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Speaker 1: Welcome to the Wire to Hunt podcast, your home for

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Speaker 1: deer hunting news, stories and strategies, and now your host,

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Speaker 1: Mark Kenyon. Welcome to the Wired to Hunt podcast. I'm

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Speaker 1: your host, Mark Kenyan, and this is episode number two

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Speaker 1: twenty nine and today Marjorie of Dreary Outdoors is back

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Speaker 1: with us again for the follow up to his unbelievably

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Speaker 1: popular Predicting Deer Moon episode that he did with us

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Speaker 1: back in two thousand and fifteen, and this time we're

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Speaker 1: taking things to a whole new level. Before we kick

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Speaker 1: things off that we want to thank our friends at

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Speaker 1: Lacrosse Boots for the support of this podcast episode. The

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Speaker 1: Cross boots are comfortable, their waterproof, they are just about

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Speaker 1: a cent free as you can get, and they're available

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Speaker 1: in all sorts of levels of insulation to suit any

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Speaker 1: time of year or temperature. As I've talked about here

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Speaker 1: over the past couple of weeks, I've got a new

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Speaker 1: pair of This year, I've started wearing that new throwback

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Speaker 1: green and yellow Elpha Burley Procept and not surprisingly they

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Speaker 1: are working great. I've been crossing creeks, climbing trees, hiking

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Speaker 1: through the woods and so hard the boots they fit

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Speaker 1: and they feel well, they are staying dry, They're doing

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Speaker 1: everything I need them to. So if you'd like to

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Speaker 1: learn more about Lacrosse boots yourself, you can visit Lacrosse

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Speaker 1: Footwear dot com. And welcome to the Wired to Hunt podcast,

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Speaker 1: brought to you by Onyx and ladies and gentlemen. Today,

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Speaker 1: we have got a good one for you. No, I'm

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Speaker 1: actually gonna take that back. We don't have a good one.

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Speaker 1: We have a great one for you today. It is

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Speaker 1: It is a special episodes one that as soon as

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Speaker 1: they got done recording this one, I just knew this

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Speaker 1: was going to be an all time favor At least

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Speaker 1: I think this is going to be an all time

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Speaker 1: favor as we have the Mad Scientists himself Mark Jury

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Speaker 1: back with us again. But I guess before I go

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Speaker 1: into explaining exactly what we've got going on in this episode,

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Speaker 1: do want to make a super quick plug here. Um,

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Speaker 1: this is actually our last preseason episode of the podcast

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Speaker 1: for two eighteen, because starting this weekend, my hunting season

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Speaker 1: is kicking off, and so is Dan season, and my

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Speaker 1: buddy Further and our producer Spencer, the whole crew, we

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Speaker 1: are all starting our hunting seasons here this weekend. So

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Speaker 1: lots of exciting stuff is going to be happening over

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Speaker 1: the coming days and weeks, and if you want to

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Speaker 1: stay up to date on all that stuff, there are

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Speaker 1: a couple of things that highly suggests you do. Number One,

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Speaker 1: make sure you're following Wired Hunt on Instagram. Number two,

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Speaker 1: make sure you subscribe to the Wired Hunt YouTube channel.

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Speaker 1: Number three, hit us up on Facebook. You know, once

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Speaker 1: the season starts, I'm gonna be posting nearly daily Instagram stories.

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Speaker 1: I'm gonna be documenting exactly what's happening each day. On YouTube,

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Speaker 1: We're gonna have our weekly video blogs. And then of

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Speaker 1: course I'll be sharing lots on Facebook too, including including

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Speaker 1: Facebook Live, Q and A sessions, which I was doing

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Speaker 1: last year during the season. I'm gonna be starting those

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Speaker 1: up again for this season here next week. So make

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Speaker 1: sure you're tapped into all these things. You can follow

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Speaker 1: along with what's going on, not just on the podcast here,

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Speaker 1: but really can see it and feel it, and we

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Speaker 1: share across all these different platforms, so it's gonna be

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Speaker 1: a fun year. Make sure you've hit the follow, hit

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Speaker 1: the subscribe buttons. It's just gonna take a couple of

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Speaker 1: seconds and hopefully be worthwhile and a good time for you.

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Speaker 1: So now with that little plug out of the way,

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Speaker 1: as I mentioned, Mark Dury is back with us and

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Speaker 1: our goal for this episode was to produce a sequel

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Speaker 1: to the podcast that we did back in two thousand

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Speaker 1: and fifteen that was episode number sixty three titled Predicting

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Speaker 1: Dear Movement with Mark Dury and and that one Mark

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Speaker 1: walked us through all sorts of different factors and variables

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Speaker 1: that it looks at when trying to determine when into

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Speaker 1: what degree dear will move. You know, this is important

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Speaker 1: because it's gonna help you understand maybe when you should

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Speaker 1: take your vacation days. This will help you determine maybe

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Speaker 1: when you should go hunting it all. This will help

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Speaker 1: you determine maybe when you should be aggressive and push

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Speaker 1: into your best places, or when you should pull back

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Speaker 1: and hunt more conservative stance, or hunt in public land

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Speaker 1: instead of pressuring your really good stuff. So understanding when

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Speaker 1: deer might move the most, or when that one or

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Speaker 1: two days when that mature muck might get up on

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Speaker 1: his feet, that's really really important because because just timing

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Speaker 1: your hunt's making sure you're in the right places at

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Speaker 1: the right time. That's probably the most important thing that

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Speaker 1: I've picked up over the last ten years that's helped

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Speaker 1: make me so much more successful. So this past episode

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Speaker 1: we did with Mark, number sixty three, it was it

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Speaker 1: was all about this idea, and it was wildly popular

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Speaker 1: and it got called out by a lot of our

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Speaker 1: listeners as one of their favorites of all time. So

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Speaker 1: I knew I eventually wanted to get Marked back on

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Speaker 1: the show to take things even further, and now it

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Speaker 1: seemed like the perfect time to do that because there's

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Speaker 1: this new mobile app that Mark and the team at

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Speaker 1: Drey Outdoors that they're launching is called deer Cast. And

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Speaker 1: this deer Cast app is really tied in directly to

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Speaker 1: this whole idea of predicting dear movement. I've tried it

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Speaker 1: out now myself. It is very cool, it's very useful.

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Speaker 1: Um I'll let Mark explain it to you guys here

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Speaker 1: himself in the second when he gets on. But but

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Speaker 1: what I can say is this, if you enjoyed episode

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Speaker 1: number sixty three, this one is going it's gonna knock

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Speaker 1: your socks stuff. I think we just go into so

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Speaker 1: much more detail. We examine all sorts of specific examples

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Speaker 1: and situations. I took a bunch of questions from you,

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Speaker 1: the listeners about the first episode we did with him,

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Speaker 1: and asked them to Mark. Asked him questions about, you know,

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Speaker 1: the things that you were confused about from the last time,

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Speaker 1: that things you want more details about last time. You know,

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Speaker 1: we explore the impacts of cold fronts and bare metric

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Speaker 1: pressure and precipitation and cloud cover and wind speed and

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Speaker 1: direction and thermals and the moon and humidity and time

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Speaker 1: of year and annual patterns and all that in just

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Speaker 1: greater detail than ever before. UM. I really think this

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Speaker 1: is this is a masterclass on predicting deer movement. I

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Speaker 1: will say this though, if you're new to deer hunting,

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Speaker 1: this one might be too in the weeds for you. UM,

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Speaker 1: At a minimum, I'd say that you should listen to

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Speaker 1: episode number sixty three first, and even after that if

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Speaker 1: this stuff seems confusing to you, you know, don't get

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Speaker 1: worried about it. This is this is kind of like

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Speaker 1: graduate level material or PhD level materials, So so you know,

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Speaker 1: go back listen to to sixteen, which is an intro

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Speaker 1: to deer hunting. Focus on those basics don't get too

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Speaker 1: wrapped up in this stuff yet. But if you are

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Speaker 1: a salty old veteran of the woods, and if your

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Speaker 1: dear daddy geek like me, I think you are going

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Speaker 1: to love this one. So rather than beat around the

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Speaker 1: bush any further, I think we should just dive her

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Speaker 1: into this one. So we're gonna take a very quick

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Speaker 1: break here and they will get mark jury on the

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Speaker 1: line for this predicting deer movement masterclass. I really hope

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Speaker 1: you enjoy it. And that said, we do need to

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Speaker 1: have a quick thank you here to our partners at

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Speaker 1: Onyx for the support of this podcast. Onyx is the

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Speaker 1: maker of the onyx Hunt app, which is a mobile

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Speaker 1: mapping application that shows you aerial and top of maps,

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Speaker 1: shows you public and private property, borders, hiking trails, campgrounds.

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Speaker 1: It allows you to mark way points, track where you've walked,

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Speaker 1: measure distances and areas, and a whole lot more. And

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Speaker 1: as I mentioned over the last couple of weeks, I've

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Speaker 1: been using onyx now for a number of years. This

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Speaker 1: year in particular, it's been especially helpful. Um I'm actually leaving,

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Speaker 1: as I've mentioned recently here, I'm leaving this weekend for

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Speaker 1: public land hunts in Montana and hopefully North Dakota to

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Speaker 1: and I'm almost a percent dependent on my onyx hunt

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Speaker 1: app to see where this public land is, to find

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Speaker 1: out how to access it, to map my ways in

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Speaker 1: and out, to mark my tree stand locations, to plan

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Speaker 1: where I think they are gonna be coming in and

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Speaker 1: out of, to measure distances from where I can park

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Speaker 1: my truck to get into spots. Um. It's just very

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Speaker 1: very useful, very helpful. I'll be, you know, pulling up

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Speaker 1: on my phone every single day over next week or two.

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Speaker 1: So if you'd like to try out yourself, you can

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Speaker 1: download it from whatever mobile app store you prefer, but

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Speaker 1: make sure you use promo code wired to get off

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Speaker 1: your order so that promo code is wired. W I

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Speaker 1: R E D. Alright, I'm back now with Mark Drury.

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Speaker 1: Thank you for joining me again. Mark, Hey, Mark, thank

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Speaker 1: you for having me a pretty shit. Yeah. I'm excited

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Speaker 1: to chat because we got to chat a decent bit

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Speaker 1: over the last couple of years with percent Wild, but

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Speaker 1: since I've kind of moved off from that this year,

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Speaker 1: we haven't caught up in I don't know, six seven months,

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Speaker 1: so I needed my Mad Scientists fix. I'm excited about

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Speaker 1: this today. I'm particularly excited too, because the last time

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Speaker 1: that you were actually on the Wired Hunt podcast, I

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Speaker 1: was way back in two thousand and fifteen. I believe

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Speaker 1: it was. That was episode number sixty three. We're now

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Speaker 1: on like two twenty nine or two thirty or something

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Speaker 1: like that, so I was a long time ago. But

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Speaker 1: that episode you came on and talked to me and

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Speaker 1: Dan about predicting deer movement, and we answered a lot

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Speaker 1: of questions that a lot of people have all the

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Speaker 1: time about what these different factors are influenced deer movement.

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Speaker 1: How you look at it, um, I've always thought that

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Speaker 1: you and Terry had a really interesting perspective on that.

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Speaker 1: In watching your videos and shows, it was that was

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Speaker 1: always one of my favorite things, was hearing why you

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Speaker 1: thought certain things were gonna happen. So we had that episode.

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Speaker 1: It turned out amazing, and it ended up being one

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Speaker 1: of our most popular episodes of all time. It's been

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Speaker 1: downloaded just short of a hundred thousand times now, a

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Speaker 1: lot of people have been diving into that episode. We've

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Speaker 1: gotten so much feedback on it. I've had people people

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Speaker 1: were commenting today when I told folks that we were

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Speaker 1: going to talk to you again about this topic. That

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Speaker 1: said it's the best audio piece of content that's ever

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Speaker 1: been put out in the hunting industry. That's what one

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Speaker 1: person said. So so we've got high, high bar to

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Speaker 1: get over today to try to top that. But but

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Speaker 1: I'm hoping we can because my idea was to go

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Speaker 1: to the two oh one level. If that was like

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Speaker 1: the predicting Dear Movement one o one, this could be

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Speaker 1: predicting dear movement two oh one or three oh one.

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Speaker 1: And where I'm getting with this is that all this

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Speaker 1: is top of mind for me right now because you

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Speaker 1: guys are launching a really cool new project that kind

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Speaker 1: of is all about this, this deer Cast app you

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Speaker 1: guys have got going on. UM. So I guess the

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Speaker 1: first thing I'm curious on Mark, can you give me,

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Speaker 1: like the deer Cast one oh one at the highest level,

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Speaker 1: what this is? Um? And then we can kind of

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Speaker 1: dig in from there, because I think you're you're putting

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Speaker 1: together a tool that's gonna be really really helpful that's

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Speaker 1: related to everything else I want to talk about today.

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Speaker 1: So I'm excited to hear more about this. I think

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Speaker 1: so if Our initial conversation was one on one, you know,

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Speaker 1: and today we're gonna talk a little bit about two

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Speaker 1: oh one. Deer cast would be you know, a graduate

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Speaker 1: course or a master's course. We have worked on this

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Speaker 1: thing tirelessly, literally from about back then until present day,

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Speaker 1: and maybe even prior to that. Terry and I have

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Speaker 1: studied deer movement for many, many years, especially over the

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Speaker 1: last decade a decade and a half. But specifically, uh,

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Speaker 1: this app that we did is and actually it's an

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Speaker 1: algorithm that we developed with an an app developer who

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Speaker 1: understood WHETHER, just like Terry and I did because he's

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Speaker 1: a pilot, so he had you know, he understood the

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Speaker 1: ins and outs of WHETHER, and he understood what we

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Speaker 1: meant when we talked about weather doing certain things because

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Speaker 1: he he was a student of it as well. But

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Speaker 1: he was not a deer hunter, which was good because

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Speaker 1: he had a clean mind. But he has a brilliant

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Speaker 1: mind in terms of we were able to create an

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Speaker 1: algorithm that on an hour by hour basis in your

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Speaker 1: location in other words, the app user's location or a

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Speaker 1: location that he sets or if he has his location

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Speaker 1: services on wherever he's standing, are there standing, it will

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Speaker 1: on an hour by our basis, interpret eleven different weather conditions.

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Speaker 1: It will interpret time of day, it will interpret um

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Speaker 1: the thirteen different phases. So it's actually interpreting about two

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Speaker 1: twenty five different things on an hour by hour basis

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Speaker 1: and then spitting out um a prediction on how the

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Speaker 1: deer should generally be moving in that area or that

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Speaker 1: set location. And we called it deer cast. Uh. So

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Speaker 1: the things that I used to take hours to study

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Speaker 1: and then decide, Okay, I think here's the day this

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Speaker 1: week the deer are gonna move. Uh. This thing does

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Speaker 1: in a matter of seconds. And it does it over

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Speaker 1: and over and over again all day, all day long,

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Speaker 1: all season long, wherever you're at, or whatever locations you

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Speaker 1: put into it. You can put multiple locations into it.

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Speaker 1: So it is um in my opinion. And I said

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Speaker 1: this the other day that the app almost knows what

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Speaker 1: the deer are gonna do before that deer knows what's

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Speaker 1: gonna do. He'll know it a few days in advance

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Speaker 1: of when the the app will know in advance of

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Speaker 1: when the deer. No, because deer move on instinct. We've

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Speaker 1: patterned that instinct and how they behave in and around

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Speaker 1: certain weather patterns, and we've plugged all that into an

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Speaker 1: algorithm that interprets the weather and then spits out what

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Speaker 1: the deer should be doing. Now, the app can't tell

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Speaker 1: you where to sit. It can't know if coyotes cleared

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Speaker 1: your bed that day. It can't know if three trespassers

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Speaker 1: walked your farm, you know, looking for a stand or

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Speaker 1: a camera. It can't know those things other influencers, but

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Speaker 1: it can know the weather and how it should influence

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Speaker 1: dear movement. Um. We also have a set pessimism in

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Speaker 1: this app for really heavily hunted areas, so we took

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Speaker 1: it to that level. We have a little bit more

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Speaker 1: of an optimism for lighter hunting areas. UM. So it

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Speaker 1: even takes into consideration that and even even outside of that,

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Speaker 1: you could customize it to your own area by just

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Speaker 1: observing dear movement, looking at what the app tell it

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Speaker 1: is telling you it's gonna do, and then having your

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Speaker 1: own set of pessimism or are optimism and go, you

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Speaker 1: know what, the app is consistently always too optimistic or

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Speaker 1: it's consistently too pessimistic form my area, and you can

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Speaker 1: you can adjust on your own. And I would advise

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Speaker 1: people to do that because not every deer hurts created equal.

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Speaker 1: You know, Mark, if I came up to Michigan and

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Speaker 1: huntred your deer, they're gonna probably react differently to the

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Speaker 1: weather than they do down at my Texas lease or

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Speaker 1: so and so forth. So the app is going to

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Speaker 1: generally tell you pick out tendencies of when deer should

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Speaker 1: be moving, but then you can, you know, adjust it

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Speaker 1: to your own hunting experiences. UH. The app is free

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Speaker 1: this first inaugural season for everybody to use and understand.

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Speaker 1: And we've got some tremendous help in there in terms

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Speaker 1: of how to use the app, how to hunt with

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Speaker 1: the app, some really cool visual tools that that should

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Speaker 1: help everybody understand it. UH. In addition to that, the

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Speaker 1: entire Dree Outdoors Library is found within this app. So

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Speaker 1: there's a hundred and fifteen DVDs that are found within

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Speaker 1: this app. There's over twenty tho minutes of d O

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Speaker 1: d t V content in there. There are stories there

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Speaker 1: that are being uploaded on a weekly daily basis. We

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Speaker 1: have twelve staff writers that are writing you know, hunting

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Speaker 1: content for us. UH. It's it's pretty incredible offering and

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Speaker 1: and for the first time ever we have deer cast

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Speaker 1: now and everybody wants to be you know, immediate gratification,

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Speaker 1: be in the now, being the know behind the scenes. Well,

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Speaker 1: every kill as they happen from the dry Outdoors team,

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Speaker 1: and historically we kill about a hundred a year. Uh,

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Speaker 1: they'll they'll be on the app the moment we can

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Speaker 1: get them up there. In other words, if Matt Drewry

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Speaker 1: goes out and kills a one eight, we're gonna try

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Speaker 1: and get that sucker uploaded onto the app, the actual

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Speaker 1: kill shot that day, with how I killed it and

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Speaker 1: what's going on in his area, so that people can

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Speaker 1: not only learn from the app and the weather predictor

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Speaker 1: and the deer movement predictor, but also how our guys

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Speaker 1: are succeeding in the field of tactics they're using, etcetera, etcetera.

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Speaker 1: So it's a it's a very fun filled app, it's

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Speaker 1: a smart app, and it's it's a product we're very

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Speaker 1: proud to put the d D and the Drewy Outdoors

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Speaker 1: brand on. Yeah, it's pretty incredible. When I first heard

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Speaker 1: about the idea of an app, I had, you know,

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Speaker 1: I knew it would be interesting, But when I've heard

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Speaker 1: about what's really going to be in it? Um, My

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Speaker 1: mind's a little bit blown. You guys have really outdone yourself.

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Speaker 1: I think I can't wait to get my hands on it. Um,

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Speaker 1: can you describe though, what like the output looks like

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Speaker 1: if going back to the dear cast portion of it,

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Speaker 1: the actual predictor portion. So I go in there, I've

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Speaker 1: I've slept to my location. Um now I'm looking at

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Speaker 1: like my five day forecast or whatever that might be,

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Speaker 1: trying to figure out, okay, what's the best days or

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Speaker 1: how are these up coming this upcoming weekend? Look, can

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Speaker 1: you describe us a little bit of what we're actually

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Speaker 1: gonna see? Is it just gonna say like Friday good,

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Speaker 1: Saturday great? Or is there more detail? What does that

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Speaker 1: it'll look like compared to like a typical weather app

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Speaker 1: or something. Absolutely it will remind you of a weather

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Speaker 1: app in terms of um, you know, it's stakes certain

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Speaker 1: things that are important to hunters, and these are ones

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Speaker 1: Terry and I picked out. For instance, I'm looking at

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Speaker 1: that my dear cast version right now, and it says

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Speaker 1: today my location is set for the farm, and it

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Speaker 1: tells me that today's average high is eighty four, which

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Speaker 1: is very important. And I don't know that I speak

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Speaker 1: much on the departure from average temperature in two thousand

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Speaker 1: and fifteen and how important it is for dear movement. Uh,

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Speaker 1: you know a little bit when we talked about fronts.

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Speaker 1: I definitely want to dive into that more though. Okay,

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Speaker 1: So the first thing it states is today's high and low,

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Speaker 1: what today's average highest, which is very important. It tells

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Speaker 1: you sunrise and sunset, very important every deer hunter. It

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Speaker 1: tells you moon rise and moonset. It tells you the

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Speaker 1: precipitate precipitate chance, It tells you the bara metric pressure,

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Speaker 1: and it tells you the wind direction and speed. So

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Speaker 1: they're in one quick snapshot basically tells you everything a

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Speaker 1: deer hunter wants to know on a day in and

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Speaker 1: day out basis, and that those are some of the

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Speaker 1: weather conditions, you know, like I'd have to go to

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Speaker 1: three different apps to find all of those out and

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Speaker 1: write them down. I don't know about you, I've never

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Speaker 1: seen one stated like that. This one has it all

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Speaker 1: right there in one screen shot for today. If I

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Speaker 1: touch today, it then takes me into the deer cast.

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Speaker 1: All right, today, the morning is good evening is good.

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Speaker 1: There are four categories of movements, which, if you think

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Speaker 1: about it, they either move really good, really at or

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Speaker 1: somewhere in the middle. So our different categories are you know, poor,

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Speaker 1: are bad, poor, good, great. That's the way that we

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Speaker 1: broke them down. You can click on tomorrow it will

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Speaker 1: give you tomorrow's sports deer cast, Thursdays, Friday's, Saturday's, or

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Speaker 1: you can click hourly detail, so it'll it'll give five

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Speaker 1: days worth of deer cast, and we could have given

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Speaker 1: fifteen if we wanted to. However, because of the variability

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Speaker 1: of weather forecast, we felt like it would be an

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Speaker 1: injustice to the hunter for him to plan a hunt

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Speaker 1: ten days out when in reality that weather data is

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Speaker 1: about accurate ten days out, if you know what I mean.

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Speaker 1: If you look at every weather forecaster out there, they're

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Speaker 1: most accurate within about twenty four to seventy two hours.

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Speaker 1: So thusly the deer cast is going to be much

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Speaker 1: more accurate in the short term and it will be

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Speaker 1: long term. We've extended it to five, but we didn't

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Speaker 1: want to go beyond that because we felt like six, seven, eight, nine,

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Speaker 1: and ten. As we watched it last fall, we had

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Speaker 1: a deer cast beta test on a ten day forecast,

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Speaker 1: but hell, by the time you got today, six, seven,

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Speaker 1: and eight, it was no longer accurate because the weather

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Speaker 1: forecast to change fifteen times, So we give it to five.

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Speaker 1: But we will absolutely admit the days that are most

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Speaker 1: accurate are the ones where the weather forecast is most accurate.

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Speaker 1: So it's days two and three, okay, But you can

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Speaker 1: click into the hourly details, and then in the hourly details,

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Speaker 1: the top line is deer movement, and you can scan

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Speaker 1: your hand across that middle or your finger and it

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Speaker 1: will take you across five different days and show you

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Speaker 1: the trends as they're trending to better movement, stable movement,

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Speaker 1: worst movement, you know, as it's tailing off, and then stable,

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Speaker 1: poor movement, whatever it is. You then go into uh

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Speaker 1: it also on that same line. All of this is

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Speaker 1: at once. It's as you dear movement shows you barometer,

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Speaker 1: it shows you precipitation, it shows you cloud cover, it

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Speaker 1: shows you temperature, it shows you average high it shows

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Speaker 1: you wind direction and wind speed. So all of that,

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Speaker 1: and that's that's not all the predictors that you're you're

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Speaker 1: looking at, but all of that is what the app

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Speaker 1: interpreting and that's what you can see on a daily basis.

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Speaker 1: So then go right below that and there's about a

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Speaker 1: ten to twelve minute video that says Phase one because

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Speaker 1: that's the first phase, and you'll see every single tactic

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Speaker 1: we use during this space. So it goes beyond understanding

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Speaker 1: the weather. Now we're getting into hunting tactics, similar to

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Speaker 1: the tactics you see on thirteen. If you took all

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Speaker 1: of those tactical breakdowns we've been across the first fourth

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Speaker 1: season and glue them all together, that is what you

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Speaker 1: would have there. So it goes through all the tactics,

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Speaker 1: goes through all our breakdown to all that information that's

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Speaker 1: on thirteen, and there after that it then goes sorry.

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Speaker 1: Then it goes into a variety of different interviews that

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Speaker 1: Tear and I did in terms of the influencers for

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Speaker 1: that day. The first one will be time of day,

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Speaker 1: so that you understand clearly in Phase one when we

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Speaker 1: see the most daylight activity, so always watch time of day.

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Speaker 1: That's very important for each phase. Then it goes into

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Speaker 1: cloud cover barometer, time of day, cloud cover overview barometer,

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Speaker 1: overview average, temperature, moon overview average temperare average temperature overview

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Speaker 1: and so and so forth. So it goes through all

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Speaker 1: these different weather influencers and then we tell you why

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Speaker 1: the deer are moving poorly that day, are great that day,

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Speaker 1: based on whatever weather conditions the app is recognizing. So

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Speaker 1: we sat and we did interviews at nauseum based on

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Speaker 1: every condition that could possibly happen during every phase. And

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Speaker 1: when it comes up, you will see a video of

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Speaker 1: Terry and I breaking it down what that weather conditions

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Speaker 1: doing or should do to your dear that particular time

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Speaker 1: of the year. It's pretty pretty thorough. I say, it's

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Speaker 1: not only the cheat sheet, it's the whole test and

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Speaker 1: all the answers. Man, I mean you've got the cheat sheet. Okay,

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Speaker 1: dear moving great today. Well, if you'll take the time,

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Speaker 1: and some people will want to and some people won't,

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Speaker 1: you're gonna be one of those guys that watch them all.

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Speaker 1: I know how you are. You can go down. You

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Speaker 1: can go down and watch all those those interviews and

431
00:22:19,880 --> 00:22:23,479
Speaker 1: it's it is four oh one in terms of weather um,

432
00:22:23,600 --> 00:22:26,800
Speaker 1: in terms of deer movement as it pertains to the weather. Yeah,

433
00:22:26,840 --> 00:22:29,040
Speaker 1: the way I'm imagining this just from what I've heard

434
00:22:29,080 --> 00:22:31,680
Speaker 1: you say, and from hearing a little bit more, it

435
00:22:31,880 --> 00:22:34,280
Speaker 1: seems like it's gonna be really not just not just

436
00:22:34,320 --> 00:22:36,720
Speaker 1: a cheat sheet, but like an incredible tool to help

437
00:22:36,760 --> 00:22:38,960
Speaker 1: you just learn more about this stuff too, because you

438
00:22:39,000 --> 00:22:41,720
Speaker 1: can you can take all these different influencers that maybe

439
00:22:41,760 --> 00:22:44,399
Speaker 1: already you're starting to pay attention to just as an individual,

440
00:22:44,720 --> 00:22:47,480
Speaker 1: and then you can compare and contrast that to what's

441
00:22:47,480 --> 00:22:50,520
Speaker 1: being told, what's being shown on the deer cast, compare

442
00:22:50,600 --> 00:22:53,440
Speaker 1: that against the different factors and and things that you're

443
00:22:53,440 --> 00:22:56,240
Speaker 1: explaining those videos. It seems like a kind of three

444
00:22:56,680 --> 00:22:59,199
Speaker 1: sixty degree way to to learn about this stuff too,

445
00:22:59,280 --> 00:23:01,600
Speaker 1: not just the endver's all, but I'll actually also learn

446
00:23:01,640 --> 00:23:04,479
Speaker 1: how to better predict some of these things yourself, um,

447
00:23:04,520 --> 00:23:07,399
Speaker 1: which will only help help you alongside the app, I

448
00:23:07,400 --> 00:23:12,440
Speaker 1: would imagine absolutely. We like to say, every single thought

449
00:23:12,560 --> 00:23:15,200
Speaker 1: that's in mine and Terry's head is in this app.

450
00:23:15,280 --> 00:23:17,439
Speaker 1: If you will take the time to watch it, you

451
00:23:17,480 --> 00:23:20,160
Speaker 1: will know exactly what's in our head. And and that's

452
00:23:20,160 --> 00:23:25,119
Speaker 1: all that's a little scary. But if it's every single thought,

453
00:23:25,200 --> 00:23:29,000
Speaker 1: but that's in there man, as it pertains the dear

454
00:23:29,040 --> 00:23:31,040
Speaker 1: movement in the weather, every thought we have is in

455
00:23:31,080 --> 00:23:34,800
Speaker 1: this app and I'm not joking. So so here's then

456
00:23:36,080 --> 00:23:38,440
Speaker 1: the question that some people are gonna have. I feel

457
00:23:38,440 --> 00:23:41,800
Speaker 1: like when we get into this topic of predicting deer movement,

458
00:23:42,080 --> 00:23:45,280
Speaker 1: there's gonna be some naysayers who are like people that

459
00:23:45,359 --> 00:23:47,480
Speaker 1: focus so much on this stuff are just looking for

460
00:23:47,520 --> 00:23:50,840
Speaker 1: excuses not to hunt. They're just looking for you know,

461
00:23:51,040 --> 00:23:53,120
Speaker 1: just go hunt when you can, is what they're gonna say.

462
00:23:53,119 --> 00:23:55,440
Speaker 1: If you can hunt, just get out there. None of

463
00:23:55,480 --> 00:23:57,720
Speaker 1: this stuff matters. People get all caught up into it

464
00:23:57,760 --> 00:24:01,639
Speaker 1: too much. So to that person, could you tell me?

465
00:24:01,680 --> 00:24:03,840
Speaker 1: What would you tell them? Why? Why is this important?

466
00:24:03,880 --> 00:24:07,160
Speaker 1: Why is it important to be able predict dear movement? Well,

467
00:24:07,200 --> 00:24:10,120
Speaker 1: I'm that person. I mean I hunted every single day

468
00:24:10,119 --> 00:24:13,159
Speaker 1: of the Iowa both season last year, from start to finish,

469
00:24:13,200 --> 00:24:14,840
Speaker 1: every day of the Missouri season. You know, if I

470
00:24:14,840 --> 00:24:16,960
Speaker 1: went to Missouri, I was in Iowa vice versa, or

471
00:24:17,000 --> 00:24:18,440
Speaker 1: I was in Texas, I hunted every day of the

472
00:24:18,480 --> 00:24:22,000
Speaker 1: season last year. So whether it's said good, bad or otherwise,

473
00:24:22,119 --> 00:24:25,600
Speaker 1: because it's in my soul, I want to go hunting. However,

474
00:24:26,119 --> 00:24:29,880
Speaker 1: where I hunted very drastically based on the deer cast

475
00:24:29,960 --> 00:24:32,040
Speaker 1: that I was looking at and what I thought was

476
00:24:32,080 --> 00:24:34,480
Speaker 1: going to happen, and I've always been that way. I

477
00:24:34,560 --> 00:24:37,800
Speaker 1: will not go into those premier great spots on a

478
00:24:37,840 --> 00:24:40,879
Speaker 1: bad day. I will, however, still go hunt. Maybe it's

479
00:24:40,920 --> 00:24:43,320
Speaker 1: an observatory stand. Maybe it's somewhere where I'm trying to

480
00:24:43,320 --> 00:24:45,119
Speaker 1: look for another buck. Maybe it's a stand where I

481
00:24:45,160 --> 00:24:47,720
Speaker 1: just want to go take a dough things like that.

482
00:24:47,880 --> 00:24:52,200
Speaker 1: So it helps you understand the good places to hunt,

483
00:24:52,440 --> 00:24:54,760
Speaker 1: the bad places to hunt, and when to hunt them.

484
00:24:54,800 --> 00:24:58,240
Speaker 1: So absolutely I'm that guy. Go hunt every single day,

485
00:24:58,440 --> 00:25:01,440
Speaker 1: but make a good choice about where you choose to sit. Yeah,

486
00:25:01,680 --> 00:25:03,320
Speaker 1: So what would it be fair to say that you

487
00:25:03,400 --> 00:25:06,359
Speaker 1: have you know all these different locations across your your

488
00:25:06,440 --> 00:25:09,920
Speaker 1: hunting properties, that there are certain times of the year

489
00:25:10,160 --> 00:25:12,560
Speaker 1: that you know certain spots can be hunted or cannot

490
00:25:12,560 --> 00:25:15,400
Speaker 1: be hunted. There are certain types of days like good days,

491
00:25:15,440 --> 00:25:18,040
Speaker 1: bad days, poor days, great days, that certain stands will

492
00:25:18,040 --> 00:25:21,119
Speaker 1: be ranked according to all these things. So you're you're

493
00:25:21,160 --> 00:25:23,760
Speaker 1: every day looking at this and say, okay, based on

494
00:25:23,880 --> 00:25:27,240
Speaker 1: my prediction of deer movement, I then it filters the

495
00:25:27,320 --> 00:25:32,320
Speaker 1: list of possible places to hunt, right absolutely absolutely does

496
00:25:32,400 --> 00:25:34,680
Speaker 1: you know? And you learn all that sort of previous

497
00:25:34,760 --> 00:25:37,360
Speaker 1: years hunting and making mistakes. It's really the only way

498
00:25:37,359 --> 00:25:40,240
Speaker 1: you can learn it. So you gotta go to make mistakes,

499
00:25:40,520 --> 00:25:43,800
Speaker 1: you know, and when you make them, successful hunting is

500
00:25:43,840 --> 00:25:47,280
Speaker 1: all about avoiding those mistakes. As you know, the older

501
00:25:47,280 --> 00:25:50,040
Speaker 1: you get, the wiser you get, the less mistakes you make,

502
00:25:50,280 --> 00:25:53,800
Speaker 1: and the more the more success you have. And that's uh,

503
00:25:53,960 --> 00:25:57,000
Speaker 1: that's part of any process, regardless of what it is,

504
00:25:57,000 --> 00:26:01,720
Speaker 1: whether it's golf or or archery, or hunting or baseball. Man,

505
00:26:01,840 --> 00:26:04,879
Speaker 1: you learn from your mistakes, and the good ones smart

506
00:26:04,920 --> 00:26:08,280
Speaker 1: one don't make many mistakes. Do you're the same? What

507
00:26:08,600 --> 00:26:10,080
Speaker 1: look at him when they are a year and a half.

508
00:26:10,520 --> 00:26:12,280
Speaker 1: Don't hunt that guy, and then you don't hunt when

509
00:26:12,280 --> 00:26:14,480
Speaker 1: he's four or five. He's made every mistake in the book.

510
00:26:14,480 --> 00:26:18,840
Speaker 1: He's still alive. He didn't make him twice, generally done twice.

511
00:26:19,040 --> 00:26:22,600
Speaker 1: That's why they're the toughest game antim to consistently kill.

512
00:26:22,600 --> 00:26:27,120
Speaker 1: In my opinion, mature don't kill six year older every year.

513
00:26:27,119 --> 00:26:30,520
Speaker 1: It's it's almost impossible, very very tough. Yeah. So so

514
00:26:30,560 --> 00:26:34,840
Speaker 1: speaking of mature white tail bucks, then you as you

515
00:26:34,960 --> 00:26:38,000
Speaker 1: as you usually do. You had a great season last year.

516
00:26:38,000 --> 00:26:39,960
Speaker 1: I think if I saw the journal interests right you

517
00:26:40,040 --> 00:26:43,919
Speaker 1: killed four white tail bucks last year. Do you have

518
00:26:44,359 --> 00:26:46,520
Speaker 1: are any of one of those or maybe two of those?

519
00:26:47,320 --> 00:26:50,359
Speaker 1: An example you can share with us about how the

520
00:26:50,440 --> 00:26:54,080
Speaker 1: predictions influenced that hunt, how you change your decision, making

521
00:26:54,080 --> 00:26:56,520
Speaker 1: your actions based off that prediction, how that ended up

522
00:26:56,600 --> 00:27:03,600
Speaker 1: leading to success, or anything along those lines. Um, everyone,

523
00:27:03,800 --> 00:27:06,199
Speaker 1: I used deer cast for because we were studying it

524
00:27:06,320 --> 00:27:11,080
Speaker 1: so so intensely. And you know, I also filmed several

525
00:27:11,080 --> 00:27:13,399
Speaker 1: people killed deer last year, you know, Taylor and my

526
00:27:13,480 --> 00:27:16,439
Speaker 1: sisters and Bruce Pettitt, and you know, we had a

527
00:27:16,480 --> 00:27:20,840
Speaker 1: tremendous season. And we also had a season that since

528
00:27:20,880 --> 00:27:23,560
Speaker 1: I've been doing this, I've never seen better conditions more

529
00:27:23,600 --> 00:27:25,719
Speaker 1: consistently than we had last ball. I don't know if

530
00:27:25,720 --> 00:27:27,760
Speaker 1: you noticed that or if they were that good for

531
00:27:27,800 --> 00:27:33,840
Speaker 1: you up there mid October on it was great. Oh, tremendous, man.

532
00:27:34,000 --> 00:27:37,280
Speaker 1: We had below average temperatures, We had incredible bouts of

533
00:27:37,359 --> 00:27:41,440
Speaker 1: high pressure that wouldn't go away, and the deer moved incredibly.

534
00:27:41,560 --> 00:27:44,320
Speaker 1: Last ball moon was great. It hit a good times,

535
00:27:44,920 --> 00:27:48,159
Speaker 1: and uh, it was fun. So I used deer casts

536
00:27:48,320 --> 00:27:51,520
Speaker 1: on every single hunt that I had. Did it steer me?

537
00:27:52,160 --> 00:27:55,639
Speaker 1: You know, differently from from the decision I would have

538
00:27:55,680 --> 00:27:58,320
Speaker 1: made anyway. No, but I was able to make those

539
00:27:58,359 --> 00:28:02,080
Speaker 1: decisions decisions in a much quicker process because keep in

540
00:28:02,119 --> 00:28:05,720
Speaker 1: mind that the deer cast is my thoughts and mine

541
00:28:05,720 --> 00:28:07,959
Speaker 1: and terries, you know, and it's what we've done for

542
00:28:08,040 --> 00:28:11,880
Speaker 1: the last ten years. We've really homed it. But if

543
00:28:11,920 --> 00:28:13,960
Speaker 1: it really wouldn't, I would have still hunted the exact

544
00:28:13,960 --> 00:28:17,000
Speaker 1: same place as I hunted. Yeah, so it probably, you know,

545
00:28:17,440 --> 00:28:20,280
Speaker 1: so it probably didn't change me because this is the

546
00:28:20,280 --> 00:28:22,439
Speaker 1: way I've been hunting based around the weather and and

547
00:28:22,480 --> 00:28:25,600
Speaker 1: those influencers and where I need to be in in uh,

548
00:28:25,680 --> 00:28:27,919
Speaker 1: where I didn't. That's that's you know why we did

549
00:28:27,920 --> 00:28:30,639
Speaker 1: the interviews back in fifteen and we started talking about

550
00:28:30,640 --> 00:28:33,720
Speaker 1: these weather influencers. Yeah, I think I asked my question wrong.

551
00:28:33,760 --> 00:28:36,840
Speaker 1: What I meant was not not deer cast, but just

552
00:28:36,920 --> 00:28:41,920
Speaker 1: simply the information, you know. So for let my hypothetical be, okay, on,

553
00:28:42,680 --> 00:28:44,480
Speaker 1: you killed the buck on the first day of October,

554
00:28:44,960 --> 00:28:48,040
Speaker 1: So could you tell us what do you remember about

555
00:28:48,040 --> 00:28:50,080
Speaker 1: the conditions that day that made you think, Okay, yeah,

556
00:28:50,120 --> 00:28:51,480
Speaker 1: this is gonna be a day I need to go

557
00:28:51,560 --> 00:28:54,920
Speaker 1: to ex place um or were the conditions some certain

558
00:28:54,960 --> 00:28:57,280
Speaker 1: way that made you say, oh, because of this, I

559
00:28:57,400 --> 00:28:59,760
Speaker 1: know that I can you know, I have to lay

560
00:28:59,800 --> 00:29:02,000
Speaker 1: back an observation stand or I know I can push

561
00:29:02,000 --> 00:29:04,000
Speaker 1: in and get to this spot because it's gonna be windy,

562
00:29:04,000 --> 00:29:06,080
Speaker 1: and I can be more aggressive. I'm curious to hear

563
00:29:06,400 --> 00:29:10,320
Speaker 1: how the specific influencers that day led to your success

564
00:29:10,320 --> 00:29:12,200
Speaker 1: and led to your decisions. That's I think when I

565
00:29:12,280 --> 00:29:16,800
Speaker 1: most Yeah, absolutely, yeah. It was October one, and I

566
00:29:16,840 --> 00:29:18,520
Speaker 1: did kill a deer that day. He was my number

567
00:29:18,520 --> 00:29:20,719
Speaker 1: one target here on the whole farm. I was extremely

568
00:29:20,760 --> 00:29:24,120
Speaker 1: fortunate because in all reality that I went to a

569
00:29:24,240 --> 00:29:26,760
Speaker 1: number two slot that day in my opinion, In other words,

570
00:29:26,800 --> 00:29:28,720
Speaker 1: I had one that I thought was a little bit better.

571
00:29:29,120 --> 00:29:31,719
Speaker 1: And it was not the first south after North, if

572
00:29:31,720 --> 00:29:33,880
Speaker 1: I'm not mistaken, it was the second, but it had

573
00:29:33,920 --> 00:29:36,640
Speaker 1: some speed to it. We also had crowd cover, which

574
00:29:36,720 --> 00:29:38,800
Speaker 1: I kind of like earlier in the season more so

575
00:29:38,880 --> 00:29:41,480
Speaker 1: than I like it late in the season. And uh,

576
00:29:41,520 --> 00:29:43,640
Speaker 1: I thought, you know what, it's gonna be pretty good today,

577
00:29:43,760 --> 00:29:46,120
Speaker 1: but I didn't think it was gonna be the optimum day.

578
00:29:46,240 --> 00:29:49,320
Speaker 1: And and indeed the forecast, the deer cast said good,

579
00:29:49,320 --> 00:29:51,600
Speaker 1: it didn't say great. So I went to a number

580
00:29:51,600 --> 00:29:54,320
Speaker 1: two slot. And I didn't think that I would see

581
00:29:54,400 --> 00:29:57,360
Speaker 1: him where I did, but I did um see him there.

582
00:29:57,440 --> 00:30:00,680
Speaker 1: He was about three or four hundred yards from where

583
00:30:00,680 --> 00:30:02,280
Speaker 1: I thought I was going to kill that deer. I

584
00:30:02,320 --> 00:30:04,040
Speaker 1: had two or three places where I thought I could

585
00:30:04,120 --> 00:30:06,960
Speaker 1: kill him, and this was lower on the totem pole.

586
00:30:07,000 --> 00:30:10,000
Speaker 1: But I went there because I didn't have the ultimate

587
00:30:10,120 --> 00:30:13,280
Speaker 1: forecast in terms of dear movement are in terms of

588
00:30:13,280 --> 00:30:15,880
Speaker 1: the weather, and I just got very fortunate that he

589
00:30:15,920 --> 00:30:18,360
Speaker 1: walked onto that field that night. I had history of

590
00:30:18,440 --> 00:30:20,840
Speaker 1: him in that field and years past, and I have

591
00:30:21,040 --> 00:30:24,320
Speaker 1: history of a big mature bucks in that particular field,

592
00:30:24,600 --> 00:30:26,680
Speaker 1: but I didn't have as much history there as I

593
00:30:26,680 --> 00:30:28,880
Speaker 1: did in a few other places. So I think the

594
00:30:28,920 --> 00:30:31,000
Speaker 1: stars kind of lined up and I had some good

595
00:30:31,040 --> 00:30:34,120
Speaker 1: fortune there. But the deer cast pushed me to go

596
00:30:34,200 --> 00:30:36,200
Speaker 1: to a number two slots instead of number one as

597
00:30:36,200 --> 00:30:38,520
Speaker 1: far as what in my mind was the best place

598
00:30:38,560 --> 00:30:40,920
Speaker 1: to kill him. Interesting. So so then my next thing

599
00:30:40,920 --> 00:30:43,600
Speaker 1: I'm curious about that is, could you describe what was

600
00:30:43,640 --> 00:30:46,360
Speaker 1: the scenario there that made that a number two? And

601
00:30:46,400 --> 00:30:49,480
Speaker 1: then what was the scenario in the top spots where

602
00:30:49,480 --> 00:30:50,880
Speaker 1: you thought you were going to kill him? What was

603
00:30:50,920 --> 00:30:55,320
Speaker 1: the train or what was. I'm just curiously understand totally

604
00:30:55,320 --> 00:31:00,320
Speaker 1: frequency of pictures of him totally frequenting that area years

605
00:31:00,360 --> 00:31:03,760
Speaker 1: passed and already last year. That was that was what

606
00:31:03,880 --> 00:31:06,200
Speaker 1: made my determination. He was my number one target. So

607
00:31:06,400 --> 00:31:08,720
Speaker 1: that's the only buck I was gonna hunt. So therefore

608
00:31:08,880 --> 00:31:13,640
Speaker 1: I was only hunting him based on previous years uh pictures.

609
00:31:14,000 --> 00:31:16,720
Speaker 1: I had a number another one close to a pond,

610
00:31:17,200 --> 00:31:19,920
Speaker 1: a staging plot that I got him a lot at

611
00:31:20,760 --> 00:31:25,920
Speaker 1: the past two or three years. Probably probably forty of

612
00:31:25,960 --> 00:31:28,240
Speaker 1: the daylight pictures that I had of that deer was

613
00:31:28,280 --> 00:31:31,880
Speaker 1: over there um at that spot, so I considered it

614
00:31:31,920 --> 00:31:34,680
Speaker 1: my number one, and then this number two spot I

615
00:31:34,720 --> 00:31:39,960
Speaker 1: had maybe daylight activity on that field um and then

616
00:31:40,000 --> 00:31:42,360
Speaker 1: obviously daylight activity in between. But I wasn't going to

617
00:31:42,440 --> 00:31:44,040
Speaker 1: go into the cover that time of year. Man, it's

618
00:31:44,040 --> 00:31:46,680
Speaker 1: all about green. It's green revisited. And both of them

619
00:31:46,680 --> 00:31:50,360
Speaker 1: were green food sources. One of them I planted um

620
00:31:50,400 --> 00:31:52,960
Speaker 1: in case we got good rains, and it came on

621
00:31:53,080 --> 00:31:55,280
Speaker 1: and it did well. The other one was a clover field,

622
00:31:55,280 --> 00:31:57,000
Speaker 1: and that's in case you don't get very good rains.

623
00:31:57,000 --> 00:32:00,280
Speaker 1: Those clover fields are incredible insurance policies. For years where

624
00:32:00,320 --> 00:32:02,840
Speaker 1: in a drought and barely get any rain, they'll they'll

625
00:32:02,880 --> 00:32:05,880
Speaker 1: get green quicker than a you know, an annual flip

626
00:32:05,880 --> 00:32:09,640
Speaker 1: plot that you put in. So I had options for him,

627
00:32:09,680 --> 00:32:11,920
Speaker 1: and he was my number one target going in. Yeah,

628
00:32:12,800 --> 00:32:19,120
Speaker 1: So what about a scenario where you get the bad conditions.

629
00:32:19,200 --> 00:32:22,520
Speaker 1: Let's say it's early October now, and I guess let

630
00:32:22,520 --> 00:32:26,080
Speaker 1: me reframe this during that time frame. Could you outline

631
00:32:26,080 --> 00:32:28,040
Speaker 1: for me what like an awful day would be? So

632
00:32:28,040 --> 00:32:30,800
Speaker 1: what would be the influencers or conditions that you seem like, oh,

633
00:32:30,920 --> 00:32:33,280
Speaker 1: this is this is gonna be a bad day. Deer

634
00:32:33,320 --> 00:32:36,000
Speaker 1: cast is showing me bad but you still want to hunt,

635
00:32:36,080 --> 00:32:40,360
Speaker 1: So what are you doing that scenario? Dropping pressure? Uh?

636
00:32:40,600 --> 00:32:43,280
Speaker 1: Third third day of south, second day of fuse is

637
00:32:43,360 --> 00:32:45,480
Speaker 1: usually tough after you know, say you've had a cold

638
00:32:45,520 --> 00:32:48,640
Speaker 1: fra a bunch of north with high pressure, and then

639
00:32:48,680 --> 00:32:51,640
Speaker 1: the first day of south always awesome. And one thing

640
00:32:51,680 --> 00:32:54,480
Speaker 1: about dear, if you're sitting there having a good sit

641
00:32:55,200 --> 00:32:57,320
Speaker 1: you're about to have a bad one because they just

642
00:32:57,400 --> 00:33:00,760
Speaker 1: don't do the same things day and day. So if

643
00:33:00,800 --> 00:33:03,440
Speaker 1: you've been having good movement, you can just about bet

644
00:33:03,440 --> 00:33:05,280
Speaker 1: you're about to have some poor movement because they just

645
00:33:05,320 --> 00:33:07,880
Speaker 1: don't do it day in and day out. So stable

646
00:33:08,040 --> 00:33:12,440
Speaker 1: pressure that's below thirties, say it's like twenty nine eight five,

647
00:33:12,480 --> 00:33:14,440
Speaker 1: and it's gonna be that for three straight days with

648
00:33:14,520 --> 00:33:19,160
Speaker 1: south winds and above average temperatures. I mean, the it's

649
00:33:19,200 --> 00:33:22,400
Speaker 1: just horrible. It's horrible. I mean, it's just you know,

650
00:33:22,840 --> 00:33:26,120
Speaker 1: when those temperatures start to creep above that average high

651
00:33:26,640 --> 00:33:30,040
Speaker 1: and really depart from it, it is such a deterrent

652
00:33:30,080 --> 00:33:34,120
Speaker 1: it's not even funny. It's almost a linear relationship between

653
00:33:34,560 --> 00:33:37,800
Speaker 1: departure from average high, whether that be in the positive

654
00:33:37,840 --> 00:33:43,120
Speaker 1: or negative direction, and overall dear movement. It's a major influencer.

655
00:33:43,160 --> 00:33:45,480
Speaker 1: It's it's one of the key things that we look at.

656
00:33:45,600 --> 00:33:47,920
Speaker 1: One of the elevens. Yeah, would you is it fair

657
00:33:47,920 --> 00:33:49,400
Speaker 1: to say that would be the top of the list,

658
00:33:49,480 --> 00:33:55,840
Speaker 1: number one, Mm hmmm, it's no, it's one of them.

659
00:33:55,880 --> 00:34:01,080
Speaker 1: It's one of them. But pressure is also up there. Um,

660
00:34:01,080 --> 00:34:04,360
Speaker 1: you know, wind speed, wind directions up there, precipts up there.

661
00:34:04,400 --> 00:34:06,680
Speaker 1: There's a lot of them that are very close in relativity,

662
00:34:06,800 --> 00:34:10,520
Speaker 1: so it but those vary, that varies from phase to phase.

663
00:34:10,560 --> 00:34:12,839
Speaker 1: That's the other thing we've we've picked apart here within

664
00:34:12,920 --> 00:34:16,399
Speaker 1: deer casts like there are certain influencers that are much

665
00:34:16,440 --> 00:34:20,320
Speaker 1: more important in phase one than they are in phase

666
00:34:20,840 --> 00:34:24,520
Speaker 1: twelve and thirteen, and the algorithm looks at that and

667
00:34:24,560 --> 00:34:28,200
Speaker 1: then interprets the importance level and ranks them accordingly. So

668
00:34:28,280 --> 00:34:32,279
Speaker 1: therefore they are waited differently by phase based on the

669
00:34:32,320 --> 00:34:35,760
Speaker 1: way we've seen them affect the deer by phase. Um,

670
00:34:35,800 --> 00:34:39,000
Speaker 1: So what kind of what kind of factors are different

671
00:34:39,000 --> 00:34:40,600
Speaker 1: in that kind of way. To give an example of

672
00:34:40,680 --> 00:34:46,160
Speaker 1: one that is really important, plod covers major differentiator. Yeah,

673
00:34:46,320 --> 00:34:51,600
Speaker 1: early season clouds almost always always a company cooler weather,

674
00:34:52,080 --> 00:34:56,520
Speaker 1: rainy days, and the deer move like crazy. Um. Later

675
00:34:56,600 --> 00:35:00,440
Speaker 1: in the year, you you you've eliminated what they're most

676
00:35:01,000 --> 00:35:03,880
Speaker 1: what they're most looking for, which is thermal cover in

677
00:35:03,920 --> 00:35:06,200
Speaker 1: the In the early part of the season, you eliminate

678
00:35:06,239 --> 00:35:08,799
Speaker 1: thermal cover at cools the earth, they move better. In

679
00:35:08,840 --> 00:35:11,759
Speaker 1: the latter part of the season, when it's cold and

680
00:35:11,800 --> 00:35:15,320
Speaker 1: you eliminate the sun, they get cooled off and therefore

681
00:35:15,320 --> 00:35:18,279
Speaker 1: they don't move as well. So it is an influencer

682
00:35:18,440 --> 00:35:21,440
Speaker 1: early in the season, it is something that influences them

683
00:35:21,440 --> 00:35:24,480
Speaker 1: in a negative way in the late season. It's a

684
00:35:24,560 --> 00:35:29,920
Speaker 1: great example of how a weather factor differentiates an importance

685
00:35:30,120 --> 00:35:34,440
Speaker 1: from phase to phase. Um, So back to my question

686
00:35:34,440 --> 00:35:36,759
Speaker 1: I asked before that though, So back to the bad day.

687
00:35:37,320 --> 00:35:40,480
Speaker 1: You've got the horrible conditions you just mentioned there, what

688
00:35:40,520 --> 00:35:42,319
Speaker 1: do you then do from a hunting standpoint? What are

689
00:35:42,360 --> 00:35:45,080
Speaker 1: you what's your go to move for those lousy days.

690
00:35:46,520 --> 00:35:50,880
Speaker 1: I'm gonna hunt something on the extreme um outskirts of

691
00:35:50,880 --> 00:35:53,160
Speaker 1: a farm. I'm probably gonna go try and fill the

692
00:35:53,200 --> 00:35:56,120
Speaker 1: freezer with a dough or I'm gonna sit somewhere where

693
00:35:56,160 --> 00:35:57,919
Speaker 1: I might be able to kill a buck, but I'm

694
00:35:57,920 --> 00:36:00,920
Speaker 1: also observing something that helps me learn a part of

695
00:36:00,960 --> 00:36:04,000
Speaker 1: the farm. I do a lot of hunt slash scout days.

696
00:36:04,600 --> 00:36:07,000
Speaker 1: In other words, I don't think I'm gonna go in

697
00:36:07,040 --> 00:36:08,960
Speaker 1: for the kill. I'm not going for the home run.

698
00:36:09,040 --> 00:36:11,200
Speaker 1: So I'm gonna sit somewhere where I can learn something

699
00:36:11,400 --> 00:36:13,359
Speaker 1: and become better at a certain part of the farm

700
00:36:13,400 --> 00:36:17,120
Speaker 1: in future days. I do a lot of observation. You know,

701
00:36:17,200 --> 00:36:19,120
Speaker 1: the cameras only tell you so much. They only show

702
00:36:19,160 --> 00:36:21,480
Speaker 1: you a few feet, right, you know you really the

703
00:36:21,520 --> 00:36:24,040
Speaker 1: way you learn a farm is with your eyeballs. Yeah,

704
00:36:26,480 --> 00:36:29,560
Speaker 1: so so let's let's step back them. Because we talked

705
00:36:29,560 --> 00:36:31,920
Speaker 1: about why this stuff is important. You know when you

706
00:36:32,080 --> 00:36:33,759
Speaker 1: when you do have the right conditions, that's going to

707
00:36:33,880 --> 00:36:36,279
Speaker 1: influence you to to go into your best spots, to

708
00:36:36,360 --> 00:36:38,719
Speaker 1: be more aggressive, to go for the kill. When you've

709
00:36:38,760 --> 00:36:41,200
Speaker 1: got the poor conditions, you're gonna state out a little bit.

710
00:36:41,200 --> 00:36:43,399
Speaker 1: You're gonna be more conservative, You're gonna observe, you're gonna

711
00:36:43,440 --> 00:36:44,840
Speaker 1: try to learn, but you're not gonna go for the

712
00:36:44,880 --> 00:36:48,040
Speaker 1: home run. UM. So deer cast is going to be

713
00:36:48,040 --> 00:36:50,040
Speaker 1: a tool to to figure all this stuff out. But

714
00:36:50,080 --> 00:36:51,600
Speaker 1: I want to dive into a little more on each

715
00:36:51,600 --> 00:36:55,319
Speaker 1: of these influencers. Can you share what the eleven influencers are,

716
00:36:55,800 --> 00:36:57,799
Speaker 1: um that you're including in there. I think we've kind

717
00:36:57,840 --> 00:37:00,319
Speaker 1: of mentioned most of them, but if we haven't, UM,

718
00:37:00,360 --> 00:37:03,880
Speaker 1: I know things that temperature, very much of pressure, wind speed,

719
00:37:03,920 --> 00:37:08,279
Speaker 1: wind direction, precipitation, moon, Um, what are the other ones

720
00:37:08,320 --> 00:37:12,319
Speaker 1: that I'm missing there? I don't have the list right

721
00:37:12,320 --> 00:37:15,840
Speaker 1: in front of me. Um. Time of day is a

722
00:37:15,840 --> 00:37:18,160
Speaker 1: big one, but that's not really a weather influencers but

723
00:37:18,400 --> 00:37:20,879
Speaker 1: but it is a weather influencer. The barometer. I don't

724
00:37:20,880 --> 00:37:27,560
Speaker 1: know if you mentioned that change in barometric pressure, wind speed,

725
00:37:28,760 --> 00:37:33,120
Speaker 1: wind directions, and then wind as it relates both backwards

726
00:37:33,160 --> 00:37:35,879
Speaker 1: and forward. That's the other thing that the app does.

727
00:37:36,680 --> 00:37:39,759
Speaker 1: It not only looks at the time of that you're

728
00:37:39,760 --> 00:37:44,440
Speaker 1: in today, it's looking backwards and it's looking forwards because

729
00:37:45,120 --> 00:37:48,600
Speaker 1: it interprets how the deer should have just acted. It

730
00:37:48,719 --> 00:37:51,960
Speaker 1: also interprets how the deer are about to act and

731
00:37:52,000 --> 00:37:54,600
Speaker 1: then gives you a prediction based on that. If that

732
00:37:54,640 --> 00:38:03,279
Speaker 1: makes sense, it's very very cool. Uh breach temperature, um temperature,

733
00:38:03,560 --> 00:38:11,400
Speaker 1: change in temperature, precipitation rate, change in precipitation, right moon,

734
00:38:12,840 --> 00:38:17,120
Speaker 1: Uh do is that? I think that's probably eleven of them.

735
00:38:17,160 --> 00:38:18,640
Speaker 1: I don't know if I missed any. Those are just

736
00:38:18,719 --> 00:38:20,560
Speaker 1: off memory. I don't have my list right in front

737
00:38:20,560 --> 00:38:23,640
Speaker 1: of me, but I think I've hit them all. Yeah, covered,

738
00:38:24,239 --> 00:38:29,640
Speaker 1: pod cover, changing cloud cover. Yeah. So, I just like you,

739
00:38:29,760 --> 00:38:32,040
Speaker 1: I geek out over this stuff. This stuff fascinates me

740
00:38:32,120 --> 00:38:34,600
Speaker 1: so much and obviously a lot of other people, because

741
00:38:34,600 --> 00:38:36,960
Speaker 1: I know you've been inundated with questions over the years,

742
00:38:37,000 --> 00:38:39,040
Speaker 1: and I've been inundated with questions over the years on

743
00:38:39,080 --> 00:38:42,440
Speaker 1: this stuff. So for a few of these, if you're

744
00:38:42,480 --> 00:38:45,720
Speaker 1: up for it, I kind of want to touch on, Okay,

745
00:38:45,760 --> 00:38:48,440
Speaker 1: influencer A and then if you can give me like

746
00:38:48,480 --> 00:38:51,600
Speaker 1: the twenty second like overview of like that this is

747
00:38:51,680 --> 00:38:54,920
Speaker 1: this is cold front one oh one, simply because if

748
00:38:54,920 --> 00:38:57,279
Speaker 1: people haven't heard the past podcast what we did with you,

749
00:38:57,400 --> 00:38:58,960
Speaker 1: or if someone's brand new to hunting, I want to

750
00:38:58,960 --> 00:39:00,680
Speaker 1: make sure we at least get the Bay six out there.

751
00:39:00,880 --> 00:39:03,720
Speaker 1: But then I've got some really detailed questions about specific

752
00:39:03,719 --> 00:39:06,520
Speaker 1: situations and things like that, um that maybe we can

753
00:39:06,560 --> 00:39:09,280
Speaker 1: dive into from there. So so let's at the highest

754
00:39:09,360 --> 00:39:13,279
Speaker 1: level really quick temperature cold fronts. Can you give me

755
00:39:13,360 --> 00:39:16,319
Speaker 1: the one on one on on why that's important what

756
00:39:16,400 --> 00:39:20,000
Speaker 1: you look at there? And then I've got a few specifics. Well,

757
00:39:20,000 --> 00:39:22,399
Speaker 1: there's so many things that go into a coal front, right.

758
00:39:22,520 --> 00:39:27,440
Speaker 1: You know, you're gonna have probably a change in wind direction,

759
00:39:27,760 --> 00:39:30,640
Speaker 1: You're gonna have a change in temperature, and if it's

760
00:39:30,680 --> 00:39:32,600
Speaker 1: the right type coal front, the kind that really gets

761
00:39:32,600 --> 00:39:35,960
Speaker 1: a moving, you're gonna have some type of falling precipitation.

762
00:39:36,560 --> 00:39:40,040
Speaker 1: That precip will change throughout the season, from rain early

763
00:39:40,120 --> 00:39:43,640
Speaker 1: in the season to potentially sleep during the rut or

764
00:39:43,800 --> 00:39:48,360
Speaker 1: or snow in late season, most likely snow. Um. So

765
00:39:48,840 --> 00:39:51,200
Speaker 1: if you if you look at every coal front, I

766
00:39:51,239 --> 00:39:53,319
Speaker 1: always say you want to kill white tailed deer. Don't

767
00:39:53,360 --> 00:39:55,720
Speaker 1: miss any coal fronts. And I'm talking about just ahead

768
00:39:55,719 --> 00:39:59,240
Speaker 1: of it, during it, and after it. That, in a nutshell,

769
00:39:59,800 --> 00:40:03,160
Speaker 1: is when the best of the best dear movement happens

770
00:40:03,719 --> 00:40:06,399
Speaker 1: is just before it, during it, and after it. Not

771
00:40:06,560 --> 00:40:10,120
Speaker 1: every coal front is created the same. In other words,

772
00:40:10,440 --> 00:40:12,799
Speaker 1: there are some that barely move the needle, and there

773
00:40:12,840 --> 00:40:16,120
Speaker 1: are some that move it a bunch. What how the

774
00:40:16,200 --> 00:40:19,480
Speaker 1: weather changes in and around that coal front. The greater

775
00:40:19,600 --> 00:40:23,200
Speaker 1: the change with the coal front, generally the more drastic,

776
00:40:23,360 --> 00:40:27,160
Speaker 1: and the better the dear moment, The less the amount

777
00:40:27,200 --> 00:40:31,600
Speaker 1: of change, the less extreme influence it will have on

778
00:40:31,640 --> 00:40:36,200
Speaker 1: the dear moment. Okay, that makes sense. So on that

779
00:40:36,280 --> 00:40:38,280
Speaker 1: topic of front, it's one of the most common questions

780
00:40:38,280 --> 00:40:42,280
Speaker 1: that I get them, is okay, what about the timing

781
00:40:42,320 --> 00:40:44,840
Speaker 1: of the front. So you talked about it's good before

782
00:40:44,840 --> 00:40:47,359
Speaker 1: the front, it's good during, it's good after. I think

783
00:40:47,360 --> 00:40:49,839
Speaker 1: people are always trying to figure out more detail about that.

784
00:40:50,000 --> 00:40:53,359
Speaker 1: So how far ahead of time and then how long

785
00:40:53,440 --> 00:40:55,600
Speaker 1: afterwards is it one day after the front passes it?

786
00:40:55,680 --> 00:40:57,680
Speaker 1: Two days, that three days? Can you give us some

787
00:40:57,760 --> 00:41:00,600
Speaker 1: detail as far as as that? And then also how

788
00:41:00,640 --> 00:41:02,880
Speaker 1: would you rank that? So if I had to choose

789
00:41:02,880 --> 00:41:08,080
Speaker 1: between before, during, or after. What's one, two, three? All

790
00:41:08,120 --> 00:41:13,360
Speaker 1: are a one, that's for sure. All are a one. Um,

791
00:41:13,600 --> 00:41:17,840
Speaker 1: meaning tops never miss just ahead during or after a

792
00:41:17,880 --> 00:41:20,040
Speaker 1: cold front, because you never know when the best is

793
00:41:20,040 --> 00:41:22,839
Speaker 1: gonna be or where you're gonna be sitting. The back

794
00:41:22,880 --> 00:41:26,799
Speaker 1: to your question of how far ahead of the front,

795
00:41:26,840 --> 00:41:31,640
Speaker 1: it's generally it's very close to it. In other words, Um,

796
00:41:31,680 --> 00:41:33,839
Speaker 1: if the front is gonna pass during the night, it's

797
00:41:33,880 --> 00:41:38,720
Speaker 1: that evening sit before, okay, if and that's just depends

798
00:41:38,760 --> 00:41:42,000
Speaker 1: on the phase. If it's a phase, that are the

799
00:41:42,080 --> 00:41:45,799
Speaker 1: time of the year when afternoon movement is generally a

800
00:41:45,840 --> 00:41:47,920
Speaker 1: little better than morning movement. In other words, it's a

801
00:41:48,000 --> 00:41:52,640
Speaker 1: feeding time of the year. Take phase one. Then then

802
00:41:52,719 --> 00:41:55,960
Speaker 1: the front that's going to pass during the night is

803
00:41:56,000 --> 00:42:00,400
Speaker 1: going to influence the previous feeding time, if that makes sense.

804
00:42:00,600 --> 00:42:04,759
Speaker 1: So if you're if opening days theft September and there's

805
00:42:04,760 --> 00:42:07,320
Speaker 1: a front supposed to pass at about ten eleven o'clock

806
00:42:07,400 --> 00:42:10,520
Speaker 1: that night, the cold fronts coming, but it's not there yet,

807
00:42:10,719 --> 00:42:12,719
Speaker 1: that evening is gonna be pretty good because they're gonna

808
00:42:12,760 --> 00:42:17,319
Speaker 1: be feeding in anticipation of that front. If, however, it

809
00:42:17,520 --> 00:42:22,080
Speaker 1: is opening morning when feeding is not nearly as important.

810
00:42:22,800 --> 00:42:26,719
Speaker 1: And say, the same time gap is in front of you,

811
00:42:26,960 --> 00:42:30,840
Speaker 1: in other words, dark as at seven o'clock PM or

812
00:42:30,880 --> 00:42:33,279
Speaker 1: seven thirty or eight, and the fronts supposed to pass

813
00:42:33,280 --> 00:42:36,640
Speaker 1: at ten, so say three hours ahead of the front. Well,

814
00:42:37,280 --> 00:42:39,239
Speaker 1: if the morning movement at that time of the year

815
00:42:39,280 --> 00:42:41,239
Speaker 1: is about seven am and the front's gonna pass at

816
00:42:41,239 --> 00:42:43,920
Speaker 1: about ten am, that's not going to be nearly as

817
00:42:44,080 --> 00:42:46,560
Speaker 1: as big of an influencer of the morning as it

818
00:42:46,600 --> 00:42:48,880
Speaker 1: would have been in the evening because evening times are

819
00:42:48,920 --> 00:42:50,920
Speaker 1: better at that time of the year. Does that make sense?

820
00:42:51,520 --> 00:42:57,000
Speaker 1: It does, Okay, So it's it's all very very detailed.

821
00:42:57,000 --> 00:42:58,960
Speaker 1: And I said that apps for one, like the app

822
00:42:59,080 --> 00:43:02,640
Speaker 1: interpret every single one of those factors on a minute

823
00:43:02,640 --> 00:43:05,640
Speaker 1: by minute basis or second by second like it will

824
00:43:05,680 --> 00:43:08,839
Speaker 1: spit that algorithm out NonStop for you right exactly where

825
00:43:08,840 --> 00:43:11,480
Speaker 1: you are. It's interpreting everything I just said. But it

826
00:43:11,520 --> 00:43:14,319
Speaker 1: does it in real time, as opposed to, like I said,

827
00:43:14,360 --> 00:43:16,040
Speaker 1: it takes me hours to sit and look at a

828
00:43:16,080 --> 00:43:18,759
Speaker 1: forecast and look at various apps and come up with

829
00:43:18,800 --> 00:43:21,600
Speaker 1: the actual prediction. The app does it for you. In fact,

830
00:43:22,239 --> 00:43:26,080
Speaker 1: I found myself getting a little bit floppy last year

831
00:43:26,560 --> 00:43:28,680
Speaker 1: because I was so dependent on the app. I mean,

832
00:43:28,719 --> 00:43:31,239
Speaker 1: I still had all this knowledge in my head, but

833
00:43:31,920 --> 00:43:34,000
Speaker 1: there were times of the year where I actually forced

834
00:43:34,080 --> 00:43:36,720
Speaker 1: myself before I looked at the app, to go through

835
00:43:36,800 --> 00:43:38,520
Speaker 1: and come up with a prediction and go, I think

836
00:43:38,560 --> 00:43:40,200
Speaker 1: it's gonna say this, and then I'd go back and

837
00:43:40,480 --> 00:43:43,239
Speaker 1: double check it because you'd ever, you know, it's human nature.

838
00:43:43,280 --> 00:43:44,759
Speaker 1: You get tired to get run down. You go, I'm

839
00:43:44,760 --> 00:43:46,160
Speaker 1: just gonna look at the app instead of looking at

840
00:43:46,200 --> 00:43:49,080
Speaker 1: all these different sites and figure all this stuff out. Um,

841
00:43:49,120 --> 00:43:51,520
Speaker 1: because it's really a thinking game. Man. If you if

842
00:43:51,520 --> 00:43:54,880
Speaker 1: you're trying to analyze what time of year in, what

843
00:43:55,000 --> 00:43:57,480
Speaker 1: all influencers are coming, how they were two or three

844
00:43:57,520 --> 00:43:59,960
Speaker 1: days ago, how they're about to be. Man, the app

845
00:44:00,040 --> 00:44:02,879
Speaker 1: so lot easier solutions, but you do it, you just

846
00:44:02,880 --> 00:44:05,600
Speaker 1: get you know, it's the understanding of it that that

847
00:44:05,680 --> 00:44:08,319
Speaker 1: makes it sweeter. Yeah, yeah, that that's That's a lot

848
00:44:08,320 --> 00:44:10,600
Speaker 1: of the fun part putting that puzzle together. But this

849
00:44:10,680 --> 00:44:12,640
Speaker 1: is this is nice to be able to look at,

850
00:44:12,960 --> 00:44:17,680
Speaker 1: you know, to quickly confirm things or to dive in further. Um. Now,

851
00:44:18,760 --> 00:44:21,319
Speaker 1: sometimes came to mind and I don't know if this

852
00:44:21,400 --> 00:44:23,279
Speaker 1: is something you guys already have baked in or not.

853
00:44:23,480 --> 00:44:26,319
Speaker 1: But is there any possibility of there being like a

854
00:44:26,360 --> 00:44:29,719
Speaker 1: feedback mechanism to this? So if I have the deer

855
00:44:29,760 --> 00:44:32,239
Speaker 1: cast app, today's supposed to be a great day, I'm

856
00:44:32,280 --> 00:44:35,759
Speaker 1: out there and it doesn't end up being that case,

857
00:44:35,840 --> 00:44:37,880
Speaker 1: doesn't end it being that way for me? Whatever reason

858
00:44:38,000 --> 00:44:42,359
Speaker 1: is there any way? Right? But what what what influenced that? Right? Yeah,

859
00:44:42,360 --> 00:44:46,200
Speaker 1: there's so many things, There's so many outside things. So

860
00:44:46,680 --> 00:44:50,560
Speaker 1: does it skew what what we feel like? We That's

861
00:44:50,560 --> 00:44:54,120
Speaker 1: why I think everybody should have their ability to to

862
00:44:54,360 --> 00:44:58,279
Speaker 1: skew their own handing experiences, not everyone else's, if that

863
00:44:58,360 --> 00:45:02,000
Speaker 1: makes sense, because what other influencers. You don't know how

864
00:45:02,040 --> 00:45:03,960
Speaker 1: somebody hunts. He might be sitting there hunting on the

865
00:45:04,000 --> 00:45:07,280
Speaker 1: wrong window, or or someone might hunt the same stand

866
00:45:07,600 --> 00:45:14,279
Speaker 1: thirty five days in a row, and and exactly you know,

867
00:45:14,880 --> 00:45:18,320
Speaker 1: and app saying great, Well, every deer in the area

868
00:45:18,400 --> 00:45:20,640
Speaker 1: knows where he sits on what window. You know, he's

869
00:45:20,640 --> 00:45:22,439
Speaker 1: sit in the same place. You know, they know where

870
00:45:22,440 --> 00:45:24,040
Speaker 1: they're going to catch him. They know what side of

871
00:45:24,080 --> 00:45:26,239
Speaker 1: the blind to go on to catching that day, because

872
00:45:26,239 --> 00:45:28,959
Speaker 1: the wind switch, you know, I'm I'm saying that would

873
00:45:29,000 --> 00:45:36,759
Speaker 1: be I think challenging UM at best. I will tell

874
00:45:36,760 --> 00:45:40,719
Speaker 1: you that we we tested it across uh the entire

875
00:45:40,760 --> 00:45:44,120
Speaker 1: Dreary Outdoors team, through a variety of geographies and a

876
00:45:44,200 --> 00:45:47,919
Speaker 1: variety of different hunting conditions, and it it had rave

877
00:45:48,040 --> 00:45:51,640
Speaker 1: reviews from everyone. UH. So it was beta tested very

878
00:45:51,680 --> 00:45:56,800
Speaker 1: thoroughly last fall, and I'm I am very very confident

879
00:45:56,880 --> 00:46:00,840
Speaker 1: that what the app for Dixon turn of deer movement,

880
00:46:01,280 --> 00:46:04,440
Speaker 1: what they most likely will be doing, is accurate in

881
00:46:04,560 --> 00:46:07,759
Speaker 1: terms of how will influenced the deer herd. The thing

882
00:46:07,840 --> 00:46:14,200
Speaker 1: the app cannot interpret is hunting pressure, pregation pressure, overall population, UM,

883
00:46:14,600 --> 00:46:18,760
Speaker 1: all those other outside influencers, you know, public ground versus

884
00:46:18,800 --> 00:46:22,800
Speaker 1: private UH, gun season, you know, the gun season Missouri

885
00:46:22,840 --> 00:46:27,000
Speaker 1: opens November fifteenth, roughly Iowa doesn't open until till December

886
00:46:27,040 --> 00:46:29,239
Speaker 1: the seventh. You know, So you have to look at

887
00:46:29,280 --> 00:46:31,360
Speaker 1: it and kind of use common sense and go, you

888
00:46:31,360 --> 00:46:34,280
Speaker 1: know what, this app always says great, but in reality

889
00:46:34,320 --> 00:46:36,680
Speaker 1: I'm kind of seeing good. Well, there might be some

890
00:46:36,760 --> 00:46:40,920
Speaker 1: other influencers that have that movement suppressed outside of the weather,

891
00:46:41,120 --> 00:46:43,400
Speaker 1: if that makes sense. Yeah, you need to need to

892
00:46:43,440 --> 00:46:46,120
Speaker 1: overlay your own circumstances over top of this, because as

893
00:46:46,360 --> 00:46:48,520
Speaker 1: you said, there's all these other outside factors that can't

894
00:46:48,520 --> 00:46:51,359
Speaker 1: be accounted for and something like this that that do

895
00:46:51,600 --> 00:46:55,680
Speaker 1: significantly influence things. You gotta you gotta grade it on

896
00:46:55,760 --> 00:47:00,160
Speaker 1: the curve if you will. Yeah, so you kind of

897
00:47:00,200 --> 00:47:02,279
Speaker 1: alluded to this next question. I have a little bit,

898
00:47:02,360 --> 00:47:06,960
Speaker 1: but I want to kind of black and white it here. Um,

899
00:47:07,080 --> 00:47:10,120
Speaker 1: the timing of the front. Does the timing of the

900
00:47:10,160 --> 00:47:14,279
Speaker 1: front in any kind of consistent way impact the intensity

901
00:47:14,280 --> 00:47:17,919
Speaker 1: of the activity. So if you were to say, would

902
00:47:17,920 --> 00:47:21,120
Speaker 1: you prefer a front to hit during peak evening activity

903
00:47:21,120 --> 00:47:25,279
Speaker 1: hours versus overnight versus morning activity versus midday like if

904
00:47:25,440 --> 00:47:27,520
Speaker 1: if we broke up our day into those four buckets

905
00:47:27,600 --> 00:47:31,399
Speaker 1: or something like that, and you could pick yes, yes, yes,

906
00:47:31,440 --> 00:47:33,200
Speaker 1: and yes, depending on the time of the year. In

907
00:47:33,239 --> 00:47:37,279
Speaker 1: other words, a front in September is not It does

908
00:47:37,320 --> 00:47:39,480
Speaker 1: not affect the deer the same as it does in

909
00:47:39,520 --> 00:47:42,200
Speaker 1: the middle part of November, as it does in the

910
00:47:42,200 --> 00:47:44,440
Speaker 1: middle part of the December, as it does in the

911
00:47:44,440 --> 00:47:47,920
Speaker 1: middle part of January, because their metabolism is at different

912
00:47:47,960 --> 00:47:52,160
Speaker 1: speeds during each each of those times, their testosterone is

913
00:47:52,200 --> 00:47:55,840
Speaker 1: at different levels during each of those times, their interest levels,

914
00:47:55,880 --> 00:47:59,120
Speaker 1: and their focus is that is on different things during

915
00:47:59,120 --> 00:48:03,160
Speaker 1: each of those times, So therefore they react differently to

916
00:48:03,239 --> 00:48:05,919
Speaker 1: the front. They're going to be times of the year

917
00:48:06,200 --> 00:48:08,520
Speaker 1: where the middle part of the day it's gonna be

918
00:48:08,600 --> 00:48:11,400
Speaker 1: magical to have a front, whereas other times of the

919
00:48:11,440 --> 00:48:13,279
Speaker 1: year it's not gonna affect them at all. They won't

920
00:48:13,280 --> 00:48:16,880
Speaker 1: move until after that front passes, you know. Um, that

921
00:48:17,040 --> 00:48:19,320
Speaker 1: was kind of my example I gave in the early

922
00:48:19,360 --> 00:48:21,319
Speaker 1: part of the season, when afternoons or the are the

923
00:48:21,400 --> 00:48:24,040
Speaker 1: order of the day. Well, if you have a front

924
00:48:24,360 --> 00:48:27,040
Speaker 1: passing within the normal movement time in the morning versus

925
00:48:27,080 --> 00:48:29,080
Speaker 1: the evening, there it's just not going to be the

926
00:48:29,120 --> 00:48:32,480
Speaker 1: same response. The evening response is going to be much

927
00:48:32,560 --> 00:48:36,040
Speaker 1: better to affront because that's when they typically moved. Couple

928
00:48:36,200 --> 00:48:38,640
Speaker 1: a rising moon with that, and you've got all the

929
00:48:38,680 --> 00:48:43,160
Speaker 1: stars lighting up. Pardon, pardon the punt um. You move

930
00:48:43,200 --> 00:48:45,799
Speaker 1: into mid November, when the rut is the major influencer,

931
00:48:46,200 --> 00:48:48,840
Speaker 1: weather kind of takes a little bit of a back seat,

932
00:48:48,920 --> 00:48:52,759
Speaker 1: but it's still a major influencer. So it's that's one

933
00:48:52,760 --> 00:48:54,560
Speaker 1: of the reasons we did the app because it is

934
00:48:54,600 --> 00:48:58,799
Speaker 1: so hard to articulate all of this in a podcast

935
00:48:58,880 --> 00:49:01,480
Speaker 1: and tell you all of this to where someone said,

936
00:49:01,520 --> 00:49:06,160
Speaker 1: you know, there's there's no one solution because it influences

937
00:49:06,200 --> 00:49:09,080
Speaker 1: them differently, almost on a day by day basis. It's

938
00:49:09,160 --> 00:49:12,080
Speaker 1: it's crazy. Um. So that's why that's one of the

939
00:49:12,160 --> 00:49:14,600
Speaker 1: reasons we did the app, just to help people understand

940
00:49:14,600 --> 00:49:19,480
Speaker 1: it better. It's a very complex set of I don't

941
00:49:19,480 --> 00:49:23,960
Speaker 1: want to say rules, but set of responses to stimulus

942
00:49:23,960 --> 00:49:27,560
Speaker 1: that we've seen. They vary drastically throughout the year. So

943
00:49:27,640 --> 00:49:29,759
Speaker 1: that's why we put it into an algorithm form so

944
00:49:29,800 --> 00:49:33,319
Speaker 1: that it might interpret it and help someone understand when

945
00:49:33,360 --> 00:49:35,680
Speaker 1: they might move the best or when they might move

946
00:49:35,719 --> 00:49:39,120
Speaker 1: the poorest. Yeah. Yeah, yeah, it definitely. There's so many

947
00:49:39,160 --> 00:49:43,120
Speaker 1: different layers, and then all the different layers need to

948
00:49:43,160 --> 00:49:46,239
Speaker 1: be waited a little bit differently. And then also when

949
00:49:46,280 --> 00:49:49,799
Speaker 1: you think about how the different layers influence each other. Um,

950
00:49:49,880 --> 00:49:54,319
Speaker 1: that is that you got it. It's tricky, man, I

951
00:49:54,320 --> 00:49:57,200
Speaker 1: mean it is. It is really really tricky, you know.

952
00:49:57,320 --> 00:50:00,680
Speaker 1: I mean, it's just it's just different as by phase

953
00:50:00,719 --> 00:50:03,720
Speaker 1: by phase. Um. You know, you look at that same

954
00:50:03,760 --> 00:50:07,239
Speaker 1: front that drops the temperature in the early season by

955
00:50:07,280 --> 00:50:12,200
Speaker 1: ten degrees, Say you were at average temperature for the

956
00:50:12,280 --> 00:50:16,440
Speaker 1: day and it drops at ten below major influencer. Okay, major,

957
00:50:16,480 --> 00:50:19,400
Speaker 1: because you seldom get a departure that far from average

958
00:50:19,480 --> 00:50:22,200
Speaker 1: during the early part of the season. Okay, go to

959
00:50:23,000 --> 00:50:29,120
Speaker 1: fast forward three months into December, middle part, same moon. Okay,

960
00:50:29,120 --> 00:50:31,320
Speaker 1: because month a month, the moon is gonna be roughly

961
00:50:31,360 --> 00:50:33,239
Speaker 1: doing the same thing. It's only twenty eight days apart

962
00:50:33,280 --> 00:50:35,480
Speaker 1: from full moon and full moon. All right, so you're

963
00:50:35,520 --> 00:50:38,600
Speaker 1: you're a little bit earlier in the month. Keen degree

964
00:50:38,680 --> 00:50:43,400
Speaker 1: drop a temperature from average high in December versus versus September.

965
00:50:44,200 --> 00:50:47,600
Speaker 1: Monstrous difference. You know what I'm saying. It doesn't have

966
00:50:47,880 --> 00:50:50,359
Speaker 1: nearly the influence that did in September that it did

967
00:50:50,600 --> 00:50:52,960
Speaker 1: that are nearly the influence in December that it did

968
00:50:53,000 --> 00:50:56,399
Speaker 1: in September. Now, if in December it's about to drop

969
00:50:56,440 --> 00:50:59,760
Speaker 1: thirty now we're talking, let's get going that that maybe

970
00:50:59,760 --> 00:51:02,160
Speaker 1: it may take that much of a drop to have

971
00:51:02,280 --> 00:51:04,680
Speaker 1: the same influence on the herd that you had a

972
00:51:04,760 --> 00:51:08,080
Speaker 1: ten degree drop in September. If that makes sense. Yeah, No,

973
00:51:08,239 --> 00:51:10,279
Speaker 1: that's a it's a very interesting point one I hadn't

974
00:51:10,280 --> 00:51:14,360
Speaker 1: really thought about before. Um, But it is all relative

975
00:51:14,400 --> 00:51:17,799
Speaker 1: to the season, and pressure is the same way, you know,

976
00:51:17,960 --> 00:51:21,680
Speaker 1: like high pressure in in December, what it takes to

977
00:51:21,719 --> 00:51:25,120
Speaker 1: make them move would explode their heads in September. It is.

978
00:51:26,040 --> 00:51:29,400
Speaker 1: It is unbelievable, the difference that the type pressure that

979
00:51:29,440 --> 00:51:32,160
Speaker 1: I look for in December is actually a suppressor in

980
00:51:32,160 --> 00:51:35,120
Speaker 1: in September, because it's relative to the season in the temperatures.

981
00:51:35,840 --> 00:51:39,360
Speaker 1: So there are peaks in pressure where it starts to

982
00:51:39,400 --> 00:51:42,120
Speaker 1: suppress movement. You know when it gets so high and

983
00:51:42,160 --> 00:51:44,880
Speaker 1: you've probably seen these days where it's like, oh my gosh,

984
00:51:44,880 --> 00:51:48,160
Speaker 1: we're we're approaching record pressure for this period. Why did

985
00:51:48,160 --> 00:51:51,000
Speaker 1: the Deermont not move today? You know that this is

986
00:51:51,080 --> 00:51:53,680
Speaker 1: high pressure. They're supposed to move, not necessarily there. You

987
00:51:53,719 --> 00:51:56,320
Speaker 1: can go above the peak in almost every one of

988
00:51:56,360 --> 00:51:58,960
Speaker 1: these weather influencers, and the APP picks those peaks up.

989
00:51:59,480 --> 00:52:02,440
Speaker 1: You know, how high wind is too high? How big

990
00:52:02,520 --> 00:52:06,200
Speaker 1: of a departure from normal is too much? How much

991
00:52:06,200 --> 00:52:09,480
Speaker 1: we'll put them into a state of shock you go into,

992
00:52:09,800 --> 00:52:13,280
Speaker 1: you go into in the early November when the ruts

993
00:52:13,280 --> 00:52:15,720
Speaker 1: just getting ready to kick, throw tenants in and snow

994
00:52:15,760 --> 00:52:18,640
Speaker 1: on them and depart from normal by forty degrees and

995
00:52:18,680 --> 00:52:20,799
Speaker 1: watch it shut every every year in the herd down.

996
00:52:21,160 --> 00:52:23,520
Speaker 1: Give me that same front in December and every one

997
00:52:23,560 --> 00:52:26,279
Speaker 1: of them is coming to a feed field, so it

998
00:52:27,320 --> 00:52:29,880
Speaker 1: varies how they react to it during the time of

999
00:52:29,920 --> 00:52:32,920
Speaker 1: the year and what their system is doing inside. Yeah,

1000
00:52:33,080 --> 00:52:36,719
Speaker 1: that's uh, that makes sense. I keep saying that, but

1001
00:52:36,800 --> 00:52:39,120
Speaker 1: it makes sense. Um, And you're you're going right where

1002
00:52:39,120 --> 00:52:42,359
Speaker 1: I was wanting to go, which is pressure. But very

1003
00:52:42,400 --> 00:52:46,200
Speaker 1: quickly before we do that, I have to follow up questions. Um.

1004
00:52:46,400 --> 00:52:50,000
Speaker 1: Number one, you're talking about the late season fronts and

1005
00:52:50,160 --> 00:52:52,720
Speaker 1: something that I've heard people mentioned a lot. I haven't

1006
00:52:52,760 --> 00:52:55,440
Speaker 1: personally seen. It is often here in Michigan or many

1007
00:52:55,440 --> 00:52:56,960
Speaker 1: of the places that I hunt, but I've heard a

1008
00:52:57,000 --> 00:52:59,560
Speaker 1: lot of people talk about that during the late season,

1009
00:52:59,680 --> 00:53:02,560
Speaker 1: not us the big cold front temperature drops, but also

1010
00:53:02,600 --> 00:53:06,239
Speaker 1: actually the opposite, so when the temperature increases to mild conditions,

1011
00:53:06,239 --> 00:53:09,919
Speaker 1: maybe in late December, some people say that's a positive thing. Um,

1012
00:53:10,239 --> 00:53:13,200
Speaker 1: is that something you've seen and what kind of specifics

1013
00:53:13,239 --> 00:53:14,880
Speaker 1: in that kind of way? Then would you need for

1014
00:53:14,920 --> 00:53:18,960
Speaker 1: that to be a positive thing? It absolutely, it absolutely is.

1015
00:53:19,040 --> 00:53:20,880
Speaker 1: And and at that time of the year, and really

1016
00:53:21,080 --> 00:53:23,640
Speaker 1: any time of the year, it comes down to energy conservation.

1017
00:53:24,239 --> 00:53:27,160
Speaker 1: And if you watch a deer, and just the example

1018
00:53:27,200 --> 00:53:29,640
Speaker 1: I gave you, the front part of the rut, major

1019
00:53:29,719 --> 00:53:32,440
Speaker 1: cold front snow, it will shock them and the and

1020
00:53:32,520 --> 00:53:34,600
Speaker 1: nothing in the herd will move. Well, they know what's

1021
00:53:34,640 --> 00:53:38,799
Speaker 1: about to happen, and they're conserving energy by betting and

1022
00:53:38,880 --> 00:53:43,520
Speaker 1: just not doing anything. Whereas if it's more life threatening

1023
00:53:43,600 --> 00:53:46,520
Speaker 1: later in the season, in other words, post rut, where

1024
00:53:46,520 --> 00:53:50,040
Speaker 1: they they've already expended their batteries low and they have

1025
00:53:50,120 --> 00:53:52,719
Speaker 1: to build that energy back up, that same front is

1026
00:53:52,760 --> 00:53:55,120
Speaker 1: gonna put them on the food source and it gets

1027
00:53:55,160 --> 00:53:59,399
Speaker 1: actually accentuated and better once the wind comes back out

1028
00:53:59,400 --> 00:54:02,440
Speaker 1: of the south, the clouds, the clouds clear out, you

1029
00:54:02,480 --> 00:54:05,319
Speaker 1: start having warming trends. Then all of a sudden they

1030
00:54:05,320 --> 00:54:09,120
Speaker 1: start moving better. However, that quickly subdues about the second

1031
00:54:09,239 --> 00:54:12,840
Speaker 1: or third day of the warmth. Okay, and then that's

1032
00:54:13,000 --> 00:54:15,280
Speaker 1: perfect because my next question was going to be about

1033
00:54:16,000 --> 00:54:18,399
Speaker 1: I never did get the specifics on how many days

1034
00:54:18,440 --> 00:54:20,520
Speaker 1: after a front. So you just mentioned after the second

1035
00:54:20,560 --> 00:54:22,720
Speaker 1: or third day after a warm front in late season,

1036
00:54:22,760 --> 00:54:24,759
Speaker 1: But what about the cold front that hits, you know,

1037
00:54:24,800 --> 00:54:26,440
Speaker 1: earlier in the year when we're really looking for those

1038
00:54:26,440 --> 00:54:30,399
Speaker 1: cold fronts, um how many days after that? Last? Find

1039
00:54:30,440 --> 00:54:34,560
Speaker 1: that answer? I find that answer very consistent throughout the season.

1040
00:54:34,600 --> 00:54:37,640
Speaker 1: It's one consistent thing that I've always seen. The first

1041
00:54:37,719 --> 00:54:40,520
Speaker 1: if you could have one day of north, three days

1042
00:54:40,560 --> 00:54:43,040
Speaker 1: of north, ten days of north, and they're all going

1043
00:54:43,080 --> 00:54:45,759
Speaker 1: to be decent movement, and then that first day of

1044
00:54:45,800 --> 00:54:49,360
Speaker 1: south is incredible. It's the first warm day. They almost

1045
00:54:49,400 --> 00:54:53,880
Speaker 1: always move the best that day after front, provided that

1046
00:54:53,960 --> 00:54:56,200
Speaker 1: you've got some high pressure coming in with it, that's

1047
00:54:56,239 --> 00:54:58,640
Speaker 1: generally the day that they move the best. It will

1048
00:54:58,840 --> 00:55:04,160
Speaker 1: gradually decrease days two, three, and four until it stabilizes,

1049
00:55:04,160 --> 00:55:05,600
Speaker 1: and then all of a sudden you're back into your

1050
00:55:05,600 --> 00:55:10,560
Speaker 1: next front. Okay, then let's day two of warmth is

1051
00:55:10,640 --> 00:55:13,920
Speaker 1: generally the worst movement you'll see in and around the front.

1052
00:55:13,960 --> 00:55:17,120
Speaker 1: The first warm day with the first south generally the best.

1053
00:55:17,400 --> 00:55:20,000
Speaker 1: Because I always say the first south. In all reality,

1054
00:55:20,760 --> 00:55:23,759
Speaker 1: that first warm day might be a west, if you

1055
00:55:23,800 --> 00:55:26,279
Speaker 1: know what I'm saying, and then the second warm day

1056
00:55:26,360 --> 00:55:28,960
Speaker 1: might be a south. Well, that second day, even though

1057
00:55:28,960 --> 00:55:31,719
Speaker 1: it's the first south, might not be as good as

1058
00:55:31,760 --> 00:55:34,160
Speaker 1: that first westerly day because it was and truly the

1059
00:55:34,200 --> 00:55:36,800
Speaker 1: first warm up day. So you kind of gotta I

1060
00:55:36,840 --> 00:55:38,880
Speaker 1: always say the first south, but in reality I should

1061
00:55:38,880 --> 00:55:42,560
Speaker 1: miss stand. I should restate that in the first warming day.

1062
00:55:42,960 --> 00:55:47,600
Speaker 1: Sometimes those are westerlies and not necessarily south. But that

1063
00:55:47,840 --> 00:55:50,880
Speaker 1: second day that it's warm, especially if it's two souths

1064
00:55:50,880 --> 00:55:53,160
Speaker 1: in a row, that second day of south is generally

1065
00:55:54,000 --> 00:55:57,600
Speaker 1: very slow and less. It's already into the next front

1066
00:55:57,719 --> 00:56:00,160
Speaker 1: and there's another one approaching. So it depends how are

1067
00:56:00,160 --> 00:56:02,759
Speaker 1: out the fronts are and all that good stuff. That's

1068
00:56:02,760 --> 00:56:05,759
Speaker 1: why the the app looks backwards and forwards as well

1069
00:56:05,920 --> 00:56:09,800
Speaker 1: before it makes a prediction. Yeah. Yeah, So I started tracking,

1070
00:56:10,920 --> 00:56:13,879
Speaker 1: you know all you know Holy Field, the whole story

1071
00:56:13,920 --> 00:56:15,560
Speaker 1: we've been talking about for years of that buck. And

1072
00:56:15,600 --> 00:56:19,200
Speaker 1: I started trying to track, you know, every different daylight

1073
00:56:19,239 --> 00:56:21,879
Speaker 1: sighting ahead of him, and every different daylight trail Cara

1074
00:56:21,920 --> 00:56:24,120
Speaker 1: picture I have of him, and then all these different

1075
00:56:24,160 --> 00:56:27,960
Speaker 1: factors and and trying to correlate something there. So I had, okay,

1076
00:56:28,000 --> 00:56:33,359
Speaker 1: sighting X, date, time of day, date or time of year, um,

1077
00:56:33,719 --> 00:56:36,480
Speaker 1: actual temperature and then I looked at the previous temperature.

1078
00:56:36,560 --> 00:56:39,160
Speaker 1: So was there a temperature difference of ten degrees or

1079
00:56:39,200 --> 00:56:41,520
Speaker 1: more over the last two days? Um? What was the moon?

1080
00:56:41,560 --> 00:56:43,520
Speaker 1: What was the wind direction? Was the change in wind direction?

1081
00:56:43,520 --> 00:56:45,520
Speaker 1: I tried to track all these things like you're talking about,

1082
00:56:46,120 --> 00:56:48,839
Speaker 1: and UM, it does get pretty crazy once you start

1083
00:56:48,880 --> 00:56:51,960
Speaker 1: factoring not just the current but also the changes but

1084
00:56:52,320 --> 00:56:55,440
Speaker 1: to all of these points. It really is in many

1085
00:56:55,440 --> 00:56:58,640
Speaker 1: of these cases, it's it's not what the temperatures today.

1086
00:56:58,719 --> 00:57:01,400
Speaker 1: It's not that the temperature seventy five. It's why it's

1087
00:57:01,200 --> 00:57:03,880
Speaker 1: if it's different, it's the delta. It's the change it

1088
00:57:03,960 --> 00:57:07,240
Speaker 1: seems to flip deer into gear. Right, it's the changes

1089
00:57:07,280 --> 00:57:11,160
Speaker 1: between these different conditions. Absolutely. That's why earlier when you

1090
00:57:11,400 --> 00:57:14,360
Speaker 1: heard me talk about pre sip, I talked about precip

1091
00:57:14,480 --> 00:57:17,480
Speaker 1: rate and then changing presip, I talked about wind speed,

1092
00:57:17,600 --> 00:57:20,400
Speaker 1: changing wind speed. So it is the delta as much

1093
00:57:20,440 --> 00:57:24,000
Speaker 1: as it is the actual condition. That's correct. Yeah, it's okay.

1094
00:57:24,160 --> 00:57:26,440
Speaker 1: Let's move to pressure. Can you give me, like the

1095
00:57:27,200 --> 00:57:29,880
Speaker 1: very top level cliff notes before we get into my

1096
00:57:29,960 --> 00:57:34,120
Speaker 1: specific questions on that. Absolutely sure, you know. I mean,

1097
00:57:34,560 --> 00:57:36,560
Speaker 1: as a general rule, the high the pressure, the better

1098
00:57:36,680 --> 00:57:39,680
Speaker 1: the deer movement. The lower of the pressure, um, the

1099
00:57:39,720 --> 00:57:43,160
Speaker 1: worst the deer movement. Uh. It depends though, how long

1100
00:57:43,200 --> 00:57:46,160
Speaker 1: you've been with high pressure and how long you've been

1101
00:57:46,200 --> 00:57:49,880
Speaker 1: with low pressure, and where it was and where it's going. So. Uh.

1102
00:57:50,000 --> 00:57:53,960
Speaker 1: Pressure is also relative to the season. So high pressure

1103
00:57:53,960 --> 00:57:55,840
Speaker 1: in the early part of the season is not considered

1104
00:57:55,920 --> 00:57:58,200
Speaker 1: high pressure during the latter part of the season, when

1105
00:57:58,200 --> 00:58:01,160
Speaker 1: that cool air really gets ushered in. I like stuff

1106
00:58:01,800 --> 00:58:04,520
Speaker 1: thirty point two to thirty point four in the late season,

1107
00:58:04,640 --> 00:58:07,920
Speaker 1: early season, I'm tickled to death. If it's twenty nine

1108
00:58:07,960 --> 00:58:11,200
Speaker 1: point nine five up to about thirty point one five,

1109
00:58:11,240 --> 00:58:13,240
Speaker 1: I consider that high pressure during the early part of

1110
00:58:13,240 --> 00:58:15,640
Speaker 1: the season. In fact, during the early point of the season,

1111
00:58:15,680 --> 00:58:18,480
Speaker 1: if it gets too high, it'll shut them down. Consequently,

1112
00:58:18,560 --> 00:58:21,040
Speaker 1: last year, we had a couple of days at bordered

1113
00:58:21,160 --> 00:58:24,000
Speaker 1: record pressure at thirty point seven point eight, and they

1114
00:58:24,040 --> 00:58:25,680
Speaker 1: did they didn't move well at all. They almost get

1115
00:58:25,680 --> 00:58:29,000
Speaker 1: a little lethargic on those extremely high pressure days where

1116
00:58:29,000 --> 00:58:31,960
Speaker 1: they move real slow and don't move move well at all.

1117
00:58:32,080 --> 00:58:34,560
Speaker 1: So there are sweet spots to pressure, just like there

1118
00:58:34,600 --> 00:58:37,920
Speaker 1: are sweet spots to temperature or anything else. Well, you

1119
00:58:38,040 --> 00:58:40,640
Speaker 1: just covered several of my specific questions. So you really

1120
00:58:40,680 --> 00:58:43,080
Speaker 1: knocked that one of the park mark, because I've had

1121
00:58:43,080 --> 00:58:45,080
Speaker 1: a lot of people ask, you know, as you just said,

1122
00:58:45,080 --> 00:58:47,520
Speaker 1: how bare metric pressure is relative to time of year,

1123
00:58:48,000 --> 00:58:50,160
Speaker 1: and a lot of people have been curious, Okay, what's

1124
00:58:50,200 --> 00:58:52,320
Speaker 1: what's a high pressure day in September versus a high

1125
00:58:52,360 --> 00:58:55,440
Speaker 1: pressure day November versus December. What you just said, so

1126
00:58:55,520 --> 00:59:00,480
Speaker 1: that's super helpful. Um, now what about this? Someone had

1127
00:59:00,520 --> 00:59:04,200
Speaker 1: asked if you would rather see a low pressure that's

1128
00:59:04,360 --> 00:59:08,640
Speaker 1: rising or a steady high pressure. So his example was

1129
00:59:09,480 --> 00:59:11,240
Speaker 1: which scenario would be better in your mind? Would it

1130
00:59:11,280 --> 00:59:15,040
Speaker 1: be like a twenty five but rising, So is that

1131
00:59:15,200 --> 00:59:17,520
Speaker 1: change what's most important? Or would you just like to

1132
00:59:17,520 --> 00:59:21,400
Speaker 1: have a higher thirty point two but steady for several days?

1133
00:59:21,440 --> 00:59:23,720
Speaker 1: And of course I know this is different depending on

1134
00:59:23,720 --> 00:59:27,480
Speaker 1: the time of year, but it is as I would answer,

1135
00:59:27,560 --> 00:59:29,680
Speaker 1: yes and yes, because at certain times of the year,

1136
00:59:30,120 --> 00:59:34,480
Speaker 1: the bouncing of pressure, especially during an afternoon sit I

1137
00:59:34,880 --> 00:59:38,280
Speaker 1: noticed because it accompanies as the fronts coming in. When

1138
00:59:38,320 --> 00:59:42,600
Speaker 1: the pressure bounces during a normal evening sit, uh, they

1139
00:59:42,680 --> 00:59:46,040
Speaker 1: generally moved quite well. In other words, it bounces from

1140
00:59:46,080 --> 00:59:47,960
Speaker 1: low and all of a sudden starts to rise while

1141
00:59:47,960 --> 00:59:50,000
Speaker 1: you're sitting there. It might be twenty nine point four

1142
00:59:50,520 --> 00:59:53,640
Speaker 1: and it bounces and starts heading back up the grid

1143
00:59:54,000 --> 00:59:58,240
Speaker 1: while you're sitting there, say four thirty five o'clock. Bam.

1144
00:59:58,280 --> 01:00:01,040
Speaker 1: That's generally a trigger that makes them move. When it's

1145
01:00:01,120 --> 01:00:06,160
Speaker 1: during a feeding pattern or feeding time of the year. Overall, though,

1146
01:00:06,480 --> 01:00:10,280
Speaker 1: I would take take the higher pressure versus that low pressure.

1147
01:00:10,280 --> 01:00:13,360
Speaker 1: It's tricky timing the low pressure. That's one thing I've found.

1148
01:00:13,560 --> 01:00:16,479
Speaker 1: They're not nearly as consistent on that low pressure side

1149
01:00:16,480 --> 01:00:18,680
Speaker 1: of things as they are with the high They generally

1150
01:00:18,680 --> 01:00:22,160
Speaker 1: move quite well on high pressures, regardless of situations. Do

1151
01:00:22,200 --> 01:00:25,120
Speaker 1: you have any theory, I mean, this is I think

1152
01:00:25,120 --> 01:00:26,560
Speaker 1: this is on guesswork here, but do you have any

1153
01:00:26,600 --> 01:00:30,640
Speaker 1: theory as to why that might why pressure influences deer

1154
01:00:30,680 --> 01:00:34,000
Speaker 1: movements so much? Like what the what the physiological impact

1155
01:00:34,240 --> 01:00:39,440
Speaker 1: is that's changing their behavior? You know, I'd say it.

1156
01:00:39,640 --> 01:00:42,280
Speaker 1: I don't know that it's necessarily the high pressure as

1157
01:00:42,360 --> 01:00:44,440
Speaker 1: much as the front that just passed that ushered that

1158
01:00:44,520 --> 01:00:47,400
Speaker 1: high pressure in if that makes sense. So, I don't

1159
01:00:47,440 --> 01:00:50,520
Speaker 1: know that it's the pressure itself as much as the

1160
01:00:50,520 --> 01:00:53,800
Speaker 1: condition that just happened. In other words, sometimes during the

1161
01:00:53,840 --> 01:00:56,760
Speaker 1: heat of the worst affront, they don't move quite as well,

1162
01:00:57,080 --> 01:00:59,600
Speaker 1: and then once the threat of the front passes, they

1163
01:00:59,640 --> 01:01:02,160
Speaker 1: all get out and start moving again, you know. So

1164
01:01:02,440 --> 01:01:05,120
Speaker 1: sometimes I think it's that more so than it is

1165
01:01:05,560 --> 01:01:09,200
Speaker 1: the actual pressure gradient itself, if that makes sense. Yeah, yeah,

1166
01:01:09,200 --> 01:01:11,800
Speaker 1: I follow you there. It's the very much of pressure

1167
01:01:11,880 --> 01:01:16,240
Speaker 1: is simply a symptom of this thing that's happening. It's

1168
01:01:16,240 --> 01:01:18,160
Speaker 1: an indicator we can look at, but it's just indicating

1169
01:01:18,200 --> 01:01:20,680
Speaker 1: that this front's moving through and all the things that

1170
01:01:20,720 --> 01:01:22,880
Speaker 1: come with that front are what's pushing dear to do

1171
01:01:22,920 --> 01:01:27,720
Speaker 1: what they do exactly. And you know, if you I

1172
01:01:27,760 --> 01:01:30,120
Speaker 1: always like I used to sell on the road, and

1173
01:01:30,280 --> 01:01:32,560
Speaker 1: I don't know if I told this anecdote back in

1174
01:01:32,840 --> 01:01:35,560
Speaker 1: fifteen or not, but I could just about tell you

1175
01:01:35,600 --> 01:01:38,760
Speaker 1: I sold Massio for ten years on the road and

1176
01:01:38,920 --> 01:01:42,320
Speaker 1: from eight nine and I could just about tell you

1177
01:01:42,400 --> 01:01:44,120
Speaker 1: whether I was going to write in order that day

1178
01:01:44,200 --> 01:01:46,720
Speaker 1: or not based on how the weather was, the mood

1179
01:01:46,760 --> 01:01:49,440
Speaker 1: people are in. Um. You know, they say, you know

1180
01:01:49,760 --> 01:01:52,520
Speaker 1: the greatest rainfalls where you sign the highest suicide right

1181
01:01:52,640 --> 01:01:55,480
Speaker 1: Rate's that type of thing. You go, you go to

1182
01:01:55,800 --> 01:01:57,600
Speaker 1: a place where it's sunny and a high pressure all

1183
01:01:57,640 --> 01:02:00,200
Speaker 1: the time. People are happy and they feel good good

1184
01:02:00,240 --> 01:02:02,400
Speaker 1: and and and when you live in the Midwest like

1185
01:02:02,440 --> 01:02:05,120
Speaker 1: we do, you get a lot of different fronts coming

1186
01:02:05,160 --> 01:02:07,640
Speaker 1: through and that low pressure you kind of feel a

1187
01:02:07,640 --> 01:02:09,960
Speaker 1: little groggy, little drag. You don't feel like getting out.

1188
01:02:09,960 --> 01:02:12,880
Speaker 1: And that's high pressure rushers in man smiling everybody's face.

1189
01:02:12,880 --> 01:02:16,480
Speaker 1: They're out there, act active and um, it's just I

1190
01:02:16,520 --> 01:02:18,560
Speaker 1: think you can feel the same thing that they feel

1191
01:02:18,600 --> 01:02:21,400
Speaker 1: inside your own body and your moods and how you

1192
01:02:21,440 --> 01:02:25,360
Speaker 1: feel and how you react to the weather. Yeah. So

1193
01:02:25,360 --> 01:02:29,800
Speaker 1: so what about this, How do you see pressure impacting

1194
01:02:29,920 --> 01:02:33,280
Speaker 1: wind or thermals or anything like that, and how does

1195
01:02:33,320 --> 01:02:36,400
Speaker 1: that then impact your decisions as far as predicting movement

1196
01:02:36,480 --> 01:02:39,520
Speaker 1: or predicting the quality of hunts if if at all well, Well,

1197
01:02:39,600 --> 01:02:42,080
Speaker 1: high high pressure makes everybody a better hunter, because the

1198
01:02:42,080 --> 01:02:46,360
Speaker 1: thermals are generally going up. Um, it makes everyone better,

1199
01:02:46,480 --> 01:02:49,720
Speaker 1: especially in the morning sits high pressure makes your stand

1200
01:02:49,800 --> 01:02:54,240
Speaker 1: choice better and you can get away with murder on

1201
01:02:54,280 --> 01:02:56,400
Speaker 1: those days. Those are the days that I go to

1202
01:02:56,760 --> 01:02:58,560
Speaker 1: that stand. You sit there, and you look and you go,

1203
01:02:58,640 --> 01:03:01,680
Speaker 1: I don't want my wind blowing any of these directions,

1204
01:03:01,680 --> 01:03:03,960
Speaker 1: but I have to sit, But I have to sit here.

1205
01:03:04,680 --> 01:03:07,919
Speaker 1: Those are the ones I reserve for the extreme high

1206
01:03:07,960 --> 01:03:11,360
Speaker 1: pressure mornings. Man. I will sneak in there, getting that

1207
01:03:11,440 --> 01:03:14,120
Speaker 1: stand and and hunt with the security of the fact

1208
01:03:14,200 --> 01:03:17,080
Speaker 1: that while that deer is probably still gonna catch me

1209
01:03:17,120 --> 01:03:19,560
Speaker 1: on the down wind side, he's not going to react

1210
01:03:19,800 --> 01:03:22,520
Speaker 1: in nearly as much of a negative way as he

1211
01:03:22,560 --> 01:03:25,600
Speaker 1: would have if the pressure was low. Man, it makes

1212
01:03:25,640 --> 01:03:28,160
Speaker 1: sense crush or better, it just it just makes you

1213
01:03:28,200 --> 01:03:32,800
Speaker 1: a better hunter when that pressure is rising and and high. Yeah,

1214
01:03:33,360 --> 01:03:35,800
Speaker 1: that's uh, that's a great thing to keep in mind.

1215
01:03:35,840 --> 01:03:38,320
Speaker 1: That again, something I hadn't thought about as much either.

1216
01:03:38,440 --> 01:03:40,480
Speaker 1: But if you have to take a swing for the fences,

1217
01:03:40,520 --> 01:03:42,720
Speaker 1: if you have to take that big risk, you might

1218
01:03:42,760 --> 01:03:44,919
Speaker 1: as well time it at the right not only good

1219
01:03:44,920 --> 01:03:47,320
Speaker 1: conditions for deer movement, but also good conditions for lower

1220
01:03:47,400 --> 01:03:52,680
Speaker 1: risk for you. Um all about risk management. Man, on

1221
01:03:52,760 --> 01:03:55,200
Speaker 1: low pressure, don't go to your best spots unless you've

1222
01:03:55,200 --> 01:03:59,320
Speaker 1: got a safe wind direction. Don't do it. Yeah, is

1223
01:03:59,360 --> 01:04:01,720
Speaker 1: there anything on this front? I feel like, I mean,

1224
01:04:01,760 --> 01:04:04,240
Speaker 1: you've been obviously studying this and following this and talking

1225
01:04:04,240 --> 01:04:06,200
Speaker 1: about this for a long time. But since we last

1226
01:04:06,200 --> 01:04:09,760
Speaker 1: talked in fifteen, has your thoughts on barre ment of

1227
01:04:09,760 --> 01:04:12,640
Speaker 1: pressure and the impacts or theories about any of this stuff.

1228
01:04:12,640 --> 01:04:14,720
Speaker 1: Has that changed at all in the last three and

1229
01:04:15,040 --> 01:04:18,080
Speaker 1: a half years or so. The thing that has changed

1230
01:04:18,200 --> 01:04:20,760
Speaker 1: is that I've seen it work in an adverse effect

1231
01:04:20,800 --> 01:04:23,040
Speaker 1: because we've had so much record pressure over the last

1232
01:04:23,080 --> 01:04:26,760
Speaker 1: few falls. And I've noticed it consistently that on those

1233
01:04:26,840 --> 01:04:32,040
Speaker 1: days where we are nearing record pressure for the the period,

1234
01:04:32,320 --> 01:04:34,840
Speaker 1: it is as much of a suppressors as it is

1235
01:04:34,840 --> 01:04:37,680
Speaker 1: an enhancer. So it has changed in that, and we

1236
01:04:37,680 --> 01:04:40,720
Speaker 1: we wrapped all of that into the into the app. Okay,

1237
01:04:40,920 --> 01:04:45,200
Speaker 1: interesting stuff. Now here's something I also I've also witnessed

1238
01:04:45,320 --> 01:04:48,640
Speaker 1: that bounced in the afternoon when when you're sitting there

1239
01:04:48,680 --> 01:04:51,840
Speaker 1: during a normal during a phase when afternoon movement is

1240
01:04:51,880 --> 01:04:55,720
Speaker 1: generally the best, and you catch about as severe bounds,

1241
01:04:55,840 --> 01:04:58,640
Speaker 1: especially the lord is with the higher it's going to

1242
01:04:59,120 --> 01:05:01,640
Speaker 1: when that bounce occurs when they're supposed to be moving

1243
01:05:01,680 --> 01:05:04,760
Speaker 1: anyway during a normal movement time last two hours if

1244
01:05:04,760 --> 01:05:07,560
Speaker 1: you will, or you know sunset minus thirty minutes or

1245
01:05:07,560 --> 01:05:10,800
Speaker 1: an hour, that is also a major influencer when you

1246
01:05:10,840 --> 01:05:12,640
Speaker 1: catch it, it's a good one that's wrapped into the

1247
01:05:12,640 --> 01:05:17,360
Speaker 1: app as well. I so, so I understand here you're saying,

1248
01:05:17,920 --> 01:05:20,120
Speaker 1: like an early season when evenings they're supposed to be

1249
01:05:20,120 --> 01:05:24,040
Speaker 1: great anyways, if you have that change happening right during

1250
01:05:24,040 --> 01:05:28,120
Speaker 1: the set, that's especially good. Well even in the later

1251
01:05:28,160 --> 01:05:31,240
Speaker 1: seasons too. I'm just saying when it's a thing where

1252
01:05:31,320 --> 01:05:34,800
Speaker 1: afternoon movement is really good, like the party's over feedback,

1253
01:05:35,040 --> 01:05:40,080
Speaker 1: green revisited, greener pastures, all of those where afternoons are optimum.

1254
01:05:40,200 --> 01:05:45,720
Speaker 1: Then when that sucker bounces during those afternoon phases killer

1255
01:05:46,160 --> 01:05:48,840
Speaker 1: interesting And I'm assuming it's only the bounce up right,

1256
01:05:48,920 --> 01:05:52,160
Speaker 1: A bounce A change down is going to be a negative,

1257
01:05:52,280 --> 01:05:57,120
Speaker 1: is that correct? Generally a negative? Generally negative. However, it

1258
01:05:57,200 --> 01:06:00,280
Speaker 1: can be a positives. If it's been so extreme eamly

1259
01:06:00,400 --> 01:06:02,760
Speaker 1: high that they didn't move the day before, then they're

1260
01:06:02,760 --> 01:06:05,120
Speaker 1: probably about to when it when it goes back into

1261
01:06:05,160 --> 01:06:06,960
Speaker 1: a level that's more of a sweet spot for them

1262
01:06:07,000 --> 01:06:09,720
Speaker 1: the next day. I have noticed that as well, and

1263
01:06:09,800 --> 01:06:13,360
Speaker 1: generally the other thing that I think they dislike about

1264
01:06:13,400 --> 01:06:16,480
Speaker 1: that really really high pressure. What's happening on those days?

1265
01:06:16,520 --> 01:06:20,200
Speaker 1: Almost no windspeed on those days, almost none. It'll be

1266
01:06:20,680 --> 01:06:23,320
Speaker 1: like three or four mile an hour or are less

1267
01:06:23,400 --> 01:06:26,720
Speaker 1: the whole day, and they just I don't know why,

1268
01:06:26,760 --> 01:06:28,600
Speaker 1: they get whipped out with low wind speeds. Then all

1269
01:06:28,600 --> 01:06:30,400
Speaker 1: of a sudden next day it drops down a little bit,

1270
01:06:30,560 --> 01:06:32,920
Speaker 1: windspeed kicks up. Boom every day in the herds on

1271
01:06:32,960 --> 01:06:35,960
Speaker 1: their feet again. It's it's it's crazy to watch them

1272
01:06:35,960 --> 01:06:38,080
Speaker 1: on it. They're fascinating creatures when you watch them on

1273
01:06:38,120 --> 01:06:42,480
Speaker 1: a day in and day out basis literally fascinating. Okay,

1274
01:06:42,520 --> 01:06:45,560
Speaker 1: let's take one last quick break to thank our partners

1275
01:06:45,640 --> 01:06:48,720
Speaker 1: at White Tail Properties for the support of this podcast

1276
01:06:48,800 --> 01:06:54,040
Speaker 1: and continuing our land Beat video recommendations series. As I

1277
01:06:54,160 --> 01:06:56,920
Speaker 1: mentioned the past, White Tailed Properties got this great YouTube

1278
01:06:56,960 --> 01:06:59,480
Speaker 1: series going on right now called land Beat. I want

1279
01:06:59,480 --> 01:07:02,120
Speaker 1: to give you zip on their latest version of that.

1280
01:07:02,240 --> 01:07:05,320
Speaker 1: They've got another one focused on fall food plots and

1281
01:07:05,360 --> 01:07:09,160
Speaker 1: Tom James really interesting and great resource when it comes

1282
01:07:09,200 --> 01:07:12,440
Speaker 1: to habitat management. And this one, Tom James talks about

1283
01:07:12,760 --> 01:07:15,840
Speaker 1: fall food plots and what his favorite seed combinations are

1284
01:07:16,000 --> 01:07:19,160
Speaker 1: for that kind of annual fall hunting food plot, and

1285
01:07:19,160 --> 01:07:22,560
Speaker 1: he talks about layering different types of forge in there.

1286
01:07:22,560 --> 01:07:24,920
Speaker 1: So you've got attraction from the early season all the

1287
01:07:24,960 --> 01:07:26,600
Speaker 1: way through the late So check this one out. It's

1288
01:07:26,680 --> 01:07:30,640
Speaker 1: quick video. It's called Fall Food Plots Slash Seed Combinations

1289
01:07:30,640 --> 01:07:34,200
Speaker 1: for Incredible Attractiveness. Came out not too long ago, so

1290
01:07:34,320 --> 01:07:38,480
Speaker 1: check that out on the White Tailed Properties YouTube channel. Yeah,

1291
01:07:38,600 --> 01:07:41,080
Speaker 1: so let's just go right there then, since you brought

1292
01:07:41,080 --> 01:07:43,000
Speaker 1: it up, can you give us the cliff notes on

1293
01:07:43,000 --> 01:07:45,920
Speaker 1: on wind speed and direction. I guess how you think

1294
01:07:46,000 --> 01:07:48,160
Speaker 1: that influences things. And then I do have a couple

1295
01:07:48,160 --> 01:07:52,880
Speaker 1: of follow ups on that already. Well, I mean again

1296
01:07:52,960 --> 01:07:55,840
Speaker 1: it's the same answer to keep giving it various per phase.

1297
01:07:56,680 --> 01:07:58,720
Speaker 1: But as a general rule, when the winds out of

1298
01:07:58,720 --> 01:08:01,439
Speaker 1: the north, they they've general are gonna move quite well.

1299
01:08:01,760 --> 01:08:04,520
Speaker 1: And then that first day out of the south, I like,

1300
01:08:04,680 --> 01:08:08,560
Speaker 1: I think there are definite wind speed sweet spots. Though

1301
01:08:09,480 --> 01:08:12,280
Speaker 1: when that wind is below about seven or eight mile

1302
01:08:12,320 --> 01:08:16,040
Speaker 1: an hour, regardless of direction, they move less than if

1303
01:08:16,080 --> 01:08:20,479
Speaker 1: it is between about eight and fifteen. Eight to fifteen

1304
01:08:20,560 --> 01:08:23,160
Speaker 1: or eight to eighteen. Somewhere in that range to me

1305
01:08:23,520 --> 01:08:26,919
Speaker 1: is the wind sweet spot. As you get to twenty

1306
01:08:26,960 --> 01:08:29,600
Speaker 1: and then above that a little bit it starts to

1307
01:08:29,640 --> 01:08:31,559
Speaker 1: suppress it just a little bit, or it may not

1308
01:08:31,640 --> 01:08:34,519
Speaker 1: suppress it, but it certainly makes them more nervous. There

1309
01:08:34,600 --> 01:08:36,839
Speaker 1: is a sweet spot for wind in terms of overall

1310
01:08:36,880 --> 01:08:39,880
Speaker 1: movement and in terms of overall relaxation of the animal.

1311
01:08:40,360 --> 01:08:43,040
Speaker 1: There is something about a twelve to fourteen mile in

1312
01:08:43,040 --> 01:08:45,240
Speaker 1: our wind where every deer is relaxed. They got their

1313
01:08:45,240 --> 01:08:47,840
Speaker 1: head down feeding and they're not sitting there wigged out.

1314
01:08:47,960 --> 01:08:51,160
Speaker 1: It's it's crazy. It's almost like turning a sound machine

1315
01:08:51,160 --> 01:08:53,559
Speaker 1: on for a baby at all, sleep like like a baby.

1316
01:08:53,560 --> 01:08:55,640
Speaker 1: With those deer will come out and see feed like

1317
01:08:55,680 --> 01:08:58,880
Speaker 1: they're supposed to. They're just not nearly as nervous in

1318
01:08:58,920 --> 01:09:01,120
Speaker 1: a mid range wind as they are in a high

1319
01:09:01,200 --> 01:09:03,559
Speaker 1: wind or a low wind some of the worst days

1320
01:09:03,640 --> 01:09:06,360
Speaker 1: or low wind days, because they hear everything. You know,

1321
01:09:06,680 --> 01:09:08,840
Speaker 1: no wind, look out every dear and the plot is

1322
01:09:08,840 --> 01:09:10,719
Speaker 1: going to have her head up all night long. It's

1323
01:09:10,720 --> 01:09:14,240
Speaker 1: it's amazing. So that brings me to my next question

1324
01:09:14,240 --> 01:09:16,560
Speaker 1: then on on wind speed. When you have those no

1325
01:09:16,760 --> 01:09:19,559
Speaker 1: wind days are very very light wind days, can you

1326
01:09:19,600 --> 01:09:23,759
Speaker 1: talk about the impacts that has not just on dear movement,

1327
01:09:23,800 --> 01:09:26,960
Speaker 1: but then also on your scent. Can you elaborate a

1328
01:09:26,960 --> 01:09:29,240
Speaker 1: little bit on what happens and what how that might

1329
01:09:29,280 --> 01:09:33,759
Speaker 1: influence a hunt. Negatively, it's if you're in a high

1330
01:09:33,840 --> 01:09:36,040
Speaker 1: ridge and it's a morning and it's high pressure, that

1331
01:09:36,120 --> 01:09:38,719
Speaker 1: helps you. But where it really hurts you if there's

1332
01:09:38,760 --> 01:09:41,479
Speaker 1: no wind in your lowan topography of an afternoon sit,

1333
01:09:41,880 --> 01:09:45,040
Speaker 1: you've got some things working against you there. Number one,

1334
01:09:45,200 --> 01:09:47,080
Speaker 1: when you first get to your spot, if you're sitting

1335
01:09:47,120 --> 01:09:49,960
Speaker 1: there three the last three hours of daylight, say, your

1336
01:09:49,960 --> 01:09:52,559
Speaker 1: pressure is gonna be rising. You don't have enough wind

1337
01:09:52,560 --> 01:09:55,160
Speaker 1: speed to take your scent to a defined spot, so

1338
01:09:55,200 --> 01:09:58,120
Speaker 1: it's gonna be variable, especially if you're low end topography,

1339
01:09:58,240 --> 01:10:01,320
Speaker 1: so you're literally scenting an every direction that you can.

1340
01:10:01,960 --> 01:10:05,040
Speaker 1: Then on those high pressure days with low wind, when

1341
01:10:05,040 --> 01:10:07,919
Speaker 1: that thermal sets in, that's one of your your biggest

1342
01:10:08,240 --> 01:10:11,960
Speaker 1: thermal days because it goes from a very warm trend boom.

1343
01:10:12,160 --> 01:10:14,400
Speaker 1: Those thermals hit and take your scent and push it

1344
01:10:14,479 --> 01:10:16,519
Speaker 1: straight to the ground, and it'll be doing it almost

1345
01:10:16,720 --> 01:10:20,640
Speaker 1: three degree radius around your tree. It's why we have

1346
01:10:20,760 --> 01:10:23,960
Speaker 1: been so successful on those days. It's why you see

1347
01:10:24,040 --> 01:10:26,240
Speaker 1: us hunting out of blinds when the wind is not blowing.

1348
01:10:26,280 --> 01:10:27,960
Speaker 1: So often you see us not a blind a lot.

1349
01:10:28,200 --> 01:10:31,280
Speaker 1: But on those days, I'm generally low in topography and

1350
01:10:31,320 --> 01:10:33,719
Speaker 1: I'm somewhere in a scent proof blind and every window

1351
01:10:33,760 --> 01:10:36,200
Speaker 1: is shut, even if they're fogging up. I have to

1352
01:10:36,280 --> 01:10:39,320
Speaker 1: keep my scent contained inside that that blind, and it

1353
01:10:39,439 --> 01:10:42,599
Speaker 1: it makes a huge difference to your over overall success.

1354
01:10:42,920 --> 01:10:45,800
Speaker 1: I've been blown and boogered and spooked and seen and

1355
01:10:45,880 --> 01:10:48,639
Speaker 1: heard by so many deer on low wind days. It's

1356
01:10:48,760 --> 01:10:51,520
Speaker 1: it's very tough to get one killed. With low winds.

1357
01:10:51,560 --> 01:10:53,240
Speaker 1: So what about if we if we're in a scenario

1358
01:10:53,320 --> 01:10:55,240
Speaker 1: we don't have a good black splind that can kind

1359
01:10:55,240 --> 01:10:58,280
Speaker 1: of seal in things like that. Um, what would be

1360
01:10:58,320 --> 01:11:03,160
Speaker 1: like the safest bet ground ground? Get it down as

1361
01:11:03,200 --> 01:11:04,960
Speaker 1: close to the ground as you can get inside of

1362
01:11:04,960 --> 01:11:08,320
Speaker 1: a ground blind. You can always get that scenario set

1363
01:11:08,400 --> 01:11:13,000
Speaker 1: up for yourself. Get low and get in that blind

1364
01:11:13,560 --> 01:11:15,920
Speaker 1: and sit there and don't freaking move because they're gonna

1365
01:11:15,960 --> 01:11:19,479
Speaker 1: catch you. What's the threshold there? What's like where do

1366
01:11:19,520 --> 01:11:23,719
Speaker 1: you draw the line as too dangerous? Low? Seven and blow?

1367
01:11:23,880 --> 01:11:28,360
Speaker 1: I hate it. Predicted seven and blow is really a booger,

1368
01:11:28,840 --> 01:11:33,080
Speaker 1: especially if you're five and below almost it's almost impossible

1369
01:11:33,120 --> 01:11:35,240
Speaker 1: to kill them those days. Plus they're going to react

1370
01:11:35,240 --> 01:11:37,080
Speaker 1: to the sound of your bow. And I'm talking archery

1371
01:11:37,080 --> 01:11:39,760
Speaker 1: down I mean guns a different scenario obviously, But if

1372
01:11:39,760 --> 01:11:41,880
Speaker 1: you're talking with a bow and you're trying to kill

1373
01:11:41,920 --> 01:11:45,080
Speaker 1: a deer, that's when you do it. Pat yourself on

1374
01:11:45,120 --> 01:11:48,960
Speaker 1: the back because it's hard to do. Now, I've got

1375
01:11:49,000 --> 01:11:51,479
Speaker 1: a scenario I want to lay out for you related

1376
01:11:51,520 --> 01:11:54,519
Speaker 1: to this kind of but the opposite. Um, And I'm

1377
01:11:54,560 --> 01:11:55,960
Speaker 1: curious to hear if you think I made the right

1378
01:11:55,960 --> 01:11:59,000
Speaker 1: decision of the wrong decision, because I was put into

1379
01:11:59,040 --> 01:12:00,880
Speaker 1: a situation where I to think through all these things

1380
01:12:00,920 --> 01:12:02,719
Speaker 1: we're talking about. I was looking at all these different

1381
01:12:02,760 --> 01:12:05,320
Speaker 1: factors to try to determine the first day to go

1382
01:12:05,400 --> 01:12:07,920
Speaker 1: hunt holy Field last year, and I wanted to wait

1383
01:12:08,160 --> 01:12:11,760
Speaker 1: and strike for the first time with the best possible situation.

1384
01:12:12,520 --> 01:12:15,280
Speaker 1: Um because he's very impected by pressure, I thought, I'm

1385
01:12:15,280 --> 01:12:17,360
Speaker 1: just gonna have a handful of opportunities, probably to get

1386
01:12:17,360 --> 01:12:20,519
Speaker 1: a stab at him. So coming to the season, I

1387
01:12:21,240 --> 01:12:22,960
Speaker 1: want to take I take what I said for a

1388
01:12:23,000 --> 01:12:25,280
Speaker 1: second back. I did hunt opening day, but then after

1389
01:12:25,360 --> 01:12:26,880
Speaker 1: opening Day I said, Okay, I'm not going to go

1390
01:12:26,920 --> 01:12:29,360
Speaker 1: back in until all the stars aligned. One of the

1391
01:12:29,400 --> 01:12:31,360
Speaker 1: things I was using was the fact that I had

1392
01:12:31,520 --> 01:12:36,080
Speaker 1: historical encounters with him the past two years. One year

1393
01:12:36,160 --> 01:12:39,320
Speaker 1: was on the twenty four one years on and so

1394
01:12:39,400 --> 01:12:41,880
Speaker 1: I thought, Okay, in two thousand seventeen, I'm gonna wait

1395
01:12:41,920 --> 01:12:44,000
Speaker 1: till that time frame because that's when he starts becoming

1396
01:12:44,080 --> 01:12:46,599
Speaker 1: daylight active. Based off these two years of histories, I thought,

1397
01:12:46,640 --> 01:12:51,080
Speaker 1: somewhere around give or take is what I'm gonna start hunting.

1398
01:12:51,080 --> 01:12:52,240
Speaker 1: So I had that in the back of my mind

1399
01:12:52,640 --> 01:12:55,120
Speaker 1: and then I thought, okay, I want that time frame,

1400
01:12:55,200 --> 01:12:59,680
Speaker 1: assuming good conditions are present. So we get to like

1401
01:12:59,720 --> 01:13:04,240
Speaker 1: the twenty one October, and as you probably remember, there's

1402
01:13:04,280 --> 01:13:07,280
Speaker 1: a big cold front rolling through, and I thought, oh

1403
01:13:07,320 --> 01:13:09,720
Speaker 1: my gosh, the deer hunting gods have shined on me.

1404
01:13:09,840 --> 01:13:12,800
Speaker 1: This is perfect. His historical patterns line up with like

1405
01:13:12,840 --> 01:13:16,040
Speaker 1: the first really great cold front of October. This is

1406
01:13:16,040 --> 01:13:17,439
Speaker 1: gonna be dying to win. So I said, all right,

1407
01:13:18,200 --> 01:13:21,000
Speaker 1: I'm hunting. It was gonna be like fifteen degrees cooler

1408
01:13:21,080 --> 01:13:24,439
Speaker 1: than the day before. Um, I had a right wind

1409
01:13:24,479 --> 01:13:26,960
Speaker 1: direction to hunt, an area where I thought he'd be,

1410
01:13:27,680 --> 01:13:29,040
Speaker 1: So I kind of had set in my mind, I'm

1411
01:13:29,040 --> 01:13:30,479
Speaker 1: gonna do it. That's the day. I'm gonna go in

1412
01:13:30,520 --> 01:13:35,439
Speaker 1: that night. But when I got to that day, now,

1413
01:13:35,479 --> 01:13:37,200
Speaker 1: all of a sudden, it was really windy. It was

1414
01:13:37,280 --> 01:13:39,320
Speaker 1: much windier than what they've been showing over the past

1415
01:13:39,360 --> 01:13:41,800
Speaker 1: couple of days. And I found myself it was like noon,

1416
01:13:42,360 --> 01:13:44,960
Speaker 1: and I'm sitting here going back and forth in my head.

1417
01:13:45,479 --> 01:13:49,719
Speaker 1: Do I hunt because the cold front past, the winds,

1418
01:13:49,760 --> 01:13:52,120
Speaker 1: the right direction, I need the time of years, right,

1419
01:13:52,200 --> 01:13:54,360
Speaker 1: you know, we've got the pre up starting to ramp up.

1420
01:13:54,760 --> 01:13:57,240
Speaker 1: History tells me that he starts moving right around. Now

1421
01:13:57,320 --> 01:13:59,599
Speaker 1: I can be right in that area, all those things

1422
01:13:59,640 --> 01:14:02,559
Speaker 1: that go, go, go, go go. But then I see

1423
01:14:02,720 --> 01:14:06,160
Speaker 1: the wind speeds at like twenty miles an hour one hour,

1424
01:14:07,439 --> 01:14:10,400
Speaker 1: And is that enough of a negative impact to say, no,

1425
01:14:10,560 --> 01:14:14,160
Speaker 1: negate everything else, because that's that's gonna hurt things. And

1426
01:14:14,200 --> 01:14:17,200
Speaker 1: again I'm thinking, I really need this first set to

1427
01:14:17,360 --> 01:14:21,200
Speaker 1: be great, is what I was thinking in my head. Well,

1428
01:14:21,320 --> 01:14:27,000
Speaker 1: I would have unted him out, you would, I would? Yes? Okay,

1429
01:14:27,040 --> 01:14:29,519
Speaker 1: Well then I feel less bad because I did go

1430
01:14:29,680 --> 01:14:34,439
Speaker 1: hunt him, but I well, I went and hunted. I

1431
01:14:34,520 --> 01:14:36,800
Speaker 1: got into the tree and the winds were worse than

1432
01:14:36,840 --> 01:14:41,200
Speaker 1: even the weather had said and probably being like something

1433
01:14:41,280 --> 01:14:43,200
Speaker 1: like that. And then I felt like it was swirling

1434
01:14:43,240 --> 01:14:45,559
Speaker 1: a little bit. It seemed like it was such a

1435
01:14:45,680 --> 01:14:48,400
Speaker 1: strong wind. It seemed to be blowing off direction and

1436
01:14:48,560 --> 01:14:50,559
Speaker 1: pitching in towards the bedding. So I was in the

1437
01:14:50,600 --> 01:14:53,439
Speaker 1: tree for ten fifteen minutes and then I said this,

1438
01:14:53,760 --> 01:14:55,840
Speaker 1: I'm screwing things up, and I actually climbed out and

1439
01:14:55,960 --> 01:14:59,040
Speaker 1: left and just didn't want to screw up anymore. So

1440
01:14:59,040 --> 01:15:02,120
Speaker 1: so you're saying, though my still gut reaction was okay,

1441
01:15:02,160 --> 01:15:05,040
Speaker 1: it wasn't stupid to go in there, so was your

1442
01:15:05,040 --> 01:15:07,839
Speaker 1: secondary reaction. I would have left the moment it kicked backwards,

1443
01:15:08,000 --> 01:15:12,639
Speaker 1: I would have I would have ran. Yeah, I basically did. Yeah,

1444
01:15:12,720 --> 01:15:14,320
Speaker 1: I would have you know the mote, the moment, and

1445
01:15:14,360 --> 01:15:15,920
Speaker 1: you know, if you feel like you know where deer's

1446
01:15:15,960 --> 01:15:18,960
Speaker 1: betting areas that and you go in and what you're

1447
01:15:18,960 --> 01:15:22,960
Speaker 1: dealing with there in that part of the season, the

1448
01:15:22,960 --> 01:15:26,360
Speaker 1: the heavy foliage acts like topography. So in other words,

1449
01:15:26,360 --> 01:15:28,439
Speaker 1: the wind can actually kick over the tree tops and

1450
01:15:28,479 --> 01:15:30,840
Speaker 1: then turn around and kick back because it's it's kicking

1451
01:15:30,880 --> 01:15:33,080
Speaker 1: off of a blocker, which is the full You know,

1452
01:15:33,200 --> 01:15:37,280
Speaker 1: if that would have been November, leaves are gone, the

1453
01:15:37,280 --> 01:15:39,599
Speaker 1: wind might have been consistent for you in that same spot.

1454
01:15:39,760 --> 01:15:43,040
Speaker 1: You know. That's why I wind scout a lot of places.

1455
01:15:43,080 --> 01:15:46,120
Speaker 1: Are I certainly when those things happened to me under

1456
01:15:46,120 --> 01:15:48,880
Speaker 1: those conditions, and I write that down somewhere in my mind,

1457
01:15:48,880 --> 01:15:51,240
Speaker 1: are on a piece of paper. I can't hunt here

1458
01:15:51,280 --> 01:15:54,080
Speaker 1: on this speed and ever again during this time brand

1459
01:15:54,400 --> 01:15:56,960
Speaker 1: you know, so you'll you'll learn that. And you only

1460
01:15:57,000 --> 01:15:59,719
Speaker 1: did it because said earlier in the podcast, you learned

1461
01:15:59,720 --> 01:16:01,599
Speaker 1: by I can your mistakes. You gotta go in there

1462
01:16:01,600 --> 01:16:03,559
Speaker 1: and get backed around a little bit and go, WHOA,

1463
01:16:03,960 --> 01:16:07,000
Speaker 1: that's bad. The wind kick back, and more often than not,

1464
01:16:07,240 --> 01:16:10,519
Speaker 1: I think people most people would have just went there

1465
01:16:10,520 --> 01:16:13,400
Speaker 1: and sat to hold hold old damn. He said, Hell

1466
01:16:13,479 --> 01:16:16,439
Speaker 1: with it, I'm here. You know that's bad. Don't miss

1467
01:16:16,439 --> 01:16:20,080
Speaker 1: mistakes like don't let a dear know that you're hunting them.

1468
01:16:20,120 --> 01:16:22,360
Speaker 1: And if you know that your wind is blowing into

1469
01:16:22,400 --> 01:16:26,320
Speaker 1: a betting area, you're making a dumb decision. Yeah. So

1470
01:16:26,320 --> 01:16:30,479
Speaker 1: so on that front, I sometimes have found earlier. I'm

1471
01:16:30,600 --> 01:16:33,040
Speaker 1: I'm making better decisions now, as we just talked about.

1472
01:16:33,040 --> 01:16:35,599
Speaker 1: But one of my excuses used to be if I'm

1473
01:16:35,640 --> 01:16:38,360
Speaker 1: in a tree stand and then like the wind seems

1474
01:16:38,400 --> 01:16:40,080
Speaker 1: to switch like that, or I noticed that the wind

1475
01:16:40,080 --> 01:16:41,800
Speaker 1: has switched and it seems to be blowing into a

1476
01:16:41,840 --> 01:16:44,559
Speaker 1: betting area, and I'm like, oh ship, it's blowing there.

1477
01:16:44,560 --> 01:16:47,920
Speaker 1: It's screwing things up. My I used to say, well,

1478
01:16:48,000 --> 01:16:50,000
Speaker 1: you've already done the damage. It's already been blown there

1479
01:16:50,000 --> 01:16:52,559
Speaker 1: for a few minutes. It's it's any deer that was

1480
01:16:52,600 --> 01:16:55,200
Speaker 1: there is gone or smart to what's going on now.

1481
01:16:55,280 --> 01:16:57,160
Speaker 1: You might as well just set it out because maybe

1482
01:16:57,200 --> 01:16:59,639
Speaker 1: something will come from one of these other directions. Um,

1483
01:17:00,000 --> 01:17:02,760
Speaker 1: that's what I used to do. Is that? Is it

1484
01:17:02,800 --> 01:17:05,120
Speaker 1: good that I'm not doing that anymore? Or is there

1485
01:17:05,200 --> 01:17:06,960
Speaker 1: something to be said about? Yeah? There, it's like a

1486
01:17:07,000 --> 01:17:09,280
Speaker 1: sunk cost. You might as well see what happens on

1487
01:17:09,320 --> 01:17:13,479
Speaker 1: the other side. Uh, compends how much time you have,

1488
01:17:13,640 --> 01:17:16,559
Speaker 1: you know. Um, for me, I'm down and I'm out,

1489
01:17:16,600 --> 01:17:18,519
Speaker 1: and I'm somewhere where the winds safe or UM in

1490
01:17:18,600 --> 01:17:20,800
Speaker 1: my truck up on a doing point, just to watch

1491
01:17:20,800 --> 01:17:24,760
Speaker 1: what happens. You know. UM, I don't like putting my

1492
01:17:24,800 --> 01:17:27,080
Speaker 1: wind over somewhere that I do not want it to be,

1493
01:17:27,520 --> 01:17:30,920
Speaker 1: and I avoid it at all costs and eliminate it

1494
01:17:31,120 --> 01:17:34,679
Speaker 1: any chance I get. I do not like that. It's safe.

1495
01:17:34,680 --> 01:17:39,839
Speaker 1: Wind directions cannot be overstated. Having one for every single

1496
01:17:40,360 --> 01:17:47,000
Speaker 1: wind condition, speed, and time of year is very very important. Um.

1497
01:17:47,040 --> 01:17:49,120
Speaker 1: That's why I think, no matter how many spots you got,

1498
01:17:49,160 --> 01:17:52,520
Speaker 1: you still don't have enough. Go find a good condition

1499
01:17:52,600 --> 01:17:54,840
Speaker 1: that you can hunt in where you have a safe

1500
01:17:54,840 --> 01:17:56,479
Speaker 1: wind direction, because at the end of the day, if

1501
01:17:56,479 --> 01:17:59,240
Speaker 1: you smell you if you're bow hunting, nine times out

1502
01:17:59,280 --> 01:18:05,920
Speaker 1: of ten, it's over. Yeah, gears and and and you

1503
01:18:06,000 --> 01:18:08,800
Speaker 1: don't see it happened like that's what's wrong with it? Like,

1504
01:18:08,880 --> 01:18:11,960
Speaker 1: that's how why it's hard to learn. You don't see

1505
01:18:11,960 --> 01:18:14,800
Speaker 1: the deer more often than on if you're in thick cover,

1506
01:18:15,040 --> 01:18:20,920
Speaker 1: that's five yards down wind reacting to your you're but

1507
01:18:21,240 --> 01:18:23,720
Speaker 1: sitting there hunting on the wrong wind, you don't see it.

1508
01:18:23,760 --> 01:18:28,839
Speaker 1: So therefore I didn't hear anything. Bro. Yeah, well, five

1509
01:18:28,960 --> 01:18:33,240
Speaker 1: different gear down wind anywhere from three D eight hundred

1510
01:18:33,400 --> 01:18:36,959
Speaker 1: all smells you, and all took a change in direction,

1511
01:18:37,160 --> 01:18:40,680
Speaker 1: and all will not forget your position like they are

1512
01:18:40,840 --> 01:18:46,240
Speaker 1: masters at remembering um being scared. In other words, human

1513
01:18:46,320 --> 01:18:49,519
Speaker 1: scent scares them. When you scared deer, he never forgets

1514
01:18:49,520 --> 01:18:51,600
Speaker 1: it in imprints in his mind, and he will not

1515
01:18:51,800 --> 01:18:54,840
Speaker 1: forgot where he got scared, how he got scared, and

1516
01:18:54,880 --> 01:18:57,760
Speaker 1: he will avoid that situation in the future. You have

1517
01:18:57,920 --> 01:19:00,160
Speaker 1: to make sure that you're not scaring that deer and

1518
01:19:00,240 --> 01:19:02,640
Speaker 1: making him afraid. Think of the thing. Think of some

1519
01:19:02,720 --> 01:19:04,920
Speaker 1: of the deepest memories in your mind. When you were

1520
01:19:04,920 --> 01:19:07,559
Speaker 1: a kid, If something scared to live and crap out

1521
01:19:07,560 --> 01:19:09,679
Speaker 1: of you, you never forget it the rest of your life.

1522
01:19:09,720 --> 01:19:11,960
Speaker 1: Dear the same way. Yeah, you know, when I was

1523
01:19:12,040 --> 01:19:14,200
Speaker 1: two or three, I put my hand on a burning

1524
01:19:14,240 --> 01:19:17,880
Speaker 1: grill and I've never done it since and you won't

1525
01:19:17,920 --> 01:19:21,759
Speaker 1: ever again, or just anything, any little thing that scares

1526
01:19:21,800 --> 01:19:24,519
Speaker 1: you when you get that adrenaline bump where you're scared,

1527
01:19:24,600 --> 01:19:28,120
Speaker 1: truly scared, you never forget that, and dear, don't forget

1528
01:19:28,160 --> 01:19:32,400
Speaker 1: it either. That's why they get so hard to kill

1529
01:19:32,840 --> 01:19:37,400
Speaker 1: in pressured areas. So two things that I've wondered about

1530
01:19:37,439 --> 01:19:40,320
Speaker 1: often on on this topic that you just mentioned there,

1531
01:19:40,360 --> 01:19:42,080
Speaker 1: and you you kind of throw some numbers, but I

1532
01:19:42,080 --> 01:19:44,200
Speaker 1: want to pinion down on a couple of things here.

1533
01:19:44,680 --> 01:19:49,040
Speaker 1: Um wind distance so something. So oftentimes I've wondered, Okay,

1534
01:19:49,080 --> 01:19:51,360
Speaker 1: how far away do I need to be worried if

1535
01:19:51,400 --> 01:19:53,880
Speaker 1: I'm crossing a field and there's a betting area way

1536
01:19:54,000 --> 01:19:58,080
Speaker 1: down wind, but it's it's two yards or seven hundred yards,

1537
01:19:58,160 --> 01:20:00,120
Speaker 1: or what's the distance that you think it's okay a

1538
01:20:00,560 --> 01:20:03,439
Speaker 1: to be from a deer bedding area or where you

1539
01:20:03,439 --> 01:20:05,800
Speaker 1: where every maybe more if it's the opposites at night

1540
01:20:05,920 --> 01:20:08,000
Speaker 1: in the feeding whatever might be. What's the distance that

1541
01:20:08,000 --> 01:20:10,200
Speaker 1: you think we need to be concerned about the threshold there?

1542
01:20:10,680 --> 01:20:17,080
Speaker 1: And then are there any kind of clean the boy

1543
01:20:17,120 --> 01:20:20,840
Speaker 1: are you? You know? So I think that would change

1544
01:20:20,880 --> 01:20:24,080
Speaker 1: based on how fanatic you are about scent control. If

1545
01:20:24,200 --> 01:20:29,679
Speaker 1: you are freaking over the top with washing and clean

1546
01:20:30,640 --> 01:20:35,680
Speaker 1: um uncented soap, the best you can find, uh titanium

1547
01:20:35,720 --> 01:20:39,640
Speaker 1: added ozone your clothes on a daily basis, clean your

1548
01:20:39,640 --> 01:20:42,920
Speaker 1: body two and three times a day, ozone every single thing,

1549
01:20:43,120 --> 01:20:47,360
Speaker 1: every piece of equipment you have. Then you could probably

1550
01:20:47,400 --> 01:20:49,640
Speaker 1: get by it maybe two or three yards, and they

1551
01:20:49,680 --> 01:20:51,240
Speaker 1: may not detect you if you do it quickly. I

1552
01:20:51,240 --> 01:20:54,759
Speaker 1: mean you can't stand there and let it permeate the area. However,

1553
01:20:54,880 --> 01:20:58,200
Speaker 1: if you're sloppy and you've got human scent all over

1554
01:20:58,240 --> 01:21:01,120
Speaker 1: you and every other scent from the day, you might

1555
01:21:01,160 --> 01:21:05,280
Speaker 1: affect him in a half mile. You know. Interesting? Now,

1556
01:21:05,280 --> 01:21:08,560
Speaker 1: what about obstacles? I heard someone recently kind of theorizing

1557
01:21:08,560 --> 01:21:11,599
Speaker 1: that they thought stuff like a big feel of standing

1558
01:21:11,680 --> 01:21:14,479
Speaker 1: corn or really really thick cover of some kind that

1559
01:21:14,560 --> 01:21:16,680
Speaker 1: might block enough wind that you could get away with

1560
01:21:16,720 --> 01:21:19,640
Speaker 1: a closer distance um from a wind standpoint and not

1561
01:21:19,720 --> 01:21:23,960
Speaker 1: get sented. Do you think there's anything to that depends

1562
01:21:23,960 --> 01:21:26,280
Speaker 1: on speed and your smell again, in my opinion, and

1563
01:21:26,320 --> 01:21:31,879
Speaker 1: how fast it passes that dear like it. Dear's natural

1564
01:21:31,920 --> 01:21:36,519
Speaker 1: reaction is to stay put and stay betted, and it's

1565
01:21:36,640 --> 01:21:39,160
Speaker 1: It's one of the only reasons we ever kill them.

1566
01:21:39,200 --> 01:21:42,639
Speaker 1: If they if they got up and ran every single

1567
01:21:42,680 --> 01:21:45,519
Speaker 1: time they smelled a human, heard a vehicle, heard a

1568
01:21:45,560 --> 01:21:49,240
Speaker 1: four wheeler, heard a guy talking, you'd never kill them. Luckily,

1569
01:21:49,640 --> 01:21:54,360
Speaker 1: their natural um defense mechanism is to just stay betted.

1570
01:21:54,840 --> 01:21:57,800
Speaker 1: So that's why you can walk to your stand even

1571
01:21:57,920 --> 01:22:01,519
Speaker 1: even on like you know, make a dumb choice going

1572
01:22:01,520 --> 01:22:04,760
Speaker 1: into your stand and and walk right by dear. If

1573
01:22:04,800 --> 01:22:07,080
Speaker 1: it's in the cover of darkness and you do it quickly,

1574
01:22:07,560 --> 01:22:10,120
Speaker 1: they're more than likely going to accept it, and they'll

1575
01:22:10,120 --> 01:22:12,240
Speaker 1: come back down after an hour or two they forget

1576
01:22:12,280 --> 01:22:16,240
Speaker 1: what happened. Um. Luckily, they will stay put more often

1577
01:22:16,240 --> 01:22:19,360
Speaker 1: than not. So I always go to my stand rather quickly,

1578
01:22:19,479 --> 01:22:22,200
Speaker 1: especially if I have a strong wind because it's covering

1579
01:22:22,200 --> 01:22:25,600
Speaker 1: your sound. Uh. If I've got a good visual you know,

1580
01:22:25,720 --> 01:22:28,559
Speaker 1: position to where I can sneak in, I go very quickly.

1581
01:22:28,600 --> 01:22:31,439
Speaker 1: I'm a very quick access guy because I don't want

1582
01:22:31,439 --> 01:22:33,840
Speaker 1: my wind going down wind of anyone position for a

1583
01:22:33,920 --> 01:22:37,559
Speaker 1: very long period of time. Something I just thought of

1584
01:22:37,680 --> 01:22:39,639
Speaker 1: that I that I think you alluded to when you're

1585
01:22:39,640 --> 01:22:43,240
Speaker 1: talking about the original influencers. UM, but I didn't ask

1586
01:22:43,280 --> 01:22:47,479
Speaker 1: about yet. Was the change in wind speed? UM, Is

1587
01:22:47,520 --> 01:22:50,040
Speaker 1: there anything there that you're seeing as a big influencer.

1588
01:22:50,120 --> 01:22:51,840
Speaker 1: Is is the change from high to low or low

1589
01:22:51,840 --> 01:22:53,880
Speaker 1: to high, or anything like that's pushing deer in one

1590
01:22:53,880 --> 01:22:58,519
Speaker 1: way or another, only in the sense that as it

1591
01:22:58,600 --> 01:23:00,640
Speaker 1: changes in and out of that suite spot that I

1592
01:23:00,760 --> 01:23:04,439
Speaker 1: mentioned I love seven day about twenty somewhere in that

1593
01:23:04,560 --> 01:23:07,680
Speaker 1: range is really good. Once you start to go above it,

1594
01:23:07,680 --> 01:23:09,479
Speaker 1: it can suppress it a little bit. Once you go

1595
01:23:09,520 --> 01:23:12,640
Speaker 1: below it, it it can suppress it a little bit. So

1596
01:23:13,200 --> 01:23:15,200
Speaker 1: as it floats in and out of the sweet spot.

1597
01:23:15,400 --> 01:23:19,280
Speaker 1: Always think in terms of that look for that sweet spot. Man,

1598
01:23:19,400 --> 01:23:22,560
Speaker 1: those days when it's out of south and it's sustained

1599
01:23:22,560 --> 01:23:26,280
Speaker 1: that twelve until dark on that first south look out,

1600
01:23:26,320 --> 01:23:31,559
Speaker 1: they're all coming. Something you talked about, I think last

1601
01:23:31,600 --> 01:23:34,280
Speaker 1: time we we had this conversation that you said that

1602
01:23:34,320 --> 01:23:37,639
Speaker 1: you were investigating UM but hadn't come to the firm

1603
01:23:37,680 --> 01:23:41,760
Speaker 1: conclusions yet. Was humidity Relative humidity? Is that something where

1604
01:23:41,800 --> 01:23:46,639
Speaker 1: you having found I found no correlation. I have studied

1605
01:23:46,680 --> 01:23:49,280
Speaker 1: it and studied it, and I cannot put a correlation

1606
01:23:49,400 --> 01:23:53,240
Speaker 1: between humidity and dear movement. I can't do it. I've

1607
01:23:53,240 --> 01:23:56,320
Speaker 1: had high humidity days where they move their butts off.

1608
01:23:56,360 --> 01:23:58,840
Speaker 1: I've had low humidity days. To me, it was other

1609
01:23:59,360 --> 01:24:02,280
Speaker 1: whether in fluencers had a much greater effect on them

1610
01:24:02,360 --> 01:24:07,719
Speaker 1: than the actual humidity. Then sticking with moisture, then talk

1611
01:24:07,840 --> 01:24:13,120
Speaker 1: to me about precipitation. I love it, absolutely love it,

1612
01:24:13,200 --> 01:24:15,639
Speaker 1: especially when we haven't had it for a while. If

1613
01:24:15,680 --> 01:24:19,800
Speaker 1: you're into a dry spell and it starts, it goes

1614
01:24:19,800 --> 01:24:22,920
Speaker 1: back to that delta. You know things are changing. You've

1615
01:24:22,920 --> 01:24:26,400
Speaker 1: been dry, it's about to get wet. Get ready because

1616
01:24:26,400 --> 01:24:29,080
Speaker 1: they're fixing to move and moving a big way. If

1617
01:24:29,120 --> 01:24:32,120
Speaker 1: it's been wet sustained three or four days heavy rain,

1618
01:24:33,120 --> 01:24:36,080
Speaker 1: when it's about to stop, it is the biggest trigger

1619
01:24:36,120 --> 01:24:37,800
Speaker 1: you will ever see for a white killed deer in

1620
01:24:37,800 --> 01:24:40,800
Speaker 1: your life. I don't give up. I don't care if

1621
01:24:40,840 --> 01:24:43,120
Speaker 1: it's at nine, ten, eleven, twelve, one o'clock of the

1622
01:24:43,200 --> 01:24:47,639
Speaker 1: day when it slows down. They're fixing to move. So

1623
01:24:48,400 --> 01:24:50,759
Speaker 1: what about the intensity? I get a lot of people.

1624
01:24:51,200 --> 01:24:53,280
Speaker 1: I personally love rain, but you hear a lot of

1625
01:24:53,280 --> 01:24:55,559
Speaker 1: people say, oh, they're not gonna move during the middle

1626
01:24:55,600 --> 01:24:57,240
Speaker 1: of the storm or during the middle of the all

1627
01:24:57,320 --> 01:25:00,880
Speaker 1: day rain. Um, do you have any thoughts on that?

1628
01:25:02,000 --> 01:25:04,280
Speaker 1: The heavier the rain, the less likely they are to

1629
01:25:04,320 --> 01:25:06,599
Speaker 1: move during it. The lighter the rain, the more likely

1630
01:25:06,640 --> 01:25:09,880
Speaker 1: they are to move during it. Those light, misty days

1631
01:25:09,920 --> 01:25:13,640
Speaker 1: like fog bordering on mist, man, they're gonna move their

1632
01:25:13,680 --> 01:25:17,439
Speaker 1: tails off. Heavy foggers a suppressor. But those those days

1633
01:25:17,439 --> 01:25:19,360
Speaker 1: where it's real wet and damp in the air and

1634
01:25:19,439 --> 01:25:22,439
Speaker 1: you can still see. If fog affects your visibility, it's

1635
01:25:22,439 --> 01:25:26,360
Speaker 1: probably affecting mayors. And if it reduces visibility down to

1636
01:25:26,400 --> 01:25:28,280
Speaker 1: where you can hardly see, they're not going to move

1637
01:25:28,360 --> 01:25:31,840
Speaker 1: very well. Um. If, however, it's one of those days

1638
01:25:31,880 --> 01:25:35,080
Speaker 1: where it's foggy just above where you can see, you know,

1639
01:25:35,120 --> 01:25:37,000
Speaker 1: it's kind of just moisture in the air, and then

1640
01:25:37,040 --> 01:25:40,960
Speaker 1: it turns into a light presept Whoo, that's a generator, man,

1641
01:25:41,120 --> 01:25:44,919
Speaker 1: Look out, cools that body they're gonna move. Light precept

1642
01:25:45,120 --> 01:25:48,840
Speaker 1: is fantastic snows the same way. Heavier the snow, the

1643
01:25:48,920 --> 01:25:51,439
Speaker 1: less they're gonna move. Lighter the snow, the more of

1644
01:25:51,479 --> 01:25:54,479
Speaker 1: an influencer it is. Yeah, I was gonna ask about

1645
01:25:54,479 --> 01:25:59,160
Speaker 1: snow next. Is there anything, um what about accumulation? Have

1646
01:25:59,240 --> 01:26:03,160
Speaker 1: you noticed any kind of correlation between a certain amount,

1647
01:26:03,280 --> 01:26:06,960
Speaker 1: like is twelve inches of snow going to result in

1648
01:26:07,120 --> 01:26:09,519
Speaker 1: in a heavier feeding impulse than a one inch snow

1649
01:26:10,840 --> 01:26:12,400
Speaker 1: bends on the time of the year and how many

1650
01:26:12,400 --> 01:26:14,600
Speaker 1: snows we've already had. If it's just if it's the

1651
01:26:14,640 --> 01:26:17,600
Speaker 1: first snow, that they'll react one way. If it's the

1652
01:26:17,640 --> 01:26:19,800
Speaker 1: tents snow, they'll react a different way. Once they get

1653
01:26:19,880 --> 01:26:22,040
Speaker 1: used to it. The snow really doesn't affect them that

1654
01:26:22,160 --> 01:26:24,160
Speaker 1: much anymore, but they got to equalize to it, and

1655
01:26:24,160 --> 01:26:26,559
Speaker 1: they gotta get used to it in their environment. You know,

1656
01:26:27,120 --> 01:26:29,920
Speaker 1: snow down in Texas and watch them versus snow up

1657
01:26:29,920 --> 01:26:32,400
Speaker 1: in Michigan and watch them. It affects every deer heard

1658
01:26:32,400 --> 01:26:35,280
Speaker 1: differently depending on how used to it, uh they are,

1659
01:26:35,439 --> 01:26:38,320
Speaker 1: how I'm not used to it they are? Yeah, Yeah,

1660
01:26:38,520 --> 01:26:40,640
Speaker 1: I feel like, you know, you've got you gotta use

1661
01:26:40,680 --> 01:26:43,200
Speaker 1: your own common sense in certain areas, you know. Yeah,

1662
01:26:43,400 --> 01:26:45,400
Speaker 1: we had snowed out that Texas ranch and I mean

1663
01:26:45,439 --> 01:26:50,599
Speaker 1: they literally didn't move for two days. It's interesting completely, Yeah,

1664
01:26:50,680 --> 01:26:54,200
Speaker 1: And I feel like I could see that's a unique scenaria,

1665
01:26:54,200 --> 01:26:56,320
Speaker 1: I think. But if I were to take a look

1666
01:26:56,320 --> 01:26:58,720
Speaker 1: at a lot of what we're talking about here, one

1667
01:26:58,720 --> 01:27:02,920
Speaker 1: of the core that consider sencis is whenever we veer

1668
01:27:03,240 --> 01:27:07,880
Speaker 1: from the average, or we veer from the status quo

1669
01:27:08,520 --> 01:27:11,599
Speaker 1: that seems to cue this change in behavior with dear,

1670
01:27:11,640 --> 01:27:13,439
Speaker 1: whether it be the change in temperature, or the change

1671
01:27:13,479 --> 01:27:17,320
Speaker 1: in wind, or the change in precipitation. Um, would you

1672
01:27:17,360 --> 01:27:19,680
Speaker 1: say that that's a consistent thing we're seeing here over

1673
01:27:19,720 --> 01:27:22,120
Speaker 1: and over again. Is is it's that shift? It's the

1674
01:27:22,160 --> 01:27:28,640
Speaker 1: shifting conditions oftentimes that's triggering something. Um that seems to

1675
01:27:28,640 --> 01:27:32,000
Speaker 1: be like it is. It is quite often change which

1676
01:27:32,080 --> 01:27:36,680
Speaker 1: the weather is ever changing. Right, So their energy conservation

1677
01:27:37,400 --> 01:27:40,559
Speaker 1: or you know, energy consumption is really what they're doing.

1678
01:27:40,600 --> 01:27:42,479
Speaker 1: They're either going to conserve energy or they're gonna go

1679
01:27:42,520 --> 01:27:47,160
Speaker 1: try and recharge their batteries. Really depends upon what time

1680
01:27:47,200 --> 01:27:49,400
Speaker 1: of the year it is, how big the front is,

1681
01:27:49,439 --> 01:27:51,599
Speaker 1: how much change there is. I mean, that's how they live.

1682
01:27:51,960 --> 01:27:54,400
Speaker 1: You know, they have to eat their slaves to their

1683
01:27:54,439 --> 01:27:58,479
Speaker 1: stomach and it revolves around the you know those fronts.

1684
01:27:58,920 --> 01:28:01,320
Speaker 1: How much it threatens their well being, how much it

1685
01:28:01,360 --> 01:28:04,920
Speaker 1: threatens their ability to stay at peak form. All of

1686
01:28:04,960 --> 01:28:07,960
Speaker 1: those things will affect them. So it really depends on

1687
01:28:08,000 --> 01:28:10,680
Speaker 1: the time of the year and how vicious the front is,

1688
01:28:10,800 --> 01:28:17,720
Speaker 1: and it it changes through each phase drastically, honestly, what

1689
01:28:20,600 --> 01:28:25,160
Speaker 1: let's let's let's switch to something different here, um, because

1690
01:28:25,200 --> 01:28:29,240
Speaker 1: there's one topic that everyone likes to argue about, and

1691
01:28:29,360 --> 01:28:32,400
Speaker 1: you've got some some strong opinions about I think that

1692
01:28:32,439 --> 01:28:35,680
Speaker 1: are interesting, but their counter to some opinions by many

1693
01:28:35,760 --> 01:28:39,320
Speaker 1: other people. And this is the moon, of course. Um.

1694
01:28:39,360 --> 01:28:41,200
Speaker 1: Can you give me the marjury one on one on

1695
01:28:41,280 --> 01:28:43,519
Speaker 1: your thoughts on the moon, and then we'll go from there.

1696
01:28:45,000 --> 01:28:48,439
Speaker 1: Weather Trump's moon in all cases, but the moon is

1697
01:28:48,479 --> 01:28:52,400
Speaker 1: a major, major influencer to deer activity. If you take

1698
01:28:52,840 --> 01:28:56,120
Speaker 1: the five to seven days on either side of the

1699
01:28:56,120 --> 01:28:59,120
Speaker 1: full moon each month, you're going to see the peak

1700
01:28:59,200 --> 01:29:02,360
Speaker 1: of daylight activity, whether it be morning or evening. If

1701
01:29:02,400 --> 01:29:04,679
Speaker 1: you take the five to seven days in and around

1702
01:29:04,680 --> 01:29:07,320
Speaker 1: the dark of the moon, you're generally going to see

1703
01:29:07,520 --> 01:29:10,160
Speaker 1: the least amount of activity. That has been my observation

1704
01:29:10,280 --> 01:29:14,160
Speaker 1: for the past twenty plus years. The app interprets that

1705
01:29:14,320 --> 01:29:17,040
Speaker 1: on a day in and day out basis, and our

1706
01:29:17,840 --> 01:29:21,200
Speaker 1: our history within our journal shows that if you want

1707
01:29:21,200 --> 01:29:24,120
Speaker 1: to watch the Dree Outdoorge Journal each and every year

1708
01:29:24,160 --> 01:29:26,400
Speaker 1: and watch it when it lights up, watch the few

1709
01:29:26,479 --> 01:29:29,120
Speaker 1: days that precede the full moon and the few days

1710
01:29:29,120 --> 01:29:32,479
Speaker 1: that follow it, and then compare and contrast that with

1711
01:29:32,560 --> 01:29:35,280
Speaker 1: the days that precede and follow the dark of the moon.

1712
01:29:36,439 --> 01:29:39,760
Speaker 1: Now does that a lot of these factors you talked about.

1713
01:29:39,760 --> 01:29:42,559
Speaker 1: You've said that at certain times of the year, an

1714
01:29:42,560 --> 01:29:46,599
Speaker 1: influencer will be weighted more heavily. So doesn't it's weighted

1715
01:29:46,600 --> 01:29:51,080
Speaker 1: the same. It's weighted the same throughout every phase. Okay, Now,

1716
01:29:51,120 --> 01:29:54,800
Speaker 1: what is one influencer that did not change? Interesting? Now,

1717
01:29:54,840 --> 01:29:58,080
Speaker 1: what about um? I'm sure you've heard about the red

1718
01:29:58,120 --> 01:30:03,160
Speaker 1: moon charts and days and that's essentially the overhead underfoot. Um.

1719
01:30:03,320 --> 01:30:05,680
Speaker 1: Have you seen anything there? Any thoughts on on that

1720
01:30:05,760 --> 01:30:07,280
Speaker 1: theory that a lot of people seem to have, Because

1721
01:30:07,280 --> 01:30:10,760
Speaker 1: I know, if I remember right, the moon the days

1722
01:30:10,760 --> 01:30:12,800
Speaker 1: that you just mentioned ahead and after the falling or

1723
01:30:12,880 --> 01:30:17,759
Speaker 1: the full moon that typically coincides with the moon setting

1724
01:30:17,800 --> 01:30:22,040
Speaker 1: and rising times matching up with those key morning or

1725
01:30:22,080 --> 01:30:24,400
Speaker 1: evening time frames. I know that's something you've pointed to.

1726
01:30:24,439 --> 01:30:27,920
Speaker 1: When those things match up, that's a that's a good time. UM.

1727
01:30:28,040 --> 01:30:30,599
Speaker 1: Folks like Adam Hayes or someone would say, well, when

1728
01:30:30,640 --> 01:30:33,360
Speaker 1: the red moon, which is overhead or underfoot, matches up

1729
01:30:33,439 --> 01:30:37,000
Speaker 1: with your key morning or evening times, those are the best.

1730
01:30:37,600 --> 01:30:40,759
Speaker 1: What's your take on that. I haven't noticed that nearly

1731
01:30:40,800 --> 01:30:44,559
Speaker 1: as much. Um. What I have noticed is that during

1732
01:30:45,200 --> 01:30:48,320
Speaker 1: certain times of the year, certain times of the day

1733
01:30:48,320 --> 01:30:52,160
Speaker 1: are very important. In other words, if you look at

1734
01:30:52,640 --> 01:30:56,479
Speaker 1: midday on September and compare that to midday on November,

1735
01:30:57,520 --> 01:30:59,840
Speaker 1: drastic difference in how the deer are going to move

1736
01:31:00,080 --> 01:31:02,519
Speaker 1: as it pertains to time of day. That's why I

1737
01:31:02,600 --> 01:31:04,920
Speaker 1: mentioned earlier when you when you download the app and

1738
01:31:04,960 --> 01:31:07,840
Speaker 1: look at it, always watch time of day for each

1739
01:31:07,920 --> 01:31:11,080
Speaker 1: individual phase because we're gonna break down what times of

1740
01:31:11,120 --> 01:31:16,960
Speaker 1: the day are optimum. So September, give me a moon

1741
01:31:17,400 --> 01:31:21,120
Speaker 1: that has overhead or underfoot at noon, it's not going

1742
01:31:21,160 --> 01:31:23,479
Speaker 1: to influence them because it's not a normal time that

1743
01:31:23,520 --> 01:31:26,679
Speaker 1: they would be moving, not nearly as much as it would. However,

1744
01:31:26,720 --> 01:31:28,800
Speaker 1: if you look at it on November fifteenth, when it

1745
01:31:28,920 --> 01:31:31,240
Speaker 1: is a normal time that they might be moving, it

1746
01:31:31,240 --> 01:31:35,120
Speaker 1: will absolutely influence them more. So, it really comes down

1747
01:31:35,160 --> 01:31:37,920
Speaker 1: to what time of the day do they normally move

1748
01:31:38,040 --> 01:31:40,160
Speaker 1: during that time of the year. If you look at

1749
01:31:40,200 --> 01:31:43,720
Speaker 1: the app, most of the year, it's the first hour

1750
01:31:43,800 --> 01:31:45,960
Speaker 1: and a half to two hours. In the last hour

1751
01:31:46,000 --> 01:31:48,280
Speaker 1: and a half to two hours, a lot of the year.

1752
01:31:48,360 --> 01:31:50,600
Speaker 1: It's the first hour, last hour as it pertains to

1753
01:31:50,640 --> 01:31:54,560
Speaker 1: sunrise around sunrise for the next hour to hour and

1754
01:31:54,560 --> 01:31:58,519
Speaker 1: a half to an oh about thirty minutes before sunrise

1755
01:31:58,560 --> 01:32:01,400
Speaker 1: to the thirty to forty five minutes that follow sunrise.

1756
01:32:01,840 --> 01:32:04,879
Speaker 1: Those are that's dear thirty both morning and evening throughout

1757
01:32:04,880 --> 01:32:08,080
Speaker 1: the year. However, there are those phases in mid November

1758
01:32:08,120 --> 01:32:10,679
Speaker 1: where you could throw that out the window and look

1759
01:32:10,720 --> 01:32:12,880
Speaker 1: at the middle part of the day and go, Okay,

1760
01:32:12,920 --> 01:32:17,720
Speaker 1: everything is moving between about they start then about the

1761
01:32:17,760 --> 01:32:20,320
Speaker 1: time that they end during the rest of the phases,

1762
01:32:20,600 --> 01:32:23,479
Speaker 1: and they end about the time they normally start during

1763
01:32:23,520 --> 01:32:26,479
Speaker 1: the rest of the phases. So it is drastically different.

1764
01:32:26,800 --> 01:32:29,200
Speaker 1: So there is a correlation and how will they move

1765
01:32:29,280 --> 01:32:31,720
Speaker 1: with the moon, But you have to time that and

1766
01:32:31,760 --> 01:32:35,880
Speaker 1: compare it to what phase you're talking about. Yeah, so

1767
01:32:37,080 --> 01:32:38,960
Speaker 1: I know when we chatted last on this topic, we

1768
01:32:39,040 --> 01:32:42,000
Speaker 1: talked about the moon in relationship to the rut, and

1769
01:32:42,640 --> 01:32:44,840
Speaker 1: if I remember correctly, you would talk about the fact

1770
01:32:44,880 --> 01:32:47,920
Speaker 1: that you know the same as most biologists and everyone

1771
01:32:47,960 --> 01:32:50,320
Speaker 1: point to that the rut is relatively consistent, is tied

1772
01:32:50,360 --> 01:32:53,640
Speaker 1: to photo period, etcetera, etcetera. Um, so I know, as

1773
01:32:53,680 --> 01:32:55,439
Speaker 1: You've mentioned a lot of the states as you guys

1774
01:32:55,439 --> 01:32:58,320
Speaker 1: put into the deer cast app peak and estus around

1775
01:32:58,320 --> 01:33:01,280
Speaker 1: with November fourteenth or fifteenth. That seems to be peak

1776
01:33:01,439 --> 01:33:03,320
Speaker 1: est states for most of the Midwest, a lot of

1777
01:33:03,320 --> 01:33:06,559
Speaker 1: parts of the country. Um. But you did say that

1778
01:33:06,640 --> 01:33:10,479
Speaker 1: the moon illuminates certain portions of the rut and makes

1779
01:33:10,479 --> 01:33:14,280
Speaker 1: those better for hunting. Um. Could you expand on that

1780
01:33:14,320 --> 01:33:16,439
Speaker 1: a little bit in general, but then talk to us

1781
01:33:16,479 --> 01:33:20,720
Speaker 1: about what that's going to do this year than you think. Absolutely,

1782
01:33:21,320 --> 01:33:25,960
Speaker 1: the rut differs in intensity each and every year, in

1783
01:33:26,040 --> 01:33:29,720
Speaker 1: my opinion, because the moon that same influte. So that

1784
01:33:29,800 --> 01:33:31,640
Speaker 1: I'm talking about if you look in and around the

1785
01:33:31,680 --> 01:33:34,120
Speaker 1: ten to fourteen days around the full moon, specifically to

1786
01:33:34,200 --> 01:33:37,320
Speaker 1: ten five before or five after, and compare that to

1787
01:33:37,360 --> 01:33:40,040
Speaker 1: the five before and five after the dark as to

1788
01:33:40,160 --> 01:33:42,559
Speaker 1: when you see the deer and how much daylight activity

1789
01:33:42,560 --> 01:33:46,000
Speaker 1: you see. It expands it in and around the full moon,

1790
01:33:46,280 --> 01:33:49,600
Speaker 1: it decreases it in and around the dark of the moon. Therefore,

1791
01:33:49,840 --> 01:33:53,200
Speaker 1: if the full moon hits during a normally good phase

1792
01:33:53,240 --> 01:33:55,479
Speaker 1: of the rut, in other words, the seeking phase, oh

1793
01:33:55,520 --> 01:33:57,920
Speaker 1: my goodness, man, did we have a rut? Well? It

1794
01:33:58,160 --> 01:34:03,160
Speaker 1: enhanced and otherwise grow eight phase. If, however, the full

1795
01:34:03,200 --> 01:34:06,479
Speaker 1: moon hits like it's going to this year during some

1796
01:34:06,560 --> 01:34:08,960
Speaker 1: tougher phases. In other words, it's going to be full

1797
01:34:08,960 --> 01:34:13,800
Speaker 1: at the tail end of the um October law and

1798
01:34:13,880 --> 01:34:16,519
Speaker 1: also again at the tail end of November, which is

1799
01:34:16,560 --> 01:34:21,719
Speaker 1: party's over and on into uh green revisited. It's gonna

1800
01:34:21,720 --> 01:34:23,479
Speaker 1: be a little bit tougher and a little bit later

1801
01:34:23,560 --> 01:34:27,160
Speaker 1: because it's coming in phases that aren't normally nearly as good.

1802
01:34:27,720 --> 01:34:31,000
Speaker 1: And conversely, the dark of the moon, which subdues movement,

1803
01:34:31,280 --> 01:34:33,320
Speaker 1: is going to be hitting in and around those phases

1804
01:34:33,360 --> 01:34:36,240
Speaker 1: that are generally better. So you're gonna see you're gonna

1805
01:34:36,280 --> 01:34:40,439
Speaker 1: be ce shortened periods of activity first hour, last hour,

1806
01:34:40,840 --> 01:34:42,960
Speaker 1: and not nearly as much during the middle part of

1807
01:34:43,000 --> 01:34:46,000
Speaker 1: the day this year until you get in and around

1808
01:34:46,000 --> 01:34:51,120
Speaker 1: that full moon. I think October could be deadly for

1809
01:34:51,200 --> 01:34:54,439
Speaker 1: some really mature bucks on scrapes as we lead in

1810
01:34:54,560 --> 01:34:58,280
Speaker 1: the full moon going into like the twenty one to

1811
01:34:59,280 --> 01:35:02,000
Speaker 1: leading into that all moon, and then right after that

1812
01:35:02,160 --> 01:35:06,960
Speaker 1: as as movement switches over to mornings like catch the

1813
01:35:07,040 --> 01:35:09,840
Speaker 1: front in and around the full moon, either leading into

1814
01:35:09,840 --> 01:35:12,280
Speaker 1: it or just following the full moon two or three days,

1815
01:35:12,520 --> 01:35:15,720
Speaker 1: and you're gonna see some major monsters get killed in

1816
01:35:15,800 --> 01:35:18,519
Speaker 1: and around scraping activities at the food source, because those

1817
01:35:18,520 --> 01:35:20,760
Speaker 1: are the first places they're gonna go looking for the

1818
01:35:20,800 --> 01:35:23,719
Speaker 1: first available dough. It could be dynamite. If it's warm,

1819
01:35:23,840 --> 01:35:25,720
Speaker 1: it's gonna subdue way down. It's not going to be

1820
01:35:25,760 --> 01:35:29,599
Speaker 1: nearly as good going into November. I think it could

1821
01:35:29,640 --> 01:35:32,080
Speaker 1: be a tougher seeking phase and into the peak of

1822
01:35:32,080 --> 01:35:35,080
Speaker 1: the rut, it's gonna be more subdued first thirty minutes,

1823
01:35:35,120 --> 01:35:38,120
Speaker 1: the last thirty minutes. But then when you get back

1824
01:35:38,160 --> 01:35:41,920
Speaker 1: into the full moon around November, I think it is

1825
01:35:42,240 --> 01:35:43,960
Speaker 1: then all of a sudden you're starting to see deer

1826
01:35:44,040 --> 01:35:46,559
Speaker 1: free up, go back to the food source. That's when

1827
01:35:46,560 --> 01:35:49,360
Speaker 1: you get back on your green green plots and you

1828
01:35:49,479 --> 01:35:52,040
Speaker 1: look for that cold front and then catch them back

1829
01:35:52,040 --> 01:35:55,240
Speaker 1: coming to green green revisited in November. This year will

1830
01:35:55,280 --> 01:35:58,960
Speaker 1: be fantastic for some giants in my opinion. So do

1831
01:35:59,000 --> 01:36:01,880
Speaker 1: you think that this full moon or what you're talking about,

1832
01:36:01,920 --> 01:36:05,479
Speaker 1: how that affects intensity of activity during the daylight that

1833
01:36:05,520 --> 01:36:09,120
Speaker 1: we can see as hunters. As you mentioned, this year

1834
01:36:09,240 --> 01:36:11,680
Speaker 1: does not line up with the traditional time frames that

1835
01:36:11,680 --> 01:36:14,479
Speaker 1: we're expecting the most seeking and chasing and daylight activity

1836
01:36:14,520 --> 01:36:16,840
Speaker 1: that we hunters want. Do you think it makes so

1837
01:36:16,960 --> 01:36:19,120
Speaker 1: much of an impact that if you had like a

1838
01:36:19,160 --> 01:36:21,400
Speaker 1: week of vacation time or two weeks of vacation time

1839
01:36:21,479 --> 01:36:23,320
Speaker 1: during the run. I think most guys would usually say

1840
01:36:23,360 --> 01:36:25,720
Speaker 1: maybe the first two weeks in November are safe bet

1841
01:36:25,800 --> 01:36:29,680
Speaker 1: for typical best running activity. But the moon, as you're

1842
01:36:29,680 --> 01:36:32,880
Speaker 1: describing it, is not focusing on or is not going

1843
01:36:32,920 --> 01:36:34,680
Speaker 1: to help us out during that time frame. Do you

1844
01:36:34,680 --> 01:36:36,559
Speaker 1: think the moon has so much of an impact that

1845
01:36:36,600 --> 01:36:38,200
Speaker 1: you would not say those would be the best two

1846
01:36:38,200 --> 01:36:42,080
Speaker 1: weeks anymore? Uh? No, those are still the best two

1847
01:36:42,080 --> 01:36:45,120
Speaker 1: weeks because that's still the phases where they're going to

1848
01:36:45,240 --> 01:36:47,680
Speaker 1: move the best. However, it's going to subdue it. You're

1849
01:36:47,720 --> 01:36:50,320
Speaker 1: not going to have as much daylight activity. So what

1850
01:36:50,520 --> 01:36:53,760
Speaker 1: then you're depending on is the weather. Uh. If you

1851
01:36:53,840 --> 01:36:56,080
Speaker 1: get bad weather during that period, it's going to seem

1852
01:36:56,120 --> 01:36:59,200
Speaker 1: like an awful run. If you get good weather during

1853
01:36:59,200 --> 01:37:02,280
Speaker 1: that period, it's to seem like a good rut. If

1854
01:37:02,320 --> 01:37:05,200
Speaker 1: the moon was lined up and you had great weather,

1855
01:37:05,479 --> 01:37:07,560
Speaker 1: then you go, oh my goodness, it's the rut of

1856
01:37:07,560 --> 01:37:10,800
Speaker 1: ball ruts. So it really takes several factors lining up

1857
01:37:10,840 --> 01:37:14,559
Speaker 1: at once in order to make something incredible versus just

1858
01:37:14,720 --> 01:37:18,040
Speaker 1: good or poor. Okay, I filu you there, and that

1859
01:37:18,040 --> 01:37:20,840
Speaker 1: that's that's kind of what my assumption was, UM, So

1860
01:37:20,920 --> 01:37:23,679
Speaker 1: that that makes sense to me. So I've got one

1861
01:37:23,840 --> 01:37:26,680
Speaker 1: last kind of line of questioning here before I take

1862
01:37:26,760 --> 01:37:29,839
Speaker 1: up your entire night mark. Um. If we're talking predicting

1863
01:37:29,880 --> 01:37:33,439
Speaker 1: dear movement, it's not just outside fact or it's not

1864
01:37:33,520 --> 01:37:37,160
Speaker 1: just like atmosphere factors like whether, it's not things just

1865
01:37:37,200 --> 01:37:39,000
Speaker 1: like the moon. But there also can be something to

1866
01:37:39,000 --> 01:37:42,240
Speaker 1: be said about knowledge like intel can help you predict

1867
01:37:42,280 --> 01:37:44,960
Speaker 1: dear movements. This is something that obviously dear cast can't

1868
01:37:45,000 --> 01:37:46,880
Speaker 1: do for you. This is something that you, as a

1869
01:37:46,960 --> 01:37:49,680
Speaker 1: hunter have to do, UM. But this is something I

1870
01:37:49,680 --> 01:37:51,920
Speaker 1: know you've talked about a lot already today. You've mentioned

1871
01:37:51,920 --> 01:37:55,320
Speaker 1: the importance of like your long distance observation sits, things

1872
01:37:55,360 --> 01:37:58,200
Speaker 1: like that. And then I brought up earlier when I

1873
01:37:58,240 --> 01:38:00,439
Speaker 1: was talking about that late October hunt for a whole field,

1874
01:38:00,439 --> 01:38:03,320
Speaker 1: how I was trying to take advantage of annual patterns,

1875
01:38:03,479 --> 01:38:05,840
Speaker 1: the fact that I knew that this deer had done

1876
01:38:05,880 --> 01:38:08,800
Speaker 1: something two years prior. Consistently I was hoping you'd do

1877
01:38:08,800 --> 01:38:13,479
Speaker 1: it again for a third year. UM, So, I guess

1878
01:38:13,600 --> 01:38:15,720
Speaker 1: if we continue the pattern we've done, Can you give

1879
01:38:15,760 --> 01:38:20,000
Speaker 1: me a quick overview of your thoughts on how annual

1880
01:38:20,040 --> 01:38:23,599
Speaker 1: patterns and what you can learn from historical trailcare pictures

1881
01:38:24,040 --> 01:38:27,000
Speaker 1: can help you predict dear movement. Um. And then I've

1882
01:38:27,040 --> 01:38:29,320
Speaker 1: got a few specific things that I've always wondered about

1883
01:38:29,479 --> 01:38:33,600
Speaker 1: that that I'm hoping you can help me understand. Absolutely,

1884
01:38:33,640 --> 01:38:37,840
Speaker 1: you know that they're extremely habitual animals. They generally do

1885
01:38:38,000 --> 01:38:41,120
Speaker 1: similar things during similar times of the year. The things

1886
01:38:41,160 --> 01:38:44,400
Speaker 1: that can affect that our moon phase and overall crop

1887
01:38:44,520 --> 01:38:50,760
Speaker 1: rotation and overall mass crop production. So while you could

1888
01:38:50,800 --> 01:38:52,840
Speaker 1: scout a deer one year you were you were giving

1889
01:38:52,880 --> 01:38:55,559
Speaker 1: your whole field example that while ago and I thought

1890
01:38:55,600 --> 01:38:59,559
Speaker 1: back to the year that you mentioned would have been

1891
01:38:59,640 --> 01:39:02,680
Speaker 1: six team when that moon would have been very favorable

1892
01:39:02,720 --> 01:39:08,080
Speaker 1: for that period, uh specifically September. I don't recall what

1893
01:39:08,200 --> 01:39:11,360
Speaker 1: fifteens moon was, but sixteens moon would have been very

1894
01:39:11,360 --> 01:39:14,840
Speaker 1: favorable right then. Uh, So that could have been the

1895
01:39:14,840 --> 01:39:16,640
Speaker 1: thing that had him on his feet during daylight. So

1896
01:39:16,720 --> 01:39:20,720
Speaker 1: always keep those conditions in mind and understand that there

1897
01:39:20,760 --> 01:39:23,280
Speaker 1: may be influencers on certain days that have him on

1898
01:39:23,320 --> 01:39:25,200
Speaker 1: his feet. The best thing you can do is go

1899
01:39:25,280 --> 01:39:28,759
Speaker 1: back and look at weather history for those days and go, Okay,

1900
01:39:28,760 --> 01:39:31,640
Speaker 1: why did he move on daylight activity here? What was

1901
01:39:31,680 --> 01:39:33,519
Speaker 1: it about the weather? Was it a major coal front,

1902
01:39:33,560 --> 01:39:35,719
Speaker 1: what was the wind, what was the departure from average,

1903
01:39:35,920 --> 01:39:38,320
Speaker 1: what was the pressure, What had the weather been, and

1904
01:39:38,360 --> 01:39:40,679
Speaker 1: what was it about to do? And try to understand

1905
01:39:40,720 --> 01:39:42,680
Speaker 1: why he moved that day, And then look at what

1906
01:39:42,720 --> 01:39:46,400
Speaker 1: the moon phase was. So I look at historical data

1907
01:39:46,439 --> 01:39:49,360
Speaker 1: from my photos. I always scout a year in advance,

1908
01:39:49,640 --> 01:39:53,080
Speaker 1: but then I take this year's coming conditions in terms

1909
01:39:53,120 --> 01:39:56,639
Speaker 1: of moon, how it affects the rut, what the mash

1910
01:39:56,640 --> 01:40:00,240
Speaker 1: crop is, what the actual crop rotation is, and then

1911
01:40:00,280 --> 01:40:02,559
Speaker 1: try to apply that to the own knowledge within my

1912
01:40:02,640 --> 01:40:05,479
Speaker 1: head and go, Okay, what's he gonna do this year?

1913
01:40:05,560 --> 01:40:09,200
Speaker 1: So it's one thing to analyze past information. It's another

1914
01:40:09,240 --> 01:40:11,640
Speaker 1: thing to take it, interpret it, and then make a

1915
01:40:11,720 --> 01:40:15,360
Speaker 1: prediction on how he's going to maneuver through the season

1916
01:40:15,680 --> 01:40:18,719
Speaker 1: based on all those conditions this coming year. Yeah, So

1917
01:40:18,920 --> 01:40:22,799
Speaker 1: you you you're, you're, you are who you are because

1918
01:40:23,040 --> 01:40:25,439
Speaker 1: you're a rock star market because those are exactly all

1919
01:40:25,479 --> 01:40:27,720
Speaker 1: the things I've struggled with to try to figure out

1920
01:40:27,720 --> 01:40:30,880
Speaker 1: which is you know, so what manners? More? Is it

1921
01:40:30,960 --> 01:40:33,679
Speaker 1: the date? So should I be so tied to those

1922
01:40:33,760 --> 01:40:38,920
Speaker 1: dates October I was? Or or do the specific conditions

1923
01:40:38,960 --> 01:40:41,639
Speaker 1: that happened matter more? Should have been more so looking

1924
01:40:41,640 --> 01:40:44,960
Speaker 1: for Okay, I don't care what its October. I'm more

1925
01:40:45,000 --> 01:40:48,519
Speaker 1: so should be looking for the X moon with the

1926
01:40:48,600 --> 01:40:52,639
Speaker 1: fifteen degree or more temperature drop and high pressure. Um

1927
01:40:53,120 --> 01:40:55,600
Speaker 1: would you rank one of the other or how do

1928
01:40:55,680 --> 01:40:57,880
Speaker 1: you how do you process all that in your head

1929
01:40:57,920 --> 01:41:01,960
Speaker 1: when you're weighing those things. I would have looked at

1930
01:41:01,960 --> 01:41:04,800
Speaker 1: conditions for sure, and I would have looked at what

1931
01:41:04,840 --> 01:41:06,960
Speaker 1: he would which direction he was heading, like what food

1932
01:41:06,960 --> 01:41:08,800
Speaker 1: source was he going to, what was he coming back to?

1933
01:41:09,080 --> 01:41:11,360
Speaker 1: How good was the mass crop, how much did it

1934
01:41:11,400 --> 01:41:14,120
Speaker 1: affect his daylight activity? How poor was the mass crop?

1935
01:41:14,640 --> 01:41:17,479
Speaker 1: You know, all those different conditions, and then you look

1936
01:41:17,479 --> 01:41:19,920
Speaker 1: at this year that the Andrew dealt and see what

1937
01:41:19,960 --> 01:41:22,040
Speaker 1: he's doing. You also look at the health of the deer,

1938
01:41:22,040 --> 01:41:24,920
Speaker 1: and this is something you I don't talk about a

1939
01:41:24,920 --> 01:41:27,839
Speaker 1: great deal, but it's something that absolutely makes a difference.

1940
01:41:28,080 --> 01:41:31,599
Speaker 1: In other words, I have seen dear in supreme health

1941
01:41:32,280 --> 01:41:36,160
Speaker 1: because they've had great feed all summer they've had great rainfall,

1942
01:41:36,760 --> 01:41:38,880
Speaker 1: and then they get into the fall and they move

1943
01:41:38,960 --> 01:41:42,040
Speaker 1: their butts off because they're in super good condition. And

1944
01:41:42,080 --> 01:41:44,280
Speaker 1: then the next year you go through a drought, you've

1945
01:41:44,320 --> 01:41:46,920
Speaker 1: got e h d lingering. They don't have the food

1946
01:41:46,960 --> 01:41:49,760
Speaker 1: source quality that they had all year. They don't feel

1947
01:41:49,800 --> 01:41:52,679
Speaker 1: as well in my opinion, and therefore they don't move

1948
01:41:52,720 --> 01:41:55,120
Speaker 1: as well. So I look at the overall health of

1949
01:41:55,120 --> 01:41:57,760
Speaker 1: the deer herd. What does rack look like from one

1950
01:41:57,840 --> 01:42:00,000
Speaker 1: year or the other? Did he all of a sudden

1951
01:42:00,040 --> 01:42:02,639
Speaker 1: not grow the rack you expected him to grow? Why

1952
01:42:02,640 --> 01:42:05,599
Speaker 1: did he not grow it? Okay? Did he have something

1953
01:42:05,680 --> 01:42:07,960
Speaker 1: nagging at him the previous year? Was it an injury?

1954
01:42:08,040 --> 01:42:10,320
Speaker 1: Was it a foot injury? Was it an antler injury

1955
01:42:10,360 --> 01:42:13,920
Speaker 1: from another deer? And is that why he was nighttime

1956
01:42:13,960 --> 01:42:16,880
Speaker 1: all all year last year? Holy Crappy had a small

1957
01:42:16,960 --> 01:42:19,760
Speaker 1: rack last year. Even though he went from three to four.

1958
01:42:19,760 --> 01:42:21,360
Speaker 1: He looked the same at age four that he did

1959
01:42:21,400 --> 01:42:24,559
Speaker 1: at age three. Oh he blew at age five? Has

1960
01:42:24,640 --> 01:42:27,479
Speaker 1: his help regained as he backed to the safe he

1961
01:42:27,560 --> 01:42:30,679
Speaker 1: was in at age three? Can I expect similar movement

1962
01:42:30,680 --> 01:42:32,760
Speaker 1: out of him at age five that a candid age three?

1963
01:42:32,840 --> 01:42:35,479
Speaker 1: Even though his methabolism is going to slow down. He's

1964
01:42:35,479 --> 01:42:38,800
Speaker 1: physiologically mature. Might he move a little better than he

1965
01:42:38,800 --> 01:42:41,080
Speaker 1: did at age four? So you can look at a

1966
01:42:41,120 --> 01:42:44,679
Speaker 1: deer's health from year to year, and almost almost every

1967
01:42:44,720 --> 01:42:47,559
Speaker 1: time it will be an indicator, along with weather and

1968
01:42:47,600 --> 01:42:51,200
Speaker 1: moon as to the overall amount of daylight activity he

1969
01:42:51,240 --> 01:42:55,720
Speaker 1: gave you. I also look at the herd dynamics. The

1970
01:42:55,800 --> 01:43:00,000
Speaker 1: population was I in a in a population area where

1971
01:43:00,000 --> 01:43:02,880
Speaker 1: are the doughs were way out of whack. Oh, all

1972
01:43:02,920 --> 01:43:05,760
Speaker 1: of a sudden they changed the season and we were

1973
01:43:05,760 --> 01:43:08,000
Speaker 1: allowed to take a lot more does or c W

1974
01:43:08,160 --> 01:43:10,479
Speaker 1: D sharpshooters winning and shot a lot more does or

1975
01:43:10,479 --> 01:43:13,920
Speaker 1: shot more dear and took the population down. Is he

1976
01:43:13,920 --> 01:43:17,280
Speaker 1: gonna move more because there are fewer dos available? Or conversely,

1977
01:43:17,760 --> 01:43:20,080
Speaker 1: the state took the dough limit down in this area

1978
01:43:20,400 --> 01:43:22,559
Speaker 1: there are more doughs. I'm seeing more doughs this year

1979
01:43:22,560 --> 01:43:24,840
Speaker 1: than I've ever seen. Is he gonna move less because

1980
01:43:24,840 --> 01:43:27,599
Speaker 1: there are more doughs available? So you have to look

1981
01:43:27,640 --> 01:43:31,519
Speaker 1: at almost every aspect that could affect that deer's movement

1982
01:43:31,600 --> 01:43:33,960
Speaker 1: and then put a game plan together on him. Because

1983
01:43:34,040 --> 01:43:36,519
Speaker 1: there are certain years where they moved very well and

1984
01:43:36,640 --> 01:43:39,040
Speaker 1: certain years where they don't. Some of that's help, some

1985
01:43:39,120 --> 01:43:41,160
Speaker 1: of that's weather, but a lot of it is just

1986
01:43:41,280 --> 01:43:44,759
Speaker 1: all the other aspects that influence him in an annual basis.

1987
01:43:45,360 --> 01:43:49,120
Speaker 1: Huh wow, you're you're blowing my mind right now, Mark,

1988
01:43:49,160 --> 01:43:51,439
Speaker 1: because those are a lot of interesting things to think about.

1989
01:43:51,520 --> 01:43:55,040
Speaker 1: And as you were walking through that like hypothetical scenario,

1990
01:43:55,120 --> 01:43:56,760
Speaker 1: a lot of it was kind of matching up with

1991
01:43:57,160 --> 01:44:00,920
Speaker 1: my holy Field situation last year because fifteen and sixteen

1992
01:44:00,960 --> 01:44:03,920
Speaker 1: he was very daylight active, he was following I kind of,

1993
01:44:04,120 --> 01:44:07,080
Speaker 1: he had some consistent behaviors, etcetera, etcetera. And then last year,

1994
01:44:07,479 --> 01:44:09,320
Speaker 1: Now this could also just because he was more mature,

1995
01:44:09,400 --> 01:44:13,360
Speaker 1: but last year he ghosted all of October. I wasn't

1996
01:44:13,400 --> 01:44:15,960
Speaker 1: getting many pictures, no daylight, Tavity, didn't do the things

1997
01:44:15,960 --> 01:44:18,599
Speaker 1: he's done the past. He showed up in early November

1998
01:44:18,640 --> 01:44:21,080
Speaker 1: for about a twelve day period and then he was

1999
01:44:21,120 --> 01:44:24,280
Speaker 1: a ghost. He was completely off all my cameras, no sightings,

2000
01:44:24,280 --> 01:44:27,320
Speaker 1: nothing for the next month and a half. And then

2001
01:44:27,439 --> 01:44:31,799
Speaker 1: I found his shed in January. So he shed really early.

2002
01:44:32,439 --> 01:44:37,280
Speaker 1: So maybe he kind of injury. Yeah, Yeah, something's naggot

2003
01:44:37,320 --> 01:44:39,200
Speaker 1: at him. When a deer's not moving during daylight and

2004
01:44:39,240 --> 01:44:41,560
Speaker 1: he should be. Something's naggingt at him. He's got a

2005
01:44:41,560 --> 01:44:43,920
Speaker 1: foot injury, he's got a horn that he got horn.

2006
01:44:43,960 --> 01:44:46,080
Speaker 1: He's got a touch of DHD. He's trying to recover

2007
01:44:46,200 --> 01:44:49,800
Speaker 1: from it. He's got some virus, he's got some infection,

2008
01:44:50,280 --> 01:44:52,599
Speaker 1: and he's not moving. Man. I've seen him. We've sat

2009
01:44:52,600 --> 01:44:56,439
Speaker 1: there and watched him freaking hoof rot in December. Bucks

2010
01:44:56,479 --> 01:44:58,920
Speaker 1: that have been moving great on all November, you get

2011
01:44:58,960 --> 01:45:01,839
Speaker 1: a muddy December. They get infection in their hoofs because

2012
01:45:02,720 --> 01:45:04,760
Speaker 1: of all the scratches on their hooves from running through

2013
01:45:04,760 --> 01:45:07,280
Speaker 1: the rut. They get a little infection that leg. Man,

2014
01:45:07,280 --> 01:45:09,680
Speaker 1: it shuts him down. They can hardly walk anymore. The

2015
01:45:09,720 --> 01:45:12,280
Speaker 1: next year, they don't. They don't move very well because

2016
01:45:12,320 --> 01:45:15,360
Speaker 1: they've had that infection. They didn't. They didn't do very well. Conversely,

2017
01:45:15,360 --> 01:45:18,439
Speaker 1: I've seen the opposite. If a deer gets injured early

2018
01:45:18,479 --> 01:45:21,320
Speaker 1: in the season, like October, he gets a cut all right,

2019
01:45:21,520 --> 01:45:24,800
Speaker 1: and then he doesn't participate in the rut. Sometimes that

2020
01:45:24,880 --> 01:45:28,800
Speaker 1: healing process that took place because of whatever bugged him

2021
01:45:28,880 --> 01:45:31,840
Speaker 1: in in September October that holds him out of the

2022
01:45:31,920 --> 01:45:35,360
Speaker 1: rut ends up making him an incredible calm the next

2023
01:45:35,439 --> 01:45:38,080
Speaker 1: year because he did not partake in the rut and

2024
01:45:38,080 --> 01:45:40,200
Speaker 1: and pull all of his body weight down. He was

2025
01:45:40,240 --> 01:45:43,000
Speaker 1: actually healing during the rut, and then the next years

2026
01:45:43,000 --> 01:45:46,040
Speaker 1: the year you see his rack explode. I I truly

2027
01:45:46,080 --> 01:45:48,519
Speaker 1: believe that that's one of the factors why you see

2028
01:45:48,560 --> 01:45:52,439
Speaker 1: these unbelievable monsters just pop up and you go, how

2029
01:45:52,520 --> 01:45:54,439
Speaker 1: in the hell did that happen? When he looked like

2030
01:45:54,520 --> 01:45:57,560
Speaker 1: this last year, It's probably because he did not participate

2031
01:45:57,640 --> 01:45:59,559
Speaker 1: much in the ruts the previous year, and it might

2032
01:45:59,560 --> 01:46:01,880
Speaker 1: have been an injury that that put him on the

2033
01:46:01,960 --> 01:46:04,519
Speaker 1: d L during the toughest period of their life each

2034
01:46:04,560 --> 01:46:07,479
Speaker 1: and every year, and that's why he rebounded, went through

2035
01:46:07,479 --> 01:46:09,839
Speaker 1: the winter healthy, and then came out of it smelling

2036
01:46:09,880 --> 01:46:13,240
Speaker 1: like a rose. Herd health and individual deer health has

2037
01:46:13,280 --> 01:46:16,559
Speaker 1: a lot to do with your ability to take any

2038
01:46:16,600 --> 01:46:19,280
Speaker 1: particular deer any year, and also what he's gonna look

2039
01:46:19,320 --> 01:46:22,400
Speaker 1: like when you take him. Yeah, yeah, I can I

2040
01:46:22,479 --> 01:46:26,280
Speaker 1: can see that being the case for sure. Um hm.

2041
01:46:27,720 --> 01:46:30,280
Speaker 1: All five year old all five year olds are not

2042
01:46:30,360 --> 01:46:32,880
Speaker 1: created different, are all not are all not created the same.

2043
01:46:33,160 --> 01:46:36,160
Speaker 1: All six year olds are not created equal. They are different.

2044
01:46:36,200 --> 01:46:40,080
Speaker 1: Animals with different personalities, dealing with different things in their life,

2045
01:46:40,200 --> 01:46:43,440
Speaker 1: and there's there are a lot like dogs or cats

2046
01:46:43,479 --> 01:46:46,639
Speaker 1: are people. I mean, there's stuff nagging at them out there.

2047
01:46:46,640 --> 01:46:48,840
Speaker 1: And the more you watch this herd health with c

2048
01:46:49,040 --> 01:46:52,080
Speaker 1: w D, e h D and the minerals that they

2049
01:46:52,120 --> 01:46:54,519
Speaker 1: take in, and what health they're in with drought, how

2050
01:46:54,640 --> 01:46:57,479
Speaker 1: much rainfall they got, what the winter was like the

2051
01:46:57,520 --> 01:47:01,960
Speaker 1: previous year, all of those things end up being factors

2052
01:47:02,000 --> 01:47:07,639
Speaker 1: that end up controlling Dear movement in future years. Look

2053
01:47:07,680 --> 01:47:11,000
Speaker 1: at how look at how subdued and the movement was

2054
01:47:11,520 --> 01:47:15,439
Speaker 1: following the e h D outbreak of twelve. Not only

2055
01:47:15,439 --> 01:47:17,599
Speaker 1: did we have fewer dear because they died, we had

2056
01:47:17,600 --> 01:47:19,800
Speaker 1: a sick herd that was trying to the ones that

2057
01:47:19,960 --> 01:47:21,880
Speaker 1: got it, that didn't die from it, we're trying to

2058
01:47:21,920 --> 01:47:24,400
Speaker 1: get rid of it. And it subdued the movement for

2059
01:47:24,439 --> 01:47:26,800
Speaker 1: the next couple of seasons. In my opinion, they just

2060
01:47:26,960 --> 01:47:29,880
Speaker 1: we didn't have as many. They weren't healthy. The racks

2061
01:47:29,920 --> 01:47:32,679
Speaker 1: look like crap. It took years to get that worked

2062
01:47:32,680 --> 01:47:35,040
Speaker 1: out of the herd. They're finally now getting back to

2063
01:47:35,040 --> 01:47:38,040
Speaker 1: where they should be, where the herd starts. The herd

2064
01:47:38,120 --> 01:47:41,280
Speaker 1: now to me resembles what it did in eleven and

2065
01:47:41,320 --> 01:47:44,400
Speaker 1: twelve before it hit. And here we are dealing with

2066
01:47:44,479 --> 01:47:48,160
Speaker 1: a monstrous drought in the Midwest again. It is almost

2067
01:47:48,200 --> 01:47:51,000
Speaker 1: unbelievable that we're put up against us again this year.

2068
01:47:52,920 --> 01:47:55,600
Speaker 1: But that's that's the way it goes, man, That's what

2069
01:47:55,640 --> 01:47:58,120
Speaker 1: they're dealing with every year. It's all weather related. Yea.

2070
01:48:00,080 --> 01:48:02,920
Speaker 1: So one last question on this annual pattern thing that

2071
01:48:02,920 --> 01:48:04,400
Speaker 1: that popped into my head as you were kind of

2072
01:48:04,400 --> 01:48:08,280
Speaker 1: walking through this um those couple of items there, And

2073
01:48:08,320 --> 01:48:10,559
Speaker 1: I've heard a couple of people theorize about this, and

2074
01:48:10,640 --> 01:48:14,679
Speaker 1: that is the idea of looking at annual patterns within

2075
01:48:15,160 --> 01:48:18,879
Speaker 1: doe family groups so that you might be able to

2076
01:48:19,000 --> 01:48:23,680
Speaker 1: predict when, like maybe a certain mature dough might go

2077
01:48:23,720 --> 01:48:25,800
Speaker 1: into Estra's at the same time every year. And if

2078
01:48:25,840 --> 01:48:28,320
Speaker 1: you know that the best dough betting are in your

2079
01:48:28,360 --> 01:48:32,160
Speaker 1: farm is over you know by the creek that whatever

2080
01:48:32,200 --> 01:48:34,840
Speaker 1: the most, that mature dough might be back there year

2081
01:48:34,840 --> 01:48:37,920
Speaker 1: after year, and she comes into Esther's the first dough

2082
01:48:38,400 --> 01:48:39,920
Speaker 1: you know every If she's the first one to come

2083
01:48:39,920 --> 01:48:42,799
Speaker 1: into Estros every year, you might know to focus there

2084
01:48:42,840 --> 01:48:44,680
Speaker 1: in a certain time frame. Is there anything to that

2085
01:48:44,720 --> 01:48:48,160
Speaker 1: you think how to percent accurate, I would adhere to that.

2086
01:48:49,120 --> 01:48:53,000
Speaker 1: I think that was very well articulated that that dear

2087
01:48:53,200 --> 01:48:55,559
Speaker 1: is not stupid. If he went there and she she

2088
01:48:55,680 --> 01:48:58,960
Speaker 1: came into Estra's early the previous year, guess who he's

2089
01:48:58,960 --> 01:49:01,160
Speaker 1: going to seek out early next year, He's not dumb.

2090
01:49:01,920 --> 01:49:05,360
Speaker 1: That is absolutely a true statement. And herd health goes

2091
01:49:05,400 --> 01:49:08,960
Speaker 1: into dose participation in the rut. If them honeys aren't

2092
01:49:08,960 --> 01:49:11,479
Speaker 1: out there moving around, those bucks don't have to move around.

2093
01:49:11,960 --> 01:49:15,120
Speaker 1: You know, how well the does move sometimes is indicative

2094
01:49:15,120 --> 01:49:17,160
Speaker 1: of how well the bucks are going to move, the

2095
01:49:17,240 --> 01:49:20,800
Speaker 1: dose or what caused the frenzy. Yeah. Yeah, So if

2096
01:49:20,840 --> 01:49:24,759
Speaker 1: you saw a particularly great amount of running activity during

2097
01:49:25,560 --> 01:49:28,840
Speaker 1: maybe maybe on this property early in the year, let's say,

2098
01:49:28,880 --> 01:49:31,599
Speaker 1: for whatever reason October twenty eight through the thirty one,

2099
01:49:31,800 --> 01:49:33,880
Speaker 1: it was just lights out on this property the last

2100
01:49:33,880 --> 01:49:36,800
Speaker 1: two years, it's probably good indicator that there's a reason

2101
01:49:36,880 --> 01:49:39,040
Speaker 1: for that, maybe outside of other factors, and that you

2102
01:49:39,040 --> 01:49:41,880
Speaker 1: should make sure to be at that spot again maybe

2103
01:49:41,880 --> 01:49:45,320
Speaker 1: around the time frame. Yes, but it could be a

2104
01:49:45,320 --> 01:49:47,639
Speaker 1: food source that has a certain dough group in that area.

2105
01:49:47,800 --> 01:49:50,040
Speaker 1: It may just be that there's more does there that year.

2106
01:49:50,040 --> 01:49:52,599
Speaker 1: It might be because there's acorns faller. The next year

2107
01:49:52,600 --> 01:49:54,320
Speaker 1: there may not be an acorn crop. They could be

2108
01:49:54,360 --> 01:49:56,920
Speaker 1: a half mile away on on a cut corn field,

2109
01:49:57,080 --> 01:49:58,760
Speaker 1: and then all of a sudden, the magic circle moves

2110
01:49:58,800 --> 01:50:02,440
Speaker 1: over there. So may sure you're trying to interpolate everything,

2111
01:50:02,920 --> 01:50:05,000
Speaker 1: you know, not just oh, it happened this year, so

2112
01:50:05,040 --> 01:50:07,599
Speaker 1: it's it's going to happen again next year. It might

2113
01:50:07,640 --> 01:50:11,000
Speaker 1: be three or four years before that same scenario happens again,

2114
01:50:11,240 --> 01:50:13,559
Speaker 1: but don't forget it because it's going to repeat itself

2115
01:50:13,600 --> 01:50:16,160
Speaker 1: at some point. You've got to look at everything else

2116
01:50:16,200 --> 01:50:18,599
Speaker 1: and and go why are they there? Are they there

2117
01:50:18,640 --> 01:50:20,679
Speaker 1: every year? Is it a food plot that I put

2118
01:50:20,720 --> 01:50:23,000
Speaker 1: there that wasn't there last year? You know? Is it

2119
01:50:23,040 --> 01:50:25,000
Speaker 1: a clover field that's green this year but it wasn't

2120
01:50:25,040 --> 01:50:27,200
Speaker 1: last year because we had a drought. Is it the

2121
01:50:27,240 --> 01:50:30,320
Speaker 1: acorns that are dropping early? You know, those types of things,

2122
01:50:30,880 --> 01:50:34,320
Speaker 1: So look at why the does are there? Yeah, that

2123
01:50:34,400 --> 01:50:36,360
Speaker 1: makes a lot of sense. So you see you see

2124
01:50:36,360 --> 01:50:39,800
Speaker 1: a pretty significant flip flop with the crop rotation then

2125
01:50:39,840 --> 01:50:41,519
Speaker 1: from corn to beans, corn to beans a lot of

2126
01:50:41,600 --> 01:50:50,280
Speaker 1: years massive, Yeah, it's massive. Yeah, yea yea, that makes sense. Well, Mark,

2127
01:50:50,320 --> 01:50:53,200
Speaker 1: I've kept you longer than I'm sure you wanted, probably,

2128
01:50:53,360 --> 01:50:55,600
Speaker 1: so I'm gonna I'm gonna let you get off the

2129
01:50:55,680 --> 01:50:58,200
Speaker 1: line now and get back to important things in life. Um.

2130
01:50:58,320 --> 01:51:02,600
Speaker 1: But this is, as it always is, fascinating. UM. I

2131
01:51:02,720 --> 01:51:04,960
Speaker 1: really appreciate taking the time to do this. And I

2132
01:51:05,040 --> 01:51:08,479
Speaker 1: guess any more details regarding dear casts that you want

2133
01:51:08,520 --> 01:51:10,599
Speaker 1: to share with the audience. We haven't talked about timing

2134
01:51:10,600 --> 01:51:12,320
Speaker 1: of when that's gonna be available yet. Can you talk

2135
01:51:12,320 --> 01:51:14,559
Speaker 1: about that too and anything else folks should know if

2136
01:51:14,560 --> 01:51:16,920
Speaker 1: they want to get their hands on that. When's your

2137
01:51:16,960 --> 01:51:19,680
Speaker 1: podcast going up? This is going to go out Thursday

2138
01:51:20,240 --> 01:51:25,280
Speaker 1: of next week, which is the twenty ninth. I think maybe,

2139
01:51:26,680 --> 01:51:28,920
Speaker 1: oh perfect timing, it will be available at twenty eight

2140
01:51:29,040 --> 01:51:34,560
Speaker 1: God willing, Fingers crossed. Fingers are very crossed. But I

2141
01:51:34,680 --> 01:51:39,800
Speaker 1: hope we have put a tremendous amount of support behind

2142
01:51:39,920 --> 01:51:43,320
Speaker 1: this app in terms of marketing, and our biggest fear

2143
01:51:43,439 --> 01:51:50,200
Speaker 1: is that it's something crashes so we won't know, you know,

2144
01:51:50,280 --> 01:51:51,760
Speaker 1: it's kind of like Y two K, We're not going

2145
01:51:51,800 --> 01:51:55,840
Speaker 1: to know where it happen here. So, UM, you know

2146
01:51:55,960 --> 01:51:58,680
Speaker 1: it's due out on so God willing it will be

2147
01:51:58,680 --> 01:52:02,960
Speaker 1: available in your podcast? Okay, okay, and they can find

2148
01:52:03,000 --> 01:52:05,360
Speaker 1: that just by going to is that available on Apple

2149
01:52:05,520 --> 01:52:07,720
Speaker 1: and Android and all those things, and just go to

2150
01:52:07,760 --> 01:52:11,040
Speaker 1: their app stores. You got it, Man, it's gonna be

2151
01:52:11,120 --> 01:52:14,479
Speaker 1: under deer cast d E E R C A S

2152
01:52:14,560 --> 01:52:19,679
Speaker 1: T one word deer cast. Perfect. Well. I'm definitely gonna

2153
01:52:19,680 --> 01:52:21,760
Speaker 1: be picking up as soon as it comes out, and

2154
01:52:22,160 --> 01:52:24,120
Speaker 1: I think, just based off what you've shared with us today,

2155
01:52:24,160 --> 01:52:25,920
Speaker 1: I gotta imagine there's gonna be a whole lot of

2156
01:52:25,960 --> 01:52:27,880
Speaker 1: other folks that are gonna be very intrigued to check

2157
01:52:27,920 --> 01:52:30,080
Speaker 1: it out as well. So I'm excited about it. Mark,

2158
01:52:30,800 --> 01:52:33,439
Speaker 1: Thanks for putting in all the work for that kind

2159
01:52:33,439 --> 01:52:35,120
Speaker 1: of thing, like, for putting in so much time and

2160
01:52:35,240 --> 01:52:37,160
Speaker 1: energy to create a tool like that for us hunters.

2161
01:52:37,479 --> 01:52:39,640
Speaker 1: I appreciate that, and I appreciate you being here and

2162
01:52:39,960 --> 01:52:43,680
Speaker 1: answering these questions. Man, I'm happy to do it. I

2163
01:52:43,800 --> 01:52:47,680
Speaker 1: hope everybody downloads it, enjoys all the different content in there,

2164
01:52:47,760 --> 01:52:50,599
Speaker 1: watches the kills as they happen. This year, looks back

2165
01:52:50,680 --> 01:52:52,920
Speaker 1: at some of our old VHS stuff. I've been sitting

2166
01:52:52,960 --> 01:52:55,599
Speaker 1: there watching videos that I haven't watched in twenty five years.

2167
01:52:55,720 --> 01:52:58,960
Speaker 1: I'm not joking of the Spring founder spring and I'm

2168
01:52:59,320 --> 01:53:01,960
Speaker 1: I'm thinking them stuff, what were we thinking? It's pretty

2169
01:53:02,000 --> 01:53:04,040
Speaker 1: funny if you want to have a laugh and the

2170
01:53:04,240 --> 01:53:06,360
Speaker 1: and the app, go into the old video section and

2171
01:53:06,439 --> 01:53:09,120
Speaker 1: watch it, and then of course deer cast. We're anxious

2172
01:53:09,160 --> 01:53:11,600
Speaker 1: to hear back from people how we can tweak it.

2173
01:53:11,720 --> 01:53:15,200
Speaker 1: The algorithm is relatively easy a tweak, and we're gonna

2174
01:53:15,240 --> 01:53:17,760
Speaker 1: be tweaking it as the seasons come and go. You know,

2175
01:53:17,920 --> 01:53:20,120
Speaker 1: if there's something that we're missing, we're gonna add it

2176
01:53:20,160 --> 01:53:22,200
Speaker 1: in there. If there's something that's a little too optimistic,

2177
01:53:22,280 --> 01:53:24,920
Speaker 1: we'll pull it down. And Uh, I think it's gonna

2178
01:53:24,920 --> 01:53:27,439
Speaker 1: be a tremendous tool for people to help them learn.

2179
01:53:27,560 --> 01:53:30,200
Speaker 1: And I hope everybody downloads it and and check it

2180
01:53:30,240 --> 01:53:31,800
Speaker 1: out and let us know what you think about it.

2181
01:53:31,880 --> 01:53:33,880
Speaker 1: That's one of the reasons we have it as as

2182
01:53:34,200 --> 01:53:36,599
Speaker 1: the inaugural season at at no charge. It's a pre

2183
01:53:36,680 --> 01:53:39,559
Speaker 1: app this year, uh next year will probably move into

2184
01:53:39,600 --> 01:53:41,679
Speaker 1: a pay model for certain parts of it. There's still

2185
01:53:41,720 --> 01:53:43,840
Speaker 1: be a large portion of it that will be free,

2186
01:53:43,880 --> 01:53:45,599
Speaker 1: but there will be certain portions of it that will

2187
01:53:45,640 --> 01:53:48,240
Speaker 1: be a pay model. But we want people to to

2188
01:53:48,400 --> 01:53:51,080
Speaker 1: get it, use it, feel it like it, UH like

2189
01:53:51,240 --> 01:53:52,560
Speaker 1: it or hate it, we want to know about it

2190
01:53:52,680 --> 01:53:54,639
Speaker 1: and we want to make it better, and we all

2191
01:53:54,920 --> 01:53:57,320
Speaker 1: we all get better if we learn. That's that's one

2192
01:53:57,400 --> 01:54:00,080
Speaker 1: thing I know. You never want to stop learning. That

2193
01:54:00,320 --> 01:54:02,320
Speaker 1: right there, I think is the perfect way to end

2194
01:54:02,360 --> 01:54:04,320
Speaker 1: this out right there. If all of us can continue

2195
01:54:04,360 --> 01:54:06,760
Speaker 1: to learn and grow his deer hunters, it's going to

2196
01:54:06,800 --> 01:54:09,479
Speaker 1: be a good thing. So I wish you all the

2197
01:54:09,520 --> 01:54:10,800
Speaker 1: lolong in the world. Mark, I hope you have an

2198
01:54:10,840 --> 01:54:14,280
Speaker 1: amazing season. Same to you. Are you still on Holy Field?

2199
01:54:14,320 --> 01:54:16,240
Speaker 1: Do you have pictures of it this year? So? He

2200
01:54:16,760 --> 01:54:19,560
Speaker 1: I found a shed, so I believe he's alive. He

2201
01:54:19,840 --> 01:54:22,360
Speaker 1: does not live on the farm. I can hunt during

2202
01:54:22,360 --> 01:54:24,240
Speaker 1: the summer. I've never got summer pictures of him. He

2203
01:54:24,280 --> 01:54:28,559
Speaker 1: always shows up, but you know, September seven somewhere around there. Um,

2204
01:54:28,800 --> 01:54:31,720
Speaker 1: so I'm hoping he shows back up again. Um, I

2205
01:54:31,840 --> 01:54:33,800
Speaker 1: just don't know. Yeah, I've seen there's a big eight

2206
01:54:33,880 --> 01:54:36,720
Speaker 1: point velvet buck that I've seen way off in the distance,

2207
01:54:37,600 --> 01:54:39,840
Speaker 1: a little ways away from that property that I think

2208
01:54:39,920 --> 01:54:42,600
Speaker 1: could maybe be him. But I can't stay on for sure,

2209
01:54:42,800 --> 01:54:46,840
Speaker 1: So the question still is unanswered. Your moon is very

2210
01:54:46,920 --> 01:54:49,240
Speaker 1: reminosus that this year, as it was in the fall

2211
01:54:49,280 --> 01:54:51,480
Speaker 1: of two thousand and sixteen. Those pictures should be very

2212
01:54:51,520 --> 01:54:53,840
Speaker 1: helpful to you. All right, Well that is a good

2213
01:54:53,920 --> 01:54:55,640
Speaker 1: pro tip. I'm gonna go take a look at those

2214
01:54:55,680 --> 01:54:59,240
Speaker 1: and think about that. So so I'm good at my man.

2215
01:54:59,320 --> 01:55:01,280
Speaker 1: Thank you, Mark, I appreciate you, all right, thank you?

2216
01:55:03,240 --> 01:55:07,000
Speaker 1: So what did you think about that one? Talk about

2217
01:55:07,160 --> 01:55:12,200
Speaker 1: just truckload of information, A lot to process there. If

2218
01:55:12,240 --> 01:55:13,960
Speaker 1: you're at all like me, you're probably gonna want to

2219
01:55:13,960 --> 01:55:16,240
Speaker 1: go back and listen to this one again. Maybe take notes,

2220
01:55:16,800 --> 01:55:19,240
Speaker 1: think back through different past situations of your own, think

2221
01:55:19,240 --> 01:55:24,000
Speaker 1: about future situations. It's it's just fascinating stuff. Mark's got

2222
01:55:24,080 --> 01:55:26,880
Speaker 1: a lot of interesting theories in this deer cast app.

2223
01:55:26,960 --> 01:55:28,520
Speaker 1: I think it's going to be a pretty neat tool.

2224
01:55:28,560 --> 01:55:30,800
Speaker 1: I've already been checking it out, and um, I like

2225
01:55:30,960 --> 01:55:34,640
Speaker 1: how it can kind of help you confirm or refute

2226
01:55:35,000 --> 01:55:37,560
Speaker 1: kind of what your assumptions or your theories might be

2227
01:55:37,720 --> 01:55:40,320
Speaker 1: about upcoming deer movement based on your own understanding of

2228
01:55:40,400 --> 01:55:43,120
Speaker 1: these factors. So hopefully you enjoyed this one as much

2229
01:55:43,160 --> 01:55:46,240
Speaker 1: as I did. Just want to remind you again follow

2230
01:55:46,240 --> 01:55:48,200
Speaker 1: along with my hunts. I take off here in just

2231
01:55:48,320 --> 01:55:51,440
Speaker 1: a couple of days for Montana and North Dakota. You

2232
01:55:51,520 --> 01:55:53,879
Speaker 1: can follow all that on the wire You're Done Instagram account,

2233
01:55:53,880 --> 01:55:56,960
Speaker 1: the Wireton YouTube channel, the Wireton Facebook page, and then

2234
01:55:57,040 --> 01:55:59,720
Speaker 1: we will continue with our podcasts as well. And by

2235
01:55:59,760 --> 01:56:03,800
Speaker 1: the way, radio kicks off next week two. So lots

2236
01:56:03,920 --> 01:56:06,320
Speaker 1: and lots of exciting things on the horizon, not to

2237
01:56:06,400 --> 01:56:08,960
Speaker 1: mention maybe your very own hunting seasons as well. And

2238
01:56:09,040 --> 01:56:10,400
Speaker 1: if you are going to be hit in the woods

2239
01:56:10,440 --> 01:56:13,400
Speaker 1: here in the coming weeks or month, good luck out there,

2240
01:56:13,440 --> 01:56:16,120
Speaker 1: shoot straight, enjoy your season. It's going to be a

2241
01:56:16,160 --> 01:56:19,200
Speaker 1: great one. I think we are all learning together throughout

2242
01:56:19,240 --> 01:56:21,480
Speaker 1: this process. We are all becoming better hunters, and I

2243
01:56:21,560 --> 01:56:23,400
Speaker 1: think this year it's all going to pay off. So

2244
01:56:23,880 --> 01:56:26,480
Speaker 1: thank you so much for joining us today and until

2245
01:56:26,560 --> 01:56:29,880
Speaker 1: next time, stay wired to Hunt.