760 --> 00:07:11,880 Speaker 1: and that deer ran that coat out of sight. As 121 00:07:11,880 --> 00:07:13,680 Speaker 1: far as I know, they're still running and that was 122 00:07:13,720 --> 00:07:16,440 Speaker 1: ten years ago. Sure, yeah, I mean they are they 123 00:07:16,520 --> 00:07:21,800 Speaker 1: are not a submissive prey at them. You know, they're 124 00:07:21,840 --> 00:07:23,440 Speaker 1: they're not just going to lay down a little them. 125 00:07:23,560 --> 00:07:27,280 Speaker 1: They'll fight and they're they're pretty ferocious themselves though. Deer is, 126 00:07:27,360 --> 00:07:31,800 Speaker 1: so it only makes sense that that they're you know, 127 00:07:32,480 --> 00:07:34,280 Speaker 1: the coach are not just going to say, well, what 128 00:07:34,320 --> 00:07:36,280 Speaker 1: are you doing, Frank, I'm not doing nothing. Let's go 129 00:07:36,360 --> 00:07:38,120 Speaker 1: kill a deer, all right, Well let's go right. It 130 00:07:38,160 --> 00:07:39,960 Speaker 1: doesn't happen that way now now. 131 00:07:40,080 --> 00:07:42,800 Speaker 2: Now with fawns, on the other hand, if Coyle comes 132 00:07:42,800 --> 00:07:44,600 Speaker 2: across faun, it's going to catch it and kill it 133 00:07:44,800 --> 00:07:48,200 Speaker 2: if it can. And you know those fawns, especially when 134 00:07:48,200 --> 00:07:51,720 Speaker 2: they're brand new, uh, their their defense mechanism is to 135 00:07:51,720 --> 00:07:53,800 Speaker 2: hold still, even once they get something gets a hold 136 00:07:53,800 --> 00:07:56,960 Speaker 2: of them. I mean, my decoy dog, any when we're 137 00:07:56,960 --> 00:07:59,640 Speaker 2: out poking around, I always hate it when she finds 138 00:07:59,640 --> 00:08:02,400 Speaker 2: a fawn because she'll she'll grab a hold of it 139 00:08:02,440 --> 00:08:05,480 Speaker 2: and try to bring it to me. And and it's 140 00:08:05,600 --> 00:08:08,400 Speaker 2: just natural for them. That's their their defense. 141 00:08:08,480 --> 00:08:09,520 Speaker 1: It's just to hold. 142 00:08:09,320 --> 00:08:11,600 Speaker 2: Still, and it's not it's a good one to keep 143 00:08:11,600 --> 00:08:16,000 Speaker 2: from getting detected. But once they're detected, they're they're pretty vulnerable. 144 00:08:17,160 --> 00:08:22,119 Speaker 1: So there, I mean, obviously there is an impact there there. 145 00:08:22,960 --> 00:08:25,240 Speaker 2: It depends on where you are. We go back to that, 146 00:08:25,360 --> 00:08:29,800 Speaker 2: it depends So if you're thinking about an impact in 147 00:08:29,920 --> 00:08:34,520 Speaker 2: the Southeast I, like I said, those studies absolutely show 148 00:08:34,600 --> 00:08:38,720 Speaker 2: that there can be and that's why that's why those 149 00:08:38,760 --> 00:08:43,320 Speaker 2: states have really focused on trying to figure out what 150 00:08:43,440 --> 00:08:47,560 Speaker 2: to do about it, you know, thinking about the impact 151 00:08:47,800 --> 00:08:52,920 Speaker 2: elsewhere in areas where we've had coyotes for a long time. 152 00:08:53,120 --> 00:08:55,120 Speaker 2: One of the things that I find interesting is to 153 00:08:55,160 --> 00:08:57,560 Speaker 2: look at the long term data that we have in Kansas. 154 00:08:58,080 --> 00:09:00,320 Speaker 2: Two sources of long term data that we have in 155 00:09:00,400 --> 00:09:04,959 Speaker 2: Kansas or deer vehicle collision data that comes from the 156 00:09:05,720 --> 00:09:10,120 Speaker 2: Department of Transportation and then Wildlife and Parks gathers what 157 00:09:10,160 --> 00:09:13,560 Speaker 2: they call the roadside index. So the roadside index is 158 00:09:13,840 --> 00:09:17,080 Speaker 2: as biologists are driving around, they write down how many 159 00:09:17,080 --> 00:09:19,720 Speaker 2: live coyotes they see and how many roadkill coyotes they see. 160 00:09:20,120 --> 00:09:24,240 Speaker 2: And so these are not you can't compare apples to apples, 161 00:09:24,480 --> 00:09:27,160 Speaker 2: but the trends hold true. Right, So when we look 162 00:09:27,160 --> 00:09:30,080 Speaker 2: at these data, we can see that coyotes have about 163 00:09:30,160 --> 00:09:34,400 Speaker 2: tripled in terms of their index from nineteen eighty six 164 00:09:34,760 --> 00:09:37,520 Speaker 2: to twenty twenty three, which is when these data end 165 00:09:37,720 --> 00:09:42,679 Speaker 2: that I've got right here, So they have increased fairly 166 00:09:42,720 --> 00:09:47,600 Speaker 2: linearly during that time. If coyotes are controlling deer populations 167 00:09:47,600 --> 00:09:50,920 Speaker 2: in Kansas, we should see that deer vehicle collisions go 168 00:09:51,040 --> 00:09:55,160 Speaker 2: down as coyote as coyote numbers increase, and we don't 169 00:09:55,160 --> 00:09:58,199 Speaker 2: see that. If you look at that deer vehicle collision data, 170 00:09:59,040 --> 00:10:02,200 Speaker 2: what it looks more like like is deer populations have 171 00:10:02,360 --> 00:10:06,079 Speaker 2: leveled off and stabilized and they're probably hovering around carrying capacity. 172 00:10:07,400 --> 00:10:11,079 Speaker 2: So that's one line of evidence that in Kansas, at 173 00:10:11,160 --> 00:10:13,480 Speaker 2: least if we look at it at a broad state level, 174 00:10:14,000 --> 00:10:18,680 Speaker 2: then coyotes probably aren't limiting the deer population. They pray 175 00:10:18,720 --> 00:10:21,960 Speaker 2: on fawns, but they're not having enough of an impact 176 00:10:22,040 --> 00:10:27,320 Speaker 2: to limit the population most likely. Another thing to look 177 00:10:27,360 --> 00:10:31,720 Speaker 2: at is that meme that we've talked about a few times, 178 00:10:31,720 --> 00:10:34,600 Speaker 2: and it says it shows a picture it's a pyramid 179 00:10:34,640 --> 00:10:37,920 Speaker 2: of deer fawns with a coyote at the top, and 180 00:10:37,960 --> 00:10:40,560 Speaker 2: it says during the coyote innning season, studies have found 181 00:10:40,600 --> 00:10:44,120 Speaker 2: that female coyotes average killing nineteen fawns to feed their offspring, 182 00:10:44,559 --> 00:10:45,960 Speaker 2: keep doing the good work. 183 00:10:46,000 --> 00:10:48,160 Speaker 1: Fellas. You know that's not true, is it. 184 00:10:48,240 --> 00:10:50,560 Speaker 2: Well? You know I saw that and I thought, man, 185 00:10:50,720 --> 00:10:53,400 Speaker 2: that's some research that slipped through the cracks on me 186 00:10:54,440 --> 00:10:56,400 Speaker 2: because I don't remember ever seeing it, and I don't 187 00:10:56,440 --> 00:10:59,600 Speaker 2: even even really know how you would do that. You know, 188 00:10:59,640 --> 00:11:03,000 Speaker 2: to be able to do that study, it's not as 189 00:11:03,000 --> 00:11:05,200 Speaker 2: simple as people might think it would be. You would 190 00:11:05,240 --> 00:11:09,840 Speaker 2: have to have camera callers on the coyotes because you 191 00:11:09,880 --> 00:11:12,520 Speaker 2: would need to be able to distinguish between dead fawns 192 00:11:12,559 --> 00:11:15,640 Speaker 2: that they found in fawns that they killed, and you 193 00:11:15,679 --> 00:11:17,160 Speaker 2: would have to be able to keep track of it 194 00:11:17,200 --> 00:11:18,400 Speaker 2: on an individual basis. 195 00:11:18,840 --> 00:11:22,960 Speaker 1: Right, So there you're cloudness issue with facts. 196 00:11:23,640 --> 00:11:26,080 Speaker 2: I'm sorry, I'm sorry, but that's what I'm supposed to 197 00:11:26,080 --> 00:11:29,120 Speaker 2: do with it is. 198 00:11:31,320 --> 00:11:34,120 Speaker 1: And it's interesting to me, and I hate to interrupt 199 00:11:34,160 --> 00:11:36,400 Speaker 1: you on no no, no, go ahead, but it's interesting 200 00:11:36,480 --> 00:11:41,000 Speaker 1: to me that you know that that's a female coat 201 00:11:41,120 --> 00:11:44,480 Speaker 1: is getting blamed for that during dinnin season. What's a 202 00:11:44,520 --> 00:11:47,040 Speaker 1: female coat doing during didn't season? 203 00:11:47,120 --> 00:11:48,839 Speaker 2: Yeah? I mean I alluded to that a little bit 204 00:11:48,880 --> 00:11:53,400 Speaker 2: in that previous episode, but during during that time right 205 00:11:53,480 --> 00:11:56,760 Speaker 2: before she gives birth and then up until that not 206 00:11:56,880 --> 00:11:59,400 Speaker 2: weaning time that would be too long, but up up 207 00:11:59,480 --> 00:12:02,480 Speaker 2: until those those pups are at least have a little 208 00:12:02,480 --> 00:12:05,719 Speaker 2: bit of independence, she's got to be provisioned with all 209 00:12:05,760 --> 00:12:06,360 Speaker 2: of her food. 210 00:12:07,640 --> 00:12:12,400 Speaker 1: So that means clay provision to mean that somebody's bringing 211 00:12:12,400 --> 00:12:14,200 Speaker 1: her her groceries. She's not leaving. 212 00:12:14,360 --> 00:12:20,199 Speaker 2: Yeah, yeah, So that's part of why that that family structure, 213 00:12:20,320 --> 00:12:24,160 Speaker 2: that family group structure is so important for coyotes. She's 214 00:12:24,400 --> 00:12:28,360 Speaker 2: getting food from the male that she bred with, and 215 00:12:28,679 --> 00:12:32,720 Speaker 2: she's also likely getting food from one to a few 216 00:12:33,160 --> 00:12:36,719 Speaker 2: of what we would call helpers, and helpers in that 217 00:12:36,800 --> 00:12:41,520 Speaker 2: family group are part of the previous year's litter that, 218 00:12:42,200 --> 00:12:46,160 Speaker 2: rather than dispersing or being forced to disperse by the 219 00:12:46,200 --> 00:12:50,640 Speaker 2: male and the female, decided to stay around. And their 220 00:12:50,880 --> 00:12:54,320 Speaker 2: role is to help provide food to that female and 221 00:12:54,360 --> 00:12:57,440 Speaker 2: the pups until they're raised, and then they're going to 222 00:12:57,480 --> 00:13:01,000 Speaker 2: go ahead and disperse that following fall when they're about 223 00:13:01,040 --> 00:13:03,640 Speaker 2: a year and a half old. Most of the time, 224 00:13:03,880 --> 00:13:08,480 Speaker 2: and when we think about dispersal, we see male bias 225 00:13:08,520 --> 00:13:12,080 Speaker 2: dispersal in most mammals, so it's it's most likely that 226 00:13:12,120 --> 00:13:14,800 Speaker 2: those helpers are going to be female pups from last year. 227 00:13:15,600 --> 00:13:18,440 Speaker 2: They don't have to be there's there's never a has 228 00:13:18,480 --> 00:13:21,120 Speaker 2: to be right. But it's more likely that they're going 229 00:13:21,160 --> 00:13:23,000 Speaker 2: to be females than it is that they're going to 230 00:13:23,000 --> 00:13:24,240 Speaker 2: be males. 231 00:13:26,040 --> 00:13:29,640 Speaker 1: But as far as the meme goes, it's not nineteen 232 00:13:29,720 --> 00:13:35,319 Speaker 1: coats per per our, nineteen fawns per code that are 233 00:13:35,360 --> 00:13:39,679 Speaker 1: female kyd during dinning season. You did the numbers. You 234 00:13:39,679 --> 00:13:42,360 Speaker 1: did the numbers on the population of deer, you did 235 00:13:42,360 --> 00:13:46,120 Speaker 1: the deer studies on the on the fawn, how many 236 00:13:46,160 --> 00:13:50,120 Speaker 1: fawns are born every year, and the number of and 237 00:13:50,200 --> 00:13:54,040 Speaker 1: the number of coats on a or estimated number of 238 00:13:54,040 --> 00:13:58,000 Speaker 1: coats in a particular area. Stopped me when I'm when 239 00:13:58,000 --> 00:14:00,640 Speaker 1: I say something wrong. And then you put those numbers 240 00:14:00,679 --> 00:14:03,960 Speaker 1: together and you came up with a more accurate depiction 241 00:14:04,440 --> 00:14:10,440 Speaker 1: or number of what that impact is on codes to fauns. 242 00:14:11,000 --> 00:14:15,640 Speaker 2: And that number is what that number for Kansas, the 243 00:14:15,720 --> 00:14:19,240 Speaker 2: maximum value that it could be is three point two 244 00:14:19,280 --> 00:14:22,880 Speaker 2: four Okay, I break that down for So this is 245 00:14:22,920 --> 00:14:26,520 Speaker 2: based on the deer surveys that Wildlife and Parks does 246 00:14:26,520 --> 00:14:30,640 Speaker 2: every year, and it's it's average average number of dos 247 00:14:30,640 --> 00:14:36,160 Speaker 2: and fauns from that data across ten years. So it's 248 00:14:36,520 --> 00:14:39,400 Speaker 2: pretty good data. This is not published, it's not peer 249 00:14:39,440 --> 00:14:42,280 Speaker 2: reviewed for any scientists that might be listening on here. Okay, 250 00:14:42,400 --> 00:14:45,160 Speaker 2: this is just numbers I went and got from wildlife 251 00:14:45,200 --> 00:14:47,840 Speaker 2: and parks. So if we assume that there's about seven 252 00:14:47,960 --> 00:14:50,480 Speaker 2: hundred thousand deer in Kansas, which is what it says, 253 00:14:51,640 --> 00:14:55,880 Speaker 2: forty two percent of those should be does okay, a 254 00:14:55,920 --> 00:14:58,120 Speaker 2: good round number to put on what we think we 255 00:14:58,160 --> 00:15:01,080 Speaker 2: should see. In terms of fauns, Purdue is one and 256 00:15:01,120 --> 00:15:03,880 Speaker 2: a half fawns per doh. Okay, So that gives us 257 00:15:03,920 --> 00:15:06,680 Speaker 2: about four hundred and forty thousand fawns produced in Kansas 258 00:15:06,720 --> 00:15:13,720 Speaker 2: every year. No, sorry, let me, let me, let me 259 00:15:13,760 --> 00:15:16,760 Speaker 2: look at this again too. So we've got two hundred 260 00:15:16,800 --> 00:15:20,080 Speaker 2: and ninety thousand dos. At one and a half fawns 261 00:15:20,120 --> 00:15:23,560 Speaker 2: per doe gives us four hundred and forty one thousand 262 00:15:23,600 --> 00:15:28,120 Speaker 2: fawns in that fall survey, twenty five percent of what 263 00:15:28,160 --> 00:15:33,040 Speaker 2: we see is fawns. Okay, okay, So what that tells 264 00:15:33,120 --> 00:15:37,800 Speaker 2: us is that one hundred and seventy five thousand fawns 265 00:15:38,320 --> 00:15:42,160 Speaker 2: out of four hundred and forty thousand fawns made it 266 00:15:42,160 --> 00:15:46,280 Speaker 2: from birth to fall in an average year. So the 267 00:15:46,360 --> 00:15:49,400 Speaker 2: maximum number of funds that could be lost in an 268 00:15:49,400 --> 00:15:52,960 Speaker 2: average years two hundred sixty six thousand. A good round 269 00:15:53,040 --> 00:15:54,840 Speaker 2: number to put on how many coyotes there are in 270 00:15:54,960 --> 00:15:58,720 Speaker 2: Kansas is five coyotes per square mile. And we won't 271 00:15:58,720 --> 00:16:00,680 Speaker 2: go into how I got those snths, but I can 272 00:16:00,680 --> 00:16:02,440 Speaker 2: tell you it's it's similar to how I got the 273 00:16:02,440 --> 00:16:05,720 Speaker 2: deer values. Right, So that gives us a little over 274 00:16:05,760 --> 00:16:09,600 Speaker 2: four hundred thousand coyotes in Kansas. At five coyotes per 275 00:16:09,600 --> 00:16:12,120 Speaker 2: square mile and eighty two thousand square miles in Kansas. 276 00:16:13,880 --> 00:16:17,880 Speaker 2: If we divide two hundred and sixty six thousand fawns 277 00:16:17,920 --> 00:16:21,240 Speaker 2: by four hundred and eleven thousand coyotes, that gives us 278 00:16:21,600 --> 00:16:28,840 Speaker 2: zero point sixty five fawns per coyote. Okay, and that's 279 00:16:28,960 --> 00:16:33,000 Speaker 2: assuming that one hundred percent of the fawns that died 280 00:16:33,200 --> 00:16:34,360 Speaker 2: were killed by coyotes. 281 00:16:34,440 --> 00:16:34,560 Speaker 1: Right. 282 00:16:35,880 --> 00:16:38,360 Speaker 2: If we say, if we go back to that female 283 00:16:38,400 --> 00:16:42,280 Speaker 2: thing and assume that there's one family group per square mile, 284 00:16:42,320 --> 00:16:44,440 Speaker 2: which is probably two dense, but that's what we're going 285 00:16:44,480 --> 00:16:47,800 Speaker 2: to assume to make the math simple, then the maximum 286 00:16:47,880 --> 00:16:51,160 Speaker 2: number that a female could kill on average across the 287 00:16:51,240 --> 00:16:56,040 Speaker 2: state would be three point twenty four if we adjust 288 00:16:56,160 --> 00:16:58,640 Speaker 2: all this for the fact that in the study that 289 00:16:58,720 --> 00:17:02,440 Speaker 2: I did, the highest predation we saw on fawns was 290 00:17:02,480 --> 00:17:06,119 Speaker 2: forty percent. Then that gives us an average of zero 291 00:17:06,160 --> 00:17:10,720 Speaker 2: point two six fawns per coyote across the state and 292 00:17:11,200 --> 00:17:13,840 Speaker 2: one point three if we look at it on a 293 00:17:13,840 --> 00:17:14,880 Speaker 2: per family group. 294 00:17:14,800 --> 00:17:21,080 Speaker 1: Basis, So it's not near I mean, that's eighteen less 295 00:17:21,359 --> 00:17:23,960 Speaker 1: coyotes that are being I mean the fawns that are 296 00:17:23,960 --> 00:17:27,639 Speaker 1: being killed, So that ratio is nowhere near the level 297 00:17:27,680 --> 00:17:31,960 Speaker 1: at what is purported and what social media is putting 298 00:17:31,960 --> 00:17:35,439 Speaker 1: out there. And while they are they are having an 299 00:17:35,520 --> 00:17:40,119 Speaker 1: effect on the landscape, it's not near like what is 300 00:17:40,200 --> 00:17:42,720 Speaker 1: led to believe. And that was something that I learned 301 00:17:42,880 --> 00:17:45,960 Speaker 1: from talking to you back when we were hunting here. 302 00:17:46,080 --> 00:17:49,959 Speaker 2: Sure. Sure, and remember this is based on Kansas numbers. 303 00:17:50,400 --> 00:17:53,440 Speaker 2: In an area where deer are a more important food 304 00:17:53,480 --> 00:17:57,000 Speaker 2: item for coyotes, it's going to be higher. But that meme, 305 00:17:57,920 --> 00:18:00,440 Speaker 2: there's no way that somebody did the project that that 306 00:18:00,480 --> 00:18:02,960 Speaker 2: meme is reporting, and that number, even if you're in 307 00:18:03,000 --> 00:18:07,600 Speaker 2: an area where where fawn predation by coyotes is important, 308 00:18:08,080 --> 00:18:10,520 Speaker 2: it's not going to be that high, right, Yeah. 309 00:18:10,280 --> 00:18:13,400 Speaker 1: Because it's just not their natural not the number one 310 00:18:13,440 --> 00:18:14,560 Speaker 1: thing on their list to eat. 311 00:18:14,680 --> 00:18:17,320 Speaker 2: Well. No, and if you think about fond density on 312 00:18:17,359 --> 00:18:20,520 Speaker 2: the landscape, it's not very profitable for a coyote to 313 00:18:20,600 --> 00:18:22,760 Speaker 2: leave and decide that's the main thing that it's going 314 00:18:22,840 --> 00:18:23,679 Speaker 2: to go looking for. 315 00:18:23,720 --> 00:18:26,119 Speaker 1: Sure, because he's going to walk by food looking for food. 316 00:18:26,240 --> 00:18:30,840 Speaker 2: Absolutely. Yeah. And the reason though that those bigger prey 317 00:18:30,840 --> 00:18:34,600 Speaker 2: items like fawns and lambs and calves are important during 318 00:18:34,640 --> 00:18:38,480 Speaker 2: that spring time frame is because they need to bring 319 00:18:38,560 --> 00:18:42,640 Speaker 2: that more food back to that female and potentially pups. 320 00:18:42,720 --> 00:18:45,560 Speaker 1: Okay, that's going to lead us into what we were 321 00:18:45,640 --> 00:18:48,080 Speaker 1: hunting up here and why we were getting the reactions 322 00:18:48,080 --> 00:18:50,959 Speaker 1: that we were getting. Yeah, you talked about that helper 323 00:18:51,000 --> 00:18:54,040 Speaker 1: that stayed. So you got the female that's nursing pups, 324 00:18:54,400 --> 00:18:57,160 Speaker 1: you got the male that's there, and they they mate 325 00:18:57,320 --> 00:19:01,119 Speaker 1: for life until one of them, to one of them dies, 326 00:19:01,160 --> 00:19:01,840 Speaker 1: Is that correct. 327 00:19:02,000 --> 00:19:05,440 Speaker 2: Probably the best data that we have for that comes 328 00:19:05,440 --> 00:19:08,160 Speaker 2: out of a study in Chicago. They're the only place 329 00:19:08,240 --> 00:19:11,440 Speaker 2: really that's got enough mated pairs that they've tracked through 330 00:19:11,520 --> 00:19:13,080 Speaker 2: time and has the DNA off. 331 00:19:12,960 --> 00:19:16,399 Speaker 1: Of Okay, so that's probability, yeah, more than likely that 332 00:19:16,480 --> 00:19:19,960 Speaker 1: they stay together to one of them dies. Yep. 333 00:19:20,040 --> 00:19:21,920 Speaker 2: And then once that one dies, it's going to get 334 00:19:21,920 --> 00:19:23,680 Speaker 2: replaced thee like. 335 00:19:24,000 --> 00:19:26,920 Speaker 1: They're not in mourning or anything like that. Yeah, correct, 336 00:19:27,960 --> 00:19:33,400 Speaker 1: But that helper, the one that stays there, male or female, 337 00:19:34,480 --> 00:19:38,080 Speaker 1: those are the that she that code, the helper code 338 00:19:38,160 --> 00:19:42,919 Speaker 1: is responsible and a large majority for feeding that nursing 339 00:19:43,520 --> 00:19:44,280 Speaker 1: mother in the den. 340 00:19:44,400 --> 00:19:47,840 Speaker 2: Correct, Not just the helpers, also the male. Okay, so 341 00:19:47,960 --> 00:19:50,280 Speaker 2: both of them. Yeah, you got both of them there. 342 00:19:50,520 --> 00:19:54,120 Speaker 2: And those are the ones that are responding to the calls. 343 00:19:54,480 --> 00:19:58,320 Speaker 2: Those are the ones that are territorial and aggressive, and 344 00:19:58,359 --> 00:20:01,200 Speaker 2: those are the codes, not all of them, but those 345 00:20:01,240 --> 00:20:05,240 Speaker 2: are the ones that are probably causing the issues with 346 00:20:06,640 --> 00:20:10,520 Speaker 2: livestock and the ones that are snatching fluffy out of 347 00:20:10,520 --> 00:20:12,800 Speaker 2: the backyard, the more aggressive ones. 348 00:20:13,119 --> 00:20:13,800 Speaker 1: Is that correct? 349 00:20:13,840 --> 00:20:17,320 Speaker 2: In his study in California where they had radio colored 350 00:20:17,320 --> 00:20:20,800 Speaker 2: coyotes and they were tracking sheep losses, one male was 351 00:20:20,840 --> 00:20:23,720 Speaker 2: responsible for seventy one percent of the sheep losses. 352 00:20:23,920 --> 00:20:24,359 Speaker 1: Is that right? 353 00:20:24,480 --> 00:20:27,480 Speaker 2: A year and the losses didn't stop until they killed. 354 00:20:27,200 --> 00:20:33,119 Speaker 1: That coyote and then it stopped. So on a micro scale, 355 00:20:33,640 --> 00:20:37,119 Speaker 1: you can make a difference calling a coat with a 356 00:20:37,840 --> 00:20:41,720 Speaker 1: predator collar or a decoy dogar using it and taking 357 00:20:41,760 --> 00:20:45,040 Speaker 1: it out of the herd on a micro scale is 358 00:20:45,119 --> 00:20:46,879 Speaker 1: not even going to be a blip on the radar. 359 00:20:47,200 --> 00:20:50,679 Speaker 2: Yeah, and you know the studies that have looked at 360 00:20:51,400 --> 00:20:55,240 Speaker 2: livestock losses and how to deal with livestock losses, the 361 00:20:55,320 --> 00:21:00,480 Speaker 2: number of coyotes removed is not related to win losses stopped. 362 00:21:01,400 --> 00:21:05,040 Speaker 2: You have to remove the individuals that are causing the 363 00:21:05,080 --> 00:21:07,600 Speaker 2: problem because, like we said last time, most coyotes aren't 364 00:21:07,680 --> 00:21:12,240 Speaker 2: killing livestock, and probably your average coyote is not killing fonts. 365 00:21:13,520 --> 00:21:16,520 Speaker 2: They get them when they find them, but it's not 366 00:21:16,680 --> 00:21:19,159 Speaker 2: the thing they're going looking for. And so when we 367 00:21:19,240 --> 00:21:23,960 Speaker 2: do have problems developed with livestock, you deal with those individuals. 368 00:21:24,280 --> 00:21:26,560 Speaker 2: And that's on the lethal control side of things. There's 369 00:21:26,560 --> 00:21:28,719 Speaker 2: all kinds of non lethal stuff that we can do 370 00:21:28,800 --> 00:21:32,800 Speaker 2: that prevent the problems from ever even occurring sometimes in 371 00:21:32,800 --> 00:21:36,280 Speaker 2: some situations, but from lethal control, it doesn't make sense 372 00:21:36,920 --> 00:21:43,240 Speaker 2: for a livestock producer to make coyote killing a job. Now, 373 00:21:43,920 --> 00:21:47,800 Speaker 2: if it does make sense for a cattle producer or 374 00:21:47,960 --> 00:21:50,880 Speaker 2: seat producer to have a good friend that's good at 375 00:21:51,040 --> 00:21:59,000 Speaker 2: killing coyotes and having decoy dogs and being able to 376 00:21:59,160 --> 00:22:03,080 Speaker 2: call coyotes and effectively this time of the year makes 377 00:22:03,119 --> 00:22:06,560 Speaker 2: it more likely that that person is going to be 378 00:22:06,560 --> 00:22:13,399 Speaker 2: better at solving livestock damage issues than someone who isn't 379 00:22:13,440 --> 00:22:16,920 Speaker 2: able to target those more aggressive coyotes that are more 380 00:22:16,960 --> 00:22:20,360 Speaker 2: aggressive because they have a litter of pups. 381 00:22:20,560 --> 00:22:23,840 Speaker 1: Right, yeah, okay, so and that's why it's important that 382 00:22:23,920 --> 00:22:26,680 Speaker 1: we hunt them. Yeah, and there's a reason. And some 383 00:22:26,720 --> 00:22:30,679 Speaker 1: folks will say, you know, I've had people ask me 384 00:22:30,720 --> 00:22:32,680 Speaker 1: about crow hunting and stuff. So you like to crow, 385 00:22:32,680 --> 00:22:35,119 Speaker 1: and oh, I love them? Like man, you eat them? Like, no, 386 00:22:35,119 --> 00:22:38,000 Speaker 1: I don't eat crows. Well, you know, I was raised 387 00:22:38,000 --> 00:22:39,840 Speaker 1: that if we don't eat it, we don't hunt it, 388 00:22:39,840 --> 00:22:42,560 Speaker 1: which is fine. But tell me give me the argument 389 00:22:42,640 --> 00:22:45,440 Speaker 1: of why because I'm not eating this code The furs 390 00:22:45,520 --> 00:22:48,119 Speaker 1: down here in this part of the world are not, 391 00:22:48,560 --> 00:22:51,000 Speaker 1: and especially in Arkansas, the furthest south you go, the 392 00:22:51,400 --> 00:22:54,040 Speaker 1: worst the fur is or the less quality the fur is, 393 00:22:54,840 --> 00:22:58,479 Speaker 1: and the fur market, which is you know, at an 394 00:22:58,480 --> 00:23:02,000 Speaker 1: all time load. Just about why why is it going 395 00:23:02,080 --> 00:23:03,720 Speaker 1: to go out hunt? Kyle? 396 00:23:04,000 --> 00:23:06,880 Speaker 2: Sure? Well, I mean it goes back to what I 397 00:23:06,920 --> 00:23:10,240 Speaker 2: was saying about being good at taking coyotes this time 398 00:23:10,240 --> 00:23:14,560 Speaker 2: of the year, right, And and I think you know, 399 00:23:14,880 --> 00:23:18,960 Speaker 2: one of the reasons to hunt is to become better 400 00:23:19,000 --> 00:23:25,560 Speaker 2: at it. And when hunting with a decoy dog or 401 00:23:25,840 --> 00:23:31,440 Speaker 2: hunting during during pupp bearing season or or whelping season, 402 00:23:31,600 --> 00:23:34,520 Speaker 2: you know, that's very, very different than calling coyotes in 403 00:23:34,560 --> 00:23:37,200 Speaker 2: the fall, and so. 404 00:23:38,840 --> 00:23:41,840 Speaker 1: One's food related, one's territorial Yeah right. 405 00:23:41,720 --> 00:23:47,040 Speaker 2: Yep, for sure, and having that skill and honing that 406 00:23:47,240 --> 00:23:50,480 Speaker 2: skill is the important reason to hunt at this time 407 00:23:50,480 --> 00:23:53,800 Speaker 2: of the year. And from from my point of view, 408 00:23:53,840 --> 00:23:56,920 Speaker 2: the thing that a lot of people probably don't realize 409 00:23:56,920 --> 00:24:00,399 Speaker 2: about most decoy dog hunters is that they're not taking 410 00:24:00,400 --> 00:24:01,879 Speaker 2: most of the coyotes that they call in. 411 00:24:02,200 --> 00:24:02,679 Speaker 1: For sure. 412 00:24:03,200 --> 00:24:06,960 Speaker 2: You don't reward a dog for not decoying a coyote 413 00:24:06,960 --> 00:24:08,240 Speaker 2: and doing what its job was. 414 00:24:08,520 --> 00:24:12,600 Speaker 1: Well, so take our hunt for insistence, without giving too 415 00:24:12,640 --> 00:24:17,760 Speaker 1: much away, we called seven or eight coats off of 416 00:24:18,000 --> 00:24:22,040 Speaker 1: probably ten stands, six or seven coats and we walked 417 00:24:22,040 --> 00:24:25,679 Speaker 1: out of there with I'll put it this way, we 418 00:24:25,720 --> 00:24:27,879 Speaker 1: could we could rode in the cab of the truck 419 00:24:27,960 --> 00:24:30,680 Speaker 1: with all the coats that we shot that day, Yeah, 420 00:24:31,320 --> 00:24:35,400 Speaker 1: and say it's not an automatic. It's not an automatic thing. 421 00:24:35,560 --> 00:24:38,879 Speaker 2: Sure, sure, So that part is more about honing a skill. 422 00:24:40,560 --> 00:24:45,520 Speaker 2: If if someone is trying to take enough coyotes that 423 00:24:46,000 --> 00:24:51,760 Speaker 2: they can have an effect on fawn survival, then late 424 00:24:52,760 --> 00:24:58,080 Speaker 2: winter probably actually early spring, so so March leading up 425 00:24:58,119 --> 00:25:02,439 Speaker 2: to fawning season, so March through August or September is 426 00:25:02,480 --> 00:25:06,359 Speaker 2: when you should be taking coyotes. If you're in an 427 00:25:06,440 --> 00:25:10,120 Speaker 2: area where they really are having an impact on deer numbers, 428 00:25:10,200 --> 00:25:14,760 Speaker 2: like the southeast or potentially the northeast US, then that 429 00:25:14,960 --> 00:25:18,720 Speaker 2: is when you can get something done. Because we talked 430 00:25:18,720 --> 00:25:21,800 Speaker 2: about those transients in the first episode about half the 431 00:25:21,840 --> 00:25:25,120 Speaker 2: coyotes in most populations are transients, and those transients are 432 00:25:25,119 --> 00:25:28,600 Speaker 2: just floating around waiting to take somebody's spot when they die, okay, 433 00:25:28,760 --> 00:25:32,280 Speaker 2: and so for every kyote you take, there's at least 434 00:25:32,280 --> 00:25:35,560 Speaker 2: one transient waiting to fill that gap on the landscape. 435 00:25:35,640 --> 00:25:38,199 Speaker 2: And so what we see most of the time is 436 00:25:38,320 --> 00:25:41,200 Speaker 2: just really high immigration rates that are replacing those coyotes. 437 00:25:41,200 --> 00:25:44,840 Speaker 2: So if you're killing them fall through the end of 438 00:25:44,880 --> 00:25:47,760 Speaker 2: what we would typically think of as first season, like February, 439 00:25:48,160 --> 00:25:50,040 Speaker 2: those kyotes are going to be replaced before its faun 440 00:25:50,080 --> 00:25:54,200 Speaker 2: eating time, so you're not really getting anything done there. 441 00:25:54,600 --> 00:25:58,840 Speaker 2: So that's another potential reason to hunt them this time 442 00:25:58,920 --> 00:26:01,719 Speaker 2: of the year. If you're doing it for that reason. 443 00:26:02,040 --> 00:26:06,280 Speaker 2: In the Great Plains or most of the Southwest, you've 444 00:26:06,280 --> 00:26:09,720 Speaker 2: probably got your priorities in the wrong place. If you 445 00:26:09,760 --> 00:26:12,760 Speaker 2: want to manage for deer or pronghorn in those places, 446 00:26:12,760 --> 00:26:15,040 Speaker 2: then you ought to be managing habitat for those species, 447 00:26:15,200 --> 00:26:17,679 Speaker 2: right And really you can get the most bang for 448 00:26:17,760 --> 00:26:22,480 Speaker 2: your buck everywhere by managing habitat because habitat management, improving 449 00:26:22,640 --> 00:26:26,919 Speaker 2: fawning cover and improving food is predator management. We just 450 00:26:26,960 --> 00:26:28,680 Speaker 2: don't think about it that way exactly. 451 00:26:28,920 --> 00:26:31,199 Speaker 1: You think of predator management as putting a bullet in 452 00:26:31,240 --> 00:26:36,040 Speaker 1: the cove or the nest predator or whatever it is 453 00:26:36,080 --> 00:26:39,880 Speaker 1: that you're trying, you know, to raise, whether it's turkeys 454 00:26:39,920 --> 00:26:42,840 Speaker 1: or quail or deer or whatever. But that what you 455 00:26:43,040 --> 00:26:48,040 Speaker 1: covied right there is absolutely more important than any number 456 00:26:48,080 --> 00:26:51,760 Speaker 1: that you could shoot coming into a call yep, because 457 00:26:51,800 --> 00:26:56,800 Speaker 1: you're absolutely going to have a larger effect on the 458 00:26:56,880 --> 00:26:59,119 Speaker 1: landscape by doing that than you are out there with 459 00:26:59,160 --> 00:27:01,800 Speaker 1: a rival. And it is fun and I love it. 460 00:27:01,880 --> 00:27:05,119 Speaker 1: I love doing it. How'd you get into decoy dog hunting? 461 00:27:06,240 --> 00:27:09,280 Speaker 2: When when I started this role as the extension wildlife 462 00:27:09,320 --> 00:27:13,479 Speaker 2: specialist and started helping people with kyo problems. I started 463 00:27:13,560 --> 00:27:17,800 Speaker 2: driving the state so much that I was lonely. Not 464 00:27:17,920 --> 00:27:19,879 Speaker 2: a sob story, but I just you know, I was 465 00:27:19,920 --> 00:27:21,840 Speaker 2: gone all the time, and I wanted to have a 466 00:27:21,880 --> 00:27:25,399 Speaker 2: buddy with me. And I've got a friend from that 467 00:27:25,520 --> 00:27:28,320 Speaker 2: I went to high school with who's really into decoy dogs. 468 00:27:28,359 --> 00:27:31,359 Speaker 2: And we started talking. He said, I need to get 469 00:27:31,359 --> 00:27:33,000 Speaker 2: a dog in your hands. Man, you do so much 470 00:27:33,080 --> 00:27:35,160 Speaker 2: coyot hunting, especially at the time of the year when 471 00:27:35,200 --> 00:27:38,720 Speaker 2: decoy dogs are are are good that you know it 472 00:27:38,760 --> 00:27:40,800 Speaker 2: could be good for you and you could be training 473 00:27:40,840 --> 00:27:42,480 Speaker 2: dogs and all this kind of stuff. And so I 474 00:27:42,920 --> 00:27:46,320 Speaker 2: got Annie, my current dog, from him. I was supposed 475 00:27:46,320 --> 00:27:52,159 Speaker 2: to be training her, and about the time that we 476 00:27:52,280 --> 00:27:55,240 Speaker 2: got her really good at decoyn he said, Okay, I 477 00:27:55,240 --> 00:27:57,280 Speaker 2: think it's about time for training to be done. I 478 00:27:57,280 --> 00:28:00,320 Speaker 2: need her back, man. She's been traveling the country with me. 479 00:28:00,400 --> 00:28:04,440 Speaker 2: She's good with people. She's just a great dog. She's 480 00:28:04,480 --> 00:28:06,879 Speaker 2: also a good trap line dog. Man. She finds coyotes, 481 00:28:06,880 --> 00:28:08,840 Speaker 2: scats and you'urine posts and all that kind of stuff 482 00:28:08,880 --> 00:28:13,959 Speaker 2: for me. But yeah, I mean, just she's she's a companion, 483 00:28:14,000 --> 00:28:17,399 Speaker 2: she's a tool, she's a hunting partner, and she helps 484 00:28:17,440 --> 00:28:19,080 Speaker 2: me be more effective at that part of my. 485 00:28:19,160 --> 00:28:23,320 Speaker 1: Job keeping coyotes in check, keeping their population numbers in 486 00:28:23,440 --> 00:28:27,200 Speaker 1: check is is serving what greater purpose? 487 00:28:28,080 --> 00:28:32,360 Speaker 2: Well? And that's I don't want to say that it's 488 00:28:32,400 --> 00:28:36,200 Speaker 2: not keeping the numbers in check because people typically aren't 489 00:28:36,200 --> 00:28:39,520 Speaker 2: going to harvest enough coyotes to keep their numbers in check. Okay, 490 00:28:39,800 --> 00:28:44,720 Speaker 2: it's more about if you're thinking about a greater purpose. Yes, 491 00:28:44,840 --> 00:28:47,880 Speaker 2: we are playing a role in wildlife management, and when 492 00:28:47,880 --> 00:28:51,480 Speaker 2: we're taking out those problem coyotes, we are. We are 493 00:28:51,520 --> 00:28:54,480 Speaker 2: providing a service to livestock producers and that sort of 494 00:28:54,520 --> 00:29:00,160 Speaker 2: thing urban residents sometimes, but you know, we we are. 495 00:29:00,960 --> 00:29:05,280 Speaker 2: We are providing so much of a greater purpose as 496 00:29:05,360 --> 00:29:08,960 Speaker 2: hunters and trappers by all of the things that we do, 497 00:29:09,200 --> 00:29:12,240 Speaker 2: the money that we pump into local economies, the service 498 00:29:12,280 --> 00:29:15,920 Speaker 2: that we provide through population regulation where coyotes that that 499 00:29:16,680 --> 00:29:18,680 Speaker 2: you know, depending on who you talk to, they may 500 00:29:18,760 --> 00:29:23,200 Speaker 2: not hold that up right, but you know, the money 501 00:29:23,240 --> 00:29:26,800 Speaker 2: that goes back into conservation of all species, from what 502 00:29:26,880 --> 00:29:31,480 Speaker 2: we spend on on the calls, the camo, the guns, 503 00:29:31,520 --> 00:29:34,800 Speaker 2: the ammunition, all that that's the stuff that funds conservation. 504 00:29:34,920 --> 00:29:38,280 Speaker 2: And then just being a part of that broader community uh, 505 00:29:38,480 --> 00:29:40,840 Speaker 2: and I think that, you know, the big thing that 506 00:29:42,000 --> 00:29:45,239 Speaker 2: I sure hope people think about from this. I'm not 507 00:29:45,320 --> 00:29:48,040 Speaker 2: telling you don't hunt coyotes. If you like to hunt coyotes, 508 00:29:48,840 --> 00:29:52,760 Speaker 2: if you're doing it for deer, then go manage deer, right, 509 00:29:53,160 --> 00:29:55,600 Speaker 2: But if you like hunting coyotes, hunt coyotes because you 510 00:29:55,680 --> 00:29:59,960 Speaker 2: like coyotes. They are an incredibly fun species to hunt 511 00:30:00,120 --> 00:30:04,680 Speaker 2: and trapped. They're smart, They're just they're a cool species, absolutely, yeah, 512 00:30:04,760 --> 00:30:10,400 Speaker 2: And they are a formidable opponent because they're smart, they're wary. 513 00:30:10,480 --> 00:30:13,400 Speaker 1: You know. Yeah, they're going to see lots of evidence 514 00:30:13,480 --> 00:30:16,360 Speaker 1: of that here next year when this film comes out there. 515 00:30:16,400 --> 00:30:20,760 Speaker 1: They are very cool to interact with anything as we 516 00:30:20,800 --> 00:30:24,360 Speaker 1: close out this thing, anything that you want to touch 517 00:30:24,400 --> 00:30:27,560 Speaker 1: on before before we close the show out, Doctor. 518 00:30:27,440 --> 00:30:30,560 Speaker 2: We talked a little bit about livestock damage, but I 519 00:30:30,640 --> 00:30:33,480 Speaker 2: want to make sure that folks don't think I'm minimizing that, 520 00:30:34,680 --> 00:30:37,280 Speaker 2: you know, and if we calves are the thing that 521 00:30:37,320 --> 00:30:39,760 Speaker 2: people talks about the most. Cots probably have more of 522 00:30:39,800 --> 00:30:43,360 Speaker 2: an impact on sheep and goats than anything. You know, 523 00:30:43,520 --> 00:30:46,480 Speaker 2: Predator losses can be thirty to forty percent when we're 524 00:30:46,480 --> 00:30:50,880 Speaker 2: looking at sheep and goats. Yeah, whereas with cattle, if 525 00:30:50,920 --> 00:30:54,120 Speaker 2: we're looking at Kansas, it's like it's less than five 526 00:30:54,160 --> 00:30:56,080 Speaker 2: percent of the calves that are lost in a given 527 00:30:56,160 --> 00:30:59,560 Speaker 2: year are lost to predators. Coyotes are responsible for most 528 00:30:59,600 --> 00:31:03,200 Speaker 2: of that. One of the things that you mentioned to 529 00:31:03,240 --> 00:31:05,200 Speaker 2: me was wanting to correct something that you had said 530 00:31:05,200 --> 00:31:09,280 Speaker 2: in a previous episode, and you said that eighty four 531 00:31:09,360 --> 00:31:12,960 Speaker 2: percent of the calf losses in Kansas were due to coyotes. Yes, 532 00:31:13,320 --> 00:31:16,360 Speaker 2: and the difference is and that's one of those things 533 00:31:16,360 --> 00:31:20,800 Speaker 2: about interpreting this. These big stats print outs, right, So 534 00:31:21,120 --> 00:31:24,680 Speaker 2: about a little less than five percent of calf losses 535 00:31:24,680 --> 00:31:28,760 Speaker 2: in Kansas reported by producers are due to predators. Eighty 536 00:31:28,840 --> 00:31:33,000 Speaker 2: four percent of that five percent is due to coyotes. 537 00:31:33,080 --> 00:31:34,760 Speaker 1: That's where I got that number. Yeah. 538 00:31:34,880 --> 00:31:40,160 Speaker 2: Yeah, But at the same time, at twenty fifteen market values, 539 00:31:40,720 --> 00:31:44,200 Speaker 2: the calves lost, the cattle lost, and the cattle that 540 00:31:44,240 --> 00:31:46,680 Speaker 2: were injured but not killed but had to be put 541 00:31:46,760 --> 00:31:50,360 Speaker 2: down by predators in Kansas amounts to about four million 542 00:31:50,880 --> 00:31:53,240 Speaker 2: in twenty sixteen market values. 543 00:31:54,000 --> 00:31:54,360 Speaker 1: Wow. 544 00:31:54,400 --> 00:31:56,640 Speaker 2: I did a calculation last night, and I don't know 545 00:31:56,640 --> 00:31:59,080 Speaker 2: how correct this is, but if we look at the 546 00:31:59,120 --> 00:32:03,960 Speaker 2: market now versus then it's about double Wow. So somewhere 547 00:32:04,000 --> 00:32:08,920 Speaker 2: between six and nine million is what that value is, 548 00:32:09,000 --> 00:32:13,160 Speaker 2: even at only less than five percent of calves being 549 00:32:13,240 --> 00:32:16,360 Speaker 2: lost to predators, and coyotes are responsible for about eighty 550 00:32:16,400 --> 00:32:17,200 Speaker 2: four percent of that. 551 00:32:17,320 --> 00:32:19,160 Speaker 1: So you look at that five percent and you think, well, 552 00:32:19,160 --> 00:32:20,719 Speaker 1: that's not near as bad as I was. And then 553 00:32:20,760 --> 00:32:23,880 Speaker 1: you look at nine million dollars or possibly nine million, 554 00:32:24,320 --> 00:32:28,080 Speaker 1: and it's a pretty big effect. Yeah, for sure. Absolutely, Well, 555 00:32:28,160 --> 00:32:30,960 Speaker 1: I learned some stuff. I relearned some stuff. I appreciate 556 00:32:31,040 --> 00:32:35,200 Speaker 1: you being here. I hope the folks enjoyed this different 557 00:32:35,280 --> 00:32:37,880 Speaker 1: kind of format. It's not just kind of a special 558 00:32:37,960 --> 00:32:39,760 Speaker 1: thing that we did because I wanted to talk to 559 00:32:39,800 --> 00:32:45,000 Speaker 1: doctor Drew because I'm so interested in these in the coyotes, 560 00:32:45,160 --> 00:32:48,880 Speaker 1: and you know, it's I'm an old dog learning new 561 00:32:48,920 --> 00:32:52,160 Speaker 1: tricks here and learning new things. But I appreciate it. Drew. 562 00:32:52,200 --> 00:32:54,960 Speaker 1: Tell me where we could find folks that are listening, 563 00:32:55,040 --> 00:32:59,440 Speaker 1: can find other information or videos, or where can they 564 00:32:59,480 --> 00:33:00,480 Speaker 1: find you? Sure? 565 00:33:00,560 --> 00:33:03,840 Speaker 2: Sure? So we have a podcast that comes out every 566 00:33:03,960 --> 00:33:07,360 Speaker 2: every other week at the Pawn Specialists from k State, 567 00:33:07,440 --> 00:33:09,560 Speaker 2: and I are He's fishery specialist is probably a more 568 00:33:09,560 --> 00:33:12,960 Speaker 2: appropriate term. It's called Finns fir and feathers. Uh. It's 569 00:33:13,000 --> 00:33:16,560 Speaker 2: everywhere you can get podcasts. It's also on our YouTube channel. 570 00:33:17,320 --> 00:33:21,280 Speaker 2: Ks r E Wildlife Management is our YouTube channel and that, 571 00:33:21,640 --> 00:33:23,560 Speaker 2: like I said, the podcast is there, but we got 572 00:33:23,640 --> 00:33:28,360 Speaker 2: lots of other wildlife management content there. One of the 573 00:33:28,400 --> 00:33:32,080 Speaker 2: only places you can find videos that are research based 574 00:33:32,240 --> 00:33:35,640 Speaker 2: about dealing with wildlife damage. There's a few other spots 575 00:33:35,640 --> 00:33:37,200 Speaker 2: out there, but that's one of the main ones. 576 00:33:37,400 --> 00:33:42,200 Speaker 1: Hey, as stewards of this creation that we're all blessed 577 00:33:42,200 --> 00:33:44,840 Speaker 1: to have, I encourage you to look these up. These 578 00:33:44,840 --> 00:33:47,560 Speaker 1: little Riva's going to put the links in the show 579 00:33:47,600 --> 00:33:50,080 Speaker 1: notes on Spotify and they'll put the links on the 580 00:33:50,200 --> 00:33:52,760 Speaker 1: on the YouTube channel as well. But check them out. 581 00:33:52,840 --> 00:33:56,440 Speaker 1: It's great stuff. Learn something. Let's all take care of 582 00:33:56,480 --> 00:33:59,560 Speaker 1: these these critters ourselves. Thank you doctor, thank you sir, 583 00:34:00,160 --> 00:34:02,880 Speaker 1: thank you all for listening. And until next week. This 584 00:34:03,000 --> 00:34:05,840 Speaker 1: is Brent Reeve. You've signing off. Yeah, be careful.