1 00:00:01,280 --> 00:00:05,120 Speaker 1: Welcome to the Wired to Hunt Foundations podcast, your guide 2 00:00:05,120 --> 00:00:08,920 Speaker 1: to the fundamentals of better deer hunting, presented by first Light, 3 00:00:09,240 --> 00:00:13,600 Speaker 1: creating proven versatile hunting apparel for the stand, saddle or blind. 4 00:00:14,120 --> 00:00:18,680 Speaker 1: First Light, Go Farther, Stay Longer, and now your host 5 00:00:19,040 --> 00:00:19,919 Speaker 1: Tony Peterson. 6 00:00:20,280 --> 00:00:23,200 Speaker 2: Hey everyone, welcome to the Wire to Hunt Foundation's podcast, 7 00:00:23,239 --> 00:00:25,000 Speaker 2: which is brought to you by a first Light. I'm 8 00:00:25,040 --> 00:00:28,280 Speaker 2: your host, Tony Peterson, and today's episode is all about 9 00:00:28,360 --> 00:00:32,360 Speaker 2: patterning deer and how we often get this task so 10 00:00:32,720 --> 00:00:39,320 Speaker 2: very wrong. When I was in high school, I got 11 00:00:39,400 --> 00:00:42,680 Speaker 2: permission to hunt this dairy farm where quite a few 12 00:00:42,720 --> 00:00:45,839 Speaker 2: people had permission to hunt. One of the other hunters 13 00:00:45,920 --> 00:00:48,360 Speaker 2: was maybe, I don't know, like ten years older than me, 14 00:00:48,920 --> 00:00:51,720 Speaker 2: and he had a reputation for being a big buck killer. 15 00:00:52,320 --> 00:00:56,000 Speaker 2: I randomly bumped into him walking out one morning and 16 00:00:56,040 --> 00:00:59,920 Speaker 2: he showed me some pictures, actual printed photographs, not self 17 00:01:00,080 --> 00:01:03,120 Speaker 2: CAMPI since it was like nineteen ninety six, there were 18 00:01:03,160 --> 00:01:06,240 Speaker 2: just several big bucks that he had killed. He then 19 00:01:06,319 --> 00:01:09,000 Speaker 2: pointed to a valley on the farm and said they 20 00:01:09,080 --> 00:01:11,000 Speaker 2: usually bet in there and dropped down on the hillside 21 00:01:11,040 --> 00:01:13,600 Speaker 2: to go feed in the evening, And I remember thinking 22 00:01:14,080 --> 00:01:16,040 Speaker 2: I don't know. I've hunted that hillside a lot and 23 00:01:16,080 --> 00:01:18,720 Speaker 2: that's just not been the case. But it turns out 24 00:01:18,720 --> 00:01:21,640 Speaker 2: that he was right, so was I. And now I'm 25 00:01:21,640 --> 00:01:28,959 Speaker 2: going to tell you how that can be true. Do 26 00:01:29,000 --> 00:01:32,920 Speaker 2: you know why we love music so much? Part of 27 00:01:32,959 --> 00:01:35,480 Speaker 2: the reason is that we have a long history, like 28 00:01:35,760 --> 00:01:40,760 Speaker 2: two million years of history, where recognizing patterns helped us 29 00:01:40,760 --> 00:01:44,440 Speaker 2: either fill our bellies or keep us from filling something 30 00:01:44,480 --> 00:01:48,480 Speaker 2: else's belly. In fact, our creation of music and our 31 00:01:48,560 --> 00:01:51,960 Speaker 2: hunting abilities are intertwined, even if that's hard to believe 32 00:01:52,560 --> 00:01:54,800 Speaker 2: because you're I don't know, as tone deaf as a 33 00:01:54,800 --> 00:01:57,600 Speaker 2: fence post, but you love to hunt. Now, whether you're 34 00:01:57,640 --> 00:02:00,920 Speaker 2: talking melody in the form of a catchy core rhythm 35 00:02:00,920 --> 00:02:02,600 Speaker 2: in the form of a guitar riff that just makes 36 00:02:02,600 --> 00:02:05,720 Speaker 2: you feel all warm and fuzzy, music is built on 37 00:02:05,800 --> 00:02:10,120 Speaker 2: a foundation of repetition. In that latter case, the key 38 00:02:10,160 --> 00:02:13,079 Speaker 2: to a good riff is that it involves playing notes 39 00:02:13,160 --> 00:02:17,200 Speaker 2: or chords, but also utilizes the silence in between. This 40 00:02:17,360 --> 00:02:20,400 Speaker 2: gives you, the listener, a chance to anticipate the next 41 00:02:20,400 --> 00:02:23,680 Speaker 2: notes and gives the song kind of this feeling that 42 00:02:23,720 --> 00:02:27,560 Speaker 2: it's progressing. Take one of the best songs that has 43 00:02:27,880 --> 00:02:31,280 Speaker 2: ever been written. Wish You Were Here by Pink Floyd. 44 00:02:31,440 --> 00:02:33,600 Speaker 2: I'm teaching my daughter to play the rhythm for this 45 00:02:33,760 --> 00:02:36,880 Speaker 2: song on her acoustic guitar, and she's pretty good, but 46 00:02:36,960 --> 00:02:40,800 Speaker 2: her timing sucks. While she might play every note in 47 00:02:40,840 --> 00:02:44,280 Speaker 2: the right order without the right spacing, it doesn't work. 48 00:02:44,880 --> 00:02:47,600 Speaker 2: The pattern falls apart, and our brains don't like it 49 00:02:47,720 --> 00:02:52,360 Speaker 2: one bit. Now, with music, it's pretty easy to identify patterns. 50 00:02:52,960 --> 00:02:56,440 Speaker 2: It happens damn near naturally to all of us. Our 51 00:02:56,480 --> 00:02:59,080 Speaker 2: brains just do the work, and we know what sounds 52 00:02:59,120 --> 00:03:02,720 Speaker 2: good and what sounds off. Disability is a bit more 53 00:03:02,760 --> 00:03:05,040 Speaker 2: subdued out there in the wild, where we might be 54 00:03:05,080 --> 00:03:08,600 Speaker 2: clued into super obvious patterns, but not into the subtle 55 00:03:08,639 --> 00:03:11,120 Speaker 2: ones and allow us to hunt deer or other critters 56 00:03:11,120 --> 00:03:15,680 Speaker 2: more effectively. This is kind of wild, considering our ability 57 00:03:15,720 --> 00:03:19,880 Speaker 2: to recognize patterns came from our continual quest to survive 58 00:03:20,000 --> 00:03:23,440 Speaker 2: and thrive as a species. Of course, you have the 59 00:03:23,480 --> 00:03:26,520 Speaker 2: patterns in nature that keep you alive but don't help 60 00:03:26,560 --> 00:03:31,120 Speaker 2: you hunt. Take honey, for example. That delicious bee puke 61 00:03:31,560 --> 00:03:35,600 Speaker 2: is one of our most ancestrally consistent foods. It can 62 00:03:35,600 --> 00:03:37,800 Speaker 2: be found all over the world, or at least in 63 00:03:37,880 --> 00:03:40,600 Speaker 2: most of the parts that people can actually live, and 64 00:03:40,640 --> 00:03:44,160 Speaker 2: it has been eaten by us for a long long time. 65 00:03:44,760 --> 00:03:48,440 Speaker 2: That's one of the reasons natural honey is also really 66 00:03:48,440 --> 00:03:51,360 Speaker 2: good for you. Your body knows what to do with honey, 67 00:03:51,680 --> 00:03:54,960 Speaker 2: unlike I don't know, say, a package of gushers or 68 00:03:54,960 --> 00:03:57,080 Speaker 2: some other junk food that was created in a lab. 69 00:03:57,960 --> 00:04:00,600 Speaker 2: We like the look of hexagon stack on top of 70 00:04:00,680 --> 00:04:03,080 Speaker 2: one another, which is a pattern that can be found 71 00:04:03,440 --> 00:04:06,760 Speaker 2: where honey is often found. We also don't like the 72 00:04:06,760 --> 00:04:09,119 Speaker 2: look of two hundred bees forming a single spot, which 73 00:04:09,160 --> 00:04:13,040 Speaker 2: makes us run. A few bees is a different story. Now. 74 00:04:13,080 --> 00:04:15,160 Speaker 2: I read a line in an article about this that 75 00:04:15,320 --> 00:04:22,120 Speaker 2: goes evolution necessitates economical and reliable brain mechanisms in some 76 00:04:22,440 --> 00:04:27,200 Speaker 2: environmental context. Take a couple of caveman hunters looking to 77 00:04:27,240 --> 00:04:30,400 Speaker 2: throw a spear into something big and meaty. Here they 78 00:04:30,440 --> 00:04:32,520 Speaker 2: head out to hunt, but on the trail ahead of 79 00:04:32,560 --> 00:04:35,760 Speaker 2: them they see some wolf tracks, or maybe the tracks 80 00:04:35,760 --> 00:04:38,640 Speaker 2: of a short face bear. They have learned that a 81 00:04:38,640 --> 00:04:42,359 Speaker 2: lot of wolves big trouble, but a few might be manageable. 82 00:04:42,760 --> 00:04:45,960 Speaker 2: They have also learned that one short face bear that's 83 00:04:46,000 --> 00:04:48,880 Speaker 2: having a bad morning can reduce their little family group 84 00:04:48,920 --> 00:04:52,440 Speaker 2: by several members in a matter of seconds. The pattern 85 00:04:52,520 --> 00:04:55,000 Speaker 2: of the wolf tracks would mean they need to investigate 86 00:04:55,040 --> 00:04:58,200 Speaker 2: to determine how many there are. Maybe there are just 87 00:04:58,279 --> 00:05:01,560 Speaker 2: two distinct sets on the trail, but old Ugg and 88 00:05:01,640 --> 00:05:04,720 Speaker 2: Cronk or whoever, swing low and high, and they find 89 00:05:04,760 --> 00:05:07,599 Speaker 2: two more sets. They have learned that wolves don't always 90 00:05:07,600 --> 00:05:11,480 Speaker 2: travel in single file, and underestimating the amount of toothy 91 00:05:11,520 --> 00:05:15,120 Speaker 2: dogs they could run into can be very costly. There's 92 00:05:15,120 --> 00:05:18,480 Speaker 2: a pattern to the wolve's behavior which shapes human behavior 93 00:05:18,480 --> 00:05:22,080 Speaker 2: into patterns. Just like the presence of one single big 94 00:05:22,160 --> 00:05:25,320 Speaker 2: danger like the short face bear, cause humans to change 95 00:05:25,360 --> 00:05:29,920 Speaker 2: their behaviors a lot. Then you have other connections that 96 00:05:29,960 --> 00:05:34,640 Speaker 2: result in us recognizing patterns. Say a certain tree bears 97 00:05:34,680 --> 00:05:36,599 Speaker 2: fruit during a few weeks of the year when the 98 00:05:36,600 --> 00:05:39,719 Speaker 2: weather is just right, and not only is that fruit 99 00:05:39,760 --> 00:05:41,839 Speaker 2: good for you to gather up and bring back to 100 00:05:41,880 --> 00:05:45,080 Speaker 2: the tribe, but it also draws in deer who understand 101 00:05:45,120 --> 00:05:48,160 Speaker 2: the same pattern you do. Now you have a plant 102 00:05:48,200 --> 00:05:51,599 Speaker 2: pattern that's tied into a weather pattern and also a 103 00:05:51,640 --> 00:05:55,040 Speaker 2: certain geographical pattern that causes humans to learn a new 104 00:05:55,040 --> 00:05:58,839 Speaker 2: pattern of behavior while being exposed to certain prey animals 105 00:05:58,920 --> 00:06:02,640 Speaker 2: and their behavior around the same kind of pattern, which 106 00:06:02,680 --> 00:06:05,200 Speaker 2: undoubtedly causes the deer to be a little more cautious 107 00:06:05,240 --> 00:06:09,760 Speaker 2: because well, we know that they're patterning us too. There 108 00:06:09,760 --> 00:06:12,279 Speaker 2: are songs that are created with nothing more than an 109 00:06:12,320 --> 00:06:15,600 Speaker 2: acoustic guitar and a singer, than there are songs created 110 00:06:15,600 --> 00:06:18,440 Speaker 2: by whole teams of folks playing a multitude of instruments 111 00:06:18,640 --> 00:06:23,000 Speaker 2: and using every single technological advancement they have to add sounds. 112 00:06:23,720 --> 00:06:27,920 Speaker 2: Patterns can be simple, and they can be complicated. As 113 00:06:28,000 --> 00:06:31,960 Speaker 2: hunters in today's world, we strive to make them simple. 114 00:06:32,680 --> 00:06:35,400 Speaker 2: We put in a food plot and hope the bucks 115 00:06:35,480 --> 00:06:37,800 Speaker 2: just decide it's a good place to eat every day, 116 00:06:38,680 --> 00:06:41,279 Speaker 2: or at least the doe do, and then we leave 117 00:06:41,320 --> 00:06:44,560 Speaker 2: them alone about, you know, until Halloween, and then the 118 00:06:44,560 --> 00:06:49,200 Speaker 2: bucks start coming in. Simple, we don't really have to 119 00:06:49,240 --> 00:06:52,640 Speaker 2: know where they bed, or where they travel or what 120 00:06:52,720 --> 00:06:55,839 Speaker 2: they do when they don't come in. We just need 121 00:06:55,880 --> 00:06:58,400 Speaker 2: to know that the pattern contains at least some level 122 00:06:58,440 --> 00:07:02,080 Speaker 2: of them entering the food plot, so we volume hunt 123 00:07:02,080 --> 00:07:06,480 Speaker 2: it once it should turn on. It's actually pretty simple 124 00:07:07,240 --> 00:07:11,760 Speaker 2: until it's not. How often have you had a good plan, now, 125 00:07:11,760 --> 00:07:14,680 Speaker 2: I mean one where you just had so much confidence, 126 00:07:15,080 --> 00:07:18,720 Speaker 2: and then you executed and you didn't see anything. What happened? 127 00:07:19,520 --> 00:07:23,200 Speaker 2: Did you not understand the pattern to their deer movement 128 00:07:24,160 --> 00:07:26,840 Speaker 2: or did they understand your pattern better than you thought? 129 00:07:27,640 --> 00:07:31,040 Speaker 2: Was it just bad luck. I'm convinced that one of 130 00:07:31,080 --> 00:07:34,920 Speaker 2: the reasons people struggle so much with elk hunting isn't 131 00:07:34,960 --> 00:07:36,720 Speaker 2: that there is a ton of pressure and the bulls 132 00:07:36,720 --> 00:07:40,240 Speaker 2: are quiet. Sure that happens, But I also think it 133 00:07:40,280 --> 00:07:42,040 Speaker 2: has to do with the fact that most of us, 134 00:07:42,520 --> 00:07:45,840 Speaker 2: and by us, I mean residents and non residents in 135 00:07:45,880 --> 00:07:49,280 Speaker 2: Western states and you know, Midwest and East who just 136 00:07:49,320 --> 00:07:52,080 Speaker 2: show up in the mountains to hunt. All of us, 137 00:07:52,880 --> 00:07:56,520 Speaker 2: It's hard to really scout elk. It's hard to really 138 00:07:56,560 --> 00:07:59,800 Speaker 2: see elk, it's hard to pattern them, and they live 139 00:07:59,840 --> 00:08:02,760 Speaker 2: in a world that is much larger than the white tails, 140 00:08:03,200 --> 00:08:07,600 Speaker 2: which means even if there is a repeatable pattern, observing 141 00:08:07,640 --> 00:08:11,360 Speaker 2: it directly or figuring it out from sign alone just 142 00:08:11,400 --> 00:08:15,840 Speaker 2: a tough proposition. White tails are different, But we've also 143 00:08:15,920 --> 00:08:20,080 Speaker 2: been conditioned to believe that they are super patternable. They 144 00:08:20,120 --> 00:08:22,880 Speaker 2: generally aren't, at least if they live in a place 145 00:08:22,920 --> 00:08:26,040 Speaker 2: with a moderate level of hunting pressure. Now I know, 146 00:08:26,120 --> 00:08:29,160 Speaker 2: I've talked about this a thousand times. But the advice 147 00:08:29,240 --> 00:08:32,120 Speaker 2: you've been hearing forever on white tails often comes from 148 00:08:32,120 --> 00:08:35,520 Speaker 2: a place where they are very patternable because they don't 149 00:08:35,559 --> 00:08:38,800 Speaker 2: have a lot to fear. I heard a story about 150 00:08:38,840 --> 00:08:42,080 Speaker 2: a giant like one hundred and ninety ish whitetail that 151 00:08:42,160 --> 00:08:44,800 Speaker 2: got shot on film by someone on one of the 152 00:08:44,840 --> 00:08:48,320 Speaker 2: most popular shows out there, and they managed to capture 153 00:08:48,400 --> 00:08:52,120 Speaker 2: two different angles of the kill with two different cameramen 154 00:08:52,640 --> 00:08:56,560 Speaker 2: because they knew how much they had of that buck's 155 00:08:56,679 --> 00:09:01,679 Speaker 2: pattern coming into a certain food plot very consistent. Now, 156 00:09:01,760 --> 00:09:06,600 Speaker 2: imagine trying that putting a hunter and a cameraman on 157 00:09:06,600 --> 00:09:08,720 Speaker 2: one side and then a cameraman on the other side 158 00:09:08,720 --> 00:09:11,720 Speaker 2: of the trail, and even killing a four key in 159 00:09:11,800 --> 00:09:15,160 Speaker 2: most places be pretty tough, let alone a deer that's 160 00:09:15,679 --> 00:09:19,560 Speaker 2: bumping up on two hundred inches. You don't have that, 161 00:09:19,679 --> 00:09:22,520 Speaker 2: But that's okay. There are still plenty of patterns out 162 00:09:22,559 --> 00:09:25,720 Speaker 2: there for you to recognize and use during your hunting 163 00:09:25,760 --> 00:09:28,600 Speaker 2: season and for every season for the rest of your life. 164 00:09:29,320 --> 00:09:31,199 Speaker 2: This is where the advice is gonna get a little tricky, 165 00:09:31,200 --> 00:09:33,680 Speaker 2: but I'm gonna do my best. When we talk of 166 00:09:33,800 --> 00:09:37,160 Speaker 2: patterning deer, we tend to default to the thinking that 167 00:09:37,200 --> 00:09:41,240 Speaker 2: concerns a single buck, or at least mature bucks. We 168 00:09:41,320 --> 00:09:44,439 Speaker 2: think about finding a giant bed, getting trail camera photos 169 00:09:44,440 --> 00:09:46,560 Speaker 2: of the deer in a food source, and then working 170 00:09:46,600 --> 00:09:48,760 Speaker 2: with that info to fill in the blanks. And that's 171 00:09:48,760 --> 00:10:01,720 Speaker 2: certainly one way to start patterning deer. The other is 172 00:10:01,760 --> 00:10:05,200 Speaker 2: to pattern deer in general. This is where most of 173 00:10:05,240 --> 00:10:09,319 Speaker 2: your big buck public land hunters have a huge advantage 174 00:10:09,360 --> 00:10:13,720 Speaker 2: over most folks. They understand that the task does involve 175 00:10:13,800 --> 00:10:17,400 Speaker 2: finding some big bucks and patterning them, but they are 176 00:10:17,480 --> 00:10:21,040 Speaker 2: starting first with the knowledge of what patterns are most 177 00:10:21,120 --> 00:10:25,040 Speaker 2: likely in the environments they'll be hunting. What I mean 178 00:10:25,120 --> 00:10:29,640 Speaker 2: by that is they scout and scout and hunt and hunt, 179 00:10:29,679 --> 00:10:32,360 Speaker 2: and pretty soon when they walk into a place that 180 00:10:32,360 --> 00:10:36,280 Speaker 2: they've never been before, they start to recognize terrain features 181 00:10:36,280 --> 00:10:39,199 Speaker 2: that mirror other terrain features they've been around a lot. 182 00:10:39,480 --> 00:10:42,640 Speaker 2: They start to see sign in specific spots. They enter 183 00:10:42,720 --> 00:10:45,760 Speaker 2: the deer's world with an understanding of how deer used 184 00:10:45,760 --> 00:10:48,320 Speaker 2: that world, and so much of the work they've put 185 00:10:48,360 --> 00:10:52,400 Speaker 2: in in other places becomes directly applicable to the task 186 00:10:52,480 --> 00:10:56,000 Speaker 2: at hand in a new spot. This goes for someone 187 00:10:56,080 --> 00:10:58,360 Speaker 2: hunting a different chunk of land in the same county 188 00:10:58,360 --> 00:11:01,480 Speaker 2: they always hunt and for somebody I don't know, traveling 189 00:11:01,480 --> 00:11:04,920 Speaker 2: from Pennsylvania to Kansas, or from South Carolina to Tennessee. 190 00:11:05,480 --> 00:11:08,120 Speaker 2: This is a hard thing for people to really grasp, 191 00:11:08,600 --> 00:11:11,800 Speaker 2: but it's true. Part of the problem here is that 192 00:11:11,840 --> 00:11:14,840 Speaker 2: we all have, you know, kind of local bias where 193 00:11:14,880 --> 00:11:17,680 Speaker 2: we think we are hunting the hardest killed deer out there. 194 00:11:18,320 --> 00:11:20,719 Speaker 2: This is always wild to me as someone who has 195 00:11:20,760 --> 00:11:23,800 Speaker 2: traveled a lot, because over time you find areas that 196 00:11:23,840 --> 00:11:27,000 Speaker 2: are just really difficult, and you hunt areas even on 197 00:11:27,040 --> 00:11:29,600 Speaker 2: public land, where the hunting is so much easier than 198 00:11:29,600 --> 00:11:33,320 Speaker 2: other spots. But what is consistent throughout is that a 199 00:11:33,320 --> 00:11:35,679 Speaker 2: lot of the locals think they are hunting the toughest 200 00:11:35,679 --> 00:11:38,640 Speaker 2: to kill deer. That gives them a built in excuse 201 00:11:38,720 --> 00:11:41,719 Speaker 2: for failure, and it also changes how they view patterns. 202 00:11:42,200 --> 00:11:46,000 Speaker 2: Think about it this way. If you hunt, say Michigan 203 00:11:46,080 --> 00:11:49,640 Speaker 2: public land, and you just know you have more hunting 204 00:11:49,640 --> 00:11:52,960 Speaker 2: competition than anyone, you might find some rubs all clustered 205 00:11:53,000 --> 00:11:55,320 Speaker 2: together on the edge of a small creek, and you 206 00:11:55,400 --> 00:11:59,320 Speaker 2: might immediately think, well, there's a decent one around, but 207 00:11:59,360 --> 00:12:01,400 Speaker 2: he's going to be not because all of the bucks 208 00:12:01,400 --> 00:12:04,559 Speaker 2: here are nocturtle because we have so much pressure. Then 209 00:12:04,600 --> 00:12:06,720 Speaker 2: you take that same hunter and he finds a similar 210 00:12:06,760 --> 00:12:09,439 Speaker 2: setup in Iowa after waiting six years to draw a tag. 211 00:12:10,160 --> 00:12:12,439 Speaker 2: Do you think he's going to write that spot off 212 00:12:12,679 --> 00:12:16,360 Speaker 2: as a lost cause? In Iowa, the sign and the 213 00:12:16,440 --> 00:12:19,400 Speaker 2: environment are pointing him in the exact same direction, but 214 00:12:19,480 --> 00:12:23,360 Speaker 2: the difference is how he views the situation. Or take 215 00:12:23,400 --> 00:12:26,320 Speaker 2: that Iowa hunter who has no idea how easy is 216 00:12:26,360 --> 00:12:28,800 Speaker 2: hunting has ben while growing up on grandma's farm and 217 00:12:28,840 --> 00:12:32,040 Speaker 2: having a couple hundred acres to himself. That person has 218 00:12:32,040 --> 00:12:35,439 Speaker 2: developed an understanding of patterns around a high deer population 219 00:12:36,080 --> 00:12:39,400 Speaker 2: and you know, relatively easy to kill deer. Then he 220 00:12:39,440 --> 00:12:42,600 Speaker 2: goes to the swamps of Louisiana or northern Wisconsin, where 221 00:12:42,640 --> 00:12:45,200 Speaker 2: the deer population is ten percent of what he's used to. 222 00:12:46,440 --> 00:12:48,240 Speaker 2: He sees a bench on a hillside with a single 223 00:12:48,280 --> 00:12:50,600 Speaker 2: bed on it, you know, a few scattered rubs here 224 00:12:50,600 --> 00:12:53,440 Speaker 2: and there, and he thinks this is like back home. 225 00:12:53,480 --> 00:12:55,320 Speaker 2: But the sign just doesn't do it for me. There 226 00:12:55,360 --> 00:12:58,800 Speaker 2: isn't enough to work with. But has he calibrated himself 227 00:12:58,800 --> 00:13:01,520 Speaker 2: to the environment or is he taking what he's used 228 00:13:01,520 --> 00:13:03,280 Speaker 2: to and applying it to a world in which it 229 00:13:03,360 --> 00:13:08,559 Speaker 2: doesn't really apply same pattern. It just appears less impactful 230 00:13:08,920 --> 00:13:11,320 Speaker 2: due to the fact that there are so many fewer deer. 231 00:13:12,200 --> 00:13:14,560 Speaker 2: Now you don't have to travel anywhere to get tripped 232 00:13:14,600 --> 00:13:17,880 Speaker 2: up by this. Take your home, farm, your lease, the 233 00:13:17,920 --> 00:13:22,320 Speaker 2: public land, you hunt whatever. You probably believe you understand 234 00:13:22,320 --> 00:13:25,680 Speaker 2: the deer movement really well. But does your hunting reflect that? 235 00:13:26,600 --> 00:13:29,280 Speaker 2: I mean, do the results of your efforts reflect a 236 00:13:29,320 --> 00:13:32,760 Speaker 2: deep understanding of what all the deer do, or what 237 00:13:33,080 --> 00:13:36,080 Speaker 2: the big deer do. Maybe, but I'll bet that they 238 00:13:36,160 --> 00:13:40,240 Speaker 2: often don't. They don't for me, And honestly, one of 239 00:13:40,320 --> 00:13:42,480 Speaker 2: the things that's the hardest for me is to kill 240 00:13:42,520 --> 00:13:46,000 Speaker 2: a big deer on places I know really well, you know, 241 00:13:46,120 --> 00:13:48,640 Speaker 2: places that also allow other hunters in, or places that 242 00:13:48,679 --> 00:13:51,320 Speaker 2: are public. I feel like I know what the deer 243 00:13:51,400 --> 00:13:54,599 Speaker 2: do on paper, But in the woods, I'm often subjected 244 00:13:54,640 --> 00:13:59,040 Speaker 2: to a reality I don't expect. Sure, we know the 245 00:13:59,040 --> 00:14:01,360 Speaker 2: bucks bet up on a ridge, and we know they 246 00:14:01,360 --> 00:14:03,720 Speaker 2: are going to get to the beans to feed, But 247 00:14:03,840 --> 00:14:07,680 Speaker 2: why do they so rarely follow that script? How do 248 00:14:07,760 --> 00:14:11,959 Speaker 2: we get it wrong so often? Well, for starters, as 249 00:14:12,040 --> 00:14:15,079 Speaker 2: much evolution as we have relating to the patterns of 250 00:14:15,120 --> 00:14:19,840 Speaker 2: our environment, the deer have the same advantage they've evolved 251 00:14:19,920 --> 00:14:23,360 Speaker 2: or recognize patterns too. I talked about this recently, but 252 00:14:23,400 --> 00:14:25,680 Speaker 2: I think a good way to look at it is 253 00:14:25,720 --> 00:14:27,920 Speaker 2: that if you're not happy with your hunting in general, 254 00:14:28,600 --> 00:14:32,240 Speaker 2: it's probably because you think you understand their patterns better 255 00:14:32,680 --> 00:14:37,320 Speaker 2: than you do, while also underestimating how good they have 256 00:14:37,600 --> 00:14:42,160 Speaker 2: you patterned. With the first part, it's best to treat 257 00:14:42,160 --> 00:14:45,320 Speaker 2: it like a scientist. What do you believe the deer 258 00:14:45,360 --> 00:14:48,760 Speaker 2: are doing, and how do you believe you'll cross paths 259 00:14:48,840 --> 00:14:52,320 Speaker 2: with the deer that you want to kill. Do that 260 00:14:52,960 --> 00:14:55,840 Speaker 2: and ask yourself how well it worked out. Are you 261 00:14:56,000 --> 00:14:59,320 Speaker 2: consistently surprised that you don't see mature bucks even though 262 00:14:59,360 --> 00:15:01,040 Speaker 2: you seem to be hunting in a way that should 263 00:15:01,080 --> 00:15:05,000 Speaker 2: produce at the very least some sightings. Then there's a 264 00:15:05,000 --> 00:15:08,200 Speaker 2: hole in your game. That's okay, there are holes in 265 00:15:08,200 --> 00:15:11,080 Speaker 2: all of our games. We mostly won't see big bucks 266 00:15:11,080 --> 00:15:14,120 Speaker 2: on any given day, but we also shouldn't let that 267 00:15:14,280 --> 00:15:18,160 Speaker 2: stop us from trying harder. And there's also another reality here. 268 00:15:18,800 --> 00:15:21,600 Speaker 2: If you want to actually pattern big bucks and kill them, 269 00:15:22,120 --> 00:15:24,520 Speaker 2: you might need to rethink when you hunt and where 270 00:15:25,360 --> 00:15:28,720 Speaker 2: deer start the season as patternable as they'll be all year, 271 00:15:29,560 --> 00:15:32,120 Speaker 2: and if you don't take advantage of that, things get 272 00:15:32,160 --> 00:15:36,280 Speaker 2: difficult in a hurry. The earlier the opener, say, you know, 273 00:15:36,320 --> 00:15:39,600 Speaker 2: a September first opener versus a mid September opener or 274 00:15:39,640 --> 00:15:43,720 Speaker 2: even in an October one opener, provides a huge advantage. 275 00:15:44,760 --> 00:15:46,600 Speaker 2: A good percentage of the bucks I have in my 276 00:15:46,680 --> 00:15:49,800 Speaker 2: walls died in September because a summer pattern is an 277 00:15:49,840 --> 00:15:53,200 Speaker 2: easy pattern to recognize. Now, I also have quite a 278 00:15:53,240 --> 00:15:55,680 Speaker 2: few bucks that I killed in mid October because they 279 00:15:55,680 --> 00:15:58,640 Speaker 2: tend to slip into a pattern. Then as well, they 280 00:15:58,680 --> 00:16:01,520 Speaker 2: react to the pressure move into the cover, and they 281 00:16:01,560 --> 00:16:04,320 Speaker 2: get harder to see for a lot of hunters who 282 00:16:04,440 --> 00:16:09,280 Speaker 2: stay outside the cover. But the great leveling agent there 283 00:16:09,440 --> 00:16:13,080 Speaker 2: is you know, those October bucks leave more and more sign, 284 00:16:14,160 --> 00:16:17,880 Speaker 2: So instead of direct observation to build a pattern, it's 285 00:16:18,040 --> 00:16:21,000 Speaker 2: often more a matter of finding sign and maybe running 286 00:16:21,000 --> 00:16:24,640 Speaker 2: some cameras. Even then you're still just playing the odds 287 00:16:24,920 --> 00:16:27,240 Speaker 2: because most dear at least after a week or two 288 00:16:27,240 --> 00:16:29,640 Speaker 2: of the season. They don't do the same thing over 289 00:16:29,680 --> 00:16:33,080 Speaker 2: and over again. I firmly believe that. Think about how 290 00:16:33,080 --> 00:16:36,120 Speaker 2: often you have checked a trail camera and has shown 291 00:16:36,120 --> 00:16:38,520 Speaker 2: a certain buck using a certain trail a couple of 292 00:16:38,560 --> 00:16:42,640 Speaker 2: times in one month. There's a loose pattern there. You know, 293 00:16:42,680 --> 00:16:44,600 Speaker 2: it's just diluted by a hell of a lot of 294 00:16:44,680 --> 00:16:49,240 Speaker 2: days where the buck did something else. This happens all 295 00:16:49,280 --> 00:16:54,000 Speaker 2: the time, and even consistent bucks are somewhat inconsistent and 296 00:16:54,080 --> 00:16:56,360 Speaker 2: that they are definitely not going to do the same 297 00:16:56,440 --> 00:16:59,560 Speaker 2: thing every day. You know, they might get thrown off 298 00:16:59,600 --> 00:17:03,280 Speaker 2: by the press, some predators, or the weather changes or whatever, 299 00:17:03,840 --> 00:17:06,080 Speaker 2: but they have a pattern they adopt when those things 300 00:17:06,119 --> 00:17:09,359 Speaker 2: happen too. We just might not know what the hell 301 00:17:09,400 --> 00:17:13,520 Speaker 2: that means. We also know that prey animals that make 302 00:17:13,560 --> 00:17:16,879 Speaker 2: their daily habits a little too well known are ripe 303 00:17:16,920 --> 00:17:20,920 Speaker 2: for predation. The deer that vary up their schedule make 304 00:17:21,000 --> 00:17:25,320 Speaker 2: themselves less patternable, which makes them more likely to survive. 305 00:17:26,200 --> 00:17:29,120 Speaker 2: I think this is where the lesson matters the most. 306 00:17:30,040 --> 00:17:32,359 Speaker 2: Just like when you're writing a song, an instinctively no 307 00:17:32,560 --> 00:17:34,840 Speaker 2: to give some space at certain points in the rhythm 308 00:17:34,920 --> 00:17:38,960 Speaker 2: or the melody, the patterns deer follow often have a 309 00:17:39,000 --> 00:17:42,600 Speaker 2: lot of dead air in between the movements. We want 310 00:17:42,680 --> 00:17:44,919 Speaker 2: bucks that do the same thing every day, but the 311 00:17:44,960 --> 00:17:47,879 Speaker 2: bucks that do that often get shot when they're a 312 00:17:47,960 --> 00:17:49,520 Speaker 2: year and a half old or two and a half 313 00:17:49,600 --> 00:17:53,439 Speaker 2: years old. The bucks that make it to maturity, you know, 314 00:17:53,520 --> 00:17:58,159 Speaker 2: either consciously or probably unconsciously, engage in a lifestyle that 315 00:17:58,480 --> 00:18:02,400 Speaker 2: isn't point a to be cookie cutter stuff. Every day. 316 00:18:02,760 --> 00:18:06,439 Speaker 2: They change up their routine often and bed here or 317 00:18:06,480 --> 00:18:08,919 Speaker 2: there and take this trail and not that one. But 318 00:18:09,000 --> 00:18:11,760 Speaker 2: over time, if you do your job, you'll see a 319 00:18:11,880 --> 00:18:15,359 Speaker 2: pattern in the conditions and the location that comes together 320 00:18:15,520 --> 00:18:17,720 Speaker 2: to give you higher odds of running into the deer 321 00:18:17,760 --> 00:18:20,920 Speaker 2: that you want to run into. That's what's so damn 322 00:18:20,920 --> 00:18:24,320 Speaker 2: fun about this stuff. You can get it dialed or 323 00:18:24,359 --> 00:18:27,800 Speaker 2: think you have it dialed, and still fail miserably. But 324 00:18:27,880 --> 00:18:30,080 Speaker 2: you can also get it dialed and wash it work 325 00:18:30,119 --> 00:18:33,480 Speaker 2: out in real time. And there are very few feelings 326 00:18:33,480 --> 00:18:36,399 Speaker 2: in hunting that rival that accomplishment because it's just so 327 00:18:36,680 --> 00:18:40,160 Speaker 2: dang rare and so special. So think about this as 328 00:18:40,200 --> 00:18:43,680 Speaker 2: your scouting right now, and as your turkey hunting, and 329 00:18:43,840 --> 00:18:46,760 Speaker 2: you know, you watch some shedbuck hop a fence in 330 00:18:46,800 --> 00:18:49,320 Speaker 2: a certain spot and drop into a valley, and as 331 00:18:49,320 --> 00:18:51,720 Speaker 2: you're thinking about getting some cameras out, you know, in 332 00:18:51,720 --> 00:18:54,240 Speaker 2: the next couple of months, think about this stuff and 333 00:18:54,280 --> 00:18:58,120 Speaker 2: their patterns. Think about coming back next week because I'm 334 00:18:58,119 --> 00:19:01,800 Speaker 2: going to talk about regrets in life and in hunting. 335 00:19:03,760 --> 00:19:05,800 Speaker 2: That's it for this week. I'm Tony Peterson. This has 336 00:19:05,840 --> 00:19:09,080 Speaker 2: been the Wired to Hunt Foundation's podcast, which is brought 337 00:19:09,200 --> 00:19:12,359 Speaker 2: to you by First Light. As always, thank you so 338 00:19:12,480 --> 00:19:15,679 Speaker 2: much for your support everybody here at Meat Eater. We 339 00:19:15,760 --> 00:19:18,600 Speaker 2: are nothing without you, so it truly means the world 340 00:19:18,640 --> 00:19:20,520 Speaker 2: to us that you show up and you support us. 341 00:19:21,119 --> 00:19:23,320 Speaker 2: If you're dying to get more of a fix on 342 00:19:23,400 --> 00:19:26,440 Speaker 2: some content, whether that's an article, maybe you know Clay's 343 00:19:26,520 --> 00:19:29,360 Speaker 2: podcast or the Element Boys or whatever, or you want 344 00:19:29,359 --> 00:19:31,960 Speaker 2: to watch some hunting videos, head on over to the 345 00:19:32,000 --> 00:19:35,440 Speaker 2: meeteater dot com tons of content there. Maybe you'll find 346 00:19:35,480 --> 00:19:37,919 Speaker 2: a recipe for that gobbler you're gonna kill this week, whatever, 347 00:19:38,000 --> 00:19:46,280 Speaker 2: go check it out. Thank you