Latest / Wired To Hunt Podcast / Ep. 291: Patterning Locations, Instead of Bucks with Joe Elsinger

Transcript

Ep. 291: Patterning Locations, Instead of Bucks with Joe Elsinger · Wired To Hunt Podcast

• 0:02
  Speaker 1: Welcome to the Wire to Hunt podcast, your home for
• 0:06
  Speaker 1: deer hunting news, stories and strategies, and now your host,
• 0:12
  Speaker 1: Mark Kenyon. Welcome to the Wired to Hunt podcast. I'm
• 0:17
  Speaker 1: your host, Mark Kenyan, and this episode number two ordered
• 0:20
  Speaker 1: in nine one. Joining me today is accomplished public land
• 0:24
  Speaker 1: deer hunter Joe Elsinger to break down how he patterns
• 0:28
  Speaker 1: locations instead of bucks and the tools he uses to
• 0:31
  Speaker 1: analyze deer movements and correlation with weather related factors. All right,
• 0:40
  Speaker 1: welcome to the Wire to Hunt podcast, brought to you
• 0:42
  Speaker 1: by on X and today, as I just mentioned, we've
• 0:46
  Speaker 1: got Joe Elsinger, also commonly known as the Professor, and
• 0:50
  Speaker 1: we call him that because he is a thinker. He
• 0:53
  Speaker 1: is uh, he's an analyzer. He's he's a detail oriented
• 0:57
  Speaker 1: problem solver I think would be a good way to
• 0:59
  Speaker 1: put it when it comes to chasing mature bucks. And
• 1:02
  Speaker 1: he's doing this on public land in the Big Woods
• 1:05
  Speaker 1: of Wisconsin and up in Iowa. He's been the show
• 1:09
  Speaker 1: a couple of times before. He's proven to be a
• 1:12
  Speaker 1: fan favorite guest, just a really good educator. I think
• 1:15
  Speaker 1: something about the way he communicates makes it easily take in,
• 1:19
  Speaker 1: but a powerful stuff. So episode number one fifty in particular,
• 1:24
  Speaker 1: is a must listen if you have an artist. Checked
• 1:26
  Speaker 1: that one out, as it covers Joe's kind of total
• 1:29
  Speaker 1: all around hunting strategy. But today we're focusing on one
• 1:33
  Speaker 1: particular topic, which is patterning deer, or or I guess
• 1:39
  Speaker 1: at least at least that's what I thought we were
• 1:41
  Speaker 1: going to talk about when I started this conversation with it,
• 1:44
  Speaker 1: because I thought, Okay, let's dive deep into patterning deer.
• 1:47
  Speaker 1: But what I quickly discovered was that's that's not really
• 1:50
  Speaker 1: what Joe is focusing on. Rather, he's all about patterning
• 1:54
  Speaker 1: specific locations, and then he's using a really detailed kind
• 1:59
  Speaker 1: of process of collecting and analyzing data to help him
• 2:03
  Speaker 1: do that help him understand when to hunt certain spots
• 2:07
  Speaker 1: throughout the year and in different prime places to be
• 2:11
  Speaker 1: all throughout the year. So it's not just about when
• 2:13
  Speaker 1: to kill this bucket, when's the best day to go
• 2:15
  Speaker 1: in after him, it's what's the best place to be
• 2:17
  Speaker 1: no matter what time of year it is. And man,
• 2:21
  Speaker 1: it's just a really interesting way of thinking about this
• 2:24
  Speaker 1: um and it's different than what most other people talk about,
• 2:28
  Speaker 1: and really the way I talk about this stuff too,
• 2:30
  Speaker 1: So this is kind of a new idea for me
• 2:33
  Speaker 1: that I'm definitely gonna be taken to heart this year.
• 2:35
  Speaker 1: So that's what we'renna be talking about. We're also going
• 2:38
  Speaker 1: to be discussing the tools he's created to analyze all
• 2:41
  Speaker 1: sorts of data like this. He's got a really interesting
• 2:45
  Speaker 1: set of analyzes he runs on trail camera data. So
• 2:48
  Speaker 1: we're gonna talk about that. We're gonna talk about the
• 2:50
  Speaker 1: lessons he's learned and the trends he's uncovered when he's
• 2:54
  Speaker 1: studying all these different types of deer settings and photos
• 2:57
  Speaker 1: and then comparing them to changes and things like temperature
• 3:00
  Speaker 1: and pressure and the moon and much more. So, Man,
• 3:03
  Speaker 1: I'll tell you what. If you enjoy geeking out over deer,
• 3:06
  Speaker 1: today's episode is for you. That's said. Before we get
• 3:11
  Speaker 1: to it, we are going to take a really quick
• 3:13
  Speaker 1: break and then we will get to our chat with Joe. Alright,
• 3:20
  Speaker 1: So with me now back on the show for I
• 3:23
  Speaker 1: think the third time, maybe, is Joe Elsinger really to
• 3:28
  Speaker 1: call you the professor? Joe, thanks for thanks for coming back.
• 3:32
  Speaker 1: Thank you. It's happy to be here. Since since the
• 3:36
  Speaker 1: professor name was applied to you on the podcast A
• 3:39
  Speaker 1: couple of years ago. Do you have anyone yet that
• 3:41
  Speaker 1: makes jokes about like tweet vests and pipes and glasses everything.
• 3:46
  Speaker 1: I think I've gotten a couple of those comments. Yeah,
• 3:49
  Speaker 1: and that's definitely not me. Anyone who's hung out with me,
• 3:52
  Speaker 1: that's definitely not me. So yeah, maybe another twenty years.
• 3:58
  Speaker 1: That's good, Glenn, it's given you a hard time. Thank
• 4:00
  Speaker 1: you Andy May for that one. I think. Yeah. Yeah, Well,
• 4:05
  Speaker 1: I'm glad you are back with us because because each
• 4:07
  Speaker 1: time I've gotten a chat with you, it's just been
• 4:09
  Speaker 1: super interesting for me, and we've we've always gotten great feedback.
• 4:12
  Speaker 1: People have found your insights really helpful. And today I'm
• 4:17
  Speaker 1: sure we're gonna we're gonna get the same kind of thing.
• 4:19
  Speaker 1: But I'm excited and I kind of want to just
• 4:22
  Speaker 1: jump right into it. Joe Hope, you don't mind me
• 4:24
  Speaker 1: avoiding four play and just going right to the main event,
• 4:28
  Speaker 1: because we got a cool topic today of patterning deer
• 4:34
  Speaker 1: and correlating deer activity to other outside factors. And this
• 4:39
  Speaker 1: idea came about because I don't know, a month or
• 4:43
  Speaker 1: two ago, me and Dan we're doing a podcast just
• 4:45
  Speaker 1: the two of us, and we were talking about um,
• 4:48
  Speaker 1: how I how both of us really are looking at
• 4:51
  Speaker 1: annual patterns and looking through trial camera data and stuff.
• 4:55
  Speaker 1: And I happened to bring up the fact that I,
• 4:57
  Speaker 1: excuse me, I had made kind of uh, pretty rudimentary
• 5:02
  Speaker 1: spreadsheet in which I was tracking all the daylight pictures
• 5:06
  Speaker 1: and daylight observations I had of a certain buck and
• 5:09
  Speaker 1: then a certain number of other variables weather related things. UM.
• 5:13
  Speaker 1: So I was talking about that to damn, and then
• 5:14
  Speaker 1: a bunch of people asked me to share that spreadsheet.
• 5:17
  Speaker 1: So I shared a picture of it on Instagram, and
• 5:19
  Speaker 1: I think maybe that's what you saw, because then you
• 5:21
  Speaker 1: reached out to me and said, hey, um, you know
• 5:24
  Speaker 1: I do the same thing. You might remember we talked
• 5:26
  Speaker 1: about it a little bit a couple of years ago,
• 5:28
  Speaker 1: but you you, you shared with me this document and
• 5:31
  Speaker 1: you just take things to a whole new level as
• 5:35
  Speaker 1: far as tracking deer movement and all the different, um
• 5:40
  Speaker 1: correlating variables, and just the document itself kind of blew
• 5:45
  Speaker 1: my mind. The level of analysis you put in here
• 5:47
  Speaker 1: trying to understand what different things impact dear movement, how
• 5:51
  Speaker 1: you're tracking these things. Um, the level of detail on
• 5:55
  Speaker 1: analysis is just it's it's fascinating and I think it
• 5:58
  Speaker 1: would really help people. There's a lot of folks know, uh,
• 6:02
  Speaker 1: to pay attention like, oh yeah, I think you know,
• 6:04
  Speaker 1: cold friends will make dear move more, or I think
• 6:06
  Speaker 1: such and such thing, and there's lots of different theories. Um.
• 6:09
  Speaker 1: Not a lot of people I know actually go about
• 6:13
  Speaker 1: tracking it in a way that can be quantified. Um.
• 6:16
  Speaker 1: But I guess if you go by the by the
• 6:19
  Speaker 1: what's the word um not nickname is a fancier word
• 6:22
  Speaker 1: for nickname blanket on right now. But if people call
• 6:24
  Speaker 1: you the professor, you should probably quantify your work and
• 6:27
  Speaker 1: you do that. Yeah, I'm an engineer by trade, so
• 6:31
  Speaker 1: that's my disclaimers. I'm a numbers guy. I'm a nerd.
• 6:34
  Speaker 1: I'm happy to admit that I'm a nerd. So it's
• 6:36
  Speaker 1: definitely not for everybody, but yeah, thanks, um, yeah you
• 6:39
  Speaker 1: are a spot on and how that? How that? Um?
• 6:43
  Speaker 1: Why I passed it on to you. So, as I
• 6:46
  Speaker 1: mentioned to you before we started recording, I was a
• 6:48
  Speaker 1: little I'm a little behind on your podcast, which I love. Um,
• 6:52
  Speaker 1: I've you know, listen to every single one, but I'm
• 6:54
  Speaker 1: a couple of months behind here. A few weeks ago
• 6:56
  Speaker 1: I finally got to that podcast where you were talking
• 6:58
  Speaker 1: about track that spreadsheet with or You're you know how
• 7:02
  Speaker 1: you've been tracking observations with Dan, and yeah, that's exactly
• 7:05
  Speaker 1: what I was like, you know what, I think I
• 7:07
  Speaker 1: need to send that to Mark. So I'm glad. Yeah,
• 7:11
  Speaker 1: it's it's spurred this bigger conversation. So so what I
• 7:14
  Speaker 1: want to do here, Joe is is talk in detail
• 7:17
  Speaker 1: about kind of you know, we we spoke briefly about
• 7:20
  Speaker 1: patterning deer a couple of years ago, but now I
• 7:22
  Speaker 1: want to go really deep into everything you're thinking about
• 7:25
  Speaker 1: when it comes to understanding dear movement, maybe understanding specific
• 7:29
  Speaker 1: deer and all of these things you're tracking and monitoring
• 7:32
  Speaker 1: and trying to make decisions based off of. So to
• 7:35
  Speaker 1: kick it off, I think I first want to lay
• 7:38
  Speaker 1: some groundwork, lay some gets, some definitions, some some foundations
• 7:41
  Speaker 1: out here. So when I say something like pattern a deer,
• 7:44
  Speaker 1: when you think about patterning a deer, what does that
• 7:48
  Speaker 1: mean to you? Yeah, so it's interesting, Um it used
• 7:53
  Speaker 1: to mean, um, probably what the first thing that pops
• 7:57
  Speaker 1: into the head of everybody else You used to look
• 8:00
  Speaker 1: at individual deer And I still do don't get me wrong.
• 8:04
  Speaker 1: But now I have kind of UM that's actually pretty
• 8:08
  Speaker 1: very hard. Everybody knows it's very very hard to pattern
• 8:10
  Speaker 1: individual deer um bucks have individual personalities. Some are easier
• 8:16
  Speaker 1: to pattern. They may have a very small core area,
• 8:19
  Speaker 1: UM it's not necessarily easy to kill. And other ones
• 8:21
  Speaker 1: have huge core areas and they seem to drift around
• 8:24
  Speaker 1: and many many different betting areas across thousands of acres
• 8:27
  Speaker 1: and everything in between. So patterning an individual deer, you know, yeah,
• 8:32
  Speaker 1: I've done it, Um, I've killed a compauty or that
• 8:35
  Speaker 1: I can say I went to a spot to kill them,
• 8:37
  Speaker 1: and I've killed them. But you're going to fail more
• 8:40
  Speaker 1: often than you succeed. UM. So now I really look
• 8:44
  Speaker 1: um at locations and I try to identify, um, the
• 8:51
  Speaker 1: optimal times for locations UM. And so I'm really patterning
• 8:55
  Speaker 1: locations UM. And I found that's actually more outful to
• 9:00
  Speaker 1: me then when I was just going around and trying
• 9:02
  Speaker 1: to figure out, Okay, this deer's here and he's going
• 9:04
  Speaker 1: to be over there tomorrow and then and then you
• 9:06
  Speaker 1: know over there, uh, you know, two days from now, UM,
• 9:10
  Speaker 1: trying to figure that out. Now I look at individual
• 9:13
  Speaker 1: locations and I keep track of the bucks in the area.
• 9:15
  Speaker 1: But I can particularly betting areas because I hunt UM.
• 9:19
  Speaker 1: You know, the refresher from some of the things that
• 9:21
  Speaker 1: I've set a previous podcast. I hunt majority, vast majority
• 9:25
  Speaker 1: of public land UM and uh, you know, even the
• 9:29
  Speaker 1: private land hunts generally shared with UM, and I don't.
• 9:33
  Speaker 1: I used toime more private land. I'm very little, but
• 9:36
  Speaker 1: I you know, no exclusive access property. So all the
• 9:39
  Speaker 1: deer are getting pressured UM. So it's really you have
• 9:43
  Speaker 1: to dial into the betting UM to have success, especially
• 9:46
  Speaker 1: with the chair bus UM. And that's what I do.
• 9:49
  Speaker 1: So I'm trying to figure out when certain betting areas
• 9:52
  Speaker 1: are used UM. And I've learned a lot about that
• 9:55
  Speaker 1: over the last few years UM primary by using observations
• 9:59
  Speaker 1: while unning, but primarily UM setting trail cameras in bedding
• 10:04
  Speaker 1: or in travel routes right next to betting UM off fall.
• 10:09
  Speaker 1: I used to think having a trail camera for four
• 10:11
  Speaker 1: weeks straight and not touching it UM was a long time.
• 10:14
  Speaker 1: Now I think that's actually short. That kind of shows
• 10:16
  Speaker 1: how I've evolved in my thought process. And now I'll
• 10:19
  Speaker 1: put them out in July, August, September. I've got a
• 10:24
  Speaker 1: few cameras out already to get need to get a
• 10:25
  Speaker 1: few more out in the next month or two, and
• 10:28
  Speaker 1: they're going to stay there until the winter. Some of
• 10:30
  Speaker 1: them I won't pick up till next spring. And I
• 10:32
  Speaker 1: get these long, big chunks of data UM, and so
• 10:36
  Speaker 1: I can sift through it and I look at wind, temperature,
• 10:40
  Speaker 1: barometric pressure, UM and all these all these factors, UM.
• 10:47
  Speaker 1: And I've learned that betting areas, there's really strong correlations
• 10:53
  Speaker 1: between some of these things and when certain betting areas
• 10:57
  Speaker 1: are being used and and there'll being is by certain books.
• 11:01
  Speaker 1: Certainly because I'm targeting buck betting. I'm sure buck betting
• 11:04
  Speaker 1: UM that that really has helped my efficiency UM in
• 11:08
  Speaker 1: targeting these these spots. So you know, I may have
• 11:12
  Speaker 1: three or four months worth at the dead off of
• 11:14
  Speaker 1: one camera, and uh, you know there's strong correlations. And hey,
• 11:20
  Speaker 1: this betting area is used with you know, strong west winds,
• 11:23
  Speaker 1: not light winds, you know, UM, you know, colder than
• 11:26
  Speaker 1: average temperatures UM, things like that at certain times of
• 11:30
  Speaker 1: the year. You know, maybe it's mostly during the rut,
• 11:33
  Speaker 1: or maybe it's mostly in the early season. UM. I
• 11:35
  Speaker 1: found betting that's primarily used in hot weather primarily used
• 11:39
  Speaker 1: in you know, cool weather, UM, windy weather, calm weather,
• 11:44
  Speaker 1: stable weather, um, bad unpleasant rainy weather. UM. It's just
• 11:50
  Speaker 1: really kind of eye opening to me. And then you're
• 11:52
  Speaker 1: able to just be that much more efficient with your
• 11:55
  Speaker 1: hunts then at any given time of the year, you know,
• 11:57
  Speaker 1: the highest optimal, the optimal I'm to be in any
• 12:00
  Speaker 1: given area. Yeah, that's the goal. And it you know,
• 12:04
  Speaker 1: it's it's never don't get me wrong. I'm still far
• 12:07
  Speaker 1: from perfection, like, but I've come a long ways. Um.
• 12:11
  Speaker 1: Now I think you know, give me six eight clean
• 12:15
  Speaker 1: hunts at times that I can pick and you know
• 12:17
  Speaker 1: I can get an opportunity here too in just that
• 12:20
  Speaker 1: many hunts on public land. Granted this is Iowa. We
• 12:23
  Speaker 1: have a very good population with share box, but still
• 12:25
  Speaker 1: you know it's public land. UM. And I would point out, Um,
• 12:29
  Speaker 1: I've done us. I'm doing more and more of this
• 12:32
  Speaker 1: research and up in uh northern Wisconsin too, um, in
• 12:36
  Speaker 1: public land up there, so it's a completely different environment.
• 12:39
  Speaker 1: But UM, it helps me kind of um confirm a
• 12:43
  Speaker 1: lot of these things that it's not just an Iowa thing.
• 12:46
  Speaker 1: You know that I'm able to do this. I'm binding
• 12:49
  Speaker 1: very strong trends in Wisconsin as well in big woods
• 12:52
  Speaker 1: habitat swamps and Tamarack swamps and you know, uh around
• 12:58
  Speaker 1: clear cuts and oak blatts and that kind of thing.
• 13:01
  Speaker 1: So um, yeah, it's it's very interesting to me anyway.
• 13:08
  Speaker 1: I'm you know, I love um that side of things.
• 13:12
  Speaker 1: It's not for everybody. I know. I've talked to people
• 13:14
  Speaker 1: about it, and some you know, it sucks all fun
• 13:16
  Speaker 1: out of it. This is intended to take the fun
• 13:18
  Speaker 1: out of it. If it's not fun to think about this,
• 13:21
  Speaker 1: then okay, just go hunting. But if you do like
• 13:23
  Speaker 1: to really try to stack the deck in your favor
• 13:26
  Speaker 1: and play the odds, you know, that's what I That's
• 13:28
  Speaker 1: what I love. It's it's funny. Speaking of Iowa, I
• 13:31
  Speaker 1: gotta call out. I gotta call out Dan, who's not
• 13:35
  Speaker 1: with us here today, but he's not here to defend himself,
• 13:39
  Speaker 1: so so sorry. In advanced Dan, I'm going to call
• 13:41
  Speaker 1: you out. But last last time or two times ago
• 13:44
  Speaker 1: that you were on the show, Joe, Um, you were
• 13:47
  Speaker 1: talking about this idea of how you run your cameras,
• 13:50
  Speaker 1: and then at the end of the episode you gave
• 13:52
  Speaker 1: both Dan and I a piece of advice and your
• 13:56
  Speaker 1: piece of advice for Dan was don't check your cameras
• 13:59
  Speaker 1: so often you go and so often check them, check them,
• 14:02
  Speaker 1: check them. And he said, oh, he's okay, I'll take
• 14:04
  Speaker 1: your advice. And then I can confirm that he has
• 14:07
  Speaker 1: not been taking your advice. He keeps talking about going
• 14:09
  Speaker 1: there checking him. I've been listed. So yeah, if I
• 14:14
  Speaker 1: remember right, last year he left one camera out like
• 14:17
  Speaker 1: all fall. He forgot to check it or maybe you
• 14:18
  Speaker 1: forgot where it was or something. Yeah, I don't know.
• 14:21
  Speaker 1: And then he was super excited about that, you know,
• 14:23
  Speaker 1: like what he learned off that, And I was like,
• 14:25
  Speaker 1: oh my god, yeah, he realizes it now, I don't know. Yeah,
• 14:29
  Speaker 1: it's so. And that's the thing, like, yes, there are
• 14:32
  Speaker 1: some most of most of you know, I'm not targeting
• 14:36
  Speaker 1: food sources. I'm targeting betting. You can hang cameras on
• 14:40
  Speaker 1: the edge of the food sources and it's a lot
• 14:42
  Speaker 1: lower impact to check them in In many circumstances, I'm
• 14:46
  Speaker 1: still lary of regular checking anything near where I'm hunting.
• 14:51
  Speaker 1: But um, and now, of course you have wireless cameras,
• 14:53
  Speaker 1: and that's a whole another um. You know, it gives
• 14:55
  Speaker 1: a whole another um. People that want to use them.
• 14:59
  Speaker 1: You know, that really pens up a lot of options
• 15:01
  Speaker 1: for monitoring. But still, if you're intruding on betting, mature
• 15:06
  Speaker 1: bucks will notice it, they will move accordingly. They may
• 15:10
  Speaker 1: still be in the area, they might only move across
• 15:12
  Speaker 1: the ridge, but they will know you're there, and they will,
• 15:15
  Speaker 1: you know, make sure that they're not you know, they
• 15:18
  Speaker 1: don't have much risk from you. So um, it's uh.
• 15:24
  Speaker 1: You know, you can hang cameras and check them frequently
• 15:27
  Speaker 1: in near food sources. Sometimes that's certainly true. But where
• 15:31
  Speaker 1: I'm putting them, I couldn't go in and check. I
• 15:33
  Speaker 1: would blow every you know, I'd blow deer out of
• 15:35
  Speaker 1: Sometimes they're where I want to hunt, and I go
• 15:37
  Speaker 1: in there and do a hunt and that's it. But
• 15:39
  Speaker 1: I've seen when in circumstances like that, Um, I've seen
• 15:44
  Speaker 1: the impact where like you know, I'll get say three
• 15:48
  Speaker 1: or four mature buck sightings in daylight over the course
• 15:52
  Speaker 1: of a week, and then I'll have been in there,
• 15:56
  Speaker 1: or more often, because it's a public land, I'll see
• 15:58
  Speaker 1: a hunter on camera, you know, whether it's a squirrel
• 16:00
  Speaker 1: hunter or another bow hunter or whatever coming through, and um,
• 16:05
  Speaker 1: it'll be several days they'll be just very minimal activity
• 16:08
  Speaker 1: and then I'll pick up again. So, um, I see
• 16:11
  Speaker 1: that all the time, even during the rut. I mean
• 16:14
  Speaker 1: a lot of people who bucks are everywhere in the rut. Yeah,
• 16:17
  Speaker 1: they definitely move a lot more, but they're still very
• 16:20
  Speaker 1: intentional about where they move. Um and um that you
• 16:26
  Speaker 1: can disturb an area and there'll be a decrease in
• 16:29
  Speaker 1: what you'll see in front of there in these these
• 16:32
  Speaker 1: high impact areas. You know, it's one thing if you're
• 16:35
  Speaker 1: just walking along the field edge, but it's another thing
• 16:36
  Speaker 1: if you're walking in a bedding area wanted yards from
• 16:40
  Speaker 1: a field, or like a northern Wisconsin it's a it's
• 16:43
  Speaker 1: it's huge up there. I'll I'll hunting swamp island where
• 16:48
  Speaker 1: I'll have a camera and then like for a week,
• 16:50
  Speaker 1: I won't get a deer, you know. So um, it's
• 16:54
  Speaker 1: it's interesting. So so in this kind of situation, if
• 16:58
  Speaker 1: you're trying to pattern a location, before we get into
• 17:02
  Speaker 1: all the variables you're looking at and all the data
• 17:04
  Speaker 1: and stuff, let's first just cover let's check the box
• 17:07
  Speaker 1: on how you get the data, which is pictures. Right.
• 17:10
  Speaker 1: Can you just walk me through a little bit more
• 17:12
  Speaker 1: detail of when you're trying to patter on a location, UM,
• 17:15
  Speaker 1: you know what you're thinking about as far as where
• 17:17
  Speaker 1: you're gonna put a camera. How many cameras do you
• 17:20
  Speaker 1: put out? Do you have like any kind of system
• 17:22
  Speaker 1: in place, like if you wanted to learn this betting area,
• 17:25
  Speaker 1: do you put several cameras around it? Or what's your
• 17:28
  Speaker 1: thought process once you're you're starting. So, I mean, now
• 17:32
  Speaker 1: I have a lot of cameras. I by my standards,
• 17:35
  Speaker 1: I used to think ten cameras is a lot. Now
• 17:38
  Speaker 1: I probably have like fifteen. And you know, I just
• 17:40
  Speaker 1: bought a couple of years and for a number of
• 17:42
  Speaker 1: years now and now I've built up a larger quantity,
• 17:47
  Speaker 1: but still it's not many. And um, I know some
• 17:49
  Speaker 1: people just carpet an area with cameras. Um I've never
• 17:53
  Speaker 1: done that. Um, partly because I don't have that many cameras.
• 17:57
  Speaker 1: I don't have. Occasional I'll drop in a couple of
• 18:00
  Speaker 1: post pretty close together if I really can't figure out
• 18:02
  Speaker 1: an area. But you do have to have a baseline
• 18:04
  Speaker 1: knowledge of how mature bucks move across um the land.
• 18:09
  Speaker 1: And I know I've talked about this before, Like you've
• 18:11
  Speaker 1: got to achieve that cameras don't even necessarily tell you
• 18:14
  Speaker 1: all that. You've got to kind of learned that the
• 18:17
  Speaker 1: hard way by a lot of hunting and a lot
• 18:18
  Speaker 1: of time invested in observing them. UM. And then you
• 18:23
  Speaker 1: you know, I can go in and I can pick
• 18:25
  Speaker 1: out you know, if I think bucks betting in an area,
• 18:29
  Speaker 1: I can pick out two or three most likely travel
• 18:32
  Speaker 1: routes in and out of that um, you know, and
• 18:35
  Speaker 1: then sometimes it's one or two that seemed to be
• 18:38
  Speaker 1: clearly favored. UM. And it's really interesting. I've gotten to
• 18:41
  Speaker 1: the point of UM and anybody else can to UM.
• 18:44
  Speaker 1: You can predict like, oh, they'll come in this way,
• 18:47
  Speaker 1: you know, to bed in the morning, and they'll leave
• 18:49
  Speaker 1: that way in the evening. Um. You know, in the
• 18:53
  Speaker 1: morning jay hook they usually do jay hook um, and
• 18:56
  Speaker 1: in the evening they usually get up and just leave
• 18:58
  Speaker 1: straight going to oot or does whoever their destination is.
• 19:02
  Speaker 1: So UM, it's often two different directions. They don't come
• 19:06
  Speaker 1: and go. And I see that on camera too. UM
• 19:09
  Speaker 1: when I'm setting a camera, like on an access route
• 19:12
  Speaker 1: into bedding, I know. Okay, well, I don't always know
• 19:17
  Speaker 1: ahead of time. Sometimes they surprise me, but usually I
• 19:20
  Speaker 1: get mostly morning activity or even activity, even though the
• 19:24
  Speaker 1: dearer there all day, they don't come and go on
• 19:26
  Speaker 1: that camera. You know. There it's the heavily favor either
• 19:30
  Speaker 1: morning or evening. And if my cameras in the bedding,
• 19:32
  Speaker 1: I'll get a lot of midday movement. Um. Bucks are
• 19:35
  Speaker 1: up and moving mid day more than you'd believe. They
• 19:38
  Speaker 1: don't move very far usually, especially on public land and stuff,
• 19:43
  Speaker 1: but they do get up. They have to get up biologically, Um,
• 19:45
  Speaker 1: they have to stand up. They cannot lay on the
• 19:48
  Speaker 1: ground for twelve hours straight, from what I understand, or
• 19:50
  Speaker 1: they'll die. So they have to get up, brows, relieve
• 19:53
  Speaker 1: themselves and be back down. UM. So I'll get them
• 19:56
  Speaker 1: doing that all the time. If my camera is literally right,
• 19:58
  Speaker 1: you know, say watch a cluster of beds or right
• 20:01
  Speaker 1: between a couple of beds. So another reason deer get
• 20:05
  Speaker 1: up and move. And this is another big indicator of
• 20:07
  Speaker 1: peed in on its temperature. UM. As a temperature changes
• 20:10
  Speaker 1: over the course of the day, deer will move. Say
• 20:12
  Speaker 1: it's hot weather, they will move to the coolest spot.
• 20:15
  Speaker 1: It's kind of temperature based bedding. And that's um. There's
• 20:19
  Speaker 1: actually some really strong trends there. Um. You know they
• 20:22
  Speaker 1: will seek cool when it's hot, and they will seek
• 20:26
  Speaker 1: warmer areas when it's cold, and you know, getting out
• 20:30
  Speaker 1: of the elements, they'll seek the thermal cover. Um, and
• 20:33
  Speaker 1: that will change over the day. You know, they may
• 20:35
  Speaker 1: be I've I've pot cameras over over individual beds, and
• 20:41
  Speaker 1: I'll get deer consistently, Like they'll bed there up until
• 20:44
  Speaker 1: ten am, and then they'll get up and leave because
• 20:47
  Speaker 1: it gets too sunlit and warm in the say the
• 20:50
  Speaker 1: summer months, and they'll they'll be moving to a more shaded,
• 20:53
  Speaker 1: cooler area. So UM, yeah, that's that's Uh. In all
• 20:58
  Speaker 1: those little you know, there's no one thing that oh
• 21:02
  Speaker 1: you know you can use this and all of a
• 21:04
  Speaker 1: sudden you get killed big bucks. There's all these little
• 21:06
  Speaker 1: layers you can put together, and um, it's fascinating. I
• 21:09
  Speaker 1: don't I'm not even I'm definitely not an expert um
• 21:13
  Speaker 1: on it, but I've started to kind of grasp the
• 21:17
  Speaker 1: overall um picture. They still surprise me. Um surprised me
• 21:22
  Speaker 1: a lot. But yeah, that's so I'm taking what I'm
• 21:25
  Speaker 1: doing here. Um. You know, I'll leave a camera. Say
• 21:28
  Speaker 1: last year, I had roughly a dozen cameras sprinkled across
• 21:33
  Speaker 1: three or four counties in Iowa. And you know ten
• 21:37
  Speaker 1: thousand acres of public land up in Wisconsin. UM. Yeah,
• 21:41
  Speaker 1: it's not each less cameras up in Wisconsin. But um
• 21:45
  Speaker 1: and pull them, pull the cards and literally UM. So
• 21:50
  Speaker 1: I this me, being a nerd over the years, I
• 21:53
  Speaker 1: used to in a spreadsheet format, enter the date, enter
• 21:58
  Speaker 1: the time, Enter my estimate at each class of the book. UM.
• 22:02
  Speaker 1: To me, that's very important because different age class of
• 22:06
  Speaker 1: bucks act differently. Um. In Iowa once they hit four
• 22:11
  Speaker 1: years old, I think they really start to act differently.
• 22:14
  Speaker 1: Up in Wisconsin. I see that change more along the
• 22:16
  Speaker 1: three year old. And I think I think, you know,
• 22:18
  Speaker 1: like Michigan it might be similar. It's where there's more
• 22:21
  Speaker 1: hunting pressure and there you know, it's just less older deer.
• 22:24
  Speaker 1: So there's UM, they get just to a certain age,
• 22:26
  Speaker 1: a certain level of experience, and you know now they're
• 22:29
  Speaker 1: not in junior high anymore, nor a high school. You
• 22:32
  Speaker 1: know now they're collegiate level um in terms of staying alive. Um.
• 22:39
  Speaker 1: And so I just make a list of the deer
• 22:42
  Speaker 1: and it was a two year old, three year old,
• 22:44
  Speaker 1: four year old my estimate? Do I get it right?
• 22:46
  Speaker 1: Every time, definitely not. But most of the time I
• 22:49
  Speaker 1: think I know about what how old a deer is? UM,
• 22:53
  Speaker 1: and then UM I used to manually enter like it
• 22:57
  Speaker 1: was in the morning, it was you know, the temperature
• 23:00
  Speaker 1: at the time they movement. I would look it up
• 23:02
  Speaker 1: and I would enter, you know, fifty five degrees UM.
• 23:06
  Speaker 1: And that got old as I started to get more data.
• 23:09
  Speaker 1: So actually before you before you say that's the dumbass
• 23:13
  Speaker 1: way that I'm still doing it, and I, yeah, have
• 23:22
  Speaker 1: some help, Yeah, yeah, absolutely, UM. And that's UM up
• 23:26
  Speaker 1: until so I started doing this UM hardcore in about
• 23:30
  Speaker 1: two thousand and thirteen, like really like looking at observations
• 23:34
  Speaker 1: and trying to find trends related to weather, UM, time
• 23:38
  Speaker 1: of year, that kind of thing. UM. Here in about
• 23:42
  Speaker 1: twenty fifteen sixteen, I figured out a way to extract
• 23:47
  Speaker 1: weather data from the Noah website. It's a government website, UM,
• 23:51
  Speaker 1: and they have locations all across the US UM, and
• 23:56
  Speaker 1: I just about guarantee hunters are within you know, miles
• 24:03
  Speaker 1: of a Noah weather station that logs this data UM,
• 24:07
  Speaker 1: and you can you can download it in a spreadsheet format.
• 24:11
  Speaker 1: And now it's without getting too complex, just using a
• 24:14
  Speaker 1: simple v look up feature in xl UM. I type
• 24:18
  Speaker 1: in the date and time for the presiding and it
• 24:21
  Speaker 1: tells me temperature, precipitation, current, past and future precipitation, wind speed,
• 24:27
  Speaker 1: wind direction, sea level pressure. Um what else I'm looking
• 24:32
  Speaker 1: at it right now? Um yeah, sunrise, sunset, moon clock position,
• 24:36
  Speaker 1: moon percent illuminated all those fundal details to me anyway,
• 24:42
  Speaker 1: So UM yeah, it took in half an hour here,
• 24:45
  Speaker 1: an hour there over the course a number e years
• 24:48
  Speaker 1: to build that. But now literally all of the time
• 24:51
  Speaker 1: it takes with data entry for entering the time of
• 24:54
  Speaker 1: the date, and um, you know there is some set
• 24:58
  Speaker 1: up you know it's based on um, you know, location specifics.
• 25:02
  Speaker 1: You have to bring in the data for your you know,
• 25:04
  Speaker 1: whatever towns closest to you, usually their airports or or
• 25:08
  Speaker 1: just weather stations in in small towns. And uh now,
• 25:12
  Speaker 1: I um, you know, I have this enormous amount of
• 25:16
  Speaker 1: data Like last year, for example, I have almost five
• 25:19
  Speaker 1: data points from two year old and older bucks in Iowa,
• 25:24
  Speaker 1: and I have almost that number of data points from
• 25:27
  Speaker 1: two year old and older bucks up in Wisconsin. You know,
• 25:31
  Speaker 1: between say August and December of of last falls, so
• 25:36
  Speaker 1: for the whole fall, and I can look at the trends.
• 25:38
  Speaker 1: You know, I look at UM not just locations specific,
• 25:41
  Speaker 1: but I want to look at UM just trends overall
• 25:45
  Speaker 1: over the over the course of the rut. UM like
• 25:48
  Speaker 1: when did a peak? UM, what influences the peaks? And
• 25:52
  Speaker 1: we can really dive into that. UM. I've learned some
• 25:55
  Speaker 1: interesting things. But so so first off, to develop something
• 26:03
  Speaker 1: like this, UM, you go and you download the weather
• 26:10
  Speaker 1: data from the Noah website for a specific location, and
• 26:14
  Speaker 1: it gives you the whole and I'm I'm assuming you
• 26:16
  Speaker 1: pick a date range, so maybe October one through January
• 26:20
  Speaker 1: one or whatever it is. It gives you a spreadsheet
• 26:22
  Speaker 1: with all of the data for every single day. You
• 26:25
  Speaker 1: create a tab in your spreadsheet, paste that into the
• 26:28
  Speaker 1: tab on your spreadsheet, and then you have another tab
• 26:32
  Speaker 1: of that spreadsheet, which is where you're putting all of
• 26:34
  Speaker 1: your observations, so the dates and the times of the observation.
• 26:39
  Speaker 1: And then through some fancy spreadsheet magic, you connect to
• 26:43
  Speaker 1: those two so that spits out the data. It connects
• 26:47
  Speaker 1: between your dately you put in there, and then what
• 26:49
  Speaker 1: the actual weather is. UM. I do not remember how
• 26:52
  Speaker 1: to use Excel that well, so I couldn't do that myself. UM,
• 26:57
  Speaker 1: but I'm sure there's there's tutorials online um or maybe
• 27:01
  Speaker 1: maybe there's even a way to get a template out
• 27:03
  Speaker 1: there for people. I don't know, but yeah, there's all
• 27:06
  Speaker 1: kinds of tutorials you can. UM. I'm kind of hesitant
• 27:10
  Speaker 1: to just blast out my my my spreadsheet to everybody.
• 27:14
  Speaker 1: I've given it to a few people, but UM, you
• 27:17
  Speaker 1: know there's like you so and I. You know, say
• 27:20
  Speaker 1: November one at noon and you had a buck run
• 27:22
  Speaker 1: past your caturil camera, you enter that date and now
• 27:26
  Speaker 1: without instead of having to manually look up, oh, the
• 27:28
  Speaker 1: temperature was fifty eight degrees and all automatically poop it
• 27:32
  Speaker 1: was fifty eight degrees and this was a barometric pressure
• 27:35
  Speaker 1: and was it raining or not? Um, you know, um
• 27:38
  Speaker 1: those kind of things. So um again, the weather Web
• 27:43
  Speaker 1: weather website is the UM it's www dot n C,
• 27:50
  Speaker 1: d C, dot n O A A dot go. And
• 27:53
  Speaker 1: then you go to the local climate climate toological data
• 27:59
  Speaker 1: and it's free. Anybody can do it and you can
• 28:01
  Speaker 1: search by your location and download the weather and it's
• 28:05
  Speaker 1: usually recorded in fifteen minute or our intervals UM for
• 28:09
  Speaker 1: your location, so you know it documents what the weather
• 28:13
  Speaker 1: was and for everyone else's reference. I'm pretty sure UM
• 28:16
  Speaker 1: Underground and all the other websites. I guess WonderGround doesn't
• 28:21
  Speaker 1: even have historical data anymore. I'm not sure. I don't
• 28:23
  Speaker 1: think they do UM, but they all get it from
• 28:26
  Speaker 1: this Noah website. I think everybody does UM. I don't
• 28:29
  Speaker 1: think I like that's to go to place to get
• 28:31
  Speaker 1: UM weather data. So so in your spreadsheets you have
• 28:35
  Speaker 1: a whole bunch of different metrics or variables tracked. Are
• 28:39
  Speaker 1: these hand selected because you think that they have some
• 28:41
  Speaker 1: kind of impact or is this just everything Noah has
• 28:44
  Speaker 1: and you just allow it all to populate. Yeah, it's
• 28:47
  Speaker 1: not everything Noah has. Noah has tracks so much it's
• 28:51
  Speaker 1: it's ridiculous. Um. They have like heating degree days and
• 28:55
  Speaker 1: cooling degree days, which might be you know, might be
• 28:58
  Speaker 1: interested you if you're a hunter and doing a lot
• 29:00
  Speaker 1: of food plots. That's a measure of a lot of
• 29:04
  Speaker 1: UM farmer's day attention to you know, how warm or
• 29:07
  Speaker 1: cool versus average it is. And then I just started
• 29:10
  Speaker 1: hand picking things. UM. So it's things that I think
• 29:14
  Speaker 1: are indicators. Now I've looked into some of them, and
• 29:17
  Speaker 1: some of them don't end up being much of an indicator. Um,
• 29:20
  Speaker 1: but it's uh, it's really interesting. I mean I can
• 29:24
  Speaker 1: run it through. You know, I look at day of
• 29:26
  Speaker 1: the week. I look at a M versus PM versus
• 29:30
  Speaker 1: mid day, and I just defined midday a little arbitrarily
• 29:33
  Speaker 1: is between ten am and two pm. Um. Um, A
• 29:38
  Speaker 1: couple of things. I look at that our location specific
• 29:41
  Speaker 1: I try to I've just started, uh looking at what
• 29:45
  Speaker 1: direction bucks are headed on camera. So sometimes, um, when
• 29:51
  Speaker 1: I'm hanging a camera right in a bedding area and
• 29:53
  Speaker 1: there's a bunch of beds around, it can be confusing
• 29:56
  Speaker 1: to me, like where they're coming from, where they're going to.
• 29:59
  Speaker 1: And I've started to find trends. So I I enter,
• 30:01
  Speaker 1: say a buck's heading from left to right on camera,
• 30:05
  Speaker 1: you know, and I can remember what direction that camera
• 30:08
  Speaker 1: was pointed. So I'll enter left, right, left, right, and
• 30:11
  Speaker 1: it will say, oh, in the morning, bucks are coming
• 30:14
  Speaker 1: from the left, and the evening they're in the afternoon
• 30:16
  Speaker 1: they're coming from the right. And then I can that uh,
• 30:19
  Speaker 1: you know, that tells me a lot more than um,
• 30:23
  Speaker 1: you know, just so oh they're you know, they're betting
• 30:26
  Speaker 1: over there, you know, and then they're switching to betting
• 30:28
  Speaker 1: over here, so UM sky conditions. I look at sky conditions.
• 30:33
  Speaker 1: It's another stat from Noah overcast versus clear or versus
• 30:38
  Speaker 1: parley cloudy UM. And then I really dive into temperature.
• 30:42
  Speaker 1: In my opinion, temperature is the number one external factor
• 30:46
  Speaker 1: you know, outside like the rut um, time of year,
• 30:49
  Speaker 1: like weather factor, it's temperature UM, without a doubt, there's
• 30:54
  Speaker 1: nothing else that comes close actually um so in terms
• 30:58
  Speaker 1: of where a deer is and why he's moving UM
• 31:01
  Speaker 1: A certain to certain places. UM. So I look at
• 31:05
  Speaker 1: temperature like departure from average, meaning I look at the
• 31:09
  Speaker 1: average temperature that time of year, and is it you know, average,
• 31:12
  Speaker 1: or is a ten degrees hotter ten degrees cooler UM.
• 31:15
  Speaker 1: I look at two hour temperature change, which is kind
• 31:18
  Speaker 1: of an arbitrary number, but UM is that you know,
• 31:21
  Speaker 1: the temperature has a big impact on UM. When a
• 31:26
  Speaker 1: buckets up and moves to another bed during the middle
• 31:29
  Speaker 1: of the day, if it's warming up or cooling off.
• 31:31
  Speaker 1: So I've learned that UM. Then I look at precipitation UM.
• 31:35
  Speaker 1: Both when it's like at the time of the photo,
• 31:38
  Speaker 1: but I also want to know like what it's going
• 31:40
  Speaker 1: to do and then what it was doing before for
• 31:42
  Speaker 1: a few hours before and after because um, so so
• 31:47
  Speaker 1: what I found both in Wisconsin and down here, and
• 31:50
  Speaker 1: I've I've heard you talk about it, Mark if for To,
• 31:52
  Speaker 1: others talk about it UM, and it sounds like you know,
• 31:55
  Speaker 1: in Michigan, there's a theory that you know, older box
• 31:59
  Speaker 1: are prefer to move in the rain. What I've found
• 32:01
  Speaker 1: so far is, at least no Wisconsin, they dear don't
• 32:04
  Speaker 1: move so much in the rain. It's distinct drop. However,
• 32:07
  Speaker 1: they do really like to move right before and right
• 32:10
  Speaker 1: after the rain. UM. And I think there are just
• 32:13
  Speaker 1: a lot of time it's adjusting bedding to new locations,
• 32:16
  Speaker 1: UM to UH to seek shelter or leaving and maybe
• 32:21
  Speaker 1: going to feed UM in preparation for the rain or
• 32:24
  Speaker 1: after the rain. So that's what I found. UM. Wind direction,
• 32:29
  Speaker 1: I look at that's very locational thing. So UM it's is.
• 32:35
  Speaker 1: But I've also I've looked at all my observations altogether
• 32:39
  Speaker 1: for an entire fall. It's actually very eye opening just
• 32:43
  Speaker 1: what average wind digressive wind directions are. And this is
• 32:46
  Speaker 1: data goes back over several years, but basically a third
• 32:49
  Speaker 1: of the time the wind is south or southwest, a
• 32:53
  Speaker 1: third of the time the wind is where northwest or
• 32:56
  Speaker 1: north and then the remaining third of the time you're
• 33:00
  Speaker 1: left with west, which actually, isn't that a straight west
• 33:03
  Speaker 1: wind isn't that common for this part of the country
• 33:06
  Speaker 1: or some easterly um So, so it's very split up.
• 33:10
  Speaker 1: You usually get a southerly wind or a northerly wind,
• 33:13
  Speaker 1: you know, and occasionally something else. UM. I look at
• 33:17
  Speaker 1: barometric pressure, barometric pressure or something that I've really dove into.
• 33:22
  Speaker 1: I thought I was going to find actually more than
• 33:25
  Speaker 1: more than I end up finding. UM. So I look
• 33:28
  Speaker 1: at pressure change. UM. But I also look at just
• 33:32
  Speaker 1: like overall pressure. Um. And there's no denying. Do you
• 33:35
  Speaker 1: really like a high barometer? You get above for this
• 33:38
  Speaker 1: part of the country thirty point two five thirty point three,
• 33:42
  Speaker 1: and there's definitely um. Deer on their feet more in daylight.
• 33:46
  Speaker 1: Um And I should have lead with this, but you know,
• 33:49
  Speaker 1: I'm really looking at daylight photos only. I pretty much
• 33:53
  Speaker 1: ignored nighttime photos because well it's just you know, I'm
• 33:58
  Speaker 1: looking at times I can hide and deer, you know,
• 34:02
  Speaker 1: um do move a lot at night. But I really
• 34:04
  Speaker 1: want to know what's making them get on their feet
• 34:06
  Speaker 1: during the day. So UM, if that helps anybody along.
• 34:09
  Speaker 1: I'm really only I'm really only looking at daylight photos
• 34:13
  Speaker 1: from you know, during hunting hours, half an hour before daylight,
• 34:16
  Speaker 1: half an hour after dark. UM. Do you track your
• 34:18
  Speaker 1: observations to like what you see with your own eyes? Yes, yep, yep,
• 34:23
  Speaker 1: I do, UM, And that's actually so that's it's good, UM,
• 34:29
  Speaker 1: But it's kind of tricky and you and I hesitate
• 34:32
  Speaker 1: to let tell anyone to compare it to your trail
• 34:34
  Speaker 1: camera observations because of your UM, the size of your
• 34:38
  Speaker 1: what you're observing, and because with a trail camera you're
• 34:42
  Speaker 1: watching you know, something fifty feet or maybe at most
• 34:45
  Speaker 1: a hundred feet in front of that camera, UM, and
• 34:48
  Speaker 1: you know, a narrow window, whereas if you're sitting on stand, UM,
• 34:52
  Speaker 1: you could maybe record things in bow range, you know,
• 34:56
  Speaker 1: like because that's a fairly small area. But if you're
• 34:59
  Speaker 1: sitting on stand and you know, in one stand you
• 35:02
  Speaker 1: might in dense cover you might only be able to
• 35:04
  Speaker 1: see forty yards or thirty yards, and another stand, if
• 35:07
  Speaker 1: you can see across fields, you might be watching deer
• 35:10
  Speaker 1: four yards away. So that doesn't really tell you know,
• 35:13
  Speaker 1: if they're they're moving over there. That doesn't really tell
• 35:16
  Speaker 1: you anything about your spot, you know. Um, so, um,
• 35:21
  Speaker 1: just what you're what you're looking at has a big
• 35:24
  Speaker 1: impact there. You need to append that observation to where
• 35:29
  Speaker 1: the deer's location was, not to understand location. Yeah, back
• 35:34
  Speaker 1: to press, so pressure they deer like a high barometer.
• 35:37
  Speaker 1: But it's not. It's it's uh, it's not as big
• 35:40
  Speaker 1: of a trend as I thought it might be. I
• 35:42
  Speaker 1: compare it to like average barometric pressure for the year,
• 35:45
  Speaker 1: which um, I know Mark Drury way back and a
• 35:48
  Speaker 1: couple of his podcasts that they had talked about that
• 35:51
  Speaker 1: given into that, and it's true. You know, average barometric
• 35:54
  Speaker 1: pressure might be around thirty inches of mercury in early season,
• 36:00
  Speaker 1: and that goes up to you know, say thirty point
• 36:02
  Speaker 1: one or or or maybe a little more by November.
• 36:07
  Speaker 1: And um, you know, so, so departure from average is important.
• 36:12
  Speaker 1: It's not just um, you know, thirty point three inches
• 36:15
  Speaker 1: of mercury is screaming high in September October, but it's not.
• 36:20
  Speaker 1: It's high, but it's not as high come mid November. Um,
• 36:24
  Speaker 1: when there's an atmosphere cools, pressure on average gets still higher. Um.
• 36:29
  Speaker 1: And then of course I dive into the moon, which
• 36:31
  Speaker 1: is everyone's favorite theory. Um. And that so I look
• 36:36
  Speaker 1: at two different things. I look at both, you know,
• 36:39
  Speaker 1: phase of the moon, so um, you know, new moon,
• 36:43
  Speaker 1: full moon, and then also what I call I probably
• 36:47
  Speaker 1: spent way too much time that this by itself, I
• 36:50
  Speaker 1: probably have spent more time on than any other thing
• 36:52
  Speaker 1: because everybody else has to write, um, moon clock position,
• 36:57
  Speaker 1: so I call it moon clock position, but you know,
• 37:00
  Speaker 1: red moon, whatever you want to call it. If a
• 37:02
  Speaker 1: moon's overhead or underfoot, to me, if it's directly overhead
• 37:06
  Speaker 1: in my mind, that's twelve o'clock. Directly underfoot, that's six o'clock.
• 37:10
  Speaker 1: If it's rising, it's nine o'clock. If it's setting at
• 37:12
  Speaker 1: three o'clock. So that's how I break it down. Yeah.
• 37:15
  Speaker 1: So um, it's just you know, yeah, it's a you know,
• 37:18
  Speaker 1: and it's not the right way. It's just the way
• 37:20
  Speaker 1: I do it, and I can visualize in my head. Um, anyway,
• 37:24
  Speaker 1: what have I found. I have found absolutely no correlation
• 37:28
  Speaker 1: with moonblock position and deer movement. So um, and that's
• 37:32
  Speaker 1: out of and and I will say I used to
• 37:35
  Speaker 1: be one that I did think there was a slight correlation.
• 37:39
  Speaker 1: I just that was my qualitative observations from sitting on
• 37:42
  Speaker 1: stand man, I thought I saw a lot of deer
• 37:44
  Speaker 1: when you know the moon was overhead and underfoot or
• 37:47
  Speaker 1: rising and setting. But if it's there, it's such a
• 37:51
  Speaker 1: slight trend, and it's so overshadowed by whether whether whether
• 37:54
  Speaker 1: whether weather information or whether you know whatever the weather
• 37:58
  Speaker 1: is at the moment um. Um, I've about written it off.
• 38:03
  Speaker 1: Um moon face. I looked at that, like do they
• 38:07
  Speaker 1: prefer a full moon or new moon? And once again
• 38:10
  Speaker 1: I have not found hardly anything. I've found only one
• 38:13
  Speaker 1: thing that seems to be in associated with like moon face,
• 38:18
  Speaker 1: and that is for whatever reasons um so so. I
• 38:22
  Speaker 1: also I don't just track each observation, but then I
• 38:26
  Speaker 1: graph him on a plot him on a big graph
• 38:29
  Speaker 1: um over the course of the fall, so October, November, December, um,
• 38:34
  Speaker 1: and to see when peak activity is. Uh so you know,
• 38:38
  Speaker 1: I'm I'm getting a whole bunch of deer early November.
• 38:41
  Speaker 1: Obviously that's peak movement. That's the rout um that shouldn't
• 38:45
  Speaker 1: surprise anybody. But um, cold fronts, there's usually a spike
• 38:49
  Speaker 1: in activity. There's no cold fronts always, as everybody knows,
• 38:52
  Speaker 1: has a big impact on deer, and the bigger the
• 38:55
  Speaker 1: cold front, the better. And I'll dive into that later.
• 38:57
  Speaker 1: I'll finish talking about the moon. Um, the moon. Um.
• 39:03
  Speaker 1: Around that full moon, the running moon, quote unquote, I
• 39:07
  Speaker 1: am seeing a spike in activity. It's not huge, but
• 39:11
  Speaker 1: it seems to every single time there's a full moon
• 39:14
  Speaker 1: anywhere from you know, mid to late October to mid November.
• 39:19
  Speaker 1: Whenever that full moon falls, I'm seeing over you know,
• 39:22
  Speaker 1: in a three to five day window around that full moon,
• 39:26
  Speaker 1: mature bucks seem to be a little more on their
• 39:29
  Speaker 1: feet more during daylight. Why. I have absolutely no idea.
• 39:34
  Speaker 1: I know there's been you know, telemetry studies that have
• 39:38
  Speaker 1: not found anything. Um. However, I will say, um, I
• 39:42
  Speaker 1: think those telemetry studies are pretty limited because of how
• 39:46
  Speaker 1: they measure data. A lot of them I've noticed measure
• 39:49
  Speaker 1: like miles per day. Well, that's not nearly precise enough.
• 39:52
  Speaker 1: You need to dial into either like during daylight and
• 39:55
  Speaker 1: for weather events you need to dial into one hour
• 39:58
  Speaker 1: or two hour increments. Did you have any uh, you know,
• 40:02
  Speaker 1: uh clarity on like what a weather event has on
• 40:05
  Speaker 1: an animal a twenty four hour you know, put it
• 40:07
  Speaker 1: this way, I'm not surprised they're not finding any correlation
• 40:11
  Speaker 1: because if you're measuring distance over twenty four hour period,
• 40:15
  Speaker 1: they're getting up, they're going to eat, they're coming back,
• 40:17
  Speaker 1: you know, and they're doing that every single day, whatever
• 40:20
  Speaker 1: the weather is. But exactly when they're doing it, well,
• 40:23
  Speaker 1: that hasn't that is impacted by you know, environmental factors.
• 40:27
  Speaker 1: That it's literally that little change is what really matters
• 40:32
  Speaker 1: to those hunters. So if if a buck moved half
• 40:34
  Speaker 1: an hour early, that might not show up on their
• 40:37
  Speaker 1: on their big studies, but that sure as heck makes
• 40:39
  Speaker 1: a huge difference for us as the hunter. That's exactly
• 40:43
  Speaker 1: I'm hoping these telemetry studies get better, and I know
• 40:46
  Speaker 1: there are a lot of them are limited I believe
• 40:48
  Speaker 1: by battery life and those collars. They can't be you know,
• 40:51
  Speaker 1: strapping nine bowl batteries onto those deer. So you know,
• 40:54
  Speaker 1: the more the more data points, more pings. You know,
• 40:57
  Speaker 1: if they're doing it every fifteen minutes or every hour
• 41:00
  Speaker 1: or three times a day, that has a big impact
• 41:02
  Speaker 1: on how often they do it. So I understand it's
• 41:04
  Speaker 1: not it's not everybody's fault, but I'm hoping people start
• 41:07
  Speaker 1: to measure these researchers start to measure UM in much
• 41:11
  Speaker 1: more frequent intervals, and the sky's a limit on what
• 41:14
  Speaker 1: we'll learn about here. So so with all this stuff,
• 41:20
  Speaker 1: all this stuff that you're looking at, I mean, you
• 41:23
  Speaker 1: listed fifteen different variables or more that you're looking at.
• 41:28
  Speaker 1: You kind of mentioned a few that seem to have
• 41:30
  Speaker 1: a big impact, some others don't. When you're actually heading
• 41:35
  Speaker 1: out to hunt, or you're sitting at home before your
• 41:39
  Speaker 1: weekend hunts or whatever, and you're thinking through, what's your
• 41:42
  Speaker 1: game plan is going to be? Which one of these
• 41:46
  Speaker 1: actually factor into your decisions? Like is there a top
• 41:49
  Speaker 1: five lists or anything like that that are the real
• 41:51
  Speaker 1: heavy heaters that you really focus your time and energy around. Yeah, so, uh,
• 41:56
  Speaker 1: number one's temperature. Um, I've really learned to that. You know,
• 42:01
  Speaker 1: deer favor cool areas when it's warm out and warm
• 42:03
  Speaker 1: areas when it's cold out. Um. They still security's top priorities.
• 42:07
  Speaker 1: So you know, they're only in certain areas that they
• 42:11
  Speaker 1: feel safe, but within those UM, Like I have a theory, UM,
• 42:16
  Speaker 1: I'm not sure that deer move less when it's hot out.
• 42:19
  Speaker 1: I think they just move in different spots, and most
• 42:22
  Speaker 1: tunners aren't watching those spots. So that's part of the
• 42:24
  Speaker 1: reason why everybody, oh, it's a cold front deer moving
• 42:27
  Speaker 1: like crazy. I actually think nobody bothers to watch the
• 42:30
  Speaker 1: warm weather spots um. And a couple of reasons. They're one,
• 42:35
  Speaker 1: they're they're not necessarily where deer spend a lot of
• 42:38
  Speaker 1: the time in the fall. You know, in the fall
• 42:40
  Speaker 1: it's usually cooler. The cold days out number the warm
• 42:43
  Speaker 1: days on average. UM. And also the cool spots are
• 42:48
  Speaker 1: usually heavier cover, lower down by water. UM. And people
• 42:54
  Speaker 1: you know, you can't see cold front deer out in
• 42:57
  Speaker 1: a field feeding and you can see him from half
• 42:59
  Speaker 1: a mile away. Um. When it's hot weather, they're seeking shade,
• 43:02
  Speaker 1: they're seeking uh, you know, cool north slopes in hill country,
• 43:07
  Speaker 1: which is a lot of what I hunt. And you
• 43:08
  Speaker 1: can't see very far in a lot of these areas.
• 43:11
  Speaker 1: So people think, oh, they're not moving. Well, I've I've
• 43:14
  Speaker 1: got deer up and walking around and it's eighty five
• 43:16
  Speaker 1: degrees you know, with humidity. I'm getting them on camera.
• 43:21
  Speaker 1: They're you know, they're probably not running around and running heavily,
• 43:24
  Speaker 1: but um, they do move UM, but it's usually like UM.
• 43:29
  Speaker 1: So that really has improved my less than if I'm
• 43:34
  Speaker 1: hunting and it's less than optimal weather, you know, warm
• 43:36
  Speaker 1: weather or whatever. UM. And I used to think. I
• 43:39
  Speaker 1: still don't like sitting on standard sweating. I'll still call
• 43:41
  Speaker 1: it less than optimal. I just don't like doing it,
• 43:44
  Speaker 1: but UM, I will do it. And I've killed a
• 43:46
  Speaker 1: couple of bucks now here with you know, warmer than
• 43:49
  Speaker 1: average temperatures in spots you're looking, you know, shade, cool,
• 43:54
  Speaker 1: north slopes, water, um, often combinations of all those UM
• 44:00
  Speaker 1: and Uh, I'm getting into the deer. That's where they are,
• 44:04
  Speaker 1: and they're getting out, and they're moving in daylight. They're
• 44:06
  Speaker 1: not maybe moving very far, and they're you know, they're
• 44:08
  Speaker 1: not walking out into fields if it's bright sunshine, especially
• 44:12
  Speaker 1: you know, if they've grown their winter coat. UM. Eighty
• 44:15
  Speaker 1: degrees in September is a lot different than eighty degrees
• 44:18
  Speaker 1: in November. After a deer it's grown it's winter coat.
• 44:20
  Speaker 1: So as you know, it has a huge impact by
• 44:22
  Speaker 1: time of year or two. So temperature, UM. You know,
• 44:25
  Speaker 1: if it's really cold out, I like the extreams because
• 44:28
  Speaker 1: that really concentrates the deer. UM. You know, I can't
• 44:33
  Speaker 1: say I like counting and super hot weather but if
• 44:35
  Speaker 1: it's super hot, the deer really stack up well, UM
• 44:38
  Speaker 1: in some of these spots, if it's super cold out
• 44:42
  Speaker 1: there flipping, you know, they're getting out of the wind,
• 44:45
  Speaker 1: so they're getting on the lee of the leeward slopes.
• 44:48
  Speaker 1: They're getting down further on the leewards the slopes, UM,
• 44:52
  Speaker 1: so they're completely out of the wind instead of up
• 44:54
  Speaker 1: close to the top. They might get a little down lower,
• 44:57
  Speaker 1: but they'll try to. They'll seek shuns, sunshine, they will um,
• 45:03
  Speaker 1: you know, they'll get if it gets really cool, then
• 45:05
  Speaker 1: they'll get up and move a lot more frequently because
• 45:08
  Speaker 1: they have to UM. And of course as it gets colder,
• 45:11
  Speaker 1: they need more calories, so they are hitting, they are
• 45:13
  Speaker 1: putting the feedback on more. There's no denying that. So um,
• 45:18
  Speaker 1: the temperature is definitely number one. UM. Sorry, But to clarify,
• 45:24
  Speaker 1: are you saying absolute temperature or temperature change or are
• 45:28
  Speaker 1: you loving that altogether? So well, yeah, so all the
• 45:32
  Speaker 1: all the above. So both temperature in relation to UM
• 45:38
  Speaker 1: average temperature for that time of year. So say it's
• 45:42
  Speaker 1: October one and it is sixty degrees out and your
• 45:45
  Speaker 1: average temperature is say seventy degrees dear, going to you know,
• 45:51
  Speaker 1: be moving uh somewhat more. They'll probably be hitting the
• 45:55
  Speaker 1: food a little more, but they'll be really seeking the
• 45:59
  Speaker 1: kind of the warmer area is they're they're not going
• 46:01
  Speaker 1: to be in the areas necessarily that um, they would
• 46:05
  Speaker 1: be um if it was uh, you know, say eighty
• 46:09
  Speaker 1: degrees um. And just like in November. Say, and this
• 46:14
  Speaker 1: is kind of one of my the lightbulb team on
• 46:17
  Speaker 1: a couple of years ago. UM. And this was northern
• 46:21
  Speaker 1: Wisconsin hunt. Um. So not not an Iowa hunt, the
• 46:24
  Speaker 1: Big Woods hunt. Um. It was I was up there
• 46:28
  Speaker 1: early early November for at hunt and we're hunting around
• 46:32
  Speaker 1: the edge of the swamp. Um. And I could hear
• 46:36
  Speaker 1: deer chasing out in the swamp. And I didn't see
• 46:38
  Speaker 1: a deer the whole day that first day. And the
• 46:40
  Speaker 1: second day, I was like, well, I'm gonna go um
• 46:42
  Speaker 1: you know. And I was right up to the edge
• 46:44
  Speaker 1: of the swamp. You know, I really thought I was
• 46:46
  Speaker 1: in it. Lots of time there nothing but I could
• 46:49
  Speaker 1: hear crashing out in the swamp. And the next day
• 46:52
  Speaker 1: I got up um and I started to just sneak
• 46:55
  Speaker 1: out into this island. And long story short, I didn't
• 46:58
  Speaker 1: kill a buck, but I had a ton of action.
• 47:02
  Speaker 1: And as soon as I started walking in the swamp,
• 47:05
  Speaker 1: you know, it was one of those days. The temperature
• 47:06
  Speaker 1: was nudge and eighty degrees in early November, and as
• 47:09
  Speaker 1: soon as I went onto the swamp, it just felt
• 47:11
  Speaker 1: a lot cooler. And the rout was going full bore
• 47:13
  Speaker 1: out in that swamp, and there was nothing out um
• 47:17
  Speaker 1: outside of that because it was hotter um. And it
• 47:21
  Speaker 1: wasn't that I was outside the curious. I was in
• 47:23
  Speaker 1: the thick stuff, but I wasn't down into into that water,
• 47:26
  Speaker 1: and those deer were running from island to island down
• 47:29
  Speaker 1: the swamp, you know, because it was warmer and and
• 47:32
  Speaker 1: uh and correspondingly, actually um, I founded that same area um.
• 47:37
  Speaker 1: The year after that, it was actually snow and so
• 47:40
  Speaker 1: it was colder than average. It was spitting snow, miserable weather.
• 47:44
  Speaker 1: I went out and sat um the same spot that
• 47:47
  Speaker 1: I sat a year ago, a year before that, except
• 47:50
  Speaker 1: it was instead of seventy eight degrees, it was thirty
• 47:53
  Speaker 1: eight degrees. And I didn't see a deer out in
• 47:57
  Speaker 1: that swamp all day long. I sat there all day long, um.
• 48:00
  Speaker 1: And then I'd had a camera there and I looked
• 48:02
  Speaker 1: and yeah, there's they were out there that was a
• 48:05
  Speaker 1: hot weather spot. They were out, you know, running around
• 48:09
  Speaker 1: in the islands and you know, and uh from island
• 48:12
  Speaker 1: to island Chason does. When it was um really hot
• 48:16
  Speaker 1: out but as as a temperature plunged, there was significantly
• 48:20
  Speaker 1: less movement out there. And then I think they were
• 48:22
  Speaker 1: out around the perimeter of the swamp more on drier
• 48:25
  Speaker 1: areas because it was cold and they didn't want to
• 48:26
  Speaker 1: walk around in the water. So Um, there's a little
• 48:30
  Speaker 1: stuff like that. So it's both departure from average temperature
• 48:35
  Speaker 1: and then also change of temperature. And that's really location
• 48:39
  Speaker 1: specific like is it heating up or is it cooling down? Um?
• 48:44
  Speaker 1: And uh are they seeking warmth or are they seeking
• 48:47
  Speaker 1: you know cool so um Yeah that m yeah for
• 48:53
  Speaker 1: for um location specific, it's definitely wind direction. Um. Deer
• 49:00
  Speaker 1: use the wind. Um, There's no no doubt about it.
• 49:04
  Speaker 1: Now they aren't always just walking into the wind or
• 49:06
  Speaker 1: walking with the wind. They're back um, although I have
• 49:08
  Speaker 1: seen like up north it seems like dear favor walking
• 49:11
  Speaker 1: with the wind. They're back more often, but it's not
• 49:13
  Speaker 1: a strong trend. But it's every location, um, and it's
• 49:17
  Speaker 1: I think it's because of wind based betting. I'll see
• 49:19
  Speaker 1: a lot more deer with certain wind directions. So um,
• 49:24
  Speaker 1: that's one of my favorite ways to filter spots. You know,
• 49:27
  Speaker 1: it's a it's an easy way. It's like, oh, this spot,
• 49:30
  Speaker 1: two thirds of movement was on southerly winds. So you're
• 49:33
  Speaker 1: hunting with a southerly wind, you have to even if
• 49:35
  Speaker 1: it doesn't seem to work right for you as a hunter,
• 49:38
  Speaker 1: you have to figure out a way to hunt it
• 49:40
  Speaker 1: effectively with that kind of wind because if it's a
• 49:42
  Speaker 1: sutherly wind spot and you're hunting with the north wind,
• 49:44
  Speaker 1: you are wasting your time. So um, that's a big one. Yeah, yeah, yeah.
• 49:51
  Speaker 1: So and I used to I think back of a
• 49:53
  Speaker 1: lot of hunts that I'd had, and I would hunt
• 49:57
  Speaker 1: before I even really understood like the windward leeward slope
• 50:01
  Speaker 1: deer definitely most of the time favor leward slopes. UM.
• 50:05
  Speaker 1: Never say always or never, but um wind slopes absolutely. Um.
• 50:14
  Speaker 1: So a windward slope UM a ridge. Imagine a ridge
• 50:18
  Speaker 1: and the wind is blowing across it, so it's blowing
• 50:21
  Speaker 1: from one side to the other. So the side of
• 50:23
  Speaker 1: that ridge that the wind is hitting is the windward
• 50:26
  Speaker 1: slope and the side away from the wind, so the
• 50:29
  Speaker 1: wind's kind of blowing over the top of your head
• 50:31
  Speaker 1: if you're out, you know, out of the wind on
• 50:34
  Speaker 1: a ridge that's the leeward slope. So, um, there's many
• 50:38
  Speaker 1: different theories. I really haven't made up my mind for
• 50:40
  Speaker 1: exactly why, um the wind, you know, the deer travel
• 50:46
  Speaker 1: on the leeward side. Um. Dan Infault has a good theory.
• 50:49
  Speaker 1: I think there's something too, you know about a thermal tunnel. Um.
• 50:52
  Speaker 1: I think there might be other things, um yeah going
• 50:55
  Speaker 1: on there too, not just that. Um. You know, deer
• 50:58
  Speaker 1: basically can smell the whole will ridge up wind of them,
• 51:02
  Speaker 1: and then you know they also can smell and also
• 51:06
  Speaker 1: see often the down the ridge below them, So they
• 51:10
  Speaker 1: have the eyesight and the and the scent than their
• 51:13
  Speaker 1: nose protecting them. Um. Anyway, so dear favorite leeward slopes,
• 51:18
  Speaker 1: and I would hunt windward slopes and I'd have a
• 51:21
  Speaker 1: rotten lock and there'd be deer sign everywhere, and why
• 51:23
  Speaker 1: I'm not seeing deer there? And then you know, after
• 51:26
  Speaker 1: a little while, and I've learned it from the hunting beast,
• 51:28
  Speaker 1: which is a great thing for pete. I don't hang
• 51:31
  Speaker 1: out there a whole lot anymore, only because I have
• 51:34
  Speaker 1: no time left in my day, in my life, it
• 51:36
  Speaker 1: seems like to spend on there. But um, it's a
• 51:40
  Speaker 1: great resource for hunters to learn more about you know,
• 51:42
  Speaker 1: um hunting and competitive environments, public land and stuff. Um.
• 51:48
  Speaker 1: But you know, the wind direction is huge, and that's
• 51:51
  Speaker 1: really you know, I have I have spots you know
• 51:54
  Speaker 1: for west wind I have spots for north winds and
• 51:57
  Speaker 1: southwest winds. Um. That's how I filter my setups, um,
• 52:02
  Speaker 1: based on where the deer are. Would you agree that
• 52:06
  Speaker 1: if we're looking at patterning deer, not by specific bucks,
• 52:10
  Speaker 1: but for patterning areas locations, is it my assumption would
• 52:15
  Speaker 1: be that wind direction and time of year are probably
• 52:19
  Speaker 1: the most impactful variables that would tell you when a
• 52:23
  Speaker 1: given spot would be good versus when it's not. Is
• 52:25
  Speaker 1: that right with you? For if I'm looking locations, so
• 52:28
  Speaker 1: those are the two biggest maybe yeah, and well and
• 52:31
  Speaker 1: temperature and temperature, like I I have really learned, like, um,
• 52:36
  Speaker 1: there's cold weather spots and there's hot weather spots. So
• 52:40
  Speaker 1: that's the that's the big three. And so you're saying
• 52:42
  Speaker 1: it's not just that deer will move more in general first,
• 52:46
  Speaker 1: just like they'd be moving. I guess my assumption is
• 52:48
  Speaker 1: going to be that you're gonna say temperature would just
• 52:51
  Speaker 1: change dear movement everywhere, but then wind direction in time
• 52:54
  Speaker 1: of year would say, okay, well this little betting air
• 52:57
  Speaker 1: picks up with those conditions. But you're saying, actually, there's
• 52:59
  Speaker 1: going to be specific locations that are when it's cold
• 53:03
  Speaker 1: deer for the spot, I guess, kind of like the
• 53:04
  Speaker 1: swamp example. Yep, yep, yep. And I've got other examples.
• 53:08
  Speaker 1: I've got, Um, I've got I've got a really killer
• 53:12
  Speaker 1: bed location picked out on public land here in Iowa,
• 53:15
  Speaker 1: and I have not killed a buck there yet. I'm
• 53:17
  Speaker 1: just waiting, um for the right buck to be in
• 53:20
  Speaker 1: the area. Um. I've hunted it a couple of times.
• 53:23
  Speaker 1: But it's a hot weather bed and buck consistently bed
• 53:27
  Speaker 1: there when it's over seventy degrees in October and November. Um,
• 53:31
  Speaker 1: and uh, it's it's you. You can't find it if
• 53:35
  Speaker 1: if it's colder than average. I've had a camera there
• 53:38
  Speaker 1: now watching this area for three years in a row
• 53:42
  Speaker 1: all fall. Um. I drop it out there late summer
• 53:45
  Speaker 1: and I picked it up in the winter and in
• 53:47
  Speaker 1: the cold weather, there's rarely a deer in that area.
• 53:51
  Speaker 1: Hot weather, it's I mean it's a strong percentage. Yeah. Um,
• 53:59
  Speaker 1: it's right above a big spring, so there's a big
• 54:02
  Speaker 1: spring coming out of the hillside and it's um about
• 54:05
  Speaker 1: halfway down a north slope, so it's in dense shade,
• 54:08
  Speaker 1: and it's right above water, so they can get a drink.
• 54:10
  Speaker 1: And it's also cooler like that cool water. You go
• 54:13
  Speaker 1: there and you just notice it's five to ten degrees
• 54:17
  Speaker 1: cooler than if you were at the top of the hill. Um.
• 54:20
  Speaker 1: It's harder than heck to hunt because it's you know,
• 54:23
  Speaker 1: kind of in a hole. But I think I think
• 54:26
  Speaker 1: I can hunt one side of it with a south wind,
• 54:28
  Speaker 1: which of course they favor. With a south wind not
• 54:31
  Speaker 1: so much, I think, because the wind kind of swirls.
• 54:34
  Speaker 1: I think it's mostly the south wind is hot, you know,
• 54:37
  Speaker 1: associated with hot weather. So um. You know. So it's
• 54:41
  Speaker 1: that's the big three. It's time of year, temperature, wind direction,
• 54:46
  Speaker 1: so um to me and everything else Like I used
• 54:50
  Speaker 1: to think, you know, it's pressure, but pressure pressure doesn't
• 54:53
  Speaker 1: dictate where a deer is. It might dictate how much
• 54:56
  Speaker 1: they're interested in food. UM, so they might get up
• 55:00
  Speaker 1: little earlier, UM if it's a good high pressure system.
• 55:03
  Speaker 1: But it's not a big UM. It's not quite the
• 55:08
  Speaker 1: driver that I thought it was. And people should keep
• 55:11
  Speaker 1: in mind, you know, pressure and temperature UM and wind
• 55:15
  Speaker 1: or and wind speed actually all they all go hand
• 55:17
  Speaker 1: in hand. That they get too complicated. But you know,
• 55:19
  Speaker 1: when you have screaming hard winds, your temper, your brometer
• 55:22
  Speaker 1: is probably moving because that's you know, wind is air
• 55:25
  Speaker 1: molecules going from one spot to another. And the reason
• 55:28
  Speaker 1: they're doing that is probably because between a low pressure
• 55:30
  Speaker 1: system and a high pressure system, you know, so so
• 55:33
  Speaker 1: that they're correlated. You know. UM. Wind speeds another one UM,
• 55:37
  Speaker 1: not just wind direction, the wind speed UM. The harder
• 55:42
  Speaker 1: the wind, the lower the deer getting the hills. In
• 55:45
  Speaker 1: my experience, UM, especially with cold winds, but in general
• 55:50
  Speaker 1: all winds, I see them drop down at elevation UM.
• 55:53
  Speaker 1: And if it's you know, it's a really screaming cold wind,
• 55:56
  Speaker 1: they may be down in those valleys. UM temper early
• 56:00
  Speaker 1: to seek shelter. So I've I've got a spot or
• 56:03
  Speaker 1: two that if I know, I'm a big cold front
• 56:06
  Speaker 1: during the rut with at least twenty mile in our
• 56:09
  Speaker 1: wind gus, I'm getting down there and the rutted on
• 56:12
  Speaker 1: down down in the valleys, and I could be up
• 56:14
  Speaker 1: on the ridge and freezing my butt off and I
• 56:16
  Speaker 1: wouldn't see a thing. So um, stuff like that. So,
• 56:21
  Speaker 1: if I'm trying to implement a tracking system kind of
• 56:27
  Speaker 1: like you have here, um, and I'm starting to think
• 56:30
  Speaker 1: about patterning locations in this kind of way, what are
• 56:34
  Speaker 1: some key things to make sure I'm doing or I
• 56:37
  Speaker 1: mean there's the basics, track a bunch of data, put
• 56:40
  Speaker 1: it in here. Is there anything or any mistakes you
• 56:43
  Speaker 1: hear people commonly make when they talk about how they're
• 56:45
  Speaker 1: trying to track dear movement activity or any anything you
• 56:48
  Speaker 1: haven't mentioned to just kind of tie up the tracking
• 56:51
  Speaker 1: part of this. Yeah, I guess that, in my opinion,
• 56:57
  Speaker 1: the most common mistake is trying to just follow around
• 56:59
  Speaker 1: it into visual deer. Like if you it's okay to
• 57:02
  Speaker 1: try to go after an individual deer, but you need
• 57:05
  Speaker 1: to fill the approach of that instead of trying to, um,
• 57:10
  Speaker 1: you know, uh, just draw a line on a map
• 57:13
  Speaker 1: for where he's where he's going. And I know there's
• 57:16
  Speaker 1: some tools that have been marketed for that it's really
• 57:19
  Speaker 1: you need to look at like where is he frequenting?
• 57:21
  Speaker 1: And then look at those spots and why are he frequenting? UM?
• 57:25
  Speaker 1: You know, in what conditions is he frequenting them? UM?
• 57:28
  Speaker 1: Instead of UM looking at it from the you know,
• 57:31
  Speaker 1: I guess trying to just project out a line on
• 57:33
  Speaker 1: a map or where the deer is going to go. UM,
• 57:36
  Speaker 1: you look at like, well, a majority of the time
• 57:39
  Speaker 1: he's over you know, on this ridge system. UM. When
• 57:44
  Speaker 1: you know, when it's you know, late October and it's
• 57:46
  Speaker 1: cold weather, and then when it was warm weather, I
• 57:49
  Speaker 1: would get him over here, you know, more down in
• 57:52
  Speaker 1: this bottom you know that's UM. I find a lot
• 57:54
  Speaker 1: more UM value in so UM. If you try to
• 58:00
  Speaker 1: target started to interrupt your strength thought there, If you
• 58:04
  Speaker 1: were trying to target a specific buck, would you change
• 58:07
  Speaker 1: anything that you're doing here from a tracking system? Would
• 58:10
  Speaker 1: you add any variables? Would you ignore any of them? Uh?
• 58:14
  Speaker 1: Anything you did? Just That's that's where UM and I
• 58:17
  Speaker 1: and I do. You know. I I try to keep
• 58:20
  Speaker 1: tabs on on individual boks. I rarely go after one
• 58:24
  Speaker 1: all by itself, you know, but it's usually like, oh,
• 58:27
  Speaker 1: there's a couple of bucks in this area, that I
• 58:29
  Speaker 1: want to go after. UM, I think the you may
• 58:35
  Speaker 1: want to bring in um more data sources, so that's
• 58:39
  Speaker 1: where it comes into. Okay, well, maybe you want to
• 58:41
  Speaker 1: move a few more cameras into the area. UM. The
• 58:44
  Speaker 1: challenge with this, you know, I am playing the long game,
• 58:47
  Speaker 1: and I know in the majority of the country, hunters
• 58:51
  Speaker 1: don't especially in public land, hunters don't have the benefit
• 58:55
  Speaker 1: of being able to follow a deer when he's three
• 58:57
  Speaker 1: and four and five years old. And I mean most
• 59:01
  Speaker 1: three year old bucks get killed in Iowa two I'm
• 59:03
  Speaker 1: publicly and okay it's not you know, some get through,
• 59:06
  Speaker 1: but most of them will die. Um and uh so
• 59:11
  Speaker 1: uh if what I'm doing is playing a long game
• 59:13
  Speaker 1: for next year, you know, I'm really not looking at
• 59:16
  Speaker 1: this year's all my cameras. Um, It's I have a
• 59:20
  Speaker 1: few cameras that I have in more easy to access
• 59:24
  Speaker 1: and maybe a couple that I check more frequently, but
• 59:28
  Speaker 1: the vast majority I hunt hang and I literally I
• 59:32
  Speaker 1: will not check them until the season's over at least
• 59:35
  Speaker 1: I'm done hunting and I'm I'm picking stuff up. So, UM,
• 59:40
  Speaker 1: if you're looking after an individual buck, you know, if
• 59:44
  Speaker 1: you you know you watch closely those good up and
• 59:47
  Speaker 1: coming three year olds. A lot of times those patterns
• 59:50
  Speaker 1: change a little bit, but there's still somewhat similar. Um.
• 59:53
  Speaker 1: They definitely get more nocturnal and more secretive when they
• 59:55
  Speaker 1: hit four UM, but their areas of and are the same.
• 1:00:00
  Speaker 1: Sometimes they do even shift home ranges UM. But gather
• 1:00:05
  Speaker 1: as much dead as you can. UM. You know, the
• 1:00:07
  Speaker 1: more options you have after a bucket, the better. You
• 1:00:10
  Speaker 1: don't want to just pin your hopes on just one
• 1:00:12
  Speaker 1: location you're probably going to fail. UM. But especially like
• 1:00:17
  Speaker 1: once again, I'm targeting betting, UM, you know I'm going
• 1:00:20
  Speaker 1: to hunt that spot once. UM. Occasionally I might hunt
• 1:00:24
  Speaker 1: a spot twice, but it's really rare. That's ninety percent
• 1:00:29
  Speaker 1: of my public land skills have been first time since
• 1:00:34
  Speaker 1: for that location for that year. UM. And that trend
• 1:00:37
  Speaker 1: to expect to continue. So and I used to hunt
• 1:00:41
  Speaker 1: spots many more times, and I just wouldn't have this success. UM.
• 1:00:44
  Speaker 1: So now I've just basically almost quit hunting spots more
• 1:00:48
  Speaker 1: than once UM, unless it's kind of special circumstances. And
• 1:00:53
  Speaker 1: I really think I got in and out clean um.
• 1:00:55
  Speaker 1: And the cleaner your entry and act the exit by
• 1:00:58
  Speaker 1: all means, you know, there are some you can hunt repeatedly,
• 1:01:01
  Speaker 1: but it's a very rare spot, I think, um, dear
• 1:01:06
  Speaker 1: will Semellia, I was gonna ask going back a little bit, um,
• 1:01:11
  Speaker 1: pivoting away from individual bucks back to locations. Um. You
• 1:01:16
  Speaker 1: mentioned you're typically targeting betting areas, but are there any
• 1:01:19
  Speaker 1: other types of places you try to pattern? Like? Do
• 1:01:21
  Speaker 1: you also set you know, fall like five months long
• 1:01:25
  Speaker 1: trail camera sets over typical funnels or anything like that
• 1:01:30
  Speaker 1: that you want to see what's happening year after year
• 1:01:32
  Speaker 1: and you can get an annual pattern off anything other
• 1:01:35
  Speaker 1: than betting areas. Yeah, Um, yeah, that's it's usually a
• 1:01:38
  Speaker 1: shorter window because bucks it's all about betting outside of
• 1:01:44
  Speaker 1: the rut, and even during the rut it's still all
• 1:01:46
  Speaker 1: about betting, but sometimes it's not just about their betting,
• 1:01:49
  Speaker 1: it's about their dough betting. So um. Usually the travel
• 1:01:52
  Speaker 1: routes that I'm targeting still connect to betting areas, they
• 1:01:55
  Speaker 1: doe betting areas and such. But I do put cameras
• 1:01:59
  Speaker 1: um like um on good really good funnels. Um. Not
• 1:02:05
  Speaker 1: usually the super obvious funnels, mostly because in public land
• 1:02:08
  Speaker 1: other people are always hunting them. Um. The classic inside
• 1:02:12
  Speaker 1: corners and stuff. I just I just don't see fully
• 1:02:17
  Speaker 1: mature bucks using them regularly on public land. Yeah, they
• 1:02:21
  Speaker 1: may occasionally, and you can occasionally kill one, but I
• 1:02:23
  Speaker 1: have a lot of higher odds getting into the more um,
• 1:02:27
  Speaker 1: the harder to c funnels. Like you've got a really
• 1:02:29
  Speaker 1: long ridge system, and on the leeward side there's this
• 1:02:32
  Speaker 1: great big ditch and basically all the deer bottlenecked into
• 1:02:35
  Speaker 1: a ditch crossing, you know, a third of the way
• 1:02:39
  Speaker 1: down from the top, or maybe there's a fence line,
• 1:02:41
  Speaker 1: you know, and a tree fell across the fence line,
• 1:02:44
  Speaker 1: and so that's that crossing on the leeward side. UM.
• 1:02:48
  Speaker 1: So I'm looking for things like that, and I'll put
• 1:02:49
  Speaker 1: a camera and say, you know, maybe there's betting up
• 1:02:52
  Speaker 1: the ridge and bending down the ridge, so I know,
• 1:02:53
  Speaker 1: deer coming back back and forth through and I'll monitor that.
• 1:02:57
  Speaker 1: So it's not always you know too, it's got to
• 1:03:01
  Speaker 1: do with betting, but it's it's sometimes it's uh bucks
• 1:03:05
  Speaker 1: behavior chasing dose um and seeking dose after you know,
• 1:03:10
  Speaker 1: around the betting areas. So yeah, I do, UM, I
• 1:03:14
  Speaker 1: do that as well, UM and I do. I don't
• 1:03:17
  Speaker 1: have much luck trying to determine trends for deer coming
• 1:03:22
  Speaker 1: out and food sources. Um. So you know, I have occasionally,
• 1:03:25
  Speaker 1: occasionally do have cameras watching food sources, but I don't
• 1:03:29
  Speaker 1: usually you I don't usually look at that data that close. Um,
• 1:03:33
  Speaker 1: just because deer have to eat, so they come out
• 1:03:37
  Speaker 1: and eat. Um. And they may they may be more
• 1:03:40
  Speaker 1: likely to come out during the day if it's optimal conditions,
• 1:03:44
  Speaker 1: then they're betting closer by. But um, I have a
• 1:03:47
  Speaker 1: lot better luck looking at betting trends than if they're
• 1:03:51
  Speaker 1: coming out and eating a food source. You know, usually
• 1:03:53
  Speaker 1: they're they're going to come out and eat every night.
• 1:03:55
  Speaker 1: Maybe maybe you can find a trend er. Oh you
• 1:03:58
  Speaker 1: came out in daylight and it was a big cold,
• 1:04:00
  Speaker 1: that kind of thing. But um. And also, um, you
• 1:04:04
  Speaker 1: actually end up with kind of too much data when
• 1:04:07
  Speaker 1: you're looking at food sources because if they're on camera
• 1:04:09
  Speaker 1: every single day, Okay, they're on camera every single day,
• 1:04:12
  Speaker 1: what are you gonna do about it? Kind of thing? Um.
• 1:04:15
  Speaker 1: Whereas betting, Oh, you know, he was using this betting
• 1:04:18
  Speaker 1: area for four days out of a seven day window,
• 1:04:21
  Speaker 1: and then he wasn't there for two weeks and then
• 1:04:23
  Speaker 1: he was back. Um. That tells me a lot more
• 1:04:28
  Speaker 1: so I interrupted you when you were talking. There's some
• 1:04:30
  Speaker 1: steaks people made. Did you finish up what you wanted
• 1:04:32
  Speaker 1: to cover? As far as where do you if you
• 1:04:37
  Speaker 1: did hut by the moon? Hunting by the moon, I'll
• 1:04:42
  Speaker 1: come out and say it. A lot of people I
• 1:04:43
  Speaker 1: know on the beast are probably mad about that. But
• 1:04:45
  Speaker 1: I don't know. I just I I A lot of
• 1:04:50
  Speaker 1: people have had success doing it, but man, I just um,
• 1:04:53
  Speaker 1: after looking at a couple of thousand data points, I
• 1:04:56
  Speaker 1: just have not found any correlation between where the moon
• 1:05:00
  Speaker 1: is and when they're moving. Um. It's and I'm not
• 1:05:05
  Speaker 1: to say maybe it does exist, but the weather is
• 1:05:08
  Speaker 1: in order of magnitude more important. UM, if he's going
• 1:05:11
  Speaker 1: to get up that and and things like hunting pressure,
• 1:05:13
  Speaker 1: you know, and that important. I've I've talked about all
• 1:05:16
  Speaker 1: this stuff. This like hunting pressure. If you're looking at
• 1:05:20
  Speaker 1: big three, UM like that probably comes first. Honestly, with
• 1:05:24
  Speaker 1: a mature box. Once he's reached that age, he will
• 1:05:27
  Speaker 1: not move if he doesn't feel UM safe. So UM.
• 1:05:33
  Speaker 1: For example, in Iowa, UM we have an early muzzleloader
• 1:05:37
  Speaker 1: season which runs third week of October. Some just as
• 1:05:40
  Speaker 1: the ruts starting the heat up or second week October.
• 1:05:43
  Speaker 1: I guess usually something like that, Um, depends on how
• 1:05:46
  Speaker 1: the calendar lays out. UM. And I've learned, you know,
• 1:05:50
  Speaker 1: there's certain areas that muzzleloader hunter hunters will frequent and
• 1:05:55
  Speaker 1: I won't get anything on my cameras in that time
• 1:05:58
  Speaker 1: period and for a little while after towards and then dear,
• 1:06:00
  Speaker 1: I'll start showing back up um and others that Actually
• 1:06:05
  Speaker 1: I see pressure betting even here. Uh you know, I
• 1:06:07
  Speaker 1: over right now we don't have quite the pressure that say,
• 1:06:10
  Speaker 1: uh you deal with in Michigan, certainly not in public
• 1:06:13
  Speaker 1: land there, UM, but I see pressure betting meeting um.
• 1:06:18
  Speaker 1: When there's a bunch of people in the woods, certain areas,
• 1:06:21
  Speaker 1: deer really frequent because humans just do not get in there.
• 1:06:25
  Speaker 1: It's just too nasty or you have to cross water
• 1:06:27
  Speaker 1: something like that. They really um you know, and when
• 1:06:31
  Speaker 1: pete humans aren't in the woods, you may not see
• 1:06:33
  Speaker 1: as many deer or mature buck sightings in those areas.
• 1:06:38
  Speaker 1: So UM, it's been eye opening to me. I have
• 1:06:40
  Speaker 1: a couple of spots that I like to hunt during
• 1:06:42
  Speaker 1: that early muscle or season because human, no other human
• 1:06:46
  Speaker 1: other than me gets anywhere near there, and uh I
• 1:06:50
  Speaker 1: have um uh, you know, and or maybe they do
• 1:06:54
  Speaker 1: get someone near there, but they still can't see it.
• 1:06:56
  Speaker 1: They're not hunting it, and dear no, they can move
• 1:06:59
  Speaker 1: just that extra two hundred yards or hundred yards and
• 1:07:02
  Speaker 1: be completely secure after the humans stick up the woods
• 1:07:05
  Speaker 1: for a few days. An interesting thing is I'm hearing
• 1:07:09
  Speaker 1: you talk about all this is I follow a lot
• 1:07:14
  Speaker 1: of this data. Similarly, I pay attention to a lot
• 1:07:17
  Speaker 1: of these things, and I really think there's something to it.
• 1:07:20
  Speaker 1: But we're kind of using it in slightly different ways.
• 1:07:23
  Speaker 1: It seems like, correct me if I'm wrong here. I'm
• 1:07:25
  Speaker 1: curious to hear if you think about it in the
• 1:07:26
  Speaker 1: same way I do. Sometimes. Um, So, it sounds like
• 1:07:29
  Speaker 1: most of the time you're looking at this data to
• 1:07:31
  Speaker 1: help you know where to hunt, like when to hunt
• 1:07:34
  Speaker 1: which spot, and you're finding that a certain wind direction
• 1:07:39
  Speaker 1: or a certain temperature will lead to the deer movement
• 1:07:42
  Speaker 1: or the deer being better than a certain location coming
• 1:07:44
  Speaker 1: to a certain location. I've always thought more so of
• 1:07:47
  Speaker 1: looking at this kind of data to tell me when
• 1:07:51
  Speaker 1: the chances of the very best or when's the very
• 1:07:53
  Speaker 1: best chance that I'm mature buck will get up moved
• 1:07:55
  Speaker 1: during daylight, and then when I get those special days,
• 1:07:59
  Speaker 1: then I target like my sweet spots, like the spots
• 1:08:01
  Speaker 1: where I think are like the highest odds for other
• 1:08:04
  Speaker 1: reasons though. Um yeah, so I'm probably missing the boat
• 1:08:08
  Speaker 1: a little bit. Maybe, but maybe is what I do
• 1:08:11
  Speaker 1: in your box of tricks too? Is that how you're
• 1:08:14
  Speaker 1: thinking about as well? Yeah, um, there are, yeah, there
• 1:08:20
  Speaker 1: are those optimal days, but I've I've kind of learned, um,
• 1:08:25
  Speaker 1: there's optimal. Yeah. We definitely are looking at it a
• 1:08:28
  Speaker 1: little differently, you know, because I I see optimal days
• 1:08:31
  Speaker 1: for optimal spots, you know, and maybe you're just stopping
• 1:08:33
  Speaker 1: at the optimal days period and then you're going to
• 1:08:35
  Speaker 1: go try to find a spot. Um. So everything ties
• 1:08:38
  Speaker 1: back to like location for me. Um and uh yeah,
• 1:08:44
  Speaker 1: so that I guess I try to complete that loop
• 1:08:47
  Speaker 1: um so um. And I maybe my thinking has uh
• 1:08:53
  Speaker 1: you know, just kind of can evolved a little bit
• 1:08:55
  Speaker 1: from that because I did used to be like, oh man,
• 1:08:58
  Speaker 1: there's a cold front hit next week, you know, get
• 1:09:01
  Speaker 1: in the woods. You know, this is the time to
• 1:09:03
  Speaker 1: hunt my best stand. Um you know, quote unquote best. Well,
• 1:09:08
  Speaker 1: now I'm like, what is my best stand? I have
• 1:09:10
  Speaker 1: a best stand. Every every single day that I want
• 1:09:12
  Speaker 1: to hunt, I have a best stand. I like that.
• 1:09:14
  Speaker 1: So yeah, so that's uh and I think that really
• 1:09:18
  Speaker 1: did help help me, um, start to think like that.
• 1:09:23
  Speaker 1: And I guess it does depend on how many options
• 1:09:26
  Speaker 1: you have, right, So someone who has ten dad acres
• 1:09:29
  Speaker 1: a public land can probably have a whole bunch of
• 1:09:31
  Speaker 1: different options. Instead for whatever reason, you just hunt fifteen
• 1:09:34
  Speaker 1: acres you own or something, all of a sudden you're limited. Yeah,
• 1:09:40
  Speaker 1: and that and that, um, you know, like just to
• 1:09:43
  Speaker 1: be like clear, I um, it's there's a lot of
• 1:09:47
  Speaker 1: blanket statements made and I have a certain strategy and
• 1:09:50
  Speaker 1: it's not for everybody, and I I do like and
• 1:09:54
  Speaker 1: Iowa doesn't have much public land period. That's part of
• 1:09:57
  Speaker 1: the reason I love to go up into Wisconsin because
• 1:10:00
  Speaker 1: then I can I can really walk all day and
• 1:10:02
  Speaker 1: still be on public land. In Iowa, that ain't happening.
• 1:10:04
  Speaker 1: You know, thousand acre parcels humongous. You know, most of
• 1:10:07
  Speaker 1: time it's too undern acre parcel um, so you're really limited.
• 1:10:11
  Speaker 1: And even I know, you know, um, Michigan is even
• 1:10:14
  Speaker 1: more partialized from listening to you know, a sixty acre
• 1:10:16
  Speaker 1: parcel is a big parcel there southern problems, and then
• 1:10:20
  Speaker 1: you go out east and you have a ten acreup parcel.
• 1:10:24
  Speaker 1: That's a big parcel, you know. So it's crazy how
• 1:10:28
  Speaker 1: different that that requires your strategy to be different. You
• 1:10:32
  Speaker 1: know you maybe you don't have a thousand acres or
• 1:10:35
  Speaker 1: ten thousand acres um, maybe you have one, you know,
• 1:10:39
  Speaker 1: twenty acre parcel. I encourage you to get more options.
• 1:10:42
  Speaker 1: More is better, but um, you may be limited. You know,
• 1:10:46
  Speaker 1: you may be limited to where you can hunt. You
• 1:10:48
  Speaker 1: can just go and hunt, and you have to find
• 1:10:49
  Speaker 1: a different strategy to fit that. This, Like I've I've
• 1:10:52
  Speaker 1: kind of developed this to fit my strategy of I
• 1:10:55
  Speaker 1: have ten times as many spots as I can hunt
• 1:10:58
  Speaker 1: as I have time to hunt any fall. So, um,
• 1:11:02
  Speaker 1: how do I figure out what are the best? You know,
• 1:11:05
  Speaker 1: I've scouted my butt off for years to find a
• 1:11:08
  Speaker 1: bunch of really good spots and I don't have time
• 1:11:10
  Speaker 1: to hunt them. So okay, well I have to filter
• 1:11:13
  Speaker 1: out and try to figure out what you know and
• 1:11:16
  Speaker 1: I and I know I'm a little bit I'm wired,
• 1:11:19
  Speaker 1: wired a little bit different because um, I'm I'm just
• 1:11:23
  Speaker 1: fanatical about efficiency, you know, Like I'm not a good
• 1:11:27
  Speaker 1: spot is not good enough for me. I want the
• 1:11:29
  Speaker 1: best spot. I want to find the best spot because
• 1:11:32
  Speaker 1: you know it's gonna be better than the good spot.
• 1:11:34
  Speaker 1: So um, and I'm always thinking like that. Over the
• 1:11:38
  Speaker 1: course of you know, twenty years upon public Land, I've
• 1:11:42
  Speaker 1: I've you know, started to I don't think I've just
• 1:11:45
  Speaker 1: changed my thinking. Now. What I'm curious about is if
• 1:11:51
  Speaker 1: you could now tie a big, nice bowl on this
• 1:11:54
  Speaker 1: for me by walking me through an example or two
• 1:11:58
  Speaker 1: about how you something from your data set that you've
• 1:12:03
  Speaker 1: tracked over a year or two or however many years,
• 1:12:05
  Speaker 1: and then implemented that into a hunt, um, and how
• 1:12:08
  Speaker 1: you picked the optimal spot for the optimal time, and
• 1:12:13
  Speaker 1: and what that all looks like. I'd love to better
• 1:12:15
  Speaker 1: understand your whole thought process as you go through that
• 1:12:18
  Speaker 1: and then execute the hunt. Yeah. Um, so let's see.
• 1:12:24
  Speaker 1: It's it's ingrained. It's been ingrained into most of my Uh. Well,
• 1:12:30
  Speaker 1: first of all, um, i haven't hunted a whole lot
• 1:12:33
  Speaker 1: the last two years. I've killed a couple of bucks. Um.
• 1:12:36
  Speaker 1: But um, you know, I've been going I'm working full
• 1:12:39
  Speaker 1: time and going back to school and two little kids,
• 1:12:42
  Speaker 1: and you know, last year I hunted seven times total,
• 1:12:45
  Speaker 1: and it wore me out. It was pretty pathetic. UM.
• 1:12:48
  Speaker 1: But the good news is my school is getting done.
• 1:12:50
  Speaker 1: I'll be done with that and I'll be able to
• 1:12:51
  Speaker 1: hit the woods a little harder here this fall. So
• 1:12:54
  Speaker 1: I'm happy that it's happy to announce that. But UM anyway, UM,
• 1:12:59
  Speaker 1: like even last year, I killed a buck UM and
• 1:13:04
  Speaker 1: it was it was October. It was right on that
• 1:13:07
  Speaker 1: full moon. UM, so I was expecting UM, I was
• 1:13:13
  Speaker 1: expecting more pre rod activity because of the full moon. UM.
• 1:13:18
  Speaker 1: There there's a spot that is it's a trial corridor UM,
• 1:13:24
  Speaker 1: and it's used to a high frequency for southerly south
• 1:13:27
  Speaker 1: and southeast winds for betting. So it's kind of a
• 1:13:29
  Speaker 1: warmer weather betting. And it happened to be UM at
• 1:13:33
  Speaker 1: that day. I think it was south south or southeast
• 1:13:38
  Speaker 1: wind UM. And uh I knew that from turro camera
• 1:13:43
  Speaker 1: sitting there for the lab for from the fall previous UM.
• 1:13:47
  Speaker 1: And so bucks preferred to bed there when it was
• 1:13:51
  Speaker 1: a little warmer than average. UM. And uh they did.
• 1:13:56
  Speaker 1: They usually betted there when uh, you know the pre
• 1:13:59
  Speaker 1: pre I was hunting heating up. So in the October
• 1:14:03
  Speaker 1: twentie thirty, the pre rod usually heating up. But it's
• 1:14:06
  Speaker 1: not linear, you know, as everybody knows who's hunted that
• 1:14:09
  Speaker 1: time period. It's really um on off hot cold. You're
• 1:14:12
  Speaker 1: either seeing nothing or you're seeing some really good action.
• 1:14:15
  Speaker 1: There doesn't seem to be much in the middle. UM.
• 1:14:18
  Speaker 1: I love the pre rod. That's my favorite time to hunt.
• 1:14:21
  Speaker 1: Um that the last half of October really um so UM.
• 1:14:27
  Speaker 1: And I knew that buck was in the area. UM
• 1:14:29
  Speaker 1: and you know, I still remember he you know, he
• 1:14:34
  Speaker 1: came in and I wish i'd gotten a camera, and I,
• 1:14:38
  Speaker 1: in general, I don't have any interest in recording and
• 1:14:40
  Speaker 1: videoing my hunts. But I shot him and he ran
• 1:14:44
  Speaker 1: and he tipped over right in front of the rising
• 1:14:45
  Speaker 1: full moon, you know. So it was coming up over
• 1:14:47
  Speaker 1: the horizon just a few minutes before um the uh
• 1:14:53
  Speaker 1: the closing time, you know. UM. So that's one example. UM,
• 1:15:00
  Speaker 1: I've a few years let's see, UM a few years
• 1:15:07
  Speaker 1: before that. I like, that's that's a good example because
• 1:15:10
  Speaker 1: it was a it was a good um a number
• 1:15:15
  Speaker 1: of years ago. UM. I used to think that deer
• 1:15:19
  Speaker 1: didn't like to move in the um when the moon
• 1:15:23
  Speaker 1: was full. And I also didn't like to think all right,
• 1:15:26
  Speaker 1: I didn't think that dear really um um moved as
• 1:15:32
  Speaker 1: much when it was warm out until I figured out, hey,
• 1:15:34
  Speaker 1: they're really moving differently. Maybe they're moving slightly less, but
• 1:15:38
  Speaker 1: like they're moving differently, and you can get on deer
• 1:15:40
  Speaker 1: when it's warm out. So um, it was definitely eye opening.
• 1:15:46
  Speaker 1: You know, it's like, hey, I can have success. It
• 1:15:48
  Speaker 1: was you know, seventy degrees as a daytime high in
• 1:15:52
  Speaker 1: late October, which is a little warmer than average for
• 1:15:54
  Speaker 1: this part of the country. And um, you know, there
• 1:15:57
  Speaker 1: was a big four year old, you know, twenty two
• 1:16:01
  Speaker 1: inch wide nine pointer you know, up um and he
• 1:16:05
  Speaker 1: was up well before dark um and then came wandering in.
• 1:16:08
  Speaker 1: So um. It's it's really ingrained. And just about every
• 1:16:13
  Speaker 1: single you know, one of my hunts has has that background. Um.
• 1:16:18
  Speaker 1: Let's see that. I can't remember what I killed the
• 1:16:22
  Speaker 1: year before I shot something, but it was another story
• 1:16:26
  Speaker 1: like that. They all kind of lending together. Yeah, yeah,
• 1:16:32
  Speaker 1: that um. That example I shared a couple of years
• 1:16:34
  Speaker 1: ago up in Wisconsin where you know, all of a sudden,
• 1:16:37
  Speaker 1: the rut was on full boar. It was hot out
• 1:16:39
  Speaker 1: and there was on full boar in the islands out
• 1:16:41
  Speaker 1: in the swamp, whereas there was no activity out around
• 1:16:45
  Speaker 1: the perimeter the swamp, you know. And it wasn't that
• 1:16:48
  Speaker 1: there was hunting pressure right there. It was just they
• 1:16:51
  Speaker 1: were out where it was cold cool. Um. And that's
• 1:16:54
  Speaker 1: been really eye opening. So UM, two or three years ago,
• 1:16:58
  Speaker 1: I shot a two years that was another really good example. UM.
• 1:17:02
  Speaker 1: I showed this is a late season hunt, and it
• 1:17:04
  Speaker 1: was a muzzloader hunt. It wasn't a bow hunt, but
• 1:17:07
  Speaker 1: we had a real cold snap and the temperature was
• 1:17:11
  Speaker 1: about um, how about negative five degrees or something like
• 1:17:16
  Speaker 1: that daytime high. UM. And I knew deer Um, I knew.
• 1:17:23
  Speaker 1: I knew there was a couple of betting areas that
• 1:17:27
  Speaker 1: we're more open. They were facing the south, Um they
• 1:17:30
  Speaker 1: were the bucks still fell secure, they betted in them. UM.
• 1:17:33
  Speaker 1: And I actually, um, you know, saw him from a
• 1:17:36
  Speaker 1: distance and uh shot him there. Uh you know, I
• 1:17:40
  Speaker 1: was on the far side of the valley, watching the
• 1:17:42
  Speaker 1: sunlit side of the valley and there was nothing, no
• 1:17:45
  Speaker 1: activity on my side of the valley because I was
• 1:17:47
  Speaker 1: and it was cold, I was I was freezing um
• 1:17:51
  Speaker 1: in on the shaded side of the valley. The sun
• 1:17:53
  Speaker 1: was kind of behind me, you know. Uh, shining on
• 1:17:56
  Speaker 1: that southerly facing slope and you know there he was,
• 1:18:01
  Speaker 1: um and uh, you know picked him off, and it
• 1:18:04
  Speaker 1: was it was I wouldn't have been there if it
• 1:18:07
  Speaker 1: wasn't for the brew of cold weather we were having.
• 1:18:10
  Speaker 1: And there was a stiff wind, so there's a pretty
• 1:18:11
  Speaker 1: screaming windshell too. So um yeah, it's it's really you know,
• 1:18:17
  Speaker 1: it's all conditional like that. So I feel like this
• 1:18:21
  Speaker 1: is a great I mean, like my big takeaway for
• 1:18:25
  Speaker 1: me personally is you know, it's good to be smart
• 1:18:30
  Speaker 1: with the timing of your hunts and you don't want
• 1:18:32
  Speaker 1: to overhunt things and you want to be targeted. Of course. Um,
• 1:18:36
  Speaker 1: that doesn't mean though that you shouldn't hunt a lot.
• 1:18:39
  Speaker 1: If you have a lot of locations to hunt, you
• 1:18:42
  Speaker 1: can find ways to pattern specific locations to know the
• 1:18:45
  Speaker 1: right spot to hunt, regardless of whether you have the
• 1:18:48
  Speaker 1: stereotypical dynamite weather big cold front and high pressure, or
• 1:18:52
  Speaker 1: maybe you've got hot weather and it's windy. But if
• 1:18:54
  Speaker 1: you happen to have been tracking all these different locations,
• 1:18:59
  Speaker 1: you'll start to see these patterns laid up with certain
• 1:19:02
  Speaker 1: maybe on the hot days are over here on the
• 1:19:04
  Speaker 1: cool great coal friends, are over here and all of
• 1:19:07
  Speaker 1: a sudden, you maybe all of a sudden double your
• 1:19:09
  Speaker 1: opportunities because you're not just paying attention to those spots
• 1:19:12
  Speaker 1: that are great for coal friends that we all key
• 1:19:14
  Speaker 1: in on. Um, yeah, it's not you know, I'm not
• 1:19:19
  Speaker 1: saying don't hunt, you know, like that's another like, oh,
• 1:19:22
  Speaker 1: you know, if you're not in the woods, you don't
• 1:19:24
  Speaker 1: kill it. That's all right, But that's right. But I
• 1:19:26
  Speaker 1: always add to that. You know, if you're not in
• 1:19:28
  Speaker 1: the woods, you can't kill one. But if you hunt
• 1:19:31
  Speaker 1: the wrong spot at the right spot at the wrong time,
• 1:19:34
  Speaker 1: you're not going to kill on either. So um, like
• 1:19:38
  Speaker 1: go hunt, hunt observation sets. That just gives you more data.
• 1:19:41
  Speaker 1: You learn so much more are you know? Now, I
• 1:19:43
  Speaker 1: don't have that much time, so I don't hunt observation sets.
• 1:19:47
  Speaker 1: But that's not because I don't think it's effective. It's
• 1:19:49
  Speaker 1: just I don't have much time. I strongly encourage people
• 1:19:52
  Speaker 1: who go sit in a tree where they can see
• 1:19:53
  Speaker 1: a long ways and you know, just watch what deer
• 1:19:55
  Speaker 1: are doing. That gives you more information on stuff we're
• 1:19:58
  Speaker 1: talking about right now. Um. But the important thing is
• 1:20:01
  Speaker 1: when you figure out preferred conditions for a spot, stay
• 1:20:05
  Speaker 1: the heck out of that spot until you have those
• 1:20:07
  Speaker 1: conditions you know, on somewhere else. So one other follow
• 1:20:13
  Speaker 1: up on this idea of if if I'm going to
• 1:20:15
  Speaker 1: start tracking locations, um, that means we're setting cameras for
• 1:20:20
  Speaker 1: you know, much longer maybe than the average person is
• 1:20:23
  Speaker 1: putting them out there. So if I'm running a camera
• 1:20:25
  Speaker 1: and put out there in August, I'm not gonna go
• 1:20:27
  Speaker 1: pick it up till late January. Maybe. You know, that's
• 1:20:29
  Speaker 1: that's a lot of time to put the camera out
• 1:20:31
  Speaker 1: there for. Is there anything you've done differently for those cameras,
• 1:20:35
  Speaker 1: whether it be how you set them up, or the
• 1:20:37
  Speaker 1: batteries you use, or anything, any little set up tips
• 1:20:40
  Speaker 1: that we should be thinking about if we're gonna start
• 1:20:42
  Speaker 1: putting a bunch out for this purpose. Yeah. Um, so
• 1:20:46
  Speaker 1: with cold weather cold water operate, if you're going to
• 1:20:49
  Speaker 1: leave it there until the cold weather, Um, you kind
• 1:20:52
  Speaker 1: of have to use lithium batteries. I've learned that the
• 1:20:55
  Speaker 1: hard way. Um, you know how the standard batteries just
• 1:21:00
  Speaker 1: they crope pretty fast, and cold weather lithium batteries are
• 1:21:03
  Speaker 1: temperature they aren't affected by temperature. Um, you also need
• 1:21:06
  Speaker 1: a good camera. Um, and that you know there's pros
• 1:21:09
  Speaker 1: and cons. You're leaving there a long time, so you're
• 1:21:11
  Speaker 1: worried about somebody walking off with it. But um, you know,
• 1:21:15
  Speaker 1: I I like, you know, my Bushnell Trophy cam is
• 1:21:19
  Speaker 1: my workhorse. UM. I just have had really good results
• 1:21:22
  Speaker 1: with that. Browning are fairly good. There's a few other
• 1:21:24
  Speaker 1: brands that I think are pretty much garbage that I
• 1:21:27
  Speaker 1: won't mention. UM. And uh, anyway you leave it. UM.
• 1:21:32
  Speaker 1: I like to put them up high. I've lost and
• 1:21:36
  Speaker 1: like two years ago, I think I had my very
• 1:21:38
  Speaker 1: first camera stole on public land. So it's going to happen,
• 1:21:41
  Speaker 1: but it's actually very rare. UM. I put them up high. UM.
• 1:21:45
  Speaker 1: I put a climbing stick and get them up their
• 1:21:47
  Speaker 1: ten foot off the ground. Angled down, you actually cover
• 1:21:50
  Speaker 1: more area. I've learned if you angle it just the
• 1:21:53
  Speaker 1: right amount and get it up that high instead of
• 1:21:55
  Speaker 1: hanging it, you know, three and a half feet off
• 1:21:57
  Speaker 1: the ground like some people do, and you can your
• 1:22:00
  Speaker 1: detection area can get a little bigger. Um. And man,
• 1:22:03
  Speaker 1: it's very you know, I've lost a couple of cameras
• 1:22:06
  Speaker 1: now and that's it. Um to theft UM. I've had
• 1:22:10
  Speaker 1: a few male function. UM. I've this is completely my fault.
• 1:22:15
  Speaker 1: I forgot to turn on UM, and my buddy, who
• 1:22:18
  Speaker 1: was probably gonna listen to this, I forgot to turn
• 1:22:20
  Speaker 1: it on, and I, you know, get up and walk off.
• 1:22:23
  Speaker 1: And then three months later I walk up, you know,
• 1:22:25
  Speaker 1: and it's still on set up mode. And you want
• 1:22:28
  Speaker 1: to hurt yourself when you do that, let me tell you. Yeah,
• 1:22:34
  Speaker 1: so guilty as charge. Most of us probably have done that. Yeah.
• 1:22:41
  Speaker 1: It's a brutal feeling. Yeah yeah, So UM, use a
• 1:22:45
  Speaker 1: camera that you have faith in, UM and work your
• 1:22:49
  Speaker 1: way up. Like I would like, just be gnawed with worry.
• 1:22:53
  Speaker 1: If I had gone straight from checking a camera every
• 1:22:56
  Speaker 1: two weeks, which I used to do, you know, eight
• 1:22:58
  Speaker 1: ten years ago. UM too, you know, I would check
• 1:23:02
  Speaker 1: it more frequently even than that before that to four months,
• 1:23:05
  Speaker 1: you know, But then I started leaving him a month
• 1:23:07
  Speaker 1: than I started leaving him a month and a half,
• 1:23:08
  Speaker 1: two months and now UM, and I have very few failures,
• 1:23:12
  Speaker 1: you know, Like last year, I think I had one
• 1:23:14
  Speaker 1: camera that failed um part way through UM out of
• 1:23:18
  Speaker 1: a dozen plus. So, UM, it doesn't happen, it doesn't
• 1:23:22
  Speaker 1: happen very often. UM. You just kind of have to
• 1:23:25
  Speaker 1: figure out what works for you. UM. I will say,
• 1:23:30
  Speaker 1: in the summer, it's much tougher to figure out optimal
• 1:23:33
  Speaker 1: camera placement. So even though I do get some cameras
• 1:23:37
  Speaker 1: out you know this time of year, it's only in
• 1:23:39
  Speaker 1: spots that I'm really really confident I know exactly where
• 1:23:42
  Speaker 1: to put it. Um. I really prefer to wait until
• 1:23:46
  Speaker 1: like late August into September, um, because the vegetation is
• 1:23:50
  Speaker 1: dying down. It's so much easier to get in place
• 1:23:52
  Speaker 1: because otherwise, yeah, you get it up this and then
• 1:23:54
  Speaker 1: you're gonna have ten thousand pictures of a leaf blown
• 1:23:57
  Speaker 1: back and forth in front of your camera, you know.
• 1:23:59
  Speaker 1: I know. So I used to run more cameras in
• 1:24:04
  Speaker 1: the summer than I do now. Actually I get a
• 1:24:06
  Speaker 1: few out, but they're only in spots where like either
• 1:24:09
  Speaker 1: there's just not much vegetation or you know, I just
• 1:24:11
  Speaker 1: know this is exactly how I need to put it, um,
• 1:24:16
  Speaker 1: because I've gotten burned a lot on the summertime cameras,
• 1:24:19
  Speaker 1: and it's harder on your cameras. Ants and um, you know, uh,
• 1:24:24
  Speaker 1: spiders building cobwebs over your you know, um, over your
• 1:24:29
  Speaker 1: sensor and stuff like that. Your or your lens or
• 1:24:31
  Speaker 1: something like that. I've seen it all so um yeah,
• 1:24:35
  Speaker 1: so um, you know I've minimized how much I hang
• 1:24:39
  Speaker 1: in the in the summer. Um. Yeah. One other thing,
• 1:24:44
  Speaker 1: so um you know talk about like optimal weather, Um,
• 1:24:48
  Speaker 1: I will I will say, you know, I've I've looked
• 1:24:51
  Speaker 1: at weather so much here um as everybody knows, like
• 1:24:55
  Speaker 1: cold fronts are good. Um, but it's not just that
• 1:24:58
  Speaker 1: um optimal. Whether the worst weather you can have for
• 1:25:01
  Speaker 1: a fall is like dead average the whole fall, um.
• 1:25:05
  Speaker 1: You I've learned. I really want swings, like I want
• 1:25:09
  Speaker 1: warmer than average, and then I want colder than average.
• 1:25:13
  Speaker 1: I want and I want those to last a little while.
• 1:25:16
  Speaker 1: If those only last a day or two each, it
• 1:25:18
  Speaker 1: seems like the deer get not confused, but they don't
• 1:25:20
  Speaker 1: have time to establish any kind of a pattern. And
• 1:25:24
  Speaker 1: it's really it just seems tougher hunting. So ideally there
• 1:25:29
  Speaker 1: would be like one great big weather system every week,
• 1:25:32
  Speaker 1: you know. In my mind, like if I could plan
• 1:25:34
  Speaker 1: out the perfect weather for a fall, you know, and
• 1:25:36
  Speaker 1: it would get well warm, significantly warmer than average, and
• 1:25:40
  Speaker 1: then you'd have a twenty five degree temperature drop and
• 1:25:43
  Speaker 1: then it would get warmer than average, and then you
• 1:25:45
  Speaker 1: have a twenty five degree temperature drop every you know,
• 1:25:48
  Speaker 1: five to seven days. So I thought I'd throw that
• 1:25:50
  Speaker 1: out there, like that's perfect. You can have too turbulent
• 1:25:53
  Speaker 1: a weather if it's all back and forth and the
• 1:25:55
  Speaker 1: winds you know, from the south one day in the
• 1:25:57
  Speaker 1: north the next day, and south and north you see
• 1:26:00
  Speaker 1: sawing that, Um, that isn't optimal and nor is like
• 1:26:06
  Speaker 1: south winds for you know, two weeks straight. Um, it's
• 1:26:09
  Speaker 1: it's definitely Um. It just seems dear kind of settle
• 1:26:13
  Speaker 1: into a routine after you know, when you get at
• 1:26:15
  Speaker 1: least two three days of consistent weather, whether whether it's
• 1:26:19
  Speaker 1: warm or cold, and then you can get a break
• 1:26:22
  Speaker 1: in a weather system and you can you can restart
• 1:26:25
  Speaker 1: those trends. So I thought, I throw that's something I've observed.
• 1:26:28
  Speaker 1: That's a great point. Those swings are pretty key. So, uh, Joe,
• 1:26:33
  Speaker 1: I know you need to run. We've taken a bunch
• 1:26:35
  Speaker 1: of your time here, and uh, I want to be
• 1:26:37
  Speaker 1: respectful of that. So maybe we can get you on again,
• 1:26:41
  Speaker 1: because there's always more and more wish you could talk
• 1:26:43
  Speaker 1: about with you. Uh, but it's always a pleasure and
• 1:26:46
  Speaker 1: uh problem thank you for doing this, Jo, no problem,
• 1:26:50
  Speaker 1: So thanks Mark, best to let this season. Let's uh,
• 1:26:54
  Speaker 1: let's stay in touch. And I'm very curious to see
• 1:26:56
  Speaker 1: how I might be able to start doing a little
• 1:26:58
  Speaker 1: bit more of this because I think you're you're on
• 1:27:00
  Speaker 1: do You're really onto something here about kind of expanding
• 1:27:04
  Speaker 1: the types of places that we're tracking and not just
• 1:27:06
  Speaker 1: dear not just the best weather, but also how alternate
• 1:27:10
  Speaker 1: weather patterns can lead dear to certain spots and maybe
• 1:27:12
  Speaker 1: we're not paying attention to so intriguing and good stuff,
• 1:27:17
  Speaker 1: and that is it. I hope all of you fellow
• 1:27:20
  Speaker 1: dear geeks out there enjoyed this one as much as
• 1:27:22
  Speaker 1: I did. Um after talking to Joe, I actually went
• 1:27:26
  Speaker 1: and started compiling a new data set for the number
• 1:27:29
  Speaker 1: one buck I'm after here in Michigan, this dear have
• 1:27:31
  Speaker 1: been calling. Tran just logged all of his daytime activity.
• 1:27:34
  Speaker 1: I've got fifteen different days worth of dailight activity that
• 1:27:38
  Speaker 1: I'm now going to be cross referencing to all this
• 1:27:41
  Speaker 1: different kind of data that we talked about. So needless
• 1:27:43
  Speaker 1: to say, I'm I'm excited and uh just can't wait
• 1:27:48
  Speaker 1: for the season to get here. So thanks for listening,
• 1:27:51
  Speaker 1: and you can check out more by heading over to
• 1:27:54
  Speaker 1: the meat Eater dot com, which is where all the
• 1:27:57
  Speaker 1: new podcasts are going, where my new articles are going,
• 1:28:00
  Speaker 1: where future new videos are going, as well as all
• 1:28:03
  Speaker 1: the rest of the mediat networks great podcasts and contributors.
• 1:28:06
  Speaker 1: You can see articles from the Baritone himself, spend some
• 1:28:10
  Speaker 1: new hearth. You can check out our podcast with Steve
• 1:28:12
  Speaker 1: ron Ellen, Ryan Callahan and Ben O'Brien and April Vokey. Um,
• 1:28:16
  Speaker 1: all sorts of good stuff out there, and uh, I
• 1:28:19
  Speaker 1: think you'll find a little bit of something no matter
• 1:28:21
  Speaker 1: what kind of person you are. So with all that said,
• 1:28:24
  Speaker 1: thank you for listening, and until next time, stay wired
• 1:28:29
  Speaker 1: to hunt.