1 00:00:02,880 --> 00:00:06,440 Speaker 1: Welcome to the Wired to Hunt podcast, your home for 2 00:00:06,519 --> 00:00:11,479 Speaker 1: deer hunting news, stories and strategies, and now your host, 3 00:00:11,880 --> 00:00:16,599 Speaker 1: Mark Kenyon. Welcome to the Wired to Hunt podcast. I'm 4 00:00:16,600 --> 00:00:19,759 Speaker 1: your host, Mark Kenyon. This episode number two, d and twelve, 5 00:00:19,800 --> 00:00:22,840 Speaker 1: and today on the show, we're joined by Bronson Strickland 6 00:00:22,920 --> 00:00:26,080 Speaker 1: and Carter Neo Meyer to discuss the impacts of and 7 00:00:26,160 --> 00:00:49,000 Speaker 1: dynamics between wolves, coyotes, prey populations and hunters. All right, folks, 8 00:00:49,120 --> 00:00:53,680 Speaker 1: welcome to the Wired to Hunt podcast. And today we've 9 00:00:53,680 --> 00:00:57,880 Speaker 1: got a particularly interesting and unique episode for you as 10 00:00:57,920 --> 00:01:01,760 Speaker 1: we are waiting into the murky water of predators, in 11 00:01:01,800 --> 00:01:05,600 Speaker 1: particular wolves and coyotes, and we're discussing the dynamic between 12 00:01:05,640 --> 00:01:08,800 Speaker 1: these predators and US hunters. Now, I've want to do 13 00:01:08,840 --> 00:01:11,440 Speaker 1: a podcast about predators for a long time, but I've 14 00:01:11,480 --> 00:01:14,280 Speaker 1: never really known exactly you're the right way to do it, 15 00:01:14,400 --> 00:01:18,840 Speaker 1: or the right people to talk to coyotes and wolves 16 00:01:18,840 --> 00:01:21,119 Speaker 1: and other predators. As many of you know, they stir 17 00:01:21,200 --> 00:01:23,200 Speaker 1: up a lot of emotions. You know, this is true 18 00:01:23,240 --> 00:01:26,319 Speaker 1: outside of the hunting community, but especially within and it's 19 00:01:26,319 --> 00:01:29,280 Speaker 1: been this way for many thousands of years. Likely you know, 20 00:01:29,280 --> 00:01:32,480 Speaker 1: if you go way back in deep history. Early on, 21 00:01:33,240 --> 00:01:36,120 Speaker 1: big predators were danger to the lives of early humans, 22 00:01:36,200 --> 00:01:38,919 Speaker 1: and then eventually they're viewed as competition for the scarce 23 00:01:39,040 --> 00:01:43,199 Speaker 1: resources of food, so so built into our human DNA. 24 00:01:43,400 --> 00:01:46,160 Speaker 1: For many, many generations, we've had this built in set 25 00:01:46,200 --> 00:01:50,840 Speaker 1: of negative associations with these animals. Now, if you fast 26 00:01:50,840 --> 00:01:54,200 Speaker 1: forward through time up to the settling of the New World, 27 00:01:54,520 --> 00:01:58,000 Speaker 1: you've got this landscape now that was jam packed with predators, 28 00:01:58,080 --> 00:02:01,800 Speaker 1: and again humans were in competition with them, and so, 29 00:02:01,840 --> 00:02:04,880 Speaker 1: starting in the east and gradually moving west, our ancestors 30 00:02:04,920 --> 00:02:08,960 Speaker 1: slowly went about knocking these predators back in an effort 31 00:02:08,960 --> 00:02:11,600 Speaker 1: to make their lives easier or to eliminate a perceived 32 00:02:11,680 --> 00:02:14,560 Speaker 1: danger or inconvenience. And they did this, you know, as 33 00:02:14,560 --> 00:02:17,640 Speaker 1: many of us know now, they did this with disturbing effectiveness. 34 00:02:17,680 --> 00:02:20,640 Speaker 1: This kind of wholesale war and predators that began the 35 00:02:20,639 --> 00:02:24,919 Speaker 1: eighteen hundreds led to hundreds of thousands of bounties being 36 00:02:24,960 --> 00:02:27,959 Speaker 1: claimed on wolves and coyotes, led to the use of 37 00:02:28,000 --> 00:02:32,480 Speaker 1: the widespread use of poison to to knock out massive, 38 00:02:32,520 --> 00:02:37,040 Speaker 1: massive numbers of coyotes and wolves and bobcats and and 39 00:02:37,080 --> 00:02:41,360 Speaker 1: all sorts of other critters. Even mange was purposely introduced 40 00:02:41,400 --> 00:02:45,120 Speaker 1: to wild animal populations to try to eliminate them. So 41 00:02:45,200 --> 00:02:47,840 Speaker 1: after decades of this, at least when it came to wolves, 42 00:02:47,919 --> 00:02:51,560 Speaker 1: our predecessors largely achieved their goal, you know, by almost 43 00:02:51,600 --> 00:02:54,600 Speaker 1: exterminating the entire wolf population in the lower forty eight 44 00:02:54,639 --> 00:02:59,560 Speaker 1: States coyotes. Hundreds and hundreds of thousands of coyotes were killed, 45 00:02:59,560 --> 00:03:01,760 Speaker 1: but they of more difficult to actually get rid of, 46 00:03:02,280 --> 00:03:05,040 Speaker 1: given some of the unique adaptabilities and the fact they 47 00:03:05,040 --> 00:03:07,040 Speaker 1: have some of these built in traits that allow them 48 00:03:07,080 --> 00:03:11,520 Speaker 1: to actually increase their reproductive capabilities and recalonize new areas 49 00:03:11,520 --> 00:03:14,600 Speaker 1: where other populations have been killed out. So so this 50 00:03:14,639 --> 00:03:17,679 Speaker 1: actually ended up leading to coyotes not only surviving the onslaught, 51 00:03:17,720 --> 00:03:21,240 Speaker 1: but also expanding their range farther east and west as 52 00:03:21,280 --> 00:03:23,120 Speaker 1: they filled in gaps that were opened up by the 53 00:03:23,160 --> 00:03:28,280 Speaker 1: removal of wolves. But long story short, this war on 54 00:03:28,360 --> 00:03:34,040 Speaker 1: predators led to dramatically changed predator levels across the country. Now, 55 00:03:34,040 --> 00:03:37,040 Speaker 1: if you fast forward through time again to today, with 56 00:03:37,160 --> 00:03:41,120 Speaker 1: changing societal values and an increased focus on restoring natural 57 00:03:41,200 --> 00:03:45,320 Speaker 1: ecosystems and native wildlife, predators such as wolves have been 58 00:03:45,320 --> 00:03:47,880 Speaker 1: able to restake a claim in parts of the lower 59 00:03:47,920 --> 00:03:51,360 Speaker 1: forty eight, and you know, both coyotes and wolves to 60 00:03:51,400 --> 00:03:54,520 Speaker 1: a lower extent are now present across wide swaths of 61 00:03:54,520 --> 00:03:58,960 Speaker 1: the country. Once again, though, just like with other early ancestors, 62 00:03:58,960 --> 00:04:02,240 Speaker 1: this is causing pension. You know, some people simply don't 63 00:04:02,280 --> 00:04:05,640 Speaker 1: want these critters around, even hunters. And again, I think 64 00:04:05,680 --> 00:04:08,520 Speaker 1: this comes down to competition in a lot of cases. 65 00:04:08,560 --> 00:04:11,280 Speaker 1: So that brings us to this podcast today and why 66 00:04:11,320 --> 00:04:14,760 Speaker 1: I wanted to put these conversations out there as a 67 00:04:14,760 --> 00:04:17,160 Speaker 1: as a hunter myself, of course, and I'll admit a 68 00:04:17,200 --> 00:04:19,120 Speaker 1: little bit of my bias here, but as a person 69 00:04:19,160 --> 00:04:22,560 Speaker 1: who believes in conservation and as our role as hunters 70 00:04:23,040 --> 00:04:26,240 Speaker 1: in conservation, I want to hear some of the vitriol 71 00:04:26,440 --> 00:04:29,760 Speaker 1: today around predators. It concerns me a little bit because 72 00:04:30,640 --> 00:04:34,680 Speaker 1: and this is just my opinion, um, but predators the 73 00:04:34,680 --> 00:04:35,880 Speaker 1: way I see it, in the way a lot of 74 00:04:35,920 --> 00:04:39,040 Speaker 1: people see it, in the way biologists see it. Predators 75 00:04:39,120 --> 00:04:41,840 Speaker 1: just as much as deer or elk or we human hunters. 76 00:04:42,240 --> 00:04:44,680 Speaker 1: They're part of the system, and we like to talk 77 00:04:44,720 --> 00:04:47,640 Speaker 1: this big game as hunters that were the greatest conservationists 78 00:04:47,640 --> 00:04:50,080 Speaker 1: in the land because of all we do for wildlife 79 00:04:50,120 --> 00:04:53,280 Speaker 1: and and access taxes. We pay the pay for conservation work. 80 00:04:53,720 --> 00:04:55,919 Speaker 1: But I'm worried that if we care about and protect 81 00:04:56,000 --> 00:05:00,120 Speaker 1: one species, be it deer or elk, or pheasants or 82 00:05:00,120 --> 00:05:01,880 Speaker 1: turkeys or whatever, if we're going to protect and care 83 00:05:01,920 --> 00:05:05,320 Speaker 1: about that species but then advocate for the total destruction 84 00:05:05,360 --> 00:05:08,320 Speaker 1: of another, I think we lose some credibility there. And 85 00:05:08,360 --> 00:05:11,000 Speaker 1: it seems in my opinion that maybe there's maybe there's 86 00:05:11,000 --> 00:05:12,760 Speaker 1: some kind of middle ground though maybe it doesn't have 87 00:05:12,839 --> 00:05:17,880 Speaker 1: to be dear or predators. Maybe there's some way that 88 00:05:17,920 --> 00:05:20,720 Speaker 1: these two things can coexist and hunters too, So rather 89 00:05:20,760 --> 00:05:23,480 Speaker 1: than looking at coyotes or wolves as the scourge of 90 00:05:23,520 --> 00:05:26,080 Speaker 1: the earth, maybe there's a different way we can look 91 00:05:26,120 --> 00:05:29,320 Speaker 1: at and relate to these animals when it comes to 92 00:05:29,480 --> 00:05:31,800 Speaker 1: when it comes to these creators, there's so much emotion 93 00:05:32,600 --> 00:05:37,320 Speaker 1: and rumor and worry in some cases miss misinformation out there. 94 00:05:37,960 --> 00:05:39,680 Speaker 1: And of course, you know this isn't just coming from 95 00:05:39,760 --> 00:05:42,400 Speaker 1: hunters or those who have concerns about predators. There is 96 00:05:42,440 --> 00:05:45,240 Speaker 1: also a lot of emotion and hyperbole coming from other 97 00:05:45,279 --> 00:05:48,920 Speaker 1: parties on sometimes the other side of these issues too. 98 00:05:49,320 --> 00:05:51,760 Speaker 1: But but either way, from either side, the way you 99 00:05:51,800 --> 00:05:54,320 Speaker 1: look at this, so often these animals are looked at 100 00:05:54,360 --> 00:05:58,880 Speaker 1: either as gods or devils, either divine or devilish. But 101 00:05:59,000 --> 00:06:04,679 Speaker 1: maybe coyotes, wolves are not good or evil. Maybe they're 102 00:06:04,720 --> 00:06:09,600 Speaker 1: just animals. Maybe they're just another piece of the system, 103 00:06:09,680 --> 00:06:13,280 Speaker 1: just like the deer and the turkeys and the raccoons 104 00:06:13,320 --> 00:06:18,039 Speaker 1: and turtles. And because of that, rather than worshiping or 105 00:06:18,120 --> 00:06:22,200 Speaker 1: demonizing these animals, maybe the way forward is just learning 106 00:06:22,240 --> 00:06:25,920 Speaker 1: about them and understanding how they fit into this millions 107 00:06:25,920 --> 00:06:28,599 Speaker 1: of years old system, and then learning how we can 108 00:06:28,600 --> 00:06:32,840 Speaker 1: fit into that system alongside of them. Maybe hunters and 109 00:06:32,880 --> 00:06:37,440 Speaker 1: predators don't need to be an either or or maybe 110 00:06:38,400 --> 00:06:40,400 Speaker 1: some of you might be thinking, maybe I'm nuts. I 111 00:06:40,440 --> 00:06:42,359 Speaker 1: can't stay for sure. I might be nuts. But in 112 00:06:42,400 --> 00:06:46,760 Speaker 1: today's episode, I wanted to present two conversations that explore 113 00:06:46,800 --> 00:06:50,720 Speaker 1: this topic, that explore this idea of predators and our 114 00:06:50,720 --> 00:06:53,760 Speaker 1: relationship with them as hunters, and as I alluded to, 115 00:06:54,160 --> 00:06:56,120 Speaker 1: my goal here is to try and address some of 116 00:06:56,160 --> 00:06:58,800 Speaker 1: the worries and the rumors around predators and then kind 117 00:06:58,800 --> 00:07:01,000 Speaker 1: of level set. I want to kind of reality check 118 00:07:01,120 --> 00:07:03,680 Speaker 1: what's going on out there, what we as hunters need 119 00:07:03,680 --> 00:07:06,960 Speaker 1: to understand about predators and their impacts on wildlife and 120 00:07:07,000 --> 00:07:09,880 Speaker 1: our hunting, and what this all means for us going forward. 121 00:07:10,120 --> 00:07:11,760 Speaker 1: That's that's kind of what I want to achieve with 122 00:07:11,840 --> 00:07:14,520 Speaker 1: this conversation. So to do that, we have two different guests. 123 00:07:14,600 --> 00:07:16,880 Speaker 1: This is kind of a two parter. First off, we 124 00:07:16,920 --> 00:07:20,880 Speaker 1: have Bronson Strickland, and Bronson's a wildlife biologist and extension 125 00:07:20,880 --> 00:07:25,640 Speaker 1: professor at Mississippi State University specializing in dear biology and research. 126 00:07:26,000 --> 00:07:27,800 Speaker 1: He's been in the show before. Hopefully you heard that 127 00:07:27,840 --> 00:07:31,360 Speaker 1: past episode. It's a great one. He's an incredible resource 128 00:07:31,440 --> 00:07:33,560 Speaker 1: of information. But I wanted Bronson to come on the 129 00:07:33,600 --> 00:07:36,720 Speaker 1: show today to help us talk about coyotes because he's 130 00:07:36,760 --> 00:07:39,920 Speaker 1: done a lot of looking into the interactions between coyotes 131 00:07:40,000 --> 00:07:43,720 Speaker 1: and deer. So Bronson's gonna help us understand what the 132 00:07:43,760 --> 00:07:46,920 Speaker 1: real impacts of coyotes are on white tails, how to 133 00:07:47,000 --> 00:07:49,480 Speaker 1: determine if coyotes are having an impact on your local 134 00:07:49,480 --> 00:07:52,400 Speaker 1: white tail population, and then finally, if they are, what 135 00:07:52,480 --> 00:07:55,560 Speaker 1: are some reasonable steps to take to to manage that issue. 136 00:07:56,040 --> 00:07:58,720 Speaker 1: And then from there we're going to switch gears and 137 00:07:58,760 --> 00:08:01,960 Speaker 1: we're gonna go from coyotes over to wolves. Now, I 138 00:08:02,000 --> 00:08:05,400 Speaker 1: did this interview with Carter nee Meyer while I was 139 00:08:05,480 --> 00:08:08,040 Speaker 1: out in Boise, Idaho for the back Country Hunters and 140 00:08:08,080 --> 00:08:11,720 Speaker 1: Anglers Rendezvous a few weeks ago, and Carter has a 141 00:08:11,800 --> 00:08:15,920 Speaker 1: really interesting perspective on the issue of wolves because he 142 00:08:16,120 --> 00:08:19,440 Speaker 1: was a government trapper and predator control agent and then 143 00:08:19,480 --> 00:08:22,440 Speaker 1: eventually was pulled into the work of the reintroduction of 144 00:08:22,440 --> 00:08:24,960 Speaker 1: wolves to the Rocky Mountain West in the nineties, and 145 00:08:24,960 --> 00:08:28,120 Speaker 1: then afterwards he was tasked with managing and sometimes killing 146 00:08:28,160 --> 00:08:30,600 Speaker 1: those wolves in later years. So he had to work 147 00:08:30,600 --> 00:08:34,600 Speaker 1: with biologists and ranchers and hunters and environmentalists kind of 148 00:08:34,640 --> 00:08:37,720 Speaker 1: everyone on all sides of the wolf issue, and coming 149 00:08:37,720 --> 00:08:40,000 Speaker 1: out of that, he has this really interesting perspective on 150 00:08:40,080 --> 00:08:44,040 Speaker 1: predators and humans and the dynamics between the two. So 151 00:08:44,080 --> 00:08:47,760 Speaker 1: in my conversation with Carter, we talked about this history, 152 00:08:47,800 --> 00:08:51,200 Speaker 1: We talked about the wolf reintroduction and subsequent events. We 153 00:08:51,280 --> 00:08:53,679 Speaker 1: talked about the impacts of wolves, and then kind of 154 00:08:53,720 --> 00:08:57,200 Speaker 1: get Carter's opinions on you know, how wolves and hunters 155 00:08:57,559 --> 00:09:01,360 Speaker 1: and other humans can can kind of occupy the same 156 00:09:01,400 --> 00:09:05,640 Speaker 1: space moving forward, How that's possible if so? Um So 157 00:09:05,679 --> 00:09:08,920 Speaker 1: that's a really interesting one too. Now, with both of 158 00:09:08,920 --> 00:09:11,880 Speaker 1: these conversations, my hope is that these discussions and guests 159 00:09:11,920 --> 00:09:13,360 Speaker 1: can help us all just do a little bit of 160 00:09:13,400 --> 00:09:16,680 Speaker 1: thinking as hunters ourselves and as conservationists, you know, you know, 161 00:09:16,720 --> 00:09:19,800 Speaker 1: how can we or should we be thinking about predators? 162 00:09:20,160 --> 00:09:22,360 Speaker 1: How can we live with prators? What do predators mean 163 00:09:22,400 --> 00:09:25,760 Speaker 1: for hunting? What does all of this mean? Um? You know, 164 00:09:25,800 --> 00:09:28,160 Speaker 1: you might not agree with everything said in today's episode, 165 00:09:28,360 --> 00:09:31,280 Speaker 1: and there's likely going to be some ideas or opinions 166 00:09:31,320 --> 00:09:33,360 Speaker 1: that are different than yours, But I don't think we 167 00:09:33,400 --> 00:09:35,360 Speaker 1: need to look at that as a bad thing. You know, 168 00:09:35,400 --> 00:09:40,320 Speaker 1: with partisan cable news, Facebook fees that are specially curated 169 00:09:40,360 --> 00:09:43,440 Speaker 1: to reflect back just the only only the things that 170 00:09:43,520 --> 00:09:46,120 Speaker 1: we already like and believe, it's sometimes easier to get 171 00:09:46,120 --> 00:09:48,280 Speaker 1: lost in this kind of echo chamber of our own 172 00:09:48,320 --> 00:09:52,280 Speaker 1: opinions were surrounded by nothing but our own worldview. I 173 00:09:52,320 --> 00:09:55,079 Speaker 1: think though, that when this happens, we kind of lose 174 00:09:55,080 --> 00:09:58,120 Speaker 1: out on something important in life, which, in my opinion, 175 00:09:58,240 --> 00:10:00,960 Speaker 1: is this ability to hear and learn about and process 176 00:10:01,040 --> 00:10:03,200 Speaker 1: new ideas in different ways of looking at the world, 177 00:10:03,480 --> 00:10:05,440 Speaker 1: and then being able to move forward, you know, with 178 00:10:05,520 --> 00:10:08,840 Speaker 1: those new ideas, maybe accepting some, maybe rejecting others, but 179 00:10:09,400 --> 00:10:12,520 Speaker 1: you know, ultimately growing in one way or another. So 180 00:10:13,040 --> 00:10:15,200 Speaker 1: I don't know about you. But I'm a fan of 181 00:10:15,240 --> 00:10:18,000 Speaker 1: hearing new perspectives and at least getting to consider them 182 00:10:18,200 --> 00:10:21,040 Speaker 1: for myself. So that's what we're gonna do today. That's 183 00:10:21,080 --> 00:10:25,120 Speaker 1: what I'm hoping we could achieve today. Before I ramble 184 00:10:25,120 --> 00:10:27,480 Speaker 1: on any further than I guess, we need to get 185 00:10:27,480 --> 00:10:29,360 Speaker 1: this party started. We had to get going with this. 186 00:10:29,480 --> 00:10:32,160 Speaker 1: It's a long episode, so I hope you can maybe 187 00:10:32,200 --> 00:10:34,120 Speaker 1: come back to us one over a couple of drives 188 00:10:34,240 --> 00:10:36,600 Speaker 1: or a couple of days at the gym, um, because 189 00:10:36,600 --> 00:10:38,840 Speaker 1: it does stretch out over two hours, but I hope 190 00:10:38,880 --> 00:10:41,800 Speaker 1: it's going to be worthwhile for you. I'm gonna leave 191 00:10:41,800 --> 00:10:44,400 Speaker 1: you with one last quick recommendation, which is to go 192 00:10:44,480 --> 00:10:48,520 Speaker 1: and read the essay titled Thinking like a Mountain by 193 00:10:48,600 --> 00:10:51,720 Speaker 1: Aldo Leopold. Uh. This is an essay that actually gets 194 00:10:51,760 --> 00:10:54,400 Speaker 1: brought up in both of these interviews, once by myself 195 00:10:54,480 --> 00:10:56,800 Speaker 1: once by the guest um, and I think it's one 196 00:10:56,840 --> 00:10:58,840 Speaker 1: that has influenced a lot of people when it comes 197 00:10:58,880 --> 00:11:03,440 Speaker 1: to this topic of preditors and ecosystems and humans. And 198 00:11:03,520 --> 00:11:05,720 Speaker 1: you can actually just go out online and google the title. 199 00:11:05,800 --> 00:11:07,959 Speaker 1: You can find it online to read and full for free. 200 00:11:08,040 --> 00:11:09,840 Speaker 1: But I thought I would leave you here with just 201 00:11:09,880 --> 00:11:12,559 Speaker 1: a quick passage from that essay that I'll read for you, 202 00:11:13,040 --> 00:11:15,880 Speaker 1: and then we'll get into our conversations with Bronson and Carter. 203 00:11:16,160 --> 00:11:19,880 Speaker 1: So here from Thinking Like a Mountain by Eldo Leopold, 204 00:11:20,760 --> 00:11:23,920 Speaker 1: I quote, in those days, we had never heard of 205 00:11:23,960 --> 00:11:27,120 Speaker 1: passing up a chance to kill a wolf. In a second, 206 00:11:27,160 --> 00:11:30,280 Speaker 1: we're pumping lead into the pack, both more excitement than accuracy. 207 00:11:30,480 --> 00:11:33,040 Speaker 1: How to aim as steep downhill shot is always confusing. 208 00:11:33,520 --> 00:11:35,840 Speaker 1: When our rifles were empty, the old wolf was down, 209 00:11:35,960 --> 00:11:38,959 Speaker 1: and a pup was dragging a leg into impassable slide rocks. 210 00:11:40,000 --> 00:11:41,840 Speaker 1: We reached the old wolf in time to watch a 211 00:11:41,880 --> 00:11:45,120 Speaker 1: fierce green fire dying in her eyes. I realized then, 212 00:11:45,240 --> 00:11:47,320 Speaker 1: and have known ever since, there was something new to 213 00:11:47,360 --> 00:11:49,960 Speaker 1: me in those eyes, something known only to her into 214 00:11:49,960 --> 00:11:52,839 Speaker 1: the mountain. I was young then and full of trigger itch. 215 00:11:53,320 --> 00:11:56,120 Speaker 1: I thought that because fewer wolves meant more dear, that 216 00:11:56,160 --> 00:11:59,440 Speaker 1: no wolves would mean Hunter's paradise. But after seeing the 217 00:11:59,480 --> 00:12:03,040 Speaker 1: green or die, I sensed that neither the wolf northern 218 00:12:03,040 --> 00:12:10,800 Speaker 1: Mountain agreed with such of you end quote. All right 219 00:12:10,840 --> 00:12:14,760 Speaker 1: with me now again on the podcast is Bronson Strickland. 220 00:12:14,760 --> 00:12:17,360 Speaker 1: Welcome back to the show. Bronson, Thank you so much 221 00:12:17,360 --> 00:12:19,800 Speaker 1: for having me. Glad to be back. Yeah, me and 222 00:12:19,880 --> 00:12:22,520 Speaker 1: Dan when we chatted with you, if it was last 223 00:12:22,559 --> 00:12:25,199 Speaker 1: year or two years ago, it was just a great conversation. 224 00:12:25,200 --> 00:12:26,920 Speaker 1: I've been wanting to have you back for a while, 225 00:12:27,280 --> 00:12:30,600 Speaker 1: and Um, I really should have brought you back on 226 00:12:30,679 --> 00:12:33,120 Speaker 1: to talk about deer since you have so much to 227 00:12:33,160 --> 00:12:36,480 Speaker 1: share in that world. UM, but I actually wanted to 228 00:12:36,559 --> 00:12:39,439 Speaker 1: talk to you today about something different, Bronson, and I 229 00:12:39,480 --> 00:12:41,240 Speaker 1: hope you're gonna be okay with that. I'm gonna take 230 00:12:41,280 --> 00:12:45,440 Speaker 1: you away from our favorite animal and talk about something 231 00:12:45,480 --> 00:12:48,840 Speaker 1: that does impact that. UM. And I was hoping to 232 00:12:48,880 --> 00:12:53,240 Speaker 1: talk to you about predators, in particular coyotes, because there's 233 00:12:53,280 --> 00:12:56,000 Speaker 1: there's a lot of noise, there's a lot of opinions, 234 00:12:56,040 --> 00:12:58,400 Speaker 1: there's a lot of worry, there's a lot of hubbub 235 00:12:58,800 --> 00:13:02,960 Speaker 1: it seems every few years, depending on where you're at, 236 00:13:03,040 --> 00:13:06,840 Speaker 1: about coyotes and their impacts on deer and deer management. 237 00:13:07,040 --> 00:13:08,959 Speaker 1: And so I kind of wanted to have a conversation 238 00:13:09,000 --> 00:13:11,200 Speaker 1: with you to help us kind of level set, like 239 00:13:11,240 --> 00:13:13,840 Speaker 1: what's the reality of this situation, what's happening out there? 240 00:13:13,920 --> 00:13:16,520 Speaker 1: What do we need to know as white tailed deer hunters? 241 00:13:16,960 --> 00:13:21,440 Speaker 1: UM and so with all that being said, Bronson, even 242 00:13:21,440 --> 00:13:23,120 Speaker 1: though your dear guy, do you think you give us 243 00:13:23,160 --> 00:13:26,880 Speaker 1: like a super high level overview of of the coyote 244 00:13:26,920 --> 00:13:29,040 Speaker 1: as a species, maybe a little bit of natural history 245 00:13:29,160 --> 00:13:32,199 Speaker 1: or its current status, anything like that, um, just to 246 00:13:32,280 --> 00:13:34,400 Speaker 1: kind of help us understand this animal more than just 247 00:13:34,800 --> 00:13:37,800 Speaker 1: it's a look kind of tiny wolf looking thing that 248 00:13:37,880 --> 00:13:40,640 Speaker 1: runs around the fields every once in a while. Well, 249 00:13:41,120 --> 00:13:44,680 Speaker 1: I thank you, Mark, I promise you I'll do my best. 250 00:13:44,720 --> 00:13:47,319 Speaker 1: And you know, I studied deer, and I don't really 251 00:13:47,720 --> 00:13:51,240 Speaker 1: you know, study coyotes specifically, except in you know, how 252 00:13:51,280 --> 00:13:55,679 Speaker 1: they're affecting white tail deer um. So in the eastern 253 00:13:55,800 --> 00:14:00,480 Speaker 1: us UM. A lot of people consider the coyote a 254 00:14:00,559 --> 00:14:04,040 Speaker 1: novel you know, predator in the white tail system. And 255 00:14:04,080 --> 00:14:07,200 Speaker 1: it really depends on where you're at geographically. We we 256 00:14:07,240 --> 00:14:10,280 Speaker 1: tend to think of, you know, over over deep time, 257 00:14:10,440 --> 00:14:15,040 Speaker 1: that the coyote was more of the western UH caneid. 258 00:14:15,280 --> 00:14:19,120 Speaker 1: You know, it's involved more in you know, open areas, 259 00:14:19,200 --> 00:14:24,080 Speaker 1: open habitat UH. It's omnivorous and so it's eating fruits 260 00:14:24,120 --> 00:14:26,440 Speaker 1: and things like that as well as small mammals. And 261 00:14:26,480 --> 00:14:29,800 Speaker 1: then you know, it's kind of opportunistic so it's not 262 00:14:29,880 --> 00:14:33,160 Speaker 1: nearly like something like a wolf or you know, cougar 263 00:14:33,240 --> 00:14:35,480 Speaker 1: slash mountain lion, where it's a you know, it's an 264 00:14:35,480 --> 00:14:40,480 Speaker 1: obligate carnivore. It's it's kind of an opportunistic omnivore. And 265 00:14:41,960 --> 00:14:45,560 Speaker 1: so as that species kind of moved from west to east, 266 00:14:45,760 --> 00:14:48,560 Speaker 1: and you know, the best we can tell from from 267 00:14:48,600 --> 00:14:53,240 Speaker 1: anecdotal evidence, genetic evidence, etcetera. You know, it's kind of 268 00:14:53,280 --> 00:14:55,960 Speaker 1: like the way we are seeing the spread of wild 269 00:14:56,000 --> 00:15:03,840 Speaker 1: hart mark up your direction is, uh, it was facilitated 270 00:15:04,240 --> 00:15:07,840 Speaker 1: greatly by human beings, and so there's always gonna be 271 00:15:07,920 --> 00:15:12,680 Speaker 1: natural movement, natural colonization. But some of the studies back 272 00:15:12,720 --> 00:15:15,400 Speaker 1: in the southeast from you know, thirty or so years 273 00:15:15,440 --> 00:15:18,760 Speaker 1: ago showed that a lot of the coyotes were brought 274 00:15:18,800 --> 00:15:23,800 Speaker 1: in and contrary to popular belief, you know, they weren't 275 00:15:23,840 --> 00:15:27,920 Speaker 1: brought in by a state wildlife agency under the cover 276 00:15:28,040 --> 00:15:31,320 Speaker 1: of night. It was brought in by hunters for the 277 00:15:31,360 --> 00:15:35,280 Speaker 1: purpose of hunting, and a lot of them were brought 278 00:15:35,280 --> 00:15:37,920 Speaker 1: into the you know, fox pens or you know things 279 00:15:37,960 --> 00:15:41,240 Speaker 1: like that where people like to run their dogs, uh 280 00:15:41,280 --> 00:15:45,400 Speaker 1: to catch them, and those eventually escape and get loose 281 00:15:45,440 --> 00:15:50,000 Speaker 1: and then over time that's augmented by natural colonization, and 282 00:15:50,040 --> 00:15:53,760 Speaker 1: now we have you know, in the two thousand eighteen, 283 00:15:53,800 --> 00:15:58,000 Speaker 1: we essentially have coyotes everywhere in the eastern United States, 284 00:15:58,240 --> 00:16:03,320 Speaker 1: and we even have coyotes in urban settings. I'm pretty 285 00:16:03,320 --> 00:16:06,360 Speaker 1: sure right now somewhere in Central Park in New York 286 00:16:06,400 --> 00:16:10,400 Speaker 1: there's probably a coyote somewhere. So that just goes to 287 00:16:10,440 --> 00:16:15,120 Speaker 1: show you how how adaptable that species is and more 288 00:16:15,120 --> 00:16:18,320 Speaker 1: than likely it's here to stay. And I don't see 289 00:16:18,360 --> 00:16:22,280 Speaker 1: any anyway at all that, um, we are not going 290 00:16:22,320 --> 00:16:27,480 Speaker 1: to be managing deer, uh with consideration of coyotes and 291 00:16:27,720 --> 00:16:31,000 Speaker 1: anytime in the near future in our lifetime certainly. Yeah, 292 00:16:31,200 --> 00:16:34,320 Speaker 1: they seem to be one of those species kind of 293 00:16:34,360 --> 00:16:39,160 Speaker 1: like deer that has become super adaptable to living with humans, 294 00:16:39,240 --> 00:16:43,160 Speaker 1: unlike most other relatively large mammals that in some cases 295 00:16:43,200 --> 00:16:46,960 Speaker 1: struggle with our encroachment on their habitat and are you know, 296 00:16:47,000 --> 00:16:49,800 Speaker 1: just are are being present in the environment all the 297 00:16:49,800 --> 00:16:53,360 Speaker 1: different things that entails. They've uniquely kind of found a 298 00:16:53,400 --> 00:16:56,840 Speaker 1: way to intertwine themselves within, like you said, even in 299 00:16:56,920 --> 00:17:00,240 Speaker 1: urban areas, kind of like white tailed deer or cockroes 300 00:17:00,560 --> 00:17:02,920 Speaker 1: or rats or these different animals that have made a 301 00:17:02,920 --> 00:17:05,879 Speaker 1: living off of living around humans. UM. They're kind of 302 00:17:05,960 --> 00:17:09,040 Speaker 1: unique in that way, and some people may not like that. 303 00:17:09,240 --> 00:17:11,520 Speaker 1: It might be viewed admirable in some ways too, if 304 00:17:11,520 --> 00:17:15,520 Speaker 1: you're looking at purely as the you know, the evolutionary, 305 00:17:17,080 --> 00:17:21,360 Speaker 1: I don't know creativity that these animals seem to have. UM. 306 00:17:21,400 --> 00:17:25,439 Speaker 1: So that being said, like you've mentioned, coyotes are becoming 307 00:17:25,480 --> 00:17:28,960 Speaker 1: ever more present across the eastern United States, south southeastern 308 00:17:29,119 --> 00:17:32,480 Speaker 1: United States. UM, and we're becoming more aware of this 309 00:17:32,560 --> 00:17:36,719 Speaker 1: is deer hunters too. There's, as you said, a lot 310 00:17:36,760 --> 00:17:39,720 Speaker 1: of work being done to understand the interaction between coyotes 311 00:17:39,760 --> 00:17:43,200 Speaker 1: and deer, and that's something you've worked on a lot before. 312 00:17:43,240 --> 00:17:46,240 Speaker 1: We dive into what the results are of that kind 313 00:17:46,240 --> 00:17:48,360 Speaker 1: of stuff and what the actual impacts are because there's 314 00:17:48,400 --> 00:17:50,919 Speaker 1: a lot of rumors and opinions and ideas of what 315 00:17:50,960 --> 00:17:53,879 Speaker 1: the impacts of kyotes are are on deer. I'm curious 316 00:17:53,880 --> 00:17:56,919 Speaker 1: just to hear what kind of actual studies have been done. 317 00:17:57,160 --> 00:17:59,879 Speaker 1: You know, what are we looking into? How are we 318 00:18:00,040 --> 00:18:02,080 Speaker 1: doing these is? How are we learning about the interactions 319 00:18:02,080 --> 00:18:06,200 Speaker 1: between coyotes and deer and that impact. Yeah, well, there's 320 00:18:06,320 --> 00:18:08,440 Speaker 1: there's a lot of ways to look at it. The 321 00:18:08,920 --> 00:18:13,960 Speaker 1: two that are probably most common and uh, I would 322 00:18:13,960 --> 00:18:17,000 Speaker 1: say very definitive. You know that they both of these 323 00:18:17,040 --> 00:18:22,680 Speaker 1: types of studies provide irrefutable evidence on impacts. Are first 324 00:18:22,720 --> 00:18:24,919 Speaker 1: of all, is just looking at what a coyote eats, 325 00:18:25,200 --> 00:18:29,720 Speaker 1: and so those are simply you know, diet analyzes and commonly, 326 00:18:29,960 --> 00:18:32,800 Speaker 1: you know, one of the cheapest and widespread and often 327 00:18:32,920 --> 00:18:36,200 Speaker 1: used are what we call scats studies. But basically you're 328 00:18:37,240 --> 00:18:42,719 Speaker 1: going into an area and you collect the poop and 329 00:18:42,960 --> 00:18:46,160 Speaker 1: uh you do an analysis on that, and you can tell, 330 00:18:46,600 --> 00:18:49,040 Speaker 1: you know, from the feces what of course what what 331 00:18:49,080 --> 00:18:51,040 Speaker 1: the animal has been eating, and so you can identify, 332 00:18:51,520 --> 00:18:54,160 Speaker 1: you know, the hair of different mammals that they've consumed, 333 00:18:54,200 --> 00:18:56,800 Speaker 1: and sometimes the remains of different fruits and so forth. 334 00:18:57,680 --> 00:19:02,040 Speaker 1: So that that was done decade ago. Um. Now you 335 00:19:02,080 --> 00:19:04,520 Speaker 1: might might imagine mark. One of the things that can 336 00:19:04,560 --> 00:19:08,920 Speaker 1: be misleading is when you find a lot of deer 337 00:19:08,960 --> 00:19:12,040 Speaker 1: in the diet of a coyote. You you don't know 338 00:19:12,080 --> 00:19:15,560 Speaker 1: if the coyote killed the deer or scavenged on the deer. 339 00:19:16,480 --> 00:19:20,080 Speaker 1: You would assume if you found fawn hair uh in 340 00:19:20,160 --> 00:19:22,600 Speaker 1: the scat. Yeah. More in like of the coyotes killed 341 00:19:22,600 --> 00:19:25,159 Speaker 1: the fawn, but for adults you never knew, and you 342 00:19:25,160 --> 00:19:28,280 Speaker 1: would see a higher prevalence rate during deer season, which 343 00:19:28,680 --> 00:19:31,440 Speaker 1: you would assume is from carcass remains or from a 344 00:19:31,480 --> 00:19:35,480 Speaker 1: wounded deer um. And so that that then leads to 345 00:19:35,560 --> 00:19:40,159 Speaker 1: more sophisticated analyzes where you can really you know, determine 346 00:19:40,200 --> 00:19:45,760 Speaker 1: impacts and and directly measure um the prevalence of predation. 347 00:19:46,400 --> 00:19:50,840 Speaker 1: And that's when you mark individual deer and and most 348 00:19:50,880 --> 00:19:54,600 Speaker 1: commonly what is done UM is what we call call 349 00:19:54,840 --> 00:19:59,200 Speaker 1: fawn depredation studies. And you know, one of the best 350 00:19:59,200 --> 00:20:01,439 Speaker 1: ways to do that it is you will mark a 351 00:20:01,520 --> 00:20:04,600 Speaker 1: dough a pregnant female. So you would capture a pregnant 352 00:20:04,640 --> 00:20:09,800 Speaker 1: female and you can actually insert this transmitter into their 353 00:20:09,880 --> 00:20:15,879 Speaker 1: vagina and when they give birth, then that transmitter comes 354 00:20:15,880 --> 00:20:18,399 Speaker 1: out of the doe's body, goes out to the ground 355 00:20:18,440 --> 00:20:21,440 Speaker 1: and then there's a difference in the ambient temperature of course, 356 00:20:21,440 --> 00:20:24,679 Speaker 1: from being inside of the dough to being exposed to 357 00:20:25,119 --> 00:20:28,439 Speaker 1: you know, the outside air, and that transmitter then sends 358 00:20:28,480 --> 00:20:31,960 Speaker 1: sends a signal a GPS location and researchers Russian and 359 00:20:33,200 --> 00:20:36,560 Speaker 1: they can find the fawn or fawns, and they basically 360 00:20:36,600 --> 00:20:38,800 Speaker 1: mark them. They put a little ear tag on them 361 00:20:38,840 --> 00:20:42,120 Speaker 1: and put some type of GPS transmitter on them, and 362 00:20:42,240 --> 00:20:45,280 Speaker 1: those little transmitters allow the researchers to know when that 363 00:20:45,359 --> 00:20:47,960 Speaker 1: fawn is alive and when it's dead. So when that 364 00:20:48,000 --> 00:20:51,439 Speaker 1: transmitter stops moving for a X amount of hours, you 365 00:20:51,480 --> 00:20:54,040 Speaker 1: get an alert saying, hey, something's going on with this fawn. 366 00:20:54,119 --> 00:20:57,919 Speaker 1: And then once again you go there and you determine um, 367 00:20:57,960 --> 00:21:02,439 Speaker 1: the cause of death. Often this is obvious based on 368 00:21:02,520 --> 00:21:06,560 Speaker 1: the way the fawn has been uh consumed or you know, 369 00:21:07,000 --> 00:21:09,480 Speaker 1: torn apart, so to speak. You can diagnose whether it 370 00:21:09,560 --> 00:21:12,639 Speaker 1: was a bobcat kill or died of starvation or a 371 00:21:12,640 --> 00:21:16,880 Speaker 1: coyote um. And then even most sophistics, the sophisticated way 372 00:21:16,920 --> 00:21:20,840 Speaker 1: to do it is if if you can't readily identify 373 00:21:20,920 --> 00:21:25,240 Speaker 1: the predator, is that you can take swabs and get 374 00:21:25,320 --> 00:21:27,600 Speaker 1: d n A samples from the remains of the fawn 375 00:21:27,760 --> 00:21:31,080 Speaker 1: so that you can detect the saliva of the predator 376 00:21:31,200 --> 00:21:33,320 Speaker 1: that was chewing on the high, chewing on the bones, 377 00:21:33,359 --> 00:21:36,600 Speaker 1: et cetera. And so that that kind of c s 378 00:21:36,640 --> 00:21:44,000 Speaker 1: I technology really allows you to definitively determine uh, you know, 379 00:21:44,160 --> 00:21:46,960 Speaker 1: the rate at which you know, you have a sample 380 00:21:47,000 --> 00:21:50,520 Speaker 1: of fawns on the landscape, this cohort of fawns, and 381 00:21:50,600 --> 00:21:54,760 Speaker 1: you can determine, you know, what we call cause specific mortality, 382 00:21:55,520 --> 00:21:57,840 Speaker 1: how many of them died and those that did die, 383 00:21:57,920 --> 00:22:01,560 Speaker 1: what were they killed by? And so those studies again 384 00:22:01,880 --> 00:22:06,280 Speaker 1: have been done largely in the last decade, probably some 385 00:22:06,400 --> 00:22:10,639 Speaker 1: a little bit more, but that's where the best technology 386 00:22:11,280 --> 00:22:13,560 Speaker 1: has has really been refined in the last decade. And 387 00:22:13,600 --> 00:22:15,400 Speaker 1: so a lot of the studies that you see now 388 00:22:15,920 --> 00:22:19,720 Speaker 1: are are are based on those types of technologies and 389 00:22:19,800 --> 00:22:26,040 Speaker 1: those types of results. So have there been any definitive 390 00:22:26,680 --> 00:22:29,600 Speaker 1: answers then that have come from these studies? Can you 391 00:22:29,640 --> 00:22:32,399 Speaker 1: give us a blanket statement and say coyotes make this 392 00:22:32,520 --> 00:22:35,160 Speaker 1: impact on dear or is a little more nuanced than that? 393 00:22:36,280 --> 00:22:40,760 Speaker 1: Unfortunately it's nuanced, and people get so sick and tired 394 00:22:40,800 --> 00:22:44,520 Speaker 1: of dear biologists always having to qualify saying, well, it depends, 395 00:22:44,560 --> 00:22:48,600 Speaker 1: but this is this is a classic it depends type study. 396 00:22:49,600 --> 00:22:53,959 Speaker 1: So you can go to any particular location and you know, 397 00:22:54,000 --> 00:22:56,879 Speaker 1: you think about these different dynamics that are going on. 398 00:22:57,000 --> 00:22:59,919 Speaker 1: Mark you've got you know, you've got variation in coyote 399 00:23:00,000 --> 00:23:04,000 Speaker 1: density as you've got variation in the number of hunters 400 00:23:04,000 --> 00:23:06,520 Speaker 1: on the landscape, you've got variation in the amount of 401 00:23:06,800 --> 00:23:10,199 Speaker 1: prey on the landscape, and then you've got variation in 402 00:23:10,240 --> 00:23:13,840 Speaker 1: the hiding places for the prey. And so there have 403 00:23:13,880 --> 00:23:18,200 Speaker 1: been several studies, uh that have you know, beyond the 404 00:23:18,240 --> 00:23:20,800 Speaker 1: shadow of a doubt, you know they will mark these 405 00:23:20,800 --> 00:23:24,359 Speaker 1: fawns and anywhere from thirty forty fifty up to you know, 406 00:23:24,600 --> 00:23:28,919 Speaker 1: sixty percent of the fawns will be eaten, killed and 407 00:23:29,000 --> 00:23:33,480 Speaker 1: eaten by coyotes. Um, you have some other places where 408 00:23:33,600 --> 00:23:36,640 Speaker 1: some of those dynamics are a little bit different and 409 00:23:36,760 --> 00:23:40,960 Speaker 1: you won't see such a big impact. I think if 410 00:23:40,960 --> 00:23:43,840 Speaker 1: you want a blanket statement, I think it's safe to 411 00:23:43,920 --> 00:23:48,359 Speaker 1: say that wherever you have a sufficient number of a 412 00:23:48,480 --> 00:23:51,920 Speaker 1: viable population of coyotes on the landscape and a viable 413 00:23:51,960 --> 00:23:56,040 Speaker 1: population of deer, you are going to have deer that 414 00:23:56,080 --> 00:23:59,880 Speaker 1: are killed either fawns, mostly fawns, and also some adults 415 00:24:00,600 --> 00:24:04,040 Speaker 1: are gonna die by coyotes every single year and there's 416 00:24:04,080 --> 00:24:08,200 Speaker 1: nothing you can do about it. The most important question 417 00:24:08,520 --> 00:24:13,760 Speaker 1: is are they a driver of that population? And you 418 00:24:13,840 --> 00:24:17,000 Speaker 1: really can't tell mark. You can't even even at a 419 00:24:17,119 --> 00:24:22,119 Speaker 1: county scale. You can't say that coyotes are driving that population. 420 00:24:22,240 --> 00:24:24,560 Speaker 1: It's a little more site specific than that. Can you 421 00:24:24,640 --> 00:24:26,639 Speaker 1: can you elaborate on what that means. But when you 422 00:24:26,680 --> 00:24:31,520 Speaker 1: say driving the population, uh, think of it as being 423 00:24:32,240 --> 00:24:37,840 Speaker 1: the most important limiting factor. So think of it as 424 00:24:37,880 --> 00:24:43,320 Speaker 1: as in terms of one single variable affecting the dynamics 425 00:24:43,359 --> 00:24:46,800 Speaker 1: of that population. Uh. It would in this case if 426 00:24:46,800 --> 00:24:50,120 Speaker 1: we were to say predation is driving the population, then 427 00:24:50,160 --> 00:24:52,800 Speaker 1: that would mean that would be the single most important 428 00:24:52,840 --> 00:24:57,199 Speaker 1: factor that is influencing the stability, rise or fall of 429 00:24:57,280 --> 00:25:00,639 Speaker 1: the dear population. Now here's a I don't know if 430 00:25:00,680 --> 00:25:03,640 Speaker 1: this is I'm assuming this is gonna be somewhere, But 431 00:25:04,040 --> 00:25:07,840 Speaker 1: is it fair to say that across most areas of 432 00:25:07,920 --> 00:25:11,920 Speaker 1: White Tail Country that hunters are the largest driver of 433 00:25:12,119 --> 00:25:15,600 Speaker 1: a population, and hunter not hunter predation, whatever you wanna 434 00:25:15,640 --> 00:25:18,119 Speaker 1: call it, our our kill of deer every year? Is 435 00:25:18,160 --> 00:25:21,840 Speaker 1: that accurate? Yeah? Yeah, I'm sure there's gonna be an 436 00:25:21,840 --> 00:25:25,399 Speaker 1: exception here or there, and especially in US urban and 437 00:25:25,440 --> 00:25:27,920 Speaker 1: suburban environments. But yeah, on the average, I think that's 438 00:25:28,000 --> 00:25:31,240 Speaker 1: very safe to say. Okay, So then so then you're 439 00:25:31,280 --> 00:25:35,480 Speaker 1: saying the tough thing, though, is finding a situation or 440 00:25:35,560 --> 00:25:39,920 Speaker 1: determining how much of a driver predator impacts actually are 441 00:25:40,440 --> 00:25:42,800 Speaker 1: um And you mentioned there's been different studies that have 442 00:25:42,920 --> 00:25:46,199 Speaker 1: shown a significant impact. There have been different studies that 443 00:25:46,240 --> 00:25:49,320 Speaker 1: have shown not a significant impact. I know from from 444 00:25:49,400 --> 00:25:51,360 Speaker 1: reading up on a lot of these myself and studying 445 00:25:51,359 --> 00:25:53,199 Speaker 1: them over the years. A lot of this has to 446 00:25:53,240 --> 00:25:56,159 Speaker 1: do with something that we call faun recruitment, and that 447 00:25:56,359 --> 00:25:59,520 Speaker 1: is kind of this indicator of that impact. Can you 448 00:25:59,600 --> 00:26:01,680 Speaker 1: can you dive into that for us, help us understand 449 00:26:01,720 --> 00:26:04,879 Speaker 1: what that means and then how coyotes might or might 450 00:26:04,920 --> 00:26:11,040 Speaker 1: not be impacting that in different areas as absolutely. Um 451 00:26:11,080 --> 00:26:14,520 Speaker 1: So we often say that if if you could only 452 00:26:14,640 --> 00:26:17,440 Speaker 1: measure one thing, you know, it's it's it's not as 453 00:26:17,480 --> 00:26:21,000 Speaker 1: fun or sexy as you know, measuring antlers. But if 454 00:26:21,000 --> 00:26:24,359 Speaker 1: you were managing a deer population, and it's like I 455 00:26:24,359 --> 00:26:27,360 Speaker 1: could only have this one piece of information to make 456 00:26:27,400 --> 00:26:30,919 Speaker 1: decisions about managing that population, it would be recruitment or 457 00:26:30,960 --> 00:26:34,280 Speaker 1: fond recruitment. And so so think of that as a 458 00:26:34,280 --> 00:26:37,720 Speaker 1: paycheck going into your account, you know, every month, every 459 00:26:37,760 --> 00:26:41,320 Speaker 1: year or whatever. If you are going to harvest the 460 00:26:41,359 --> 00:26:45,600 Speaker 1: population at some level, I'm gonna take five ten percent 461 00:26:45,840 --> 00:26:49,000 Speaker 1: In some places, in real productive herds, thirty percent of 462 00:26:49,080 --> 00:26:52,280 Speaker 1: the herd could be harvested every year. You have to 463 00:26:52,320 --> 00:26:55,480 Speaker 1: know what the inputs are going to be. If I'm 464 00:26:55,480 --> 00:26:59,600 Speaker 1: putting thirty percent in, I can take thirty percent out 465 00:26:59,680 --> 00:27:02,600 Speaker 1: and that population would remain stable. So that is what 466 00:27:02,760 --> 00:27:05,600 Speaker 1: fawn recruitment is. And so biologists are wanting to know, 467 00:27:06,359 --> 00:27:10,280 Speaker 1: you know, how often, how many fawns are and and 468 00:27:10,320 --> 00:27:15,840 Speaker 1: recruiting just simply means living long enough to be recruited 469 00:27:15,960 --> 00:27:19,359 Speaker 1: into the population. And we typically mean that you know, 470 00:27:19,400 --> 00:27:22,000 Speaker 1: they made it through hunting season, they made it to winter, 471 00:27:22,560 --> 00:27:26,879 Speaker 1: and assume they're going to be recruited into the springtime population. Okay, 472 00:27:26,920 --> 00:27:30,600 Speaker 1: So Mark, let's say you have a scenario where you 473 00:27:30,720 --> 00:27:35,080 Speaker 1: had twenty years ago, there were very few coyotes, uh, 474 00:27:35,280 --> 00:27:38,600 Speaker 1: in this particular area, and it's the heavily hunted area, 475 00:27:39,840 --> 00:27:44,560 Speaker 1: and doe harvest is pretty high, buck carves is pretty high. Uh. 476 00:27:44,600 --> 00:27:48,320 Speaker 1: You know, so it's providing ideal hunting recreation for you know, 477 00:27:48,480 --> 00:27:54,480 Speaker 1: the public. And now you change that one single variable. Uh, 478 00:27:54,600 --> 00:27:57,720 Speaker 1: the amount of hunters haven't changed, the amount of hunting 479 00:27:57,760 --> 00:28:00,879 Speaker 1: area hasn't changed. You kind of every year. I'm just 480 00:28:00,960 --> 00:28:03,240 Speaker 1: making up numbers here. But we're gonna, you know, we're 481 00:28:03,240 --> 00:28:07,720 Speaker 1: gonna have five hundred hunter mandates on our property this 482 00:28:07,800 --> 00:28:09,919 Speaker 1: year and every year, you know, your permit system, and 483 00:28:10,280 --> 00:28:12,400 Speaker 1: five people get to spend a day on the out 484 00:28:12,440 --> 00:28:15,679 Speaker 1: on out on that property a year killing deer. And 485 00:28:15,720 --> 00:28:19,679 Speaker 1: then you add in this new element um called you know, 486 00:28:19,840 --> 00:28:25,320 Speaker 1: coyote fawn depredation. And rather than recruiting again let's just 487 00:28:25,359 --> 00:28:28,000 Speaker 1: say easy numbers. Whereas you used to recruit you know, 488 00:28:28,200 --> 00:28:31,960 Speaker 1: three hundred fawns into the population every year, now you're 489 00:28:32,000 --> 00:28:37,080 Speaker 1: only recruiting a hundred fawns into the population. The result 490 00:28:37,119 --> 00:28:41,280 Speaker 1: won't be immediate, but over time, three years later, four 491 00:28:41,360 --> 00:28:46,000 Speaker 1: years later, five years later, because that paycheck going into 492 00:28:46,080 --> 00:28:49,920 Speaker 1: the account is getting less and less and less, you 493 00:28:49,960 --> 00:28:53,560 Speaker 1: start noting the principle in your account. The adult population 494 00:28:53,680 --> 00:28:57,640 Speaker 1: goes down, down, down, because you are spending more than 495 00:28:57,680 --> 00:29:01,239 Speaker 1: you're putting in. And that has been one of the 496 00:29:01,240 --> 00:29:05,080 Speaker 1: biggest UH sources of some of these studies over the 497 00:29:05,080 --> 00:29:08,840 Speaker 1: past a decade, is what in the heck is going on. 498 00:29:09,200 --> 00:29:13,240 Speaker 1: We've got this big property or this area, uh maybe 499 00:29:13,240 --> 00:29:16,560 Speaker 1: you know county scale type thing where we used to 500 00:29:16,560 --> 00:29:19,440 Speaker 1: have plenty of deer and now hunters aren't killing as 501 00:29:19,440 --> 00:29:21,360 Speaker 1: many deer as they used to, they're not seeing as 502 00:29:21,360 --> 00:29:25,360 Speaker 1: many deer as they used to, and coincidentally, we are 503 00:29:25,400 --> 00:29:28,480 Speaker 1: seeing a lot more coyotes than we used to. And 504 00:29:28,560 --> 00:29:30,280 Speaker 1: sure enough, when you do some of those studies and 505 00:29:30,320 --> 00:29:33,160 Speaker 1: you start marking those fawns and and figuring out what 506 00:29:33,200 --> 00:29:36,560 Speaker 1: caused specific mortality, is you learned that, Yeah, well that's 507 00:29:36,560 --> 00:29:39,320 Speaker 1: the reason the dear population is declining because they're only 508 00:29:39,400 --> 00:29:42,320 Speaker 1: recruiting about half as many fawns as we used to. 509 00:29:44,280 --> 00:29:49,160 Speaker 1: So is yeah, what am I trying to say here? 510 00:29:50,200 --> 00:29:55,560 Speaker 1: Is that always? M hm? He guess Number one? How 511 00:29:55,560 --> 00:29:58,960 Speaker 1: often is that actually happening? Because you hear you hear 512 00:29:59,000 --> 00:30:02,720 Speaker 1: people talk about coyotes, coyotes, coyotes, But the situation you 513 00:30:02,760 --> 00:30:06,280 Speaker 1: just mentioned where you have that fund recruitment rate reduced 514 00:30:06,320 --> 00:30:10,400 Speaker 1: so significantly that the population does decline, do you have 515 00:30:10,440 --> 00:30:13,840 Speaker 1: any idea? I mean, could you say that, you know, 516 00:30:13,920 --> 00:30:18,120 Speaker 1: maybe if we had to lump all of White Tail 517 00:30:18,120 --> 00:30:20,600 Speaker 1: Country into a bucket, and then could you say that 518 00:30:20,760 --> 00:30:24,040 Speaker 1: in one out of ten, ten percent of our populations 519 00:30:24,040 --> 00:30:26,000 Speaker 1: had that kind of impact or is it fifty of 520 00:30:26,000 --> 00:30:28,840 Speaker 1: the populations are having those kind of Is this rare? 521 00:30:29,040 --> 00:30:32,880 Speaker 1: Is this common. Um. I don't know how exactly articulate this, 522 00:30:33,000 --> 00:30:38,040 Speaker 1: but is this the rule of the exception? I would 523 00:30:38,080 --> 00:30:42,880 Speaker 1: say somewhere in between. I think. I think it definitely 524 00:30:43,040 --> 00:30:47,280 Speaker 1: tends to be more of an exception. UM and and 525 00:30:47,400 --> 00:30:52,160 Speaker 1: market all depends on scale as well. You know, Um, 526 00:30:52,400 --> 00:30:54,160 Speaker 1: is the deer herd doing well in the state of 527 00:30:54,200 --> 00:30:59,960 Speaker 1: Michigan or Iowa? Well, yeah, what about in this county 528 00:31:00,000 --> 00:31:02,760 Speaker 1: pretty much? How about on this property or you know, 529 00:31:02,920 --> 00:31:06,600 Speaker 1: or within this five thousand acre area. Um, you would 530 00:31:06,680 --> 00:31:09,160 Speaker 1: kind of have to look at it like that. You know, 531 00:31:09,920 --> 00:31:13,920 Speaker 1: in the eastern, especially the southeastern US, the deer herd 532 00:31:14,000 --> 00:31:18,800 Speaker 1: is certainly doing just fine. In the presence of coyotes. 533 00:31:19,720 --> 00:31:22,080 Speaker 1: People are still seeing dear, people are still hunting deer. 534 00:31:22,440 --> 00:31:24,200 Speaker 1: You know, there's a lot of support that the deer 535 00:31:24,280 --> 00:31:28,840 Speaker 1: population has declined somewhat, but not a lot when you 536 00:31:28,880 --> 00:31:30,920 Speaker 1: look at that type of scale. You know, and I 537 00:31:30,920 --> 00:31:34,240 Speaker 1: can speak for Mississippi, you know, the deer herd depending 538 00:31:34,320 --> 00:31:37,680 Speaker 1: on the index and the analysis you do, Yeah, over 539 00:31:37,720 --> 00:31:40,120 Speaker 1: the past decade, it may have declined a little bit, 540 00:31:40,600 --> 00:31:43,680 Speaker 1: but not a lot. Now you can go to certain 541 00:31:43,720 --> 00:31:47,680 Speaker 1: areas within Mississippi based on a lot of details and 542 00:31:47,680 --> 00:31:50,320 Speaker 1: it's usually the interaction of you know, is there a 543 00:31:50,400 --> 00:31:53,040 Speaker 1: high predator population like coyotes, and what is what are 544 00:31:53,040 --> 00:31:56,960 Speaker 1: the habitat conditions like And there's some pretty powerful evidence 545 00:31:57,080 --> 00:32:00,240 Speaker 1: that coyotes have really taken a toll on that your 546 00:32:00,240 --> 00:32:06,480 Speaker 1: population at at a much more local scale. So you know, 547 00:32:06,520 --> 00:32:09,000 Speaker 1: you kind of said, Mark, you know, is it is 548 00:32:09,040 --> 00:32:12,800 Speaker 1: it you know, ten percent or you know, I am 549 00:32:12,840 --> 00:32:16,959 Speaker 1: just really guestimating here. I would say it's probably somewhere 550 00:32:17,040 --> 00:32:20,280 Speaker 1: less than and it might even be it may even 551 00:32:20,320 --> 00:32:24,240 Speaker 1: be less than ten percent. Where coyotes are really you know, driving, 552 00:32:24,520 --> 00:32:27,640 Speaker 1: you know, they are the single most important thing of 553 00:32:27,800 --> 00:32:32,120 Speaker 1: affecting the population. Okay, but but there are certainly things 554 00:32:32,200 --> 00:32:36,160 Speaker 1: that we can do proactively with that. Uh, it's just 555 00:32:36,280 --> 00:32:40,000 Speaker 1: identifying why is the deer population declining so much? Is 556 00:32:40,040 --> 00:32:43,960 Speaker 1: it indeed coyotes? And then you know what what type 557 00:32:43,960 --> 00:32:46,080 Speaker 1: of steps can you can you take to to help 558 00:32:46,080 --> 00:32:48,720 Speaker 1: it out, to help the deer hurt out? So here 559 00:32:48,760 --> 00:32:54,360 Speaker 1: here's a question, could would it be or is there 560 00:32:54,400 --> 00:32:57,840 Speaker 1: are there any benefits to having coyotes on the landscape 561 00:32:57,880 --> 00:33:01,120 Speaker 1: as a deer hunter and manager, because one way I 562 00:33:01,160 --> 00:33:03,800 Speaker 1: could see this in some situations and so maybe I'll 563 00:33:03,840 --> 00:33:06,240 Speaker 1: throw out a possibility and you tell me if this 564 00:33:06,280 --> 00:33:09,600 Speaker 1: is true or false or maybe somewhere between. But for 565 00:33:09,720 --> 00:33:13,520 Speaker 1: decades now, um white tailed researchers and managers have been 566 00:33:13,520 --> 00:33:15,720 Speaker 1: telling us that we have too many deer, too many doughs, 567 00:33:15,760 --> 00:33:18,040 Speaker 1: too many doughs. We need to we need to harvest more, 568 00:33:18,080 --> 00:33:20,600 Speaker 1: we try, need to try to bring the population back 569 00:33:20,600 --> 00:33:23,680 Speaker 1: in balance with the habitat. And in a lot of places, 570 00:33:23,720 --> 00:33:26,360 Speaker 1: even now, even where I hunt and and hang out, 571 00:33:26,600 --> 00:33:28,440 Speaker 1: that still doesn't seem to be the case. They're still 572 00:33:28,440 --> 00:33:31,680 Speaker 1: seem to be way more dear than a healthy habitat 573 00:33:31,720 --> 00:33:34,920 Speaker 1: and support, which is leading to probably deer that aren't 574 00:33:34,960 --> 00:33:37,840 Speaker 1: quite as healthy as they could be, probably leading maybe 575 00:33:37,840 --> 00:33:40,880 Speaker 1: in part, is impacting fond recruitment too, because these these 576 00:33:40,880 --> 00:33:43,040 Speaker 1: deer aren't getting the nutrition they need because of the 577 00:33:43,080 --> 00:33:45,160 Speaker 1: fact that the habitat isn't in balance of the herd. 578 00:33:45,760 --> 00:33:49,560 Speaker 1: In a situation like that, is having natural predators back 579 00:33:49,600 --> 00:33:52,240 Speaker 1: on the landscape a good thing because they can help 580 00:33:52,320 --> 00:33:54,960 Speaker 1: us balance things because if we the hunters aren't doing 581 00:33:55,040 --> 00:33:59,440 Speaker 1: enough ourselves, they serve that ecosystem function. Is that a 582 00:33:59,480 --> 00:34:01,200 Speaker 1: way to look at this in some cases too, Or 583 00:34:01,240 --> 00:34:06,520 Speaker 1: is that Bologney. I think that's the furthest thing from blogny. Um. 584 00:34:06,840 --> 00:34:09,800 Speaker 1: I agree with that sentiment and the way you describe 585 00:34:09,800 --> 00:34:14,359 Speaker 1: that perfectly. And you know that it's never ever with 586 00:34:14,400 --> 00:34:17,520 Speaker 1: the deer management and deer hunters, it's never gonna be 587 00:34:17,560 --> 00:34:22,440 Speaker 1: a you know, one size shoe fits all. Um, my 588 00:34:22,560 --> 00:34:24,920 Speaker 1: colleague here at the Deer Lab, Steve Demeris, that is 589 00:34:25,000 --> 00:34:27,880 Speaker 1: something that has been a presentation he has given many 590 00:34:27,920 --> 00:34:32,920 Speaker 1: many times, um, different seminars, is you know, the sky 591 00:34:33,160 --> 00:34:36,399 Speaker 1: is not necessarily falling here. We we have a new 592 00:34:36,440 --> 00:34:38,799 Speaker 1: predator on the landscape, has been here quite some time, 593 00:34:38,840 --> 00:34:41,960 Speaker 1: and it's gonna getting a lot of attention. But there 594 00:34:41,960 --> 00:34:47,600 Speaker 1: are probably more situations where the coyote maybe helping the 595 00:34:47,640 --> 00:34:51,720 Speaker 1: deer herd out some bringing some of bringing this herd 596 00:34:51,880 --> 00:34:55,400 Speaker 1: back into check and back into balance with with the habitat. 597 00:34:56,480 --> 00:34:59,319 Speaker 1: And a lot of that mark is the what have 598 00:34:59,480 --> 00:35:03,560 Speaker 1: hunters expected to see for so long? And we think 599 00:35:03,560 --> 00:35:06,680 Speaker 1: back when when the uh qd M, the Quality of 600 00:35:06,719 --> 00:35:12,319 Speaker 1: Deer Management Association began and started educating people about we've 601 00:35:12,360 --> 00:35:15,360 Speaker 1: got to get this dear herd back into balance with 602 00:35:15,440 --> 00:35:18,480 Speaker 1: the habitat, you know, for healthy deer and for healthy 603 00:35:18,520 --> 00:35:22,919 Speaker 1: habitats and in a lot of places, Um, it's it's 604 00:35:23,000 --> 00:35:28,239 Speaker 1: just really it causes Um, how should I say it, 605 00:35:28,239 --> 00:35:31,520 Speaker 1: it's too much a work that you know, the novelty 606 00:35:31,760 --> 00:35:34,879 Speaker 1: of doe harvest wears off really quickly for a lot 607 00:35:34,920 --> 00:35:39,640 Speaker 1: of people. And so rather than a particular hunting club 608 00:35:39,640 --> 00:35:42,600 Speaker 1: in the South having to kill fifty seventy a hundred 609 00:35:42,600 --> 00:35:46,080 Speaker 1: and fifty does every year, you know, coyotes moving into 610 00:35:46,120 --> 00:35:49,040 Speaker 1: the system and maybe only having to harvest fifty does 611 00:35:49,120 --> 00:35:52,719 Speaker 1: a year. Um, that's really not a bad trade off. 612 00:35:53,600 --> 00:35:56,239 Speaker 1: And you know in a lot of those systems too, 613 00:35:56,520 --> 00:36:00,799 Speaker 1: where you have healthy habitat, I think you're gonna be 614 00:36:00,840 --> 00:36:03,480 Speaker 1: hard pressed to see where coyotes are going to be 615 00:36:03,520 --> 00:36:06,360 Speaker 1: really hurting the deer herd at all. So in a 616 00:36:06,400 --> 00:36:09,479 Speaker 1: case like that, I think you're actually helping the deer 617 00:36:09,520 --> 00:36:12,840 Speaker 1: hunting scenario and helping the deer herd quality having that 618 00:36:12,920 --> 00:36:16,560 Speaker 1: predator in the system. Yeah, it's interesting because this is 619 00:36:16,560 --> 00:36:19,319 Speaker 1: actually impacting me right now. Um. One of the main 620 00:36:19,360 --> 00:36:22,080 Speaker 1: properties at hunt in Michigan for the longest, for the 621 00:36:22,080 --> 00:36:23,960 Speaker 1: first I don't know, five six, seven years that I've 622 00:36:24,000 --> 00:36:27,040 Speaker 1: hunted here, I'd never got a coyote on trail camera, 623 00:36:27,120 --> 00:36:31,040 Speaker 1: never saw one, never heard one. UM nothing. And UM. 624 00:36:31,080 --> 00:36:34,120 Speaker 1: I had heard about there being some really significant UM 625 00:36:34,239 --> 00:36:37,719 Speaker 1: coyote trapping and hunting being done in the area over 626 00:36:37,760 --> 00:36:41,040 Speaker 1: the years, UM guys running in with dogs and lots 627 00:36:41,040 --> 00:36:42,200 Speaker 1: of stuff like that, and it just seemed like there're 628 00:36:42,200 --> 00:36:44,319 Speaker 1: never as much of a population left over, at least 629 00:36:44,320 --> 00:36:47,080 Speaker 1: that I was anecdotally seeing. UM. And then over the 630 00:36:47,160 --> 00:36:50,239 Speaker 1: last couple of years, I have been seeing that tick up. 631 00:36:50,280 --> 00:36:52,839 Speaker 1: I'm hearing them at night, I'm seeing them getting one 632 00:36:52,920 --> 00:36:55,480 Speaker 1: picked on trail camera. And at first I was like, oh, 633 00:36:55,600 --> 00:36:57,839 Speaker 1: is this going to be an issue, But then very 634 00:36:57,920 --> 00:37:01,040 Speaker 1: quickly another side of me said, well, weight Mark, for 635 00:37:01,200 --> 00:37:03,120 Speaker 1: years now, you've complained about the fact that no one 636 00:37:03,120 --> 00:37:06,560 Speaker 1: else shoots those around here, and there's so many deer, 637 00:37:06,600 --> 00:37:10,280 Speaker 1: and it's just totally out of whack. There's so many doughs, 638 00:37:10,320 --> 00:37:12,760 Speaker 1: hardly any bucks. You can't go anywhere in the property 639 00:37:12,800 --> 00:37:16,759 Speaker 1: without spooking deer. Maybe this isn't such a bad thing, UM, 640 00:37:16,920 --> 00:37:20,200 Speaker 1: And I think that it's really natural. It's kind of 641 00:37:20,400 --> 00:37:23,640 Speaker 1: ingrained human nature because of kind of our our deep 642 00:37:23,760 --> 00:37:28,600 Speaker 1: history with predators as competition in many cases. You know, 643 00:37:28,640 --> 00:37:30,440 Speaker 1: way back in the day, we looked at these animals 644 00:37:30,440 --> 00:37:32,920 Speaker 1: as competition for a scarce resource, which is our food, 645 00:37:33,360 --> 00:37:35,799 Speaker 1: and or as a danger to our health. And that 646 00:37:35,920 --> 00:37:38,960 Speaker 1: I think has stuck with us over the thousands of 647 00:37:39,040 --> 00:37:41,440 Speaker 1: years ever since. And I think there's there's always this 648 00:37:41,560 --> 00:37:46,319 Speaker 1: natural tendency to when they when they're one of the 649 00:37:46,360 --> 00:37:48,440 Speaker 1: options to point a finger at, it's really easy to 650 00:37:48,480 --> 00:37:50,880 Speaker 1: point that finger and be like, oh, that's that's the issue. 651 00:37:51,440 --> 00:37:54,480 Speaker 1: Maybe sometimes it's not quite as much as our gut 652 00:37:54,480 --> 00:37:56,719 Speaker 1: instinct always tells us. And that's kind of what I'm 653 00:37:57,000 --> 00:37:59,800 Speaker 1: what I'm kind of seeing in this own personal example 654 00:37:59,800 --> 00:38:03,960 Speaker 1: of my own here. Um. Not. Something else that I 655 00:38:03,960 --> 00:38:05,960 Speaker 1: I've read a lot about and I know you you've 656 00:38:06,000 --> 00:38:08,400 Speaker 1: talked about in the past on some of your own podcasts, 657 00:38:08,719 --> 00:38:13,200 Speaker 1: is some of the ways that deer naturally deal with predation. Um. 658 00:38:13,320 --> 00:38:15,320 Speaker 1: Can you talk a little bit about things like birth 659 00:38:15,320 --> 00:38:17,959 Speaker 1: synchrony and some of the other things that that white 660 00:38:18,000 --> 00:38:23,240 Speaker 1: tails do to to help live with predators and survive. Yeah, 661 00:38:23,280 --> 00:38:27,439 Speaker 1: that that's probably and it's really interesting topic. UM. Yeah. 662 00:38:27,520 --> 00:38:32,320 Speaker 1: But but synchronizing birth is kind of you know, natural 663 00:38:32,360 --> 00:38:35,560 Speaker 1: selection over time, you know, and that's just a product 664 00:38:35,600 --> 00:38:41,640 Speaker 1: of differential survival and reproduction. Um. But but over time 665 00:38:42,480 --> 00:38:46,160 Speaker 1: when you quote swamp the predators. So if if you 666 00:38:46,200 --> 00:38:48,960 Speaker 1: could pick you know, a three day or a three 667 00:38:48,960 --> 00:38:53,280 Speaker 1: week time when all of the females dropped their fonts, 668 00:38:53,400 --> 00:38:59,000 Speaker 1: their their calves, their pups, whatever, um, you simply overwhelm 669 00:38:59,040 --> 00:39:02,440 Speaker 1: the number of predators that are on the landscape and 670 00:39:02,520 --> 00:39:05,920 Speaker 1: so it stinks for for your offspring to be chosen. 671 00:39:06,040 --> 00:39:09,359 Speaker 1: You know, they're the ones that's eaten. But it's kind 672 00:39:09,400 --> 00:39:15,240 Speaker 1: of one of those uh bet hedging strategies where um, 673 00:39:15,280 --> 00:39:18,719 Speaker 1: if you can swamp the predator population by having yet 674 00:39:18,719 --> 00:39:22,920 Speaker 1: the synchronized birth event, then you know that is that 675 00:39:23,040 --> 00:39:26,160 Speaker 1: is a way to ensure that at a population scale, 676 00:39:26,680 --> 00:39:29,600 Speaker 1: you know, you're you're always gonna have recruit have some 677 00:39:29,680 --> 00:39:32,799 Speaker 1: type of recruitment of young um the other way. So 678 00:39:32,840 --> 00:39:36,759 Speaker 1: that that's kind of more at a population scale. Now, 679 00:39:37,080 --> 00:39:41,440 Speaker 1: of course, at an individual scale, UM, the mother is 680 00:39:41,480 --> 00:39:45,839 Speaker 1: going to be selecting the most appropriate cover and so 681 00:39:45,880 --> 00:39:50,400 Speaker 1: there's gonna be variation uh in in habitat, vegetation, the 682 00:39:50,400 --> 00:39:53,480 Speaker 1: appropriate amount of cover on the landscape, and that could 683 00:39:53,520 --> 00:39:57,440 Speaker 1: be based on experience. You know what a mother has learned. Uh, 684 00:39:57,600 --> 00:39:59,760 Speaker 1: mother has learned that if I go to this area 685 00:40:00,000 --> 00:40:02,560 Speaker 1: and I bed down and this type of cover, I 686 00:40:02,680 --> 00:40:06,480 Speaker 1: keep having fawns, and so she repeats that behavior over 687 00:40:06,520 --> 00:40:09,719 Speaker 1: and over again. Um, whereas you have another mother that 688 00:40:09,840 --> 00:40:12,719 Speaker 1: doesn't have doesn't even live in the best habitat or 689 00:40:13,640 --> 00:40:17,160 Speaker 1: or doesn't have you know, access to it, um drops 690 00:40:17,160 --> 00:40:20,319 Speaker 1: her fawn and they keep getting eaten. And so you know, 691 00:40:20,400 --> 00:40:24,120 Speaker 1: things just kind of evolve over time like that is 692 00:40:24,160 --> 00:40:29,560 Speaker 1: an individual strategy. And here's something really remarkable of how 693 00:40:29,600 --> 00:40:34,759 Speaker 1: these these things can really evolve in real time and 694 00:40:34,800 --> 00:40:40,359 Speaker 1: in our lifetime is my colleague Marcus Lashley, he and 695 00:40:40,480 --> 00:40:43,319 Speaker 1: others when he was a PhD student in post doc 696 00:40:43,360 --> 00:40:46,759 Speaker 1: at NC State, they did a real interesting study on 697 00:40:47,080 --> 00:40:52,480 Speaker 1: Fort Bragg. And so it's a really really open landscape 698 00:40:52,520 --> 00:40:56,920 Speaker 1: and lots of details here, but um, bottom line they 699 00:40:57,080 --> 00:41:01,319 Speaker 1: they used to prescribe fire on an annual basis or 700 00:41:01,400 --> 00:41:05,960 Speaker 1: every other year, and Um, the vegetation because of that 701 00:41:06,160 --> 00:41:08,440 Speaker 1: is kept very very low to the ground. So it's 702 00:41:08,440 --> 00:41:12,879 Speaker 1: a very very open landscape in terms of the understory. 703 00:41:14,040 --> 00:41:20,000 Speaker 1: So what you have is more developed structure near what 704 00:41:20,040 --> 00:41:22,400 Speaker 1: we call the drains or the creek banks. You know, 705 00:41:22,560 --> 00:41:26,240 Speaker 1: is these these wetter areas where the fire stops burning. 706 00:41:26,760 --> 00:41:30,680 Speaker 1: And these may be very narrow corridors, but it's where 707 00:41:30,719 --> 00:41:33,600 Speaker 1: you might have more shrub development and things like that. 708 00:41:34,920 --> 00:41:37,880 Speaker 1: And so a doe being a doe, you know, going 709 00:41:38,040 --> 00:41:41,919 Speaker 1: somewhere where you know in her you know her her 710 00:41:41,920 --> 00:41:44,560 Speaker 1: search image, you know, through her eyes and brain of 711 00:41:44,640 --> 00:41:45,920 Speaker 1: this is where I need to lay down and have 712 00:41:46,000 --> 00:41:52,000 Speaker 1: a fawn. Unfortunately, because that vegetation type is so limited 713 00:41:52,360 --> 00:41:58,359 Speaker 1: and linear, that coyotes can easily hunt those drains. And 714 00:41:58,440 --> 00:42:02,040 Speaker 1: so he actually saw that fawn survival dropped in a 715 00:42:02,080 --> 00:42:07,040 Speaker 1: really really good hiding cover was lower than in an 716 00:42:07,080 --> 00:42:09,919 Speaker 1: area that was completely wide open with hardly any cover 717 00:42:10,040 --> 00:42:14,239 Speaker 1: what's what whatsoever, because the coyotes were not searching that 718 00:42:14,360 --> 00:42:18,360 Speaker 1: open landscape. The coyote was being a coyote and walking 719 00:42:18,400 --> 00:42:21,560 Speaker 1: an edge, walking along that edge, smelling the fawn and 720 00:42:21,960 --> 00:42:25,959 Speaker 1: you know, uh, capturing it and killing it. So that's 721 00:42:26,000 --> 00:42:29,120 Speaker 1: one of the things where the dope picking the dope 722 00:42:29,160 --> 00:42:33,120 Speaker 1: pick to the right cover, you know. But unfortunately, because 723 00:42:33,200 --> 00:42:36,040 Speaker 1: that type of cover was so rare on the landscape, 724 00:42:36,960 --> 00:42:43,720 Speaker 1: it actually gave the coyote the advantage. Interesting, so they're working, 725 00:42:43,920 --> 00:42:49,279 Speaker 1: uh simultaneously, Mark, could could you speak a little bit 726 00:42:49,360 --> 00:42:55,160 Speaker 1: more to this habitat component of coyote impacts on fawn predation, 727 00:42:55,640 --> 00:42:57,719 Speaker 1: because it seems like more and more of the things 728 00:42:57,719 --> 00:42:59,879 Speaker 1: I read, it seems that that's a huge factor. See 729 00:43:00,000 --> 00:43:03,520 Speaker 1: mentioned the linear cover versus a different type. Can you 730 00:43:03,560 --> 00:43:05,319 Speaker 1: talk a little bit more about that, what we're learning 731 00:43:05,320 --> 00:43:12,799 Speaker 1: about how habitat does influence the impact. Yeah. Absolutely, And 732 00:43:13,320 --> 00:43:18,200 Speaker 1: this has been really difficult to prove so far. Um 733 00:43:19,120 --> 00:43:21,360 Speaker 1: it ends up being a little bit more of a 734 00:43:21,400 --> 00:43:25,080 Speaker 1: complicated study than you might imagine trying to develop all 735 00:43:25,080 --> 00:43:27,640 Speaker 1: these all these cover types and so forth, So you 736 00:43:27,719 --> 00:43:31,319 Speaker 1: end up kind of looking retrospectively that, Okay, what were 737 00:43:31,320 --> 00:43:34,319 Speaker 1: the habitat characteristics where fond survival was greater? What were 738 00:43:34,320 --> 00:43:40,040 Speaker 1: the habitat characteristics where fond survival was less? And bottom line, Mark, 739 00:43:40,200 --> 00:43:45,719 Speaker 1: it's um. It can come in a lot of different shapes. 740 00:43:46,000 --> 00:43:49,480 Speaker 1: So I don't like to say, like, for in your 741 00:43:49,560 --> 00:43:51,839 Speaker 1: neck of the woods, Mark, I wouldn't say it needs 742 00:43:51,840 --> 00:43:56,280 Speaker 1: to be this particular cover type or this vegetation type. 743 00:43:56,840 --> 00:44:00,319 Speaker 1: It's more like and I don't I don't know, Mark, 744 00:44:00,360 --> 00:44:02,480 Speaker 1: if you saw this little video we we made we've 745 00:44:02,480 --> 00:44:05,080 Speaker 1: had on our social media site, we called the the 746 00:44:05,680 --> 00:44:10,320 Speaker 1: basketball technique, but it kind of that kind of provides 747 00:44:10,440 --> 00:44:14,359 Speaker 1: you know visually, um, what we're talking about. And so 748 00:44:14,400 --> 00:44:16,480 Speaker 1: we just kind of as a little game to demonstrate 749 00:44:16,480 --> 00:44:18,520 Speaker 1: a point is you know, you'll have me and Marcus 750 00:44:18,560 --> 00:44:20,480 Speaker 1: or me and Steve, and you know, one of you 751 00:44:20,600 --> 00:44:23,319 Speaker 1: cover your eyes, turn around and let me hurl a 752 00:44:23,360 --> 00:44:26,240 Speaker 1: basketball not very far you know, ten or fifteen yards 753 00:44:26,320 --> 00:44:31,600 Speaker 1: or whatever, and then try to find it. And obviously 754 00:44:31,600 --> 00:44:34,080 Speaker 1: where there is well to develop cover, so I'm talking 755 00:44:34,120 --> 00:44:38,520 Speaker 1: about cover that is knee high to waist high, Um, 756 00:44:38,600 --> 00:44:42,719 Speaker 1: it can take you a while to find that basketball. However, 757 00:44:42,920 --> 00:44:47,080 Speaker 1: if you were to go uh in a typical forest 758 00:44:47,280 --> 00:44:49,680 Speaker 1: stand So let's go into a place that has a 759 00:44:49,719 --> 00:44:53,480 Speaker 1: developed forest, a developed canopy. You know with eight nine 760 00:44:54,560 --> 00:44:59,279 Speaker 1: canopy closure, that shading has caused the the understory to 761 00:44:59,320 --> 00:45:03,360 Speaker 1: grow away. And so you even though you have trees 762 00:45:03,400 --> 00:45:07,000 Speaker 1: and you have the structural cover, uh, in terms of 763 00:45:07,000 --> 00:45:10,520 Speaker 1: a forest, when you get down on your knees, you 764 00:45:10,520 --> 00:45:12,840 Speaker 1: can see anything on the ground. Not only can you 765 00:45:12,880 --> 00:45:15,400 Speaker 1: see a basketball, you can see a baseball if you 766 00:45:15,480 --> 00:45:18,680 Speaker 1: rolled it on the ground. That is not providing any 767 00:45:18,760 --> 00:45:22,920 Speaker 1: type of fawning cover. And so it's more easy pickings. 768 00:45:22,960 --> 00:45:25,760 Speaker 1: A coyote or a group of coyotes can work through 769 00:45:25,800 --> 00:45:32,120 Speaker 1: that type of vegetation really really easy. It's not to 770 00:45:32,239 --> 00:45:35,239 Speaker 1: say whatsoever that, hey, if I have great fawning cover, 771 00:45:35,760 --> 00:45:39,920 Speaker 1: I'm never gonna experience mortality from coyotes. Not not at all. 772 00:45:40,520 --> 00:45:43,520 Speaker 1: But what you've done is you've increased the search time. 773 00:45:44,320 --> 00:45:48,880 Speaker 1: You've you've complicated the coyotes eyes, you've complicated his nose, 774 00:45:49,680 --> 00:45:51,880 Speaker 1: the scent where it's coming from, it's going to be 775 00:45:51,920 --> 00:45:55,239 Speaker 1: broken up. And so essentially you you've just made it 776 00:45:55,800 --> 00:45:59,440 Speaker 1: um much more difficult for a coyote to find a fawn. 777 00:46:00,239 --> 00:46:02,080 Speaker 1: They may find them eventually, but they're not going to 778 00:46:02,160 --> 00:46:04,879 Speaker 1: find them at the same rate. And so that's what 779 00:46:04,880 --> 00:46:08,920 Speaker 1: what we're looking at, Mark, is you want larger areas. 780 00:46:09,000 --> 00:46:13,200 Speaker 1: Bigger is better. You don't want them in strips. And 781 00:46:13,239 --> 00:46:15,800 Speaker 1: that was like what I was referring to with Marcus 782 00:46:15,840 --> 00:46:20,279 Speaker 1: study is you can just think about this where if 783 00:46:20,320 --> 00:46:24,560 Speaker 1: the only cover you had was ten or fifteen yards 784 00:46:24,600 --> 00:46:28,560 Speaker 1: wide and a hundred yards long, man a coyote could 785 00:46:28,640 --> 00:46:31,319 Speaker 1: hunt that out in a matter of minutes. It's just 786 00:46:31,400 --> 00:46:33,919 Speaker 1: literally gotta walk on the edge up one side, down 787 00:46:33,920 --> 00:46:35,800 Speaker 1: the other, through the middle of it, and it's probably 788 00:46:35,840 --> 00:46:38,480 Speaker 1: going to detect via side or smell of fawn that's 789 00:46:38,520 --> 00:46:41,680 Speaker 1: in there. But now if you had this in a larger, 790 00:46:41,800 --> 00:46:45,560 Speaker 1: wider area in terms of acres, you know, ten acres 791 00:46:45,640 --> 00:46:47,640 Speaker 1: or twenty acres or thirty acres, and you had that 792 00:46:47,680 --> 00:46:51,600 Speaker 1: distributed all over the landscape, now you've really stacked the 793 00:46:51,640 --> 00:46:54,959 Speaker 1: odds in favor of the fawn being able to hide 794 00:46:55,000 --> 00:46:59,680 Speaker 1: from a hide from the predator like a coyote. So 795 00:47:01,280 --> 00:47:05,160 Speaker 1: tell me this then, Bronson, because we're talking about some 796 00:47:05,200 --> 00:47:07,759 Speaker 1: of the different habitat impacts. But I guess I kind 797 00:47:07,760 --> 00:47:09,600 Speaker 1: of got ahead of myself by asking you about that, 798 00:47:09,680 --> 00:47:11,279 Speaker 1: because what I want to what I want to make 799 00:47:11,320 --> 00:47:13,560 Speaker 1: sure we understand two is how do we even know 800 00:47:13,680 --> 00:47:16,319 Speaker 1: this is a problem. So I guess my first question is, 801 00:47:16,719 --> 00:47:21,240 Speaker 1: how do we determine if we might have a coyote 802 00:47:21,680 --> 00:47:24,239 Speaker 1: issue or or influence that we need to think about, 803 00:47:24,320 --> 00:47:25,600 Speaker 1: Like how do you how do you figure out if 804 00:47:25,600 --> 00:47:28,080 Speaker 1: your fonal recruitment rate is too low or or whatever 805 00:47:28,120 --> 00:47:30,680 Speaker 1: it might be. How do we determine that? And then 806 00:47:30,680 --> 00:47:32,719 Speaker 1: I want to know I guess my second question would be, 807 00:47:33,160 --> 00:47:35,640 Speaker 1: then how do we determine which one of the levers 808 00:47:35,680 --> 00:47:38,080 Speaker 1: we need to push? So I think based on what 809 00:47:38,080 --> 00:47:42,560 Speaker 1: you're saying, here, if we determine there's a challenge here 810 00:47:42,719 --> 00:47:45,839 Speaker 1: with our fond recruitment, I'm thinking there's three different levels 811 00:47:45,920 --> 00:47:47,440 Speaker 1: we can push, and you tell me if I'm wrong here. 812 00:47:47,480 --> 00:47:50,279 Speaker 1: But number one, first level you just talked about could 813 00:47:50,320 --> 00:47:52,799 Speaker 1: be habitat. We could change your habitat to try to 814 00:47:52,840 --> 00:47:55,520 Speaker 1: address that issue. Number two, we could try to push 815 00:47:55,560 --> 00:47:58,040 Speaker 1: the predator level, which would be some kind of predator management. 816 00:47:58,320 --> 00:48:02,200 Speaker 1: And then number three we could just adjust our own 817 00:48:02,280 --> 00:48:05,080 Speaker 1: doe harvest. So hunter doe harvest, you can adjust that 818 00:48:05,160 --> 00:48:08,080 Speaker 1: lever um. So here I am asking me a thousand questions. 819 00:48:08,120 --> 00:48:10,400 Speaker 1: I guess number one, Branson, are those there? Are those 820 00:48:10,480 --> 00:48:12,719 Speaker 1: the three levers? And then I'm gonna take us one 821 00:48:12,760 --> 00:48:15,440 Speaker 1: step back after you answer me that, Yeah, that that's 822 00:48:15,440 --> 00:48:17,680 Speaker 1: because that those are the three levers. Yeah, those are 823 00:48:17,719 --> 00:48:20,560 Speaker 1: the three options you have. If you manipulate any one 824 00:48:20,800 --> 00:48:23,440 Speaker 1: or all of those, then you can make a change exactly. 825 00:48:24,239 --> 00:48:26,239 Speaker 1: So then would that be in the case, how do 826 00:48:26,320 --> 00:48:31,440 Speaker 1: we determine if there's an issue? I guess, yeah, let's 827 00:48:31,480 --> 00:48:33,959 Speaker 1: start that. How do we figure that out? Okay, so 828 00:48:34,280 --> 00:48:37,800 Speaker 1: you can do this um with with the data collection, 829 00:48:38,160 --> 00:48:42,839 Speaker 1: so it doesn't need to be anything sophisticated, but all 830 00:48:42,880 --> 00:48:46,560 Speaker 1: it is is going to take some time. So and 831 00:48:46,840 --> 00:48:52,040 Speaker 1: I have seen this firsthand, and so I'll be and heck, 832 00:48:52,080 --> 00:48:54,520 Speaker 1: one of these was the home hunting club that I 833 00:48:54,560 --> 00:48:58,120 Speaker 1: was a part of. I started noticing a big problem 834 00:48:58,160 --> 00:49:03,279 Speaker 1: in that if you have really healthy deer I mean 835 00:49:03,400 --> 00:49:07,719 Speaker 1: the doze that we were harvesting or in fantastic condition 836 00:49:08,560 --> 00:49:14,000 Speaker 1: uh body size, body fat. But man, I started noticing 837 00:49:14,040 --> 00:49:15,520 Speaker 1: this trend. This was the first year I was in 838 00:49:15,560 --> 00:49:17,799 Speaker 1: this hunting club, and like, gosh, I don't understand this. 839 00:49:18,480 --> 00:49:22,440 Speaker 1: Half of the dose that we harvest during both season, 840 00:49:22,640 --> 00:49:27,000 Speaker 1: not late gun season, during archery season are not lactating. 841 00:49:27,680 --> 00:49:31,319 Speaker 1: Like we've we've got a problem here. And so I 842 00:49:31,400 --> 00:49:33,240 Speaker 1: let this go on just to make sure it wasn't 843 00:49:33,400 --> 00:49:36,560 Speaker 1: an anomaly. And you know, year two, yes, the exact 844 00:49:36,600 --> 00:49:40,760 Speaker 1: same Thing's like we we have less than uh fifties 845 00:49:40,800 --> 00:49:46,640 Speaker 1: sometimes only for lactation and adult females that are otherwise 846 00:49:46,640 --> 00:49:52,359 Speaker 1: in fantastic condition. Um. Then we started noticing that. UM. 847 00:49:53,600 --> 00:49:55,920 Speaker 1: I noticed right when I got on the property or 848 00:49:56,000 --> 00:50:00,200 Speaker 1: the hunting club that uh, the state of our forest 849 00:50:00,480 --> 00:50:03,319 Speaker 1: on that property was it was the obvious to me 850 00:50:03,560 --> 00:50:08,160 Speaker 1: that we didn't have any cover and coinced completely coincidental. 851 00:50:08,239 --> 00:50:12,120 Speaker 1: A little natural experiment took place. Uh. The property owner 852 00:50:12,280 --> 00:50:15,880 Speaker 1: of where we leased was a timber company. UH. Timber 853 00:50:15,920 --> 00:50:21,200 Speaker 1: company then came in and did a timber harvest, removed 854 00:50:21,239 --> 00:50:26,240 Speaker 1: three or four acres September. Uh. The next spring and summer, 855 00:50:26,440 --> 00:50:30,000 Speaker 1: now we had cover everywhere and even more developed the 856 00:50:30,080 --> 00:50:35,880 Speaker 1: next year and immediately, UH, the fawning fawn survival and 857 00:50:35,960 --> 00:50:38,960 Speaker 1: lactation rates shot right back up to normal. They were 858 00:50:39,000 --> 00:50:42,799 Speaker 1: seventy and eight. So that was just something personally that 859 00:50:42,840 --> 00:50:45,879 Speaker 1: happened to me. I didn't have to take any sophisticated measurements. 860 00:50:46,440 --> 00:50:50,000 Speaker 1: It's just basically where if I'm looking at lactation rate 861 00:50:50,239 --> 00:50:53,480 Speaker 1: and it is well below fifty or then you have 862 00:50:54,000 --> 00:50:58,799 Speaker 1: fawn's dying for some reason. Now, how would you assume 863 00:50:59,080 --> 00:51:02,120 Speaker 1: that it's kaya bodies? Well, A lot of that can 864 00:51:02,160 --> 00:51:05,759 Speaker 1: come from uh, your camera surveys. A lot of that 865 00:51:05,800 --> 00:51:08,560 Speaker 1: can come from scat surveys. You know. Things I would 866 00:51:08,600 --> 00:51:09,920 Speaker 1: do is I would get on my a t V. 867 00:51:10,040 --> 00:51:11,920 Speaker 1: And I would just drive our roads and when you're 868 00:51:11,920 --> 00:51:15,640 Speaker 1: seeing uh scat everywhere, I'm seeing deer hair in it 869 00:51:16,160 --> 00:51:17,879 Speaker 1: when I'm putting up. But you know I was doing 870 00:51:17,920 --> 00:51:20,800 Speaker 1: camera surveys all year long, and mean I get camera 871 00:51:20,880 --> 00:51:23,919 Speaker 1: surveys where I see a pack of two or three 872 00:51:23,920 --> 00:51:26,840 Speaker 1: coyotes in one frame and then an hour later I 873 00:51:26,880 --> 00:51:30,080 Speaker 1: see them running back with a fawn head in its mouth. 874 00:51:30,760 --> 00:51:33,000 Speaker 1: You know, all these things like that are pretty easy 875 00:51:33,080 --> 00:51:36,080 Speaker 1: to diagnose that when the deer herd, the condition of 876 00:51:36,120 --> 00:51:40,640 Speaker 1: the dough is very healthy and reproduction is low, then 877 00:51:40,640 --> 00:51:44,279 Speaker 1: that's probably what's going on. And even if you don't 878 00:51:44,320 --> 00:51:45,960 Speaker 1: want to, you know, if you don't want to get 879 00:51:46,000 --> 00:51:47,799 Speaker 1: back to the skin and shed and you don't you're 880 00:51:47,840 --> 00:51:50,400 Speaker 1: not sure about how to do this, lactation measurements and 881 00:51:50,480 --> 00:51:55,440 Speaker 1: lactation index um, use the tools that we have available 882 00:51:55,480 --> 00:51:58,200 Speaker 1: to you, or you know, just writing it down that 883 00:51:58,440 --> 00:52:01,920 Speaker 1: every time you go sit in a stand, you are 884 00:52:02,000 --> 00:52:04,880 Speaker 1: recording how many doughse and how many fawns you are seeing. 885 00:52:06,040 --> 00:52:09,360 Speaker 1: And if you get to beat the end of archery season, 886 00:52:09,440 --> 00:52:12,600 Speaker 1: assuming you had sufficient samples and well into gun season 887 00:52:13,040 --> 00:52:17,799 Speaker 1: where your hunters still can accurately identify an adult dode 888 00:52:17,920 --> 00:52:22,359 Speaker 1: or versus a fawn, and you've only seen about uh 889 00:52:22,520 --> 00:52:25,480 Speaker 1: one fawn for every three does or something like that, 890 00:52:26,239 --> 00:52:29,759 Speaker 1: then you very well may have you know, uh a 891 00:52:29,840 --> 00:52:33,160 Speaker 1: lot of fawns being eaten by predators. Is there any 892 00:52:33,520 --> 00:52:39,239 Speaker 1: formula or um easy system to input data into the 893 00:52:39,280 --> 00:52:41,960 Speaker 1: will help us determine some of those things that you said, 894 00:52:42,000 --> 00:52:45,040 Speaker 1: like fawn recruitment or whether it maybe whether observations or 895 00:52:45,040 --> 00:52:47,759 Speaker 1: trial camera surveys. Is there something like that out there 896 00:52:47,800 --> 00:52:50,640 Speaker 1: that you could point people towards to help actually, you know, 897 00:52:50,880 --> 00:52:55,440 Speaker 1: quantify this a little bit. Oh, absolutely well. A tool 898 00:52:55,480 --> 00:52:58,960 Speaker 1: that we develop some I'm very biased here of course, 899 00:52:59,080 --> 00:53:02,279 Speaker 1: but it's one of the tools we developed called the 900 00:53:02,520 --> 00:53:05,759 Speaker 1: Deer Hunt App, you know, a mobile app, and not 901 00:53:05,880 --> 00:53:08,000 Speaker 1: only does it do that for you, you know, you 902 00:53:08,000 --> 00:53:10,400 Speaker 1: can keep track of buck age structure, you can keep 903 00:53:10,480 --> 00:53:13,600 Speaker 1: track of adult sex ratio, you can keep track of 904 00:53:13,640 --> 00:53:16,000 Speaker 1: where hunters are seeing deer, where they're not seeing deer, 905 00:53:16,040 --> 00:53:19,760 Speaker 1: they're seeing them during the morning or during the afternoon, etcetera, etcetera. 906 00:53:20,200 --> 00:53:23,200 Speaker 1: But but literally, mark that was one of the most 907 00:53:23,280 --> 00:53:28,800 Speaker 1: prominent goals we had in mind, was that someone while 908 00:53:28,880 --> 00:53:32,719 Speaker 1: they are hunting is to collect data and you don't 909 00:53:32,760 --> 00:53:35,200 Speaker 1: have to rely to when your hunt is over and 910 00:53:35,320 --> 00:53:38,160 Speaker 1: drive back and record it on a data sheet. It 911 00:53:38,320 --> 00:53:41,000 Speaker 1: is simply an app that you can open up specific 912 00:53:41,040 --> 00:53:44,000 Speaker 1: to you, specific to your your property or your hunting 913 00:53:44,000 --> 00:53:48,080 Speaker 1: club and during your hunt you're just recording. You're just 914 00:53:48,120 --> 00:53:52,040 Speaker 1: tapping a button, doe, dough fawn or there's a dough 915 00:53:52,160 --> 00:53:56,239 Speaker 1: and two fawns. And then over time, if you and 916 00:53:56,440 --> 00:54:00,359 Speaker 1: enough people are doing that, then yeah, on on our app, 917 00:54:00,400 --> 00:54:02,520 Speaker 1: you just run a report and there is a metric 918 00:54:02,600 --> 00:54:06,440 Speaker 1: for you FAWD recruitment falls perdue and so literally the 919 00:54:06,480 --> 00:54:10,440 Speaker 1: math has done for you. And it's it's nothing that 920 00:54:10,560 --> 00:54:13,240 Speaker 1: you can't do yourself. I mean it is literally nothing 921 00:54:13,239 --> 00:54:15,120 Speaker 1: that if you got back to your truck or to 922 00:54:15,200 --> 00:54:17,000 Speaker 1: the skin and shed or whatever and wrote it down 923 00:54:17,040 --> 00:54:20,120 Speaker 1: on an index card or in an Excel spreadsheet. We're 924 00:54:20,120 --> 00:54:22,879 Speaker 1: not doing anything special. We're just making it very very 925 00:54:23,000 --> 00:54:27,040 Speaker 1: easy for you to do it and conveniently to do it. Yeah, 926 00:54:27,120 --> 00:54:31,360 Speaker 1: I love it. That's that's a big thing. Convenience. Um 927 00:54:31,400 --> 00:54:34,440 Speaker 1: So hey, Mark one more. I'd be remiss if I 928 00:54:34,440 --> 00:54:37,799 Speaker 1: didn't say this too. It depends on where you're at 929 00:54:38,000 --> 00:54:41,000 Speaker 1: in the country and relative to when fawning dates are 930 00:54:41,200 --> 00:54:43,840 Speaker 1: parturition dates. But also another way to do that is 931 00:54:44,120 --> 00:54:50,120 Speaker 1: of course with a camera survey. Um. Some people might 932 00:54:50,160 --> 00:54:53,480 Speaker 1: do a preseason you can kind of kill uh um 933 00:54:53,520 --> 00:54:56,400 Speaker 1: a bunch of birds with one stone and do a 934 00:54:56,440 --> 00:55:00,160 Speaker 1: preseason camera survey, and you can see, hey, what's my 935 00:55:00,200 --> 00:55:02,600 Speaker 1: buck age structure, what bucks do I want to protect? 936 00:55:02,719 --> 00:55:06,040 Speaker 1: What bucks DOILL want to harvest? And if if fawning 937 00:55:06,560 --> 00:55:10,640 Speaker 1: season was back, you know, six weeks or two months 938 00:55:10,680 --> 00:55:13,840 Speaker 1: before that time, then you would be able to also 939 00:55:13,960 --> 00:55:16,600 Speaker 1: count the number of fawns per doe you're seeing there. 940 00:55:17,200 --> 00:55:20,120 Speaker 1: So another easy tool you can do there that's not 941 00:55:20,200 --> 00:55:22,840 Speaker 1: as easy in Mississippi. A lot of times our fawns 942 00:55:22,840 --> 00:55:25,920 Speaker 1: are hitting the ground uh just maybe sometimes even a 943 00:55:25,920 --> 00:55:29,520 Speaker 1: few weeks before both season begins, and so we typically 944 00:55:29,719 --> 00:55:33,480 Speaker 1: underestimate fond recruitment when we do a preseason camera survey, 945 00:55:33,880 --> 00:55:36,319 Speaker 1: so we'll sometimes do do hours at the end of 946 00:55:36,320 --> 00:55:38,759 Speaker 1: the season. But but I wanted to say that, So 947 00:55:39,560 --> 00:55:41,600 Speaker 1: there there's typically three things you can look at. The 948 00:55:41,640 --> 00:55:45,800 Speaker 1: lactation index, you can look at uh during deer season 949 00:55:45,880 --> 00:55:49,279 Speaker 1: hunter observations, and then use your camera surveys through three 950 00:55:49,280 --> 00:55:52,040 Speaker 1: different ways you can tell now sometimes just thought of 951 00:55:52,120 --> 00:55:54,560 Speaker 1: as as you're describing this, you know, if we're looking 952 00:55:54,560 --> 00:55:59,080 Speaker 1: at those three different um OH variables or whatever, it 953 00:55:59,080 --> 00:56:01,719 Speaker 1: help us determine if there's an issue. Could those things 954 00:56:01,760 --> 00:56:05,440 Speaker 1: be impacted by other factors though, So could something like 955 00:56:06,280 --> 00:56:09,279 Speaker 1: just poor habitat in general, poor nutrition available, Could that 956 00:56:09,400 --> 00:56:12,200 Speaker 1: impact faun recruitment or lactation rates and things like that. 957 00:56:12,280 --> 00:56:16,200 Speaker 1: So we might be seeing these negative red flashing lights 958 00:56:16,280 --> 00:56:18,319 Speaker 1: and then we say, oh, it's gonna be coyotes then, 959 00:56:18,360 --> 00:56:22,120 Speaker 1: but could it be something else? Absolutely, I'm I'm glad 960 00:56:22,120 --> 00:56:25,000 Speaker 1: you brought that up. Um, So for me, what would 961 00:56:25,040 --> 00:56:28,319 Speaker 1: be the biggest signal to me that not only do 962 00:56:28,400 --> 00:56:31,759 Speaker 1: I have a fawn cover habitat problem, I've got a 963 00:56:31,920 --> 00:56:36,960 Speaker 1: food habitat problem. If the deer and poor condition, so 964 00:56:37,600 --> 00:56:40,839 Speaker 1: if dose, if their body weight is blow average, if 965 00:56:40,880 --> 00:56:44,920 Speaker 1: buck body weights and antler weight, antler sizes blow average, 966 00:56:45,320 --> 00:56:48,080 Speaker 1: and and even looking at fat, you know, getting when 967 00:56:48,080 --> 00:56:50,120 Speaker 1: you're skinning the deer and looking at that level of 968 00:56:50,160 --> 00:56:52,719 Speaker 1: fat on the rump, looking at kidney fat index, things 969 00:56:52,760 --> 00:56:55,879 Speaker 1: like that. That's when I start leaning more towards we've 970 00:56:55,920 --> 00:57:00,880 Speaker 1: got a situation here that yeah, predators maybe uh augmenting 971 00:57:01,239 --> 00:57:04,279 Speaker 1: the situation. They may not be the cause of it. 972 00:57:04,280 --> 00:57:07,279 Speaker 1: It looks like we've got a nutrition problem, and then 973 00:57:07,320 --> 00:57:09,680 Speaker 1: the predators are simply you know, making it a little 974 00:57:09,680 --> 00:57:13,759 Speaker 1: bit worse. So I look at the condition of the deer. Now, 975 00:57:14,120 --> 00:57:18,120 Speaker 1: you can always have a disease event, you know, it's 976 00:57:18,120 --> 00:57:20,720 Speaker 1: all It could always be possible that there's some specific 977 00:57:20,800 --> 00:57:23,680 Speaker 1: virus that may hit fawns a little more than it 978 00:57:23,720 --> 00:57:26,960 Speaker 1: would adults. Um, But that's probably just gonna be a 979 00:57:26,960 --> 00:57:30,160 Speaker 1: one year anomaly type thing. Most of these mark are 980 00:57:30,200 --> 00:57:32,920 Speaker 1: pretty chronic. You're not just gonna have this one year 981 00:57:33,000 --> 00:57:35,280 Speaker 1: where faun recruitment is really down unless it was some 982 00:57:35,320 --> 00:57:39,240 Speaker 1: type of disease. Usually these things build slowly over time. 983 00:57:39,240 --> 00:57:44,800 Speaker 1: The habitat gets progressively worse over time, Predator populations grow 984 00:57:45,000 --> 00:57:47,600 Speaker 1: over time, and you start seeing this trend that you 985 00:57:47,640 --> 00:57:52,680 Speaker 1: can pick up. Okay, so we've we've kind of determined 986 00:57:52,840 --> 00:57:57,680 Speaker 1: that if you're seeing a healthy deer population like the 987 00:57:57,720 --> 00:58:00,240 Speaker 1: deer that are on your property or healthy, what your 988 00:58:00,280 --> 00:58:03,280 Speaker 1: fond recruitment is lower, the lactation raise is low. That's 989 00:58:03,320 --> 00:58:06,320 Speaker 1: pointing two. Okay, maybe we have a predator impact happening here. 990 00:58:06,640 --> 00:58:09,320 Speaker 1: And as we talked about already, that's probably more so 991 00:58:09,440 --> 00:58:11,280 Speaker 1: the exception than the role. But let's say we're in 992 00:58:11,280 --> 00:58:14,840 Speaker 1: that situation where we're looking at these different factors and saying, Okay, yeah, 993 00:58:14,960 --> 00:58:18,080 Speaker 1: it really does look like predators are making a significant impact. Here. 994 00:58:18,600 --> 00:58:21,160 Speaker 1: We've got three levers of press. As we talked about already. 995 00:58:21,200 --> 00:58:23,400 Speaker 1: We we said we could actually manage the predators. We 996 00:58:23,520 --> 00:58:27,200 Speaker 1: could improve the habitat, or we could adjust our harvest. 997 00:58:27,920 --> 00:58:31,360 Speaker 1: Could you rank for me how affect or how would 998 00:58:31,360 --> 00:58:34,080 Speaker 1: you rank those three levers in effect in scale of 999 00:58:34,280 --> 00:58:37,560 Speaker 1: what's the most effective to least effective, and or which 1000 00:58:37,560 --> 00:58:39,800 Speaker 1: ones we should try first? Like? How should we go 1001 00:58:39,920 --> 00:58:43,720 Speaker 1: through those lists of levers? Okay? Sure thing? So one 1002 00:58:43,720 --> 00:58:46,400 Speaker 1: thing we have to consider from from the onset is 1003 00:58:46,440 --> 00:58:48,760 Speaker 1: do you own the property or not? Or do you 1004 00:58:48,800 --> 00:58:54,439 Speaker 1: have permission and the ability to manage the habitat? So 1005 00:58:54,800 --> 00:58:57,840 Speaker 1: like me the situation I was in, I least property, 1006 00:58:58,800 --> 00:59:01,400 Speaker 1: I had that that option, that lever was taken away 1007 00:59:01,400 --> 00:59:03,919 Speaker 1: from me. I can't manage the habitat. So I'm left 1008 00:59:03,960 --> 00:59:08,720 Speaker 1: with two things. I'm left with. Um, we need to 1009 00:59:08,840 --> 00:59:13,160 Speaker 1: adjust our expectations. So it might be that we just say, hey, 1010 00:59:13,360 --> 00:59:16,160 Speaker 1: our dear herd is going to be smaller than it 1011 00:59:16,240 --> 00:59:21,720 Speaker 1: used to be. Um, we might are we satisfied with that? Uh? 1012 00:59:21,840 --> 00:59:25,160 Speaker 1: Maybe rather than harvesting this level of dose every year, 1013 00:59:25,800 --> 00:59:28,160 Speaker 1: we only need to harvest you know, this level half 1014 00:59:28,200 --> 00:59:31,240 Speaker 1: the amount of dose every year and we might reach 1015 00:59:31,360 --> 00:59:34,320 Speaker 1: then an equilibrium. The coyotes are gonna take some, but 1016 00:59:34,640 --> 00:59:37,800 Speaker 1: the hunters are taking less, and so we can reach 1017 00:59:37,880 --> 00:59:40,440 Speaker 1: that that balancing point of where we're still happy as 1018 00:59:40,520 --> 00:59:43,040 Speaker 1: hunters with the number of deer we're seeing in the 1019 00:59:43,080 --> 00:59:47,520 Speaker 1: condition of those deer that we're seeing. Um. The other 1020 00:59:47,520 --> 00:59:49,920 Speaker 1: one would be, if I'm leasing land, would be to 1021 00:59:50,240 --> 00:59:55,680 Speaker 1: try to manage the predator, and that is just not 1022 00:59:55,760 --> 00:59:59,280 Speaker 1: going to be for most people that effective. Um, it's 1023 00:59:59,320 --> 01:00:02,640 Speaker 1: gonna be very costly unless you're doing it all yourself. 1024 01:00:03,560 --> 01:00:06,920 Speaker 1: And these coyotes are pretty darn amazing in terms of 1025 01:00:08,000 --> 01:00:11,720 Speaker 1: how quickly once you remove them from the landscape, that 1026 01:00:11,880 --> 01:00:15,960 Speaker 1: territory or home range that was left vacant uh quickly 1027 01:00:16,000 --> 01:00:21,840 Speaker 1: becomes occupied. And so we advise people if that is 1028 01:00:21,880 --> 01:00:25,320 Speaker 1: an action you choose to take, you really need to 1029 01:00:25,360 --> 01:00:31,680 Speaker 1: focus your trapping efforts during or immediately preceding the fawning season. 1030 01:00:32,160 --> 01:00:35,320 Speaker 1: Whenever fawns are hitting the ground uh in your neck 1031 01:00:35,360 --> 01:00:37,720 Speaker 1: of the woods, right before that is when the trapping 1032 01:00:37,760 --> 01:00:41,800 Speaker 1: effort should be taken place. And you know, if it's 1033 01:00:41,800 --> 01:00:44,400 Speaker 1: one of these, if you have a sizable property and 1034 01:00:44,520 --> 01:00:47,360 Speaker 1: you're only removing two or three coyotes off that property. 1035 01:00:48,760 --> 01:00:52,720 Speaker 1: Unless you just have fun doing it, you're probably not 1036 01:00:52,760 --> 01:00:56,720 Speaker 1: having an impact whatsoever. You really need to remove a 1037 01:00:56,880 --> 01:01:00,480 Speaker 1: large proportion of coyotes off the lands escape and then 1038 01:01:00,560 --> 01:01:07,480 Speaker 1: it becomes an annual event. But of the those those 1039 01:01:07,520 --> 01:01:11,560 Speaker 1: coyotes are gonna transient coyotes that are moving around looking 1040 01:01:11,600 --> 01:01:14,120 Speaker 1: for an open territory as soon as the one's gone 1041 01:01:14,120 --> 01:01:18,400 Speaker 1: to backfill and and occupy that new territory. So that 1042 01:01:18,400 --> 01:01:21,120 Speaker 1: that brings me to you know what, am I getting 1043 01:01:21,160 --> 01:01:25,080 Speaker 1: the most bang for the buck for pun intended? That 1044 01:01:25,560 --> 01:01:28,640 Speaker 1: is gonna, you know, be enduring that I'm gonna get 1045 01:01:28,800 --> 01:01:32,040 Speaker 1: years and years of benefit from. And that's gonna be 1046 01:01:32,080 --> 01:01:38,880 Speaker 1: habitat management. I'm never gonna eliminate fawn predation by coyotes. 1047 01:01:38,960 --> 01:01:42,600 Speaker 1: I'm never going to eliminate that, but I think it 1048 01:01:42,640 --> 01:01:46,320 Speaker 1: can be minimized to a great degree by just managing 1049 01:01:46,360 --> 01:01:50,320 Speaker 1: the understory. And that's gonna be the habitat tools we 1050 01:01:50,400 --> 01:01:53,600 Speaker 1: talk about all the time. At Priority number one is 1051 01:01:53,840 --> 01:01:59,680 Speaker 1: getting sunlight on the ground, and whether that be whether 1052 01:01:59,720 --> 01:02:03,160 Speaker 1: that be with prescribed fire, whether that be with typically 1053 01:02:03,160 --> 01:02:06,400 Speaker 1: it's gonna take a thinning operation. It might be a 1054 01:02:06,400 --> 01:02:09,920 Speaker 1: clear cut. It might be thinning whatever that is, but 1055 01:02:09,960 --> 01:02:14,800 Speaker 1: getting sunlight on the ground and developing that understory so 1056 01:02:14,880 --> 01:02:18,360 Speaker 1: that you can develop both cover and food. Like I say, 1057 01:02:18,440 --> 01:02:20,560 Speaker 1: you know, knee hide to waste tile where you can 1058 01:02:20,560 --> 01:02:23,840 Speaker 1: throw that basketball and hide it. That is probably gonna 1059 01:02:23,920 --> 01:02:27,600 Speaker 1: be over time, the least amount of effort you have 1060 01:02:27,680 --> 01:02:29,760 Speaker 1: to put in and you're gonna get the most result 1061 01:02:29,960 --> 01:02:35,640 Speaker 1: from it over time. Yeah, there's one other lever um 1062 01:02:35,680 --> 01:02:38,200 Speaker 1: that I'm wondering if you would add to this too, 1063 01:02:38,240 --> 01:02:41,200 Speaker 1: that I just thought of. I've I've heard in the past. 1064 01:02:41,720 --> 01:02:46,520 Speaker 1: We mentioned earlier birth synchrony, that you can influence birth 1065 01:02:46,560 --> 01:02:50,360 Speaker 1: synchrony um a little bit with your herd structure, with 1066 01:02:50,480 --> 01:02:53,280 Speaker 1: doing things to improve your heard, whether it be aid 1067 01:02:53,360 --> 01:02:56,000 Speaker 1: structure or about to do ratio. Is that true? Are 1068 01:02:56,000 --> 01:02:57,920 Speaker 1: the things we can do when we make our hunting 1069 01:02:58,160 --> 01:03:01,200 Speaker 1: shooter don't shoot decisions that actually help us make sure 1070 01:03:01,200 --> 01:03:04,920 Speaker 1: we get that prey overload that could help minimize predation 1071 01:03:04,960 --> 01:03:11,880 Speaker 1: as well. Um, Yes, to a degree. Um. Usually the 1072 01:03:11,920 --> 01:03:15,880 Speaker 1: way that happens historically, you know, when we talk about 1073 01:03:15,960 --> 01:03:19,840 Speaker 1: back in the day before you know, quality deer management 1074 01:03:19,880 --> 01:03:23,720 Speaker 1: really took hold in North America when we had when 1075 01:03:23,760 --> 01:03:28,000 Speaker 1: we were during the establishment period, dose were protected and 1076 01:03:28,120 --> 01:03:30,760 Speaker 1: the you know, the bucks were just hammered, and we 1077 01:03:30,840 --> 01:03:34,440 Speaker 1: had these adult sex ratios that were way out of whack, 1078 01:03:34,520 --> 01:03:36,840 Speaker 1: and so we had four to one, five to one, 1079 01:03:36,880 --> 01:03:41,400 Speaker 1: six to one, etcetera adult dose to adult bucks. That 1080 01:03:41,600 --> 01:03:47,160 Speaker 1: is the single biggest cause of the ruts or conception 1081 01:03:47,280 --> 01:03:50,680 Speaker 1: dates being spread out so long. And the reason that 1082 01:03:50,880 --> 01:03:54,440 Speaker 1: is is that when you have dose coming into heat, 1083 01:03:54,760 --> 01:03:58,200 Speaker 1: they are pretty much already synchronized in an area, and 1084 01:03:58,280 --> 01:04:01,440 Speaker 1: so they're coming into heat and you literally don't have 1085 01:04:01,600 --> 01:04:05,680 Speaker 1: enough adult bucks to breathe the dose as they come 1086 01:04:05,720 --> 01:04:09,640 Speaker 1: in to heat, and so you might have you might 1087 01:04:09,680 --> 01:04:12,120 Speaker 1: only get half of the dough's bread during their first 1088 01:04:12,240 --> 01:04:15,360 Speaker 1: extra cycle, and then they have to cycle again, you know, 1089 01:04:15,400 --> 01:04:17,560 Speaker 1: about twenty eight days later, and then they're bread the 1090 01:04:17,600 --> 01:04:21,040 Speaker 1: second time and maybe even the third time. That's typically 1091 01:04:21,120 --> 01:04:25,080 Speaker 1: when we see those partriition dates really spread out. We 1092 01:04:25,120 --> 01:04:29,120 Speaker 1: don't see that as much nowadays. Um, without a doubt. 1093 01:04:29,160 --> 01:04:31,920 Speaker 1: In some places, the sex ratio is still far in 1094 01:04:32,000 --> 01:04:34,400 Speaker 1: favor of females, but it's typically not on a large 1095 01:04:34,400 --> 01:04:37,320 Speaker 1: scale the way it used to be. So just getting 1096 01:04:37,320 --> 01:04:41,200 Speaker 1: the adult the buck to do sex ratio in that 1097 01:04:41,320 --> 01:04:44,080 Speaker 1: good you know, two to one or one and a 1098 01:04:44,120 --> 01:04:48,800 Speaker 1: half to one ratio, then then your your partriition dates 1099 01:04:48,800 --> 01:04:51,520 Speaker 1: are pretty much going to be synchronized for you without 1100 01:04:51,560 --> 01:04:55,720 Speaker 1: you having to really take any active role. Okay. Interesting, 1101 01:04:56,000 --> 01:04:57,760 Speaker 1: That's always been one of those things that I've wondered 1102 01:04:57,760 --> 01:05:00,600 Speaker 1: if if you can improve things a little bit there. Um. 1103 01:05:00,800 --> 01:05:04,320 Speaker 1: So it's good to get that additional context. So I 1104 01:05:04,320 --> 01:05:06,440 Speaker 1: feel like we we've covered a lot here, Bronson. We've 1105 01:05:06,480 --> 01:05:09,919 Speaker 1: kind of gone down this funnel of ideas to help 1106 01:05:10,000 --> 01:05:12,560 Speaker 1: us understand, Okay, what's the situation, how much of an 1107 01:05:12,560 --> 01:05:15,120 Speaker 1: impact of predators have in what ways of the making 1108 01:05:15,120 --> 01:05:18,520 Speaker 1: an impact? How do we determine what that impact is, 1109 01:05:18,640 --> 01:05:21,000 Speaker 1: how do we choose what levers to push if there 1110 01:05:21,120 --> 01:05:25,480 Speaker 1: is an impact? Um. It's it's really interesting stuff. And 1111 01:05:25,520 --> 01:05:27,600 Speaker 1: I think what I was hoping we could do here, 1112 01:05:27,600 --> 01:05:29,280 Speaker 1: and what I think we did is I think we've 1113 01:05:29,360 --> 01:05:33,160 Speaker 1: kind of kind of done like a reality check because 1114 01:05:33,240 --> 01:05:34,840 Speaker 1: there's a lot. As we talked about a little bit 1115 01:05:34,880 --> 01:05:37,760 Speaker 1: a while ago, it's easy sometimes to point the finger 1116 01:05:37,800 --> 01:05:42,240 Speaker 1: at like the big pointy, sharp edge, sharp fang, shiny 1117 01:05:42,320 --> 01:05:44,880 Speaker 1: thing and say that's that's the big bad wolf for 1118 01:05:44,920 --> 01:05:47,800 Speaker 1: the big bag coyote, maybe sometimes they are, they are 1119 01:05:47,840 --> 01:05:50,360 Speaker 1: a challenge, maybe sometimes they aren't. But I think going 1120 01:05:50,400 --> 01:05:52,960 Speaker 1: through this helps us understand, Okay, what are the impact? 1121 01:05:53,440 --> 01:05:56,920 Speaker 1: How do we work within the constraints of whatever situation 1122 01:05:57,040 --> 01:05:59,400 Speaker 1: we're in to to deal with that, live with that, 1123 01:05:59,480 --> 01:06:03,400 Speaker 1: whatever it might be. UM. But I'm going to ask you, 1124 01:06:04,200 --> 01:06:06,360 Speaker 1: and maybe you don't want to do this, but would 1125 01:06:06,400 --> 01:06:10,080 Speaker 1: you if you're willing to take off your scientists research 1126 01:06:10,160 --> 01:06:12,280 Speaker 1: or biologist hat I take off that head and then 1127 01:06:12,320 --> 01:06:17,800 Speaker 1: put just your hunter um or. And I'm assuming based 1128 01:06:17,840 --> 01:06:19,560 Speaker 1: on everything I know about you and as I've talked 1129 01:06:19,560 --> 01:06:21,560 Speaker 1: to you, I think that you are not only just 1130 01:06:21,600 --> 01:06:24,240 Speaker 1: a hunter and a researcher, but a conservationist and someone 1131 01:06:24,280 --> 01:06:31,040 Speaker 1: who appreciates wildlife. Is there if we're looking outside just 1132 01:06:31,080 --> 01:06:36,960 Speaker 1: the management implications, is there an ethical um obligation that 1133 01:06:37,000 --> 01:06:39,400 Speaker 1: we have just as people who who like to call 1134 01:06:39,440 --> 01:06:46,400 Speaker 1: ourselves conservationists UM two, not just what am I trying 1135 01:06:46,400 --> 01:06:50,160 Speaker 1: to say to to somewhat embrace or learn to coexist 1136 01:06:50,240 --> 01:06:53,680 Speaker 1: with predators? Is there is there something to be said 1137 01:06:53,880 --> 01:06:57,360 Speaker 1: about learning to live with these other animals versus the 1138 01:06:57,400 --> 01:07:00,320 Speaker 1: scorched earth policy of the fact that our compet Titian 1139 01:07:00,360 --> 01:07:01,880 Speaker 1: we gotta wipe him off the face of the earth, 1140 01:07:01,880 --> 01:07:04,920 Speaker 1: because that's kind of what we did in the eighteen hundreds, 1141 01:07:04,920 --> 01:07:08,600 Speaker 1: in early nineteen hundreds. Um, and things have changed. Um, 1142 01:07:08,600 --> 01:07:10,560 Speaker 1: But I'm just curious if you would be willing to 1143 01:07:10,600 --> 01:07:13,320 Speaker 1: speak at all to what your opinion or thoughts are 1144 01:07:13,360 --> 01:07:17,200 Speaker 1: on on the ethics of of how we interact with predators. Um, 1145 01:07:17,240 --> 01:07:18,760 Speaker 1: if it's a good thing, if it's a bad thing, 1146 01:07:18,800 --> 01:07:20,920 Speaker 1: if we can learn to find a middle ground. Is 1147 01:07:20,920 --> 01:07:24,000 Speaker 1: that something you can offer a few thoughts on. Well, heck, yeah, 1148 01:07:24,120 --> 01:07:26,640 Speaker 1: I don't. I don't think I can be wrong since 1149 01:07:26,760 --> 01:07:29,000 Speaker 1: you said I could take off my scientist's cap and 1150 01:07:29,120 --> 01:07:35,640 Speaker 1: just give you my opinion. Um. You know, I certainly 1151 01:07:35,760 --> 01:07:40,479 Speaker 1: have a bias, um, just because of who I am 1152 01:07:40,600 --> 01:07:45,600 Speaker 1: and how I'm made up and my interest. Um. I 1153 01:07:45,640 --> 01:07:50,200 Speaker 1: think back to an Aldo Leopold essay, one of my 1154 01:07:50,440 --> 01:07:54,880 Speaker 1: most favorite, and it's called think like a Mountain, and 1155 01:07:55,120 --> 01:07:58,800 Speaker 1: Aldo's perspective was, you know, and there's so many nuances. 1156 01:07:58,880 --> 01:08:03,760 Speaker 1: I mean, it's just beautiful, just a beautiful essay. But 1157 01:08:03,760 --> 01:08:11,400 Speaker 1: but essentially the mountain needed the wolf because when when Aldo, 1158 01:08:11,480 --> 01:08:13,960 Speaker 1: you know, shot that last she wolf and saw the 1159 01:08:14,040 --> 01:08:16,760 Speaker 1: fire go out in that she wolf's eye that the 1160 01:08:16,840 --> 01:08:22,320 Speaker 1: mountain subsequently suffered for that, and the dear population grew 1161 01:08:22,439 --> 01:08:25,680 Speaker 1: and took over the range. And you know, he was 1162 01:08:25,720 --> 01:08:29,360 Speaker 1: really making a point there that predators are part of 1163 01:08:29,360 --> 01:08:33,559 Speaker 1: the system, and predators are are are needed, you know, 1164 01:08:33,680 --> 01:08:39,320 Speaker 1: for for for a balanced ecosystem. So UM, I really 1165 01:08:39,360 --> 01:08:42,479 Speaker 1: think you know, in society at large, you know, and 1166 01:08:42,479 --> 01:08:46,720 Speaker 1: there's all sorts of different sides to this argument, but 1167 01:08:47,640 --> 01:08:51,840 Speaker 1: there was very compelling evidence for you need in Yellowstone, 1168 01:08:51,840 --> 01:08:54,519 Speaker 1: you need to have some wolves. Uh, you need to 1169 01:08:54,560 --> 01:08:58,320 Speaker 1: have the predator. Um. One of my mentors years ago, 1170 01:08:58,479 --> 01:09:02,280 Speaker 1: I hope I can remember his famous quote said it 1171 01:09:02,400 --> 01:09:05,840 Speaker 1: so beautifully. One of my advisors when I was undergraduate 1172 01:09:05,840 --> 01:09:10,200 Speaker 1: was Larry Marshington at the University of Georgia and said, 1173 01:09:10,240 --> 01:09:16,040 Speaker 1: the the predator needs the the prey needs the predator, 1174 01:09:16,160 --> 01:09:19,479 Speaker 1: just like the predator needs the prey. If you take 1175 01:09:19,520 --> 01:09:25,720 Speaker 1: away the predator, Uh, a deer becomes a cow, a 1176 01:09:25,800 --> 01:09:31,000 Speaker 1: wolf becomes a dog, and what does man become. I 1177 01:09:31,040 --> 01:09:33,080 Speaker 1: don't know if I got that exactly right, but that's 1178 01:09:33,160 --> 01:09:36,639 Speaker 1: the part I could remember, and and that thing really 1179 01:09:36,720 --> 01:09:40,599 Speaker 1: stuck with me that you know, we also play a predator, 1180 01:09:40,720 --> 01:09:44,240 Speaker 1: we play a predatory role with deer and and uh 1181 01:09:44,320 --> 01:09:47,360 Speaker 1: and other animals in the environments we live in. And 1182 01:09:47,439 --> 01:09:51,400 Speaker 1: so I think it's really important. I think it's important 1183 01:09:51,439 --> 01:09:54,920 Speaker 1: for the ecological integrity of of the places we hunt 1184 01:09:55,080 --> 01:09:58,800 Speaker 1: and conserve that the predator should be part of the system. Now, 1185 01:09:58,840 --> 01:10:04,960 Speaker 1: without a doubt, Uh, can they Um? Can population levels 1186 01:10:04,960 --> 01:10:10,640 Speaker 1: get out of control? Absolutely? Uh? Can humans coexist in 1187 01:10:10,680 --> 01:10:13,320 Speaker 1: some areas with some really large predators, Well, that's gonna 1188 01:10:13,360 --> 01:10:18,799 Speaker 1: be really difficult. It'd be really difficult for um mountain 1189 01:10:18,840 --> 01:10:22,880 Speaker 1: lions to be saturated saturate the forests of Mississippi, you know. 1190 01:10:22,960 --> 01:10:25,320 Speaker 1: There there are some of these really big predators that 1191 01:10:25,320 --> 01:10:28,520 Speaker 1: that do make it more difficult for us to coexist 1192 01:10:28,640 --> 01:10:32,599 Speaker 1: in terms of a human safety perspective, but in terms 1193 01:10:32,600 --> 01:10:36,160 Speaker 1: of a predator that maybe limiting in some places a 1194 01:10:36,200 --> 01:10:39,200 Speaker 1: deer population by taking a few adults deer here and 1195 01:10:39,240 --> 01:10:43,400 Speaker 1: there and taking a few falls here and there. You know, honestly, 1196 01:10:43,439 --> 01:10:48,000 Speaker 1: I'm just fine with that. Yeah. Yeah, I appreciate you 1197 01:10:48,040 --> 01:10:50,960 Speaker 1: sharing that, bronze, And I think that's a really really 1198 01:10:50,960 --> 01:10:54,640 Speaker 1: helpful perspective to here, especially from your from your experience 1199 01:10:54,680 --> 01:10:56,920 Speaker 1: that being involved in a lot of the a lot 1200 01:10:56,960 --> 01:11:00,720 Speaker 1: of the data and numbers and research behind understanding these 1201 01:11:00,720 --> 01:11:03,639 Speaker 1: interactions both from the ecological perspective, but then also from 1202 01:11:03,640 --> 01:11:08,799 Speaker 1: the social perspective, how hunters and predators kind of sometimes 1203 01:11:08,840 --> 01:11:13,360 Speaker 1: clash sometimes can coexist. That dynamic between these two sometimes 1204 01:11:13,400 --> 01:11:17,320 Speaker 1: competing um parts of the system out there, it causes 1205 01:11:17,360 --> 01:11:20,680 Speaker 1: a lot of turmoil at times. But I think, and 1206 01:11:20,720 --> 01:11:23,240 Speaker 1: I gain this is just my opinion, but I think 1207 01:11:23,280 --> 01:11:25,840 Speaker 1: that it's it is important for us to find that 1208 01:11:26,280 --> 01:11:28,880 Speaker 1: way to coexist for all the reasons you just said, 1209 01:11:29,320 --> 01:11:32,280 Speaker 1: and then also because and this is something that i've 1210 01:11:32,920 --> 01:11:38,559 Speaker 1: again I've thought just from a pragmatic standpoint that if 1211 01:11:38,600 --> 01:11:41,679 Speaker 1: if we want to call ourselves conservations, if we want 1212 01:11:41,680 --> 01:11:44,360 Speaker 1: to like make this pitch to the outside world that 1213 01:11:44,360 --> 01:11:47,960 Speaker 1: we as hunters are good for conservation and we protect 1214 01:11:48,000 --> 01:11:51,000 Speaker 1: wildlife and do all these things. Um, if we just 1215 01:11:51,120 --> 01:11:54,599 Speaker 1: point to deer and say we we do that for deer, 1216 01:11:54,640 --> 01:11:56,360 Speaker 1: but we're not going to care at all about this 1217 01:11:56,439 --> 01:11:59,120 Speaker 1: other pocket of of species, I think we lose some 1218 01:11:59,160 --> 01:12:01,559 Speaker 1: credibility there. And that's always been one of the things 1219 01:12:01,600 --> 01:12:04,720 Speaker 1: that if if we care at all about how the 1220 01:12:04,760 --> 01:12:08,200 Speaker 1: rest of the of the country looks at hunting and hunters, 1221 01:12:08,360 --> 01:12:10,920 Speaker 1: and how we can go forward in the future. I 1222 01:12:10,920 --> 01:12:14,080 Speaker 1: think simply from that standpoint, it benefits us to learn 1223 01:12:14,120 --> 01:12:17,200 Speaker 1: to to be conservations for all species and animals and 1224 01:12:17,479 --> 01:12:20,599 Speaker 1: learn to think about these things as is a it's 1225 01:12:20,640 --> 01:12:23,439 Speaker 1: a larger integrated system. I think that's beneficial just from 1226 01:12:23,439 --> 01:12:27,080 Speaker 1: that standpoint to um, So, I could not agree more, 1227 01:12:27,280 --> 01:12:30,040 Speaker 1: could not agree more. Yeah, when you say integrated system, 1228 01:12:30,240 --> 01:12:33,920 Speaker 1: that that's an ecosystem, and that that's what we're supposed 1229 01:12:33,960 --> 01:12:37,559 Speaker 1: to preserve and and protect and conserve and be a 1230 01:12:37,560 --> 01:12:40,519 Speaker 1: part of. Yeah, how do we keep the integrity of 1231 01:12:40,520 --> 01:12:43,240 Speaker 1: an ecosystem while we're a part of it and and 1232 01:12:43,280 --> 01:12:46,519 Speaker 1: predators are a part of it as well. Yeah. So, 1233 01:12:46,520 --> 01:12:48,960 Speaker 1: So to wrap this up, Bronson, I want to read you, 1234 01:12:49,320 --> 01:12:52,640 Speaker 1: um a summary from a University of Georgia report that 1235 01:12:52,760 --> 01:12:55,759 Speaker 1: came out a year and a half or two years ago. UM. 1236 01:12:55,800 --> 01:12:57,400 Speaker 1: I think it kind of sums up a lot of 1237 01:12:57,400 --> 01:12:59,680 Speaker 1: what we've talked about really neatly, and I just like 1238 01:12:59,760 --> 01:13:01,599 Speaker 1: to read it and then if you want to add 1239 01:13:01,640 --> 01:13:04,040 Speaker 1: anything or clarify anything, just so we can kind of 1240 01:13:04,080 --> 01:13:05,800 Speaker 1: wrap a bow on this for everyone. Tell me if 1241 01:13:05,840 --> 01:13:08,080 Speaker 1: you agree with us too. Um. But the summery of 1242 01:13:08,080 --> 01:13:12,439 Speaker 1: this report says this quote white tailed deer have multiple predators, 1243 01:13:12,439 --> 01:13:16,559 Speaker 1: and individuals sometimes are killed by those predators. However, healthy 1244 01:13:16,600 --> 01:13:20,480 Speaker 1: deer herds can and do exist in places with abundant predators. 1245 01:13:20,960 --> 01:13:23,640 Speaker 1: Although it is easy to dismiss the role of predators 1246 01:13:23,640 --> 01:13:27,080 Speaker 1: as purely negative when regarding deer management, it's important to 1247 01:13:27,080 --> 01:13:29,960 Speaker 1: remember that predators are a natural and normal part of 1248 01:13:29,960 --> 01:13:34,240 Speaker 1: a healthy, well managed ecosystem. To assume predators have no 1249 01:13:34,320 --> 01:13:38,479 Speaker 1: beneficial purpose and deer management is to ignore the facts. However, 1250 01:13:38,880 --> 01:13:42,479 Speaker 1: when predator populations become too abundant and affect deer management 1251 01:13:42,479 --> 01:13:46,440 Speaker 1: goals and open discussion regarding the appropriate management action is justified. 1252 01:13:46,640 --> 01:13:51,640 Speaker 1: Predator reductions via trapping or shooting, habitat management, excuse me, 1253 01:13:51,720 --> 01:13:54,720 Speaker 1: habitat management, and or changes in deer harvests are all 1254 01:13:54,760 --> 01:13:59,320 Speaker 1: possible options that require careful and calculated review of available facts. 1255 01:13:59,760 --> 01:14:04,080 Speaker 1: The answer is not a landscape without predators. End quote. 1256 01:14:04,960 --> 01:14:06,880 Speaker 1: Does that kind of tie this all up? Or do 1257 01:14:06,920 --> 01:14:09,120 Speaker 1: you disagree with anything there? Or would you add anything? 1258 01:14:10,439 --> 01:14:15,719 Speaker 1: I think that was appropriate and beautiful. Yeah, I could 1259 01:14:15,720 --> 01:14:19,519 Speaker 1: not agree or endorse that anymore. I think the they 1260 01:14:19,800 --> 01:14:23,920 Speaker 1: hit the nail on the head. Awesome, Bronson. I can't 1261 01:14:23,960 --> 01:14:25,920 Speaker 1: thank you enough. For taking the time to talk through 1262 01:14:25,920 --> 01:14:28,679 Speaker 1: all this with us, and I want to make sure 1263 01:14:28,800 --> 01:14:31,000 Speaker 1: to give you an opportunity to share with our audience 1264 01:14:31,600 --> 01:14:34,280 Speaker 1: where they can learn more from you from what you 1265 01:14:34,320 --> 01:14:36,759 Speaker 1: guys are doing over the Deer Lab. Any new projects 1266 01:14:36,760 --> 01:14:38,880 Speaker 1: you have, what what can you tell us and where 1267 01:14:38,880 --> 01:14:42,360 Speaker 1: can we find some of this stuff? Yeah? Absolutely, thank 1268 01:14:42,360 --> 01:14:47,040 Speaker 1: you for the opportunity. I really enjoyed today. Um So 1269 01:14:47,200 --> 01:14:50,000 Speaker 1: some things we have coming up. We are in the 1270 01:14:50,080 --> 01:14:52,719 Speaker 1: midst where you're halfway through a project that I can't 1271 01:14:52,720 --> 01:14:55,719 Speaker 1: wait to visit with you in the future about looking 1272 01:14:55,720 --> 01:15:01,280 Speaker 1: at the interaction of bucks and hunters and and uh, 1273 01:15:01,320 --> 01:15:03,719 Speaker 1: we're doing an experiment. It was very similar to something 1274 01:15:03,760 --> 01:15:07,040 Speaker 1: Steve Demeris did in Oklahoma about a decade ago. But 1275 01:15:07,560 --> 01:15:11,599 Speaker 1: we're looking at the response of bucks essentially to hunting pressure. 1276 01:15:12,320 --> 01:15:15,960 Speaker 1: How often they get disturbed, Does it change their activity pattern, 1277 01:15:16,040 --> 01:15:18,479 Speaker 1: does it change where they spend time and how they 1278 01:15:18,520 --> 01:15:21,120 Speaker 1: spend time? And so we think that's gonna be really 1279 01:15:21,120 --> 01:15:25,360 Speaker 1: really insightful looking at that how hunters and level of 1280 01:15:25,479 --> 01:15:28,240 Speaker 1: hunting intensity is going to impact the deer hurts. So 1281 01:15:28,920 --> 01:15:31,440 Speaker 1: we have that going on, and we have some prescribed 1282 01:15:31,479 --> 01:15:34,479 Speaker 1: fire studies going on looking at timing of fire and 1283 01:15:34,479 --> 01:15:38,120 Speaker 1: when is it most beneficial from a deer and wildlife 1284 01:15:38,120 --> 01:15:43,200 Speaker 1: perspective to burn a lot of other projects like that. UM. 1285 01:15:43,320 --> 01:15:46,320 Speaker 1: We have a podcast that I would hope people would 1286 01:15:46,320 --> 01:15:50,240 Speaker 1: tune into, and it's all about dear biology and deer 1287 01:15:50,280 --> 01:15:54,519 Speaker 1: management and science. And it's it's less about hunting but 1288 01:15:54,640 --> 01:15:57,559 Speaker 1: more about the nitty gritty of the things you probably 1289 01:15:57,680 --> 01:15:59,919 Speaker 1: put you to sleep when you were in high school biology. 1290 01:16:00,040 --> 01:16:03,160 Speaker 1: But when we take those topics and kind of apply 1291 01:16:03,280 --> 01:16:06,400 Speaker 1: them to to deer management, and we try to take 1292 01:16:06,840 --> 01:16:09,759 Speaker 1: all the different questions and myths you know that people 1293 01:16:09,800 --> 01:16:13,240 Speaker 1: may talk about, you know, learning about the moon phase 1294 01:16:13,600 --> 01:16:16,599 Speaker 1: or you know, learning about this particular plant or food plot. 1295 01:16:16,640 --> 01:16:19,840 Speaker 1: We just try to really scientifically, you know, evaluate all 1296 01:16:19,840 --> 01:16:23,719 Speaker 1: these types of topics and get that information out. Uh. 1297 01:16:23,920 --> 01:16:27,360 Speaker 1: Something we did recently we're excited about. We we wrote 1298 01:16:27,360 --> 01:16:30,240 Speaker 1: a book on a topic that is near and dear 1299 01:16:30,360 --> 01:16:34,280 Speaker 1: to our hearts, Steve de Marison and myself, UM about 1300 01:16:34,320 --> 01:16:38,040 Speaker 1: bucket management. And the name of the book is Strategic 1301 01:16:38,120 --> 01:16:42,559 Speaker 1: Harvest System How to break through the bucket management glass ceiling. 1302 01:16:42,640 --> 01:16:46,080 Speaker 1: And so it's something and that market might have been 1303 01:16:46,160 --> 01:16:49,280 Speaker 1: something you and I talked about last time about you know, 1304 01:16:49,400 --> 01:16:51,960 Speaker 1: really how to manage the buck side of the deer 1305 01:16:52,000 --> 01:16:54,240 Speaker 1: herd to you know, to get you where you want 1306 01:16:54,280 --> 01:16:57,519 Speaker 1: to be, and that is available on Amazon if anyone 1307 01:16:57,640 --> 01:17:03,000 Speaker 1: is interested in in that. UM, I guess that is 1308 01:17:03,000 --> 01:17:06,559 Speaker 1: it for now. The the our our website is MSU 1309 01:17:06,680 --> 01:17:09,120 Speaker 1: deer lab dot com. If someone was interested in that 1310 01:17:09,200 --> 01:17:12,519 Speaker 1: hunting app that we talked about for measuring fund recruitment, 1311 01:17:12,560 --> 01:17:14,639 Speaker 1: we've got a page there with all of our apps 1312 01:17:14,680 --> 01:17:19,080 Speaker 1: that they can download and that are free to use. Awesome. Well, 1313 01:17:19,280 --> 01:17:22,000 Speaker 1: you guys are just putting out so many helpful resources. 1314 01:17:22,520 --> 01:17:26,080 Speaker 1: I highly recommend the Deer University podcast. I've really enjoyed it. 1315 01:17:26,080 --> 01:17:28,120 Speaker 1: You guys are doing a great job. I haven't got 1316 01:17:28,160 --> 01:17:29,680 Speaker 1: to check out the book yet, but I need to 1317 01:17:29,800 --> 01:17:32,120 Speaker 1: because I'm sure that's gonna be just jam packed with 1318 01:17:32,160 --> 01:17:35,000 Speaker 1: helpful information. So Bronson, thanks for the work you guys 1319 01:17:35,040 --> 01:17:37,400 Speaker 1: are doing. And uh thanks for sharing it with us 1320 01:17:37,400 --> 01:17:41,000 Speaker 1: here on the podcast. Anytime, glad to help anyway I can. 1321 01:17:42,920 --> 01:17:46,040 Speaker 1: All right, and that is the end of part one. Now, 1322 01:17:46,080 --> 01:17:49,240 Speaker 1: before we move on to part two, we need to 1323 01:17:49,240 --> 01:17:51,639 Speaker 1: take a quick break to thank our partners at White 1324 01:17:51,640 --> 01:17:55,280 Speaker 1: Tail Properties who helped make this podcast possible. In white 1325 01:17:55,320 --> 01:17:59,639 Speaker 1: Tail Properties somewhat recently has started really cool YouTube video 1326 01:17:59,680 --> 01:18:04,360 Speaker 1: seere is called the land Beat, and on this series 1327 01:18:04,400 --> 01:18:06,960 Speaker 1: they've got a whole bunch of different topics covered related 1328 01:18:07,000 --> 01:18:10,639 Speaker 1: to managing your property for white tails and wildlife, sharing 1329 01:18:10,680 --> 01:18:14,599 Speaker 1: some really great information. The most recent video is titled 1330 01:18:14,680 --> 01:18:17,519 Speaker 1: Planting Fruit Trees, in which they talked through a bunch 1331 01:18:17,520 --> 01:18:20,759 Speaker 1: of ideas about planting and establishing fruit trees for wildlife 1332 01:18:20,800 --> 01:18:23,040 Speaker 1: on your property. They talked through the tools that you need, 1333 01:18:23,520 --> 01:18:27,240 Speaker 1: different tips to ensure that those trees survive. Um very 1334 01:18:27,240 --> 01:18:30,240 Speaker 1: interesting stuff, so I'd highly recommend heading over to the 1335 01:18:30,280 --> 01:18:34,360 Speaker 1: white Tail Properties YouTube channel, subscribe there and check out 1336 01:18:34,400 --> 01:18:37,519 Speaker 1: that Planting Fruit Trees video and look for many more 1337 01:18:37,520 --> 01:18:39,800 Speaker 1: of these to come. I hear there's gonna be a 1338 01:18:39,800 --> 01:18:42,160 Speaker 1: bunch more coming in the near future, so check them 1339 01:18:42,160 --> 01:18:44,800 Speaker 1: out and you can also learn more at white tail 1340 01:18:44,920 --> 01:18:49,320 Speaker 1: properties dot com. Now back to the show. As I mentioned, 1341 01:18:49,400 --> 01:18:52,920 Speaker 1: our next guest is Carter Niemeyer. He's going to give 1342 01:18:53,000 --> 01:18:57,120 Speaker 1: us a wolf perspective when it comes to predators and 1343 01:18:57,200 --> 01:19:00,720 Speaker 1: hunter human dynamics. Like I mentioned, Ler, he's got an 1344 01:19:00,720 --> 01:19:04,160 Speaker 1: interesting and unique perspective and I think we can all 1345 01:19:04,240 --> 01:19:06,599 Speaker 1: learn a little bit from from that as well. So 1346 01:19:06,840 --> 01:19:10,400 Speaker 1: here we go. Hope you enjoy all right, So with 1347 01:19:10,439 --> 01:19:12,439 Speaker 1: me now, and I'm really excited about this. Is Carter 1348 01:19:12,560 --> 01:19:15,479 Speaker 1: knee Meyer. That's the right way. Your last name right, 1349 01:19:15,560 --> 01:19:19,439 Speaker 1: knie Meyer. That is correct? Perfect, And Carter. I read 1350 01:19:19,439 --> 01:19:23,320 Speaker 1: your book Wolfer a few years ago because I've always 1351 01:19:23,320 --> 01:19:28,400 Speaker 1: been interested fascinated by wolves in general, being an outdoorsman 1352 01:19:29,080 --> 01:19:31,360 Speaker 1: person who just loves wildlife and wild places. They've always 1353 01:19:31,400 --> 01:19:34,680 Speaker 1: been one of those animals that is just intriguing. They 1354 01:19:34,840 --> 01:19:38,400 Speaker 1: to their detriment, maybe they symbolize a lot um and 1355 01:19:38,439 --> 01:19:41,160 Speaker 1: so that was always interesting growing up. But then also 1356 01:19:41,200 --> 01:19:44,519 Speaker 1: as a hunter within my world and in this community, 1357 01:19:44,720 --> 01:19:48,400 Speaker 1: there's obviously a whole lot of negative energy around them too. 1358 01:19:48,479 --> 01:19:51,240 Speaker 1: So I've always been just interested in that dynamic and 1359 01:19:51,280 --> 01:19:55,160 Speaker 1: why there is this these strong polarizing emotions around this 1360 01:19:55,240 --> 01:19:59,800 Speaker 1: animal from different different communities. Um In your book and 1361 01:20:00,000 --> 01:20:03,519 Speaker 1: your perspective for me was still refreshing because it seemed 1362 01:20:03,560 --> 01:20:05,880 Speaker 1: like you could approach this topic with a level of 1363 01:20:06,120 --> 01:20:11,639 Speaker 1: objectivity and logic that um I could. I could take 1364 01:20:11,680 --> 01:20:13,680 Speaker 1: in what you had to say and know that it's 1365 01:20:13,680 --> 01:20:15,760 Speaker 1: seeing there's no bs there because you've seen it from 1366 01:20:15,800 --> 01:20:18,120 Speaker 1: all sides. You approached it from a from a set 1367 01:20:18,160 --> 01:20:20,200 Speaker 1: of experiences that I think is pretty unique compared to 1368 01:20:20,240 --> 01:20:23,320 Speaker 1: most people that like to throw their hat in the 1369 01:20:23,400 --> 01:20:26,240 Speaker 1: ring when it comes to the wolf debate. Um, so 1370 01:20:26,320 --> 01:20:28,400 Speaker 1: I guess number one, thank you for taking the time 1371 01:20:28,400 --> 01:20:31,920 Speaker 1: to talk. And number two, rather than me try to 1372 01:20:32,240 --> 01:20:35,920 Speaker 1: butcher your history, I'd just love to hear it from you. 1373 01:20:36,560 --> 01:20:38,920 Speaker 1: How did you get to this point? Um? Can you 1374 01:20:38,920 --> 01:20:40,959 Speaker 1: give me a little bit background how you got involved 1375 01:20:41,000 --> 01:20:45,760 Speaker 1: with predators and then eventually into this whole wolf thing. Well, 1376 01:20:45,800 --> 01:20:48,080 Speaker 1: it's been a long story, it's turning out to be 1377 01:20:48,080 --> 01:20:51,000 Speaker 1: because I'm seventy one years old now, so we go 1378 01:20:51,160 --> 01:20:55,479 Speaker 1: way back. But I got my first gun when I 1379 01:20:55,520 --> 01:20:58,840 Speaker 1: was nine, and Uh, I started trapping foxes when I 1380 01:20:58,880 --> 01:21:02,240 Speaker 1: was a teenager. And UH grew up in northern Iowa 1381 01:21:03,120 --> 01:21:06,040 Speaker 1: in a rural setting, rural community, and we had a 1382 01:21:06,040 --> 01:21:12,280 Speaker 1: little farm ourselves. So that early hunting, trapping, fishing experience 1383 01:21:12,800 --> 01:21:17,200 Speaker 1: really made me an outdoorsman. And UH some points, I 1384 01:21:17,240 --> 01:21:18,720 Speaker 1: think when I got a car, it was not to 1385 01:21:18,840 --> 01:21:22,519 Speaker 1: date girls, it was to go hunting and trapping. So 1386 01:21:22,800 --> 01:21:25,720 Speaker 1: it perked my interest enough that when I got out 1387 01:21:25,760 --> 01:21:29,400 Speaker 1: of high school, I went to college, got a bachelor 1388 01:21:29,560 --> 01:21:35,400 Speaker 1: master's degree at Iowa State University in wildlife biology, and 1389 01:21:36,160 --> 01:21:40,360 Speaker 1: my first job, unexpected to me, was offered to me 1390 01:21:40,560 --> 01:21:46,960 Speaker 1: out in northeast Montana, a little town called Plentywood. Um. 1391 01:21:47,000 --> 01:21:49,479 Speaker 1: I was offered the job on a Thursday. I accepted 1392 01:21:49,520 --> 01:21:51,679 Speaker 1: it on a Friday, and a hopton am track train 1393 01:21:51,760 --> 01:21:55,639 Speaker 1: on a Saturday and landed in Wolf Point, interesting name, 1394 01:21:56,160 --> 01:22:03,240 Speaker 1: Montana and was ready to go to work that next Monday. Um. 1395 01:22:03,439 --> 01:22:07,639 Speaker 1: That job was raby's suppression. It was catching skunks trying 1396 01:22:07,680 --> 01:22:10,320 Speaker 1: to suppress a raby's outbreak there because that's what I 1397 01:22:10,360 --> 01:22:13,920 Speaker 1: did my master's study on. It was serology study of rabies. 1398 01:22:14,840 --> 01:22:17,360 Speaker 1: And then that job fizzled out. So I was a 1399 01:22:17,360 --> 01:22:20,080 Speaker 1: fur trapper that winter up plenty Wood and I trapped 1400 01:22:21,200 --> 01:22:24,960 Speaker 1: close to four hundred fox and coyotes. Prices were good then, 1401 01:22:25,040 --> 01:22:30,920 Speaker 1: and I did that to survive, and uh, my reputation 1402 01:22:31,040 --> 01:22:35,960 Speaker 1: began to grow and the agency called Wildlife Services. Um, 1403 01:22:36,040 --> 01:22:38,759 Speaker 1: I thought this guy likes to trap, We need a trapper. 1404 01:22:38,880 --> 01:22:44,080 Speaker 1: So my first job was to actually be well, yes, 1405 01:22:44,120 --> 01:22:46,680 Speaker 1: I'm gonna skip one part of my career and go 1406 01:22:46,800 --> 01:22:50,599 Speaker 1: straight to Dylan, Montana. And my job was catch golden 1407 01:22:50,600 --> 01:22:55,240 Speaker 1: eagles that were praying on livestock down there. Um. So, 1408 01:22:55,280 --> 01:23:00,000 Speaker 1: in one springtime period from March to the first of June, 1409 01:23:01,120 --> 01:23:05,320 Speaker 1: I and another fellow trapped on forty nine golden eagles 1410 01:23:05,760 --> 01:23:11,799 Speaker 1: out of a township size area that were killing newborn lambs. 1411 01:23:13,439 --> 01:23:16,680 Speaker 1: All those eagles were banded, put in boxes, and we 1412 01:23:16,760 --> 01:23:21,800 Speaker 1: shipped them to Colorado, Northwest Montana and someone to Yellowstone. 1413 01:23:22,600 --> 01:23:25,839 Speaker 1: We tried to break up that migration, dispersed those birds, 1414 01:23:25,880 --> 01:23:31,200 Speaker 1: and it didn't solve the problem, but it effectively diminished 1415 01:23:31,200 --> 01:23:34,840 Speaker 1: the problem. How do you catch a golden eagle? Ah, 1416 01:23:34,840 --> 01:23:40,519 Speaker 1: that's an excellent question. Um. We used coyote traps, the 1417 01:23:40,560 --> 01:23:44,320 Speaker 1: regular foothold traps. They were weakened traps, older traps, and 1418 01:23:44,360 --> 01:23:48,360 Speaker 1: we wrapped them with sponge rubber weather stripping so that 1419 01:23:48,479 --> 01:23:52,719 Speaker 1: they were basically rubber eyes jaws. And then we found 1420 01:23:52,760 --> 01:23:56,040 Speaker 1: newborn lambs that the eagles were feeding on. And we 1421 01:23:56,160 --> 01:24:01,360 Speaker 1: also killed whitetail jack rabbits and stake them to the 1422 01:24:01,400 --> 01:24:05,840 Speaker 1: ground and conceal these traps around these dead rabbits and 1423 01:24:05,960 --> 01:24:09,640 Speaker 1: the dead lambs out in the fields, and the eagles 1424 01:24:09,720 --> 01:24:15,080 Speaker 1: would fly down to scavenge, thinking that I'm eating something 1425 01:24:15,160 --> 01:24:18,080 Speaker 1: another eagle killed and they would step in that trap, 1426 01:24:18,320 --> 01:24:22,040 Speaker 1: usually with a toe, and then they would just lay 1427 01:24:22,040 --> 01:24:24,400 Speaker 1: out on the ground with their wings fanned out. And 1428 01:24:24,479 --> 01:24:27,200 Speaker 1: we would sit on a high ridge about a mile away. 1429 01:24:27,760 --> 01:24:30,040 Speaker 1: And every time you catch an eagle, we had several 1430 01:24:30,040 --> 01:24:33,519 Speaker 1: trap sites. The birds, once they were caught would flop 1431 01:24:33,520 --> 01:24:35,479 Speaker 1: out on the ground, fan their wings out, and you 1432 01:24:35,479 --> 01:24:39,840 Speaker 1: would see this big dark circle on the ground. Uh. 1433 01:24:39,920 --> 01:24:44,760 Speaker 1: So we drive over, grabbed their feet, um put them 1434 01:24:44,800 --> 01:24:49,320 Speaker 1: in wooden boxes with a slide door, and uh we 1435 01:24:49,439 --> 01:24:56,519 Speaker 1: kept them in log cabins. Actually fed them dead livestock, rabbits, lambs, 1436 01:24:57,520 --> 01:25:00,040 Speaker 1: and every time we had about fifteen in captivity and 1437 01:25:00,200 --> 01:25:03,439 Speaker 1: they would go out on a shipment to Colorado or 1438 01:25:03,479 --> 01:25:07,760 Speaker 1: some direction. And we just kept doing that until June 1439 01:25:07,880 --> 01:25:10,799 Speaker 1: come and then the migration of eagles pretty much stopped. 1440 01:25:11,680 --> 01:25:15,160 Speaker 1: At the time, the government was being pressured to give 1441 01:25:15,240 --> 01:25:18,120 Speaker 1: kill permitst or answers to shoot all these eagles, but 1442 01:25:18,720 --> 01:25:24,799 Speaker 1: that didn't happen, so we we trappers were the alternative answer. 1443 01:25:25,400 --> 01:25:28,519 Speaker 1: Can you describe what it is that Wildlife Services did 1444 01:25:29,040 --> 01:25:30,680 Speaker 1: or does now? Because I don't think a lot of 1445 01:25:30,680 --> 01:25:35,960 Speaker 1: people understand that. Yes, UM, Wildlife Services back when they 1446 01:25:36,040 --> 01:25:39,439 Speaker 1: hired me in nineteen seventy five were called a d 1447 01:25:39,560 --> 01:25:43,799 Speaker 1: C or Animal Damage Control, so they went by that title, 1448 01:25:43,880 --> 01:25:47,080 Speaker 1: and then there was a name change. At that time, 1449 01:25:47,120 --> 01:25:50,599 Speaker 1: Animal Damage Control was within the US Fish and Wildlife 1450 01:25:50,600 --> 01:25:54,800 Speaker 1: Service Department of Interior. Subsequently it moved into the U 1451 01:25:54,880 --> 01:25:57,759 Speaker 1: s Department of Agriculture, and then the name was changed 1452 01:25:57,760 --> 01:26:05,800 Speaker 1: to Wildlife Services. Today, and it sounds somewhat sarcastic, but 1453 01:26:06,360 --> 01:26:09,720 Speaker 1: Wildlife Services are basically the hired gun of the livestock 1454 01:26:09,760 --> 01:26:13,880 Speaker 1: industry because most of our work, especially at that time, 1455 01:26:14,000 --> 01:26:20,840 Speaker 1: was responding to reports of livestock being killed by mostly coyotes, 1456 01:26:21,360 --> 01:26:26,040 Speaker 1: but also eagles, black bears, grizzly bears, wolves, not so 1457 01:26:26,120 --> 01:26:31,960 Speaker 1: much wolves, then mountain lions, and our agency would respond. 1458 01:26:32,040 --> 01:26:35,479 Speaker 1: There was about a dozen trappers in the western part 1459 01:26:35,520 --> 01:26:38,320 Speaker 1: of Montana about a dozen in the eastern portion of Montana. 1460 01:26:39,560 --> 01:26:43,799 Speaker 1: UH those trappers would assess the damage, determined what predator 1461 01:26:43,880 --> 01:26:47,120 Speaker 1: was involved, and then we would remove the problem animal. 1462 01:26:47,200 --> 01:26:52,840 Speaker 1: And with the exception of grizzly bears, those and golden eagles, 1463 01:26:52,840 --> 01:26:57,719 Speaker 1: of course, the predators were killed and UM Wildlife Services 1464 01:26:57,760 --> 01:27:01,880 Speaker 1: still exist today and it varies from state to state 1465 01:27:02,040 --> 01:27:07,280 Speaker 1: what they do. UM some of these Western states like Montana, Wyoming, 1466 01:27:07,400 --> 01:27:15,120 Speaker 1: Idaho are heavy into killing coyotes and removing problem bears 1467 01:27:15,200 --> 01:27:19,800 Speaker 1: lands wolves. You get into states like Washington, Oregon, it 1468 01:27:19,840 --> 01:27:23,200 Speaker 1: could be pigeon control, you know, feral pigeons on buildings 1469 01:27:23,280 --> 01:27:27,479 Speaker 1: or under bridges. It could be protecting salmon smalt from 1470 01:27:28,000 --> 01:27:36,800 Speaker 1: different kinds of bird predators. UM A big project of 1471 01:27:36,840 --> 01:27:44,240 Speaker 1: Wildlife Services nowadays two is helping out airports national international 1472 01:27:44,400 --> 01:27:48,920 Speaker 1: size airports to reduce bird strikes where birds get in 1473 01:27:48,960 --> 01:27:53,280 Speaker 1: front of jet aircraft could kill everybody on board. That's 1474 01:27:53,280 --> 01:27:58,720 Speaker 1: a big project. And then uh more and more. Take 1475 01:27:58,760 --> 01:28:03,599 Speaker 1: the state of Texas. They've got an estimated four million 1476 01:28:03,920 --> 01:28:09,200 Speaker 1: plus farrell hogs. So wildlife services down there have they're 1477 01:28:09,240 --> 01:28:14,160 Speaker 1: still hunting predators, native predators, but they're also trying to 1478 01:28:14,320 --> 01:28:21,600 Speaker 1: reduce the feral pig population and so they are very diversified, 1479 01:28:22,240 --> 01:28:24,360 Speaker 1: and they exist in many states from here to the 1480 01:28:24,400 --> 01:28:30,240 Speaker 1: east coast to the South. And uh, whatever is a 1481 01:28:30,360 --> 01:28:34,719 Speaker 1: unique situation or problem with nuisance animals in those states, 1482 01:28:34,880 --> 01:28:40,240 Speaker 1: wildlife services adapt their programs to those needs. So Southern 1483 01:28:40,800 --> 01:28:42,920 Speaker 1: after the Golden Eagles, then for you what was next 1484 01:28:43,000 --> 01:28:45,840 Speaker 1: where you go from there? Well, I guess I did 1485 01:28:45,840 --> 01:28:48,360 Speaker 1: such a good job they made me a district supervisor. 1486 01:28:48,439 --> 01:28:55,040 Speaker 1: So I essentially became a twenty some year old supervisor 1487 01:28:55,160 --> 01:28:58,800 Speaker 1: over a bunch of fifty year old seasoned government trappers 1488 01:29:00,120 --> 01:29:04,320 Speaker 1: and pretty much helped them lying out what they were 1489 01:29:04,320 --> 01:29:06,679 Speaker 1: going to do or what I wanted them to do. 1490 01:29:07,640 --> 01:29:11,280 Speaker 1: So um it took it. It taught me a lot 1491 01:29:11,280 --> 01:29:13,080 Speaker 1: of finesse at a very young age how to get 1492 01:29:13,120 --> 01:29:14,840 Speaker 1: a bunch of ornery old guys old enough to be 1493 01:29:14,880 --> 01:29:17,759 Speaker 1: your dad to listen to you and do what you asked. 1494 01:29:18,680 --> 01:29:22,200 Speaker 1: And so along those lines too, I got involved in 1495 01:29:22,240 --> 01:29:27,960 Speaker 1: a lot of problem grizzly bear management. And because I 1496 01:29:28,040 --> 01:29:32,640 Speaker 1: was the college boy, the college educated Iowegian, a lot 1497 01:29:32,680 --> 01:29:35,960 Speaker 1: of those OTTD guys called me um. I was kind 1498 01:29:35,960 --> 01:29:41,200 Speaker 1: of the technical guy with the dart gun and the drugs. Uh. 1499 01:29:41,280 --> 01:29:43,720 Speaker 1: Those trappers preferred not to know what a milligram a 1500 01:29:43,800 --> 01:29:48,920 Speaker 1: mill of leader or was so bringing carter down. So 1501 01:29:49,000 --> 01:29:51,679 Speaker 1: when we had a problem grizzly, we would set foot 1502 01:29:51,720 --> 01:29:54,240 Speaker 1: snares catch the grizzly, and I would be the dart 1503 01:29:54,320 --> 01:29:57,320 Speaker 1: man to knock the bear down. Uh. Never killed a 1504 01:29:57,360 --> 01:30:00,120 Speaker 1: single grizzly during my tenure. We put them all in 1505 01:30:00,200 --> 01:30:02,920 Speaker 1: a culvert trap and turned them over to the state 1506 01:30:03,840 --> 01:30:07,160 Speaker 1: who relocated them or took some up in Canada and 1507 01:30:07,160 --> 01:30:13,320 Speaker 1: relocated them. And then, uh, that was pretty much my responsibility. 1508 01:30:13,080 --> 01:30:16,240 Speaker 1: I spent a lot of time to directing State of 1509 01:30:16,320 --> 01:30:22,479 Speaker 1: Montana three helicopters devoted entirely to killing coyotes. So my 1510 01:30:22,600 --> 01:30:26,880 Speaker 1: job too is to make sure those helicopters were cycled 1511 01:30:27,000 --> 01:30:30,599 Speaker 1: around to the trappers and that everyone was prepared and 1512 01:30:30,640 --> 01:30:33,640 Speaker 1: did their homework and knew where they wanted to hunt coyotes, 1513 01:30:33,720 --> 01:30:37,400 Speaker 1: and I pulled the fuel trailer for them. At that time, 1514 01:30:37,439 --> 01:30:40,720 Speaker 1: we skinned coyotes, saved the pelts, sold them, put in 1515 01:30:40,760 --> 01:30:48,600 Speaker 1: the fuel fund, and uh and then um that That 1516 01:30:48,680 --> 01:30:52,080 Speaker 1: was pretty much my career until about mid nineteen eighties 1517 01:30:52,280 --> 01:30:56,840 Speaker 1: when suddenly gray wolves started coming across the border from 1518 01:30:56,840 --> 01:30:59,680 Speaker 1: Canada and showing up in the North Fork of the 1519 01:30:59,680 --> 01:31:03,480 Speaker 1: Flat Hit around Glacier and on the Blackfoot Indian Reservation. 1520 01:31:04,360 --> 01:31:07,840 Speaker 1: And that's where I became acquainted with gray wolves, which 1521 01:31:07,920 --> 01:31:11,440 Speaker 1: were never on my radar before that. So can you 1522 01:31:11,439 --> 01:31:13,559 Speaker 1: You've got a whole book worth of knowledge about this 1523 01:31:13,600 --> 01:31:16,760 Speaker 1: whole experience that I encourage people to read, called wolfer 1524 01:31:17,040 --> 01:31:19,240 Speaker 1: Um but can you give us the cliff notes version 1525 01:31:19,320 --> 01:31:22,559 Speaker 1: of what happened from that point when those gray wolves 1526 01:31:22,560 --> 01:31:25,759 Speaker 1: started coming down across the border to the point where 1527 01:31:26,000 --> 01:31:31,599 Speaker 1: reintroduction happened and what your involvement was through that process. Yeah. 1528 01:31:31,680 --> 01:31:35,400 Speaker 1: So the recolonization um where wolves were just crossing the 1529 01:31:35,479 --> 01:31:40,960 Speaker 1: border on their own, started around six and uh from 1530 01:31:41,000 --> 01:31:44,880 Speaker 1: that point forward, we had wolf packs pop up west 1531 01:31:44,880 --> 01:31:47,719 Speaker 1: to callis Bell, Montana, and then down the nine mile 1532 01:31:48,120 --> 01:31:53,000 Speaker 1: just outside of Missoula, and a pack showed up just 1533 01:31:53,040 --> 01:31:55,880 Speaker 1: west to Hellna, Montana. So they were coming down on 1534 01:31:55,920 --> 01:31:59,720 Speaker 1: their own. And um, my job at the time, you know, 1535 01:31:59,760 --> 01:32:02,680 Speaker 1: we no no budget, we had no experience, and we 1536 01:32:02,720 --> 01:32:06,280 Speaker 1: had no field equipment you know, traps to capture wolves. 1537 01:32:07,000 --> 01:32:10,680 Speaker 1: And during that time I inadvertently darted a wolf from 1538 01:32:10,680 --> 01:32:13,040 Speaker 1: a helicopter, which had never been done in the lower 1539 01:32:13,080 --> 01:32:16,040 Speaker 1: forty eight to my knowledge. So I became Carter the 1540 01:32:16,120 --> 01:32:20,000 Speaker 1: Darter and pretty much was the go to guy to 1541 01:32:20,080 --> 01:32:22,920 Speaker 1: do the all of that early wolf capture work, either 1542 01:32:22,960 --> 01:32:28,240 Speaker 1: with foothold traps or with the helicopter when there was 1543 01:32:28,280 --> 01:32:32,680 Speaker 1: a problem, and then even started helping the agencies you know, 1544 01:32:32,960 --> 01:32:36,040 Speaker 1: collar them just to start counting them and keep track 1545 01:32:36,120 --> 01:32:38,280 Speaker 1: of the packs. And if I can interrupt you real 1546 01:32:38,320 --> 01:32:40,960 Speaker 1: fast before you go any further, at this point in 1547 01:32:41,040 --> 01:32:44,640 Speaker 1: your in your life and your career, what we what 1548 01:32:44,720 --> 01:32:48,200 Speaker 1: did you think about wolves? Like, what was your feelings 1549 01:32:48,360 --> 01:32:52,560 Speaker 1: about wolves being back in America? Were you approaching it 1550 01:32:52,640 --> 01:32:55,200 Speaker 1: from like, crap, these guys are back, this is trouble 1551 01:32:55,280 --> 01:32:57,880 Speaker 1: or were you just interested in them? Or what do 1552 01:32:57,920 --> 01:33:02,880 Speaker 1: you think? I was fat sinated with wolves, never had 1553 01:33:02,920 --> 01:33:08,720 Speaker 1: one negative thought about a wolf. I felt privileged to 1554 01:33:09,160 --> 01:33:15,280 Speaker 1: be the guy to actually start looking at the wolf 1555 01:33:15,360 --> 01:33:18,400 Speaker 1: problem that was perceived, and to be the get go 1556 01:33:18,479 --> 01:33:22,479 Speaker 1: to guy to go out and examine livestock and see 1557 01:33:22,520 --> 01:33:26,799 Speaker 1: what what the wolves did if they did kill them. Indeed, 1558 01:33:27,320 --> 01:33:33,759 Speaker 1: so no, I've never had really a negative thought towards wolves. Ever. Um, 1559 01:33:33,800 --> 01:33:37,960 Speaker 1: I was fascinated. And then I think after that, I 1560 01:33:38,040 --> 01:33:42,840 Speaker 1: just developed a tremendous respect for the animal and admiration, 1561 01:33:44,160 --> 01:33:47,439 Speaker 1: and uh it went from there and and of course 1562 01:33:48,960 --> 01:33:53,080 Speaker 1: you have to remain objective always. And so there's a 1563 01:33:53,080 --> 01:33:57,240 Speaker 1: lot of tough times when you catch this beautiful wolf 1564 01:33:57,240 --> 01:33:59,880 Speaker 1: and look in its eyes and think what a cool 1565 01:34:00,040 --> 01:34:04,839 Speaker 1: animal and later either recover its body or someone had 1566 01:34:04,920 --> 01:34:08,839 Speaker 1: killed it, or in some cases later in my career, 1567 01:34:09,080 --> 01:34:11,160 Speaker 1: I had to go out and be the trigger man 1568 01:34:11,240 --> 01:34:15,080 Speaker 1: and kill him myself. And so you you have to 1569 01:34:15,120 --> 01:34:20,280 Speaker 1: accept that. UM. But one of the things I guess 1570 01:34:20,320 --> 01:34:23,840 Speaker 1: I learned or taught myself was to be objective and 1571 01:34:24,240 --> 01:34:28,680 Speaker 1: not to be biased and not to have predetermined um 1572 01:34:29,760 --> 01:34:34,519 Speaker 1: perceptions of what was going on. Uh. I always compare 1573 01:34:34,520 --> 01:34:37,240 Speaker 1: it to being in law enforcement. You know, the guy 1574 01:34:37,320 --> 01:34:41,559 Speaker 1: carrying the badge. You've collecked evidence. You're not to judge 1575 01:34:41,560 --> 01:34:43,840 Speaker 1: and jury. You just collect evidence and present it to 1576 01:34:43,880 --> 01:34:47,120 Speaker 1: a judge and jury. And that's what my job became. 1577 01:34:47,160 --> 01:34:49,360 Speaker 1: More and more was looking at more and more dead 1578 01:34:49,400 --> 01:34:55,639 Speaker 1: livestock because as wolves received publicity, more people started looking 1579 01:34:55,680 --> 01:34:58,799 Speaker 1: at that dead cow in the field through a different 1580 01:34:58,800 --> 01:35:03,120 Speaker 1: set of eyes, you know, in different lenses. Uh. And 1581 01:35:03,160 --> 01:35:07,679 Speaker 1: so I started really learning a lot about forensics because 1582 01:35:07,720 --> 01:35:12,400 Speaker 1: I skinned out these animals and would look for injuries 1583 01:35:13,400 --> 01:35:20,520 Speaker 1: that were caused by predation versus injuries caused by accidents. 1584 01:35:20,640 --> 01:35:24,960 Speaker 1: And then you're also looking for lightning strikes, birthing problems. 1585 01:35:25,800 --> 01:35:30,320 Speaker 1: Um said before the National statistics, you know about five 1586 01:35:30,360 --> 01:35:36,240 Speaker 1: percent of livestock die from predation causes, so of them 1587 01:35:36,240 --> 01:35:39,840 Speaker 1: are dying from all kinds of possibilities. So how do 1588 01:35:39,920 --> 01:35:43,200 Speaker 1: you know that that an animal was killed by wolf? 1589 01:35:43,240 --> 01:35:45,120 Speaker 1: What are those telltale signs that you look for to 1590 01:35:45,160 --> 01:35:48,960 Speaker 1: determine whether or not this was actually a wolf. Well, 1591 01:35:49,000 --> 01:35:51,960 Speaker 1: the key is you need to have someone find that 1592 01:35:52,120 --> 01:35:55,880 Speaker 1: carcass as soon as possible. But we're looking for trauma, 1593 01:35:56,160 --> 01:36:00,920 Speaker 1: and trauma UH is usually revealed with em reach. A 1594 01:36:00,960 --> 01:36:04,519 Speaker 1: lot of profuse bleeding means the animal was alive, there 1595 01:36:04,560 --> 01:36:08,040 Speaker 1: was blood pressure at the time, and there's something happened 1596 01:36:08,040 --> 01:36:13,640 Speaker 1: to this animal. But again, UH, predation can resemble gunshot 1597 01:36:13,680 --> 01:36:17,160 Speaker 1: wounds just so people can imagine what it looks like. 1598 01:36:18,040 --> 01:36:22,080 Speaker 1: So it remains it's important to remove the skin from 1599 01:36:22,080 --> 01:36:26,000 Speaker 1: the animal and you know, is it a gunshot or 1600 01:36:26,200 --> 01:36:30,200 Speaker 1: are these tooth punctures? Or did this animal run into 1601 01:36:30,200 --> 01:36:33,759 Speaker 1: a fence post? Did it get impaled on an irrigation pipe. 1602 01:36:34,520 --> 01:36:40,080 Speaker 1: There's so many possibilities, but every predator has a signature. 1603 01:36:40,120 --> 01:36:44,400 Speaker 1: I call it wolves kill uniquely compared to how a 1604 01:36:44,479 --> 01:36:48,280 Speaker 1: mountain lion kills, compared to how a grizzly bear kills, 1605 01:36:49,040 --> 01:36:54,360 Speaker 1: compared to eagles using talents. So you have to become 1606 01:36:54,400 --> 01:36:59,080 Speaker 1: familiar with those signatures and look at where the injuries occur. 1607 01:36:59,600 --> 01:37:03,080 Speaker 1: Cougar is attack a lot at the neck throat area. 1608 01:37:03,840 --> 01:37:07,679 Speaker 1: UH might inflict some claw marks where they hang onto 1609 01:37:07,720 --> 01:37:12,640 Speaker 1: the victim. Bears are dorsal attack. They come over the shoulders, 1610 01:37:12,720 --> 01:37:16,960 Speaker 1: over the back, bite down on their prey. Even a 1611 01:37:17,000 --> 01:37:20,800 Speaker 1: thousand pound herford will be bitten over the shoulders and 1612 01:37:21,040 --> 01:37:23,559 Speaker 1: over the top of the neck by a grizzly bear, 1613 01:37:23,600 --> 01:37:29,439 Speaker 1: for instance. And UH wolves attack laterally and from behind. 1614 01:37:30,120 --> 01:37:33,799 Speaker 1: Wolves try to get their prey running, and then they 1615 01:37:33,840 --> 01:37:38,760 Speaker 1: attack from the side and behind and so UH. Of 1616 01:37:38,800 --> 01:37:44,599 Speaker 1: the wolf attack, injuries will be revealed under the legs, 1617 01:37:44,720 --> 01:37:47,040 Speaker 1: under the front legs, the armpit or whatever you want 1618 01:37:47,040 --> 01:37:50,799 Speaker 1: to call it, in the groin areas, around the soft 1619 01:37:50,880 --> 01:37:54,920 Speaker 1: belly and downwards, say, where the utter is. And then 1620 01:37:55,080 --> 01:37:57,559 Speaker 1: a lot of bite wounds occur along what they call 1621 01:37:57,640 --> 01:38:00,599 Speaker 1: the hamstrings, you know, from the genitals down the back 1622 01:38:00,640 --> 01:38:04,720 Speaker 1: of the hind leg. So once you do this for 1623 01:38:04,760 --> 01:38:10,120 Speaker 1: a long time, you can pretty quickly determine what you're 1624 01:38:10,160 --> 01:38:13,559 Speaker 1: working with. And then all these other causes of death 1625 01:38:14,920 --> 01:38:18,679 Speaker 1: often resulting no trauma. You've got a animal laying they're dead, 1626 01:38:18,760 --> 01:38:22,880 Speaker 1: not a mark on it. And again I'm not a veterinarian. 1627 01:38:22,920 --> 01:38:25,800 Speaker 1: By training, but when the rancher would allow me, we 1628 01:38:25,880 --> 01:38:30,160 Speaker 1: would open up that animal, we'd skin it, say there, well, 1629 01:38:30,160 --> 01:38:33,960 Speaker 1: there's no predation involved. So you go inside and they 1630 01:38:34,000 --> 01:38:41,360 Speaker 1: die of ulcers and uh issues internally pneumonia, And talk 1631 01:38:41,439 --> 01:38:44,280 Speaker 1: to any veterinarian and ask him how many bacteria and 1632 01:38:44,360 --> 01:38:48,720 Speaker 1: viruses kill livestock And you couldn't learn it in a lifetime. 1633 01:38:49,600 --> 01:38:54,439 Speaker 1: So I'm looking for hemorrhach That tells me that there's 1634 01:38:54,439 --> 01:38:57,760 Speaker 1: some trauma here which overlaps what predation would appear to be. 1635 01:38:58,840 --> 01:39:02,280 Speaker 1: So you're arding animals, You're starting to track these animals 1636 01:39:02,360 --> 01:39:06,280 Speaker 1: are coming down into Montana. You're checking on livestock predation, 1637 01:39:06,400 --> 01:39:09,479 Speaker 1: trying to understand are these wolf kills? Are they not? 1638 01:39:10,320 --> 01:39:15,400 Speaker 1: What what happens from there? Well? When when predators are 1639 01:39:15,400 --> 01:39:18,479 Speaker 1: not involved, sometimes that's a tough pill to swallow because 1640 01:39:18,760 --> 01:39:23,400 Speaker 1: a lot of people farm opinions and have all the 1641 01:39:23,439 --> 01:39:26,320 Speaker 1: answers before you get there, their minds made up. And 1642 01:39:26,360 --> 01:39:31,600 Speaker 1: when you say, I'm sorry, but predation, we can't confirm 1643 01:39:31,720 --> 01:39:35,840 Speaker 1: that happened here. And then if you killed you try 1644 01:39:35,920 --> 01:39:41,280 Speaker 1: to find an explanation for them, which included, you know, 1645 01:39:41,360 --> 01:39:43,960 Speaker 1: put the put the cow in the back of my 1646 01:39:44,000 --> 01:39:46,360 Speaker 1: government truck. I'll take it to your vet you need, 1647 01:39:46,720 --> 01:39:49,439 Speaker 1: so I refer them to their veterinarians. When I say 1648 01:39:49,439 --> 01:39:51,960 Speaker 1: it's not predation. If you really think you might have 1649 01:39:52,040 --> 01:39:55,879 Speaker 1: black leg or scours, go to go to an expert 1650 01:39:55,960 --> 01:40:00,280 Speaker 1: on that field if predation was involved. Early e on, 1651 01:40:00,479 --> 01:40:06,160 Speaker 1: we didn't kill wolves. We relocated them. So uh, summertime, 1652 01:40:06,280 --> 01:40:11,679 Speaker 1: especially using foothold traps, we catched those wolves, moved them 1653 01:40:11,720 --> 01:40:16,400 Speaker 1: to less problem area. Early on it was up in 1654 01:40:16,400 --> 01:40:20,160 Speaker 1: Glacier Park. It was politically expedient. Every wolf we got 1655 01:40:20,200 --> 01:40:22,920 Speaker 1: our hands on turned loose alive at a radio collars 1656 01:40:23,000 --> 01:40:26,760 Speaker 1: so that we could keep track of where that wolf is, 1657 01:40:26,800 --> 01:40:30,600 Speaker 1: what it did. And some of those were repeat offenders. Yeah, 1658 01:40:31,200 --> 01:40:36,400 Speaker 1: until about two thousand and two, we'd relocated a hundred 1659 01:40:36,479 --> 01:40:43,320 Speaker 1: and seventeen approximately a problem wolves h required not killing them. 1660 01:40:43,479 --> 01:40:47,320 Speaker 1: After about two thousand and two, Uh, no more relocations 1661 01:40:47,560 --> 01:40:50,360 Speaker 1: at least I had ho Wyoming Montana and we started 1662 01:40:50,840 --> 01:40:57,960 Speaker 1: killing the offenders. So where where did the idea of 1663 01:40:58,640 --> 01:41:02,080 Speaker 1: actually reintroducing wolves then to these different parts a little 1664 01:41:02,080 --> 01:41:04,479 Speaker 1: farther south? Where did that begin? What what happened? And 1665 01:41:04,520 --> 01:41:06,240 Speaker 1: how did you get pulled into that? Because the wolves 1666 01:41:06,280 --> 01:41:09,360 Speaker 1: are already coming down. Imagine, as you were saying, there 1667 01:41:09,439 --> 01:41:13,600 Speaker 1: was already some some controversy around that. Probably there are 1668 01:41:13,600 --> 01:41:16,080 Speaker 1: people upset about it, maybe some people were excited about it. 1669 01:41:16,600 --> 01:41:18,960 Speaker 1: But then there started to be this rise of interest 1670 01:41:19,000 --> 01:41:22,840 Speaker 1: in bringing them back to places like Yellowstone. Um, can 1671 01:41:22,880 --> 01:41:24,600 Speaker 1: you can you get us to that point? Catch us 1672 01:41:24,640 --> 01:41:26,120 Speaker 1: up on that, and then how you got pulled in 1673 01:41:26,200 --> 01:41:31,479 Speaker 1: all of it? Okay, Well, again, realizing that I worked 1674 01:41:31,800 --> 01:41:35,519 Speaker 1: with the U. S Department of Agriculture Wildlife Services at 1675 01:41:35,520 --> 01:41:41,639 Speaker 1: the time, and I was taking on these wolf responsibilities. Um, 1676 01:41:41,680 --> 01:41:44,640 Speaker 1: I was having to coordinate with the US Fish and 1677 01:41:44,640 --> 01:41:49,719 Speaker 1: Wildlife Service, who were the management authority over wolves whether 1678 01:41:49,760 --> 01:41:54,519 Speaker 1: they lived or died. So, um, it really wasn't any 1679 01:41:54,560 --> 01:41:59,240 Speaker 1: of my decision at the time two be part of 1680 01:41:59,240 --> 01:42:03,320 Speaker 1: those discussions. But back in the late sixties early seventies, 1681 01:42:03,320 --> 01:42:07,280 Speaker 1: there was talk about recovering wolves, so there was a 1682 01:42:07,320 --> 01:42:10,639 Speaker 1: lot of research done, a lot of field time where 1683 01:42:11,080 --> 01:42:14,320 Speaker 1: biologists went out and surveyed and looked for wolves in 1684 01:42:14,360 --> 01:42:20,799 Speaker 1: the lower forty eight states. Ah. And then to fast 1685 01:42:20,840 --> 01:42:28,360 Speaker 1: forward about fours when the discussions accelerated about talking about 1686 01:42:28,360 --> 01:42:31,240 Speaker 1: wolf reintroduction and I was sort of hearing about it, 1687 01:42:31,280 --> 01:42:34,440 Speaker 1: myself and I was in meetings where it was discussed. 1688 01:42:35,000 --> 01:42:37,960 Speaker 1: But they wrote an Environmental impact statement then, and I 1689 01:42:38,000 --> 01:42:40,160 Speaker 1: say they It was the US Fish and Wildlife Service. 1690 01:42:41,080 --> 01:42:43,599 Speaker 1: So at that time I was sort of swept up 1691 01:42:43,640 --> 01:42:48,559 Speaker 1: in this movement because I was a review member of 1692 01:42:48,640 --> 01:42:54,040 Speaker 1: the e i S team representing Wildlife Services who and 1693 01:42:54,120 --> 01:42:58,160 Speaker 1: we sort of represented the livestock growers, So I was 1694 01:42:58,200 --> 01:43:01,800 Speaker 1: privy to the discussions and when the c i S 1695 01:43:01,920 --> 01:43:07,799 Speaker 1: was written. At that point, there were conditions that if 1696 01:43:08,160 --> 01:43:15,240 Speaker 1: a viable wolfpack was found before the reintroduction actually occurred, 1697 01:43:15,240 --> 01:43:18,320 Speaker 1: that they weren't going to do it. But the surveys, 1698 01:43:18,400 --> 01:43:23,960 Speaker 1: the counting, the looking, the searching did not confirm any viability, 1699 01:43:24,320 --> 01:43:31,320 Speaker 1: any breeding activity in Idaho, Wyoming, Montana. Were their wolves here. Absolutely, 1700 01:43:31,360 --> 01:43:34,360 Speaker 1: there were single individuals running around. People seen them, they 1701 01:43:34,360 --> 01:43:38,200 Speaker 1: were videoed, and those wolves were from Canada because we 1702 01:43:39,000 --> 01:43:42,840 Speaker 1: exterminated wolves in these states by the nineties, So these 1703 01:43:42,880 --> 01:43:48,719 Speaker 1: weren't progeny of some pre existing population. Uh. The fact 1704 01:43:48,720 --> 01:43:56,320 Speaker 1: that no viability was recognized identified the reintroduction occurred beginning 1705 01:43:56,320 --> 01:44:03,760 Speaker 1: of UH first year. The wolves were captured at Hinton, Alberta, 1706 01:44:03,880 --> 01:44:07,160 Speaker 1: which is just east of Jasper Park. Second year. They 1707 01:44:07,200 --> 01:44:11,679 Speaker 1: came from Fort Fort St. John, British Columbia, Canada, caught 1708 01:44:11,800 --> 01:44:15,040 Speaker 1: in a region west of a little place called Pink 1709 01:44:15,080 --> 01:44:20,840 Speaker 1: Mountain on the Alaska Highway. I was part of the 1710 01:44:20,920 --> 01:44:24,800 Speaker 1: capture team in helicopters who went up to get those 1711 01:44:24,840 --> 01:44:28,840 Speaker 1: wolves again. I was working for US d A Wildlife Services, 1712 01:44:29,040 --> 01:44:31,559 Speaker 1: but the US Fish and Wildlife Service borrowed me and 1713 01:44:31,680 --> 01:44:37,280 Speaker 1: covered my uh cost and salary while I worked kind 1714 01:44:37,280 --> 01:44:40,280 Speaker 1: of as a contractor for them. So that's how I 1715 01:44:40,320 --> 01:44:44,679 Speaker 1: got involved in the actual reintroduction. So so the story 1716 01:44:44,760 --> 01:44:48,160 Speaker 1: that we hear a lot um, especially maybe in the 1717 01:44:48,240 --> 01:44:51,040 Speaker 1: hunting community where there is some animosity around the return 1718 01:44:51,080 --> 01:44:55,360 Speaker 1: of wolves. Even today, you still hear that when the 1719 01:44:55,439 --> 01:44:58,719 Speaker 1: government went and got these wolves to reintroduce, they found 1720 01:44:58,720 --> 01:45:00,880 Speaker 1: these super wolves up in handed other of these big 1721 01:45:00,920 --> 01:45:03,360 Speaker 1: monsters that weren't anything like the wolves that were down 1722 01:45:03,360 --> 01:45:06,839 Speaker 1: in America beforehand. You were literally one of the guys 1723 01:45:06,840 --> 01:45:09,840 Speaker 1: that was up there bringing these cap trapping these wolves 1724 01:45:09,840 --> 01:45:12,759 Speaker 1: and bringing them down. So can you tell me these 1725 01:45:12,800 --> 01:45:16,880 Speaker 1: weren't super wolves? Right? Well? No, and and let's back up. 1726 01:45:16,920 --> 01:45:20,120 Speaker 1: I mean, I keep hearing these testimonies about these wolves 1727 01:45:20,120 --> 01:45:22,800 Speaker 1: are different than the ones that were here. I don't 1728 01:45:22,800 --> 01:45:25,920 Speaker 1: know anyone living that saw the wolves that lived here. 1729 01:45:26,520 --> 01:45:29,280 Speaker 1: You had to be alive before ninet and you had 1730 01:45:29,280 --> 01:45:34,679 Speaker 1: to be alive up until the reintroduction from the nineteen forties. 1731 01:45:34,800 --> 01:45:36,920 Speaker 1: Weren't very many people like that. There were a few. 1732 01:45:38,040 --> 01:45:39,640 Speaker 1: There's people tell me while I have some of the 1733 01:45:39,640 --> 01:45:44,719 Speaker 1: original wolf pelts from the original wolves, Well that's fine 1734 01:45:44,720 --> 01:45:48,120 Speaker 1: and dany I'm not going to argue that. But what 1735 01:45:48,360 --> 01:45:51,240 Speaker 1: really went into the planning was that the wolves that 1736 01:45:51,280 --> 01:45:57,719 Speaker 1: were selected to be reintroduced, the only source was Canada, 1737 01:45:58,240 --> 01:46:03,920 Speaker 1: and you needed wolves recognized moose, deer, and elk as 1738 01:46:03,920 --> 01:46:06,479 Speaker 1: pray species. So you don't want to run up to 1739 01:46:06,560 --> 01:46:09,519 Speaker 1: Alaska and bring down a bunch of Cariboo hunters, you know, 1740 01:46:09,880 --> 01:46:13,400 Speaker 1: or go to Minnesota and bring a bunch of wolves 1741 01:46:13,400 --> 01:46:16,559 Speaker 1: and hunt deer, white tailed deer or whatever. So that 1742 01:46:16,640 --> 01:46:19,880 Speaker 1: the attempt was to bring down a wolf that was 1743 01:46:20,000 --> 01:46:25,200 Speaker 1: closest to this area. And as I talked about in 1744 01:46:25,240 --> 01:46:30,920 Speaker 1: a seminar today, um through radio collaring, it's obvious that 1745 01:46:31,320 --> 01:46:36,240 Speaker 1: the wolves in Canada have no barrier like a fence 1746 01:46:36,320 --> 01:46:39,439 Speaker 1: or a moat or something to keep wolves from Canada 1747 01:46:39,560 --> 01:46:43,040 Speaker 1: coming into the Lower forty eight. They always have been. 1748 01:46:43,439 --> 01:46:48,759 Speaker 1: The problem was from forty with a few exceptions along 1749 01:46:48,800 --> 01:46:51,920 Speaker 1: the border, we were killing them because there's old news 1750 01:46:52,040 --> 01:46:55,120 Speaker 1: articles people finding wolves dead in their field, usually a 1751 01:46:55,120 --> 01:46:59,000 Speaker 1: gun shot, rifle shot in the side, or perhaps somebody 1752 01:46:59,160 --> 01:47:01,320 Speaker 1: flew over him in an air plane hunting coyotes and 1753 01:47:01,320 --> 01:47:05,559 Speaker 1: shot him in the back with babies. Um. It wasn't 1754 01:47:05,680 --> 01:47:13,080 Speaker 1: till we broke that gauntlet by actually airlifting wolves into 1755 01:47:13,120 --> 01:47:16,280 Speaker 1: the lower forty eight and releasing them here did enough 1756 01:47:16,280 --> 01:47:20,880 Speaker 1: wolves get to the same vicinity to go ahead and 1757 01:47:20,960 --> 01:47:29,519 Speaker 1: breed and actually, you know, be viable and the We 1758 01:47:29,600 --> 01:47:34,240 Speaker 1: achieved our objectives over three hundred wolves for three consecutive years, 1759 01:47:34,680 --> 01:47:38,960 Speaker 1: equitably distributed over Idaho, Wyoming, Montana. We reached that goal 1760 01:47:39,040 --> 01:47:43,200 Speaker 1: by two thousand and two, that soon after the reintroduction 1761 01:47:43,200 --> 01:47:47,320 Speaker 1: in six to show you how prolific and resilient wolves are, 1762 01:47:48,640 --> 01:47:53,120 Speaker 1: so like you, Like you've said, we essentially exterminated wolves 1763 01:47:53,160 --> 01:47:56,920 Speaker 1: across America by the forties because of long spread kind 1764 01:47:56,960 --> 01:47:59,840 Speaker 1: of campaign against predators for for so long as we 1765 01:48:00,479 --> 01:48:04,639 Speaker 1: expand our own populations across the West. Um, some people 1766 01:48:04,720 --> 01:48:07,840 Speaker 1: today would say that we did that for good reason, 1767 01:48:08,040 --> 01:48:10,280 Speaker 1: that you know, they shouldn't be on the landscape, because 1768 01:48:10,280 --> 01:48:12,519 Speaker 1: of the trouble to livestock, because of the trouble to 1769 01:48:12,680 --> 01:48:15,519 Speaker 1: hunters and wildlife populations and whatnot. So some people are 1770 01:48:15,560 --> 01:48:17,000 Speaker 1: saying it was a good thing, and then you have 1771 01:48:17,040 --> 01:48:18,800 Speaker 1: other people that look at and look at that as 1772 01:48:18,800 --> 01:48:22,840 Speaker 1: a travesty taking an entire species off of a landscape, 1773 01:48:23,160 --> 01:48:26,000 Speaker 1: a place that that it belongs has been for tens 1774 01:48:26,000 --> 01:48:29,479 Speaker 1: of thousands of years, millions of years maybe. UM. So 1775 01:48:30,040 --> 01:48:32,240 Speaker 1: when you got involved in this, obviously there was a 1776 01:48:32,320 --> 01:48:35,720 Speaker 1: lot of noise on either side of that spectrum. You 1777 01:48:35,760 --> 01:48:37,960 Speaker 1: were right there in the middle of it. Actually, hands on. 1778 01:48:38,400 --> 01:48:40,439 Speaker 1: What were your feelings at that point about the idea 1779 01:48:40,439 --> 01:48:43,080 Speaker 1: of reintroducing them. Did you feel like did you have 1780 01:48:43,080 --> 01:48:46,920 Speaker 1: a strong opinion? Um, at the time all of this 1781 01:48:47,360 --> 01:48:50,800 Speaker 1: reintroduction being discussed, UM, I don't know if I had 1782 01:48:50,840 --> 01:48:55,479 Speaker 1: an opinion, but I thought it was a cool idea, 1783 01:48:56,400 --> 01:49:00,639 Speaker 1: and gray wolves are native to this, to our lower 1784 01:49:00,680 --> 01:49:04,479 Speaker 1: forty eight states, and I thought, what a cool idea 1785 01:49:04,600 --> 01:49:07,320 Speaker 1: to bring back a native species and put it here. 1786 01:49:08,520 --> 01:49:12,320 Speaker 1: And uh, I guess, being real honest, was when I 1787 01:49:12,360 --> 01:49:17,240 Speaker 1: heard this team was farming, I wanted to be on it. Uh. 1788 01:49:17,320 --> 01:49:22,360 Speaker 1: It was, it was historical, it never been done, may 1789 01:49:22,400 --> 01:49:26,320 Speaker 1: never ever be done again. But UM, I have no 1790 01:49:26,439 --> 01:49:30,439 Speaker 1: remorse or whatever you want to call it about being 1791 01:49:30,479 --> 01:49:33,640 Speaker 1: part of it. I think it was a decision the 1792 01:49:33,720 --> 01:49:37,439 Speaker 1: country made at the time. Um I don't know exactly, 1793 01:49:37,439 --> 01:49:43,360 Speaker 1: but I think comments and letters and assemble all these 1794 01:49:43,479 --> 01:49:46,080 Speaker 1: comments came in on the environmental impact statement. I think 1795 01:49:46,120 --> 01:49:49,680 Speaker 1: we're talking around a quarter of a million comments, and 1796 01:49:50,360 --> 01:49:56,840 Speaker 1: the decision was made. Certainly wasn't my decision, but the sun, moon, 1797 01:49:57,000 --> 01:50:01,840 Speaker 1: stars and constellations and the politics all lined up uniquely 1798 01:50:02,000 --> 01:50:05,799 Speaker 1: at that time, during those couple of years, and it happened, 1799 01:50:06,760 --> 01:50:10,799 Speaker 1: and certainly a lot of people resentful of it happening. 1800 01:50:12,479 --> 01:50:16,400 Speaker 1: People just like wolves, but they dislike federal government as 1801 01:50:16,479 --> 01:50:20,479 Speaker 1: much or more. I've heard people say, you know, I 1802 01:50:20,479 --> 01:50:26,120 Speaker 1: don't like wolves, but I hate the government biologists that 1803 01:50:26,160 --> 01:50:32,080 Speaker 1: brought him here. You know. So there's this feeling that exists. Yeah, 1804 01:50:32,080 --> 01:50:34,439 Speaker 1: can you talk about that dynamic that was especially present 1805 01:50:34,479 --> 01:50:36,880 Speaker 1: at that point, because it seems like, like you just said, 1806 01:50:36,880 --> 01:50:40,840 Speaker 1: there was there was a lot of negativity towards the wolf, 1807 01:50:40,920 --> 01:50:42,680 Speaker 1: but then it also seemed like a lot of the 1808 01:50:42,720 --> 01:50:45,120 Speaker 1: hate was towards the fact that the government was forcing 1809 01:50:45,200 --> 01:50:49,040 Speaker 1: wolves on people. That some people that didn't want it. Um, 1810 01:50:49,160 --> 01:50:51,880 Speaker 1: can you talk about that what was going on there too? Yeah, well, 1811 01:50:51,880 --> 01:50:56,240 Speaker 1: I'll just kind of give you my viewpoint through the 1812 01:50:56,360 --> 01:51:00,080 Speaker 1: situation that existed, is that the wolves that were to 1813 01:51:00,120 --> 01:51:07,160 Speaker 1: be reintroduced needed vast open spaces, low human presence and 1814 01:51:07,280 --> 01:51:12,160 Speaker 1: low livestock numbers, and recognize available prey like deer Elkin, 1815 01:51:12,200 --> 01:51:19,320 Speaker 1: moose Um, the frank Church, and Yellowstone. We're just it 1816 01:51:19,439 --> 01:51:24,320 Speaker 1: was decided by scientists above me a different paygrade that 1817 01:51:25,400 --> 01:51:30,040 Speaker 1: those locations fit the bill. And we have to go 1818 01:51:30,080 --> 01:51:33,840 Speaker 1: back to talk about public land. Vast amounts of public 1819 01:51:33,920 --> 01:51:38,439 Speaker 1: land in the West. They don't belong two people. Just 1820 01:51:38,560 --> 01:51:41,320 Speaker 1: because you live in Idaho doesn't mean it's your public land. 1821 01:51:41,920 --> 01:51:44,320 Speaker 1: It belongs to everybody in the country. That's the way 1822 01:51:44,360 --> 01:51:49,880 Speaker 1: I've always looked at public land. Um, the public spoke 1823 01:51:51,000 --> 01:51:57,520 Speaker 1: the public. The majority, you can argue, but the percentages 1824 01:51:57,560 --> 01:52:00,760 Speaker 1: were higher to do it than to not do it. 1825 01:52:02,200 --> 01:52:07,240 Speaker 1: And I'll give ranchers and rural folks have benefit that 1826 01:52:07,400 --> 01:52:10,960 Speaker 1: they were probably outnumbered, outgunned, and out politics at the 1827 01:52:11,040 --> 01:52:15,360 Speaker 1: time because this was so new to everybody that the 1828 01:52:15,439 --> 01:52:20,320 Speaker 1: resistance you might say, wasn't organized to push back any harder. 1829 01:52:21,479 --> 01:52:25,240 Speaker 1: So the to go with the flow had happened, and 1830 01:52:26,080 --> 01:52:29,640 Speaker 1: there's a lot of resentments because in there has been 1831 01:52:29,760 --> 01:52:33,120 Speaker 1: tremendous number of lawsuits, you know, over listing and delisting, 1832 01:52:33,240 --> 01:52:36,160 Speaker 1: back and forth, the wolves been on the list and 1833 01:52:36,240 --> 01:52:40,840 Speaker 1: off the list, and as you get more groups and 1834 01:52:40,920 --> 01:52:46,759 Speaker 1: more attorneys involved and more hindsight, there's I think still 1835 01:52:46,800 --> 01:52:49,840 Speaker 1: these resentments that gosh, if we had just done it 1836 01:52:49,920 --> 01:52:52,479 Speaker 1: this way and they'd listened to us, you know, this 1837 01:52:52,479 --> 01:52:56,200 Speaker 1: wouldn't have happened. And scientists at the time, I mean 1838 01:52:56,439 --> 01:53:04,760 Speaker 1: very prominent scientists, including wolf people, were opposed to it 1839 01:53:05,320 --> 01:53:07,479 Speaker 1: because they said, Wow, it's just going to create so 1840 01:53:07,560 --> 01:53:10,840 Speaker 1: much negativity. Why don't we just wait them out, let 1841 01:53:10,880 --> 01:53:12,920 Speaker 1: them come down on their own. There's people who believe 1842 01:53:13,000 --> 01:53:15,479 Speaker 1: that would have happened. Maybe it would have, maybe it 1843 01:53:15,479 --> 01:53:19,599 Speaker 1: wouldn't have. Um I think piecemeal they would have come, 1844 01:53:19,640 --> 01:53:23,320 Speaker 1: but have been very very slow. But we were killing 1845 01:53:23,360 --> 01:53:28,160 Speaker 1: wolves back in soon as it starts showing up, we 1846 01:53:28,160 --> 01:53:32,000 Speaker 1: were already killing them. To say that if we had 1847 01:53:32,080 --> 01:53:35,679 Speaker 1: just let them come in on their own, we could 1848 01:53:35,680 --> 01:53:39,840 Speaker 1: have lived with that, it's really not true because even 1849 01:53:39,920 --> 01:53:42,679 Speaker 1: when they were under the full protection of the Endangered 1850 01:53:42,720 --> 01:53:49,280 Speaker 1: Species Act, there was paperwork permitting us to kill endangered wolves. 1851 01:53:50,200 --> 01:53:54,720 Speaker 1: So in the reintroduction, they were introduced as experimental non 1852 01:53:54,800 --> 01:53:58,960 Speaker 1: essential wolves, which meant there was a lot more flexibility 1853 01:53:59,000 --> 01:54:04,160 Speaker 1: built in, and there has been because the numbers are 1854 01:54:04,200 --> 01:54:07,519 Speaker 1: so dynamic moving along. But we've killed about a wolf 1855 01:54:07,560 --> 01:54:09,960 Speaker 1: for every cow or calf that's been killed, you know, 1856 01:54:10,080 --> 01:54:15,519 Speaker 1: domestic animals. Um so control has always been on the 1857 01:54:15,560 --> 01:54:18,000 Speaker 1: table and it's always been applied where wolves have been 1858 01:54:18,040 --> 01:54:23,519 Speaker 1: a problem. So the wolf introduction happens in like you said, 1859 01:54:23,640 --> 01:54:27,160 Speaker 1: in Yellowstone, the frank Church. Now, you know, over the 1860 01:54:27,160 --> 01:54:32,200 Speaker 1: course of the next twenty years, the wolves did wonderfully 1861 01:54:32,280 --> 01:54:36,040 Speaker 1: from their perspective. They've reproduced, they've spread out, they've dispersed 1862 01:54:36,120 --> 01:54:39,960 Speaker 1: there now you know, present in states like Washington and 1863 01:54:40,000 --> 01:54:44,480 Speaker 1: Oregon and now recently northern California. There's been some spot 1864 01:54:44,480 --> 01:54:47,120 Speaker 1: in Nevada. They're they're dispersing all over the place. It 1865 01:54:47,160 --> 01:54:50,160 Speaker 1: seemed to between doing pretty well from a biological perspective, 1866 01:54:50,200 --> 01:54:52,360 Speaker 1: from the species perspective, but then you hear all these 1867 01:54:52,400 --> 01:54:57,240 Speaker 1: stories from people, whether it be hunters or livestock producers, 1868 01:54:58,160 --> 01:55:01,040 Speaker 1: who talk about all the negative packs that these wolves 1869 01:55:01,040 --> 01:55:04,920 Speaker 1: have had. Um They talk about decimated wildlife populations, the 1870 01:55:04,920 --> 01:55:08,320 Speaker 1: elk herds destroyed in certain regions. You hear about how 1871 01:55:08,360 --> 01:55:11,240 Speaker 1: they're hammering their calves and their sheep and different things 1872 01:55:11,280 --> 01:55:13,920 Speaker 1: like this. And I'm sure those things were being talked 1873 01:55:13,920 --> 01:55:17,240 Speaker 1: about in ninety six and they're still being talked about 1874 01:55:17,240 --> 01:55:20,720 Speaker 1: in two thousand eighteen. UM. But you've been on the ground. 1875 01:55:20,800 --> 01:55:24,360 Speaker 1: You've been going to check on these scenes. You've had 1876 01:55:24,400 --> 01:55:27,320 Speaker 1: to kill some wolves, You've had to tell some livestock 1877 01:55:27,360 --> 01:55:30,120 Speaker 1: producers this wasn't a wolf. You've you've actually been there, 1878 01:55:31,640 --> 01:55:34,040 Speaker 1: You actually have seen what the impacts have or have 1879 01:55:34,160 --> 01:55:37,560 Speaker 1: not been. So what have those impacts have been in reality? 1880 01:55:37,600 --> 01:55:40,400 Speaker 1: Not the stories and the conspiracy theories, but what has 1881 01:55:40,480 --> 01:55:47,360 Speaker 1: the real impact been. Well, the I S addressed all 1882 01:55:47,440 --> 01:55:52,960 Speaker 1: of the possibilities and being issues in the e I 1883 01:55:53,240 --> 01:55:57,839 Speaker 1: S was if it happened to address human health and safety, 1884 01:55:58,240 --> 01:56:06,160 Speaker 1: pets lives, stock, big game, ungulates, things like that. Um. 1885 01:56:06,360 --> 01:56:09,080 Speaker 1: Since the reintroduction in the lower forty eight States, nobody's 1886 01:56:09,120 --> 01:56:13,200 Speaker 1: been killed by wolves. UM. There's some stories going around. 1887 01:56:13,320 --> 01:56:17,920 Speaker 1: I call them anecdotal um. They need to be documented 1888 01:56:17,960 --> 01:56:21,680 Speaker 1: better if we're to believe them. But it's been only 1889 01:56:21,720 --> 01:56:24,600 Speaker 1: two humans killed in the twenty one century. Both of 1890 01:56:24,640 --> 01:56:28,560 Speaker 1: them occurred north of the border, one in Canada, one 1891 01:56:28,600 --> 01:56:36,160 Speaker 1: in Alaska, where there's sixty wolves estimated to live. UM. 1892 01:56:36,320 --> 01:56:40,440 Speaker 1: To talk about livestock loss, there has been some livestock loss. 1893 01:56:40,920 --> 01:56:45,600 Speaker 1: It's not across the board. Most ranchers have not had 1894 01:56:45,640 --> 01:56:50,800 Speaker 1: to deal with it. Certain individuals have. It's been taken serious. 1895 01:56:50,840 --> 01:56:55,000 Speaker 1: Wolves have been killed and in uh to correct the 1896 01:56:55,040 --> 01:56:59,839 Speaker 1: problems since then too. There's compensation for ranchers to offset 1897 01:57:00,040 --> 01:57:06,400 Speaker 1: some of the costs. AH, but progressive ranchers are taking 1898 01:57:06,400 --> 01:57:10,520 Speaker 1: it seriously and watching their livestock closer. And I think 1899 01:57:10,560 --> 01:57:14,480 Speaker 1: it's essential that people recognize that wolves aren't going to 1900 01:57:14,520 --> 01:57:18,120 Speaker 1: go away, that they can be a threat to livestock. 1901 01:57:19,200 --> 01:57:23,360 Speaker 1: Then you get into this two pronged discussion over private 1902 01:57:23,480 --> 01:57:28,280 Speaker 1: land versus public land. Um, if people I don't mean 1903 01:57:28,320 --> 01:57:30,920 Speaker 1: it in a negative way, but if if private landowners 1904 01:57:30,960 --> 01:57:34,040 Speaker 1: want to come in with napalm and kill every predator 1905 01:57:34,120 --> 01:57:37,600 Speaker 1: on their place, be my guest. I'm not going to 1906 01:57:37,760 --> 01:57:42,960 Speaker 1: fight that individual rights issue on your private property. But 1907 01:57:43,080 --> 01:57:46,160 Speaker 1: I think to be killing native predators, of which wolves 1908 01:57:46,160 --> 01:57:49,760 Speaker 1: are native, on public lands, we got to look at 1909 01:57:49,800 --> 01:57:54,880 Speaker 1: that a lot closer, and that it's just not that simple. UM. 1910 01:57:55,000 --> 01:58:00,800 Speaker 1: Their impact on big game animals like elk. I would 1911 01:58:01,760 --> 01:58:05,040 Speaker 1: have to contradict anyone who said that wolves are having 1912 01:58:05,040 --> 01:58:09,400 Speaker 1: a negative impact on elk overall. Now we can pick 1913 01:58:09,680 --> 01:58:14,640 Speaker 1: certain zones and certain districts in certain parts, UH, say, Idaho, 1914 01:58:15,480 --> 01:58:21,000 Speaker 1: there's some places where it's a habitat problem, always has been. Uh. 1915 01:58:21,160 --> 01:58:25,040 Speaker 1: Northern Idaho had a catastrophic fire back in n that 1916 01:58:25,120 --> 01:58:29,280 Speaker 1: created some spectacular elk habitat, and there were some years 1917 01:58:29,320 --> 01:58:31,680 Speaker 1: that elk hunting was fabulous. I am told it was 1918 01:58:31,760 --> 01:58:36,120 Speaker 1: before my time. Since then, those catastrophic fire areas have 1919 01:58:36,200 --> 01:58:39,840 Speaker 1: grown back and they're not as productive as they used 1920 01:58:39,840 --> 01:58:44,800 Speaker 1: to be. UM. There's other parts of Idaho and pretty 1921 01:58:44,880 --> 01:58:47,600 Speaker 1: much the states of Wyoming and Montana who are seeing 1922 01:58:48,120 --> 01:58:55,760 Speaker 1: tremendous elk herds over management objectives. UM. Montana has too 1923 01:58:55,800 --> 01:58:59,360 Speaker 1: many elk. It's been out there in the newspaper more 1924 01:58:59,360 --> 01:59:03,000 Speaker 1: than once. Hunter excess is the problem. More so in anything, 1925 01:59:03,040 --> 01:59:06,840 Speaker 1: it's not wolves killing elk. It's that the herd of 1926 01:59:06,880 --> 01:59:11,480 Speaker 1: elk have doubled in over twenty years, but the hunters 1927 01:59:11,480 --> 01:59:13,360 Speaker 1: can't get at them because much of the land is 1928 01:59:13,400 --> 01:59:19,400 Speaker 1: being sold in different ownership and all that. So in 1929 01:59:19,480 --> 01:59:28,320 Speaker 1: Idaho I believe set a new white tailed dear harvest record. Uh. 1930 01:59:28,320 --> 01:59:32,400 Speaker 1: And Idaho, Montana, Wyoming all have been having record or 1931 01:59:32,480 --> 01:59:38,560 Speaker 1: near record elk harvests, especially peaking in like round, which 1932 01:59:38,600 --> 01:59:43,720 Speaker 1: tells me two thousand wolves or more on the landscape. 1933 01:59:44,400 --> 01:59:49,480 Speaker 1: We've got good elk herds and good deer herds and 1934 01:59:49,640 --> 01:59:54,080 Speaker 1: hundred success Uh. Some states like Idaho, you know, maybe 1935 01:59:54,240 --> 01:59:57,360 Speaker 1: one out of four hundred successful. In Wyoming it's one 1936 01:59:57,400 --> 02:00:00,680 Speaker 1: out of two hundred successful. So you can't convinced me 1937 02:00:00,880 --> 02:00:03,760 Speaker 1: right now. And I think anybody who's a hunter and 1938 02:00:03,840 --> 02:00:08,480 Speaker 1: it's being honest, uh, we'll have to admit that times 1939 02:00:08,480 --> 02:00:10,640 Speaker 1: are pretty darn good. If you liked that big game 1940 02:00:11,360 --> 02:00:13,160 Speaker 1: and it seems like and tell me if this is true. 1941 02:00:13,160 --> 02:00:16,840 Speaker 1: But I've heard, you know, right after the reintroduction in 1942 02:00:16,880 --> 02:00:19,040 Speaker 1: those areas specifically where wolves have been gone for a 1943 02:00:19,040 --> 02:00:22,440 Speaker 1: long time and now they're back, that at first these 1944 02:00:22,480 --> 02:00:25,600 Speaker 1: prey populations they didn't know that that was a danger yet, 1945 02:00:25,680 --> 02:00:28,520 Speaker 1: so it was easy pickings for the wolves. And so 1946 02:00:28,560 --> 02:00:31,640 Speaker 1: you did see some maybe drastic reductions in those populations 1947 02:00:31,640 --> 02:00:35,480 Speaker 1: outside of Yellowstone and some of those regions, but relatively quickly, 1948 02:00:35,880 --> 02:00:39,800 Speaker 1: I imagine those elk herds started realizing when you see 1949 02:00:39,800 --> 02:00:43,400 Speaker 1: a furry legged, ninety pound dog runna towards you, you 1950 02:00:43,400 --> 02:00:45,560 Speaker 1: go had the other direction real quick. And they started 1951 02:00:45,640 --> 02:00:48,200 Speaker 1: changing where they you know, where they fed, where they betted. 1952 02:00:48,240 --> 02:00:51,280 Speaker 1: They started becoming like elk again, what real elk had 1953 02:00:51,320 --> 02:00:53,800 Speaker 1: been like for thousands and thousands of years beforehand. And 1954 02:00:53,840 --> 02:00:55,760 Speaker 1: now you're seeing a lot of these places you're hearing 1955 02:00:55,800 --> 02:00:59,200 Speaker 1: and seeing about these elk populations rebounding and getting you know, 1956 02:00:59,320 --> 02:01:02,160 Speaker 1: right back up there pretty high levels, maybe not pre 1957 02:01:02,800 --> 02:01:06,160 Speaker 1: wolf levels exactly in some of these regions, but very healthy. 1958 02:01:06,440 --> 02:01:09,560 Speaker 1: That's what I've been hearing, um, is that what's been 1959 02:01:09,600 --> 02:01:11,360 Speaker 1: happening in most of these places that there's been a 1960 02:01:11,440 --> 02:01:15,280 Speaker 1: kind of rebound effect. Pray, dear elka figured out, Okay, yeah, 1961 02:01:15,520 --> 02:01:18,360 Speaker 1: we can adapt to living with wolves. Yeah, and I 1962 02:01:18,360 --> 02:01:22,000 Speaker 1: think most areas of wolves and elkive adapted each other, 1963 02:01:22,080 --> 02:01:27,440 Speaker 1: you know more through a natural uh getting used to 1964 02:01:27,440 --> 02:01:33,360 Speaker 1: one another. Talk outside of Yellowstone. But what we have nowadays, 1965 02:01:33,480 --> 02:01:39,320 Speaker 1: two is that elk are thriving in many parts of Idaho, Wyoming, 1966 02:01:39,360 --> 02:01:47,400 Speaker 1: Montana because of irrigated pastures, grassland, alfalfa fields, lawns um 1967 02:01:47,520 --> 02:01:51,160 Speaker 1: there's a you know, people are trying to there's people 1968 02:01:51,200 --> 02:01:54,000 Speaker 1: who are of the opinion that all those elk are 1969 02:01:54,080 --> 02:01:56,000 Speaker 1: down in these fields because the wolves won't let them 1970 02:01:56,000 --> 02:01:58,160 Speaker 1: go back to the mountains. But a lot of these 1971 02:01:58,160 --> 02:02:00,520 Speaker 1: elkers don't want to go back very far in mountains 1972 02:02:00,560 --> 02:02:04,200 Speaker 1: because when you've got grazing and forage like they have 1973 02:02:04,360 --> 02:02:06,400 Speaker 1: down here, why would you want to go up there. 1974 02:02:07,080 --> 02:02:12,200 Speaker 1: So that that's one of the issues. UM mentioning Yellowstone 1975 02:02:12,240 --> 02:02:16,880 Speaker 1: being that beautiful laboratory to study wolves. Um. There were 1976 02:02:16,880 --> 02:02:20,400 Speaker 1: about an estimated nineteen thousand elk and Yellowstone at the 1977 02:02:20,440 --> 02:02:26,360 Speaker 1: time of the reintroduction, and that heard diminished quickly over 1978 02:02:27,040 --> 02:02:31,320 Speaker 1: these twenty years down to around you know, between four 1979 02:02:31,320 --> 02:02:35,600 Speaker 1: and five thousand elk. UM. That has been the example 1980 02:02:35,680 --> 02:02:38,520 Speaker 1: by people who are anti wolf. Basically, look what they 1981 02:02:38,520 --> 02:02:41,200 Speaker 1: did to the elk and Yellowstone. Well, you've got a 1982 02:02:41,240 --> 02:02:45,520 Speaker 1: factor in grizzly bears, caribou, you've got a factor in drought, 1983 02:02:46,560 --> 02:02:49,240 Speaker 1: you've got a factor in forage conditions in the park. 1984 02:02:49,320 --> 02:02:53,440 Speaker 1: There was a lot of things at work, including wolves. 1985 02:02:53,480 --> 02:02:57,320 Speaker 1: But for those interested, if they check with scientists in 1986 02:02:57,440 --> 02:03:02,120 Speaker 1: Yellowstone Park, this year report just come out. It's a 1987 02:03:02,120 --> 02:03:06,960 Speaker 1: good report elk from a year agos estimate and counts 1988 02:03:07,560 --> 02:03:14,600 Speaker 1: are up. They're showing an increase now we're talking over 1989 02:03:14,680 --> 02:03:18,320 Speaker 1: seven thousand elk counted. They're on the way up. And 1990 02:03:18,400 --> 02:03:21,440 Speaker 1: what are the wolves done. When the wolves were reintroduced 1991 02:03:21,440 --> 02:03:24,600 Speaker 1: in Yellowstone, their population peaked at about a hundred and 1992 02:03:24,640 --> 02:03:29,200 Speaker 1: seventy two wolves for a while. Through no hunting and 1993 02:03:29,200 --> 02:03:33,720 Speaker 1: trapping or predator control in the park, that population has 1994 02:03:34,200 --> 02:03:38,920 Speaker 1: diminished to about one wolves plus or minus now. So 1995 02:03:38,960 --> 02:03:43,760 Speaker 1: the wolf population has plateaued and come back to a 1996 02:03:43,840 --> 02:03:47,880 Speaker 1: sort of balance with the available prey and the prayer 1997 02:03:47,920 --> 02:03:52,720 Speaker 1: on the increase. And that's reflected by what's going on 1998 02:03:53,080 --> 02:03:58,360 Speaker 1: outside the park in many parts of especially Montana, Wyoming. 1999 02:03:58,400 --> 02:04:03,680 Speaker 1: But I know regions of Idaho around this Boise Country 2000 02:04:04,120 --> 02:04:09,520 Speaker 1: going east and going northa here um elk numbers are 2001 02:04:09,920 --> 02:04:15,000 Speaker 1: are doing well, I guess, maintaining and increasing. Do hunters 2002 02:04:15,040 --> 02:04:17,840 Speaker 1: need to worry? There's a lot of people in different 2003 02:04:17,840 --> 02:04:19,920 Speaker 1: parts of the country where wolves are coming into the 2004 02:04:19,920 --> 02:04:23,280 Speaker 1: country again, or there's places like in the Upper Great 2005 02:04:23,360 --> 02:04:25,960 Speaker 1: Lakes where the wolf populations are still listed and they're 2006 02:04:26,000 --> 02:04:28,760 Speaker 1: kind of expanding in places like that, And there's there's 2007 02:04:28,800 --> 02:04:31,120 Speaker 1: some like fear and I feel like lots of times 2008 02:04:31,400 --> 02:04:33,720 Speaker 1: wolves or coyotes are the easy thing to pointed finger 2009 02:04:33,760 --> 02:04:37,720 Speaker 1: at because it's it's big, it's charismatic, there's all this 2010 02:04:38,920 --> 02:04:42,800 Speaker 1: I don't know, cultural stuff, stigma around these animals, and 2011 02:04:42,840 --> 02:04:44,880 Speaker 1: so it's really easy when something's not going well for 2012 02:04:44,920 --> 02:04:47,600 Speaker 1: you as a hunter, or you're not seeing animals or 2013 02:04:47,640 --> 02:04:50,640 Speaker 1: whatever it might be, that is a really easy thing 2014 02:04:50,680 --> 02:04:52,600 Speaker 1: to a it's got to be that I saw one, 2015 02:04:52,760 --> 02:04:54,720 Speaker 1: and since I've been here and i'm we haven't seen 2016 02:04:54,760 --> 02:04:58,080 Speaker 1: the deer, elk or whatever it is. Um, Can you 2017 02:04:58,120 --> 02:05:02,720 Speaker 1: speak to you or experiences with predators and being a 2018 02:05:02,760 --> 02:05:07,080 Speaker 1: hunter yourself, Do we need to be worried about predators? 2019 02:05:07,120 --> 02:05:10,040 Speaker 1: Can we co exist as hunters with predators? How do 2020 02:05:10,080 --> 02:05:13,840 Speaker 1: we do that? How do we think about that? Well, 2021 02:05:13,880 --> 02:05:19,120 Speaker 1: my opinion and from over thirty years experience in the field, 2022 02:05:21,200 --> 02:05:28,160 Speaker 1: it's undoubtable. We can live with predators. It's here's one 2023 02:05:28,200 --> 02:05:31,040 Speaker 1: of the reactions of just like killing coyotes, you know, 2024 02:05:31,160 --> 02:05:33,600 Speaker 1: and the government got involved over a hundred years ago 2025 02:05:33,760 --> 02:05:38,200 Speaker 1: in removing coyotes because they are a problem and their 2026 02:05:38,360 --> 02:05:40,360 Speaker 1: vermin whatever you want to call him, there a nuisance, 2027 02:05:40,360 --> 02:05:45,400 Speaker 1: say kill livestock. Um, coyotes some more you persecute them, 2028 02:05:45,440 --> 02:05:48,960 Speaker 1: actually you benefit them. I mean you're you're trying to 2029 02:05:49,080 --> 02:05:53,560 Speaker 1: kill them off for whatever reason, from retaliation and vengeance 2030 02:05:53,680 --> 02:05:58,919 Speaker 1: to just being practical at their problem. Um, those coyotes 2031 02:05:58,960 --> 02:06:03,600 Speaker 1: react to that. You lower the coyote density. You actually 2032 02:06:03,600 --> 02:06:08,040 Speaker 1: make the surviving coyotes healthier because freeze up some food 2033 02:06:08,080 --> 02:06:13,600 Speaker 1: that their competitors are eating. Um, the females get good nourishment, 2034 02:06:13,720 --> 02:06:19,560 Speaker 1: so they have maybe bigger litters of pups, and because 2035 02:06:19,600 --> 02:06:24,040 Speaker 1: of the available food, the more pups survive. And on 2036 02:06:24,160 --> 02:06:28,360 Speaker 1: a scale with wolves, wolves require two hundred and fifty 2037 02:06:28,960 --> 02:06:32,760 Speaker 1: square miles for a territory, similar things happen with wolves. 2038 02:06:33,160 --> 02:06:37,760 Speaker 1: You go in and you kill them for whatever justification 2039 02:06:37,880 --> 02:06:42,160 Speaker 1: you have. Um, you can break up those wolf packs. 2040 02:06:42,240 --> 02:06:45,040 Speaker 1: You can actually cause them to disperse sooner than they 2041 02:06:45,040 --> 02:06:50,920 Speaker 1: would and you recognize recognizing again whether you're talking foxes, coyotes, wolves, 2042 02:06:51,040 --> 02:06:53,920 Speaker 1: or any species. For the most part, when you empty 2043 02:06:53,920 --> 02:06:57,840 Speaker 1: out an area, create a vacuum. Nature abhors a vacuum, 2044 02:06:57,920 --> 02:07:04,080 Speaker 1: and animals that species outside that area you just cleaned 2045 02:07:04,080 --> 02:07:09,120 Speaker 1: out start moving in. So to me, it's senseless to 2046 02:07:09,880 --> 02:07:17,960 Speaker 1: think somehow that eradicating predators is going to solve the problem. Um. 2047 02:07:18,000 --> 02:07:21,040 Speaker 1: But now if you want to hunt coyotes or wolves recreationally, 2048 02:07:22,000 --> 02:07:25,520 Speaker 1: you can justify that and it's legal. Um. That's the 2049 02:07:25,560 --> 02:07:31,440 Speaker 1: way it is. UM. That's sport, that's recreation. That's called 2050 02:07:31,440 --> 02:07:34,440 Speaker 1: trophy hunting, because I don't think many people take fox 2051 02:07:34,440 --> 02:07:40,120 Speaker 1: and coyotes home and eat them. So UM, as long 2052 02:07:40,160 --> 02:07:44,480 Speaker 1: as state management agencies see this surplus, that we have 2053 02:07:44,560 --> 02:07:50,320 Speaker 1: a viable population of wolves or coyotes or whatever, and 2054 02:07:50,400 --> 02:07:53,840 Speaker 1: they provide very liberal seasons for people to hunt and 2055 02:07:53,840 --> 02:07:56,920 Speaker 1: trap them, I guess that's the way it is, even 2056 02:07:56,920 --> 02:08:02,440 Speaker 1: though many in society don't understand or except that. What 2057 02:08:02,520 --> 02:08:07,920 Speaker 1: have you learned, um, from your experiences with livestock producers 2058 02:08:08,000 --> 02:08:10,640 Speaker 1: or hunters or other parties that have been opposed to 2059 02:08:11,040 --> 02:08:15,320 Speaker 1: predators coming back into the area? Um? Have we have 2060 02:08:15,360 --> 02:08:18,560 Speaker 1: we learned anything that we can apply to how we 2061 02:08:18,920 --> 02:08:23,520 Speaker 1: manage this in the future. So, whether it be managing 2062 02:08:23,960 --> 02:08:30,240 Speaker 1: predator populations or the balance between predator and wildlife and hunters. Well, 2063 02:08:30,240 --> 02:08:32,920 Speaker 1: I guess maybe I should rephrase it. What's your vision 2064 02:08:32,960 --> 02:08:35,240 Speaker 1: for the future. What's the best way to do this 2065 02:08:35,320 --> 02:08:39,840 Speaker 1: better in the future. Well, I guess again, if you're 2066 02:08:39,840 --> 02:08:44,760 Speaker 1: a rancher, Um, do your homework. Recognize if you got 2067 02:08:44,800 --> 02:08:47,680 Speaker 1: wolves in your backyard or wolves moving into the neighborhood, 2068 02:08:48,440 --> 02:08:52,480 Speaker 1: you're gonna have to be more vigilant. I think any businessman, 2069 02:08:52,680 --> 02:08:55,920 Speaker 1: regardless of the business you run, you have to know 2070 02:08:55,960 --> 02:09:00,880 Speaker 1: your risks. UM. And the state managed many agencies have 2071 02:09:00,960 --> 02:09:04,400 Speaker 1: been pretty liberal, as were the federal managers too that 2072 02:09:04,800 --> 02:09:08,000 Speaker 1: when wolves were determined to be a problem, they were removed. 2073 02:09:09,000 --> 02:09:11,320 Speaker 1: But I think more and more as a society, we 2074 02:09:11,520 --> 02:09:15,800 Speaker 1: are also putting the burden on on say the rancher 2075 02:09:15,880 --> 02:09:21,120 Speaker 1: for instance, that since you raise livestock and many of 2076 02:09:21,160 --> 02:09:24,440 Speaker 1: you use public lands in the west as part of 2077 02:09:24,480 --> 02:09:28,600 Speaker 1: your grazing scheme, and um, you're gonna have to be 2078 02:09:28,600 --> 02:09:31,000 Speaker 1: a little more tolerant of them. So we're right at 2079 02:09:31,040 --> 02:09:35,200 Speaker 1: a kind of a stage at this point that we've 2080 02:09:35,200 --> 02:09:41,040 Speaker 1: got to recognize wolves are socially and legally protected and managed. 2081 02:09:41,080 --> 02:09:44,560 Speaker 1: Now they're not going to go away, and and a 2082 02:09:44,680 --> 02:09:47,960 Speaker 1: smart businessman will adapt, and perhaps you're going to have 2083 02:09:48,000 --> 02:09:51,280 Speaker 1: to put a range writer or cowboy out there with 2084 02:09:51,440 --> 02:09:55,839 Speaker 1: them and be more vigilant. Uh. And on a smaller scale, 2085 02:09:55,960 --> 02:09:59,960 Speaker 1: maybe it's you know, fencing flagry ribbon. I mean They're 2086 02:10:00,080 --> 02:10:03,360 Speaker 1: a whole list of these non lethal ways, but I 2087 02:10:03,400 --> 02:10:08,040 Speaker 1: think most of all, it's keeping an eye on your livestock. UM. 2088 02:10:08,040 --> 02:10:10,720 Speaker 1: I worked some colleagues in Canada who are taken care 2089 02:10:10,760 --> 02:10:16,520 Speaker 1: of some pretty large cow calf pair units and keeping 2090 02:10:16,680 --> 02:10:21,360 Speaker 1: predation very low. But it takes work and commitment to 2091 02:10:21,400 --> 02:10:25,640 Speaker 1: do that. UM. I know a lot of people don't 2092 02:10:25,680 --> 02:10:34,920 Speaker 1: accept my suggestions there. UM. Otherwise, UM, you can hunt 2093 02:10:34,960 --> 02:10:37,360 Speaker 1: him and trap them and kill them and persecute them, 2094 02:10:37,840 --> 02:10:44,040 Speaker 1: but long as it's within the contained within the legal hunting, trapping, snaring, 2095 02:10:44,200 --> 02:10:48,480 Speaker 1: and regulated seasons. I think the wolves are when I 2096 02:10:48,520 --> 02:10:52,040 Speaker 1: talk about viability, I think they're pretty much replacing themselves 2097 02:10:52,840 --> 02:10:56,040 Speaker 1: after the killing has happened and they have puffs in 2098 02:10:56,080 --> 02:10:59,320 Speaker 1: the spring, They're pretty much replacing their numbers here from 2099 02:10:59,360 --> 02:11:01,480 Speaker 1: what I see. Yeah, I've heard a lot. There's been 2100 02:11:01,480 --> 02:11:04,080 Speaker 1: a lot of studies done more of the Eastern United 2101 02:11:04,120 --> 02:11:07,960 Speaker 1: States around coyotes and trying to manage them, and a 2102 02:11:08,040 --> 02:11:10,280 Speaker 1: lot of people trying to manage for other wildlife species 2103 02:11:10,280 --> 02:11:12,680 Speaker 1: and understanding the impact the coyotes have on faunds or 2104 02:11:12,680 --> 02:11:15,120 Speaker 1: different things like that, and a lot of times they 2105 02:11:15,120 --> 02:11:18,840 Speaker 1: find that really, unless you do a whole scale eradication 2106 02:11:18,960 --> 02:11:22,200 Speaker 1: via some kind of trapping program at a specific time, 2107 02:11:22,640 --> 02:11:24,280 Speaker 1: you know, just the occasional. You know, some of the 2108 02:11:24,320 --> 02:11:26,200 Speaker 1: guys will say I'll shoot every coyote I see when 2109 02:11:26,200 --> 02:11:29,680 Speaker 1: I'm not hunting because of the killing my fawnds or something. Um. 2110 02:11:29,720 --> 02:11:33,040 Speaker 1: But to your early earlier point, science has shown that 2111 02:11:33,080 --> 02:11:35,360 Speaker 1: doesn't really make any impact at all because they just 2112 02:11:35,400 --> 02:11:40,000 Speaker 1: come right back in their litters increase UM. In many cases, 2113 02:11:40,040 --> 02:11:45,600 Speaker 1: it seems like the smarter way to manage that situation 2114 02:11:46,000 --> 02:11:50,640 Speaker 1: is maybe to a learn to live with this coexistence 2115 02:11:50,720 --> 02:11:54,240 Speaker 1: with another productor species. And then in some areas where 2116 02:11:54,240 --> 02:11:56,040 Speaker 1: you have like private landers and so there's things you 2117 02:11:56,040 --> 02:11:58,840 Speaker 1: can do to improve habitat to help provide a better 2118 02:11:58,840 --> 02:12:01,840 Speaker 1: situation for fawns so that you know that you can 2119 02:12:01,880 --> 02:12:05,280 Speaker 1: do the the the prey dumping kind of I think 2120 02:12:05,280 --> 02:12:07,440 Speaker 1: it overload where there's so many fonds on the landscape 2121 02:12:07,440 --> 02:12:09,920 Speaker 1: at one time and there's good fawning habitat, and then 2122 02:12:09,960 --> 02:12:12,640 Speaker 1: the coyotes might not necessarily kill as many fonds. Those 2123 02:12:12,680 --> 02:12:14,640 Speaker 1: little things that you can do that to learn to 2124 02:12:14,640 --> 02:12:18,000 Speaker 1: to live with predators but still achieve whatever goals you 2125 02:12:18,040 --> 02:12:20,400 Speaker 1: might have as a hunter manager. Different things like that 2126 02:12:20,400 --> 02:12:24,040 Speaker 1: that seemed to be maybe more effective pragmatically than just 2127 02:12:24,120 --> 02:12:26,560 Speaker 1: shooting or persecuting this other animal that you think is 2128 02:12:26,640 --> 02:12:29,240 Speaker 1: competing with you for the animal you want to see 2129 02:12:29,400 --> 02:12:33,440 Speaker 1: or shoot yourself or whatever it might be. Um, when 2130 02:12:33,480 --> 02:12:37,040 Speaker 1: we went to college, you know, we're talked, we talked, 2131 02:12:37,080 --> 02:12:42,760 Speaker 1: We're taught about biological carrying capacity. And that's with the water, 2132 02:12:42,840 --> 02:12:45,800 Speaker 1: habitat food. You know, whether you're talking to ring neck 2133 02:12:45,880 --> 02:12:53,120 Speaker 1: pheasants or coyotes or wolves, there's so much space, so 2134 02:12:53,240 --> 02:12:57,320 Speaker 1: much food, so much water that they require to be 2135 02:12:57,600 --> 02:13:04,160 Speaker 1: at their maximum density. And so that's the biological carrying capacity. 2136 02:13:04,600 --> 02:13:09,080 Speaker 1: Now we've gone to social carrying capacity to manage wolves 2137 02:13:09,120 --> 02:13:14,360 Speaker 1: as an example, we're talking about human tolerance now, Um, 2138 02:13:14,480 --> 02:13:20,320 Speaker 1: absent humans here, I mean absent humans in Idaho, absent 2139 02:13:20,880 --> 02:13:23,160 Speaker 1: humans killing wolves in Idaho. There's not a doubt in 2140 02:13:23,160 --> 02:13:26,000 Speaker 1: my mind that wolves would plateau at a certain number 2141 02:13:27,600 --> 02:13:30,480 Speaker 1: in relationship to the available food base. You know, the 2142 02:13:30,520 --> 02:13:32,880 Speaker 1: deer and the elk, whether you hunted or trapped him 2143 02:13:32,920 --> 02:13:35,760 Speaker 1: or did anything, we're not gonna We're just never going 2144 02:13:35,800 --> 02:13:38,960 Speaker 1: to get there. I don't think as humans because no 2145 02:13:39,000 --> 02:13:41,760 Speaker 1: one is willing to risk it accepted in the in 2146 02:13:41,880 --> 02:13:45,560 Speaker 1: the state agencies who manage them are they look at 2147 02:13:45,960 --> 02:13:50,760 Speaker 1: we have enough wolves, we can kill this many. As 2148 02:13:50,800 --> 02:13:53,960 Speaker 1: long as we stay above this threshold, we can do this. 2149 02:13:54,280 --> 02:13:58,400 Speaker 1: And that's our culture. That's the tradition, you know, with 2150 02:13:58,560 --> 02:14:01,520 Speaker 1: hunting and harvest sting the surplus. That's we're going to 2151 02:14:01,680 --> 02:14:08,760 Speaker 1: keep doing that. But yeah, I just think that it's 2152 02:14:08,840 --> 02:14:12,080 Speaker 1: futile if you think you're controlling them. I mean, all 2153 02:14:12,120 --> 02:14:15,320 Speaker 1: you can do really is reduce them in areas and 2154 02:14:15,520 --> 02:14:20,720 Speaker 1: target problems and deal with that. But going back into 2155 02:14:20,760 --> 02:14:25,520 Speaker 1: my predator control career, there's two concepts. There's corrective control 2156 02:14:25,640 --> 02:14:30,120 Speaker 1: and preventative control. Corrective control is when you have say, 2157 02:14:30,160 --> 02:14:32,920 Speaker 1: two coyotes killing someone sheep, and you go in and 2158 02:14:32,960 --> 02:14:37,480 Speaker 1: you kill those two kyotes. You've corrected the problem, the 2159 02:14:37,520 --> 02:14:40,800 Speaker 1: problems over, you go home and no more work to 2160 02:14:40,840 --> 02:14:46,440 Speaker 1: be done. But preventative control is always going on, which is, 2161 02:14:48,240 --> 02:14:51,320 Speaker 1: if there's a coyote out there and he's alive, he 2162 02:14:51,400 --> 02:14:54,520 Speaker 1: might eat a sheep. So we used to send up 2163 02:14:54,520 --> 02:14:58,240 Speaker 1: the gun ships all winter and shoot every kyote we 2164 02:14:58,280 --> 02:15:03,080 Speaker 1: could shoot wherever we had agreements to fly. And now's 2165 02:15:03,080 --> 02:15:07,800 Speaker 1: still going on in parts of Idaho, Wyoming, Montana, and 2166 02:15:07,800 --> 02:15:12,520 Speaker 1: then throw in sport, recreational hunting and trapping of wolves. 2167 02:15:13,200 --> 02:15:20,440 Speaker 1: There is that attempt to socially adjust the carrying capacity 2168 02:15:20,600 --> 02:15:25,400 Speaker 1: downward so that wolves won't be a problem to ranchers. 2169 02:15:25,480 --> 02:15:29,800 Speaker 1: Wolves aren't going to be a problem killing an excessive 2170 02:15:29,880 --> 02:15:32,440 Speaker 1: number of big game animals that hunters want to pursue. 2171 02:15:32,600 --> 02:15:35,680 Speaker 1: So but that's but that's the way the system is 2172 02:15:35,680 --> 02:15:40,160 Speaker 1: working and has worked and probably will continue to. Although 2173 02:15:41,560 --> 02:15:48,800 Speaker 1: there's people out there trying to attack that um, attack 2174 02:15:48,880 --> 02:15:52,960 Speaker 1: that culture or that mentality and try and get everyone 2175 02:15:53,000 --> 02:15:56,000 Speaker 1: to look at wolves and coyotes and they're a social 2176 02:15:56,240 --> 02:16:01,280 Speaker 1: or a family group. You're breaking up a family and 2177 02:16:01,320 --> 02:16:05,160 Speaker 1: you're not letting that family function ecologically like they could 2178 02:16:05,600 --> 02:16:09,080 Speaker 1: if humans didn't interfere. Right, it's funny with wolves. I 2179 02:16:09,160 --> 02:16:11,320 Speaker 1: think it was either you or whoever introduced you earlier 2180 02:16:11,320 --> 02:16:14,200 Speaker 1: today during the seminar, said that wolves are often looked 2181 02:16:14,200 --> 02:16:17,920 Speaker 1: at as either a a devil or a deity or 2182 02:16:17,960 --> 02:16:20,280 Speaker 1: a center saint. I mean, it's it's one thing or 2183 02:16:20,320 --> 02:16:24,879 Speaker 1: the other people worship them as this bigger than anything 2184 02:16:24,920 --> 02:16:28,080 Speaker 1: type of thing, or it's the worst type of evil. 2185 02:16:28,600 --> 02:16:33,039 Speaker 1: These animals are are evil, killing the poor, helpless, dear. 2186 02:16:33,240 --> 02:16:36,120 Speaker 1: They do these like rage killings, or they kill a 2187 02:16:36,120 --> 02:16:38,560 Speaker 1: bunch of animals just out of lust. Um, you hear 2188 02:16:38,600 --> 02:16:41,160 Speaker 1: all these these polarized to oppositities, or on the other side, 2189 02:16:41,200 --> 02:16:44,160 Speaker 1: you hear about these loving families of animals that have 2190 02:16:44,240 --> 02:16:47,360 Speaker 1: special personalities, and we can't, you know, we can't break 2191 02:16:47,400 --> 02:16:50,080 Speaker 1: up the family and daughters and sons. And then they 2192 02:16:50,280 --> 02:16:54,120 Speaker 1: humanize these animals in these different ways. And um, I 2193 02:16:54,160 --> 02:16:55,800 Speaker 1: think there's a middle ground where you can look at 2194 02:16:55,800 --> 02:16:58,440 Speaker 1: these things as as as an animal, a really unique, 2195 02:16:58,480 --> 02:17:02,400 Speaker 1: interesting to be spected and appreciate animal, but also something 2196 02:17:02,440 --> 02:17:04,920 Speaker 1: that that's part of this larger ecosystem that we as 2197 02:17:05,000 --> 02:17:07,320 Speaker 1: humans are now a part of two and we have 2198 02:17:07,920 --> 02:17:09,840 Speaker 1: for a very very long time, we've been a part 2199 02:17:09,879 --> 02:17:14,360 Speaker 1: of that food chain. Humanity has become a giant footprint 2200 02:17:14,440 --> 02:17:20,360 Speaker 1: on the globe, and predators especially are in a world 2201 02:17:20,400 --> 02:17:22,199 Speaker 1: of hurd in a lot of places in the world. 2202 02:17:23,320 --> 02:17:29,920 Speaker 1: And so I enjoy predators. I just I'm not a 2203 02:17:29,959 --> 02:17:32,560 Speaker 1: predator killer anymore. I there was a time in my 2204 02:17:32,600 --> 02:17:35,800 Speaker 1: life when I did that, and now I would rather 2205 02:17:35,840 --> 02:17:38,160 Speaker 1: go out and locate a pack of wolves and set 2206 02:17:38,240 --> 02:17:40,240 Speaker 1: up on a ridge of the spotting scope and watch 2207 02:17:40,280 --> 02:17:44,959 Speaker 1: them and just enjoy them same way seeing a mountain 2208 02:17:45,000 --> 02:17:48,959 Speaker 1: lion run across the road or watching black bears, you know, 2209 02:17:49,120 --> 02:17:52,520 Speaker 1: grazing in the spring up on the grassy slopes. That's 2210 02:17:52,560 --> 02:17:57,240 Speaker 1: where I'm at. And there's a time when, like I say, 2211 02:17:57,360 --> 02:18:00,800 Speaker 1: they're they're legal to hunt and trap or kill predators. 2212 02:18:02,160 --> 02:18:04,080 Speaker 1: As long as it's legal and you've got a tag, 2213 02:18:04,320 --> 02:18:08,879 Speaker 1: go for it. Yeah, but it boils down to individual choices. 2214 02:18:10,200 --> 02:18:14,800 Speaker 1: We have this huge impact, and um, I just pick 2215 02:18:14,840 --> 02:18:18,560 Speaker 1: and choose. I still hunt, and I my wife and 2216 02:18:18,600 --> 02:18:22,040 Speaker 1: I eat elk meat, so that's what I hunt pretty much, 2217 02:18:22,680 --> 02:18:25,959 Speaker 1: not hunting all these other things anymore because two people 2218 02:18:26,000 --> 02:18:32,640 Speaker 1: can only eat so much. Yeah, I, as we've talked about, 2219 02:18:32,640 --> 02:18:35,800 Speaker 1: I've always been fascinated by wolves too. Um. But I 2220 02:18:35,840 --> 02:18:38,840 Speaker 1: also recognized the right to hunt them now and and 2221 02:18:39,160 --> 02:18:42,879 Speaker 1: state level management to maintain sustainable populations. I think that's 2222 02:18:42,920 --> 02:18:46,080 Speaker 1: I think that's great and and worthy, and I understand 2223 02:18:46,080 --> 02:18:47,680 Speaker 1: that the need in places to do some of the 2224 02:18:47,680 --> 02:18:49,360 Speaker 1: things that are done. But at the same time, I've 2225 02:18:49,400 --> 02:18:54,520 Speaker 1: never had this, um, I've never had the desire to 2226 02:18:55,000 --> 02:18:56,680 Speaker 1: kill a wolf. That's one of those animals that I 2227 02:18:56,680 --> 02:18:58,640 Speaker 1: think I would be more like what you just described 2228 02:18:58,680 --> 02:19:01,080 Speaker 1: there were for if I saw, I would just want 2229 02:19:01,080 --> 02:19:04,400 Speaker 1: to watch it, and nothing against someone who does want 2230 02:19:04,440 --> 02:19:06,800 Speaker 1: to hunt that animal, because I've hunted plenty of other 2231 02:19:06,840 --> 02:19:09,720 Speaker 1: animals and I've enjoyed that, and I get it. Um. 2232 02:19:09,800 --> 02:19:13,720 Speaker 1: But Eldo Leopold, you know, the great conservationist and wilderness 2233 02:19:13,760 --> 02:19:17,720 Speaker 1: advocate and game manager and philosopher of sorts. He he 2234 02:19:17,800 --> 02:19:20,240 Speaker 1: had this experience back in the twenties when he was 2235 02:19:20,280 --> 02:19:24,280 Speaker 1: down in New Mexico as a young Force Service UM 2236 02:19:24,800 --> 02:19:27,440 Speaker 1: ranger of sorts. And he at the time believed that 2237 02:19:27,640 --> 02:19:29,520 Speaker 1: the more wolves you killed, the more deer that would 2238 02:19:29,520 --> 02:19:31,440 Speaker 1: be in the landscape. So he thought, he shoot every 2239 02:19:31,480 --> 02:19:34,440 Speaker 1: wolf you see. And he has his famous essay maybe 2240 02:19:34,480 --> 02:19:37,520 Speaker 1: maybe you're familiar with it, UM called thinking like a Mountain, 2241 02:19:37,560 --> 02:19:40,600 Speaker 1: where he he shoots this wolf and he walks up 2242 02:19:40,600 --> 02:19:42,199 Speaker 1: to it, and he said he saw the green fire 2243 02:19:42,240 --> 02:19:45,360 Speaker 1: in his eyes die and he realized that all those 2244 02:19:45,840 --> 02:19:49,240 Speaker 1: preconceived notions he had, he realized that, and he had 2245 02:19:49,280 --> 02:19:52,040 Speaker 1: triggering it. Yeah, he had triggered it. And he realized 2246 02:19:52,040 --> 02:19:54,480 Speaker 1: that he'd been wrong, and something died there. And he 2247 02:19:54,600 --> 02:19:57,600 Speaker 1: realized that something that only now the mountain knew was 2248 02:19:57,760 --> 02:20:00,480 Speaker 1: was lost. Um. He had this kind of tiphany, and 2249 02:20:00,520 --> 02:20:02,480 Speaker 1: then from there he started to look at things a 2250 02:20:02,520 --> 02:20:05,800 Speaker 1: little bit differently. Um, the predators can also be part 2251 02:20:05,879 --> 02:20:09,879 Speaker 1: of this system that we are part of. Two. Um, 2252 02:20:10,080 --> 02:20:12,960 Speaker 1: you have killed wolves, you have been a part that 2253 02:20:13,000 --> 02:20:17,920 Speaker 1: You've You've walked up to a dead wolf. Um, what 2254 02:20:18,800 --> 02:20:20,760 Speaker 1: has that? What's that like? Is there something? Is that 2255 02:20:20,800 --> 02:20:23,360 Speaker 1: a powerful moment even for you having been involved with 2256 02:20:23,800 --> 02:20:30,800 Speaker 1: all these things? Yes, because I've personally, you know, my 2257 02:20:30,800 --> 02:20:38,959 Speaker 1: my capture record is I've caught myself or in since 2258 02:20:39,000 --> 02:20:43,520 Speaker 1: I'm in control of the situation or the person in charge. 2259 02:20:43,600 --> 02:20:46,320 Speaker 1: I've caught three hundred wolves and you might say had 2260 02:20:46,360 --> 02:20:50,120 Speaker 1: them on life support. We check temperature, pulse, respiration, we 2261 02:20:50,160 --> 02:20:55,760 Speaker 1: have drugs, mobilizing drugs, keeping them alive, to put a 2262 02:20:55,760 --> 02:20:58,840 Speaker 1: collar on him. Take some measurements when you do that 2263 02:20:58,879 --> 02:21:05,720 Speaker 1: with three hundred live animals as beautiful as wolves are, UM, 2264 02:21:05,879 --> 02:21:09,800 Speaker 1: I have lost any desire to kill one. So when 2265 02:21:09,800 --> 02:21:12,360 Speaker 1: I see one killed, or I see videos of them 2266 02:21:12,400 --> 02:21:16,840 Speaker 1: being shot or whatever, UM, I can imagine that it's 2267 02:21:16,840 --> 02:21:19,720 Speaker 1: a rush for somebody who hasn't been around that before, 2268 02:21:19,879 --> 02:21:22,879 Speaker 1: and that you know, a wolf is beautiful, I wanted 2269 02:21:22,920 --> 02:21:25,520 Speaker 1: for trophy or a wolf is I mean, he's got 2270 02:21:25,520 --> 02:21:28,680 Speaker 1: big fangs and uh, you know, he's a dangerous animal, 2271 02:21:28,760 --> 02:21:30,959 Speaker 1: and my buddies are going to really look up to 2272 02:21:31,000 --> 02:21:34,120 Speaker 1: be dealing with it. I look at wolves as you know, 2273 02:21:34,240 --> 02:21:39,000 Speaker 1: they're they're the source of our domestic dogs. They're just 2274 02:21:39,080 --> 02:21:43,360 Speaker 1: a big dog, but they're wild and untamed and um 2275 02:21:44,320 --> 02:21:50,879 Speaker 1: so yeah, to me, it's it's a bummer, anticlimactic A 2276 02:21:51,000 --> 02:21:54,439 Speaker 1: job I had to do when I was killing him 2277 02:21:54,480 --> 02:21:58,640 Speaker 1: as a result of livestock damage something like that, and 2278 02:21:58,760 --> 02:22:03,720 Speaker 1: I choose as a whortsman I could not possibly get 2279 02:22:03,760 --> 02:22:06,520 Speaker 1: any enjoyment out of, you know. And I've killed a 2280 02:22:06,520 --> 02:22:09,000 Speaker 1: couple of mountain lions in my life, and I found 2281 02:22:09,040 --> 02:22:13,320 Speaker 1: that anticlimactic. I've killed a few black bear early on 2282 02:22:13,560 --> 02:22:15,760 Speaker 1: when I first got to the West. You know, I 2283 02:22:15,840 --> 02:22:17,600 Speaker 1: got to get a bear, gotta get a lion, got 2284 02:22:17,600 --> 02:22:20,360 Speaker 1: to get a wolf, or whatever the feeling people have 2285 02:22:20,560 --> 02:22:24,760 Speaker 1: when it's something new. Um. But I've been there, done it, 2286 02:22:25,400 --> 02:22:28,400 Speaker 1: and got no joy out of it as a result, 2287 02:22:29,080 --> 02:22:33,279 Speaker 1: So I don't do it anymore. And that's my personal choice. Yeah, 2288 02:22:33,440 --> 02:22:36,520 Speaker 1: And it's it's interesting to your perspective, given like you said, 2289 02:22:36,560 --> 02:22:38,880 Speaker 1: you've kind of been around at all. You've seen both 2290 02:22:38,920 --> 02:22:45,240 Speaker 1: sides of it. Um, it's very frustrating being a predator manager, 2291 02:22:45,320 --> 02:22:49,840 Speaker 1: you know, in predator control, it's very frustrating because I 2292 02:22:49,879 --> 02:22:52,120 Speaker 1: don't want to have to kill the lion or the bear, 2293 02:22:52,320 --> 02:22:55,560 Speaker 1: or the wolf or even the coyote. I don't want to, 2294 02:22:56,600 --> 02:23:00,720 Speaker 1: but so often they persist. I mean, it's like gone it. 2295 02:23:01,320 --> 02:23:03,520 Speaker 1: I was hoping if we did this or that, or 2296 02:23:03,959 --> 02:23:06,920 Speaker 1: maybe the rnswer moved his sheep somewhere. You know, you 2297 02:23:07,040 --> 02:23:11,480 Speaker 1: made some adjustments that the sheep can live, the livestock 2298 02:23:11,520 --> 02:23:14,360 Speaker 1: can live, the wolves or the predators can live. And 2299 02:23:14,400 --> 02:23:18,320 Speaker 1: then there's that persistence that it can't be resolved that way. 2300 02:23:18,400 --> 02:23:21,119 Speaker 1: We can't move away from the problem. The problem just 2301 02:23:21,280 --> 02:23:26,920 Speaker 1: moves with us. So yeah, I've just never enjoyed going 2302 02:23:26,959 --> 02:23:30,560 Speaker 1: out and killing that predator and going home with some 2303 02:23:30,720 --> 02:23:35,480 Speaker 1: satisfaction of Uh, I did solve the problem. That gave 2304 02:23:35,520 --> 02:23:40,840 Speaker 1: me relief. And when you remove a problem, I mean it, 2305 02:23:41,440 --> 02:23:45,240 Speaker 1: let's the community calm down too. You don't want this 2306 02:23:45,440 --> 02:23:52,680 Speaker 1: persistent headline every day, wolves killing cattle, wolves killing cattle. Um. 2307 02:23:52,760 --> 02:23:56,280 Speaker 1: Everybody gets tired of that, and sometimes you just gotta 2308 02:23:56,280 --> 02:23:58,840 Speaker 1: bite the bullet so to speak, no pun intended, and 2309 02:24:00,800 --> 02:24:05,080 Speaker 1: remove the problem. Uh, it's not been fun for me, 2310 02:24:05,240 --> 02:24:07,800 Speaker 1: but it's it's it's been a job that I've chosen 2311 02:24:07,879 --> 02:24:11,000 Speaker 1: to do and accepted the responsibility that goes with it. 2312 02:24:11,160 --> 02:24:16,119 Speaker 1: And uh, sometimes things ain't always fun at the job. Yeah, 2313 02:24:16,200 --> 02:24:19,039 Speaker 1: any job, but I imagine there were times, particularly in 2314 02:24:19,080 --> 02:24:23,600 Speaker 1: your case. UM. So, wolf seasons are open in many 2315 02:24:23,640 --> 02:24:27,000 Speaker 1: areas now, many states across the West, Um, several states, 2316 02:24:27,000 --> 02:24:31,160 Speaker 1: I guess, not so in the Great Lakes. UM. So 2317 02:24:31,200 --> 02:24:34,800 Speaker 1: regardless of what your opinions are though on that, Um, 2318 02:24:34,879 --> 02:24:37,920 Speaker 1: people are killing wolves now, people are killing lots of counties. 2319 02:24:38,000 --> 02:24:41,080 Speaker 1: Predator management is something that's done across the country. UM, 2320 02:24:41,120 --> 02:24:43,600 Speaker 1: in many cases. You know, I think it's, like you said, 2321 02:24:43,720 --> 02:24:48,720 Speaker 1: it's legal, well founded, people enjoy it. It's happening. Um. 2322 02:24:48,760 --> 02:24:51,520 Speaker 1: But you did speak a little bit earlier today about 2323 02:24:52,120 --> 02:24:54,200 Speaker 1: some of the things we can do as hunters that 2324 02:24:54,240 --> 02:24:55,800 Speaker 1: if we're going to go and do these types of 2325 02:24:55,800 --> 02:24:59,520 Speaker 1: things that can help us mitigate some of the risks 2326 02:24:59,560 --> 02:25:03,840 Speaker 1: as far is bad pr with that, because because there 2327 02:25:04,000 --> 02:25:07,760 Speaker 1: is so much, it's so emotionally charged, um, that when 2328 02:25:07,800 --> 02:25:10,080 Speaker 1: one side of this debate sees a dead wolf on 2329 02:25:10,120 --> 02:25:13,840 Speaker 1: Facebook or something, it can turn to a firestorm of 2330 02:25:13,840 --> 02:25:18,400 Speaker 1: of more madness. Um, what would be your your advice 2331 02:25:18,440 --> 02:25:20,880 Speaker 1: to to other hunters as far as how we talk 2332 02:25:20,959 --> 02:25:25,520 Speaker 1: about wolves or how we um post pictures, whether it 2333 02:25:25,520 --> 02:25:28,120 Speaker 1: be of dead wolves or talking about hunting or anything 2334 02:25:28,160 --> 02:25:31,520 Speaker 1: like that. How do we handle our pr when it 2335 02:25:31,520 --> 02:25:37,959 Speaker 1: comes to predators as hunters better. Well, my individual opinion 2336 02:25:38,040 --> 02:25:40,120 Speaker 1: on this, and I guess others would look at it 2337 02:25:40,160 --> 02:25:44,480 Speaker 1: from my walt perspectives. But if you're a hunter and 2338 02:25:44,520 --> 02:25:48,680 Speaker 1: you hate what you're hunting, um, you don't represent me. 2339 02:25:49,840 --> 02:25:52,760 Speaker 1: There's no animal I've ever killed because I hated it, 2340 02:25:52,920 --> 02:25:56,080 Speaker 1: whether it was a mouse or a pheasant or a wolf, 2341 02:25:57,360 --> 02:26:03,879 Speaker 1: um as you huted to the It just it makes 2342 02:26:03,879 --> 02:26:06,920 Speaker 1: me angry when I see some guy who's legally shouted 2343 02:26:06,959 --> 02:26:10,280 Speaker 1: wolf and he puts a bear hug on it and 2344 02:26:10,360 --> 02:26:12,440 Speaker 1: he tries to hold it up. And you know, with 2345 02:26:12,520 --> 02:26:17,200 Speaker 1: a little camera angle, you can make wolves look gigantic, 2346 02:26:17,320 --> 02:26:21,400 Speaker 1: you can make antlers look enormous, you can make fish 2347 02:26:21,680 --> 02:26:27,280 Speaker 1: look unbelievable. Um, if you want to take that picture, 2348 02:26:27,840 --> 02:26:29,760 Speaker 1: be my guest, take it home, put it in your 2349 02:26:29,800 --> 02:26:33,039 Speaker 1: album book. I don't want to see it. I mean 2350 02:26:33,080 --> 02:26:35,560 Speaker 1: there was a time and I was I'm as guilty 2351 02:26:35,600 --> 02:26:38,200 Speaker 1: as an next when when I was younger. You know, 2352 02:26:38,320 --> 02:26:41,640 Speaker 1: you got your first whatever, your first pheasants, your first rabbit, 2353 02:26:41,760 --> 02:26:45,119 Speaker 1: your first geese. Sure you got pictures and you took 2354 02:26:45,120 --> 02:26:47,920 Speaker 1: pictures and your friends you carried them around, showed them 2355 02:26:47,920 --> 02:26:50,879 Speaker 1: to each other. But that was on a pretty small 2356 02:26:50,920 --> 02:26:54,600 Speaker 1: scale at you know, in the home or community area. 2357 02:26:55,200 --> 02:27:01,720 Speaker 1: But people putting these photos of them holding their dead 2358 02:27:02,000 --> 02:27:07,279 Speaker 1: whatever going on Facebook and public media, that can go viral. 2359 02:27:07,360 --> 02:27:09,959 Speaker 1: I mean, you're doing hunters no favor at all. You're 2360 02:27:10,000 --> 02:27:13,560 Speaker 1: doing trapping no favor. A lot of people say, well, Carter, 2361 02:27:13,600 --> 02:27:16,439 Speaker 1: if you're a trapper, you ought to be representing trappers. 2362 02:27:17,480 --> 02:27:21,640 Speaker 1: I tell trappers count your blessings that trapping is even legal, 2363 02:27:22,640 --> 02:27:26,440 Speaker 1: and if you enjoy trapping and the state permits it, 2364 02:27:27,160 --> 02:27:33,040 Speaker 1: be my guest. But if you wonder why everybody's down 2365 02:27:33,120 --> 02:27:37,240 Speaker 1: on you as a trapper or a hunter, when you 2366 02:27:37,280 --> 02:27:42,040 Speaker 1: look at the display of death being shoved in people's face, 2367 02:27:42,560 --> 02:27:47,960 Speaker 1: nobody wants to see that um And I know that 2368 02:27:48,600 --> 02:27:51,720 Speaker 1: no matter how much I plead, it's not going to change. 2369 02:27:52,400 --> 02:27:54,879 Speaker 1: So if you hate wolves and you want to put 2370 02:27:54,920 --> 02:27:59,039 Speaker 1: your gory pictures of the wolves that you shot, the 2371 02:27:59,120 --> 02:28:01,560 Speaker 1: latest one right now is somebody with an a r 2372 02:28:01,680 --> 02:28:07,720 Speaker 1: fIF in Alaska that mowed down ten wolves on a snowmobile. Nonetheless. Two, 2373 02:28:07,720 --> 02:28:13,200 Speaker 1: I mean I have no respect whatsoever for somebody does 2374 02:28:13,200 --> 02:28:16,480 Speaker 1: that go out there on the ground, take your little 2375 02:28:16,480 --> 02:28:20,880 Speaker 1: single shot weapon, one shot, let's see you get ten wolves. 2376 02:28:21,640 --> 02:28:24,600 Speaker 1: And uh, I really don't care if you do or not. 2377 02:28:24,959 --> 02:28:29,959 Speaker 1: I'm not interested, and neither is the majority of the 2378 02:28:29,959 --> 02:28:32,800 Speaker 1: world I think is sick of carnage and sick of death. 2379 02:28:33,640 --> 02:28:38,600 Speaker 1: So I think hunters that want to perpetuate this sport, 2380 02:28:39,040 --> 02:28:47,000 Speaker 1: this hobby, this privilege have to really work at policing, hunting, 2381 02:28:47,200 --> 02:28:51,640 Speaker 1: trying to get people. Two. I guess just be ethical. 2382 02:28:52,760 --> 02:28:55,480 Speaker 1: You can. You can go out and do this with 2383 02:28:55,600 --> 02:28:59,400 Speaker 1: respect for what you kill, and you can do it 2384 02:28:59,400 --> 02:29:04,640 Speaker 1: in the private see of the field where you take it. Uh. 2385 02:29:04,920 --> 02:29:07,040 Speaker 1: I don't hauld things home on the hood of my truck. 2386 02:29:07,280 --> 02:29:10,240 Speaker 1: I mean, we we kill a deer and elk, we 2387 02:29:10,320 --> 02:29:12,080 Speaker 1: cut it up in the field, we put it in 2388 02:29:12,480 --> 02:29:15,600 Speaker 1: we call them game bags, wrap them up to keep 2389 02:29:15,680 --> 02:29:18,440 Speaker 1: the insects and dirt off of them, and we put 2390 02:29:18,480 --> 02:29:21,200 Speaker 1: it in our vehicle and we transported home. And we 2391 02:29:21,280 --> 02:29:26,720 Speaker 1: don't advertise to the whole world and every town we 2392 02:29:26,840 --> 02:29:29,279 Speaker 1: drive through the look at me, look what I killed. 2393 02:29:30,360 --> 02:29:32,720 Speaker 1: And I think that's what it's about. If you want 2394 02:29:32,720 --> 02:29:34,840 Speaker 1: to take pictures and show them to your family and 2395 02:29:34,879 --> 02:29:39,520 Speaker 1: your friends and your relatives, perfectly fine. I don't want 2396 02:29:39,520 --> 02:29:42,320 Speaker 1: to see him unless you're a friend of mine and 2397 02:29:42,360 --> 02:29:44,760 Speaker 1: I I want to see it, and you want to 2398 02:29:44,760 --> 02:29:48,840 Speaker 1: offer that opportunity for me to view it. Yeah, that 2399 02:29:48,840 --> 02:29:50,880 Speaker 1: that that's how I look at it. It's a big, 2400 02:29:50,879 --> 02:29:54,400 Speaker 1: tall order because, uh, we've just got so many people 2401 02:29:54,440 --> 02:29:58,440 Speaker 1: involved in hunting, and we all have different values and 2402 02:29:58,480 --> 02:30:04,080 Speaker 1: attitudes and we all react differently. It definitely is a 2403 02:30:04,080 --> 02:30:06,600 Speaker 1: tricky topic. And it's one of those things where when 2404 02:30:06,640 --> 02:30:10,760 Speaker 1: this imagery, especially imagery gets out there online, that when 2405 02:30:10,800 --> 02:30:13,560 Speaker 1: when seen by someone who doesn't have the context of 2406 02:30:13,760 --> 02:30:15,320 Speaker 1: why we do what we do or how we do 2407 02:30:15,400 --> 02:30:18,400 Speaker 1: what we do, when they just see this image, especially 2408 02:30:18,440 --> 02:30:22,800 Speaker 1: if it's not a particular respectful image, um yeah, it 2409 02:30:22,800 --> 02:30:25,600 Speaker 1: can be seen and be really upsetting the people and 2410 02:30:26,520 --> 02:30:29,520 Speaker 1: cause cause harm to the overall cunning community in a 2411 02:30:29,560 --> 02:30:32,000 Speaker 1: lot of ways. Where and I talked to us all 2412 02:30:32,040 --> 02:30:35,640 Speaker 1: this time, but we live in a democracy where we 2413 02:30:35,640 --> 02:30:38,240 Speaker 1: are not the majority, and um, if we want to 2414 02:30:38,240 --> 02:30:40,160 Speaker 1: continue what we're doing, we just need to be mindful 2415 02:30:40,200 --> 02:30:43,560 Speaker 1: of that and careful about that. In the end, it 2416 02:30:43,640 --> 02:30:47,920 Speaker 1: may result and nobody's fault but our own. If we 2417 02:30:47,959 --> 02:30:54,119 Speaker 1: want to maintain the privilege to be hunters, and yeah, 2418 02:30:54,440 --> 02:31:00,560 Speaker 1: falls back on our responsibility to promote it in a 2419 02:31:00,600 --> 02:31:04,600 Speaker 1: positive image. If there can be one mm hm and 2420 02:31:04,640 --> 02:31:07,400 Speaker 1: you know one of my when it's looping back to 2421 02:31:07,480 --> 02:31:10,920 Speaker 1: predators to UM. When I think about this, the the 2422 02:31:10,959 --> 02:31:14,440 Speaker 1: importance of hunters representing themselves well to the general public 2423 02:31:14,560 --> 02:31:17,800 Speaker 1: because we need their essentially their approval to continue what 2424 02:31:17,840 --> 02:31:21,000 Speaker 1: we're doing in the future. UM, to maintain that privilege. 2425 02:31:21,520 --> 02:31:24,520 Speaker 1: Part of our big claim to legitimacy as hunters very 2426 02:31:24,520 --> 02:31:27,199 Speaker 1: often is that we are great conservationists. We are stewards 2427 02:31:27,240 --> 02:31:29,920 Speaker 1: of the land of the wild life. We care about 2428 02:31:29,959 --> 02:31:32,879 Speaker 1: these animals. UM. We do so much to to help 2429 02:31:33,040 --> 02:31:36,400 Speaker 1: keep these animals and sustainable populations and and whatnot. But 2430 02:31:36,560 --> 02:31:40,640 Speaker 1: when you start being selective about what animals you care about, 2431 02:31:40,720 --> 02:31:42,800 Speaker 1: and you say, oh, yeah, I'm like great conservations, I 2432 02:31:42,879 --> 02:31:45,040 Speaker 1: care about deer and l can do this. But when 2433 02:31:45,080 --> 02:31:47,200 Speaker 1: it comes to wolves, shoot, shovel and shut up, get 2434 02:31:47,280 --> 02:31:50,400 Speaker 1: rid of those things. When you start seeing that happen, 2435 02:31:50,440 --> 02:31:54,160 Speaker 1: I think we lose all credibility to being conservationist if 2436 02:31:54,240 --> 02:31:56,200 Speaker 1: you start just being selected, I only care about the 2437 02:31:56,240 --> 02:31:59,240 Speaker 1: animals I want to shoot myself. UM. So I think 2438 02:31:59,600 --> 02:32:02,360 Speaker 1: if even if you don't like wolves, even if you're 2439 02:32:02,400 --> 02:32:05,080 Speaker 1: not interested in them in any way, even if you 2440 02:32:05,160 --> 02:32:07,520 Speaker 1: view them as competition for your resource, that's the way 2441 02:32:07,520 --> 02:32:10,320 Speaker 1: you want to see it. Whatever. But just from a 2442 02:32:10,360 --> 02:32:13,280 Speaker 1: pragmatic standpoint, if you want to be able to continue 2443 02:32:13,320 --> 02:32:16,920 Speaker 1: to hunt, you got to walk the walk of of 2444 02:32:16,959 --> 02:32:20,720 Speaker 1: being a real responsible hunter and conservationoust which which means 2445 02:32:20,720 --> 02:32:23,520 Speaker 1: we need to show respect to all the animals and 2446 02:32:23,560 --> 02:32:28,879 Speaker 1: the landscape and maintaining a true balanced natural ecosystem includes 2447 02:32:29,160 --> 02:32:33,360 Speaker 1: wolves and coyotes and bears and um, people can see 2448 02:32:33,440 --> 02:32:35,320 Speaker 1: rights of the b s. If if we're not being 2449 02:32:35,320 --> 02:32:38,480 Speaker 1: true to that, in my opinion, well, these predators and 2450 02:32:38,480 --> 02:32:41,480 Speaker 1: prey go together. I mean, it's it's the beginning of time. 2451 02:32:41,600 --> 02:32:48,320 Speaker 1: There's specific predators who prey on certain prey species, and 2452 02:32:48,480 --> 02:32:50,680 Speaker 1: I look at that. It's absolutely I mean, when I 2453 02:32:50,680 --> 02:32:53,360 Speaker 1: go out to a marsh, if I see a maink 2454 02:32:53,400 --> 02:32:56,760 Speaker 1: attack a muskrat, I'm thinking that's the way it's supposed 2455 02:32:56,800 --> 02:33:01,920 Speaker 1: to work. Um. And you just take in our backyard, 2456 02:33:02,200 --> 02:33:06,440 Speaker 1: we feed birds all winter, and we have sharp shinn 2457 02:33:06,480 --> 02:33:11,360 Speaker 1: and Cooper's hawks come through our yard every day all 2458 02:33:11,480 --> 02:33:17,720 Speaker 1: winter and kill a junco or kill a finch. We say, 2459 02:33:17,800 --> 02:33:23,400 Speaker 1: that's the way it works, and there's always more juncos 2460 02:33:23,440 --> 02:33:27,760 Speaker 1: and more finches next winter, so they replace themselves. And 2461 02:33:27,840 --> 02:33:33,840 Speaker 1: those hawks have every right to exist and to eat 2462 02:33:33,879 --> 02:33:38,280 Speaker 1: those prey. And I hear so many humans saying, well, 2463 02:33:38,280 --> 02:33:40,400 Speaker 1: I just ain't right. You know the way the way 2464 02:33:40,440 --> 02:33:44,400 Speaker 1: the wolves kill or the way the hawks kill. Well, 2465 02:33:45,600 --> 02:33:50,240 Speaker 1: look in the mirror, humans, you're either killing your food 2466 02:33:50,320 --> 02:33:53,879 Speaker 1: or someone's killing it for you. Uh. And it ain't 2467 02:33:53,879 --> 02:33:56,160 Speaker 1: pretty either, no matter how you want to paint it. 2468 02:33:56,879 --> 02:34:01,720 Speaker 1: So I, as I have gotten older, I am careful 2469 02:34:01,800 --> 02:34:05,520 Speaker 1: not to judge what goes on out in nature. It's 2470 02:34:06,000 --> 02:34:08,600 Speaker 1: kill or be killed. This is pretty much how it works. 2471 02:34:09,160 --> 02:34:13,039 Speaker 1: And the humans were just one species, and I don't 2472 02:34:13,040 --> 02:34:17,400 Speaker 1: look at us as superior to these other species. Now 2473 02:34:17,400 --> 02:34:20,080 Speaker 1: there's others who would say, well, Carter, you're dead, dear dead, wrong. 2474 02:34:20,720 --> 02:34:22,440 Speaker 1: And I've had a lot of people tell me, look, 2475 02:34:22,959 --> 02:34:28,400 Speaker 1: if an elk needs killing, I'll kill it, And sorry, 2476 02:34:28,680 --> 02:34:32,440 Speaker 1: I don't accept that at all. And there's people who say, well, 2477 02:34:32,480 --> 02:34:35,840 Speaker 1: the wolves are killing my elk and they're killing my dear. 2478 02:34:37,080 --> 02:34:39,959 Speaker 1: And so I've said that to people in the situation 2479 02:34:40,000 --> 02:34:42,160 Speaker 1: it's right. I said, well, you know, I have a 2480 02:34:42,160 --> 02:34:44,280 Speaker 1: deer and elk tag in my billfold this year, and 2481 02:34:44,879 --> 02:34:48,440 Speaker 1: they can have my dear in my elk if we're 2482 02:34:48,440 --> 02:34:53,880 Speaker 1: gonna add this possession. You know that there ours. They're 2483 02:34:53,920 --> 02:34:58,039 Speaker 1: not ours. We're just privilege some of us to be 2484 02:34:58,080 --> 02:35:01,720 Speaker 1: able to hunt the surplus us and uh get the 2485 02:35:01,760 --> 02:35:06,119 Speaker 1: opportunity to take some really good quality organic meat home 2486 02:35:06,160 --> 02:35:09,080 Speaker 1: with us to eat. But I don't look at us 2487 02:35:09,120 --> 02:35:13,400 Speaker 1: as privileged over any more than those predators out there 2488 02:35:13,400 --> 02:35:17,640 Speaker 1: that are doing what they do. I Uh, I really 2489 02:35:17,680 --> 02:35:21,080 Speaker 1: appreciate your perspective on all of this. It's it's really interesting. 2490 02:35:21,120 --> 02:35:24,080 Speaker 1: I think the things you've been involved with give you 2491 02:35:25,640 --> 02:35:28,000 Speaker 1: just give you a context that I think a lot 2492 02:35:28,040 --> 02:35:30,120 Speaker 1: of people don't have. The I mean, I can, I 2493 02:35:30,160 --> 02:35:33,320 Speaker 1: can say whatever I want about wolves from what I've 2494 02:35:33,360 --> 02:35:35,000 Speaker 1: read or seen, but I have no on the ground 2495 02:35:35,080 --> 02:35:36,879 Speaker 1: experience like that, And so many people that like to 2496 02:35:36,920 --> 02:35:39,280 Speaker 1: debate about wolves have no real on the ground context 2497 02:35:39,360 --> 02:35:42,160 Speaker 1: with predators in many cases. Um, but but someone in 2498 02:35:42,200 --> 02:35:44,640 Speaker 1: your shoes, who's who's been there, who's talked to all 2499 02:35:44,680 --> 02:35:48,240 Speaker 1: sides of this. UM, who's who's come at this as 2500 02:35:48,720 --> 02:35:51,039 Speaker 1: a predator manager at one point in your life as 2501 02:35:51,080 --> 02:35:56,560 Speaker 1: a hunter, as someone who enjoys wildlife. UM, it's just um, 2502 02:35:56,600 --> 02:35:59,400 Speaker 1: it's fascinating, it's interesting. I appreciate you speaking up about 2503 02:35:59,400 --> 02:36:02,400 Speaker 1: these things, give your opinion. I think, UM, we need 2504 02:36:02,400 --> 02:36:05,640 Speaker 1: to hear all sorts of different things like this, and uh, 2505 02:36:05,680 --> 02:36:07,720 Speaker 1: it's much appreciated. So thank yous for taking the time 2506 02:36:07,760 --> 02:36:10,120 Speaker 1: to to talk with us about it. Car Well, I 2507 02:36:10,120 --> 02:36:12,840 Speaker 1: feel privileged getting the opportunity to talk to you for 2508 02:36:12,879 --> 02:36:18,240 Speaker 1: a while about this. Never hesitate to share my opinions 2509 02:36:18,240 --> 02:36:21,440 Speaker 1: with people that want to listen. And that is a 2510 02:36:21,640 --> 02:36:28,280 Speaker 1: rap on our Wolves and Coyotes and Hunters podcast. Hopefully 2511 02:36:28,320 --> 02:36:30,600 Speaker 1: you found this one as interesting as I thought it was. 2512 02:36:31,240 --> 02:36:34,280 Speaker 1: I appreciate you sticking around hearing it out, listening to 2513 02:36:34,360 --> 02:36:37,560 Speaker 1: these different ideas, ways of thinking about predators and how 2514 02:36:37,600 --> 02:36:40,320 Speaker 1: we relate to them as hunters. UM. A couple of 2515 02:36:40,320 --> 02:36:44,400 Speaker 1: book recommendations for you. Number one, if you enjoyed hearing 2516 02:36:44,440 --> 02:36:46,840 Speaker 1: what Carter had to say, he has two very interesting 2517 02:36:46,840 --> 02:36:50,160 Speaker 1: books out. One is called Wolfer. I've read that. I've 2518 02:36:50,240 --> 02:36:52,760 Speaker 1: found that very interesting. It goes into detail of his 2519 02:36:52,840 --> 02:36:55,520 Speaker 1: whole history within this issue. And then his more recent 2520 02:36:55,520 --> 02:36:59,760 Speaker 1: book is called wolf Land. Also, um a book related 2521 02:36:59,800 --> 02:37:04,000 Speaker 1: to coyotes is called Coyote America by Dan Flores, and 2522 02:37:04,040 --> 02:37:06,640 Speaker 1: that is a really interesting book too. And then finally, 2523 02:37:06,680 --> 02:37:09,320 Speaker 1: if you want to read Thinking Like a Mountain and 2524 02:37:09,480 --> 02:37:13,560 Speaker 1: other essays by Aldo Leopold, I can't recommend enough his 2525 02:37:13,680 --> 02:37:17,800 Speaker 1: book A Sand County Almanac. So give those ones a read. 2526 02:37:17,840 --> 02:37:20,200 Speaker 1: I think you'll find something interesting and they're related to 2527 02:37:20,200 --> 02:37:23,440 Speaker 1: this entire topic that we talked about. Now, to wrap 2528 02:37:23,480 --> 02:37:26,240 Speaker 1: it up, I just want to thank our partners who 2529 02:37:26,280 --> 02:37:29,240 Speaker 1: helped make this possible. Big Things to Sick a Gear 2530 02:37:29,320 --> 02:37:32,800 Speaker 1: Yetie Cooler's, Matthew's Archery, may Haven Optics, White Tail Institute 2531 02:37:32,800 --> 02:37:36,680 Speaker 1: of North America, Trophy Ridge and hunter A Maps. And finally, 2532 02:37:37,160 --> 02:37:40,120 Speaker 1: thank you all for listening. I appreciate you coming at 2533 02:37:40,120 --> 02:37:43,000 Speaker 1: this episode with an open mind. I appreciate your comments 2534 02:37:43,040 --> 02:37:45,120 Speaker 1: and your opinions and their thoughts. I'm always interested in 2535 02:37:45,120 --> 02:37:47,640 Speaker 1: hearing what you think about this stuff. So thanks for listening, 2536 02:37:47,760 --> 02:37:51,600 Speaker 1: thanks for sharing your feedback, and until next time, stay 2537 02:37:52,240 --> 02:37:53,560 Speaker 1: wired to hunt