1
00:00:08,760 --> 00:00:13,320
Speaker 1: If this is the Meat Eater Podcast coming at you shirtless, severely,

2
00:00:13,480 --> 00:00:15,720
Speaker 1: bug bitten, and in my case, underwear.

3
00:00:15,360 --> 00:00:19,360
Speaker 2: Listeningcast, you can't predict anything.

4
00:00:20,120 --> 00:00:22,800
Speaker 1: The Meat Eater Podcast is brought to you by first Light.

5
00:00:23,000 --> 00:00:26,079
Speaker 1: Whether you're checking trail cams, hanging deer stands, or scouting

6
00:00:26,120 --> 00:00:29,560
Speaker 1: for el, First Light has performance apparel to support every

7
00:00:29,640 --> 00:00:32,400
Speaker 1: hunter in every environment. Check it out at first light

8
00:00:32,520 --> 00:00:35,640
Speaker 1: dot com. F I R S T l I t

9
00:00:35,800 --> 00:00:43,520
Speaker 1: e dot com. Joined today by Dusty Lassiter, former Wyoming

10
00:00:43,640 --> 00:00:47,120
Speaker 1: game and fish bear management specialists, the keyword there being former.

11
00:00:48,680 --> 00:00:49,760
Speaker 3: Yeah.

12
00:00:49,880 --> 00:00:51,840
Speaker 1: I love the agency guys. But the problem with having

13
00:00:51,880 --> 00:00:54,440
Speaker 1: agency guys on to talk about wildlife management is they

14
00:00:54,480 --> 00:00:56,560
Speaker 1: got to worry about them getting in trouble. Yeah.

15
00:00:56,600 --> 00:00:58,280
Speaker 4: I don't have to worry about getting in trouble anymore.

16
00:00:58,520 --> 00:01:00,520
Speaker 1: Real, there's no trouble. Nothing can do it to you.

17
00:01:01,560 --> 00:01:02,840
Speaker 1: Let the air out of your tires.

18
00:01:03,280 --> 00:01:05,440
Speaker 4: Yeah, write me a ticket.

19
00:01:05,480 --> 00:01:09,680
Speaker 1: I guess no. Again, I have nothing, But you know,

20
00:01:10,000 --> 00:01:12,080
Speaker 1: I have like a lot of respect and the admiration

21
00:01:12,200 --> 00:01:15,200
Speaker 1: for agency biologists and game wardens Like you know, I

22
00:01:15,240 --> 00:01:18,680
Speaker 1: love it. So many of them are driven by passion

23
00:01:18,840 --> 00:01:21,319
Speaker 1: and a desire to do good. But when talking about

24
00:01:21,360 --> 00:01:25,080
Speaker 1: policy just gets tricky for him because you know, they

25
00:01:25,880 --> 00:01:27,000
Speaker 1: they get reprimanded.

26
00:01:27,080 --> 00:01:30,399
Speaker 4: Yeah, you get muzzled a little bit, and you know

27
00:01:30,480 --> 00:01:33,679
Speaker 4: you're trying to walk the party line a little bit,

28
00:01:33,760 --> 00:01:34,959
Speaker 4: you know, the department line.

29
00:01:35,120 --> 00:01:39,600
Speaker 1: Yeah. Uh, give everybody a run through of what you've

30
00:01:39,600 --> 00:01:42,120
Speaker 1: done in your career around grizzly bears and wolves.

31
00:01:41,840 --> 00:01:46,280
Speaker 4: And oh man, So I started in twenty ten and

32
00:01:47,640 --> 00:01:51,559
Speaker 4: I was just supposed to be on for one fall.

33
00:01:51,600 --> 00:01:54,840
Speaker 4: In one spring, I got hired on because one of

34
00:01:54,840 --> 00:01:59,440
Speaker 4: my coworkers was going back to college. And that was

35
00:01:59,480 --> 00:02:02,480
Speaker 4: the busiest year that we'd ever had. We caught sixty

36
00:02:02,480 --> 00:02:06,360
Speaker 4: seven grizzly bears in Wyoming outside of Yellstowe National Park.

37
00:02:07,080 --> 00:02:11,920
Speaker 4: And then in that year, so damn man. Yeah, yeah, it.

38
00:02:11,840 --> 00:02:13,320
Speaker 1: Was all in barrel traps.

39
00:02:14,200 --> 00:02:16,640
Speaker 4: Yeah. We we call them culvert traps, but they're really

40
00:02:16,880 --> 00:02:21,160
Speaker 4: big square box traps. Now the Montana guys still use

41
00:02:21,240 --> 00:02:24,320
Speaker 4: those culverts, but it's a pain in the butt to

42
00:02:24,400 --> 00:02:25,760
Speaker 4: pull a bear in and out of them.

43
00:02:26,560 --> 00:02:29,919
Speaker 1: Yeah remember that round, Remember that video Callahan climbing in there,

44
00:02:30,120 --> 00:02:32,880
Speaker 1: climbing one of them tubes of that bearris basically like

45
00:02:32,960 --> 00:02:34,640
Speaker 1: laid out on it. Yeah.

46
00:02:34,720 --> 00:02:37,240
Speaker 4: Yeah, yeah, so we we I think we dealt with

47
00:02:37,360 --> 00:02:40,200
Speaker 4: enough bears. We came up with a better trap design. Honestly,

48
00:02:40,760 --> 00:02:41,880
Speaker 4: what do you what were you guys?

49
00:02:42,280 --> 00:02:44,480
Speaker 1: Man? I got so many questions go on. I just

50
00:02:44,560 --> 00:02:46,360
Speaker 1: remember that later. I want to ask you about what

51
00:02:46,480 --> 00:02:48,600
Speaker 1: kind of how you like, what your favorite bait and

52
00:02:48,639 --> 00:02:50,800
Speaker 1: stuff is. But keep going. Yeah, so you got on.

53
00:02:51,000 --> 00:02:52,880
Speaker 1: You guys started just hammering bears.

54
00:02:53,200 --> 00:02:56,639
Speaker 4: Yeah, it was just call after call. I would try

55
00:02:56,680 --> 00:02:58,120
Speaker 4: to go home just to take a nap, and I

56
00:02:58,120 --> 00:03:01,160
Speaker 4: would get flagged down on the road somebody being like,

57
00:03:01,919 --> 00:03:04,600
Speaker 4: I got a I got a bear. Actually, one of

58
00:03:04,639 --> 00:03:08,040
Speaker 4: those guys was Jim Zumbo. You know. He flagged me

59
00:03:08,080 --> 00:03:10,440
Speaker 4: down on the road and he's like, yeah, I just

60
00:03:10,480 --> 00:03:13,600
Speaker 4: got back from Alaska. I'd killed my twentieth black bear,

61
00:03:14,160 --> 00:03:17,239
Speaker 4: and he was he was smoking some salmon and a

62
00:03:17,280 --> 00:03:20,720
Speaker 4: grizzly bear came by and smashed his salmon smoker.

63
00:03:21,000 --> 00:03:22,120
Speaker 1: Oh I got it, so.

64
00:03:23,840 --> 00:03:25,040
Speaker 4: Yeah, so I started.

65
00:03:25,200 --> 00:03:29,920
Speaker 1: Jim Zumbo, Yeah, came home from Alaska, was smoking salmon

66
00:03:29,919 --> 00:03:32,640
Speaker 1: that he brought home from Alaska, and a grizzly showed

67
00:03:32,720 --> 00:03:34,520
Speaker 1: up and smashed Jim zumbole smoker.

68
00:03:34,680 --> 00:03:39,640
Speaker 4: Yeah exactly, yep, yep, so pretty legit kind of funny.

69
00:03:39,920 --> 00:03:40,160
Speaker 5: Yeah.

70
00:03:40,280 --> 00:03:44,160
Speaker 1: Yeah, and I wanted one up with my George Bush

71
00:03:44,200 --> 00:03:49,320
Speaker 1: story h joke.

72
00:03:51,800 --> 00:03:53,840
Speaker 4: Yeah. So that was just a really busy season and

73
00:03:54,160 --> 00:03:58,080
Speaker 4: there was a need for more help, so they hired

74
00:03:58,080 --> 00:04:00,000
Speaker 4: me on another season.

75
00:04:00,480 --> 00:04:04,680
Speaker 1: And because you were a big game guide, yeah I was.

76
00:04:05,160 --> 00:04:08,480
Speaker 4: You know, I went to the University Wyoming, got finance degree,

77
00:04:08,680 --> 00:04:12,800
Speaker 4: came home and just loved where I lived. And when

78
00:04:12,800 --> 00:04:14,800
Speaker 4: I came home, I was working on the thoroughfare as

79
00:04:14,840 --> 00:04:17,719
Speaker 4: a guide, and you know, just doing construction, trying to

80
00:04:17,720 --> 00:04:18,560
Speaker 4: make ends meet, and.

81
00:04:20,120 --> 00:04:21,880
Speaker 3: Home as Cody, Home as Cody.

82
00:04:21,920 --> 00:04:25,840
Speaker 4: That's where I grew up. And I was just wrong place,

83
00:04:25,920 --> 00:04:29,920
Speaker 4: wrong time, honestly, because there weren't a lot of people

84
00:04:30,000 --> 00:04:33,040
Speaker 4: that went to college and came back and I had

85
00:04:33,080 --> 00:04:35,760
Speaker 4: a lot of knowledge and skill about horses in the

86
00:04:35,760 --> 00:04:38,440
Speaker 4: back country, and you know, my life was immersed in

87
00:04:39,160 --> 00:04:42,400
Speaker 4: wildlife and bears growing up, and my parents worked for

88
00:04:42,440 --> 00:04:45,640
Speaker 4: outfitters and you know, they were stopping in at the

89
00:04:45,680 --> 00:04:49,520
Speaker 4: house and telling crazy stories and I was just sucked in.

90
00:04:49,680 --> 00:04:54,240
Speaker 4: So that's why I came home. And I wasn't intending

91
00:04:54,279 --> 00:04:58,119
Speaker 4: to get into bear work, and I just fell into

92
00:04:58,160 --> 00:05:02,559
Speaker 4: it and the timing was right, and yeah, they hired

93
00:05:02,600 --> 00:05:05,279
Speaker 4: me on and you know, that first year I saw

94
00:05:05,320 --> 00:05:08,839
Speaker 4: twenty five bears, and then that next season I was

95
00:05:08,880 --> 00:05:13,120
Speaker 4: in on another twenty five Grizzly captures and had fifty

96
00:05:13,160 --> 00:05:18,320
Speaker 4: under my belt and a pretty quick, you know amount

97
00:05:18,360 --> 00:05:18,720
Speaker 4: of time.

98
00:05:18,920 --> 00:05:21,400
Speaker 1: So were you doing all the were you doing all

99
00:05:21,440 --> 00:05:25,839
Speaker 1: the relocations on those two? Like how many are euthanized

100
00:05:25,839 --> 00:05:26,960
Speaker 1: and how many are relocated?

101
00:05:27,320 --> 00:05:30,120
Speaker 4: So at the time, my boss was a guy named

102
00:05:30,160 --> 00:05:34,560
Speaker 4: Mark Persino, and we were really still in the recovery

103
00:05:34,600 --> 00:05:38,719
Speaker 4: phase with these bears, and we probably only euthanized one

104
00:05:38,760 --> 00:05:42,200
Speaker 4: out of five when I started, and they were in

105
00:05:42,279 --> 00:05:49,000
Speaker 4: really bad shape. You know, they'd been repeat offenders. Never

106
00:05:50,200 --> 00:05:53,599
Speaker 4: it's never the three strikes and you're out. People say

107
00:05:53,640 --> 00:05:55,479
Speaker 4: that all the time, and I get so sick of that.

108
00:05:55,480 --> 00:05:56,080
Speaker 1: That's not true.

109
00:05:56,160 --> 00:05:59,839
Speaker 4: No, that's not true. It's not California. So but yeah,

110
00:05:59,880 --> 00:06:02,160
Speaker 4: there were some bears that, you know, I'd been in

111
00:06:02,360 --> 00:06:05,880
Speaker 4: multiple livestock conflicts that were removing or I caught a

112
00:06:05,920 --> 00:06:09,560
Speaker 4: female that year that her back leg was broke and

113
00:06:09,600 --> 00:06:12,640
Speaker 4: it was six inches shorter than her other back leg,

114
00:06:13,040 --> 00:06:14,880
Speaker 4: and I had the bone in my office and it's

115
00:06:14,920 --> 00:06:19,000
Speaker 4: just a you know, melded piece of calcium.

116
00:06:19,240 --> 00:06:21,240
Speaker 1: How do you think she broke her leg, No idea.

117
00:06:21,320 --> 00:06:22,240
Speaker 4: I always wondered that.

118
00:06:23,080 --> 00:06:25,080
Speaker 1: You know, on a bear like that, on a grizzy

119
00:06:25,160 --> 00:06:30,000
Speaker 1: like that, it's in heart, it's in bad shape, it's desperate,

120
00:06:30,080 --> 00:06:33,800
Speaker 1: and it's not gonna You're not gonna you know what

121
00:06:33,920 --> 00:06:35,840
Speaker 1: the word to use. You're not going to rehabilitate it.

122
00:06:36,000 --> 00:06:39,279
Speaker 4: No, it just wasn't going to be successful relocating that

123
00:06:39,360 --> 00:06:42,720
Speaker 4: kind of bear. And she was emaciated, and she actually

124
00:06:42,760 --> 00:06:47,479
Speaker 4: had a yearling that we didn't know about at the time.

125
00:06:47,880 --> 00:06:49,840
Speaker 4: You know, she was she was trying to orphan a

126
00:06:50,720 --> 00:06:54,800
Speaker 4: yearling bear because she was not even producing milk. She

127
00:06:54,880 --> 00:06:56,560
Speaker 4: was in such poor physical shape.

128
00:06:56,760 --> 00:07:00,080
Speaker 1: Got it. You say she was trying to orphan it.

129
00:07:00,839 --> 00:07:04,039
Speaker 4: Yeah, I mean it was. It was following her around,

130
00:07:04,160 --> 00:07:08,839
Speaker 4: but she's not providing for it at all. And we

131
00:07:08,960 --> 00:07:12,840
Speaker 4: ended up catching that bear too, and and we relocated

132
00:07:12,880 --> 00:07:17,600
Speaker 4: that bear, but she just wasn't a good candidate for relocation.

133
00:07:18,040 --> 00:07:21,040
Speaker 1: Yeah. And when you relocate the grizzlies, how do you

134
00:07:21,360 --> 00:07:23,800
Speaker 1: how do you figure out where to try because you

135
00:07:23,840 --> 00:07:27,760
Speaker 1: got to put him so far away from you got

136
00:07:27,800 --> 00:07:31,880
Speaker 1: to put them so far away, Yeah, to reduce the

137
00:07:31,920 --> 00:07:34,520
Speaker 1: temptation you're going to get in trouble again. And that's

138
00:07:34,560 --> 00:07:36,880
Speaker 1: and that's got to be like very time consuming.

139
00:07:37,600 --> 00:07:42,760
Speaker 4: Yeah, it definitely takes some man power, but you're trying

140
00:07:42,800 --> 00:07:46,280
Speaker 4: to take it as far away from the conflict as possible.

141
00:07:46,520 --> 00:07:50,760
Speaker 4: And there's really about six relocation sites in Wyoming that

142
00:07:50,880 --> 00:07:54,880
Speaker 4: we use, you know, And that kind of had changed

143
00:07:54,960 --> 00:07:57,440
Speaker 4: over the time that I'd been at the department. We

144
00:07:57,840 --> 00:08:00,760
Speaker 4: started doing some relocation that weren't as.

145
00:08:00,680 --> 00:08:04,000
Speaker 1: Far and use helicopters to dump them off.

146
00:08:04,440 --> 00:08:07,200
Speaker 4: We don't. We had one bear trap that you could

147
00:08:07,480 --> 00:08:11,760
Speaker 4: take off the wheels and haul with the helicopter, But

148
00:08:12,680 --> 00:08:14,520
Speaker 4: and the time that I was there, the eleven years

149
00:08:14,560 --> 00:08:15,600
Speaker 4: I was there, we never did that.

150
00:08:16,120 --> 00:08:18,640
Speaker 1: Yeah, now tell me how you catch one.

151
00:08:20,200 --> 00:08:23,080
Speaker 4: So most of the time you're using a culvert trap,

152
00:08:23,120 --> 00:08:25,600
Speaker 4: and you want to get that thing as low to

153
00:08:25,640 --> 00:08:27,800
Speaker 4: the ground as possible. You want to set it as

154
00:08:27,840 --> 00:08:34,240
Speaker 4: close to the conflict as possible, and you just put

155
00:08:34,240 --> 00:08:35,920
Speaker 4: a piece of bait in the front of that thing,

156
00:08:36,080 --> 00:08:39,199
Speaker 4: usually a road killed deer with a string that goes

157
00:08:39,920 --> 00:08:44,360
Speaker 4: up up the front wall around the top, and then

158
00:08:44,480 --> 00:08:47,360
Speaker 4: it's sitting on a pair of ice scripts and the

159
00:08:47,400 --> 00:08:51,080
Speaker 4: door is sitting on those vice scripts. So bear comes

160
00:08:51,120 --> 00:08:54,079
Speaker 4: in pulls that bait springs, the vice grip springs the

161
00:08:54,160 --> 00:08:57,120
Speaker 4: vice script and the door shuts and there's a pin

162
00:08:57,240 --> 00:09:01,680
Speaker 4: that shoots. Yeah, a lot of times we use beaver

163
00:09:01,800 --> 00:09:04,640
Speaker 4: caster is always my favorite thing to use. A little lure, Yeah,

164
00:09:04,720 --> 00:09:07,360
Speaker 4: a little bit of lure in there. If it's ket

165
00:09:07,440 --> 00:09:11,680
Speaker 4: in on fruit, we'd use apples and watermelon things like that.

166
00:09:11,920 --> 00:09:13,160
Speaker 1: Stick that back of the trap.

167
00:09:13,760 --> 00:09:16,800
Speaker 4: Yeah, even like a trail into it a lot of times.

168
00:09:17,080 --> 00:09:19,080
Speaker 4: A lot of times you make a drag and they'll

169
00:09:19,080 --> 00:09:20,199
Speaker 4: follow a drag for a.

170
00:09:20,160 --> 00:09:24,280
Speaker 1: Long long ways, like drag a road kill deer, right, yep?

171
00:09:25,800 --> 00:09:27,680
Speaker 1: How far might you drag that deer to make a

172
00:09:27,720 --> 00:09:28,280
Speaker 1: cent trail?

173
00:09:28,920 --> 00:09:32,360
Speaker 4: I mean, my old boss had done it a couple

174
00:09:32,360 --> 00:09:36,000
Speaker 4: of miles and cock bears running a couple miles on them. Yeah,

175
00:09:36,200 --> 00:09:38,560
Speaker 4: and they're finding now with these GPS callers, that a

176
00:09:38,559 --> 00:09:42,480
Speaker 4: bear can smell a carcass ten to fifteen miles away,

177
00:09:42,520 --> 00:09:45,359
Speaker 4: and we'll just start blining it for a carcass.

178
00:09:45,600 --> 00:09:45,800
Speaker 1: Yeah.

179
00:09:45,800 --> 00:09:48,480
Speaker 6: I followed a grizzly bear track and the bob wants

180
00:09:48,600 --> 00:09:51,240
Speaker 6: nine miles to a I don't know how far he started,

181
00:09:51,280 --> 00:09:53,360
Speaker 6: but I followed the tracks for nine miles in front

182
00:09:53,400 --> 00:09:54,480
Speaker 6: of me to a moose carcass.

183
00:09:54,600 --> 00:09:57,720
Speaker 4: Yeah, that was impressive. Yeah, they got a pretty good sniffer.

184
00:09:57,880 --> 00:10:01,320
Speaker 1: Yeah. I've told the story to anyone that'll listen to it.

185
00:10:01,640 --> 00:10:05,600
Speaker 1: But we're one time camped up on the Arctic slope

186
00:10:05,800 --> 00:10:07,920
Speaker 1: and you know of the off the north slope of

187
00:10:07,960 --> 00:10:10,080
Speaker 1: the Brooks Range. Yeah, and we were camped where a

188
00:10:10,120 --> 00:10:13,280
Speaker 1: creek came into a bigger river. And one morning we

189
00:10:13,320 --> 00:10:16,600
Speaker 1: got up and walked three miles up that tributary and

190
00:10:16,679 --> 00:10:20,920
Speaker 1: killed caribou okay, spent the day up there, carried it

191
00:10:20,960 --> 00:10:23,480
Speaker 1: down that tributary to our camp. That night, we're sitting

192
00:10:23,480 --> 00:10:26,560
Speaker 1: in our camp and here comes a grizzly down the

193
00:10:26,600 --> 00:10:29,600
Speaker 1: gravel bar, digging roots. You see him move in, digging,

194
00:10:29,679 --> 00:10:33,000
Speaker 1: move and digging. He gets to the mouth of that tributary.

195
00:10:33,040 --> 00:10:35,160
Speaker 1: It's kind of like a slight little canyon. He gets

196
00:10:35,160 --> 00:10:37,240
Speaker 1: in the mouth of that tributary and stands up like

197
00:10:37,320 --> 00:10:41,200
Speaker 1: someone shocked him wow, waves his nose in the air,

198
00:10:41,240 --> 00:10:43,920
Speaker 1: and took off at a full run. So I don't

199
00:10:43,960 --> 00:10:47,240
Speaker 1: I can't tell you for sure, you know what I mean,

200
00:10:47,280 --> 00:10:49,640
Speaker 1: But it was like there was no discussing it. It was

201
00:10:49,679 --> 00:10:52,200
Speaker 1: like that sound of a bit smells that cariboo.

202
00:10:51,880 --> 00:10:53,880
Speaker 4: Yeah, I'm sure that's exactly what happened.

203
00:10:54,040 --> 00:10:56,319
Speaker 1: Yeah, coming down that coming down that creek, and that's

204
00:10:56,320 --> 00:10:57,880
Speaker 1: only three miles and you're talking about.

205
00:10:57,640 --> 00:11:01,320
Speaker 4: How far GPS colors are saying in ten to fifteen.

206
00:11:01,160 --> 00:11:02,960
Speaker 1: What do you what do you see on a GPS

207
00:11:03,040 --> 00:11:05,600
Speaker 1: collar that suggests to you that a grizzly is onto something?

208
00:11:05,840 --> 00:11:07,959
Speaker 4: Oh, it's meandering and then all of a sudden it's

209
00:11:07,960 --> 00:11:08,800
Speaker 4: a straight line.

210
00:11:09,400 --> 00:11:09,679
Speaker 1: You know.

211
00:11:09,880 --> 00:11:14,199
Speaker 4: It's like, just like you're talking about, there wasn't any

212
00:11:15,160 --> 00:11:16,920
Speaker 4: second thoughts in that bear's mind.

213
00:11:16,800 --> 00:11:19,320
Speaker 1: Got it? And then he's just going there, he's going. Yeah,

214
00:11:20,040 --> 00:11:21,719
Speaker 1: there's a lot of there's a lot of bruh on

215
00:11:21,800 --> 00:11:23,720
Speaker 1: the news right now. There's always been a bear, there's

216
00:11:23,720 --> 00:11:28,520
Speaker 1: always been a very polarizing bear. Yeah, in the polarizing

217
00:11:28,559 --> 00:11:35,040
Speaker 1: bear in the Yellowstone National Park area. Yeah, goes by

218
00:11:35,080 --> 00:11:37,680
Speaker 1: the handle three nine nine, which I always like because

219
00:11:38,080 --> 00:11:39,520
Speaker 1: I like it when they you know, when they give

220
00:11:39,559 --> 00:11:41,840
Speaker 1: the animals like a name like pedals or something, then

221
00:11:41,880 --> 00:11:46,400
Speaker 1: you know it's trouble. So if it has its research number.

222
00:11:46,280 --> 00:11:47,840
Speaker 3: There's some clinical detachment there.

223
00:11:47,920 --> 00:11:51,920
Speaker 1: Yeah. A research number allows the citizens at large to

224
00:11:53,200 --> 00:11:56,559
Speaker 1: stay a little usually allows citizens at large to stay

225
00:11:56,559 --> 00:12:02,640
Speaker 1: a little chilled out aboutelebrity animals. But three nine nine

226
00:12:02,840 --> 00:12:06,520
Speaker 1: it was. It might as well have been named cookie, right.

227
00:12:06,559 --> 00:12:10,520
Speaker 1: It just got really famous. And the American public, particularly

228
00:12:10,600 --> 00:12:15,280
Speaker 1: those who are very unfamiliar with wildlife, will have this

229
00:12:15,440 --> 00:12:22,120
Speaker 1: view that they look at an individual animal and they

230
00:12:22,160 --> 00:12:27,160
Speaker 1: see it with like like crystalline clarity, that one, and

231
00:12:27,200 --> 00:12:30,400
Speaker 1: they cease to view it as in context of its

232
00:12:30,440 --> 00:12:33,920
Speaker 1: like species at large, meaning you could have eight hundred

233
00:12:33,920 --> 00:12:38,000
Speaker 1: grizzlies in the area and it's kind of whatever, but

234
00:12:38,240 --> 00:12:42,800
Speaker 1: that one, nothing better happened to, right, right, They're not

235
00:12:43,760 --> 00:12:45,599
Speaker 1: it's not like it. They don't have an awareness of

236
00:12:45,640 --> 00:12:48,920
Speaker 1: the population at large. They have an awareness of that one.

237
00:12:49,679 --> 00:12:52,640
Speaker 1: I'm not lecturing you. I'm just trying to update listeners. Yeah,

238
00:12:53,280 --> 00:12:56,119
Speaker 1: when making an analogy about it, I'll make the analogy

239
00:12:56,160 --> 00:13:01,120
Speaker 1: of that someone like a hunter, some one in the concert,

240
00:13:01,240 --> 00:13:05,320
Speaker 1: like someone in the wildlife hunter based wildlife conservation might

241
00:13:05,440 --> 00:13:12,240
Speaker 1: view habitat as an apple tree. And if this apple

242
00:13:12,280 --> 00:13:15,000
Speaker 1: tree is taken care of, it will continuously produce apples,

243
00:13:15,440 --> 00:13:18,240
Speaker 1: and the apples are someone expendable, some get eaten, some

244
00:13:18,400 --> 00:13:21,760
Speaker 1: dying rot take care of the tree in perpetuity, it'll

245
00:13:22,200 --> 00:13:31,079
Speaker 1: put apples out animal rights people and preservation minded preservationist

246
00:13:31,120 --> 00:13:34,720
Speaker 1: minded people aren't that interested in the apple tree. But

247
00:13:34,840 --> 00:13:39,040
Speaker 1: now and then there's an apple that really catches their eye. Yeah,

248
00:13:39,080 --> 00:13:43,080
Speaker 1: and they are very concerned about what happens to that apple.

249
00:13:43,880 --> 00:13:46,079
Speaker 4: Yeah, it's a good analogy.

250
00:13:46,320 --> 00:13:51,960
Speaker 1: I guess this bear became that apple. Yeah, bear three

251
00:13:52,080 --> 00:13:52,560
Speaker 1: nine nine.

252
00:13:52,640 --> 00:13:57,240
Speaker 3: It's usually an apple that photographs well and it's pretty dependable.

253
00:13:58,080 --> 00:14:00,400
Speaker 3: It's an apple that shows up again and again.

254
00:14:01,120 --> 00:14:03,800
Speaker 1: Yeah, you know, or it would be like a moose

255
00:14:04,120 --> 00:14:09,720
Speaker 1: that's piebald. So because moose, you know, generally, people aren't

256
00:14:09,760 --> 00:14:11,640
Speaker 1: able to distinguish one from the other. Then you get

257
00:14:11,640 --> 00:14:14,199
Speaker 1: a moose in some neighborhood that as a white splotch

258
00:14:14,240 --> 00:14:18,040
Speaker 1: on it, and then people are able to put individuality

259
00:14:18,080 --> 00:14:20,840
Speaker 1: to it. And then someone gets that moose and it

260
00:14:20,880 --> 00:14:26,440
Speaker 1: causes a whole shit show. Three ninety nine. The bear's

261
00:14:26,720 --> 00:14:28,560
Speaker 1: had books written about it. It just got hit by

262
00:14:28,560 --> 00:14:31,840
Speaker 1: a car. Yeah, And our little preamble chat I brought

263
00:14:31,920 --> 00:14:36,600
Speaker 1: up to you that it's that bear now is getting

264
00:14:36,640 --> 00:14:41,760
Speaker 1: its final it's being put to rest with much fanfare

265
00:14:41,800 --> 00:14:44,440
Speaker 1: and consternation. Yeah. I mentioned it to you, and you

266
00:14:44,480 --> 00:14:48,440
Speaker 1: had a comment about your view on on this particular bear.

267
00:14:48,520 --> 00:14:50,600
Speaker 1: You didn't deal with it professionally.

268
00:14:50,000 --> 00:14:52,760
Speaker 4: Correct, No, I know her type though.

269
00:14:52,960 --> 00:14:57,880
Speaker 1: Yeah, tell me about that bear. What that like? You

270
00:14:57,960 --> 00:14:59,240
Speaker 1: mentioned a thing about management.

271
00:14:59,560 --> 00:15:04,760
Speaker 4: Yeah, yeah, I think that's poor wildlife management. And we

272
00:15:04,840 --> 00:15:07,400
Speaker 4: learned this lesson early on with a bear named one

273
00:15:07,440 --> 00:15:09,760
Speaker 4: oh four. So before three ninety nine, there was a

274
00:15:09,760 --> 00:15:11,400
Speaker 4: bear named the number was.

275
00:15:11,400 --> 00:15:11,840
Speaker 1: One O four.

276
00:15:11,960 --> 00:15:14,520
Speaker 4: It was a celebrity bear, celebrity bear, another shiny apple,

277
00:15:15,000 --> 00:15:20,720
Speaker 4: if you will. And my predecessors tried to relocate that

278
00:15:20,800 --> 00:15:28,520
Speaker 4: bear mover she got so not trap shy, but trap savvy,

279
00:15:28,960 --> 00:15:33,080
Speaker 4: not savvy like she enjoyed traps. You could you could

280
00:15:33,160 --> 00:15:35,880
Speaker 4: drive down the road with the door open and she'd

281
00:15:35,920 --> 00:15:38,200
Speaker 4: come running down the road and jump in the trap

282
00:15:38,240 --> 00:15:39,120
Speaker 4: and you would catch her.

283
00:15:39,360 --> 00:15:41,560
Speaker 1: You know. She was that kind of freaking like I

284
00:15:41,600 --> 00:15:43,359
Speaker 1: was just associated it with food.

285
00:15:43,200 --> 00:15:46,200
Speaker 4: Yeah, because there was so many positive experiences jumping in

286
00:15:46,280 --> 00:15:46,920
Speaker 4: traps and.

287
00:15:47,040 --> 00:15:48,600
Speaker 1: You eat the whole damn deer and then some guy

288
00:15:48,640 --> 00:15:52,400
Speaker 1: that's yeat yeah exactly, and you walk back home. I

289
00:15:52,440 --> 00:15:53,480
Speaker 1: get it, I get it.

290
00:15:53,960 --> 00:15:58,960
Speaker 4: Yeah. So we just learned early on that those habituated

291
00:15:59,000 --> 00:16:02,560
Speaker 4: bears aren't successful. And she also got hit by a

292
00:16:02,600 --> 00:16:06,440
Speaker 4: vehicle one oh four and you know, I always thought

293
00:16:06,440 --> 00:16:08,440
Speaker 4: that was gonna happen to three ninety nine. It took

294
00:16:08,480 --> 00:16:10,040
Speaker 4: longer than I would have guessed.

295
00:16:10,200 --> 00:16:11,800
Speaker 1: You pictured to getting struck by a car.

296
00:16:12,040 --> 00:16:14,120
Speaker 4: Yeah, and one of her cubs got hit by a car,

297
00:16:15,640 --> 00:16:15,840
Speaker 4: you know.

298
00:16:15,960 --> 00:16:17,240
Speaker 2: And really.

299
00:16:19,040 --> 00:16:21,600
Speaker 4: The park Service could talk about more. They probably know

300
00:16:21,680 --> 00:16:25,120
Speaker 4: all the individual cubs that she had, but as far

301
00:16:25,160 --> 00:16:27,400
Speaker 4: as I'm aware, there's only one of her cubs that's

302
00:16:27,400 --> 00:16:31,840
Speaker 4: still alive in existing because they just get so habituated

303
00:16:31,880 --> 00:16:36,520
Speaker 4: to people, they don't learn normal bear manners is what

304
00:16:36,560 --> 00:16:40,160
Speaker 4: I call it. So, you know, one of her cubs

305
00:16:40,240 --> 00:16:43,400
Speaker 4: got shot by a guy who he was he was

306
00:16:43,480 --> 00:16:45,680
Speaker 4: hunting and he's in his camper and this bears walk

307
00:16:45,720 --> 00:16:48,720
Speaker 4: and ride at him like it's coming to eat him,

308
00:16:48,920 --> 00:16:51,080
Speaker 4: you know, but that bear's used to getting its picture

309
00:16:51,160 --> 00:16:55,200
Speaker 4: taken and that guy's scared for his life because he

310
00:16:55,240 --> 00:16:57,440
Speaker 4: thinks this bear is gonna hurt him.

311
00:16:57,560 --> 00:16:58,760
Speaker 1: And you don't think it was.

312
00:17:00,600 --> 00:17:02,680
Speaker 4: It was so used to people, it was smiling the

313
00:17:02,720 --> 00:17:05,080
Speaker 4: whole way it was coming in. I'm sure, you know.

314
00:17:07,160 --> 00:17:10,640
Speaker 4: So I just don't think it sets bears up for success.

315
00:17:10,720 --> 00:17:13,520
Speaker 4: And three ninety nine was really polarizing. I mean, some

316
00:17:13,560 --> 00:17:17,320
Speaker 4: people loved her. Some people hated her. I think people

317
00:17:17,359 --> 00:17:21,840
Speaker 4: forget that she mauled a guy years ago, so I

318
00:17:21,840 --> 00:17:23,200
Speaker 4: mean she was still a grizzly bear.

319
00:17:24,119 --> 00:17:26,720
Speaker 1: And what do you say people hated that bear? Do

320
00:17:26,760 --> 00:17:28,399
Speaker 1: you mean that they hated that bear because what it

321
00:17:28,400 --> 00:17:30,280
Speaker 1: Because it was a symbol for something.

322
00:17:30,160 --> 00:17:33,040
Speaker 4: I think. So I think I think people would make

323
00:17:33,119 --> 00:17:35,520
Speaker 4: comments that I would see and it would really ruffle

324
00:17:35,520 --> 00:17:38,480
Speaker 4: feathers where you know, if they would say things like

325
00:17:39,560 --> 00:17:42,360
Speaker 4: if they dealist grizzly bears and I can hunt, I'm

326
00:17:42,359 --> 00:17:48,920
Speaker 4: gonna shoot that bear, and that just that really affected

327
00:17:48,920 --> 00:17:49,800
Speaker 4: people negatively.

328
00:17:50,160 --> 00:17:56,239
Speaker 3: So well that Shane Shane who got scratched off by

329
00:17:56,240 --> 00:17:56,840
Speaker 3: the bear.

330
00:17:57,680 --> 00:18:01,679
Speaker 1: He said right in his chair, Yeah, and he had.

331
00:18:01,520 --> 00:18:03,560
Speaker 3: Good reason to believe that it was three ninety nine.

332
00:18:05,480 --> 00:18:07,640
Speaker 1: That's what he had said. Well they well, how would

333
00:18:07,600 --> 00:18:10,600
Speaker 1: they not know for certain, sorry that he was scratched

334
00:18:10,640 --> 00:18:11,560
Speaker 1: up by Yeah.

335
00:18:11,400 --> 00:18:13,240
Speaker 3: That's that was one of the things that he said.

336
00:18:13,359 --> 00:18:15,080
Speaker 4: And she was in the vicinity.

337
00:18:15,240 --> 00:18:18,040
Speaker 3: She was in the vicinity. But it was like if

338
00:18:18,119 --> 00:18:20,639
Speaker 3: three ninety nine was the one that did this to you,

339
00:18:20,720 --> 00:18:22,680
Speaker 3: we don't want to know about it. Was that kind

340
00:18:22,680 --> 00:18:27,399
Speaker 3: of a thing. So it's I mean, that was that

341
00:18:27,520 --> 00:18:29,080
Speaker 3: was one of the things that he mentioned sort of

342
00:18:29,080 --> 00:18:31,480
Speaker 3: off handedly, and he's like, if it was three ninety nine,

343
00:18:31,520 --> 00:18:34,199
Speaker 3: I don't think anybody would come out and declare to

344
00:18:34,240 --> 00:18:35,879
Speaker 3: the world that three ninety nine had done this and

345
00:18:35,960 --> 00:18:38,360
Speaker 3: needs to get destroyed, because it would just cause such

346
00:18:38,359 --> 00:18:40,720
Speaker 3: an uproar. So it was kind of like there were

347
00:18:42,040 --> 00:18:45,240
Speaker 3: there's like a buffer zone built around this bear to

348
00:18:45,320 --> 00:18:49,640
Speaker 3: protect it from the consequences of its bad behavior once

349
00:18:49,680 --> 00:18:52,399
Speaker 3: people get so attached to it. Yeah, I got you,

350
00:18:53,400 --> 00:18:55,640
Speaker 3: but he he post I think when three ninety nine

351
00:18:55,680 --> 00:18:58,800
Speaker 3: died too. He posted something again to the effect of

352
00:18:58,840 --> 00:19:00,960
Speaker 3: like there's a good chance that this was the bear

353
00:19:00,960 --> 00:19:01,359
Speaker 3: that did it.

354
00:19:02,280 --> 00:19:05,200
Speaker 1: Wow, let me ask you another one.

355
00:19:05,520 --> 00:19:07,560
Speaker 4: Yeah, that was that was a hard question. I'm sure

356
00:19:07,640 --> 00:19:11,320
Speaker 4: people are gonna cry over that. So three was just

357
00:19:12,000 --> 00:19:13,240
Speaker 4: touched a lot of heart strings.

358
00:19:13,400 --> 00:19:14,280
Speaker 1: Rip yep.

359
00:19:15,440 --> 00:19:19,080
Speaker 3: Three nine was never going to die, you know, in

360
00:19:19,160 --> 00:19:24,920
Speaker 3: a warm bed with a roaring fire, surrounded by loved ones, right, Like, yeah,

361
00:19:25,080 --> 00:19:27,919
Speaker 3: I was sick. That's the the craziest part is like,

362
00:19:27,960 --> 00:19:31,239
Speaker 3: getting whacked by cars not the worst way to go.

363
00:19:32,080 --> 00:19:34,480
Speaker 1: Wild Animal Cal went out, Cal did there's a col

364
00:19:34,560 --> 00:19:36,600
Speaker 1: in the field about this on YouTube type and Cal

365
00:19:36,640 --> 00:19:38,480
Speaker 1: in the Field grizzly Barry, you'll see this one. But

366
00:19:39,440 --> 00:19:41,560
Speaker 1: there's a col in the field where he goes out

367
00:19:41,560 --> 00:19:44,160
Speaker 1: with some Idaho guys and they work and they they

368
00:19:44,240 --> 00:19:47,399
Speaker 1: colvert trap a grizzly and work up the grizzly. So

369
00:19:47,480 --> 00:19:52,680
Speaker 1: they colvert trap a grizzly and it's got a lip tattoo,

370
00:19:54,520 --> 00:19:57,439
Speaker 1: so they like an identifying marker, right, they call in

371
00:19:57,480 --> 00:20:01,800
Speaker 1: the lip tattoo and and they're like, oh, we know

372
00:20:01,880 --> 00:20:08,280
Speaker 1: that bear. They had had a collared female grizzly in

373
00:20:08,320 --> 00:20:13,439
Speaker 1: the park. She found a carcass. She found a buffalo

374
00:20:13,560 --> 00:20:18,280
Speaker 1: carcass and was on it. And they get a mortality

375
00:20:18,320 --> 00:20:22,600
Speaker 1: signal and they go there and there's their sow with

376
00:20:22,720 --> 00:20:26,960
Speaker 1: the collar dead on top of the buffalo carcass, and

377
00:20:27,000 --> 00:20:29,199
Speaker 1: standing on top of the both of them is this

378
00:20:30,119 --> 00:20:34,439
Speaker 1: male bear. Yeah right, but man, you could explain that

379
00:20:34,560 --> 00:20:36,680
Speaker 1: kind of stuff all day long, like that the number

380
00:20:36,720 --> 00:20:39,600
Speaker 1: one cause of death of Yellowstone wolves as wolves. Like

381
00:20:39,680 --> 00:20:43,720
Speaker 1: you could explain that stuff all day long, but it

382
00:20:43,800 --> 00:20:48,879
Speaker 1: is never gonna It just doesn't resonate. You know. People

383
00:20:48,920 --> 00:20:53,000
Speaker 1: will look at certain causes of death, like if three

384
00:20:53,119 --> 00:20:55,159
Speaker 1: ninety nine had been killed by a male grizzly, I

385
00:20:55,200 --> 00:20:59,760
Speaker 1: don't think people would be upset, you know what I mean? Yeah, people,

386
00:21:00,440 --> 00:21:02,920
Speaker 1: it's it's that they're upset because it's human caused.

387
00:21:03,920 --> 00:21:07,399
Speaker 4: Yeah, people put different values on different animals, and and

388
00:21:07,440 --> 00:21:11,080
Speaker 4: they even yeah, even at the individual level, put values

389
00:21:11,080 --> 00:21:14,560
Speaker 4: on animals. And yeah, people just really valued that bear.

390
00:21:15,560 --> 00:21:19,840
Speaker 1: So let me hte you with another easier to answer one.

391
00:21:19,880 --> 00:21:22,840
Speaker 1: But you'll get this will make other people mad. Good,

392
00:21:25,160 --> 00:21:28,399
Speaker 1: Now you're gonna, Now you're gonna. We have we know,

393
00:21:28,560 --> 00:21:32,160
Speaker 1: we have a full spectrum of listeners. Sure, we got

394
00:21:32,240 --> 00:21:34,040
Speaker 1: we got the horseshoe, you got, we got, we got

395
00:21:35,400 --> 00:21:38,240
Speaker 1: left we got righty's lefties, and then we got where

396
00:21:38,280 --> 00:21:41,680
Speaker 1: the rights and the lefties meet, which is crazy redneck hippies.

397
00:21:41,960 --> 00:21:42,240
Speaker 4: Sure.

398
00:21:42,480 --> 00:21:44,680
Speaker 1: Yeah, So no matter what you say, your eyes and

399
00:21:44,800 --> 00:21:47,399
Speaker 1: get someone that's gonna get mad. And this will be

400
00:21:47,400 --> 00:21:50,960
Speaker 1: a thing where where the the the the right bottom

401
00:21:51,000 --> 00:21:53,560
Speaker 1: of the horseshoe get will get very irritated no matter

402
00:21:53,560 --> 00:21:58,120
Speaker 1: what you say, uh, bear spray or pistols like when

403
00:21:58,160 --> 00:22:00,840
Speaker 1: you're out. Yeah, no one, what you know, having dealt

404
00:22:00,840 --> 00:22:03,159
Speaker 1: with as many grizzlies as you we dealt with and

405
00:22:03,240 --> 00:22:05,760
Speaker 1: been to as many conflict sights as you've been to,

406
00:22:06,240 --> 00:22:08,080
Speaker 1: and touched as many of them as he touched to

407
00:22:08,720 --> 00:22:10,760
Speaker 1: and talked to as many people has been messed up

408
00:22:10,760 --> 00:22:14,640
Speaker 1: by grizzlies as you've talked to bear spray or pistol.

409
00:22:14,400 --> 00:22:18,159
Speaker 4: Without a doubt bear spray really, yeah, and.

410
00:22:18,240 --> 00:22:26,520
Speaker 1: Tell me more now I'm mad. You promise he's a

411
00:22:26,560 --> 00:22:30,240
Speaker 1: gun grabber. The other day Yanni was talking about them

412
00:22:30,280 --> 00:22:33,280
Speaker 1: needing to ban the Red Rider. I was like, now,

413
00:22:33,320 --> 00:22:36,160
Speaker 1: you're a gun grabber trying to take away people's Red Rider.

414
00:22:36,240 --> 00:22:36,679
Speaker 3: What was his?

415
00:22:36,840 --> 00:22:40,600
Speaker 1: Uh, he's got some cockamami theory that cheating a kid

416
00:22:40,640 --> 00:22:42,520
Speaker 1: to shoot on a Red Rider to get used to

417
00:22:42,560 --> 00:22:48,880
Speaker 1: a heavy trigger pull. My little kids, Yeah, my little

418
00:22:48,920 --> 00:22:50,840
Speaker 1: kids shooting Red Riders. I remember they used to shoo

419
00:22:50,880 --> 00:22:53,240
Speaker 1: him with two fingers because you cannot get that go off.

420
00:22:53,680 --> 00:22:54,919
Speaker 3: I thought it was going to be like he was

421
00:22:54,960 --> 00:22:56,320
Speaker 3: anti BB gun fights.

422
00:22:57,280 --> 00:22:59,800
Speaker 1: He's he thinks he thinks of Red Rider. He just

423
00:23:00,240 --> 00:23:03,720
Speaker 1: form And I think that's a very Unamerican statement. You

424
00:23:03,720 --> 00:23:07,160
Speaker 1: shoot your eye out Bear spray unequivocally.

425
00:23:08,160 --> 00:23:12,000
Speaker 4: Yeah. I have one caveat to that. If you're really

426
00:23:12,040 --> 00:23:16,680
Speaker 4: well experienced with with handguns, then by all means carry

427
00:23:16,680 --> 00:23:19,800
Speaker 4: a handgun. But a lot of people just aren't and

428
00:23:19,880 --> 00:23:25,879
Speaker 4: I investigated so many cases of self defense defensive life shootings,

429
00:23:25,920 --> 00:23:30,680
Speaker 4: and people are just really bad shots with pistols and

430
00:23:31,000 --> 00:23:32,640
Speaker 4: a lot of times they would even hit the bear,

431
00:23:33,000 --> 00:23:37,199
Speaker 4: but they don't hit it lethally. And bear spray. The

432
00:23:37,240 --> 00:23:39,600
Speaker 4: beauty of it is it makes a four foot cloud,

433
00:23:40,359 --> 00:23:41,760
Speaker 4: so you don't have to be accurate.

434
00:23:43,440 --> 00:23:45,080
Speaker 1: And how much do they hate that bear spray?

435
00:23:46,160 --> 00:23:47,480
Speaker 4: I've never seen it not work.

436
00:23:47,960 --> 00:23:50,440
Speaker 1: So do you know that? Red a statistic and I

437
00:23:50,440 --> 00:23:51,520
Speaker 1: didn't really spend a lot of time.

438
00:23:51,680 --> 00:23:53,600
Speaker 4: If you spray it on the ground, they'll come sniff

439
00:23:53,640 --> 00:23:56,040
Speaker 4: it though. It becomes an attractant.

440
00:23:55,760 --> 00:23:58,880
Speaker 1: Oh oh yeah, I got I'll tell you a good

441
00:23:58,920 --> 00:24:02,919
Speaker 1: one about that. But I read a statistic and I

442
00:24:02,960 --> 00:24:04,959
Speaker 1: never really spent much time on it, but it seemed

443
00:24:05,000 --> 00:24:09,040
Speaker 1: like it seemed significant that twenty five percent of the

444
00:24:09,080 --> 00:24:13,439
Speaker 1: time a pistol or sorry, twenty five percent of the

445
00:24:13,440 --> 00:24:16,680
Speaker 1: time when a firearm is discharged in a bear attack,

446
00:24:16,960 --> 00:24:17,919
Speaker 1: it hits a human.

447
00:24:18,720 --> 00:24:19,800
Speaker 4: Yeah, that's the other reason.

448
00:24:20,240 --> 00:24:20,840
Speaker 1: Have you heard that?

449
00:24:21,800 --> 00:24:24,360
Speaker 4: No, I haven't heard that statistic. That seems high. There's

450
00:24:24,400 --> 00:24:26,480
Speaker 4: a lot of not shoot not there.

451
00:24:26,720 --> 00:24:30,399
Speaker 1: But listen, man, like I know, yeah, I know a

452
00:24:30,440 --> 00:24:32,600
Speaker 1: bunch of cases where that's happened, and I haven't looked

453
00:24:32,640 --> 00:24:33,399
Speaker 1: into it. I just read it.

454
00:24:34,200 --> 00:24:37,960
Speaker 4: You know, there was a case on the Montana Idaho border.

455
00:24:38,000 --> 00:24:40,520
Speaker 4: It ended up being in Montana where the guy was

456
00:24:40,560 --> 00:24:43,640
Speaker 4: getting mauled and his buddy tried to shoot the bear

457
00:24:43,720 --> 00:24:45,160
Speaker 4: off him and actually killed his friend.

458
00:24:45,280 --> 00:24:49,840
Speaker 1: Yeah, they had shot that that bear. They were black

459
00:24:49,880 --> 00:24:53,000
Speaker 1: bear hunting. They mistook it for a black bear, so

460
00:24:53,040 --> 00:24:56,359
Speaker 1: they shot it and the bear runs into the into

461
00:24:56,400 --> 00:24:59,520
Speaker 1: the brush. He thinks he hit a black bear, so

462
00:24:59,560 --> 00:25:03,119
Speaker 1: he goes trailing in there after it and boom.

463
00:25:03,359 --> 00:25:05,359
Speaker 4: I just remember it was so close on the border,

464
00:25:05,440 --> 00:25:10,160
Speaker 4: they didn't know who had jurisdiction about it. So yeah,

465
00:25:10,200 --> 00:25:14,600
Speaker 4: so that's that's why I carry bear spray. And you know,

466
00:25:15,000 --> 00:25:17,600
Speaker 4: ultimately it's up to people. I know there's gun lovers

467
00:25:17,600 --> 00:25:19,800
Speaker 4: they want to carry guns and that's fine, but a

468
00:25:19,840 --> 00:25:22,280
Speaker 4: lot of people just don't practice shooting pistols enough.

469
00:25:22,480 --> 00:25:25,040
Speaker 1: Yeah. Yeah, I think it does say a lot about

470
00:25:25,080 --> 00:25:28,920
Speaker 1: your The choice might say more about your mind frame

471
00:25:29,040 --> 00:25:32,680
Speaker 1: than it does your like your strat your sense of strategy. Right.

472
00:25:33,160 --> 00:25:36,520
Speaker 3: I remember being like up at Sportsman's Warehouse and Anchorage

473
00:25:36,840 --> 00:25:39,840
Speaker 3: and seeing people that just got off a plane and

474
00:25:40,359 --> 00:25:44,600
Speaker 3: they're going to buy a pistol for their Alaska vacation

475
00:25:45,359 --> 00:25:47,560
Speaker 3: and then you know, pawn it off or whatever at

476
00:25:47,560 --> 00:25:50,760
Speaker 3: the end of the vacation. Like, I think there's like

477
00:25:50,800 --> 00:25:54,600
Speaker 3: a there's an assumption that if you, if you believe

478
00:25:54,680 --> 00:25:57,199
Speaker 3: in the handgun, like you just go get when you

479
00:25:57,240 --> 00:25:59,920
Speaker 3: get a box ammo, and you keep it near you,

480
00:26:00,800 --> 00:26:03,639
Speaker 3: and like that's just a recipe for disaster. But I

481
00:26:03,640 --> 00:26:07,760
Speaker 3: think there's a lot of overconfident and I'm i myself,

482
00:26:07,800 --> 00:26:09,920
Speaker 3: I have no confidence in my handgun shooting ability, and

483
00:26:09,960 --> 00:26:11,240
Speaker 3: I shoot one pretty regularly.

484
00:26:11,320 --> 00:26:13,920
Speaker 1: But I'll tell you, my little my I'll walk you

485
00:26:14,000 --> 00:26:18,720
Speaker 1: through my irrational thoughts on it. If there's slight risk

486
00:26:19,000 --> 00:26:22,159
Speaker 1: of First off, I I condemn and yell at and

487
00:26:22,200 --> 00:26:24,880
Speaker 1: harrass and tease anyone that carries bear spray where there's

488
00:26:24,920 --> 00:26:29,000
Speaker 1: no grizzlies, indefensible it works on lions.

489
00:26:29,080 --> 00:26:35,280
Speaker 7: What if it's just on your by hardness teas worthy

490
00:26:35,320 --> 00:26:35,760
Speaker 7: in her as.

491
00:26:36,160 --> 00:26:39,080
Speaker 1: Bear spray is not nice to get shot with, and

492
00:26:39,119 --> 00:26:41,520
Speaker 1: they and it like they go off. I've been in

493
00:26:41,520 --> 00:26:45,800
Speaker 1: two I've been never mauled by a bear, been charged

494
00:26:45,800 --> 00:26:47,959
Speaker 1: by them, but never mauled. But twice I've been hosed

495
00:26:47,960 --> 00:26:48,960
Speaker 1: by people's bear spray.

496
00:26:50,640 --> 00:26:52,440
Speaker 4: Mine doesn't come off that.

497
00:26:53,160 --> 00:27:00,000
Speaker 1: They trust it every two years, Yes, trust me, it's

498
00:27:00,080 --> 00:27:03,600
Speaker 1: like it happens. Those are not those The plastic nozzles

499
00:27:03,640 --> 00:27:08,560
Speaker 1: on those cans are not invulnerable. One time, on just

500
00:27:08,600 --> 00:27:11,520
Speaker 1: standing around a car unloading backpacks, someone stepped on the

501
00:27:11,520 --> 00:27:17,119
Speaker 1: plastic nozzle everything. And one time I got pickpocketed in

502
00:27:17,119 --> 00:27:19,400
Speaker 1: the thick in the like a willow choked hell hole.

503
00:27:20,080 --> 00:27:21,760
Speaker 1: And also I was like, what is that noise going?

504
00:27:25,119 --> 00:27:28,160
Speaker 1: All your ship's done, all your gear is gone, You

505
00:27:28,200 --> 00:27:29,160
Speaker 1: cannot get it out.

506
00:27:29,600 --> 00:27:29,800
Speaker 5: Wait?

507
00:27:29,920 --> 00:27:31,800
Speaker 7: Is it bad to keep your bear spray.

508
00:27:32,160 --> 00:27:32,680
Speaker 1: In your car?

509
00:27:33,280 --> 00:27:33,639
Speaker 3: Yeah?

510
00:27:34,160 --> 00:27:37,280
Speaker 7: Keep itature It'll total your car.

511
00:27:38,320 --> 00:27:40,680
Speaker 1: Know, I know people whose car has been told your car.

512
00:27:40,840 --> 00:27:43,200
Speaker 1: When that goes off your car, it will total your car.

513
00:27:44,040 --> 00:27:46,480
Speaker 4: Temperatures are dropping. I had a friend who did that

514
00:27:46,560 --> 00:27:52,000
Speaker 4: and he's still driving his vehicle giving yeah all the time.

515
00:27:52,240 --> 00:27:54,359
Speaker 1: Put get a small amimal can. There's one right outside

516
00:27:54,359 --> 00:27:56,520
Speaker 1: the door of the of the studio. Get a small

517
00:27:56,560 --> 00:27:59,720
Speaker 1: animal can and put it in the ammal can. And

518
00:27:59,720 --> 00:28:01,840
Speaker 1: then when you're using it, Carrie, when you're done using it,

519
00:28:01,840 --> 00:28:04,080
Speaker 1: put in an animal can. I was gonna I'm gonna tell

520
00:28:04,080 --> 00:28:06,640
Speaker 1: you my irrational logic. Let me tell my funny story. Yeah,

521
00:28:07,160 --> 00:28:10,680
Speaker 1: we had the Ranella family. We had we went into

522
00:28:10,680 --> 00:28:13,399
Speaker 1: the summer with two bear sprays, and we have like

523
00:28:13,400 --> 00:28:16,280
Speaker 1: a little camping spot where there's grizzlies. So when we

524
00:28:16,320 --> 00:28:18,119
Speaker 1: get there, before I get a sense of what's going on,

525
00:28:18,200 --> 00:28:20,000
Speaker 1: I'll like tell my kids, like, take the spray if

526
00:28:20,000 --> 00:28:21,760
Speaker 1: you're gonna go fish, or take the spray and bring

527
00:28:21,800 --> 00:28:25,000
Speaker 1: the dog. And then once we kind of get a

528
00:28:25,040 --> 00:28:27,520
Speaker 1: sense of what's up, everybody relaxes about it. But at

529
00:28:27,560 --> 00:28:30,159
Speaker 1: first it's thick, you know, at first I'll take the

530
00:28:30,160 --> 00:28:32,679
Speaker 1: bear spray. So the end of the summer we only have.

531
00:28:32,880 --> 00:28:36,000
Speaker 1: Now there's one bear spray, and of course no one

532
00:28:36,040 --> 00:28:37,879
Speaker 1: knows what happened to the other bear spray. Well, me

533
00:28:37,920 --> 00:28:40,840
Speaker 1: and my wife are up shutting our little camping area down.

534
00:28:41,600 --> 00:28:47,120
Speaker 1: And here right outside of our little composting outhouse toilet, Yeah,

535
00:28:47,200 --> 00:28:50,880
Speaker 1: right outside the door is the can of bear spray,

536
00:28:51,480 --> 00:28:56,239
Speaker 1: empty with four holes in it. It got at by

537
00:28:56,240 --> 00:28:56,520
Speaker 1: a bear.

538
00:28:56,760 --> 00:28:59,520
Speaker 4: Got yep, got eaten by a bear. Seen that before?

539
00:28:59,680 --> 00:29:04,080
Speaker 1: Yeah, Uh, here's my irrational logic. Okay, slight risk of grizzlies,

540
00:29:04,120 --> 00:29:07,800
Speaker 1: I use spray. High risk of grizzlies. I bring my

541
00:29:07,880 --> 00:29:12,400
Speaker 1: ten milimeters pistol ultra high risk of grizzlies. I bring

542
00:29:12,440 --> 00:29:15,040
Speaker 1: my sawd off pump twelve gage with slugs in it.

543
00:29:15,800 --> 00:29:20,200
Speaker 4: Yeah, I've found this spray and pray.

544
00:29:22,520 --> 00:29:24,200
Speaker 1: And I always look at it, and I always look

545
00:29:24,200 --> 00:29:26,160
Speaker 1: at all three of them. I'm like, hey, man, like,

546
00:29:26,200 --> 00:29:27,080
Speaker 1: what are you thinking here?

547
00:29:28,400 --> 00:29:33,920
Speaker 4: That's a that's a myth I can dispel too. Is people, Uh,

548
00:29:34,040 --> 00:29:37,680
Speaker 4: people take shotguns and they alternate buckshot and slugs.

549
00:29:37,800 --> 00:29:39,400
Speaker 1: Oh yeah, because you know, I know that. No, I

550
00:29:39,400 --> 00:29:41,440
Speaker 1: think it's supposed to. Brody told me you're supposed to

551
00:29:41,480 --> 00:29:46,600
Speaker 1: run two bird shots. Yeah. Then you start going. Then

552
00:29:46,640 --> 00:29:50,120
Speaker 1: you start going slug but shots, because it's like you

553
00:29:50,200 --> 00:29:54,320
Speaker 1: warn it, boom, you warn it boom. Then like it's

554
00:29:54,360 --> 00:29:57,640
Speaker 1: getting closer. Now you hit it with the slug boom.

555
00:29:58,040 --> 00:30:00,840
Speaker 1: Then it's so close and everything's so chaotic. Then you

556
00:30:00,840 --> 00:30:01,880
Speaker 1: start going buckshot.

557
00:30:02,280 --> 00:30:05,680
Speaker 3: And most bears are aware of this choreography, this elaborate

558
00:30:05,760 --> 00:30:07,120
Speaker 3: choreography before.

559
00:30:06,880 --> 00:30:10,480
Speaker 6: They Yeah, all the time, there's.

560
00:30:09,600 --> 00:30:10,320
Speaker 3: The warning shot.

561
00:30:10,400 --> 00:30:11,360
Speaker 4: Yeah, there's warning.

562
00:30:12,280 --> 00:30:14,080
Speaker 1: He tells his bite. Listen when you're coming in, he's

563
00:30:14,080 --> 00:30:16,400
Speaker 1: gonna hit you two bird shots. Yeah, then you got

564
00:30:16,400 --> 00:30:18,480
Speaker 1: to dodge the slug. Watch out for the buckshot.

565
00:30:18,600 --> 00:30:21,320
Speaker 4: Yeah, a zig and then a zag.

566
00:30:22,000 --> 00:30:24,360
Speaker 6: Here's my scenario that I find myself in all the time.

567
00:30:24,520 --> 00:30:26,880
Speaker 6: As most hunters, we don't get to pick our weather,

568
00:30:27,000 --> 00:30:28,720
Speaker 6: but we do get to pick which direction.

569
00:30:28,480 --> 00:30:29,600
Speaker 1: We walk when we're out hunting.

570
00:30:29,640 --> 00:30:31,280
Speaker 6: And most of the time the winds in my face,

571
00:30:32,240 --> 00:30:35,400
Speaker 6: and a lot of times the winds honking. I don't

572
00:30:35,400 --> 00:30:36,920
Speaker 6: trust bear spray when the wind's blowing.

573
00:30:37,880 --> 00:30:41,320
Speaker 4: Okay, So I've had that question a bunch over the years.

574
00:30:41,360 --> 00:30:44,000
Speaker 4: And I had a really good friend who was horn

575
00:30:44,080 --> 00:30:48,120
Speaker 4: hunting in the spring. It was super windy out. A

576
00:30:48,240 --> 00:30:53,200
Speaker 4: sow with cubs, real little cubs, charges him, and you know,

577
00:30:53,280 --> 00:30:56,080
Speaker 4: the winds in his face. He spray's bear spray. Half

578
00:30:56,120 --> 00:30:57,920
Speaker 4: of it goes in her face, half of it gets

579
00:30:57,960 --> 00:31:03,360
Speaker 4: in his face. They both ran off trying so it. Yeah,

580
00:31:03,440 --> 00:31:05,880
Speaker 4: the propellant still gets out there, but not as far

581
00:31:05,880 --> 00:31:06,880
Speaker 4: as it normally would.

582
00:31:07,000 --> 00:31:09,320
Speaker 6: I'd love to practice in the wind, but I don't.

583
00:31:09,160 --> 00:31:12,120
Speaker 1: Want to get a case of those inert cans.

584
00:31:12,360 --> 00:31:13,720
Speaker 3: Yeah, I think that'd be interesting.

585
00:31:15,120 --> 00:31:16,840
Speaker 1: I should get a case of those inert cans. I

586
00:31:17,000 --> 00:31:19,960
Speaker 1: just like shoot each other around, like laser tag around.

587
00:31:20,360 --> 00:31:21,000
Speaker 1: That would be fun.

588
00:31:21,160 --> 00:31:25,400
Speaker 3: I tried to shoot a sow and cubs with a

589
00:31:25,440 --> 00:31:28,080
Speaker 3: can of bear spray out of a window.

590
00:31:28,880 --> 00:31:29,840
Speaker 1: And the when I was.

591
00:31:29,840 --> 00:31:34,520
Speaker 3: Working Yellowstone, they were coming in and tearing up our cat.

592
00:31:34,560 --> 00:31:36,080
Speaker 3: When I was working up in Alaska, they'd come in

593
00:31:36,120 --> 00:31:38,400
Speaker 3: and tear up stuff on the portrait and trying to

594
00:31:38,400 --> 00:31:40,480
Speaker 3: give a bad and like they would come in, they'd

595
00:31:40,520 --> 00:31:42,320
Speaker 3: get into the fish shack to get into the tool

596
00:31:42,360 --> 00:31:44,400
Speaker 3: shed that eat rubber boots that do all this stuff.

597
00:31:44,440 --> 00:31:46,120
Speaker 3: And like so I was, I stayed in the main

598
00:31:46,160 --> 00:31:49,400
Speaker 3: lodge that they kept coming into and open the window

599
00:31:50,600 --> 00:31:52,920
Speaker 3: and they were walking past, and I sprayed, and it

600
00:31:53,000 --> 00:31:56,400
Speaker 3: might have been just outside of the range, but all

601
00:31:56,400 --> 00:32:00,040
Speaker 3: that bear spray went along the building and they like

602
00:32:00,120 --> 00:32:04,120
Speaker 3: went ten feet back and stood up and then kind

603
00:32:04,120 --> 00:32:05,719
Speaker 3: of circled around and came right back in.

604
00:32:07,160 --> 00:32:11,640
Speaker 1: Killed you shut the window real quick. And then actually

605
00:32:11,640 --> 00:32:13,360
Speaker 1: we sat around. I was with this kid.

606
00:32:13,440 --> 00:32:16,400
Speaker 3: We just like we were sitting in the cabin like

607
00:32:16,520 --> 00:32:18,760
Speaker 3: later on, like forty five minutes later, and we were

608
00:32:18,800 --> 00:32:21,120
Speaker 3: both kind of like does it smell weird? And then

609
00:32:21,120 --> 00:32:24,479
Speaker 3: we started getting like you know, like licking your cheeks

610
00:32:24,560 --> 00:32:27,120
Speaker 3: and like your lips and stuff, and and we'd gotten

611
00:32:27,160 --> 00:32:29,840
Speaker 3: like a trace amount inside and it had been swirling

612
00:32:29,880 --> 00:32:31,640
Speaker 3: and swirling, and we spent like the rest of the

613
00:32:31,720 --> 00:32:34,800
Speaker 3: night just like kind of licking our lips and rubbing

614
00:32:34,800 --> 00:32:38,720
Speaker 3: our noses and stuff. Yeah, that was my one experience

615
00:32:38,760 --> 00:32:40,239
Speaker 3: actually discharging.

616
00:32:39,720 --> 00:32:42,280
Speaker 4: A can can't tell you a story.

617
00:32:42,440 --> 00:32:46,080
Speaker 1: Yep, please sory here. I'm jealousy. I was. I was

618
00:32:46,600 --> 00:32:50,160
Speaker 1: impressed that Randall got to shoot at one with a spray,

619
00:32:50,200 --> 00:32:51,960
Speaker 1: But go on to have video of it somewhere.

620
00:32:52,080 --> 00:32:54,640
Speaker 4: I actually never did get at a spray a bear

621
00:32:54,680 --> 00:32:58,800
Speaker 4: with one. But I was deer hunting one fall and

622
00:32:59,560 --> 00:33:02,200
Speaker 4: I was going in some really heavy dark timber and

623
00:33:02,240 --> 00:33:05,120
Speaker 4: my dad always taught me to load around in my gun.

624
00:33:05,840 --> 00:33:08,920
Speaker 4: So I'm going through the timber and I walk under

625
00:33:08,960 --> 00:33:12,160
Speaker 4: this tree and there's a magpie sitting in the tree

626
00:33:12,560 --> 00:33:14,880
Speaker 4: and he's just staring at me. He's just looking right

627
00:33:14,920 --> 00:33:16,880
Speaker 4: down at me, and I'm looking up at him, and

628
00:33:16,920 --> 00:33:20,040
Speaker 4: I'm thinking, boy, that's weird that magpie.

629
00:33:20,360 --> 00:33:21,280
Speaker 1: Why is he hanging out?

630
00:33:21,360 --> 00:33:23,160
Speaker 4: Yeah? Why is he hang out? Or just staring at

631
00:33:23,160 --> 00:33:26,560
Speaker 4: each other? And I go another i don't know, thirty

632
00:33:26,640 --> 00:33:30,640
Speaker 4: yards and I hear something and I turn around and

633
00:33:30,680 --> 00:33:34,320
Speaker 4: there's this bore coming down the hill at me. He's

634
00:33:34,680 --> 00:33:35,600
Speaker 4: coming right at me and.

635
00:33:35,560 --> 00:33:36,360
Speaker 1: How many yards way?

636
00:33:37,280 --> 00:33:40,840
Speaker 4: Maybe twenty? Guy, I mean, he's coming for me. And

637
00:33:41,520 --> 00:33:45,160
Speaker 4: I was thinking myself, I got one shot with this rifle,

638
00:33:45,520 --> 00:33:48,200
Speaker 4: you know, I got one chance to kill this thing,

639
00:33:48,320 --> 00:33:50,880
Speaker 4: and it's going to be on top of me. And

640
00:33:51,120 --> 00:33:53,280
Speaker 4: I realized what my dad was trying to teach me

641
00:33:53,440 --> 00:33:56,040
Speaker 4: was just to be prepared, you know, And I would

642
00:33:56,040 --> 00:33:58,400
Speaker 4: have been way better off with a can of bear

643
00:33:58,480 --> 00:34:01,560
Speaker 4: spray in my hand, just walking through the woods and

644
00:34:01,920 --> 00:34:04,120
Speaker 4: as a guide. I do that sometimes, you know, if

645
00:34:04,120 --> 00:34:06,120
Speaker 4: it's real tight quarters, I don't have a problem walking

646
00:34:06,120 --> 00:34:09,120
Speaker 4: around with the cann of bear spray. Even if you

647
00:34:09,200 --> 00:34:12,040
Speaker 4: spray yourself, you're gonna live to talk about it.

648
00:34:12,160 --> 00:34:13,280
Speaker 1: So what happened?

649
00:34:14,040 --> 00:34:18,040
Speaker 4: He Yeah, I sprayed him and he didn't care.

650
00:34:19,239 --> 00:34:20,719
Speaker 3: Yeah.

651
00:34:20,800 --> 00:34:22,799
Speaker 4: I started yelling at him and he was coming down

652
00:34:22,800 --> 00:34:24,279
Speaker 4: the hill at me, and he just kind of did

653
00:34:24,280 --> 00:34:27,880
Speaker 4: a quarter pass, which is like a classic bear move,

654
00:34:28,000 --> 00:34:31,960
Speaker 4: you know. It was it was a bluff, but I

655
00:34:32,000 --> 00:34:35,040
Speaker 4: thought it was the real deal. And I just remember thinking, like,

656
00:34:35,120 --> 00:34:37,719
Speaker 4: I gotta wait until this thing is right on top

657
00:34:37,760 --> 00:34:40,040
Speaker 4: of me before I shoot, because I only got one chance.

658
00:34:41,200 --> 00:34:43,759
Speaker 1: So what is after all those bears you worked up,

659
00:34:46,680 --> 00:34:48,920
Speaker 1: what is a big bear in the rockies.

660
00:34:49,920 --> 00:34:52,600
Speaker 4: A big bear is five hundred pounds. The biggest bear

661
00:34:52,600 --> 00:34:56,040
Speaker 4: ever caught was six twenty four in the spring, would

662
00:34:56,080 --> 00:34:58,760
Speaker 4: have been a true seven hundred pound bear in the fall.

663
00:35:00,040 --> 00:35:00,839
Speaker 4: When people come.

664
00:35:00,760 --> 00:35:03,600
Speaker 1: Into big bear, that's a huge bear because every bear

665
00:35:03,719 --> 00:35:06,080
Speaker 1: is like I just cut.

666
00:35:05,920 --> 00:35:09,120
Speaker 4: People's number in half immediately, you know, whatever it is,

667
00:35:09,160 --> 00:35:09,960
Speaker 4: I cut it in half.

668
00:35:10,760 --> 00:35:12,960
Speaker 1: They tell you how big the bear was, Yeah, yep.

669
00:35:13,400 --> 00:35:16,120
Speaker 4: And you know, all those bears I worked up. The

670
00:35:16,160 --> 00:35:20,759
Speaker 4: sows are almost always right around three hundred pounds two

671
00:35:20,840 --> 00:35:25,000
Speaker 4: seventy five, three twenty five. They stop growing when they're

672
00:35:25,040 --> 00:35:27,960
Speaker 4: about seven to eight years old, where the males just

673
00:35:28,200 --> 00:35:32,120
Speaker 4: keep putting on weight, keep getting bigger. So a five

674
00:35:32,200 --> 00:35:34,480
Speaker 4: hundred pounds adult male is a huge bear in the

675
00:35:34,520 --> 00:35:35,520
Speaker 4: alstone ecosystem.

676
00:35:35,600 --> 00:35:38,120
Speaker 1: That's a huge bear. Yeah. And what's a more typical

677
00:35:38,200 --> 00:35:40,200
Speaker 1: male like, like, what is like a four or five

678
00:35:40,280 --> 00:35:43,040
Speaker 1: year old male two fifty?

679
00:35:43,600 --> 00:35:46,240
Speaker 4: You know, I don't know, three hundred.

680
00:35:46,440 --> 00:35:49,160
Speaker 1: God, they seem so much bigger, badder, Yeah, and they're bad,

681
00:35:49,200 --> 00:35:50,799
Speaker 1: but they seem so much bigger. Yeah.

682
00:35:50,800 --> 00:35:55,080
Speaker 4: And people overestimate wolves too, and really, you know, lions

683
00:35:55,120 --> 00:35:59,279
Speaker 4: are way bigger than wolves. But people because of the hair,

684
00:35:59,520 --> 00:36:04,640
Speaker 4: especially the fall bears, animolves, but bears especially they get

685
00:36:04,640 --> 00:36:07,680
Speaker 4: that that winner code on and people just think they're

686
00:36:07,719 --> 00:36:11,200
Speaker 4: way bigger than they are. You know, they're like, it's

687
00:36:11,200 --> 00:36:15,680
Speaker 4: a sow with a two full drown cubs, and it's like, no,

688
00:36:15,760 --> 00:36:18,319
Speaker 4: that thing weighs one hundred and fifty pounds, but it's

689
00:36:18,360 --> 00:36:20,920
Speaker 4: got so much hair it looks like as big as her.

690
00:36:21,160 --> 00:36:21,359
Speaker 1: Yeah.

691
00:36:22,520 --> 00:36:22,640
Speaker 5: Uh.

692
00:36:23,320 --> 00:36:28,120
Speaker 1: You were with the agency when the delisting looked like

693
00:36:28,120 --> 00:36:29,000
Speaker 1: it was going to go through.

694
00:36:29,880 --> 00:36:31,319
Speaker 4: Yeah, ok, it did go through.

695
00:36:33,440 --> 00:36:35,040
Speaker 1: Well, sorry, when it looked like they were no, well

696
00:36:35,080 --> 00:36:40,640
Speaker 1: it didn't an undid they were delisted yeah multiple times? Yeah, okay,

697
00:36:40,719 --> 00:36:43,400
Speaker 1: So help me with the timeline here, just to give

698
00:36:43,440 --> 00:36:50,200
Speaker 1: people rough sense what will happen is Well, first off,

699
00:36:50,200 --> 00:36:53,399
Speaker 1: I'm me saying this is not surprise. This is surprisingly

700
00:36:53,480 --> 00:37:01,800
Speaker 1: not a partisan like Democrat versus Republican issue generally grizzly bears. Well,

701
00:37:02,200 --> 00:37:03,800
Speaker 1: hear me out, because because I'm going to top of

702
00:37:03,800 --> 00:37:07,200
Speaker 1: all the dlistings. Okay, yeah, so you can, you can.

703
00:37:07,239 --> 00:37:09,320
Speaker 1: You can give that because there's definitely a tendency and

704
00:37:09,360 --> 00:37:11,960
Speaker 1: a tendency. But just I just think that people have

705
00:37:12,040 --> 00:37:15,920
Speaker 1: the opinion, they have their erroneous idea that somehow like

706
00:37:15,960 --> 00:37:19,800
Speaker 1: a governor or whatever can just declare right right that

707
00:37:20,200 --> 00:37:23,000
Speaker 1: something would happen right, that you would that that it's

708
00:37:23,120 --> 00:37:25,480
Speaker 1: that it's a simple that doing this is a simple process.

709
00:37:25,520 --> 00:37:28,759
Speaker 1: It just takes the right political figure to do it.

710
00:37:28,760 --> 00:37:30,359
Speaker 1: It's I'm going to explain how it's a little bit

711
00:37:30,400 --> 00:37:35,000
Speaker 1: more complicated in that right. In seventy four seventy nineteen

712
00:37:35,040 --> 00:37:37,720
Speaker 1: seventy four, nineteen seventy five, grizzly bears and the lower

713
00:37:37,800 --> 00:37:43,200
Speaker 1: forty eight were listed as an endangered They're listed as

714
00:37:43,200 --> 00:37:46,239
Speaker 1: a threatened species under the Endangered Species Act, so they're

715
00:37:46,280 --> 00:37:50,839
Speaker 1: given Federal and Endangered Species Act Species Act protection under

716
00:37:50,840 --> 00:37:55,480
Speaker 1: the EESA. And seventy four seventy five Richard Nixon, Dick Nixon.

717
00:37:57,560 --> 00:37:59,640
Speaker 4: Don't remember him, heard of.

718
00:38:01,520 --> 00:38:10,480
Speaker 1: Republican signed in the e s A signed Ina signed in.

719
00:38:12,640 --> 00:38:14,080
Speaker 1: Then he established the EPA.

720
00:38:14,680 --> 00:38:19,040
Speaker 3: That's that's the National Environmental Protection Act.

721
00:38:19,160 --> 00:38:21,319
Speaker 1: Oh, I'm sorry, I thought you were talking about the

722
00:38:21,640 --> 00:38:23,319
Speaker 1: native milk.

723
00:38:23,480 --> 00:38:23,560
Speaker 4: No.

724
00:38:23,640 --> 00:38:29,160
Speaker 1: Sorry, Oh yeah, Richard Nixon CRAS and Endangered Species Act.

725
00:38:29,200 --> 00:38:32,399
Speaker 1: And one of the first like marquee species to get

726
00:38:32,440 --> 00:38:35,080
Speaker 1: protection under that is grizzy bears and lower forty eight.

727
00:38:36,200 --> 00:38:41,160
Speaker 1: All kinds of years go by and wildlife managers kind

728
00:38:41,160 --> 00:38:44,000
Speaker 1: of look and say, well, the saying the lower forty

729
00:38:44,080 --> 00:38:46,560
Speaker 1: eight is not a great way of looking at this.

730
00:38:47,440 --> 00:38:51,560
Speaker 1: For instance, Golden Gate Park in San Francisco once upon

731
00:38:51,560 --> 00:38:54,560
Speaker 1: a time had grizzly bears, and I don't we don't

732
00:38:54,719 --> 00:38:58,279
Speaker 1: view that Golden Gate Park is going to recover that

733
00:38:58,360 --> 00:39:01,879
Speaker 1: San Francisco is going to recover it's grizzly bear population, right,

734
00:39:02,400 --> 00:39:08,360
Speaker 1: is never gonna work. So over time they establish they

735
00:39:08,440 --> 00:39:11,000
Speaker 1: take a look and they go like, where really could

736
00:39:11,000 --> 00:39:15,520
Speaker 1: we have grizzly bears? Like where is the right food resources,

737
00:39:16,120 --> 00:39:20,359
Speaker 1: low enough human population, proper habitat where you could feasibly

738
00:39:20,440 --> 00:39:23,040
Speaker 1: have a population of grizzly bears? And they come up

739
00:39:23,080 --> 00:39:28,040
Speaker 1: with six. One is in the Northern Casque what they

740
00:39:28,080 --> 00:39:31,360
Speaker 1: call the Northern Cascade ecosystem. So one is like basically

741
00:39:32,640 --> 00:39:35,279
Speaker 1: the Northern Cascades in Washington where you're kind of rolling

742
00:39:35,320 --> 00:39:35,759
Speaker 1: into BC.

743
00:39:36,680 --> 00:39:39,399
Speaker 4: Zero bears, sometimes one, sometimes one.

744
00:39:40,280 --> 00:39:42,880
Speaker 1: It depends on what side of the Yeah, it depends

745
00:39:42,920 --> 00:39:44,160
Speaker 1: on what side of the border.

746
00:39:44,520 --> 00:39:47,280
Speaker 3: If you're from Wyoming, it looks a lot like zero bears.

747
00:39:47,520 --> 00:39:51,760
Speaker 1: Yeah, yeah, so yeah, they if they have it bears

748
00:39:51,760 --> 00:39:57,360
Speaker 1: because one walked over there for a minute. Moving eastward,

749
00:39:57,719 --> 00:40:04,960
Speaker 1: you have the bitter Root cell Kirk cell Way none.

750
00:40:06,080 --> 00:40:09,120
Speaker 4: None, sell Kirks have bears, the bitter bitter Root does.

751
00:40:09,160 --> 00:40:11,920
Speaker 1: The Bitterot side. That's one. Oh, I forgot. They gave

752
00:40:11,960 --> 00:40:13,440
Speaker 1: a name to these things that already say the name

753
00:40:13,680 --> 00:40:17,879
Speaker 1: they call the distinct distinct population segments. So they say, okay,

754
00:40:17,920 --> 00:40:20,080
Speaker 1: we're gonna say that there's a grizzly bear population or

755
00:40:20,080 --> 00:40:23,080
Speaker 1: the possibility of a grizzy bear population in the Lower Cascades.

756
00:40:25,480 --> 00:40:29,200
Speaker 4: Uh, there's another one in Cabinet Yacks.

757
00:40:29,280 --> 00:40:33,880
Speaker 1: That's right, Cabinet Yack has bears. Bitter Root sell Kirk,

758
00:40:34,200 --> 00:40:37,760
Speaker 1: Bitter cell Way, Selway. Sorry, sell Kirks are in BC

759
00:40:38,280 --> 00:40:43,800
Speaker 1: Bitterroot cell Way, Northern Continental Divide, which is Bob Marshall

760
00:40:44,320 --> 00:40:49,560
Speaker 1: Glacier National Park, in some other areas up there, all

761
00:40:49,600 --> 00:40:54,319
Speaker 1: the way out to the front Range. Uh. Then the

762
00:40:54,360 --> 00:40:56,120
Speaker 1: g y E did I do them all? Am I

763
00:40:56,160 --> 00:40:56,680
Speaker 1: missing any?

764
00:40:57,160 --> 00:40:57,640
Speaker 3: I think that's it?

765
00:40:57,719 --> 00:41:02,000
Speaker 1: Okay Uh, And they go like, so let's stop talking

766
00:41:02,000 --> 00:41:05,040
Speaker 1: about the lower forty eight writ large and let's talk

767
00:41:05,080 --> 00:41:09,439
Speaker 1: about let's get real okay right and talk about where

768
00:41:09,440 --> 00:41:11,120
Speaker 1: could we actually have these bears. And then they looked

769
00:41:11,120 --> 00:41:13,319
Speaker 1: at like Okay, So instead of saying that we're going

770
00:41:13,360 --> 00:41:16,120
Speaker 1: to recover them across their range in the lower forty eight,

771
00:41:16,120 --> 00:41:22,680
Speaker 1: which basically was the one hundredth meridian westward New Mexico, Arizona,

772
00:41:23,480 --> 00:41:28,360
Speaker 1: Utah into northern Old Mexico coastal California. Right Like, let's

773
00:41:28,360 --> 00:41:31,040
Speaker 1: just look at this. And so they say, let's say

774
00:41:31,960 --> 00:41:36,200
Speaker 1: that we're going to try to recover and manage these

775
00:41:36,239 --> 00:41:39,040
Speaker 1: as distinct population segments. And they look and say, if

776
00:41:39,040 --> 00:41:42,400
Speaker 1: we're going to do that, there's two places, the Northern

777
00:41:42,440 --> 00:41:48,600
Speaker 1: Continial Divide ecosystem in the Greater Yellowstone ecosystem, which is

778
00:41:48,719 --> 00:41:51,600
Speaker 1: a chunk of ground about the size of Indiana. And

779
00:41:51,640 --> 00:41:54,879
Speaker 1: they're like, those are recovered. The rest of the Lower

780
00:41:54,920 --> 00:41:58,160
Speaker 1: forty eight not, but these areas I recovered, and so

781
00:41:58,560 --> 00:42:01,480
Speaker 1: let's move those out of the e Let's move those

782
00:42:01,520 --> 00:42:05,200
Speaker 1: out of endangered species at protection. The US Fish and

783
00:42:05,200 --> 00:42:08,960
Speaker 1: Wildlife Service has management has management authority. The US Fish

784
00:42:08,960 --> 00:42:11,480
Speaker 1: and Wildlife Service has to come forward and they do this.

785
00:42:12,840 --> 00:42:16,879
Speaker 1: The US This has happened with Democrats in the White House.

786
00:42:16,960 --> 00:42:18,600
Speaker 1: This has happened with the Republicans in the White House.

787
00:42:18,600 --> 00:42:21,360
Speaker 1: They'll come forward and say the US Fish and Wildlife

788
00:42:21,360 --> 00:42:28,480
Speaker 1: Service says, we propose that we propose that we delist

789
00:42:28,800 --> 00:42:33,919
Speaker 1: the grizzly. Then you have preservations like three ninety nine

790
00:42:33,920 --> 00:42:38,400
Speaker 1: type people. Preservations organizations will go like, well, Jesus, that

791
00:42:38,440 --> 00:42:41,080
Speaker 1: could mean that three ninety nine could get hunted. So

792
00:42:41,239 --> 00:42:46,920
Speaker 1: then they will sue in federal court to block the dlisting.

793
00:42:47,560 --> 00:42:50,120
Speaker 1: So they'll delist, and then there's a lawsuit and they'll

794
00:42:50,239 --> 00:42:53,560
Speaker 1: they'll never sue on basis they don't sue on how

795
00:42:53,600 --> 00:42:58,799
Speaker 1: many bears there are. They sue on uh, well, we

796
00:42:58,840 --> 00:43:03,520
Speaker 1: don't think the DPS thing was fair, Yeah, right, because

797
00:43:03,520 --> 00:43:06,239
Speaker 1: you can't treat them as distinct because because a bear

798
00:43:06,239 --> 00:43:08,160
Speaker 1: could move from one to the others. So we we're

799
00:43:08,200 --> 00:43:11,840
Speaker 1: going to attack the logic of the of the DPS.

800
00:43:12,120 --> 00:43:17,560
Speaker 1: Or you'll say, well, have you considered white bark pine

801
00:43:17,680 --> 00:43:21,920
Speaker 1: blister rust and how there's a fungus that's killing white

802
00:43:21,920 --> 00:43:24,160
Speaker 1: bark pines and grizzlies like the eat white bark pines,

803
00:43:24,360 --> 00:43:26,960
Speaker 1: and since we don't know what will really happen in

804
00:43:27,000 --> 00:43:29,880
Speaker 1: the long term to white bark pines, we're suing to

805
00:43:29,960 --> 00:43:34,240
Speaker 1: block the listing. Or well, what if cutthroat trout don't

806
00:43:34,280 --> 00:43:36,840
Speaker 1: do that? Well in the future, and ten percent of

807
00:43:36,920 --> 00:43:40,080
Speaker 1: bears might eat a cutthroat trout at some point in

808
00:43:40,080 --> 00:43:42,239
Speaker 1: their life. So we're going to sue to block the

809
00:43:42,320 --> 00:43:46,480
Speaker 1: delisting because we don't really know how well cutthroats are doing.

810
00:43:46,360 --> 00:43:50,000
Speaker 3: The risks because then the Fish and Wildlife Service is

811
00:43:50,080 --> 00:43:55,280
Speaker 3: required as part of that review process to consider all factors,

812
00:43:55,920 --> 00:43:59,440
Speaker 3: and they kind of have an impossible job, right, I mean,

813
00:43:59,480 --> 00:44:03,320
Speaker 3: like there's they basically are saying, we did a comprehensive review,

814
00:44:03,360 --> 00:44:07,400
Speaker 3: our conclusions are x, Y, and Z, and the litigators

815
00:44:07,400 --> 00:44:11,080
Speaker 3: are saying, it's not that comprehensive. You missed this, you

816
00:44:11,120 --> 00:44:13,200
Speaker 3: miss that, And they're kind of poking holes in the

817
00:44:13,239 --> 00:44:13,960
Speaker 3: bigger picture.

818
00:44:14,040 --> 00:44:16,400
Speaker 1: Yeah, and it will be It will come from anti

819
00:44:16,520 --> 00:44:22,000
Speaker 1: hunting organizations like the Center for Biological Diversity, Humane Society,

820
00:44:22,120 --> 00:44:26,440
Speaker 1: United States, Greater y Elson Coalition. Who else is a common

821
00:44:26,440 --> 00:44:34,000
Speaker 1: player here? Center H And they'll they'll do these delistings

822
00:44:34,920 --> 00:44:37,000
Speaker 1: or they'll they'll sue to block the delistings.

823
00:44:37,080 --> 00:44:40,160
Speaker 4: Last one was the crow the Crow tribe tribe.

824
00:44:41,200 --> 00:44:43,840
Speaker 1: What was the argument there, Uh.

825
00:44:44,840 --> 00:44:46,080
Speaker 4: That we shouldn't be delisting.

826
00:44:46,640 --> 00:44:51,239
Speaker 1: You know that's interesting. That was a long That was

827
00:44:51,239 --> 00:44:54,440
Speaker 1: a long preamble to my question yeah, you were around

828
00:44:54,520 --> 00:44:57,640
Speaker 1: for all this, yes, now, both of them. Okay, what

829
00:44:57,760 --> 00:45:01,640
Speaker 1: I remember being really interesting about this is the three

830
00:45:01,920 --> 00:45:05,520
Speaker 1: the three states that have chunks of ground and what

831
00:45:05,520 --> 00:45:08,520
Speaker 1: we call the Greater Yellstone Ecosystem, a name that I

832
00:45:08,560 --> 00:45:10,959
Speaker 1: resent because it call they should call it the Greater

833
00:45:11,040 --> 00:45:12,000
Speaker 1: Cody ecosystem.

834
00:45:12,160 --> 00:45:13,360
Speaker 4: They should call Wyoming bears.

835
00:45:13,440 --> 00:45:15,440
Speaker 1: Yeah, they should call it the Greater Cody ecosystem.

836
00:45:15,480 --> 00:45:16,440
Speaker 4: Most simmar in Wyoming.

837
00:45:16,520 --> 00:45:20,600
Speaker 1: Yeah, the Wyoming ecosystem. Yeah, there's three states. The bulk

838
00:45:20,600 --> 00:45:22,759
Speaker 1: of it's in Wyholming. But the three states take an

839
00:45:22,760 --> 00:45:25,520
Speaker 1: attitude where they're like, uh, okay, if d listing goes

840
00:45:25,560 --> 00:45:28,080
Speaker 1: through and we take what that means is the states

841
00:45:28,120 --> 00:45:31,560
Speaker 1: now manage it as a wild as wildlife under their jurisdiction.

842
00:45:32,719 --> 00:45:35,400
Speaker 1: Idaho says, this is twenty twenty.

843
00:45:35,560 --> 00:45:37,759
Speaker 4: Is this when it's happened last seventeen?

844
00:45:37,880 --> 00:45:38,080
Speaker 1: Yeah?

845
00:45:38,800 --> 00:45:39,200
Speaker 3: Earlier?

846
00:45:39,320 --> 00:45:43,759
Speaker 1: Yeah, Idaho says we're going to give out one grizzly tag.

847
00:45:44,000 --> 00:45:45,600
Speaker 4: Yeah.

848
00:45:45,960 --> 00:45:50,600
Speaker 1: Montana chicken shits out right and they say, not going

849
00:45:50,640 --> 00:45:52,840
Speaker 1: to play this game. We're not doing any grizzly tags.

850
00:45:52,880 --> 00:45:55,680
Speaker 4: Montana actually had to give part of their quota to

851
00:45:55,719 --> 00:45:58,399
Speaker 4: Idaho so the Ida Idaho could have one.

852
00:45:58,560 --> 00:46:02,759
Speaker 1: Oh is that right? Yeah, Wyoming just lays all on

853
00:46:02,840 --> 00:46:07,359
Speaker 1: the table. Yeah, and they're gonna give out twenty four tags, right. Yeah.

854
00:46:09,520 --> 00:46:13,160
Speaker 1: Guys like me who really want who really think that

855
00:46:13,160 --> 00:46:16,040
Speaker 1: the grizzies should be delisted, and I think that state

856
00:46:16,120 --> 00:46:20,239
Speaker 1: management and I'm very open and enthusiastic about a very

857
00:46:20,280 --> 00:46:23,480
Speaker 1: limited grizzly bear hunting season. Guys like me. As part

858
00:46:23,520 --> 00:46:27,319
Speaker 1: of our rhetoric, if we were being unscrupulous, we would

859
00:46:27,360 --> 00:46:30,160
Speaker 1: say that by opening up a hunting season, it'll reduce

860
00:46:30,320 --> 00:46:33,240
Speaker 1: conflict because bears will learn to be scared of people.

861
00:46:34,480 --> 00:46:35,560
Speaker 4: Not true.

862
00:46:36,880 --> 00:46:40,080
Speaker 1: That's why I stopped saying it, because it was intellectually dishonest. Yeah,

863
00:46:40,280 --> 00:46:42,960
Speaker 1: talk about that. I just spent like an hour setting

864
00:46:43,040 --> 00:46:45,960
Speaker 1: up the question. But give me your feelings on all

865
00:46:46,040 --> 00:46:49,320
Speaker 1: of this, all of this whole deal, all of this hunt,

866
00:46:49,400 --> 00:46:52,880
Speaker 1: don't hunt, the bears need to learn to be scared

867
00:46:52,920 --> 00:46:55,200
Speaker 1: and respect humans, and blah blah blah.

868
00:46:55,320 --> 00:46:57,440
Speaker 4: Yeah, I don't know where you can start. He opened

869
00:46:57,480 --> 00:47:01,200
Speaker 4: up so many holes there I beight shops.

870
00:47:03,440 --> 00:47:05,480
Speaker 6: Do you think grizzlies would be nervous of people if

871
00:47:05,480 --> 00:47:06,600
Speaker 6: we started hunting them again?

872
00:47:07,440 --> 00:47:09,760
Speaker 1: I got one?

873
00:47:10,040 --> 00:47:11,080
Speaker 4: If I got one?

874
00:47:11,200 --> 00:47:14,840
Speaker 1: Did you hear about bear four twenty two.

875
00:47:15,160 --> 00:47:18,040
Speaker 4: I mean maybe at some level. I don't know personally

876
00:47:18,120 --> 00:47:20,400
Speaker 4: because I haven't been there, but they talk about bears

877
00:47:20,400 --> 00:47:23,560
Speaker 4: on Kodiak Island being like really weary of human scent

878
00:47:24,400 --> 00:47:27,360
Speaker 4: because they're heavily hunted and always have been and always

879
00:47:27,400 --> 00:47:32,000
Speaker 4: have been, and same with Sweden. So maybe at some level,

880
00:47:32,120 --> 00:47:35,279
Speaker 4: But the reality is, you know, you have black bear

881
00:47:35,400 --> 00:47:39,799
Speaker 4: populations all over America that are hunted and there's still

882
00:47:39,800 --> 00:47:43,280
Speaker 4: black bear conflicts, so you're still gonna have conflicts with bears.

883
00:47:45,160 --> 00:47:48,600
Speaker 4: Bears do learn on experience with humans. If they have

884
00:47:48,640 --> 00:47:52,799
Speaker 4: a negative encounter, then they're more likely to run away

885
00:47:52,800 --> 00:47:55,799
Speaker 4: from a human. But I just don't think you'll hunt

886
00:47:55,800 --> 00:47:59,680
Speaker 4: them at a level that would be that would change

887
00:47:59,719 --> 00:48:00,400
Speaker 4: their being behavior.

888
00:48:00,840 --> 00:48:01,240
Speaker 1: Yeah.

889
00:48:01,480 --> 00:48:05,520
Speaker 4: So you know, they delisted in two thousand and seven,

890
00:48:06,600 --> 00:48:08,759
Speaker 4: and that delisting went from two thousand and seven to

891
00:48:08,800 --> 00:48:11,120
Speaker 4: two thousand and nine when a judge put him back

892
00:48:11,160 --> 00:48:11,720
Speaker 4: on the list.

893
00:48:11,920 --> 00:48:14,680
Speaker 1: Because it's always the same judge in Missoula.

894
00:48:14,760 --> 00:48:17,000
Speaker 4: Wow, this was a different judge. I was, Oh, yeah,

895
00:48:17,040 --> 00:48:20,359
Speaker 4: there was Molloy and then Dana Christiansen, and we knew

896
00:48:20,400 --> 00:48:23,000
Speaker 4: we were in trouble when when Dana Christiansen had said

897
00:48:23,480 --> 00:48:27,600
Speaker 4: My spirit animal is the wolverine. You know any judge with.

898
00:48:27,560 --> 00:48:29,480
Speaker 1: That, that's cultural appropriation anyways.

899
00:48:29,719 --> 00:48:32,160
Speaker 4: Yeah, I don't know any judge with a spirit animal.

900
00:48:32,239 --> 00:48:35,280
Speaker 1: Yeah, they should have gotten him. They should have attacked

901
00:48:35,360 --> 00:48:38,320
Speaker 1: him from the woke spectrum and said that that's cultural

902
00:48:38,320 --> 00:48:42,400
Speaker 1: appropriation and you should be fired. That was before wokens.

903
00:48:42,480 --> 00:48:47,560
Speaker 1: I believe man be freaking out. Man, I just don't coffee.

904
00:48:47,560 --> 00:48:48,200
Speaker 1: It just died.

905
00:48:48,680 --> 00:48:49,759
Speaker 4: Get some more coffee on that.

906
00:48:50,520 --> 00:48:55,760
Speaker 3: For anyone listening. Steve spilled a large cup of coffee

907
00:48:55,760 --> 00:48:59,399
Speaker 3: on his computer moments before we began recording Field.

908
00:48:59,400 --> 00:49:02,000
Speaker 1: Do you have the tech capabilities to plug that clip in?

909
00:49:03,120 --> 00:49:04,959
Speaker 1: Which clip? Well, because I was kind of talking about

910
00:49:05,080 --> 00:49:07,319
Speaker 1: I was talking to Oh, absolutely, yeah, we can do it.

911
00:49:08,239 --> 00:49:10,440
Speaker 1: Cut out me saying that bad stuff about that actor

912
00:49:10,480 --> 00:49:20,399
Speaker 1: though it doesn't really inspire. Oh shit, one of those

913
00:49:20,440 --> 00:49:27,319
Speaker 1: dudes that doesn't really inspire, like it, guys. I was

914
00:49:27,320 --> 00:49:30,040
Speaker 1: observing that there's an actor that's in a lot of movies,

915
00:49:30,040 --> 00:49:31,520
Speaker 1: but no one cares about him, and I don't want

916
00:49:31,600 --> 00:49:33,319
Speaker 1: that to get out. I feel like that's that's the

917
00:49:33,360 --> 00:49:36,200
Speaker 1: definition of a great character actor. No one cares about him,

918
00:49:36,239 --> 00:49:38,440
Speaker 1: but you're you're happy to see him right, Yeah, I

919
00:49:38,480 --> 00:49:38,839
Speaker 1: don't know.

920
00:49:39,000 --> 00:49:40,319
Speaker 3: He always brings it. Yeah.

921
00:49:41,000 --> 00:49:43,839
Speaker 1: Uh so so yeah, so back back to this and

922
00:49:43,840 --> 00:49:45,759
Speaker 1: and and pardon me for not know what I'm talking about.

923
00:49:45,760 --> 00:49:47,240
Speaker 1: I thought it was the same judge both times.

924
00:49:47,239 --> 00:49:50,240
Speaker 4: But anyways, No, you're right that they do go judge shopping.

925
00:49:50,480 --> 00:49:54,399
Speaker 4: That that's part of this whole thing. But yeah, two

926
00:49:54,400 --> 00:49:56,560
Speaker 4: thousand and seven, two thousand and nine, Wyoming didn't have

927
00:49:56,560 --> 00:49:59,800
Speaker 4: a hunting season even though the population was recovered. We

928
00:49:59,800 --> 00:50:03,600
Speaker 4: could to use hunting as management tool, and when they

929
00:50:03,640 --> 00:50:07,440
Speaker 4: got relisted, I think the state's opinion was, the next

930
00:50:07,480 --> 00:50:10,040
Speaker 4: time they get delisted, we're gonna hunt these things, and

931
00:50:10,080 --> 00:50:13,440
Speaker 4: we're it's not to control the population, it's to create

932
00:50:13,480 --> 00:50:15,960
Speaker 4: a social pattern of hunting.

933
00:50:16,480 --> 00:50:19,920
Speaker 1: That's what see, that's that's a good way of putting it. Yeah,

934
00:50:19,960 --> 00:50:22,919
Speaker 1: that's what I want the states to do it because

935
00:50:22,920 --> 00:50:26,600
Speaker 1: I want them to quickly exercise the management authority.

936
00:50:26,320 --> 00:50:31,399
Speaker 4: And Montana checking out chickening out was a bad move

937
00:50:31,400 --> 00:50:34,160
Speaker 4: in my opinion, because you're setting a precedent that that

938
00:50:34,239 --> 00:50:35,120
Speaker 4: you're not hunting them.

939
00:50:35,200 --> 00:50:37,120
Speaker 1: Yeah, and I remember they were going to chicken out

940
00:50:37,120 --> 00:50:38,640
Speaker 1: for five years or something like that.

941
00:50:39,000 --> 00:50:42,040
Speaker 4: Yeah, I think that's true this time around too. They've

942
00:50:42,040 --> 00:50:45,160
Speaker 4: said that recently in recent history.

943
00:50:45,320 --> 00:50:47,959
Speaker 1: Yeah, I don't know that they would make that choice now,

944
00:50:48,719 --> 00:50:50,520
Speaker 1: but at the time they were they had a plan

945
00:50:50,600 --> 00:50:52,760
Speaker 1: to like formally chicken out for five years.

946
00:50:52,920 --> 00:50:53,200
Speaker 4: Yeah.

947
00:50:53,960 --> 00:50:56,560
Speaker 1: Uh. You know what's interesting about that when I say,

948
00:50:56,600 --> 00:50:59,480
Speaker 1: like even the Idaho play, as weird as it was

949
00:50:59,520 --> 00:51:02,360
Speaker 1: to do one on the Idaho play of the social

950
00:51:02,400 --> 00:51:05,440
Speaker 1: maneuver of doing the hunt. I remember I was talking

951
00:51:05,480 --> 00:51:07,560
Speaker 1: to these guys that were really involved in the elk

952
00:51:07,600 --> 00:51:14,359
Speaker 1: reintroduction in Kentucky and they were nervous about this. So

953
00:51:15,040 --> 00:51:18,000
Speaker 1: they ever since when when they started working on the

954
00:51:18,000 --> 00:51:22,120
Speaker 1: elk reintroduction, which was state agency Rocky Mountain Elk Foundation,

955
00:51:22,760 --> 00:51:26,320
Speaker 1: it was like, because of hunting, and will hunt them,

956
00:51:26,560 --> 00:51:28,960
Speaker 1: and we'll hunt them, even though those years in the future,

957
00:51:30,120 --> 00:51:34,880
Speaker 1: they baked it into every conversation to not then down

958
00:51:34,920 --> 00:51:38,719
Speaker 1: the road go like, oh, hey, now that we got

959
00:51:38,760 --> 00:51:41,480
Speaker 1: all these elk, how about we have a hunting season.

960
00:51:41,520 --> 00:51:44,320
Speaker 1: It was like they were they were deliberate about setting

961
00:51:44,320 --> 00:51:49,080
Speaker 1: an expectation that that's where this would go. And you

962
00:51:49,160 --> 00:51:51,239
Speaker 1: see when you see signs around any anyway you go

963
00:51:51,280 --> 00:51:54,120
Speaker 1: around in this area, you'll see signs delisting means hunting

964
00:51:54,640 --> 00:51:58,719
Speaker 1: and it's it's meant to be delisting means hunting, and

965
00:51:58,760 --> 00:52:01,560
Speaker 1: it's meant to be like an anti delisting. They're coming

966
00:52:01,640 --> 00:52:04,360
Speaker 1: right out and saying, we're not gonna we're not looking

967
00:52:04,360 --> 00:52:06,040
Speaker 1: to argue about how many bears they are, because no

968
00:52:06,040 --> 00:52:09,040
Speaker 1: one's gonna argue that bears are stable. They're looking to

969
00:52:09,080 --> 00:52:13,560
Speaker 1: be like they're using the ESA, they're using any Endangered

970
00:52:13,600 --> 00:52:17,680
Speaker 1: Species Act not as a management tool. They're using it

971
00:52:17,719 --> 00:52:20,960
Speaker 1: as a way that they can prevent something from happening

972
00:52:21,040 --> 00:52:24,400
Speaker 1: that they don't want to happen. It's like, it's my

973
00:52:24,560 --> 00:52:28,080
Speaker 1: favorite Animal Protection Act. It is not the Endangered Species Act,

974
00:52:28,280 --> 00:52:30,520
Speaker 1: and they even know it, and their rhetoric mirrors it.

975
00:52:30,560 --> 00:52:32,920
Speaker 1: But when I look and I see that sign delisting

976
00:52:33,080 --> 00:52:35,520
Speaker 1: means hunting, I always think, I sure hope they're right.

977
00:52:36,239 --> 00:52:39,719
Speaker 4: Yeah, you're rooting for that.

978
00:52:41,280 --> 00:52:43,839
Speaker 1: And they'll always show a sow with cubs, the one

979
00:52:43,840 --> 00:52:46,080
Speaker 1: they use around here. Sure, they show a saw with

980
00:52:46,160 --> 00:52:50,040
Speaker 1: cubs with a crosshair. Yeah. I'm like, but you can't

981
00:52:50,040 --> 00:52:53,759
Speaker 1: shoot cells with cubs. Yeah, so that's a poacher. They

982
00:52:53,800 --> 00:52:54,880
Speaker 1: should arrest that person.

983
00:52:57,000 --> 00:53:00,920
Speaker 4: We actually had, like I remember having five heights talking

984
00:53:00,960 --> 00:53:03,680
Speaker 4: about how many bears we were going to harvest and

985
00:53:04,160 --> 00:53:06,920
Speaker 4: a game warden in a district that has a lot

986
00:53:06,960 --> 00:53:09,800
Speaker 4: of bears thought that twenty four was like not nearly

987
00:53:09,960 --> 00:53:12,880
Speaker 4: enough and and was upset about it. And it's like,

988
00:53:12,920 --> 00:53:17,160
Speaker 4: we're not trying to manage the population totally through hunting.

989
00:53:17,640 --> 00:53:21,759
Speaker 4: We're trying to create a social standard for hunting. You know,

990
00:53:25,320 --> 00:53:27,279
Speaker 4: I say we, But that was past.

991
00:53:27,840 --> 00:53:30,919
Speaker 1: Years when we first started this podcast, million years ago

992
00:53:31,880 --> 00:53:34,560
Speaker 1: in an office where me and my wife, Me and

993
00:53:34,560 --> 00:53:37,720
Speaker 1: my wife had dinner not a great one either, across

994
00:53:37,719 --> 00:53:42,040
Speaker 1: the road from our original old office last night on

995
00:53:42,080 --> 00:53:46,000
Speaker 1: our little date night. Anyways, in that office upstairs, we

996
00:53:46,200 --> 00:53:49,000
Speaker 1: and one of our early early podcasts we first launched

997
00:53:49,040 --> 00:53:52,440
Speaker 1: a podcast. We had a guy from the USGS, Frank

998
00:53:52,760 --> 00:53:56,279
Speaker 1: mcmahonan man. What is his name, Van Man? We had

999
00:53:56,360 --> 00:53:59,919
Speaker 1: him on talk about He yeah, he does demographics on Grizzy.

1000
00:54:00,480 --> 00:54:00,719
Speaker 4: Sure.

1001
00:54:01,000 --> 00:54:05,080
Speaker 1: So the USGS is a it's a federal organization, and

1002
00:54:05,120 --> 00:54:10,200
Speaker 1: the USGS doesn't do policy. The USGS doesn't manage land, Okay,

1003
00:54:10,320 --> 00:54:13,600
Speaker 1: like the US Forest Service, the Usdaight manages land, US

1004
00:54:13,640 --> 00:54:17,400
Speaker 1: Fish and Wildlife Service manages refuges, the National Park Service

1005
00:54:17,480 --> 00:54:21,320
Speaker 1: manages parks. You have a bunch of land management federal agencies.

1006
00:54:21,360 --> 00:54:24,680
Speaker 1: The USGS doesn't do land management, they don't do policy.

1007
00:54:24,760 --> 00:54:29,680
Speaker 1: Their mandate is information. Sure, they provide information. So this

1008
00:54:29,680 --> 00:54:32,080
Speaker 1: this guest we had, it's a great podcast. We want

1009
00:54:32,080 --> 00:54:34,000
Speaker 1: to go back and listen. Love it's still relevant today.

1010
00:54:34,600 --> 00:54:38,760
Speaker 1: This guest we had explained we got to talk about demographics,

1011
00:54:39,480 --> 00:54:43,879
Speaker 1: grizzy bear demographics. And there's the number. At that time,

1012
00:54:43,920 --> 00:54:45,279
Speaker 1: I don't know what the number is now. The number

1013
00:54:45,280 --> 00:54:47,000
Speaker 1: at that time was something like it was like fixed.

1014
00:54:47,000 --> 00:54:52,040
Speaker 1: It was like carved in stone, seven hundred okay, yeah,

1015
00:54:52,280 --> 00:54:53,640
Speaker 1: and it will And he explained that. I was like,

1016
00:54:53,640 --> 00:54:56,719
Speaker 1: where does that number come from? What they had looked

1017
00:54:56,719 --> 00:54:59,600
Speaker 1: at is at a time they looked at, Okay, in

1018
00:54:59,680 --> 00:55:07,439
Speaker 1: this ecosystem, how much space does a breeding age female use?

1019
00:55:07,760 --> 00:55:10,239
Speaker 4: Thirty square kilometers was the estimate.

1020
00:55:10,120 --> 00:55:13,239
Speaker 1: That okayep And they would draw what's that little shape

1021
00:55:13,280 --> 00:55:16,560
Speaker 1: you draw on them at an octagon or polygon?

1022
00:55:16,840 --> 00:55:22,400
Speaker 4: Yeah, it was actually a grid. Okay, but yeah, and

1023
00:55:22,440 --> 00:55:24,120
Speaker 4: that was called the chow To model.

1024
00:55:24,239 --> 00:55:26,919
Speaker 1: Yeah. Explain, yeah, okay, so you know about the shit, Yeah,

1025
00:55:27,520 --> 00:55:30,600
Speaker 1: explain how the number was arrived at. And then and

1026
00:55:30,640 --> 00:55:32,759
Speaker 1: then I'm going to share with you something he told

1027
00:55:32,760 --> 00:55:35,359
Speaker 1: me about the number that I was like we spent

1028
00:55:35,440 --> 00:55:38,520
Speaker 1: an hour talking about yeah, because he would say at

1029
00:55:38,640 --> 00:55:43,160
Speaker 1: least I'd go, how many at least seven forty? Well,

1030
00:55:43,160 --> 00:55:46,040
Speaker 1: how many at least seven forty? Yeah, well how many

1031
00:55:46,239 --> 00:55:47,440
Speaker 1: at least seven forty?

1032
00:55:49,160 --> 00:55:51,719
Speaker 4: Yeah, So that model has been updated twice since then.

1033
00:55:51,760 --> 00:55:54,319
Speaker 1: Okay, but explain how it's like, it's really fascinating how

1034
00:55:54,320 --> 00:55:55,359
Speaker 1: you make a model like this.

1035
00:55:55,480 --> 00:55:57,799
Speaker 4: Okay, So bears are really hard to count because they're

1036
00:55:57,960 --> 00:56:03,239
Speaker 4: solitary nature. They're not territory. Their home ranges overlap, so just.

1037
00:56:03,160 --> 00:56:06,279
Speaker 1: Say solitary but not territorial, right.

1038
00:56:06,880 --> 00:56:10,680
Speaker 4: They like to be in visialistic, but they don't have territories,

1039
00:56:11,160 --> 00:56:14,520
Speaker 4: not like a mountain lion. Solitary nature has a territory.

1040
00:56:14,560 --> 00:56:17,239
Speaker 4: It's keeping other cats out of there. So if there's

1041
00:56:17,239 --> 00:56:19,520
Speaker 4: food availability, their home ranges overlap.

1042
00:56:20,239 --> 00:56:22,080
Speaker 1: Oh, I've never even thought about that term. That's a

1043
00:56:22,080 --> 00:56:24,600
Speaker 1: great term. Solitary but not territorial.

1044
00:56:24,320 --> 00:56:27,120
Speaker 4: Right, And that's what happened with the model. That's what

1045
00:56:27,160 --> 00:56:31,440
Speaker 4: makes them really difficult to count. So the early research

1046
00:56:31,520 --> 00:56:36,920
Speaker 4: showed that a grizzly bear sal's home range was thirty

1047
00:56:36,920 --> 00:56:42,600
Speaker 4: square kilometers, so when they were counting, if you're counting

1048
00:56:42,640 --> 00:56:46,160
Speaker 4: bears and there's you break the system, the ecosystem up

1049
00:56:46,200 --> 00:56:48,960
Speaker 4: into a grid, and there's a sow with cubs in

1050
00:56:48,960 --> 00:56:52,440
Speaker 4: one of those squares. You cross off that grid because

1051
00:56:52,480 --> 00:56:57,040
Speaker 4: you don't want to you want to lean conservative, you

1052
00:56:57,080 --> 00:57:00,960
Speaker 4: don't want to overestimate the population. One with that model

1053
00:57:01,080 --> 00:57:05,160
Speaker 4: is as the population gets higher in density, your model

1054
00:57:05,200 --> 00:57:09,480
Speaker 4: gets more and more biased because of those home ranges overlapping.

1055
00:57:10,000 --> 00:57:10,280
Speaker 1: Yep.

1056
00:57:11,120 --> 00:57:16,360
Speaker 4: So that model maxed out at seven forty, Like I

1057
00:57:16,400 --> 00:57:20,560
Speaker 4: can't remember seven fifty. Maybe you couldn't get it. You

1058
00:57:20,600 --> 00:57:23,640
Speaker 4: couldn't shove any more grizzly bears into the ecosystem in

1059
00:57:23,680 --> 00:57:26,600
Speaker 4: that model. They went back and they looked at color

1060
00:57:26,680 --> 00:57:29,520
Speaker 4: data and they found out that SAO's home range was

1061
00:57:29,560 --> 00:57:31,760
Speaker 4: more like fourteen square kilometers.

1062
00:57:32,480 --> 00:57:35,240
Speaker 1: You know, I gotta this is great, but I want

1063
00:57:35,240 --> 00:57:37,760
Speaker 1: to add in a thing here. Yeah. That he'd explained

1064
00:57:37,840 --> 00:57:42,280
Speaker 1: is be that when they make the model, you're just

1065
00:57:42,600 --> 00:57:46,400
Speaker 1: you count you're trying to count breeding age females, and

1066
00:57:46,400 --> 00:57:46,960
Speaker 1: then you look.

1067
00:57:46,840 --> 00:57:49,040
Speaker 4: At what with cubs of the year, okay, and then to.

1068
00:57:49,000 --> 00:57:51,840
Speaker 1: Look at what you know about the demographics, meaning that

1069
00:57:51,960 --> 00:57:53,640
Speaker 1: you could go into a let's say you could go

1070
00:57:53,640 --> 00:58:00,520
Speaker 1: into a country perhaps and count how many how many

1071
00:58:00,840 --> 00:58:04,920
Speaker 1: females with children are in this country, and then probably

1072
00:58:04,960 --> 00:58:07,800
Speaker 1: go like, okay, so we know human males and human

1073
00:58:07,880 --> 00:58:11,760
Speaker 1: females are born at a one to one ratio. We

1074
00:58:11,880 --> 00:58:18,600
Speaker 1: know that like a female is most active reproductively between

1075
00:58:19,040 --> 00:58:22,280
Speaker 1: twenty four and thirty eight, and that they have on

1076
00:58:22,480 --> 00:58:26,760
Speaker 1: average two point two kids, and so we can just

1077
00:58:26,800 --> 00:58:29,560
Speaker 1: look at how many moms there are and make a

1078
00:58:29,600 --> 00:58:31,960
Speaker 1: guess at what the human population is in that country.

1079
00:58:32,560 --> 00:58:34,320
Speaker 1: That's kind of what you're doing with grizzies, right, You're like,

1080
00:58:34,880 --> 00:58:38,320
Speaker 1: we know that that you got males, you got cubs,

1081
00:58:38,400 --> 00:58:41,800
Speaker 1: but if we can know this one number, we can

1082
00:58:41,840 --> 00:58:45,400
Speaker 1: extrapolate outward to get a sense of how many are there,

1083
00:58:46,080 --> 00:58:47,760
Speaker 1: rather than mechanically counting them.

1084
00:58:47,920 --> 00:58:50,520
Speaker 4: Yeah, you have. You know that they're the driver of

1085
00:58:50,520 --> 00:58:54,000
Speaker 4: the population. But what you're describing is actually more like

1086
00:58:54,040 --> 00:58:57,280
Speaker 4: a census, and that's closer to what the model is now.

1087
00:58:57,600 --> 00:59:02,840
Speaker 4: It's an integrated population model. But you know, yeah, the

1088
00:59:03,240 --> 00:59:09,080
Speaker 4: ratio of bears in the ecosystem you have, however many

1089
00:59:09,120 --> 00:59:13,120
Speaker 4: adult males you have, however many subadult bears and females

1090
00:59:13,120 --> 00:59:17,800
Speaker 4: with cubs are driving your population. So it's just a

1091
00:59:17,920 --> 00:59:25,120
Speaker 4: multiplier understood essentially, so it got changed to fourteen square

1092
00:59:25,160 --> 00:59:30,120
Speaker 4: kilometers and that made the estimate more like twelve hundred bears.

1093
00:59:30,920 --> 00:59:33,840
Speaker 4: And then what you just described is now what they're

1094
00:59:33,880 --> 00:59:38,880
Speaker 4: doing is an integrated population model, and it's more of

1095
00:59:38,920 --> 00:59:42,840
Speaker 4: a census and you can plug in other factors.

1096
00:59:43,200 --> 00:59:43,720
Speaker 1: I got it.

1097
00:59:43,760 --> 00:59:47,439
Speaker 4: So what's the number now, ten oneenty thirty.

1098
00:59:48,280 --> 00:59:49,520
Speaker 1: How good you think that number is?

1099
00:59:51,880 --> 00:59:55,600
Speaker 4: I think that's pretty accurate. I think there's definitely parts

1100
00:59:55,640 --> 00:59:58,360
Speaker 4: of the ecosystem where there's higher densities than other parts.

1101
00:59:58,960 --> 01:00:02,320
Speaker 4: And growing up in Cody, I just assumed everywhere had

1102
01:00:02,400 --> 01:00:05,080
Speaker 4: really high densities, and you go to other parts and

1103
01:00:05,120 --> 01:00:08,880
Speaker 4: they're just not. And this new modeling system is going

1104
01:00:08,880 --> 01:00:11,800
Speaker 4: to incorporate some of that and show you where where

1105
01:00:11,840 --> 01:00:17,240
Speaker 4: there's more density of bears. And that's only in the

1106
01:00:17,280 --> 01:00:21,440
Speaker 4: demographic monitoring monitoring area. So there's bears that live outside

1107
01:00:22,120 --> 01:00:25,520
Speaker 4: where they're even looking for bears. So that is a

1108
01:00:25,600 --> 01:00:30,040
Speaker 4: minimum because they're not counting bears that aren't in suitable habitat.

1109
01:00:30,600 --> 01:00:32,840
Speaker 4: Oh really, yeah, they might be living years.

1110
01:00:32,880 --> 01:00:34,720
Speaker 1: They're not counting bears that don't count.

1111
01:00:35,200 --> 01:00:35,480
Speaker 3: Yeah.

1112
01:00:35,560 --> 01:00:38,720
Speaker 1: Yeah, So if a bear moves out into like if

1113
01:00:38,760 --> 01:00:41,520
Speaker 1: a bear moves out of and moves out into like

1114
01:00:41,640 --> 01:00:44,160
Speaker 1: Fort Benton, out of out of the Shouldo area and

1115
01:00:44,240 --> 01:00:47,800
Speaker 1: just keeps going east. He leaves the counting.

1116
01:00:47,440 --> 01:00:50,160
Speaker 4: Area if he's there year round, if he's outside of

1117
01:00:50,200 --> 01:00:53,560
Speaker 4: their their demographic monitoring area. And I don't know about

1118
01:00:53,560 --> 01:00:55,920
Speaker 4: the NCDE, but that's how they did it with the

1119
01:00:55,960 --> 01:00:58,760
Speaker 4: g ye got it. Yeah, you got to be in

1120
01:00:58,800 --> 01:01:01,680
Speaker 4: a bear place to be a bear. Yeah, stract don't

1121
01:01:01,680 --> 01:01:02,800
Speaker 4: count outliers.

1122
01:01:03,000 --> 01:01:06,680
Speaker 1: So there's about So tell me the number again, you think, oney? Thirty?

1123
01:01:06,800 --> 01:01:09,600
Speaker 4: Yeah, and it was as high as twelve hundred was

1124
01:01:09,760 --> 01:01:11,880
Speaker 4: estimate a couple of years ago before they changed to

1125
01:01:11,920 --> 01:01:15,920
Speaker 4: this other model. But it has a lot more factors.

1126
01:01:15,960 --> 01:01:18,400
Speaker 4: It's a lot more accurate. God, it's my understanding.

1127
01:01:18,760 --> 01:01:19,160
Speaker 1: That's good.

1128
01:01:19,240 --> 01:01:21,360
Speaker 4: No, I still thought it was that old seven.

1129
01:01:22,080 --> 01:01:24,160
Speaker 1: Yeah. I didn't know that anyone moved beyond that number.

1130
01:01:24,240 --> 01:01:27,640
Speaker 4: That was laughable. People in my hometown never believe that.

1131
01:01:28,960 --> 01:01:36,840
Speaker 1: Why do they Why do they seem to congregate in

1132
01:01:36,880 --> 01:01:39,720
Speaker 1: these little micro areas so much. There's just some like

1133
01:01:39,800 --> 01:01:42,160
Speaker 1: valleys that are like such hot spots, and you go

1134
01:01:42,200 --> 01:01:44,160
Speaker 1: to another valley and you could go to another value

1135
01:01:44,200 --> 01:01:46,440
Speaker 1: and hang out there over the years, ten ten years

1136
01:01:46,880 --> 01:01:48,960
Speaker 1: and never lay eyes on one. But then there's like,

1137
01:01:49,520 --> 01:01:51,360
Speaker 1: you can't it just doesn't. You can't really tell the

1138
01:01:51,360 --> 01:01:52,720
Speaker 1: difference from looking at them.

1139
01:01:52,960 --> 01:01:56,400
Speaker 4: It's just food availability, food sources, and some of it's

1140
01:01:56,480 --> 01:02:00,320
Speaker 4: learned behavior. And my part of the woods, we have

1141
01:02:00,360 --> 01:02:03,240
Speaker 4: what are called moth sites, and there's these bears on

1142
01:02:03,280 --> 01:02:06,840
Speaker 4: moth sites, and you know, I've done flights where I've

1143
01:02:06,840 --> 01:02:09,440
Speaker 4: counted forty bears on moss sites. So there's a high

1144
01:02:09,480 --> 01:02:12,480
Speaker 4: concentration of food, and that's one of the highest caloric

1145
01:02:12,600 --> 01:02:14,080
Speaker 4: value foods in the ecosystem.

1146
01:02:14,160 --> 01:02:15,160
Speaker 1: He explain what that means.

1147
01:02:15,880 --> 01:02:16,640
Speaker 4: Cloric value?

1148
01:02:16,760 --> 01:02:19,400
Speaker 1: No, what a moth? I know about it? Oh, yeah,

1149
01:02:19,640 --> 01:02:21,440
Speaker 1: I know a little bit, but just tell people what

1150
01:02:21,480 --> 01:02:21,840
Speaker 1: that is.

1151
01:02:22,000 --> 01:02:25,640
Speaker 4: So there's these army cutworm moths that migrate from the

1152
01:02:25,680 --> 01:02:29,080
Speaker 4: Midwest and they come up in the mountains at night

1153
01:02:29,240 --> 01:02:32,240
Speaker 4: pollinate flowers, and then in the daytime they get in

1154
01:02:32,320 --> 01:02:37,480
Speaker 4: these talus slopes and they use that as a heat refugia,

1155
01:02:38,200 --> 01:02:41,320
Speaker 4: and bears come along and they flip over those rocks

1156
01:02:41,320 --> 01:02:44,280
Speaker 4: and eat those bugs. And they're probably eating twenty to

1157
01:02:44,360 --> 01:02:45,240
Speaker 4: forty thousand of.

1158
01:02:45,200 --> 01:02:48,080
Speaker 1: Those moths a day, licking them up.

1159
01:02:47,960 --> 01:02:53,400
Speaker 4: Licking them up, yep. And it's just a really rich

1160
01:02:53,480 --> 01:02:56,280
Speaker 4: food source for bears in ecosystem. But what I was

1161
01:02:56,320 --> 01:02:59,160
Speaker 4: going to say is there's places in the ecosystem where

1162
01:02:59,200 --> 01:03:02,640
Speaker 4: there's moss sites and there's not bears utilizing them, So

1163
01:03:02,920 --> 01:03:05,840
Speaker 4: they think it's a learned behavior, like.

1164
01:03:05,960 --> 01:03:12,480
Speaker 1: They know about it, right yep. Huh, Like if you

1165
01:03:12,520 --> 01:03:14,840
Speaker 1: took all the bears out and put new ones back in,

1166
01:03:14,880 --> 01:03:16,040
Speaker 1: they might not find those.

1167
01:03:15,880 --> 01:03:19,280
Speaker 4: Moths maybe not for a while, or they use different ones,

1168
01:03:20,160 --> 01:03:21,200
Speaker 4: or they could use different ones.

1169
01:03:21,280 --> 01:03:24,880
Speaker 1: Yeah, yeah, huh. What are some of the other main foods,

1170
01:03:24,880 --> 01:03:27,000
Speaker 1: Like everybody likes to think of them just you know,

1171
01:03:27,120 --> 01:03:29,920
Speaker 1: eating elk calves, But when you had a list like

1172
01:03:29,960 --> 01:03:32,120
Speaker 1: their main grub sources, what do you think it is?

1173
01:03:33,360 --> 01:03:37,160
Speaker 4: Uh, vegetation. You know, bears eat a lot of different

1174
01:03:37,280 --> 01:03:40,439
Speaker 4: roots and tubers and corns, and that's a big one.

1175
01:03:40,440 --> 01:03:44,360
Speaker 4: In the spring, elk calves is a big food source.

1176
01:03:44,480 --> 01:03:49,320
Speaker 4: I mean, that's kind of undeniable. These moths sites. There

1177
01:03:49,360 --> 01:03:52,840
Speaker 4: are a few places in the ecosystem where they eat

1178
01:03:52,920 --> 01:03:58,800
Speaker 4: those cutthroat trout that are spawning white bark pine. But

1179
01:03:59,160 --> 01:04:02,520
Speaker 4: they did a food synthesis analysis on bears and found

1180
01:04:02,600 --> 01:04:04,880
Speaker 4: that they eat over two hundred and sixty different plants

1181
01:04:04,880 --> 01:04:09,400
Speaker 4: and animals so kid. Yeah, in the Yellstone ecosystem, they

1182
01:04:09,400 --> 01:04:12,680
Speaker 4: have the most diverse diet.

1183
01:04:11,880 --> 01:04:13,800
Speaker 1: Two hundred and sixty species. Yep.

1184
01:04:14,320 --> 01:04:16,280
Speaker 4: That bear that I caught there was six twenty four.

1185
01:04:17,200 --> 01:04:20,200
Speaker 4: I figured that he was probably eating meat year round.

1186
01:04:20,640 --> 01:04:23,920
Speaker 4: You know, that bear was going from winter kill carcasses

1187
01:04:24,840 --> 01:04:30,960
Speaker 4: to elk calves, to moths, to killing cattle in the

1188
01:04:31,000 --> 01:04:35,360
Speaker 4: fall because we'd caught him before killing cattle, to eating

1189
01:04:35,400 --> 01:04:38,440
Speaker 4: gut piles. You know, he was eating probably nothing but meat.

1190
01:04:38,760 --> 01:04:39,680
Speaker 4: How old was that bear?

1191
01:04:40,480 --> 01:04:40,760
Speaker 2: Mmm?

1192
01:04:42,000 --> 01:04:46,160
Speaker 4: I don't remember. I caught another bear that was five

1193
01:04:46,280 --> 01:04:49,960
Speaker 4: hundred and twenty pounds in the spring, same exact location,

1194
01:04:50,960 --> 01:04:54,440
Speaker 4: and I caught him eight years later and he was

1195
01:04:54,480 --> 01:04:55,479
Speaker 4: twenty eight years old.

1196
01:04:55,960 --> 01:04:57,880
Speaker 1: Wow, Holy cow man.

1197
01:04:58,480 --> 01:05:02,040
Speaker 4: So that other bear could be thirty I think. I think, well,

1198
01:05:02,120 --> 01:05:04,200
Speaker 4: when he was twenty eight, that bear was past his prime.

1199
01:05:04,600 --> 01:05:07,480
Speaker 4: Maybe when other bear was probably between fifteen and twenty.

1200
01:05:07,560 --> 01:05:11,000
Speaker 1: Gotcha, Yeah, man, it's twenty eight.

1201
01:05:12,040 --> 01:05:14,520
Speaker 4: Zach Turnbull caught one that was thirty two in the

1202
01:05:14,600 --> 01:05:15,440
Speaker 4: Upper Green.

1203
01:05:16,960 --> 01:05:18,480
Speaker 1: And that's got to be getting close to mass.

1204
01:05:18,520 --> 01:05:22,000
Speaker 4: That's the oldest bear they've caught in the ecosystem.

1205
01:05:22,160 --> 01:05:28,680
Speaker 1: Yeah, yeah, yeah. In your mind, what is the what

1206
01:05:28,840 --> 01:05:32,720
Speaker 1: is the most common sort of way things play out

1207
01:05:32,760 --> 01:05:34,720
Speaker 1: when people get scratched up by a bear.

1208
01:05:36,200 --> 01:05:39,360
Speaker 4: Hmmm, what do you mean, like, how.

1209
01:05:39,680 --> 01:05:41,560
Speaker 1: If you were if you were no, no, no, no, I'm sorry,

1210
01:05:41,640 --> 01:05:44,480
Speaker 1: if you were going to look at from all the

1211
01:05:44,520 --> 01:05:46,760
Speaker 1: things you've heard and seen, when someone gets mauled by

1212
01:05:46,760 --> 01:05:48,480
Speaker 1: a bear, what is the normal.

1213
01:05:48,160 --> 01:05:50,040
Speaker 4: Scenario surprise encounter?

1214
01:05:50,720 --> 01:05:53,720
Speaker 1: Probably like you're spooking it.

1215
01:05:53,960 --> 01:05:57,840
Speaker 4: Yeah, and probably sounds with cubs more than anything else.

1216
01:05:58,720 --> 01:06:01,240
Speaker 4: You know, I see a big adult mail track, I'm

1217
01:06:01,280 --> 01:06:03,880
Speaker 4: not nervous. I see a little tiny cub track, and

1218
01:06:03,880 --> 01:06:06,240
Speaker 4: I'm like really looking around.

1219
01:06:06,520 --> 01:06:11,560
Speaker 1: Yeah, so it's that you like jump it at close range.

1220
01:06:12,120 --> 01:06:15,480
Speaker 4: Yeah, that's the majority of them. You know, there's a

1221
01:06:15,520 --> 01:06:18,520
Speaker 4: lot of cases every year where guys get elk down

1222
01:06:18,640 --> 01:06:22,920
Speaker 4: and and there's bears coming into those dead elk or

1223
01:06:22,960 --> 01:06:26,200
Speaker 4: they're going back to retrieve a bear or excuse me

1224
01:06:26,280 --> 01:06:29,439
Speaker 4: an elk carcass and and they jump a bear. That's

1225
01:06:29,440 --> 01:06:33,320
Speaker 4: pretty common too. I mean it's it's food, cubs and

1226
01:06:33,800 --> 01:06:38,040
Speaker 4: personal space, And a lot of times you're getting cubs

1227
01:06:38,080 --> 01:06:39,760
Speaker 4: and personal space at the same time.

1228
01:06:40,080 --> 01:06:43,880
Speaker 1: Got it, that's trouble. Yeah, do you believe you know,

1229
01:06:43,920 --> 01:06:45,600
Speaker 1: there's like a thing I don't know if it's a

1230
01:06:45,880 --> 01:06:48,480
Speaker 1: if it's a what's the opposite of an urban legend,

1231
01:06:49,080 --> 01:06:49,840
Speaker 1: rural legend?

1232
01:06:51,560 --> 01:06:52,160
Speaker 4: Rural myth?

1233
01:06:52,600 --> 01:06:58,040
Speaker 1: Okay, like my brother redneck talk my brother Danny, he

1234
01:06:58,160 --> 01:07:03,280
Speaker 1: now and then goes in, uh hunts kodyac but after

1235
01:07:03,360 --> 01:07:05,800
Speaker 1: you know, he hunts in the winter for black tail deer. Right,

1236
01:07:06,280 --> 01:07:10,720
Speaker 1: and he'll swear when the bears are down, he'll swear

1237
01:07:10,760 --> 01:07:14,320
Speaker 1: to red fox. No, a gunshot. There's a lot of

1238
01:07:14,320 --> 01:07:17,040
Speaker 1: red fox there. He's like, you shoot a deer and

1239
01:07:17,080 --> 01:07:20,840
Speaker 1: they're just there. Yeah, and he's like, you know, they're

1240
01:07:20,840 --> 01:07:23,320
Speaker 1: smelling it whatever. But it's so fast you can't help.

1241
01:07:23,320 --> 01:07:27,320
Speaker 1: But wonder like, are they're like, oh, they're like and they're.

1242
01:07:27,120 --> 01:07:29,080
Speaker 4: Like, ooh yeah, go that way.

1243
01:07:29,120 --> 01:07:31,120
Speaker 1: You hear people say this about grizzlies.

1244
01:07:30,840 --> 01:07:31,640
Speaker 4: Yeah, all the time.

1245
01:07:31,760 --> 01:07:32,560
Speaker 1: Do you think that's true?

1246
01:07:32,600 --> 01:07:33,240
Speaker 4: No, not at all.

1247
01:07:33,320 --> 01:07:34,600
Speaker 1: You don't think they can't do a gunshot.

1248
01:07:34,640 --> 01:07:37,560
Speaker 4: No. I'll tell you why, because I have friends that

1249
01:07:37,640 --> 01:07:41,320
Speaker 4: are really poor shots, have guided hunters. They're really poor shots.

1250
01:07:41,920 --> 01:07:43,960
Speaker 4: And you sit there for fifteen twenty minutes and no

1251
01:07:44,040 --> 01:07:46,560
Speaker 4: bears show shows up. We have a shooting range outside

1252
01:07:46,560 --> 01:07:47,000
Speaker 4: of Cody.

1253
01:07:47,040 --> 01:07:47,760
Speaker 1: It's not full bears.

1254
01:07:47,800 --> 01:07:52,760
Speaker 4: It's not full of bears, even though I've caught bears

1255
01:07:52,760 --> 01:07:54,919
Speaker 4: adjacent to it, but they're not running to that thing,

1256
01:07:55,600 --> 01:08:00,600
Speaker 4: you know, got it. So it's really when you get

1257
01:08:00,640 --> 01:08:04,280
Speaker 4: an animal down that blood, that room and smell that guts.

1258
01:08:04,520 --> 01:08:07,200
Speaker 4: As soon as that hits the air, you gotta clock

1259
01:08:07,240 --> 01:08:10,200
Speaker 4: on you. And what I like to do as a

1260
01:08:10,240 --> 01:08:13,320
Speaker 4: guide is start a fire, you know, as long as

1261
01:08:13,360 --> 01:08:15,520
Speaker 4: there's not a fireband if I'm in a good location,

1262
01:08:16,840 --> 01:08:20,160
Speaker 4: you know, and started upwind because that kind of masks

1263
01:08:20,200 --> 01:08:24,799
Speaker 4: that scent and fire. The real reason is it calms

1264
01:08:24,800 --> 01:08:27,719
Speaker 4: your hunter down because as soon as they kill something,

1265
01:08:27,760 --> 01:08:29,120
Speaker 4: they're like super bear scared.

1266
01:08:29,439 --> 01:08:32,280
Speaker 1: Yeah, we do that fire thing caughtting up moose in

1267
01:08:32,320 --> 01:08:36,240
Speaker 1: alask especially when it's real thick, I'll get a fire gone.

1268
01:08:36,360 --> 01:08:38,320
Speaker 1: I don't know if it's like my owne I just have.

1269
01:08:38,520 --> 01:08:41,559
Speaker 1: I don't know. I like to have the idea that

1270
01:08:41,600 --> 01:08:45,680
Speaker 1: it somehow broadcasts the human presence more might be total horseshit.

1271
01:08:45,360 --> 01:08:47,200
Speaker 4: Yeah, I think so. I don't think bears want to

1272
01:08:47,200 --> 01:08:50,840
Speaker 4: come into a fire. So that's just something I've learned

1273
01:08:51,160 --> 01:08:52,559
Speaker 4: since after the game and fish.

1274
01:08:52,640 --> 01:08:56,679
Speaker 1: You know, have you handled bears that had killed people?

1275
01:08:58,240 --> 01:09:02,479
Speaker 4: Hmmm, No, I've handled there's that have mall people. Yeah,

1276
01:09:03,080 --> 01:09:05,639
Speaker 4: after the mall and yeah.

1277
01:09:05,479 --> 01:09:07,639
Speaker 7: Didn't you tell me that story about how.

1278
01:09:08,560 --> 01:09:12,720
Speaker 4: Yeah, so the first yeah, one of my yeah, one

1279
01:09:12,720 --> 01:09:16,519
Speaker 4: of my first conflicts that I came on. I wasn't

1280
01:09:16,560 --> 01:09:20,240
Speaker 4: even hired on full time yet. I came in the office.

1281
01:09:20,280 --> 01:09:23,240
Speaker 4: I was just volunteering on my days off. And my

1282
01:09:23,320 --> 01:09:26,080
Speaker 4: boss was on the phone and he said, I remember

1283
01:09:26,160 --> 01:09:28,960
Speaker 4: him saying, three maybe four people mauled. I'm on the

1284
01:09:28,960 --> 01:09:31,200
Speaker 4: way to the hospital. And he got off the phone

1285
01:09:31,200 --> 01:09:32,680
Speaker 4: and he said, hey, can you help us for a

1286
01:09:32,720 --> 01:09:37,160
Speaker 4: couple of days, And I said yeah. And there was

1287
01:09:37,160 --> 01:09:40,880
Speaker 4: a mauling at by cook City, a campground called Soda Butte.

1288
01:09:42,560 --> 01:09:46,840
Speaker 4: There was a human fatality there. And ran up there

1289
01:09:46,880 --> 01:09:50,040
Speaker 4: with the trap and you know that was obviously in Montana,

1290
01:09:50,200 --> 01:09:53,719
Speaker 4: but we assisted Montana and trying to catch those bears

1291
01:09:53,760 --> 01:09:58,200
Speaker 4: and they set the traps. They caught those bears, I

1292
01:09:58,880 --> 01:10:02,240
Speaker 4: you know, set but we didn't catch anything. And then

1293
01:10:02,280 --> 01:10:07,439
Speaker 4: I was shuttling samples to our vet lab and layer

1294
01:10:07,600 --> 01:10:12,160
Speaker 4: me what kind of samples, well, tissue samples from the

1295
01:10:12,200 --> 01:10:15,000
Speaker 4: bear to make sure that it was a match. Okay,

1296
01:10:16,479 --> 01:10:19,799
Speaker 4: but she had mauled three people and the first tint

1297
01:10:20,560 --> 01:10:22,960
Speaker 4: was a young kid and his girlfriend and a dog,

1298
01:10:23,160 --> 01:10:25,479
Speaker 4: and she tried to Sorry, she didn't maul, but she

1299
01:10:25,479 --> 01:10:28,400
Speaker 4: she tried to attack three different people. She tried to

1300
01:10:28,439 --> 01:10:32,040
Speaker 4: come into that tent and the dog started barking, and

1301
01:10:32,840 --> 01:10:35,800
Speaker 4: she left it, and that kid got so afraid. I

1302
01:10:35,800 --> 01:10:38,680
Speaker 4: call him a kid. He's probably like eighteen nineteen. He

1303
01:10:38,760 --> 01:10:42,679
Speaker 4: packed up all his stuff and left, and that Soo

1304
01:10:43,160 --> 01:10:46,920
Speaker 4: went further down the campground and there was a couple

1305
01:10:46,960 --> 01:10:52,680
Speaker 4: who slept in separate tents because the husband snored and

1306
01:10:54,080 --> 01:10:57,679
Speaker 4: maybe maybe they're in a fight, and that Soo ripped

1307
01:10:57,680 --> 01:11:00,640
Speaker 4: into a tent and tried to grab that and she

1308
01:11:00,720 --> 01:11:04,519
Speaker 4: fought it off, and it actually broke a tooth out

1309
01:11:04,680 --> 01:11:07,519
Speaker 4: of the bear's head in her arm.

1310
01:11:08,280 --> 01:11:11,040
Speaker 1: Wow. Yeah, it's weird, like all the shit he bit

1311
01:11:11,560 --> 01:11:13,679
Speaker 1: in his life that that would break his tooth off.

1312
01:11:13,720 --> 01:11:15,120
Speaker 4: It was It was a sow, but she was so

1313
01:11:15,160 --> 01:11:19,519
Speaker 4: malnourished that she was desperate, and that was Those are

1314
01:11:19,560 --> 01:11:24,960
Speaker 4: predatory attacks, obviously, which is different than your defensive aggressive attacks.

1315
01:11:25,360 --> 01:11:27,960
Speaker 4: So then she, yeah, she went further down the campground

1316
01:11:28,000 --> 01:11:30,360
Speaker 4: and she got in another tent and she killed and

1317
01:11:30,720 --> 01:11:35,040
Speaker 4: ate a guy, and there was three other yearling bears

1318
01:11:35,080 --> 01:11:40,559
Speaker 4: with her through those attacks. So I didn't work up

1319
01:11:40,560 --> 01:11:43,920
Speaker 4: that bear personally, but yeah, I've worked up other bears

1320
01:11:43,920 --> 01:11:44,639
Speaker 4: of mald people.

1321
01:11:46,160 --> 01:11:47,479
Speaker 1: Does that give you a creepy feeling?

1322
01:11:48,280 --> 01:11:48,519
Speaker 5: Mmm?

1323
01:11:49,200 --> 01:11:52,360
Speaker 4: Yeah, I mean I will never forget the look in

1324
01:11:52,400 --> 01:11:54,880
Speaker 4: that bear's eyes. It's so to bete. I mean, she

1325
01:11:55,040 --> 01:11:59,640
Speaker 4: was so demoralized, and yeah, I'll just never forget the

1326
01:11:59,720 --> 01:12:02,960
Speaker 4: way she had her head on her paws and just

1327
01:12:03,000 --> 01:12:04,480
Speaker 4: look completely demoralized.

1328
01:12:05,160 --> 01:12:08,280
Speaker 1: Like what do you mean demoralized? M just.

1329
01:12:10,080 --> 01:12:11,760
Speaker 4: There was like a sadness in her eyes. I don't

1330
01:12:11,800 --> 01:12:12,519
Speaker 4: know how else is that?

1331
01:12:12,680 --> 01:12:12,880
Speaker 1: Right?

1332
01:12:14,160 --> 01:12:15,880
Speaker 4: And you catch a lot of bears and see a

1333
01:12:15,920 --> 01:12:18,280
Speaker 4: lot of bears and traps and they avoid eye contact.

1334
01:12:18,840 --> 01:12:22,400
Speaker 4: That's really normal, but there was just like a feeling

1335
01:12:22,439 --> 01:12:24,320
Speaker 4: about it. I don't know how else to describe it.

1336
01:12:25,120 --> 01:12:29,280
Speaker 1: Hum, when they're avoiding eye contact, what do you think.

1337
01:12:29,160 --> 01:12:33,160
Speaker 4: That is in the bear world? You know, that's aggressive posturing.

1338
01:12:34,120 --> 01:12:36,160
Speaker 1: When I was teaching, eye contact is aggressive.

1339
01:12:36,280 --> 01:12:38,559
Speaker 4: Yeah, when I was teaching kids, i'd say, you know,

1340
01:12:38,680 --> 01:12:41,360
Speaker 4: especially middle school girls, you know, when you see somebody

1341
01:12:41,400 --> 01:12:43,400
Speaker 4: in the hallways and you kind of stare them down,

1342
01:12:44,479 --> 01:12:49,080
Speaker 4: that's aggressive posturing. You know you're being mean, right, And

1343
01:12:49,120 --> 01:12:51,639
Speaker 4: they all understand that and that's the same with bears,

1344
01:12:52,400 --> 01:12:55,320
Speaker 4: is they pretty much avoid eye contact until they're raid

1345
01:12:55,400 --> 01:12:57,479
Speaker 4: to rumble the rate to fight.

1346
01:12:58,360 --> 01:13:00,679
Speaker 1: M so they'll look away from one another.

1347
01:13:01,240 --> 01:13:04,080
Speaker 4: Yeah, yep, those big adult males, when you see them fight,

1348
01:13:04,120 --> 01:13:06,720
Speaker 4: they'll circle each other and they'll be avoiding eye contact,

1349
01:13:06,720 --> 01:13:09,599
Speaker 4: and when they finally get the nerve to lock eyes,

1350
01:13:09,720 --> 01:13:13,519
Speaker 4: that's when they're you know, trying to fight each other.

1351
01:13:14,360 --> 01:13:16,640
Speaker 1: Do you think there's a tell if a bear is

1352
01:13:16,640 --> 01:13:19,120
Speaker 1: gonna falls charge or charge charge? Do you think there's

1353
01:13:19,160 --> 01:13:20,280
Speaker 1: a physical tell? Ye?

1354
01:13:20,880 --> 01:13:24,800
Speaker 4: Head posture, Okay, if they're really intent on hurting you,

1355
01:13:24,880 --> 01:13:27,320
Speaker 4: their head is as low to the ground as possible.

1356
01:13:27,400 --> 01:13:29,920
Speaker 4: They're trying to get there. And you see that with

1357
01:13:29,960 --> 01:13:34,559
Speaker 4: self defense shootings. A lot of times guys aim center mass.

1358
01:13:34,760 --> 01:13:38,120
Speaker 4: Center mass is the hump, you know, and it doesn't

1359
01:13:38,200 --> 01:13:42,439
Speaker 4: kill them. When they're shooting bears. If it's a bluff charge,

1360
01:13:42,479 --> 01:13:44,760
Speaker 4: a lot of times their head is high. You know,

1361
01:13:44,800 --> 01:13:47,360
Speaker 4: they're kind of high on their front legs and they're

1362
01:13:47,400 --> 01:13:55,000
Speaker 4: not coming as fast as they could head down, head down, Yep,

1363
01:13:55,320 --> 01:13:57,920
Speaker 4: aim low.

1364
01:13:56,840 --> 01:14:03,640
Speaker 8: With your spray, yeah, shot, yeah, with your yeah at

1365
01:14:03,640 --> 01:14:06,559
Speaker 8: what let's say, once coming you got prayer spray at

1366
01:14:06,560 --> 01:14:07,240
Speaker 8: what distance?

1367
01:14:07,479 --> 01:14:10,080
Speaker 1: For you personally, Like, at what distance are you touching

1368
01:14:10,080 --> 01:14:10,760
Speaker 1: that spray off?

1369
01:14:10,840 --> 01:14:11,799
Speaker 4: Oh, thirty yards?

1370
01:14:12,400 --> 01:14:14,519
Speaker 1: Yeah, and you're just letting it rip. Let it rip,

1371
01:14:14,920 --> 01:14:16,960
Speaker 1: don't be like trying to don't try to conserve.

1372
01:14:17,600 --> 01:14:21,160
Speaker 4: I would, I'd hold it down for a second and spray,

1373
01:14:21,240 --> 01:14:23,960
Speaker 4: and you know, if it kept coming, I'm going to

1374
01:14:24,040 --> 01:14:27,719
Speaker 4: keep spraying. But yeah, about a second's all it takes.

1375
01:14:29,120 --> 01:14:31,919
Speaker 1: What do you think about the wolverine situation, the wolverine

1376
01:14:31,920 --> 01:14:36,640
Speaker 1: delisting m or sorry, the wolverine listing? Do you think

1377
01:14:36,680 --> 01:14:38,320
Speaker 1: the wolverine listing is warranted?

1378
01:14:41,840 --> 01:14:43,920
Speaker 4: I think we're living in a time and age where

1379
01:14:44,400 --> 01:14:49,000
Speaker 4: a lot wildlife habitats just getting chopped up, and wolverines

1380
01:14:49,080 --> 01:14:54,320
Speaker 4: need a really big home range. And there were links

1381
01:14:54,360 --> 01:14:56,280
Speaker 4: in Wyoming and they just kind of blinked out and

1382
01:14:56,320 --> 01:15:02,120
Speaker 4: nobody ever noticed. So I don't know a ton about wolverines,

1383
01:15:02,160 --> 01:15:06,400
Speaker 4: but I think you probably gotta do everything you can

1384
01:15:06,479 --> 01:15:09,639
Speaker 4: to protect their habitat at this point, you think, so, yeah,

1385
01:15:09,680 --> 01:15:13,479
Speaker 4: and I you know, they just have such a huge

1386
01:15:13,520 --> 01:15:19,719
Speaker 4: home range and this was probably for the south extent

1387
01:15:19,760 --> 01:15:25,120
Speaker 4: of their habitat anyways, Yeah, right well down into Colorado. Yeah,

1388
01:15:25,240 --> 01:15:27,120
Speaker 4: historically they're probably so far down.

1389
01:15:27,840 --> 01:15:29,639
Speaker 1: Yeah, I think that they're using two they use two

1390
01:15:29,680 --> 01:15:30,479
Speaker 1: hundred and fifty.

1391
01:15:30,280 --> 01:15:34,639
Speaker 4: Square miles five hundred five hundred square that's wild, it's more.

1392
01:15:37,840 --> 01:15:39,800
Speaker 4: But same thing with links, you know. They they went

1393
01:15:39,880 --> 01:15:41,640
Speaker 4: really far south. And I had a friend that was

1394
01:15:41,680 --> 01:15:44,400
Speaker 4: a trapper and he'd always say, it's not like the

1395
01:15:44,479 --> 01:15:50,200
Speaker 4: Canadians are excited every time a bobcat crosses into Canada.

1396
01:15:50,600 --> 01:15:51,479
Speaker 1: You know, a good point.

1397
01:15:52,080 --> 01:15:54,920
Speaker 4: It's just we have a different mentality because they're coming south.

1398
01:15:55,680 --> 01:15:57,000
Speaker 1: Yeah, that's a good point.

1399
01:15:57,600 --> 01:15:58,880
Speaker 4: What do you think about wolverines?

1400
01:15:59,360 --> 01:16:07,400
Speaker 1: Man? Uh, I think that they I think that we

1401
01:16:07,520 --> 01:16:14,559
Speaker 1: lack any kind of historic reference. So when someone goes

1402
01:16:14,600 --> 01:16:16,760
Speaker 1: and looks and they think that there's a low number

1403
01:16:16,800 --> 01:16:21,360
Speaker 1: of wolverines that no one's ever looked at it in

1404
01:16:21,360 --> 01:16:24,840
Speaker 1: a sophisticated sense before. One way you could look at

1405
01:16:24,880 --> 01:16:27,719
Speaker 1: the research they did is you'd say, man, there's wolvernes

1406
01:16:27,720 --> 01:16:31,080
Speaker 1: all over the place, right because they go out and

1407
01:16:31,120 --> 01:16:33,120
Speaker 1: do the they hang the carcasses and do the trail

1408
01:16:33,120 --> 01:16:34,360
Speaker 1: camp stuff and catch hairs.

1409
01:16:34,439 --> 01:16:36,240
Speaker 4: Yeah I actually did that one, did you?

1410
01:16:36,640 --> 01:16:39,640
Speaker 1: And so you'd look and be like wow. Like one interpretation,

1411
01:16:39,720 --> 01:16:41,360
Speaker 1: you'd be like, huh, that's cool. There's a lot of

1412
01:16:41,360 --> 01:16:45,559
Speaker 1: wolverines out there because no one knew. But instead you

1413
01:16:45,640 --> 01:16:50,720
Speaker 1: take that you you realize there aren't many, but you

1414
01:16:50,800 --> 01:16:56,559
Speaker 1: don't know how many there ever were, right, and then

1415
01:16:56,600 --> 01:16:59,160
Speaker 1: you point to an area, you know, you point to

1416
01:16:59,160 --> 01:17:02,040
Speaker 1: an area and cannon they had seen a decline, but

1417
01:17:02,080 --> 01:17:04,760
Speaker 1: it's not the same kind of area. You're on the

1418
01:17:04,800 --> 01:17:07,200
Speaker 1: southern edge, and you just go like, there aren't many,

1419
01:17:07,240 --> 01:17:09,920
Speaker 1: therefore they must be endangered. I feel like, without being

1420
01:17:09,960 --> 01:17:14,599
Speaker 1: able to have it, demons like a demonstrated decline over time.

1421
01:17:17,960 --> 01:17:20,000
Speaker 1: I'm a little suspect, and I also I'm a little

1422
01:17:20,000 --> 01:17:22,760
Speaker 1: suspect because I think that they are a I think

1423
01:17:22,800 --> 01:17:27,040
Speaker 1: that it's a little bit of a red herring. I

1424
01:17:27,080 --> 01:17:31,120
Speaker 1: think that they're being used, that they're being used as

1425
01:17:31,200 --> 01:17:33,760
Speaker 1: a tool to get at something that, to get at

1426
01:17:33,760 --> 01:17:34,400
Speaker 1: something different.

1427
01:17:35,800 --> 01:17:38,479
Speaker 4: Sure that's probably saving habitat.

1428
01:17:38,280 --> 01:17:41,240
Speaker 1: Yeah, yeah. And it's like it's like, we want to

1429
01:17:41,280 --> 01:17:45,919
Speaker 1: save habitat, which I totally understand. We want to save habitat,

1430
01:17:46,040 --> 01:17:49,000
Speaker 1: we want to slow certain development. The way to do

1431
01:17:49,080 --> 01:17:53,120
Speaker 1: that is to do the wolverine and get the wolverine listed.

1432
01:17:53,439 --> 01:17:56,000
Speaker 1: But then the wolverine will get listed and it'll wind

1433
01:17:56,080 --> 01:17:58,559
Speaker 1: up being that you'll see that you can't go and

1434
01:17:58,600 --> 01:18:01,760
Speaker 1: snow and beyond certain areas, and you can't trap in

1435
01:18:01,800 --> 01:18:05,120
Speaker 1: certain areas. And you'd be like, but but running a

1436
01:18:05,120 --> 01:18:07,799
Speaker 1: snowmobil and trapping aren't have it. Don't do habitat destruction.

1437
01:18:08,200 --> 01:18:10,080
Speaker 1: If this is all about habitat destruction, why do we

1438
01:18:10,720 --> 01:18:14,320
Speaker 1: do it this way? Well, this is very personal.

1439
01:18:15,200 --> 01:18:18,880
Speaker 3: Yeah, Steve still collecting his thoughts on this subject.

1440
01:18:19,360 --> 01:18:21,280
Speaker 4: You know, back to the point I made earlier about

1441
01:18:21,320 --> 01:18:27,320
Speaker 4: links linking out in Wyoming, there's a chance that part

1442
01:18:27,360 --> 01:18:29,880
Speaker 4: of that was because of snowmobiles and and what that

1443
01:18:30,000 --> 01:18:33,120
Speaker 4: does is creates a path for coyotes to go kill

1444
01:18:33,160 --> 01:18:38,000
Speaker 4: snowshoe hairs, which obviously links are dependent on. Got it,

1445
01:18:38,160 --> 01:18:41,639
Speaker 4: And so you know, it doesn't seem like snowmobiling has

1446
01:18:41,640 --> 01:18:43,200
Speaker 4: an impact, but it.

1447
01:18:43,280 --> 01:18:47,839
Speaker 1: May, you know, one of the weirdest ones of those God.

1448
01:18:47,680 --> 01:18:50,240
Speaker 4: I don't want to be like a making make me

1449
01:18:50,479 --> 01:18:52,679
Speaker 4: sound very green here. That's great.

1450
01:18:53,160 --> 01:18:56,320
Speaker 1: Listen that that's that's that's great for me. I mean, uh,

1451
01:18:57,320 --> 01:18:59,400
Speaker 1: you know, I like it's a it's good things to

1452
01:18:59,680 --> 01:19:04,360
Speaker 1: beerious about. Yeah, uh, think about this. One time we

1453
01:19:04,400 --> 01:19:06,479
Speaker 1: spent a lot of time years ago on when there

1454
01:19:06,560 --> 01:19:10,799
Speaker 1: was still some caribou that were living in the Idaho Panhandle. Yeah,

1455
01:19:10,840 --> 01:19:13,040
Speaker 1: and the efforts to try to save those caribou in

1456
01:19:13,080 --> 01:19:15,200
Speaker 1: the in the Selkirk Range, and they would come into

1457
01:19:15,400 --> 01:19:18,479
Speaker 1: Idaho Panhandle. Sure, right now there's no caribou in the

1458
01:19:18,520 --> 01:19:19,280
Speaker 1: lower forty.

1459
01:19:19,000 --> 01:19:22,760
Speaker 4: Eight Yeah, super sad.

1460
01:19:23,320 --> 01:19:26,320
Speaker 1: When they looked at that. An interesting thing was that

1461
01:19:27,439 --> 01:19:31,280
Speaker 1: they were seeing so much wolf predation on caribou, and

1462
01:19:31,280 --> 01:19:34,559
Speaker 1: it was like, why wasn't there, Like, that's nothing new.

1463
01:19:35,080 --> 01:19:39,760
Speaker 1: You've had wolves on the landscape right in BC. The

1464
01:19:39,760 --> 01:19:42,679
Speaker 1: caribou there, why wasn't it. It was like white tailed

1465
01:19:42,680 --> 01:19:49,280
Speaker 1: deer numbers, like like certain certain timber harvest practices created

1466
01:19:49,280 --> 01:19:53,440
Speaker 1: a lot of white tailed deer and elk and moose habitat.

1467
01:19:54,680 --> 01:19:59,960
Speaker 1: As you brought up that number of ungulates this is

1468
01:20:00,120 --> 01:20:03,440
Speaker 1: theory obviously, as you brought up that number of ungulates

1469
01:20:04,479 --> 01:20:08,640
Speaker 1: at the edge of caribou habitat, it created an incentive

1470
01:20:09,200 --> 01:20:14,040
Speaker 1: for wolves to hunt in the area. And once wolves

1471
01:20:14,160 --> 01:20:15,800
Speaker 1: had taken the habit of hunting in that area, because

1472
01:20:15,800 --> 01:20:20,280
Speaker 1: they're killing deerd or killing moose, they're getting some caribou. Historically,

1473
01:20:20,360 --> 01:20:24,440
Speaker 1: there hadn't been enough like bio mass on the landscape

1474
01:20:24,600 --> 01:20:27,680
Speaker 1: to warrant them hunting the area and they would just

1475
01:20:27,680 --> 01:20:31,559
Speaker 1: be elsewhere. It's a theory, but it's interesting and you

1476
01:20:31,680 --> 01:20:35,240
Speaker 1: think of like like you do this and kylet's now

1477
01:20:35,479 --> 01:20:37,439
Speaker 1: push up on snowbill trails and hunt and they got

1478
01:20:37,439 --> 01:20:39,640
Speaker 1: a way to get from spot to spot and it

1479
01:20:40,600 --> 01:20:44,000
Speaker 1: right right, it's a human cause. It's a human cause,

1480
01:20:44,280 --> 01:20:48,000
Speaker 1: very like step by step, kind of hard to track.

1481
01:20:49,479 --> 01:20:52,479
Speaker 4: Yeah, I think the corequence of events, the correlations probably

1482
01:20:52,520 --> 01:20:56,599
Speaker 4: when snowmobiles got souped up. I'd be curious if that

1483
01:20:56,760 --> 01:21:02,360
Speaker 4: was like the years when when those animal's behavior started

1484
01:21:02,360 --> 01:21:02,840
Speaker 4: to change.

1485
01:21:03,160 --> 01:21:05,080
Speaker 1: Got it when high marking became a thing.

1486
01:21:05,240 --> 01:21:08,280
Speaker 4: Yeah, because when I was growing up, you know, you

1487
01:21:08,360 --> 01:21:10,599
Speaker 4: were about a foot off the ground and that thing

1488
01:21:10,640 --> 01:21:14,120
Speaker 4: didn't go very fast. Yeah, but now you can, you

1489
01:21:14,120 --> 01:21:15,640
Speaker 4: can go anywhere with a snowmobile.

1490
01:21:15,880 --> 01:21:19,439
Speaker 1: Yeah. I picked up a wolverine on a trail camera

1491
01:21:20,640 --> 01:21:21,200
Speaker 1: last year.

1492
01:21:21,479 --> 01:21:23,160
Speaker 4: Yeah, and that's cool.

1493
01:21:23,640 --> 01:21:26,880
Speaker 1: I felt like I was I felt like I was

1494
01:21:26,880 --> 01:21:28,439
Speaker 1: real excited. I sent it to everybody.

1495
01:21:28,520 --> 01:21:34,519
Speaker 4: It was like trapping, Yeah, yeah, it was like trapping

1496
01:21:34,560 --> 01:21:35,040
Speaker 4: to get one.

1497
01:21:35,600 --> 01:21:36,519
Speaker 1: Yeah on a camera.

1498
01:21:36,880 --> 01:21:40,080
Speaker 4: No, We've had some game fish guys get some on cameras,

1499
01:21:40,080 --> 01:21:42,680
Speaker 4: but it's really rare. And when they were doing that

1500
01:21:42,720 --> 01:21:46,639
Speaker 4: population estimate, you know, it was I want to say,

1501
01:21:46,640 --> 01:21:48,840
Speaker 4: not more than five in the whole state, And they

1502
01:21:48,840 --> 01:21:53,720
Speaker 4: put a lot of effort into trying to identify wolverines.

1503
01:21:54,400 --> 01:21:57,080
Speaker 4: Something that was really cool, though, is they had a

1504
01:21:57,080 --> 01:22:00,160
Speaker 4: wolverine that had a white arm with a black spot,

1505
01:22:00,680 --> 01:22:04,880
Speaker 4: so really unique. And she'd actually been caught in the

1506
01:22:04,920 --> 01:22:07,920
Speaker 4: northern part of Yellowstone and had a had a number

1507
01:22:07,960 --> 01:22:10,479
Speaker 4: and I think for a while had a transmitter in

1508
01:22:10,520 --> 01:22:12,760
Speaker 4: her I'm not sure if that's true, but she was

1509
01:22:12,840 --> 01:22:15,519
Speaker 4: fourteen years old. I want to say, wow, r really yep,

1510
01:22:15,720 --> 01:22:17,919
Speaker 4: because they're so identifiable.

1511
01:22:17,240 --> 01:22:19,120
Speaker 1: They knew about how many and Wyoming.

1512
01:22:20,200 --> 01:22:23,800
Speaker 4: Well through all the you know, I think the population

1513
01:22:23,920 --> 01:22:26,679
Speaker 4: estenate is probably twenty Is it that low?

1514
01:22:26,760 --> 01:22:28,479
Speaker 1: Is that low? Yeah?

1515
01:22:29,560 --> 01:22:32,640
Speaker 4: She's really God I might be miss speaking twenty to

1516
01:22:32,680 --> 01:22:43,880
Speaker 4: fifty one hundred, No more than.

1517
01:22:39,800 --> 01:22:42,519
Speaker 1: We got a lot better to tabitat though. Here. Yeah,

1518
01:22:43,400 --> 01:22:44,759
Speaker 1: in the northwest part of the states.

1519
01:22:44,840 --> 01:22:48,400
Speaker 3: So how far away was she she said she was

1520
01:22:48,439 --> 01:22:50,240
Speaker 3: She had been caught in the northern part of Elstone.

1521
01:22:50,280 --> 01:22:52,680
Speaker 3: Do you know where she was then reidentified?

1522
01:22:52,680 --> 01:22:53,320
Speaker 1: How far away?

1523
01:22:53,920 --> 01:23:00,519
Speaker 4: Fish hawks? Probably eighty miles away? Wow, twenty one and

1524
01:23:00,600 --> 01:23:01,080
Speaker 4: twenty two.

1525
01:23:01,640 --> 01:23:06,479
Speaker 6: Wyoming game and fish set approximately twenty four wolverinesh.

1526
01:23:05,560 --> 01:23:06,240
Speaker 1: Look at this guy.

1527
01:23:06,760 --> 01:23:08,280
Speaker 4: It's been a while since I thought about that.

1528
01:23:09,360 --> 01:23:11,679
Speaker 1: Man. It makes my cameras things seem even cooler.

1529
01:23:11,840 --> 01:23:15,280
Speaker 4: You know who you know who? Osborne Russell is sure man.

1530
01:23:15,600 --> 01:23:16,759
Speaker 1: He calls them common.

1531
01:23:17,120 --> 01:23:19,880
Speaker 4: Yeah, and he talks about him in by Salt Lake,

1532
01:23:21,120 --> 01:23:21,840
Speaker 4: So yeah.

1533
01:23:21,720 --> 01:23:23,599
Speaker 1: There's a lot of he calls them common.

1534
01:23:23,800 --> 01:23:28,280
Speaker 3: There's a lot of carkajew references in the Mountain Man journals.

1535
01:23:28,640 --> 01:23:31,479
Speaker 1: Ye know that oral history stuff does because I would

1536
01:23:31,479 --> 01:23:32,840
Speaker 1: not call them common.

1537
01:23:32,880 --> 01:23:36,120
Speaker 4: Right, So there's gotta be more than there is now.

1538
01:23:36,520 --> 01:23:39,600
Speaker 1: Yeah, Osborne Russell, we covered this very We're working on

1539
01:23:39,680 --> 01:23:42,080
Speaker 1: a thing called the Mountain Men. Yeah, sure, part of

1540
01:23:42,120 --> 01:23:46,960
Speaker 1: our American History series. And the other thing that you

1541
01:23:47,000 --> 01:23:51,120
Speaker 1: just wouldn't believe is, uh, the number of big horns.

1542
01:23:51,800 --> 01:23:53,800
Speaker 1: Oh yeah in the early eighteen hundreds.

1543
01:23:53,960 --> 01:23:56,240
Speaker 4: Yeah, like not elk, right.

1544
01:23:57,040 --> 01:24:00,599
Speaker 1: Big horns. Hundreds, like hundreds of big horns.

1545
01:24:01,160 --> 01:24:06,160
Speaker 4: I've talked horns, yeah, big horns and deer. I've talked

1546
01:24:06,160 --> 01:24:10,160
Speaker 4: to Larry Todd about this, and there's only two Indian

1547
01:24:10,240 --> 01:24:14,240
Speaker 4: camps in Wyoming that have elk parts in them. So

1548
01:24:15,880 --> 01:24:18,040
Speaker 4: what I don't understand is there's a really big elk

1549
01:24:18,080 --> 01:24:22,439
Speaker 4: migration that comes from Yellowstone and it goes to south

1550
01:24:22,479 --> 01:24:25,479
Speaker 4: of Kody, and you know, I imagine it's been going on

1551
01:24:25,520 --> 01:24:29,479
Speaker 4: for thousands of years. But you think maybe there weren't

1552
01:24:29,520 --> 01:24:32,559
Speaker 4: that many elk back then, or you know, it's more

1553
01:24:32,560 --> 01:24:33,599
Speaker 4: buffalo than elk.

1554
01:24:33,640 --> 01:24:37,559
Speaker 1: And yeah, Osborne Russell would run into people who were

1555
01:24:38,880 --> 01:24:40,759
Speaker 1: like sheep specialists.

1556
01:24:40,439 --> 01:24:45,839
Speaker 4: Sheep eaters, sheep. Yeah, we have a bunch of artifacts

1557
01:24:45,880 --> 01:24:49,000
Speaker 4: around us that were sheep eater artifacts. They're they're part

1558
01:24:49,000 --> 01:24:53,160
Speaker 4: of the Shoshown tribe. But we just learned.

1559
01:24:53,200 --> 01:24:54,240
Speaker 3: That's why I scratched it.

1560
01:24:54,880 --> 01:24:57,000
Speaker 1: I asked, I actually asked as a person.

1561
01:24:57,200 --> 01:25:02,240
Speaker 4: Yea, well I've never known, only preferred. Yeah, that's the

1562
01:25:02,360 --> 01:25:03,479
Speaker 4: river that flows through Cody.

1563
01:25:04,520 --> 01:25:10,240
Speaker 1: That's yeah, that's that's what got Yeah, you're sitting in Okay.

1564
01:25:10,360 --> 01:25:14,559
Speaker 3: Well he would know the rivers and the places go

1565
01:25:14,640 --> 01:25:17,559
Speaker 3: by Shoshone, but the people go by Shoshone is sort.

1566
01:25:17,360 --> 01:25:20,760
Speaker 1: Of what he was. He was a rapp a hole. Yeah,

1567
01:25:20,840 --> 01:25:23,760
Speaker 1: but he lives with Yeah, lives. Yeah, that's true.

1568
01:25:24,080 --> 01:25:26,439
Speaker 3: The conclusion we collectively arrived at.

1569
01:25:28,160 --> 01:25:30,479
Speaker 4: Have you ever seen the bows that those sheep eaters make?

1570
01:25:30,680 --> 01:25:33,280
Speaker 1: No? But I read Osborne Russell's description of the bows.

1571
01:25:34,680 --> 01:25:37,320
Speaker 4: Yeah, they're pretty cool. There's a guy named Bob Lucas

1572
01:25:37,479 --> 01:25:40,360
Speaker 4: that there's a video of him making one. But they

1573
01:25:40,760 --> 01:25:43,519
Speaker 4: take a big horn, sheep horn, and they reverse the

1574
01:25:43,600 --> 01:25:46,880
Speaker 4: curl and then they glue it and tie it together

1575
01:25:46,960 --> 01:25:48,639
Speaker 4: and it's basically a recurved bow.

1576
01:25:49,080 --> 01:25:50,840
Speaker 1: They steam it, reverse it right yep.

1577
01:25:52,680 --> 01:25:52,800
Speaker 7: Uh.

1578
01:25:53,240 --> 01:25:57,720
Speaker 1: Osborne Russell figures very heavily into our into the thing

1579
01:25:57,760 --> 01:26:00,439
Speaker 1: we're working on because he did such.

1580
01:26:00,280 --> 01:26:02,200
Speaker 4: A good job of documenting stuff.

1581
01:26:02,400 --> 01:26:08,520
Speaker 1: Yeah, such a phenomenal job of making a journal. Uh.

1582
01:26:08,920 --> 01:26:10,800
Speaker 1: Tell me about your guide in business? Who do you

1583
01:26:10,840 --> 01:26:11,280
Speaker 1: guide for?

1584
01:26:12,600 --> 01:26:16,160
Speaker 4: I've guided for a bunch of different outfitters, to be honest,

1585
01:26:16,240 --> 01:26:19,840
Speaker 4: and I took this season pretty much off because I

1586
01:26:19,920 --> 01:26:25,360
Speaker 4: just had a kid. But I've worked for Yellowstone Country Outfitters,

1587
01:26:25,520 --> 01:26:31,160
Speaker 4: three oh seven Outfitters, ran Crick Outfitters, Livingstone Outfitters. So

1588
01:26:31,360 --> 01:26:33,080
Speaker 4: I've got to see a lot of country.

1589
01:26:32,880 --> 01:26:34,679
Speaker 1: And your specialty these horseback trips.

1590
01:26:35,120 --> 01:26:42,640
Speaker 4: Yeah, everything's horseback, horseback and mule sawbucks or deckers sawbuck guy. Yeah,

1591
01:26:42,840 --> 01:26:46,080
Speaker 4: I've never understood that though. Montana guys. Yeah, I can't

1592
01:26:46,080 --> 01:26:48,639
Speaker 4: take a toothbrush if they don't man yet.

1593
01:26:49,080 --> 01:26:49,320
Speaker 1: You know.

1594
01:26:50,680 --> 01:26:52,519
Speaker 3: Yeah, I've always thought the same thing.

1595
01:26:53,439 --> 01:26:56,960
Speaker 4: Yeah, we always laugh at Sawbucks. Yeah, you'll have to

1596
01:26:57,000 --> 01:27:00,000
Speaker 4: teach me, so all right, Yeah, trade seems pretty easy.

1597
01:27:01,600 --> 01:27:04,360
Speaker 4: So there's two style of pack saddles. One is what

1598
01:27:04,439 --> 01:27:10,439
Speaker 4: you call sawbook, which is seems self explanatory. You hang

1599
01:27:10,560 --> 01:27:12,599
Speaker 4: paniards and then you have a lash rope where you

1600
01:27:12,640 --> 01:27:17,520
Speaker 4: tie a hitch so keep everything pinned down. And Montana

1601
01:27:17,560 --> 01:27:23,200
Speaker 4: guys run what's called decker pack saddles, and they have

1602
01:27:23,360 --> 01:27:27,200
Speaker 4: ropes hanging off the bars on their packs and then

1603
01:27:27,560 --> 01:27:32,120
Speaker 4: they tie a hitch, usually with something that's man eat up,

1604
01:27:32,360 --> 01:27:38,320
Speaker 4: so they pack all their camping stuff in a in

1605
01:27:38,400 --> 01:27:45,639
Speaker 4: a canvas manny and fold it up real nice, like yeah, manny,

1606
01:27:45,640 --> 01:27:50,519
Speaker 4: petty sort, you're tracking, you're tracking? Help me out here.

1607
01:27:50,960 --> 01:27:52,040
Speaker 6: Yeah, no, that's accurate.

1608
01:27:52,120 --> 01:27:53,040
Speaker 4: I don't know what you don't know.

1609
01:27:53,160 --> 01:27:56,760
Speaker 6: My theory is decker like when you lash down at

1610
01:27:57,240 --> 01:28:01,200
Speaker 6: decker saddle, say with a YETI cool, And then you

1611
01:28:01,240 --> 01:28:03,320
Speaker 6: can crow's foot it to really lash it down. You

1612
01:28:03,320 --> 01:28:05,479
Speaker 6: can bump into a lot more trees and have it

1613
01:28:05,520 --> 01:28:09,479
Speaker 6: stays stay set. Compared to Sawbucks, addles might move around

1614
01:28:09,479 --> 01:28:11,599
Speaker 6: a little bit more or get loose.

1615
01:28:12,320 --> 01:28:12,800
Speaker 3: I don't know.

1616
01:28:13,520 --> 01:28:16,160
Speaker 4: I've never some pretty steep country.

1617
01:28:15,960 --> 01:28:18,720
Speaker 6: Well steep maybe how thick is it?

1618
01:28:18,720 --> 01:28:21,920
Speaker 4: It's pretty thick. Well, it sounds like.

1619
01:28:24,360 --> 01:28:26,599
Speaker 3: I guess whatever style floats your boat.

1620
01:28:26,800 --> 01:28:29,639
Speaker 4: I know that you can pack real awkward loads with deckers.

1621
01:28:29,680 --> 01:28:30,839
Speaker 4: They're a lot more versatile.

1622
01:28:31,000 --> 01:28:34,519
Speaker 6: Yeah, we would pack raft frames sixteen foot raft rames

1623
01:28:35,040 --> 01:28:37,040
Speaker 6: them on the uphill side.

1624
01:28:37,280 --> 01:28:40,880
Speaker 4: Okay, yeah, we just don't take that stuff. So yeah,

1625
01:28:41,120 --> 01:28:41,679
Speaker 4: very awkward?

1626
01:28:42,280 --> 01:28:43,880
Speaker 1: Are you mostly deer? Mostly elk?

1627
01:28:44,400 --> 01:28:50,080
Speaker 4: I've done it all sheep, mountain goat deer elk, not

1628
01:28:50,160 --> 01:28:54,800
Speaker 4: grizzly bear, but everything else. Uh no, never have a

1629
01:28:54,800 --> 01:28:56,800
Speaker 4: guated black bears. Actually kind of got burned out on

1630
01:28:56,840 --> 01:28:57,719
Speaker 4: the bear thing, so.

1631
01:28:57,800 --> 01:28:59,960
Speaker 1: Oh, messing with bears like a person gets a job

1632
01:29:00,040 --> 01:29:01,160
Speaker 1: to ice cream shop, then.

1633
01:29:01,040 --> 01:29:05,320
Speaker 4: I don't like ice cream no more, exactly exactly the

1634
01:29:05,400 --> 01:29:07,080
Speaker 4: same reason I don't eat Mexican FID.

1635
01:29:07,880 --> 01:29:10,839
Speaker 1: And you're and you're looking for your ear between careers.

1636
01:29:10,840 --> 01:29:14,639
Speaker 4: Now you know I'm doing construction, but I'm definitely open

1637
01:29:14,760 --> 01:29:18,800
Speaker 4: to doing something that benefits wildlife. I don't want the

1638
01:29:18,840 --> 01:29:21,839
Speaker 4: best thing that I've done for wildlife to be catching

1639
01:29:21,880 --> 01:29:23,040
Speaker 4: and killing bears.

1640
01:29:23,280 --> 01:29:26,599
Speaker 1: So what drove you to do? You mind saying why

1641
01:29:26,600 --> 01:29:29,679
Speaker 1: did you leave the state agency in Wyoming fishing game.

1642
01:29:30,080 --> 01:29:32,840
Speaker 4: I was just really personally conflicted with some of the

1643
01:29:32,960 --> 01:29:36,599
Speaker 4: management decisions that were being made. You know, So there

1644
01:29:36,640 --> 01:29:39,719
Speaker 4: were a lot of reasons I was. I was super burnout.

1645
01:29:40,040 --> 01:29:42,280
Speaker 4: If I had to give one more bear safety talk,

1646
01:29:42,360 --> 01:29:47,280
Speaker 4: I was gonna suck start a forty four? God what

1647
01:29:47,400 --> 01:29:48,040
Speaker 4: or bear spray?

1648
01:29:48,160 --> 01:29:51,040
Speaker 1: What would be at what would be an area of management? Like,

1649
01:29:51,080 --> 01:29:53,320
Speaker 1: what would be like an area of management that you

1650
01:29:53,360 --> 01:29:55,360
Speaker 1: would find conflict. You don't need to tell me the

1651
01:29:55,400 --> 01:29:57,559
Speaker 1: exact conflict, but when you say that, what do you mean?

1652
01:29:58,880 --> 01:29:59,360
Speaker 1: What do you mean?

1653
01:29:59,400 --> 01:30:00,240
Speaker 4: What do you mean? Like?

1654
01:30:00,320 --> 01:30:04,600
Speaker 1: Do you mean the way they sat harvest objectives?

1655
01:30:05,280 --> 01:30:05,400
Speaker 2: Oh?

1656
01:30:05,960 --> 01:30:08,360
Speaker 1: The way they where I had conflict? Or was it

1657
01:30:08,439 --> 01:30:10,439
Speaker 1: like administrative issues? You know?

1658
01:30:11,920 --> 01:30:14,639
Speaker 4: Yeah, it was leadership and it I just didn't feel

1659
01:30:14,720 --> 01:30:20,040
Speaker 4: like relocation and removal decisions were really consistent.

1660
01:30:20,240 --> 01:30:22,600
Speaker 3: So god, oh on the bear question, yeah, it's like

1661
01:30:22,640 --> 01:30:24,360
Speaker 3: how you're handling individual bears.

1662
01:30:24,640 --> 01:30:28,280
Speaker 4: Yeah, yeah, you know, I'd had a certain standard with

1663
01:30:28,400 --> 01:30:32,479
Speaker 4: my old boss, and I just felt like it wasn't

1664
01:30:32,520 --> 01:30:32,880
Speaker 4: the same.

1665
01:30:35,520 --> 01:30:37,800
Speaker 1: Do you is my last question for you? Do you

1666
01:30:38,479 --> 01:30:40,840
Speaker 1: give me your personal take? I like, like came in

1667
01:30:40,880 --> 01:30:43,120
Speaker 1: so hot and heavy on delisting. What's your personal take?

1668
01:30:43,160 --> 01:30:43,799
Speaker 1: On delisting.

1669
01:30:45,120 --> 01:30:49,960
Speaker 4: Hmmm. I think it's the best thing to keep states

1670
01:30:50,000 --> 01:30:53,280
Speaker 4: into managing bears, which is probably the best thing for

1671
01:30:53,479 --> 01:30:56,960
Speaker 4: the people on the landscape. And I also think hunting

1672
01:30:57,120 --> 01:31:02,200
Speaker 4: is a positive because it creates its advocates for wildlife,

1673
01:31:02,280 --> 01:31:06,840
Speaker 4: creates advocates for bears. People right now say there's too

1674
01:31:06,880 --> 01:31:09,400
Speaker 4: many bears on the landscape, but as soon as you

1675
01:31:09,439 --> 01:31:11,559
Speaker 4: start hunting them, they'll be like, I don't know where

1676
01:31:11,560 --> 01:31:16,400
Speaker 4: all the big bears have gone. These guys are hunting

1677
01:31:16,439 --> 01:31:19,520
Speaker 4: too many. It's a non residence.

1678
01:31:19,760 --> 01:31:22,120
Speaker 3: Yeah, it'll just be some other boogeyman.

1679
01:31:22,400 --> 01:31:23,679
Speaker 1: Yeah, yeah, that's a good point.

1680
01:31:23,720 --> 01:31:29,000
Speaker 4: Man. So, but they continue to expand. And a big

1681
01:31:29,040 --> 01:31:34,679
Speaker 4: issue that the court see is that genetic connectivity between

1682
01:31:34,800 --> 01:31:39,280
Speaker 4: the GYE and the NCDE, and right now they're only

1683
01:31:39,320 --> 01:31:43,439
Speaker 4: thirty six miles apart. And I think that whether you

1684
01:31:43,560 --> 01:31:47,559
Speaker 4: delist or not, I think they eventually make that connectivity.

1685
01:31:48,520 --> 01:31:50,479
Speaker 4: But there was a bear that showed up in the

1686
01:31:50,479 --> 01:31:56,120
Speaker 4: Big Horns two years ago actually, and you know that

1687
01:31:56,160 --> 01:32:00,599
Speaker 4: bear was removed ethanized right away. And I think they're

1688
01:32:00,640 --> 01:32:03,960
Speaker 4: going to continue to expand whether you try to contain

1689
01:32:04,000 --> 01:32:04,479
Speaker 4: them or not.

1690
01:32:04,760 --> 01:32:06,400
Speaker 1: Oh, was that a containment decision?

1691
01:32:08,880 --> 01:32:13,360
Speaker 4: Social acceptance, you know, but we've caught and killed a

1692
01:32:13,400 --> 01:32:16,679
Speaker 4: lot of bears over the years, and you're just trying

1693
01:32:16,720 --> 01:32:19,760
Speaker 4: to contain them into the absorcos. This year, they'll hit

1694
01:32:19,840 --> 01:32:25,879
Speaker 4: seventy bears have died in the Elstone ecosystem, and probably

1695
01:32:25,920 --> 01:32:30,040
Speaker 4: forty of those will be management removals. And you got

1696
01:32:30,080 --> 01:32:36,800
Speaker 4: everything from bears getting killed in irrigation canals, there were

1697
01:32:37,000 --> 01:32:41,519
Speaker 4: bears electrocuted. There's bears that get hit by vehicles, like

1698
01:32:41,560 --> 01:32:44,240
Speaker 4: three ninety nine obviously, so.

1699
01:32:46,080 --> 01:32:47,439
Speaker 1: Seventy to one calendar year.

1700
01:32:47,720 --> 01:32:49,400
Speaker 4: Yeah, I think it'll be a record year this year.

1701
01:32:49,640 --> 01:32:52,360
Speaker 6: Montana's at twenty eight right now.

1702
01:32:54,160 --> 01:32:57,280
Speaker 4: I don't think it's over yet. There's still bears out.

1703
01:33:00,439 --> 01:33:03,200
Speaker 1: One of the uh one of the arguments I heard

1704
01:33:03,240 --> 01:33:06,320
Speaker 1: from when I talked about I was joking and I

1705
01:33:06,439 --> 01:33:08,920
Speaker 1: half joking about Montana chickening out on the bear hunt.

1706
01:33:08,920 --> 01:33:10,519
Speaker 1: But one of the things they brought up is they

1707
01:33:10,560 --> 01:33:18,920
Speaker 1: had no They felt that their quota would get hit

1708
01:33:19,000 --> 01:33:24,120
Speaker 1: by non hunting purposes and if they did a hunt.

1709
01:33:24,600 --> 01:33:27,800
Speaker 4: This is kind of like the logic, right, Yeah.

1710
01:33:27,360 --> 01:33:29,799
Speaker 1: If they did a hunt and killed a couple bears,

1711
01:33:31,200 --> 01:33:34,479
Speaker 1: they would burn up their quota and then they wouldn't

1712
01:33:34,479 --> 01:33:36,840
Speaker 1: be able to do bear management on problem bears because

1713
01:33:36,840 --> 01:33:39,160
Speaker 1: they would have already hit their human Cause quota.

1714
01:33:41,640 --> 01:33:42,840
Speaker 3: Doesn't sound unreasonable.

1715
01:33:43,040 --> 01:33:45,880
Speaker 1: Fee feels more across that bridge when you come to it.

1716
01:33:46,400 --> 01:33:50,639
Speaker 4: Yeah, I think again, it's what you what the number

1717
01:33:50,680 --> 01:33:53,960
Speaker 4: you believe is in the ecosystem. And the reason Wyoming

1718
01:33:54,080 --> 01:33:57,720
Speaker 4: was going to be so high is because twelve of

1719
01:33:57,760 --> 01:34:01,120
Speaker 4: those bears were going to be outside the demographic monitoring area,

1720
01:34:01,200 --> 01:34:03,400
Speaker 4: so they weren't even counted towards the population.

1721
01:34:03,600 --> 01:34:06,160
Speaker 1: Got it, got.

1722
01:34:05,960 --> 01:34:09,719
Speaker 4: It, you know. And the DMA is about twenty thousand

1723
01:34:09,800 --> 01:34:13,799
Speaker 4: square miles and bear distribution right now is about fifty

1724
01:34:13,880 --> 01:34:14,920
Speaker 4: thousand square miles.

1725
01:34:15,800 --> 01:34:21,720
Speaker 1: Oh, it's a grizzly coming to a neighborhood near you.

1726
01:34:22,520 --> 01:34:26,000
Speaker 4: Yeah. So everywhere I would go, people go, there's kids

1727
01:34:26,000 --> 01:34:28,040
Speaker 4: in the neighborhood. You got to get this bear out

1728
01:34:28,040 --> 01:34:30,040
Speaker 4: of here, you know. And then one lady called me

1729
01:34:30,080 --> 01:34:32,960
Speaker 4: and she goes, there's old people in this neighborhood. You

1730
01:34:33,040 --> 01:34:35,320
Speaker 4: got to get this bear out of here. I'm like, Oh,

1731
01:34:35,360 --> 01:34:38,519
Speaker 4: there's no appropriate age to live with a bear.

1732
01:34:38,920 --> 01:34:40,880
Speaker 1: There's two things that are going to happen. I like

1733
01:34:40,880 --> 01:34:44,640
Speaker 1: to joke about golfers and Montana is uniquely created a

1734
01:34:44,640 --> 01:34:50,680
Speaker 1: golfer Gophers. No, I believe that someday Montana will have

1735
01:34:50,720 --> 01:34:54,720
Speaker 1: a golfer get mall about golfing, oh in Whitefish.

1736
01:34:55,320 --> 01:34:58,280
Speaker 6: Yeah, probably at Meadow Lake Resort, Columbia Fall the big

1737
01:34:58,280 --> 01:34:58,880
Speaker 6: scot they.

1738
01:34:58,800 --> 01:35:00,559
Speaker 3: Called one on a golf course down the bitter.

1739
01:35:00,880 --> 01:35:03,240
Speaker 1: Yeah, we will have. It'll be like it'll be I

1740
01:35:03,240 --> 01:35:05,680
Speaker 1: hope he doesn't get it bad. If he gets a

1741
01:35:05,760 --> 01:35:10,439
Speaker 1: bad I'll feel bad. But I I uh, it'll be

1742
01:35:10,479 --> 01:35:12,439
Speaker 1: an interesting day when we have a golfer get malb

1743
01:35:13,160 --> 01:35:14,280
Speaker 1: digging through the rough looking.

1744
01:35:16,960 --> 01:35:18,880
Speaker 3: It's probably not gonna be a good golfer because he's

1745
01:35:18,880 --> 01:35:20,519
Speaker 3: gonna be sticking to the fairways.

1746
01:35:20,520 --> 01:35:22,240
Speaker 1: And yeah, he's gonna be down to the dick. He's

1747
01:35:22,240 --> 01:35:23,800
Speaker 1: gonna be down to the creek bottom looking for his

1748
01:35:23,840 --> 01:35:24,320
Speaker 1: golf ball.

1749
01:35:24,320 --> 01:35:25,920
Speaker 4: Another good reason to work on your backswing.

1750
01:35:26,320 --> 01:35:28,519
Speaker 1: We're gonna have a golfer, get Mall, and that's going

1751
01:35:28,600 --> 01:35:32,200
Speaker 1: to change public opinion. And then for whatever reason, like

1752
01:35:32,240 --> 01:35:32,879
Speaker 1: we have a little.

1753
01:35:32,720 --> 01:35:36,479
Speaker 4: Mountain range right here in town Bridgers, Uh, you know,

1754
01:35:36,560 --> 01:35:37,160
Speaker 4: not right here.

1755
01:35:37,160 --> 01:35:39,559
Speaker 1: I mean it's way bigger than that. But it toes

1756
01:35:39,600 --> 01:35:43,880
Speaker 1: off like this, you know, toes off into town and man,

1757
01:35:43,880 --> 01:35:44,680
Speaker 1: there's grizzlies right.

1758
01:35:44,640 --> 01:35:47,720
Speaker 4: Across the highway, I know, thirty six miles.

1759
01:35:47,560 --> 01:35:50,320
Speaker 1: And it's like, at some point in time, this is

1760
01:35:50,320 --> 01:35:52,960
Speaker 1: we have this real popular hiking trail called the m Yeah,

1761
01:35:53,000 --> 01:35:57,840
Speaker 1: it's not out of the it's not out of it's

1762
01:35:57,840 --> 01:36:00,360
Speaker 1: like a reasonable thing that someone's gonna get scratch on

1763
01:36:00,439 --> 01:36:03,839
Speaker 1: the m Hill. I feel like that'll impact public opinion

1764
01:36:04,560 --> 01:36:06,800
Speaker 1: when a golf forgets it. Yeah.

1765
01:36:06,800 --> 01:36:10,479
Speaker 3: I mean there is in Missoula the Rattlesnake Wilderness right there.

1766
01:36:11,040 --> 01:36:12,720
Speaker 3: You know, you can take a city bus to it,

1767
01:36:12,880 --> 01:36:14,760
Speaker 3: and they had a sow and cubs that set up

1768
01:36:14,800 --> 01:36:16,600
Speaker 3: in one of the first gulches there. That's like a

1769
01:36:16,600 --> 01:36:20,040
Speaker 3: really popular mountain biking area. But I remember going to

1770
01:36:20,080 --> 01:36:23,519
Speaker 3: an event and there's a bear biologist there talking about

1771
01:36:23,640 --> 01:36:27,720
Speaker 3: grizzlies coming into the Missoula area, and he's like, you know,

1772
01:36:27,760 --> 01:36:30,280
Speaker 3: they're in Gold Creek, they're down on the golf courses

1773
01:36:30,320 --> 01:36:33,840
Speaker 3: in the bitter Root, they're in the Rattlesnake. And he said,

1774
01:36:34,920 --> 01:36:37,400
Speaker 3: I would be surprised if in five years there aren't

1775
01:36:37,760 --> 01:36:45,080
Speaker 3: sort of resident known bear families, you know, population groups

1776
01:36:45,160 --> 01:36:48,120
Speaker 3: here and there in the city around the city.

1777
01:36:48,160 --> 01:36:50,280
Speaker 1: I should say, I don't want people to think I'm

1778
01:36:50,280 --> 01:36:52,800
Speaker 1: bringing that up like a golfer getting scratched. I'm not

1779
01:36:52,840 --> 01:36:54,679
Speaker 1: bringing this up as a thing that I'm worried about,

1780
01:36:56,880 --> 01:36:58,800
Speaker 1: and I don't think it's a negative. I mean, I'm

1781
01:36:58,800 --> 01:37:01,400
Speaker 1: not the golfer get scratched. I'm not saying I want,

1782
01:37:01,439 --> 01:37:03,320
Speaker 1: I don't want. I think I'd love it if we

1783
01:37:03,360 --> 01:37:05,679
Speaker 1: had bears. I'd like if there's grizzlies all over town,

1784
01:37:08,200 --> 01:37:12,400
Speaker 1: like go to Anchorage. Yeah for sure. Yeah, yeah, yeah,

1785
01:37:12,680 --> 01:37:17,000
Speaker 1: I like them. Yeah, I'm not an anti bear guy whatsoever. Right,

1786
01:37:17,040 --> 01:37:19,559
Speaker 1: I love the bears. I like seeing them. I get

1787
01:37:19,560 --> 01:37:21,439
Speaker 1: excited I see him anyway. You never I never meet

1788
01:37:21,439 --> 01:37:24,639
Speaker 1: anybody who's bummed out that they saw a grizzly. Yeah,

1789
01:37:25,040 --> 01:37:25,719
Speaker 1: I love them.

1790
01:37:25,840 --> 01:37:28,599
Speaker 4: As soon as you get mauled, people's attitude sure changes.

1791
01:37:28,720 --> 01:37:30,519
Speaker 1: I love them. I just want it to go. I

1792
01:37:30,560 --> 01:37:32,600
Speaker 1: want to be that there's a bunch of bears, and

1793
01:37:32,600 --> 01:37:35,000
Speaker 1: I want it to be that there's there's a state

1794
01:37:35,080 --> 01:37:37,160
Speaker 1: managed and there's a tag draw. That's what I want.

1795
01:37:37,680 --> 01:37:42,000
Speaker 4: Yeah, everybody thinks about their self interest, right, especially me. Yeah,

1796
01:37:43,080 --> 01:37:46,080
Speaker 4: I think it's the story that you that you portray

1797
01:37:46,120 --> 01:37:50,960
Speaker 4: into the future. Here how people paint bears. So three

1798
01:37:51,080 --> 01:37:53,120
Speaker 4: ninety nine is a great example, Like you could paint

1799
01:37:53,160 --> 01:37:56,439
Speaker 4: her as a bear that mould people, or you could

1800
01:37:56,439 --> 01:37:59,880
Speaker 4: paint her as the biggest advocate for bears in the

1801
01:38:00,120 --> 01:38:03,880
Speaker 4: mm hmm in the world. So yeah, future bears is

1802
01:38:04,360 --> 01:38:05,080
Speaker 4: up to the public.

1803
01:38:05,160 --> 01:38:08,960
Speaker 1: Really. Yeah, and my you know, you mentioned like everybody

1804
01:38:09,000 --> 01:38:12,679
Speaker 1: wants what their own self interest is. I should clarify that. Uh,

1805
01:38:13,000 --> 01:38:15,479
Speaker 1: I'm not gonna draw a Grizzly bear tag. I live

1806
01:38:15,520 --> 01:38:19,360
Speaker 1: in a state that one had they done, I don't

1807
01:38:19,400 --> 01:38:21,320
Speaker 1: know that. I orn't even put in for the tag. Yeah,

1808
01:38:22,520 --> 01:38:26,320
Speaker 1: uh we didn't do it. If we did one, you're

1809
01:38:26,320 --> 01:38:27,679
Speaker 1: not gonna draw it. I mean, what are the odds

1810
01:38:27,680 --> 01:38:29,880
Speaker 1: you're gonna draw it? You know. It's like I've been

1811
01:38:29,960 --> 01:38:33,240
Speaker 1: applying for big horn sheep tag for decades, haven't drawn

1812
01:38:33,280 --> 01:38:33,679
Speaker 1: one yet.

1813
01:38:33,720 --> 01:38:36,120
Speaker 7: I a lot.

1814
01:38:36,560 --> 01:38:39,400
Speaker 1: No, not not like, yeah, you get you're not gonna draw,

1815
01:38:39,520 --> 01:38:41,360
Speaker 1: Like the draws are gonna be slim. So it's not

1816
01:38:41,400 --> 01:38:44,920
Speaker 1: like it's not like I feel that this is my pathway. Yeah,

1817
01:38:45,040 --> 01:38:47,080
Speaker 1: I mean I hunt the last every year. This isn't

1818
01:38:47,120 --> 01:38:49,479
Speaker 1: my like, I'm not pursuing this as because it's my

1819
01:38:49,560 --> 01:38:52,040
Speaker 1: personal pathway to getting a Grizzly. It's like it's not

1820
01:38:52,080 --> 01:38:55,080
Speaker 1: gonna happen. I'm not going to get a grizzly in Montana.

1821
01:38:55,080 --> 01:38:56,640
Speaker 1: I'm not gonna get a grizzy in Idahol. I'm not

1822
01:38:56,640 --> 01:38:59,439
Speaker 1: gonna get a grizzy in Wyoming. This isn't all me,

1823
01:39:00,320 --> 01:39:03,920
Speaker 1: you know, with some like Machiavellian plan by which I'll

1824
01:39:03,960 --> 01:39:06,960
Speaker 1: be able to hunt grizzlies in my neighborhood. It's like,

1825
01:39:07,120 --> 01:39:11,040
Speaker 1: just as an advocate four hunters, and as an advocate

1826
01:39:11,120 --> 01:39:14,880
Speaker 1: for state management, and as an advocate for responsible use

1827
01:39:14,920 --> 01:39:19,720
Speaker 1: of renewable resources, here's an animal that that people, that

1828
01:39:19,840 --> 01:39:24,040
Speaker 1: has was historically a game animal that has people that

1829
01:39:24,160 --> 01:39:26,640
Speaker 1: there's people that hunt them in other places, there's a

1830
01:39:26,720 --> 01:39:31,720
Speaker 1: desire to hunt them. Hunting them is not incompatible with

1831
01:39:32,000 --> 01:39:35,719
Speaker 1: having a stable population, as we've demonstrated with mountain lions,

1832
01:39:35,840 --> 01:39:39,080
Speaker 1: black bears, white tailed deer, mule deer, elk moose, big

1833
01:39:39,120 --> 01:39:41,160
Speaker 1: orange sheep, mountain goats. I could go on and on.

1834
01:39:41,920 --> 01:39:44,560
Speaker 1: It's not incompatible. I don't know why there should be

1835
01:39:44,600 --> 01:39:45,080
Speaker 1: any different.

1836
01:39:45,920 --> 01:39:46,800
Speaker 4: This guy's put in.

1837
01:39:50,040 --> 01:39:51,640
Speaker 1: You know what I'll do right now? You know what

1838
01:39:51,640 --> 01:39:55,000
Speaker 1: I'm gonna do right now now, I'm gonna tell you something.

1839
01:39:55,080 --> 01:39:57,479
Speaker 1: Right now, I'm gonna tell you something right now, just

1840
01:39:57,520 --> 01:40:00,479
Speaker 1: because you said that, I promise I won't put in. Okay,

1841
01:40:00,640 --> 01:40:04,320
Speaker 1: for how long ever, I won't.

1842
01:40:04,120 --> 01:40:04,400
Speaker 2: Put it in.

1843
01:40:05,080 --> 01:40:05,760
Speaker 1: I won't put in.

1844
01:40:06,000 --> 01:40:07,000
Speaker 4: It's a true advocate.

1845
01:40:07,479 --> 01:40:09,200
Speaker 1: And you go scroll the records and see if you

1846
01:40:09,280 --> 01:40:10,680
Speaker 1: ever see me put in, I won't put in.

1847
01:40:11,320 --> 01:40:12,599
Speaker 4: I got friends I'll call.

1848
01:40:13,120 --> 01:40:16,960
Speaker 1: I'm not going to put it. I said one time before,

1849
01:40:17,080 --> 01:40:20,360
Speaker 1: like to talk about in drilling an ant war. Yeah,

1850
01:40:20,400 --> 01:40:21,880
Speaker 1: And people are like, oh yeah, just because you hunt

1851
01:40:21,920 --> 01:40:23,760
Speaker 1: up there all the time. I'm like, okay, if I

1852
01:40:23,760 --> 01:40:25,920
Speaker 1: could sign a contract that said they won't drill an

1853
01:40:26,040 --> 01:40:28,799
Speaker 1: war but I can't ever go there, I would sign.

1854
01:40:28,640 --> 01:40:32,360
Speaker 4: The contract right me too, I'm not going there.

1855
01:40:32,439 --> 01:40:34,240
Speaker 1: Yeah, it's like okay, fine, I need to go there,

1856
01:40:34,320 --> 01:40:37,720
Speaker 1: just whatever. That's fine. And if I had to sign

1857
01:40:37,760 --> 01:40:41,280
Speaker 1: a contract, we'll dlist and turn over to State management

1858
01:40:41,280 --> 01:40:43,160
Speaker 1: and create a hunting season tomorrow, but you have to

1859
01:40:43,200 --> 01:40:45,639
Speaker 1: agree that you'll never apply for a tag. I'd be like, okay, cool,

1860
01:40:47,960 --> 01:40:48,960
Speaker 1: that's not what it is for me.

1861
01:40:49,680 --> 01:40:52,760
Speaker 4: I think the real question here is can you get

1862
01:40:53,080 --> 01:40:57,960
Speaker 4: bears off the list? Can you have state management without

1863
01:40:58,160 --> 01:41:02,200
Speaker 4: people continuing to sue and and tear down the ESA,

1864
01:41:02,400 --> 01:41:05,439
Speaker 4: or do you have to change the ESA in order

1865
01:41:05,560 --> 01:41:08,400
Speaker 4: to get animals delisted, and I think that would be

1866
01:41:08,439 --> 01:41:12,320
Speaker 4: horrible if if you don't get bears off the list.

1867
01:41:12,840 --> 01:41:16,360
Speaker 1: You know, That's why my advice to people who support

1868
01:41:16,360 --> 01:41:19,880
Speaker 1: the ESA is to stop effing around with the essay,

1869
01:41:20,280 --> 01:41:23,800
Speaker 1: what weaponizing it, because you're gonna, you're gonna, you're gonna

1870
01:41:23,800 --> 01:41:26,559
Speaker 1: do You're gonna do to the essay what they did

1871
01:41:26,600 --> 01:41:30,479
Speaker 1: to the spot at owl. Like the spot at Owl

1872
01:41:30,600 --> 01:41:33,960
Speaker 1: used to be an owl, yeah, and then it became

1873
01:41:34,040 --> 01:41:39,280
Speaker 1: a symbol of overreach. Right, you're gonna now create You're

1874
01:41:39,320 --> 01:41:42,160
Speaker 1: gonna be like you have here. You sit like let's

1875
01:41:42,160 --> 01:41:45,720
Speaker 1: say you were like Joey ESA, Right, you're like the

1876
01:41:45,920 --> 01:41:50,200
Speaker 1: diehard defender of the ESA. My advice to you stop

1877
01:41:50,280 --> 01:41:54,320
Speaker 1: weaponizing the ESA. Then delist that bear which is a

1878
01:41:54,400 --> 01:42:00,840
Speaker 1: hit recovery, which which hit recovery objectives twenty five years ago. Yeah,

1879
01:42:00,840 --> 01:42:02,840
Speaker 1: but and move on to what's next.

1880
01:42:03,120 --> 01:42:04,760
Speaker 4: The reason I brought up that bear in the Big

1881
01:42:04,800 --> 01:42:07,960
Speaker 4: Horns is that's in the DPS and that's unoccupied habitat.

1882
01:42:08,600 --> 01:42:13,479
Speaker 4: So you know, in theory, the ESA calls for bears

1883
01:42:14,000 --> 01:42:16,479
Speaker 4: moving into that suitable habitat.

1884
01:42:16,120 --> 01:42:18,200
Speaker 1: But they mapped out when they listed them. They mapped

1885
01:42:18,240 --> 01:42:20,840
Speaker 1: out recovery objectives and they hit recovery objectives twenty some

1886
01:42:20,960 --> 01:42:21,360
Speaker 1: years ago.

1887
01:42:22,200 --> 01:42:23,520
Speaker 4: Yeah that's true.

1888
01:42:23,680 --> 01:42:29,919
Speaker 1: Yeah, Okay, So why bother, why bother having an Endangered

1889
01:42:29,920 --> 01:42:36,000
Speaker 1: Species Act? Why bother making recovery objectives if it's just bullshit? Yeah,

1890
01:42:36,040 --> 01:42:36,840
Speaker 1: if you don't mean it.

1891
01:42:37,360 --> 01:42:41,720
Speaker 4: Yeah, it erodes public trust, no doubt about it.

1892
01:42:42,240 --> 01:42:44,160
Speaker 1: Two percent of the things that go on the ESA

1893
01:42:44,280 --> 01:42:49,040
Speaker 1: come off because of recovery. Okay, things will come off

1894
01:42:49,040 --> 01:42:51,240
Speaker 1: because they realize it wasn't warranted. Things will come off

1895
01:42:51,240 --> 01:42:53,559
Speaker 1: because they'll go extinct. Two percent of the things that

1896
01:42:53,600 --> 01:42:55,840
Speaker 1: go on the ESA come off because recovery. Here, you

1897
01:42:55,880 --> 01:42:58,600
Speaker 1: have a recovered thing. Why is it not celebrated?

1898
01:43:00,160 --> 01:43:00,360
Speaker 4: Right?

1899
01:43:00,439 --> 01:43:04,000
Speaker 1: They didn't bitch Like eagles came off, no problem, peregrine fault.

1900
01:43:06,000 --> 01:43:07,920
Speaker 1: But this one they just got to hold it tight

1901
01:43:07,960 --> 01:43:11,040
Speaker 1: to their chest, yep. Because it's not about the ESSA.

1902
01:43:11,120 --> 01:43:12,840
Speaker 4: It's a money maker, that's what it is.

1903
01:43:13,640 --> 01:43:16,960
Speaker 1: Yeah. So forget me saying I'm coming at it from

1904
01:43:16,960 --> 01:43:18,680
Speaker 1: a perspective of one hundred. I'm coming at it from

1905
01:43:18,720 --> 01:43:20,720
Speaker 1: a perspective of someone that wants to get on with

1906
01:43:20,920 --> 01:43:24,920
Speaker 1: UH to like salvage the ESA and not make it

1907
01:43:24,960 --> 01:43:26,679
Speaker 1: that it just is a thing of derision.

1908
01:43:27,360 --> 01:43:28,799
Speaker 4: Glad I bolstered your argument.

1909
01:43:28,960 --> 01:43:31,920
Speaker 1: No, thank you cut all that out, feel so I

1910
01:43:31,960 --> 01:43:35,960
Speaker 1: can just start saying that like I thought of it.

1911
01:43:36,880 --> 01:43:38,559
Speaker 1: Well man, thanks for coming on the show.

1912
01:43:38,520 --> 01:43:40,479
Speaker 4: Thanks for having me appreciate it. It's good to meet

1913
01:43:40,520 --> 01:43:40,880
Speaker 4: you guys.

1914
01:43:40,960 --> 01:43:42,400
Speaker 1: Is there anything that I that you wish you got

1915
01:43:42,439 --> 01:43:43,679
Speaker 1: to talk about that I asked about.

1916
01:43:43,840 --> 01:43:45,639
Speaker 4: I meant to talk about snaring bears.

1917
01:43:46,000 --> 01:43:47,760
Speaker 1: That's something I didn't talk tell me about that.

1918
01:43:48,439 --> 01:43:51,000
Speaker 4: So another way we catch them is with foot snares,

1919
01:43:51,560 --> 01:43:56,240
Speaker 4: and you use what's called an aldrewe spring, and you

1920
01:43:57,880 --> 01:43:59,960
Speaker 4: put the spring and a snare loop and you dig

1921
01:44:00,080 --> 01:44:04,240
Speaker 4: a hole and then you recreate the surfaces though it's

1922
01:44:04,320 --> 01:44:07,840
Speaker 4: just ground, and you try to get a bear to

1923
01:44:07,880 --> 01:44:10,240
Speaker 4: step in that. And that's a fun part of trapping.

1924
01:44:10,600 --> 01:44:12,760
Speaker 1: So how do you get him step in there? Hanging

1925
01:44:12,800 --> 01:44:13,120
Speaker 1: a bait?

1926
01:44:14,120 --> 01:44:15,680
Speaker 4: A lot of times you have a cubby set and

1927
01:44:15,720 --> 01:44:21,280
Speaker 4: you're trying to direct them into your set, but you're

1928
01:44:21,320 --> 01:44:24,080
Speaker 4: putting sticks, and bears don't like to step on sticks

1929
01:44:24,120 --> 01:44:26,960
Speaker 4: and hurt their feet, so you can kind of control

1930
01:44:27,000 --> 01:44:29,080
Speaker 4: their foot movement with those.

1931
01:44:32,960 --> 01:44:35,400
Speaker 1: When you're doing that, so he actually thinks he's putting

1932
01:44:35,439 --> 01:44:36,960
Speaker 1: his foot on the ground and his foot breaks through

1933
01:44:37,000 --> 01:44:37,320
Speaker 1: the ground.

1934
01:44:37,520 --> 01:44:40,160
Speaker 4: Yeah, and it hits this Yeah, it's a pit trap,

1935
01:44:40,160 --> 01:44:43,840
Speaker 4: but it hits this trigger and that trigger flings a

1936
01:44:43,920 --> 01:44:47,679
Speaker 4: spring and that pulls that snare cable tight. And the

1937
01:44:47,680 --> 01:44:50,040
Speaker 4: snare cable just has a little bracket that only slides

1938
01:44:50,040 --> 01:44:52,799
Speaker 4: one way, you know. And you caught a bear.

1939
01:44:53,000 --> 01:44:55,240
Speaker 1: And can you is he too messed up? Or can

1940
01:44:55,240 --> 01:44:56,240
Speaker 1: you release him? Oh?

1941
01:44:56,280 --> 01:44:58,160
Speaker 4: Yeah, no, you you release those bears.

1942
01:44:58,240 --> 01:44:59,240
Speaker 1: He's gotta be pissed.

1943
01:44:59,360 --> 01:45:00,920
Speaker 3: Do you get him on video when you do that?

1944
01:45:01,560 --> 01:45:04,000
Speaker 3: I got some sounds like a fun visual mm hmm.

1945
01:45:04,080 --> 01:45:07,560
Speaker 4: Got some pictures somewhere, I think. But he's pissed a

1946
01:45:07,640 --> 01:45:10,160
Speaker 4: lot of times they're trying to run off and they

1947
01:45:10,240 --> 01:45:12,240
Speaker 4: hit the end of that snare cable and they roll over.

1948
01:45:12,400 --> 01:45:15,400
Speaker 4: And sometimes they are pissed and they try to charge you.

1949
01:45:15,840 --> 01:45:17,200
Speaker 1: Yep, in regular trap.

1950
01:45:17,200 --> 01:45:19,439
Speaker 4: And you call that blocking, Yeah, exactly.

1951
01:45:19,760 --> 01:45:23,719
Speaker 1: Yeah. A bobcat trapper was explaining one time that people

1952
01:45:23,720 --> 01:45:26,400
Speaker 1: would use blocking for bobcats, but they don't realize this.

1953
01:45:26,520 --> 01:45:30,080
Speaker 1: Bobcats want to stand on little things, so they'd put

1954
01:45:30,120 --> 01:45:33,679
Speaker 1: little rocks to block, or put a log to block,

1955
01:45:33,800 --> 01:45:36,280
Speaker 1: But he wants to be on that. Yeah, so this guy,

1956
01:45:36,439 --> 01:45:38,519
Speaker 1: you know, you know to sycamore, you know, a sycamore ball.

1957
01:45:38,560 --> 01:45:40,080
Speaker 1: They don't live around here, but it's like that little

1958
01:45:40,120 --> 01:45:43,960
Speaker 1: poky little it's like a poky little seed pod. There's

1959
01:45:44,000 --> 01:45:46,519
Speaker 1: this trapper to he doesn't even live in that area,

1960
01:45:46,520 --> 01:45:49,800
Speaker 1: but he gets big things of those sycamore things because

1961
01:45:49,800 --> 01:45:52,360
Speaker 1: it's real spiky, and the cat don't want to put

1962
01:45:52,360 --> 01:45:55,000
Speaker 1: his foot on it. So then you can actually control

1963
01:45:55,040 --> 01:45:57,240
Speaker 1: his foot placement. But you put a stick there and

1964
01:45:57,240 --> 01:46:01,960
Speaker 1: that cat's like, oh sweet things. And missus the pants

1965
01:46:01,960 --> 01:46:04,040
Speaker 1: you're standing on, your blocking you know, the stuff that's

1966
01:46:04,040 --> 01:46:05,760
Speaker 1: supposed to keep them from wanting to do it. Yeah,

1967
01:46:05,840 --> 01:46:09,760
Speaker 1: so you want stuff that looks like uncomfortable for his foot. Interesting,

1968
01:46:10,600 --> 01:46:13,960
Speaker 1: keep that in mind. I might just go trap bears

1969
01:46:13,960 --> 01:46:16,880
Speaker 1: on my own, just for fun. Bear trapping.

1970
01:46:17,000 --> 01:46:19,519
Speaker 4: Yeah, whose ear tag is this?

1971
01:46:21,680 --> 01:46:23,920
Speaker 1: Well, dude, thanks thanks for coming out, man, I appreciate it.

1972
01:46:24,000 --> 01:46:25,720
Speaker 4: Yeah, thanks for having me, and good luck on your

1973
01:46:25,840 --> 01:46:28,280
Speaker 4: job hunt. Thanks appreciate that name.

1974
01:46:28,400 --> 01:46:30,000
Speaker 1: Name what line of work you want, because maybe someoneill

1975
01:46:30,040 --> 01:46:30,880
Speaker 1: call you and give you a job.

1976
01:46:31,280 --> 01:46:33,680
Speaker 4: Land conservation I think could be up my alley. I

1977
01:46:33,680 --> 01:46:36,760
Speaker 4: think that would be beneficial to wildlife. So should I

1978
01:46:36,800 --> 01:46:38,160
Speaker 4: throw out my email. Can I do that?

1979
01:46:39,160 --> 01:46:41,800
Speaker 7: They you can throw out your email if you want

1980
01:46:41,800 --> 01:46:44,800
Speaker 7: a bajillion people messaging you, or they can email loss

1981
01:46:44,880 --> 01:46:45,679
Speaker 7: Yeah yeah that's.

1982
01:46:45,560 --> 01:46:47,280
Speaker 4: Mine Wor they can also take through.

1983
01:46:47,200 --> 01:46:47,720
Speaker 1: His own job.

1984
01:46:48,600 --> 01:46:49,479
Speaker 2: Yep, that's true.

1985
01:46:50,720 --> 01:46:53,639
Speaker 4: My email is just Dusty dot Lassiter L A S

1986
01:46:53,640 --> 01:46:57,280
Speaker 4: S E T E R ten at Gmail. Looking for work,

1987
01:46:57,479 --> 01:46:59,320
Speaker 4: looking for work. I got a great job. I have

1988
01:46:59,360 --> 01:47:02,559
Speaker 4: a great boss, but I still want to do something

1989
01:47:02,600 --> 01:47:03,639
Speaker 4: that benefits wildlife.

1990
01:47:04,760 --> 01:47:06,840
Speaker 1: I got a construction project I might lay out in

1991
01:47:06,880 --> 01:47:07,280
Speaker 1: front of you.

1992
01:47:07,320 --> 01:47:09,080
Speaker 4: To I can handle it.

1993
01:47:09,080 --> 01:47:11,600
Speaker 1: It's in grizzly country.

1994
01:47:10,479 --> 01:47:13,720
Speaker 4: Yeah, I'm a mediocre carpenter.

1995
01:47:13,280 --> 01:47:15,519
Speaker 1: But that's what that's kind. I'm looking for.

1996
01:47:18,040 --> 01:47:18,719
Speaker 4: More of a painter.

1997
01:47:20,920 --> 01:47:22,559
Speaker 1: All right, man, thanks so much than.

1998
01:47:23,960 --> 01:47:28,960
Speaker 5: The fingers are told so cold that they burn. Were

1999
01:47:29,160 --> 01:47:33,000
Speaker 5: standing in the creek in our Burney.

2000
01:47:34,479 --> 01:47:40,760
Speaker 2: Just for me in a warm bomb. And then back to.

2001
01:47:40,400 --> 01:48:06,719
Speaker 5: The pros chasing cotton tail High. I was just ten,

2002
01:48:06,920 --> 01:48:14,559
Speaker 5: but High got to join his Carol protested Grandpa's firm.

2003
01:48:15,560 --> 01:48:20,720
Speaker 2: I've had him shooting since he was me. High. He

2004
01:48:20,880 --> 01:48:23,320
Speaker 2: sees tayd him.

2005
01:48:25,400 --> 01:48:29,759
Speaker 5: Then an apro close with the ball on the wind

2006
01:48:30,960 --> 01:48:36,479
Speaker 5: hot home tray and bring it in her round moved

2007
01:48:36,600 --> 01:48:42,679
Speaker 5: up ahead, just into the lane where case colored Steve

2008
01:48:43,000 --> 01:48:49,080
Speaker 5: has put two on the ground. Morning turn high and

2009
01:48:49,400 --> 01:48:54,120
Speaker 5: he was singing, came about to spill as a shot

2010
01:48:54,280 --> 01:48:59,679
Speaker 5: shell off Lou at its ord home, and I couldn't

2011
01:48:59,840 --> 01:49:04,639
Speaker 5: have off. We're in in fingers on the ema, lips

2012
01:49:04,760 --> 01:49:05,960
Speaker 5: turning blue.

2013
01:49:07,000 --> 01:49:09,920
Speaker 2: Ever, at the end.

2014
01:49:10,000 --> 01:49:18,080
Speaker 5: Of Novegeber, the memories all showver me, bitter sleep, goness,

2015
01:49:18,439 --> 01:49:30,080
Speaker 5: early morn, cotton tail hunting, afternoon targets, esteemed dinner feeds,

2016
01:49:30,160 --> 01:49:35,240
Speaker 5: forty hot people with cousins, and of those who have

2017
01:49:35,680 --> 01:49:42,120
Speaker 5: half forgotten, and all all harried, rarely so happy.

2018
01:49:43,000 --> 01:49:46,559
Speaker 2: House spoke first in me in the.

2019
01:49:46,600 --> 01:49:58,879
Speaker 5: Bond that was away back in my you. I watched

2020
01:49:58,920 --> 01:50:04,920
Speaker 5: it all changed through the heat. It's time we roll

2021
01:50:05,640 --> 01:50:07,439
Speaker 5: both bedrock.

2022
01:50:06,960 --> 01:50:12,120
Speaker 2: And bone and old age wilts. Even the most pierced.

2023
01:50:13,800 --> 01:50:20,240
Speaker 5: Grandpa we lost in the cold of Dember Carol. Few

2024
01:50:20,600 --> 01:50:29,920
Speaker 5: turns before, how bout farm when they couldn't remember. Nothing's

2025
01:50:30,080 --> 01:50:35,400
Speaker 5: the same anymore, Born God.

2026
01:50:35,439 --> 01:50:38,120
Speaker 2: Leave the old home lost.

2027
01:50:37,840 --> 01:50:42,040
Speaker 5: It shee You can hear the wind a whistle at too.

2028
01:50:44,400 --> 01:50:49,600
Speaker 5: She creaks, and she bones and all over chrown. But

2029
01:50:49,760 --> 01:50:52,960
Speaker 5: we'll get her looking brand new.

2030
01:50:54,960 --> 01:50:57,920
Speaker 2: Here at the end.

2031
01:50:58,000 --> 01:51:05,360
Speaker 5: Of November, memories all show over me bitter sweet, go

2032
01:51:05,760 --> 01:51:18,080
Speaker 5: his early morn cotton sail, hunting after new targets and skins, feeds,

2033
01:51:18,160 --> 01:51:24,800
Speaker 5: forty hot people, dozins, and of those who have half forgotten,

2034
01:51:25,760 --> 01:51:32,680
Speaker 5: brand all harriet, rarely so happy. Their housefold burst in

2035
01:51:33,120 --> 01:51:37,799
Speaker 5: and fed in the pond, swear ris up.

2036
01:51:37,800 --> 01:51:43,640
Speaker 2: A few kids on my own, maybe one day grandson to.

2037
01:51:45,960 --> 01:51:49,840
Speaker 5: How want the same hells with the hand on each

2038
01:51:49,960 --> 01:51:53,240
Speaker 5: shoulder open maybe week kick.

2039
01:51:53,240 --> 01:51:59,440
Speaker 2: Up, few ran over. They feel this place.

2040
01:52:01,840 --> 01:52:08,840
Speaker 5: Every at the end of November. Memory and all show

2041
01:52:08,840 --> 01:52:12,200
Speaker 5: over media, bitter sweet.

2042
01:52:12,160 --> 01:52:18,519
Speaker 2: As early morn, cant and tale afternoons.

2043
01:52:18,560 --> 01:52:28,720
Speaker 5: Targets speak, two feeds, forty hot people, cousins and of

2044
01:52:29,000 --> 01:52:37,440
Speaker 5: coles who have half forgotten, and all harried, rarely so happy.

2045
01:52:37,840 --> 01:52:41,719
Speaker 5: House foolhursted and made in the part