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Speaker 1: Welcome to the Wired 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 in this episode number two sixty three,

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Speaker 1: and today's the final part of our two part two

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Speaker 1: thousand eighteen review, And today that means Spencer and I

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Speaker 1: are reviewing trends and observations about the two thousand eighteen

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Speaker 1: deer hunting season from across the country. All right, welcome

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Speaker 1: to another episode of the Wired to Hunt podcast, brought

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Speaker 1: to you by Onyx, and today we are kinda relatedly um,

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Speaker 1: but but better late than never. We're kind of wrapping

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Speaker 1: up our radio mini series that we had going throughout

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Speaker 1: the two thousand eighteen hunting season up until mid December.

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Speaker 1: Every week, as you probably remember, we chatted with hunters

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Speaker 1: across the country to find out what was happening out

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Speaker 1: in the woods. Howward, you're reacting to hunting pressure, to

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Speaker 1: different weather conditions, to changing food sources, to all sorts

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Speaker 1: of things like that, and then you know, discussing different

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Speaker 1: ways to take advantage of that. So Spencer is with

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Speaker 1: me and the two of us are kind of thought

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Speaker 1: for today's episode was to kind of look back at

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Speaker 1: the year from a radio perspective and look at this

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Speaker 1: kind of like thirty thousand foot overview of what were

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Speaker 1: some of the trends that we saw Spencer from all

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Speaker 1: the people that he talked to, what were some of

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Speaker 1: the things that that he heard consistently at different times

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Speaker 1: of year, and and are there anything we can learn

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Speaker 1: from that when we try to look back on like

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Speaker 1: the big patterns of two thousand and eighteen that maybe

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Speaker 1: we could apply to future years. Um. So, so that

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Speaker 1: that's kind of the game plan, Spencer. I know that

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Speaker 1: we've done this in the past. Do you do you

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Speaker 1: feel good about that game plan for today? Is there

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Speaker 1: anything you want to do differently or do you just

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Speaker 1: want to hop right into what you thought were some

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Speaker 1: of the major trends this here? Yes, So let's give

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Speaker 1: a little bit more context. This is the third season

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Speaker 1: Now Road Radio, with about a dozen episodes this year,

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Speaker 1: spanning from September to December UM. Last year, we did

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Speaker 1: a recap in January as well, and do you remember

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Speaker 1: what were a few of the main things that we

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Speaker 1: hit on that we thought were kind of the themes

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Speaker 1: for the seen Row. Do you recall what we talked

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Speaker 1: about Denmark? Okay, I feel like I'm back in high

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Speaker 1: school and I'm being quiz and I didn't do my homework.

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Speaker 1: I should have prepared for this. But if I can,

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Speaker 1: if I can go off of the top of my head,

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Speaker 1: I think the things that I remember standing out from

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Speaker 1: two thousand seventeen, Um, I remember we had some really

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Speaker 1: well timed cold friends, right, Yeah, that was the big

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Speaker 1: one for you know. I think we talked about how

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Speaker 1: if you pulled out a calendar at the beginning of

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Speaker 1: fall and you circled the dates that you wanted cold fronts,

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Speaker 1: that's what we got last year. You know. They were

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Speaker 1: hitting on like Fridays and Saturdays when guys were off

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Speaker 1: work and going to be in the woods. They were

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Speaker 1: coming at the end of October to the beginning of November.

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Speaker 1: They were just like the perfectly time cold fronts if

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Speaker 1: you like hunting cold fronts. Seventeen was the year. So

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Speaker 1: that was like the one big takeaway I think from

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Speaker 1: that year. Um, there were a few other things that

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Speaker 1: we touched on, and the other one that I think

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Speaker 1: was important was everybody we talked to, whether it was

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Speaker 1: like Arkansas Illinois, Kentucky, Uh, you know New York. Everyone

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Speaker 1: was talking about the massive acorn crop. Now that's something

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Speaker 1: that can be like super localized. Maybe not always a

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Speaker 1: national theme such as weather patterns can be, but I

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Speaker 1: think in overall, uh, everybody was talking about how the

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Speaker 1: acorns were affecting to your movement. Yeah. Now I wanna

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Speaker 1: I wanna continue establishing context here and and think back

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Speaker 1: a little bit on a prediction that you correct me

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Speaker 1: if I'm wrong, But didn't you make a prediction last

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Speaker 1: year that we're in for like an especially good year

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Speaker 1: as far as big healthy deer? Was that last year

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Speaker 1: that you thought that was gonna be the case based

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Speaker 1: off of kind of coming out of e h D

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Speaker 1: four years prior and a bunch of things like that.

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Speaker 1: So I think I wrote that piece for Wired to

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Speaker 1: Hunt back in like um, if I remember correctly, I

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Speaker 1: titled like We're in the glory days of white tail hunting,

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Speaker 1: and I was talking um kind of specifically about like

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Speaker 1: my part of the country in South Dakota, because we

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Speaker 1: just got hammered with the h D, Like there were

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Speaker 1: some counties that had estimates as high as loss um

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Speaker 1: And so coming out of that, I talked about how

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Speaker 1: then in like four years removed from that that UM

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Speaker 1: in the next few years, I was thinking would be

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Speaker 1: really good for hunters and deer because agencies were getting

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Speaker 1: out ahead of it, so they were cutting back on

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Speaker 1: tag numbers, populations were rebounding pretty quickly in most areas. UM,

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Speaker 1: we were getting like mature bucks that had not experienced

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Speaker 1: very much pressure. And so I thought all of those

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Speaker 1: things were kind of brewing for like some good years

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Speaker 1: to come, you know, with the timing of E H.

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Speaker 1: D hitting. Yeah, And I was thinking the same thing too,

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Speaker 1: because what you what you had in these areas, and

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Speaker 1: it wasn't just in South Dakota, I mean it was

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Speaker 1: it was pretty widespread across a lot of the Midwest

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Speaker 1: back in two thousand twelve and two thousand thirteen. So

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Speaker 1: in a bunch of localized areas you had deer populations,

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Speaker 1: you know, pretty dramatically in some spots being reduced. And

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Speaker 1: and I thought the same thing. I thought, Okay, any

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Speaker 1: deer that survived or the deer that were born that

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Speaker 1: following year, they're all of a sudden entering a world

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Speaker 1: where competition for resources is much less than it used

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Speaker 1: to be. So there's the same level of nutrition, but

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Speaker 1: much lower social stress, much less competition for food, much

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Speaker 1: less competition for the best betting. All these things lead

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Speaker 1: to those bucks that were starting their lives around that

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Speaker 1: time period. All of a sudden, we're like, I don't know,

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Speaker 1: if you and me like got dropped off at like

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Speaker 1: windsor Palace with all the food and resources and servants

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Speaker 1: we could possibly want, Like, we become really fat and

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Speaker 1: happy over the next four years. And so if you

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Speaker 1: took you know that let's say the two thousand thirteen

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Speaker 1: h D was the last really bad one across a

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Speaker 1: lot of the country. So if there was a deer

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Speaker 1: that was born that next year or even that spring,

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Speaker 1: right go four or five years out, now we're to

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Speaker 1: this year. Um So my question then being have you

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Speaker 1: seen her? Do you think? Now? I know this is

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Speaker 1: this is not quantitative in any way at all. This

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Speaker 1: is simply just based off you know, stories, we hear, pictures,

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Speaker 1: we see trying to look trying to guess on a trend,

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Speaker 1: just based off the vibe we're picking up. But you

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Speaker 1: and me we see and talk to a lot of

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Speaker 1: people in the hunting world. UM, I kind of feel

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Speaker 1: like that prediction kind of proved true over the last

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Speaker 1: couple of years. Um, there's been I wish I could

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Speaker 1: have quantified this. I wish we looked into it. UM,

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Speaker 1: But there have been a number of particularly large deer killed.

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Speaker 1: There's been a number of people, if we're just looking

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Speaker 1: at like very visible folks so quote unquote famous deer hunters,

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Speaker 1: and a lot of these people who consistently killed big

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Speaker 1: mature bucks, but the last year or two they're killing

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Speaker 1: their various biggest deer ever. Take for example, Mark Jury

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Speaker 1: last year in the year before it killed his first

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Speaker 1: plus deer this year and I started last year, Lelikowski

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Speaker 1: killed his first tower and then this year killed his

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Speaker 1: largest typical buck ever. Now again, you know, I'm not

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Speaker 1: trying to say this is what it's all about and

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Speaker 1: that's what matters. It's just kind of an interesting thing

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Speaker 1: to see. And I'm just curious if if the e

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Speaker 1: h D rebound had anything to do with some of

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Speaker 1: these deer reaching a genetic potential that maybe in past

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Speaker 1: years they wouldn't. UM, I don't know. Does any of

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Speaker 1: that ring true to you, Spencer? Yeah, I think so.

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Speaker 1: And I think maybe like one of the biggest things

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Speaker 1: that people thinking about the health of herds. UM when

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Speaker 1: that hit in two thousand twelve, I would have been

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Speaker 1: like nineteen years old or something. I feel like I

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Speaker 1: hadn't even heard of e h D up until that point,

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Speaker 1: and then all of a sudden, it was something that

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Speaker 1: everybody was aware of. Um, you know that it was

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Speaker 1: even coming up in some of my like college biology

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Speaker 1: classes that I don't think those professors had either ever

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Speaker 1: talked about it prior to that either. So even if

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Speaker 1: it um you know, physically did not make a difference

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Speaker 1: in two thousand twelve going forward, which I would say

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Speaker 1: that you and I agree it did, at least they

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Speaker 1: got people thinking about these things, maybe inspired somebody to

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Speaker 1: join q d m A, or inspired somebody to uh,

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Speaker 1: you know, go to college to be a wildlife biologists,

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Speaker 1: or put a put an extra watering hole in on

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Speaker 1: their property something like that. So, you know, two thousand

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Speaker 1: twelve was devastating, but there was a lot of silver

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Speaker 1: linings that came out of that. And uh, as we

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Speaker 1: were just talking about this, I pulled up that article

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Speaker 1: that I wrote that was on June two sixteen, and

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Speaker 1: some of the things I talked about were like, um,

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Speaker 1: you know, agencies took notice of deer herds being eliminated

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Speaker 1: and and you know, deer numbers being short. In Nebraska,

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Speaker 1: UH took away eighty seven thousand tags, Missouri cut back

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Speaker 1: and unlimited dough tags. Iowa eliminated forty one permits, South

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Speaker 1: Dakota removed forty percent of its rifle tags. Ohio reduced

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Speaker 1: analyst tags and forty four different counties. UM. So that

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Speaker 1: was one of the big things that uh, you know,

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Speaker 1: I think we get less pressure in the woods and

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Speaker 1: then yeah, like you talked about less competition for resources. Yeah,

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Speaker 1: and and to your point, it definitely did spark some

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Speaker 1: kind of attention within the deer hunting community because for

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Speaker 1: a long time, right, deer populations seem to be super healthy,

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Speaker 1: no big issues. Everyone was going along hunky dory, and

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Speaker 1: then there was this kind of sort of hard reset.

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Speaker 1: It was a combination of things. I mean, there's the

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Speaker 1: big h G that hit um over those couple of years.

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Speaker 1: There were also a lot of changes in habitat. I

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Speaker 1: remember coming out of that that time period talking with

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Speaker 1: Kip Adams from the Quality Deer Management Association. I can't

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Speaker 1: remember the numbers, but he spoke to the fact that

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Speaker 1: over that several year time period, the amount of land

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Speaker 1: that had formerly been in CRP or some kind of

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Speaker 1: cover that had been now changed into full blown just

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Speaker 1: agricultural cop crops. Um was there was a dramatic reduction

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Speaker 1: in c RP acreage, if I remember right. So a

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Speaker 1: bunch of different things were changing, resulting in kind of

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Speaker 1: tougher time for some of these populations. So, yeah, a

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Speaker 1: lot of populations dropped. I remember seeing you know, we

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Speaker 1: were talking about harvest numbers going down for a lot

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Speaker 1: of states. It was just a whole lot of attention

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Speaker 1: during those couple of years. Two thousand fourteen fifteen, I

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Speaker 1: think that was around that time period, and that's when

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Speaker 1: stuff like the National Deer Alliance started, um, the q

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Speaker 1: dum A started, i think readjusting some of their goals.

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Speaker 1: So it's an interesting point you made that um that

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Speaker 1: at the time there was a lot of worry about oh,

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Speaker 1: is this like the beginning of a sharp negative trend

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Speaker 1: within the deer hunting world. And I think we can

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Speaker 1: look at things now in two thousand and eighteen and say, hey,

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Speaker 1: like there was a hiccup there, but it seems like

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Speaker 1: either the hunting population or the management agencies are all

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Speaker 1: of us together kind of course corrected appropriately because at

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Speaker 1: least anecdotally, things sound like things sound that most things

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Speaker 1: are positive outside of you know, some disease issues like

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Speaker 1: c w D concerns and stuff like that. So I

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Speaker 1: don't know, man, this is a we're going really high

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Speaker 1: level now talking about several year trends, UM. But it

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Speaker 1: is interesting to to kind of look at that and

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Speaker 1: then zoom into this past year. So if that's the

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Speaker 1: larger trend over the last couple of years, UM, I

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Speaker 1: would say that I feel like two thousand eighteen continued

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Speaker 1: that trend, like I think over all, UM, would you

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Speaker 1: agree that most people looked at two thousand and eighteen positively.

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Speaker 1: It wasn't like a few years back where people like, oh,

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Speaker 1: this is one of the worst years we've had in

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Speaker 1: a long time, blah blah blah. No, I feel like

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Speaker 1: most folks said, hey, this felt like a good year. Um.

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Speaker 1: There was you know, good decent conditions. I mean, I

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Speaker 1: felt like there was a lot of success being had

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Speaker 1: across the country, right, I mean, super high level. Would

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Speaker 1: you agree with that too, Yeah, So let's get started

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Speaker 1: discussing some of that stuff. And I have you know,

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Speaker 1: like six points from eighteen then I think were the

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Speaker 1: themes of this last fall the first one of those

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Speaker 1: because that can I put a pause on you? Yes, sorry, Spencer. UM,

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Speaker 1: I am curious so well, I'm I'm looking at these

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Speaker 1: these things, and we've talked about these a little bit. Um,

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Speaker 1: I'm curious what like, if we were to put these

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Speaker 1: in order, are you going to one through these in

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Speaker 1: the order of significance you think, or are you gonna

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Speaker 1: go through these as far as um maybe the timelogically chronologically? Okay,

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Speaker 1: So then um, as we go along, I'm curious to

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Speaker 1: see if you and me. The point I'm getting too

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Speaker 1: is I'm curious if you and me feel the same

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Speaker 1: about the significance of some of these. So, um, as

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Speaker 1: we go along, I'll figure out some way to do that. Okay,

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Speaker 1: maybe I'll like crow like a bird over here or

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Speaker 1: something when I get to my number one, you know,

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Speaker 1: and you'll know that's my my top joy. Let's start

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Speaker 1: off your chronologically. And I think one of the biggest

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Speaker 1: factors uh that from from the rut and uh you know,

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Speaker 1: chronologically was that early October cold front that we had. Um,

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Speaker 1: it was something that we talked about on radio. I

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Speaker 1: think all four colors we had that week touched on it,

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Speaker 1: like you gotta get in the woods. We were coming

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Speaker 1: out of a long stretch I think of like some

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Speaker 1: stagnant whether maybe even above average temperatures, and then it

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Speaker 1: was around like October. Do you remember the specific date

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Speaker 1: tomorrow what happened? I know, I think it was it

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Speaker 1: was like the eleventh, third, I feel like the twelve,

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Speaker 1: at least here in Michigan. On the twelfth, we are

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Speaker 1: getting the rain from that front. And then it continued

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Speaker 1: like I think eleventh, even of the eleventh through like

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Speaker 1: the fifteen seemed to be that sweet spot for me

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Speaker 1: here in southern Michigan, so somewhere on that give or

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Speaker 1: take based on where you're in the country, right, And

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Speaker 1: it seemed like the entire country felt it too, like

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Speaker 1: from North Dakota, you know, over to the Caroline As

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Speaker 1: everyone got a bit of that cold front that came

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Speaker 1: through in early October. And we talked to him on

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Speaker 1: the podcast that yeah, you know, get in the woods, Bucks,

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Speaker 1: we're gonna be moving or whatever. And then after that

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Speaker 1: cold front passed, it seemed like social media lit up

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Speaker 1: with Big Bucks hitting the ground. Yeah, I d percent agree.

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Speaker 1: That was definitely something that stood out. Um. And and

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Speaker 1: in retrospect, like that was happening, people were talking about it,

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Speaker 1: everyone was excited. And I remember going out for for

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Speaker 1: one hunt myself, maybe two, Um, but I didn't hit

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Speaker 1: it super hard. And then I went out and checked

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Speaker 1: cameras on the eight or nineteenth or something on one

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Speaker 1: of the properties I guess that I hunt, and I

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Speaker 1: was kicking myself because I checked these cameras and it

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Speaker 1: was like full blown rut type of pictures. I mean,

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Speaker 1: every buck that I knew of in the area in daylight,

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Speaker 1: day after day, like all over the place. It was.

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Speaker 1: It was shocking how impactful that coal front was during

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Speaker 1: that time period, and it was for me. It was

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Speaker 1: one of those things where I didn't practice what I

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Speaker 1: preached a little bit where I was like maybe a

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Speaker 1: little bit too conservative. Like I knew the coal Front

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Speaker 1: was gonna be happening. I knew it was gonna be good,

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Speaker 1: but I didn't take advantage of it, probably as much

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Speaker 1: as I should have. I should have hit it really hard,

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Speaker 1: um in retrospect, because like you said, there were bucks

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Speaker 1: hitting the ground all over the place. Um, didn't. Wasn't

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Speaker 1: it during that time period that you saw Lieutenant Dan once?

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Speaker 1: Wasn't mid October? Writer on there? Yeah, it was right

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Speaker 1: around that call. I think was towards the end of

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Speaker 1: that cold front. Um. That was one of the few

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Speaker 1: sightings that I had of him, uh in the fall.

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Speaker 1: And so that, along with some other good deer movement

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Speaker 1: that I saw plus good trail, came intel from that

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Speaker 1: cold front. Uh. And then our callers who you know,

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Speaker 1: talked about, Hey, it's gonna be great deer movement, and

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Speaker 1: then a lot of them capitalized on it. I don't

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Speaker 1: remember who was on that episode specifically, but I think

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Speaker 1: like two or three out of the four people we

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Speaker 1: talked to went out and killed big Bucks. And then,

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Speaker 1: like I said, just the rest of you know, social

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Speaker 1: media echoing that and and seeing a lot of big

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Speaker 1: Bucks hitting the ground. And for me personally, this kind

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Speaker 1: of gave credence to like hunting around cold fronts. I've

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Speaker 1: always considered myself kind of like a cold front ruther

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Speaker 1: or uh someone Yeah yeah, And so like I liked to,

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Speaker 1: I remind myself and remind other people that, um, you know,

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Speaker 1: there have not been any studies that show a correlation

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Speaker 1: between like cold fronts and buck movement, and there's been

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Speaker 1: a lot of them done, and uh, you know a

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Speaker 1: number of biologists have had tried tracking this, but nobody

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Speaker 1: is seeing like positive influence on deer movement when we

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Speaker 1: experience a cold front. Now that goes against like almost

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Speaker 1: all calming hunting knowledge. And you know what you'll hear

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Speaker 1: like big buck experts talk about. And so I've always

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Speaker 1: leaned more towards the science. But man, seeing that happened, Uh,

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Speaker 1: that was kind of vindicating for those guys who say

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Speaker 1: cold fronts help you kill deer. Now in the same like,

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Speaker 1: if we're going to bring that up, we also need

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Speaker 1: to acknowledge that when those cold fronts come through, Uh,

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Speaker 1: a lot of people are sitting in their better stands,

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Speaker 1: Like they're hunting an area they normally wouldn't be. They're

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Speaker 1: hunting an area that they had maybe been holding off

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Speaker 1: for until we got a good cold front. They're more focused,

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Speaker 1: like they are doing more to control their scent. You know,

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Speaker 1: if if you're if you're more serious about it, you

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Speaker 1: think there's gonna be a deer walking by, You're more

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Speaker 1: folks into your entrance and exit. So I think just

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Speaker 1: in general, there's something to cold fronts making people a

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Speaker 1: better hunter because they're more confident and maybe they're hunting

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Speaker 1: areas that they've been you know, saving for that specific day.

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Speaker 1: So I think there's also still a lot of that

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Speaker 1: involved that hunter sees a cold frontcoming and uh, they're

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Speaker 1: hunting style changes. Yeah. I get your I get it,

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Speaker 1: I get your theory. This it's like a self fulfilling prophecy.

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Speaker 1: If you have that belief in the cold front, if

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Speaker 1: you have that confidence in it, you do things differently.

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Speaker 1: And there's probably some truth to that, um But I

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Speaker 1: just I just don't think you can deny the what

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Speaker 1: we just see year after year after year. And I

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Speaker 1: will say even Matt ross In in Lindsay Thomas Jr.

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Speaker 1: Both from the Quality Deer Management Association, both guys commonly

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Speaker 1: cite those studies that you reference there, even though they

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Speaker 1: are very familiar with studies. They both on this podcast

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Speaker 1: have said, but we know that dear move more than

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Speaker 1: in cold cold friends, that we've all seen it. Um.

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Speaker 1: So it just makes me always wonder, like how I

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Speaker 1: always and I've said so many times, I've never figured

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Speaker 1: out the right way to articulate it. But the how

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Speaker 1: researchers are measuring this delta in deer movement based off

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Speaker 1: cold fronts or or whether or something like that, I

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Speaker 1: feel like what they're measuring as statistically significant or not,

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Speaker 1: it's got to be different than what we as hunters do.

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Speaker 1: So maybe there's there's less than three percent increase in

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Speaker 1: total deer movement throughout the day. This is hypothetical numbers,

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Speaker 1: but maybe the researchers saw there's less than three percent

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Speaker 1: increase or decrease in deer movement based off whether so

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Speaker 1: it's not statistically significant, meaning whether it doesn't impact deer movement.

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Speaker 1: But if that three percent bump in dear movement is

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Speaker 1: actually six percent increase during daylight hours, and if that

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Speaker 1: six percent increase happens to typically be within the last

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Speaker 1: half hour of daylight and during that time period, it's

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Speaker 1: actually a increase a movement Because you're looking at this narrative,

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Speaker 1: like I feel like these different things. When you narrow

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Speaker 1: the scope of what you're specifically looking for, all of

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Speaker 1: a sudden, it might actually lead to something different. So

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Speaker 1: I wish and maybe maybe this has been done. I

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Speaker 1: can't remember every single study, but it would be really

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Speaker 1: interesting to see if if folks could measure this from

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Speaker 1: like a hunter's perspective, like what really matters, Like what's

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Speaker 1: the total distance moved from a betting location to a

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Speaker 1: food location? Does that increase um a few days after

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Speaker 1: a weather system or does the amount of time on

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Speaker 1: foot change the two or three days after a cold front?

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Speaker 1: Like those kinds of things would be very hunter centric

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Speaker 1: and focus. Um, that would be really interesting to me. Um.

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Speaker 1: I don't know if that's done or not. And I'm

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Speaker 1: I'm admittedly a hypocrite on this, Like if I see

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Speaker 1: a cold front coming up, I get excited about it.

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Speaker 1: I'm doing the same thing as everyone else. I'm hunting

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Speaker 1: a better stand. Uh. You know, I am changing my

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Speaker 1: hunting habits. Uh like everyone else does. Who gets excited

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Speaker 1: about a cold front? So I say all that, and

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Speaker 1: I cite the science, but I still feel the same

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Speaker 1: way that there is likely uh you know, better buck

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Speaker 1: movement and your odds are better of killing a mature

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Speaker 1: animal when we get those cold fronts. And you know,

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Speaker 1: what are your thoughts on this? Mark that maybe like

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Speaker 1: the early October cold front like around that tenth, eleventh, twelve, thirteen, fourteenth,

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Speaker 1: whatever it was, that that like makes a bigger difference

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Speaker 1: for buck movement than if we got it at the

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Speaker 1: end of October. After seeing what happened here in do

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Speaker 1: you think that those cold fronts are like better or

402
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Speaker 1: more preferred than maybe if you go on any other

403
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Speaker 1: time in the year, Like, how would you now bank

404
00:21:45,600 --> 00:21:48,879
Speaker 1: the significance of the cold front in early October versus

405
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Speaker 1: other times of year. Yeah, so I think that your

406
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Speaker 1: increased value is higher when you get a cold front

407
00:22:00,080 --> 00:22:03,200
Speaker 1: that's you know, in early to mid part of October

408
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Speaker 1: or late in the season versus closer to the rut.

409
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Speaker 1: Because closer to the rut, you're already going to get

410
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Speaker 1: that increase in dear activity because of rising hormones, stops

411
00:22:13,119 --> 00:22:15,199
Speaker 1: from love, everything around the rut ramping up as you

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Speaker 1: get into late October into November. That stuff is happening

413
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Speaker 1: regardless of weather. Whether definitely can accentuate it, they can

414
00:22:22,480 --> 00:22:27,000
Speaker 1: definitely amplify it, or it can dampen it. But you know,

415
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Speaker 1: it's not quite as make or break while if you

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Speaker 1: get this kind of coal front on October eleventh, when

417
00:22:33,359 --> 00:22:36,359
Speaker 1: typically a lot of things are causing deer movement to

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Speaker 1: maybe not be quite as visible because of hunting pressure

419
00:22:39,440 --> 00:22:41,840
Speaker 1: because of you know, changing food, so all the all

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Speaker 1: the things that people, um kind of see as an

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Speaker 1: October level. Um, when you have this mega cold front

422
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Speaker 1: hit right at that time, we saw, all of a sudden,

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Speaker 1: what would typically be a slower time of year for

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Speaker 1: most people, or maybe even the slowest time of year

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Speaker 1: for a lot of people, all of a sudden became

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Speaker 1: like one of the top couple day periods of the

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Speaker 1: entire season. I think if we were to if we

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Speaker 1: were to rank by a couple of day periods throughout

429
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Speaker 1: the year, that's got to be one of the best

430
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Speaker 1: chunks of time this entire season. Um. So yeah, I

431
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Speaker 1: think you had a really high impact. And for me,

432
00:23:14,359 --> 00:23:16,960
Speaker 1: just like you said, this is another great reminder that

433
00:23:17,359 --> 00:23:19,320
Speaker 1: when you have those fronts hitting, and the big thing

434
00:23:19,359 --> 00:23:22,880
Speaker 1: for me was that they might be so important when

435
00:23:22,920 --> 00:23:25,240
Speaker 1: they hit at times like this, that you change your

436
00:23:25,280 --> 00:23:29,000
Speaker 1: strategy completely um at times. So for me, like I

437
00:23:29,200 --> 00:23:33,800
Speaker 1: would I uber conservative in the middle of October usually, um,

438
00:23:33,880 --> 00:23:35,960
Speaker 1: that probably would have been a time to strike. And

439
00:23:36,000 --> 00:23:39,560
Speaker 1: a friend like like my buddy Andy Andy May had

440
00:23:39,560 --> 00:23:43,320
Speaker 1: this kind of thing October twelve called front hit it's raining.

441
00:23:43,800 --> 00:23:46,120
Speaker 1: He struck, He went into one of his best properties

442
00:23:46,160 --> 00:23:49,439
Speaker 1: and killed an awesome mature buck. Um, I didn't do

443
00:23:49,480 --> 00:23:51,639
Speaker 1: that and I didn't kill him mature buck. So that

444
00:23:51,720 --> 00:23:53,399
Speaker 1: was another AHA moment for me. I think is a

445
00:23:53,440 --> 00:23:57,040
Speaker 1: good reminder that, um, those are days that you know

446
00:23:57,880 --> 00:24:00,639
Speaker 1: it's worth taking a swing at. And I think, uh,

447
00:24:01,080 --> 00:24:04,560
Speaker 1: like talking about the October law transitions nicely into our

448
00:24:04,600 --> 00:24:09,000
Speaker 1: next subject, which is the acorn crop of eighteen. Now,

449
00:24:10,320 --> 00:24:15,000
Speaker 1: this is maybe more of a theme in because of

450
00:24:15,040 --> 00:24:17,919
Speaker 1: what it was in seventeen. Like I said before, I

451
00:24:17,920 --> 00:24:20,159
Speaker 1: think that was like one of the biggest factors of

452
00:24:20,160 --> 00:24:23,679
Speaker 1: the seventeen rut. Uh And one of the things that

453
00:24:23,720 --> 00:24:26,240
Speaker 1: came up all the time on Route radio was the

454
00:24:26,280 --> 00:24:30,159
Speaker 1: massive acorn crop. Nowen it seemed like from people we

455
00:24:30,200 --> 00:24:32,679
Speaker 1: talked to that it was like an average to below

456
00:24:32,760 --> 00:24:37,800
Speaker 1: average acorn crop, and so maybe not like super significant

457
00:24:37,800 --> 00:24:39,359
Speaker 1: when it came to deer movement. But if you were

458
00:24:39,440 --> 00:24:42,840
Speaker 1: somebody who came out of the fall of Seen and

459
00:24:42,880 --> 00:24:45,480
Speaker 1: had these ideas about how bucks were moving in mid

460
00:24:45,520 --> 00:24:49,560
Speaker 1: October and what you know, your property sets up like

461
00:24:49,640 --> 00:24:52,560
Speaker 1: for mid October, and we're basing that off of like

462
00:24:52,600 --> 00:24:57,280
Speaker 1: a massive, massive acorn crop, then maybe eighteen was very

463
00:24:57,359 --> 00:25:01,240
Speaker 1: different for you, and uh, you know, created a bigger

464
00:25:01,320 --> 00:25:04,359
Speaker 1: learning curve because that huge acorn cropples in there and

465
00:25:04,520 --> 00:25:07,280
Speaker 1: it seemed like it was an average year for acorns

466
00:25:07,320 --> 00:25:10,880
Speaker 1: in much of the country. Yeah, I felt I felt

467
00:25:10,920 --> 00:25:14,000
Speaker 1: similarly both, you know, for my own personal experiences and

468
00:25:14,040 --> 00:25:18,080
Speaker 1: here mother folks that this year now it's it can

469
00:25:18,119 --> 00:25:22,040
Speaker 1: be pretty localized. Like there's some people who talk to like, oh, man, acorns,

470
00:25:22,040 --> 00:25:24,199
Speaker 1: that's where it's at, because there's gonna be some of

471
00:25:24,200 --> 00:25:27,640
Speaker 1: those little spots where there's mega crops. I actually, um

472
00:25:27,680 --> 00:25:29,840
Speaker 1: on one of the properties I hunt did have a

473
00:25:29,880 --> 00:25:33,120
Speaker 1: ton of acorns this year, um, and that maybe could

474
00:25:33,160 --> 00:25:35,160
Speaker 1: have been part of the reason why I didn't see

475
00:25:35,200 --> 00:25:37,760
Speaker 1: as much activity on some of the usual food sources.

476
00:25:37,880 --> 00:25:42,200
Speaker 1: So I think that I think maybe my takeaway from

477
00:25:42,240 --> 00:25:45,600
Speaker 1: that this year is just a reminder to me and

478
00:25:45,640 --> 00:25:48,440
Speaker 1: all of us of how important that crop is, whether

479
00:25:48,480 --> 00:25:51,760
Speaker 1: it's there or not. And what I probably need to

480
00:25:51,800 --> 00:25:54,919
Speaker 1: do a better job of each year is trying to

481
00:25:54,960 --> 00:25:57,960
Speaker 1: figure that out. You know, do your do your late

482
00:25:58,000 --> 00:26:02,240
Speaker 1: summer scouting um of food sources and really figure out, Okay,

483
00:26:02,480 --> 00:26:04,280
Speaker 1: what is the mass crop like this year, and how

484
00:26:04,320 --> 00:26:07,639
Speaker 1: does that change things? Uh, it's easy. I'm guilty of

485
00:26:07,680 --> 00:26:10,840
Speaker 1: lots of times just focusing on the egg and thinking, Okay,

486
00:26:10,840 --> 00:26:13,679
Speaker 1: I got corn in this field, I've got beans in

487
00:26:13,720 --> 00:26:17,240
Speaker 1: this one, uh lfalfa and this one, and and think

488
00:26:17,280 --> 00:26:20,760
Speaker 1: about too much how that impacts the deer and to

489
00:26:20,840 --> 00:26:24,160
Speaker 1: the exclusion of of hard masks and and and even

490
00:26:24,240 --> 00:26:26,880
Speaker 1: soft mass. Now, soft masses is obviously something that's usually

491
00:26:26,920 --> 00:26:30,720
Speaker 1: not as widespread but locally on certain properties apple trees

492
00:26:30,800 --> 00:26:33,960
Speaker 1: or simmons or whatever. Um, those things could all really

493
00:26:34,040 --> 00:26:37,520
Speaker 1: change dear behavior. So I think it's probably just another

494
00:26:37,560 --> 00:26:40,800
Speaker 1: reminder that that's something you don't want to overlook. Um,

495
00:26:41,160 --> 00:26:43,240
Speaker 1: you probably don't have a ton of mass in South Dakota,

496
00:26:43,520 --> 00:26:48,360
Speaker 1: by you do not very much. Like I've said before, Um,

497
00:26:48,600 --> 00:26:53,520
Speaker 1: South Dakota ranks like third in terms of least amount

498
00:26:53,600 --> 00:26:56,600
Speaker 1: of trees per square miles. So uh, we just don't

499
00:26:56,640 --> 00:26:59,639
Speaker 1: have a lot of hardwoods the way it is, and

500
00:27:00,240 --> 00:27:04,080
Speaker 1: specifically where I hunt, there are like where I hunt,

501
00:27:04,280 --> 00:27:06,960
Speaker 1: there's probably not an acorn for five miles. So it's

502
00:27:07,000 --> 00:27:10,159
Speaker 1: nothing that has ever been on my radar much. But

503
00:27:10,560 --> 00:27:13,320
Speaker 1: when it comes to rot radio, that is often like

504
00:27:13,680 --> 00:27:16,800
Speaker 1: something on imprompted that comes up and is a number

505
00:27:16,800 --> 00:27:21,440
Speaker 1: one factor for guys like in mid October. Yeah, Now,

506
00:27:21,640 --> 00:27:26,200
Speaker 1: did you have any um, any trends that you kinda

507
00:27:26,600 --> 00:27:28,080
Speaker 1: you had your finger on the pulse a little bit

508
00:27:28,119 --> 00:27:32,679
Speaker 1: more than me. But as far as egg crops um,

509
00:27:32,720 --> 00:27:35,320
Speaker 1: either of that being the quality of food available this

510
00:27:35,400 --> 00:27:38,400
Speaker 1: year or the timing of when things came out this year,

511
00:27:38,880 --> 00:27:41,040
Speaker 1: was there anything like that that you think impact of

512
00:27:41,040 --> 00:27:43,440
Speaker 1: the deer season. I've got a few things that maybe did,

513
00:27:43,480 --> 00:27:46,880
Speaker 1: but I'm curious from your perspective, was there any other big,

514
00:27:47,160 --> 00:27:50,240
Speaker 1: far reaching food related trends outside of the acorn crop

515
00:27:52,200 --> 00:27:54,960
Speaker 1: if you want to talk about like big egg, then

516
00:27:55,280 --> 00:27:57,000
Speaker 1: that would go to our next point as far as

517
00:27:57,080 --> 00:28:00,040
Speaker 1: how I feel that affected things? Was the really that

518
00:28:00,240 --> 00:28:03,880
Speaker 1: fall that we had um for some areas like September

519
00:28:03,920 --> 00:28:07,879
Speaker 1: and October were record breaking months for the amount of

520
00:28:07,880 --> 00:28:12,000
Speaker 1: precipitation that in certain states or certain counties got UM.

521
00:28:12,200 --> 00:28:14,800
Speaker 1: And that was another thing that came up on tons

522
00:28:14,800 --> 00:28:19,399
Speaker 1: of episodes of radio was how rain was affecting deer movement,

523
00:28:19,400 --> 00:28:22,520
Speaker 1: affecting deer patterns, things like that, and then the long

524
00:28:22,640 --> 00:28:25,919
Speaker 1: term effective that one of those things was creating a

525
00:28:26,000 --> 00:28:30,479
Speaker 1: late harvest. Because when you constantly have brain um, you know,

526
00:28:31,040 --> 00:28:34,560
Speaker 1: throughout mid October that was keeping the fields really wet

527
00:28:34,840 --> 00:28:39,200
Speaker 1: and keep from other fields. And so maybe compared to

528
00:28:39,400 --> 00:28:41,920
Speaker 1: the last few years, this year was a really late

529
00:28:42,000 --> 00:28:45,760
Speaker 1: harvest um for for most areas, I think, And so

530
00:28:45,840 --> 00:28:47,920
Speaker 1: that is something that would affect dear movement when it

531
00:28:47,960 --> 00:28:51,200
Speaker 1: comes to food sources. And I think the primary factor

532
00:28:51,280 --> 00:28:54,120
Speaker 1: for that was the amount of rain that we had. Yeah,

533
00:28:54,440 --> 00:28:58,120
Speaker 1: definitely definitely felt that, heard that saw that. I know

534
00:28:58,200 --> 00:28:59,760
Speaker 1: there are a lot of people around me here and

535
00:29:00,000 --> 00:29:02,720
Speaker 1: in Michigan that we're actually still taking out corn here

536
00:29:02,400 --> 00:29:07,320
Speaker 1: in December, so that that's pretty indicative of that that

537
00:29:07,400 --> 00:29:11,720
Speaker 1: wet fall theory. And uh, again, I think most people

538
00:29:12,400 --> 00:29:15,880
Speaker 1: are aware of this, but for new hunters especially, it's

539
00:29:15,920 --> 00:29:17,560
Speaker 1: something to think about when you have a lot of

540
00:29:17,600 --> 00:29:21,320
Speaker 1: egg around where you hunt, keeping in mind when those

541
00:29:21,320 --> 00:29:23,560
Speaker 1: crops are coming out and thinking about how that's going

542
00:29:23,600 --> 00:29:26,120
Speaker 1: to impact dear not just when the crops are coming out,

543
00:29:26,120 --> 00:29:29,640
Speaker 1: but also when the crops mature and change, right, being

544
00:29:29,680 --> 00:29:33,760
Speaker 1: aware of how deer feeding habits change as crops change

545
00:29:34,480 --> 00:29:36,600
Speaker 1: at a super high level. You know, where I hunt

546
00:29:36,920 --> 00:29:39,440
Speaker 1: most of the time, it's it's beans and corn most

547
00:29:39,440 --> 00:29:42,160
Speaker 1: of the area, So you're seeing you know, dear really

548
00:29:42,200 --> 00:29:44,200
Speaker 1: being in the soybeans in the summer when they're green,

549
00:29:44,440 --> 00:29:47,560
Speaker 1: and then as those soybeans start to yellow. Now, I know, Spencer,

550
00:29:47,600 --> 00:29:49,600
Speaker 1: you did a little looking into this and maybe you

551
00:29:49,640 --> 00:29:53,320
Speaker 1: can offer different thoughts, but usually the attractiveness of those

552
00:29:53,680 --> 00:29:57,280
Speaker 1: yellowing and drying soybean leaves that goes down and then

553
00:29:57,400 --> 00:30:01,800
Speaker 1: you see green um summer corn not being all that attractive.

554
00:30:01,800 --> 00:30:04,600
Speaker 1: But as that dries into the fall, then deer start

555
00:30:04,640 --> 00:30:08,040
Speaker 1: craving the carbohydrates that corn has and as it gets

556
00:30:08,040 --> 00:30:10,360
Speaker 1: cold or they start getting pulled to those grains more

557
00:30:10,400 --> 00:30:12,200
Speaker 1: and more and more. So once you get to that

558
00:30:12,240 --> 00:30:14,240
Speaker 1: cold weather time period, then all of a sudden, corn

559
00:30:14,720 --> 00:30:18,480
Speaker 1: and the actual beans from soybeans become very attractive. So

560
00:30:18,520 --> 00:30:20,720
Speaker 1: that's another one of those things that just to keep

561
00:30:20,760 --> 00:30:23,640
Speaker 1: in mind as a as a new hunter, you want

562
00:30:23,680 --> 00:30:27,640
Speaker 1: to understand how deer are transitioning from food source to

563
00:30:27,640 --> 00:30:30,160
Speaker 1: food source as the year progresses, because that can really

564
00:30:30,280 --> 00:30:34,120
Speaker 1: change where you want to hunt. Um, I'm sure you

565
00:30:34,120 --> 00:30:37,200
Speaker 1: you've seen all those same things, right, Yeah. And I

566
00:30:37,760 --> 00:30:40,480
Speaker 1: looked back to the episode that we had in August

567
00:30:40,600 --> 00:30:44,040
Speaker 1: when it was me you further and Dan Uh and

568
00:30:44,120 --> 00:30:46,920
Speaker 1: Dan and I had talked about how like he onto

569
00:30:47,040 --> 00:30:50,800
Speaker 1: Iwah hunted in South Dakota, that the deck gets reshoffled

570
00:30:50,840 --> 00:30:54,480
Speaker 1: when harvest happens. Um, just because like you'll have bucks

571
00:30:54,520 --> 00:30:57,080
Speaker 1: that are literally betting in those fields. If they find

572
00:30:57,080 --> 00:30:59,920
Speaker 1: a low spot in a you know, a corn field,

573
00:31:00,160 --> 00:31:03,360
Speaker 1: they'll bed there or you know that kind of thing.

574
00:31:03,400 --> 00:31:05,440
Speaker 1: So we can change like where they're betting, and it

575
00:31:05,440 --> 00:31:09,240
Speaker 1: will change where they're feeding. And so that is always, uh,

576
00:31:09,280 --> 00:31:12,600
Speaker 1: you know, a big change for archery hunters when that

577
00:31:12,680 --> 00:31:16,240
Speaker 1: harvest happens. And this year, with how wet things were,

578
00:31:16,520 --> 00:31:19,400
Speaker 1: you probably felt that reshuffling of the deck a little

579
00:31:19,400 --> 00:31:23,680
Speaker 1: bit later than normal. Yeah. And the one possible benefit

580
00:31:23,880 --> 00:31:26,240
Speaker 1: of it, I've always thought, I've always been kind of

581
00:31:26,280 --> 00:31:28,560
Speaker 1: a fan of years when the corn stays in the

582
00:31:28,560 --> 00:31:32,200
Speaker 1: extra long and that this is selfish, um, But when

583
00:31:32,200 --> 00:31:34,600
Speaker 1: the corn stays in at least around where I hunt

584
00:31:34,600 --> 00:31:39,000
Speaker 1: here in Michigan, that becomes a sanctuary for deer. And

585
00:31:39,120 --> 00:31:43,040
Speaker 1: if the corn is standing after or on November fift

586
00:31:43,280 --> 00:31:46,080
Speaker 1: on opening day of gunn season, I believe there's a

587
00:31:46,200 --> 00:31:50,960
Speaker 1: dramatically lower number of young bucks getting killed because a

588
00:31:50,960 --> 00:31:53,480
Speaker 1: lot of these bucks in general probably um, they know

589
00:31:53,680 --> 00:31:57,200
Speaker 1: to stay in there, to stay safe. They're not they're

590
00:31:57,200 --> 00:31:59,200
Speaker 1: not being seen by hunters. So there's a lot of

591
00:31:59,240 --> 00:32:01,080
Speaker 1: deer that probably would have made it through those first

592
00:32:01,080 --> 00:32:04,400
Speaker 1: couple of days. Um, that do when you've got standing

593
00:32:04,440 --> 00:32:06,520
Speaker 1: corn the air, So I'm not staying would be a

594
00:32:06,560 --> 00:32:08,640
Speaker 1: good thing all the time, because of course, you know,

595
00:32:08,680 --> 00:32:11,280
Speaker 1: these deer populations have to be haunted and taken, but

596
00:32:11,960 --> 00:32:15,320
Speaker 1: selfishly in a small term or small time kind of deal.

597
00:32:15,360 --> 00:32:17,160
Speaker 1: I kind of like it when there's a standing cornfield

598
00:32:17,200 --> 00:32:19,280
Speaker 1: if I'm hoping that a buck or two might make

599
00:32:19,320 --> 00:32:21,840
Speaker 1: it through. Um. But of course, then if you're actually

600
00:32:21,840 --> 00:32:23,240
Speaker 1: trying to kill that deer, you can make it tough

601
00:32:23,240 --> 00:32:26,320
Speaker 1: for you to So something to think about. Well, let's

602
00:32:26,400 --> 00:32:28,960
Speaker 1: pause now for a quick second to think. Our partners

603
00:32:29,000 --> 00:32:32,800
Speaker 1: at white Tail Properties and Spencer will take it from

604
00:32:32,800 --> 00:32:34,880
Speaker 1: here with a quick chat with a white Tail Properties

605
00:32:34,960 --> 00:32:38,560
Speaker 1: land specialist. This week with white Tail Properties, we are

606
00:32:38,640 --> 00:32:42,800
Speaker 1: joined by Tom James, a land specialist out of Central Indiana,

607
00:32:42,960 --> 00:32:44,680
Speaker 1: and Tom is going to be telling us about what

608
00:32:44,760 --> 00:32:48,000
Speaker 1: the very first habitat improvements should be for a land manager.

609
00:32:49,760 --> 00:32:53,200
Speaker 1: Good question. Um. Some of the first key things, the

610
00:32:53,200 --> 00:32:55,920
Speaker 1: fundamentals if you want to think about, is when you

611
00:32:56,000 --> 00:33:00,200
Speaker 1: think in terms of what a deer requires, the food, security, covering, water,

612
00:33:01,000 --> 00:33:03,240
Speaker 1: and the qd m A has a great analogy of

613
00:33:03,320 --> 00:33:06,760
Speaker 1: the thinking about the lowest hole on the bucket that

614
00:33:06,800 --> 00:33:08,360
Speaker 1: you need to plug out to keep the water from

615
00:33:08,400 --> 00:33:12,960
Speaker 1: leaking out. So what could be missing on your property

616
00:33:13,240 --> 00:33:16,280
Speaker 1: that the surrounding land they have, and so you want

617
00:33:16,280 --> 00:33:19,000
Speaker 1: to do a quick assessment. Maybe it's food, Maybe it's water,

618
00:33:19,080 --> 00:33:21,719
Speaker 1: maybe if you can, maybe it's cover. If you can

619
00:33:21,720 --> 00:33:23,800
Speaker 1: look through your woods and see two dred yards, then

620
00:33:23,840 --> 00:33:26,880
Speaker 1: you've got an issue with with too much shade, not

621
00:33:27,040 --> 00:33:31,520
Speaker 1: enough sunlight creating new potential brows and cover for your deer.

622
00:33:31,560 --> 00:33:35,440
Speaker 1: So maybe it's a timber a timber either stand improvement

623
00:33:35,520 --> 00:33:37,760
Speaker 1: or a harvest or a combination of two that's gonna

624
00:33:37,800 --> 00:33:40,040
Speaker 1: allow some more new growth to come in and picking

625
00:33:40,080 --> 00:33:42,920
Speaker 1: up your property. Maybe it's as simple as you're not

626
00:33:43,040 --> 00:33:46,120
Speaker 1: leaving an area alone as a sanctuary. If you're trapesing

627
00:33:46,120 --> 00:33:48,479
Speaker 1: all over forty acres and pushing deer off every time

628
00:33:48,560 --> 00:33:51,080
Speaker 1: you go, then that's that's obviously an issue. So maybe

629
00:33:51,080 --> 00:33:53,960
Speaker 1: it's just an adjustment in the way that you move

630
00:33:54,000 --> 00:33:57,080
Speaker 1: around and hunt the property and approach things. Uh, if

631
00:33:57,120 --> 00:34:00,840
Speaker 1: food is your lacking ingredient or your lowest hole in

632
00:34:00,880 --> 00:34:03,680
Speaker 1: the bucket. Then even in timber it takes some work,

633
00:34:03,800 --> 00:34:07,280
Speaker 1: but you can certainly clear out some openings and plant food.

634
00:34:07,840 --> 00:34:12,000
Speaker 1: Um and I would suggest considering both perennial food and

635
00:34:12,080 --> 00:34:14,200
Speaker 1: annual food stuff that you can leave in like clover

636
00:34:14,239 --> 00:34:17,080
Speaker 1: and chicory as a perennial coming back every year and

637
00:34:17,120 --> 00:34:19,759
Speaker 1: do some fall planted cereal grains and brassicas for the

638
00:34:19,760 --> 00:34:22,080
Speaker 1: fall time. So you've got a year round program going on.

639
00:34:22,880 --> 00:34:25,719
Speaker 1: And typically it's not an issue in the Midwest. But

640
00:34:25,800 --> 00:34:28,400
Speaker 1: if if water is a lacking ingredient, then maybe you

641
00:34:28,400 --> 00:34:30,880
Speaker 1: can create a water hole or even some of the

642
00:34:30,880 --> 00:34:34,759
Speaker 1: new systems like the banks water watering tanks that you

643
00:34:34,800 --> 00:34:36,600
Speaker 1: can set up that are mobile and fill up and

644
00:34:36,719 --> 00:34:38,960
Speaker 1: provide water sources for your deer so that they don't

645
00:34:39,040 --> 00:34:42,359
Speaker 1: have to leave the property to water. Again, that's fairly rare,

646
00:34:42,400 --> 00:34:46,040
Speaker 1: but that could be a consideration. If you'd like to

647
00:34:46,120 --> 00:34:48,680
Speaker 1: learn more and to see the properties that Tom currently

648
00:34:48,719 --> 00:34:53,359
Speaker 1: has listed for sale, visit whitetail properties dot com. Backslash

649
00:34:53,600 --> 00:34:58,320
Speaker 1: James that's j. A. M. E. S. So let's touch

650
00:34:58,360 --> 00:35:01,520
Speaker 1: more on like the amount of precipitation that we had

651
00:35:01,560 --> 00:35:05,560
Speaker 1: in October and September. Um, this question I think you

652
00:35:05,600 --> 00:35:08,360
Speaker 1: get all the time, mark is how does rain affect

653
00:35:08,360 --> 00:35:11,800
Speaker 1: dear movement? And what I mean by that is like instantaneously,

654
00:35:11,960 --> 00:35:15,080
Speaker 1: say you go out for an evening sit and it

655
00:35:15,239 --> 00:35:19,160
Speaker 1: is pouring rain or sprinkling or whatever. Um, how does

656
00:35:19,280 --> 00:35:22,880
Speaker 1: that affect a bucks movement? Because that's something that people

657
00:35:22,920 --> 00:35:29,319
Speaker 1: will probably experiencing and wondering a lot in Yeah, good question, um,

658
00:35:29,320 --> 00:35:32,240
Speaker 1: And I do get this question a ton. Every time

659
00:35:32,440 --> 00:35:34,239
Speaker 1: it gets to be October and November and you've got

660
00:35:34,280 --> 00:35:36,400
Speaker 1: a big rainstorm moving across the country, you'll start to

661
00:35:36,440 --> 00:35:39,440
Speaker 1: see these tweets show up or Facebook messages. So it

662
00:35:39,560 --> 00:35:44,080
Speaker 1: is something to address. And my perspective might be a

663
00:35:44,120 --> 00:35:47,879
Speaker 1: little bit different than some folks, UM. I know, like

664
00:35:47,920 --> 00:35:50,400
Speaker 1: talking to Dan and other folks in Iowa and some

665
00:35:50,440 --> 00:35:53,719
Speaker 1: of these other states have a little bit lower hunting pressure. Um,

666
00:35:53,840 --> 00:35:56,479
Speaker 1: they've kind of pointed to these real rainy, dreary days

667
00:35:56,480 --> 00:36:00,640
Speaker 1: and say, mah, not that good. Um. I have seen

668
00:36:00,960 --> 00:36:03,960
Speaker 1: in Michigan that when you've got a rainy day, it

669
00:36:04,160 --> 00:36:06,840
Speaker 1: is one of the very best days of the season.

670
00:36:07,000 --> 00:36:11,200
Speaker 1: So I try to prioritize rainy, nasty days just like

671
00:36:11,239 --> 00:36:14,000
Speaker 1: a cold front hitting them and oftentimes they come together. Right,

672
00:36:14,000 --> 00:36:15,920
Speaker 1: you got a cold front pushing through and the rain

673
00:36:16,040 --> 00:36:19,040
Speaker 1: comes through. Um So that might be just the fact

674
00:36:19,120 --> 00:36:22,439
Speaker 1: that it's it's coinciding with other factors that increased deer movement.

675
00:36:22,480 --> 00:36:25,239
Speaker 1: But whatever it is, UM, I have found rainy days

676
00:36:25,280 --> 00:36:27,680
Speaker 1: to be great days to see that mature buck that

677
00:36:27,760 --> 00:36:31,359
Speaker 1: usually doesn't move in daylight, that rainy, dreary, cooler day

678
00:36:32,239 --> 00:36:34,399
Speaker 1: might be the one day he does it. I've seen

679
00:36:34,440 --> 00:36:36,040
Speaker 1: it time and time again with a lot of the

680
00:36:36,080 --> 00:36:39,200
Speaker 1: bucks I've hunted over the last six to ten years.

681
00:36:39,200 --> 00:36:42,440
Speaker 1: Probably I can point to numerous examples, especially in Michigan

682
00:36:42,600 --> 00:36:45,760
Speaker 1: and um And I brought this up in the past,

683
00:36:46,440 --> 00:36:48,000
Speaker 1: and I don't know if there's any credence to this

684
00:36:48,080 --> 00:36:54,160
Speaker 1: at all. This is purely um purely spitball in here.

685
00:36:54,280 --> 00:36:57,000
Speaker 1: But John Eberhart had always talked about the fact that

686
00:36:57,040 --> 00:37:00,960
Speaker 1: he thought that it might be hunting pressure related and

687
00:37:01,160 --> 00:37:05,200
Speaker 1: that these mature bucks felt safer on those rainy, crappy

688
00:37:05,320 --> 00:37:10,600
Speaker 1: days because typically humans aren't encountered on those days. Humans

689
00:37:10,640 --> 00:37:12,120
Speaker 1: just don't go out in the woods is often in

690
00:37:12,200 --> 00:37:15,040
Speaker 1: those days, whether it be hunters or anyone. Um So

691
00:37:15,120 --> 00:37:17,759
Speaker 1: his theory as I remember was that that might be

692
00:37:17,800 --> 00:37:20,759
Speaker 1: part of the reason why these deer feel more comfortable. Um.

693
00:37:20,800 --> 00:37:22,680
Speaker 1: I don't know if there's anything to it, but it's

694
00:37:22,719 --> 00:37:26,840
Speaker 1: certainly seemed to be the case for me. Um. So

695
00:37:27,080 --> 00:37:33,920
Speaker 1: that said, I do think that drizzly days, steady rain days, um,

696
00:37:34,120 --> 00:37:35,520
Speaker 1: I'm gonna be out in the tree stand if I

697
00:37:35,560 --> 00:37:40,480
Speaker 1: can be. If it's absolutely torrential downpour like monsoon, then yeah,

698
00:37:40,640 --> 00:37:43,760
Speaker 1: I'm seeing those deer hunker down bed and not moving.

699
00:37:44,520 --> 00:37:48,680
Speaker 1: But oftentimes I will still go out and hunt because

700
00:37:48,719 --> 00:37:50,719
Speaker 1: if there's a break in that weather, or if there's

701
00:37:50,760 --> 00:37:54,239
Speaker 1: like an expected break an hour before daylight, hour before

702
00:37:54,320 --> 00:37:57,480
Speaker 1: dark or something like that, just after the monsoon passes,

703
00:37:57,560 --> 00:37:59,560
Speaker 1: or whenever that little break in the weather happens, that

704
00:37:59,640 --> 00:38:01,759
Speaker 1: can be huge trigger and you get a bunch of

705
00:38:01,800 --> 00:38:04,400
Speaker 1: deer moving then right afterwards. And if you are you know,

706
00:38:04,400 --> 00:38:06,919
Speaker 1: if you took the whole day off, the whole evening

707
00:38:07,000 --> 00:38:09,080
Speaker 1: hunt off because it was gonna rain most of the day,

708
00:38:09,440 --> 00:38:12,279
Speaker 1: you missed out on that twenty minute window that all

709
00:38:12,280 --> 00:38:14,160
Speaker 1: of a sudden, there's these deer moving all over the place.

710
00:38:14,560 --> 00:38:16,600
Speaker 1: So I like try to take advantage of as much

711
00:38:16,680 --> 00:38:19,200
Speaker 1: as possible, even though it's not always fun. If you're

712
00:38:19,239 --> 00:38:22,840
Speaker 1: getting rained on the whole set um, it's usually worth while.

713
00:38:23,880 --> 00:38:26,799
Speaker 1: I would just caution. My one thing with rainy day

714
00:38:26,840 --> 00:38:29,080
Speaker 1: sits is that you do have to think about the

715
00:38:29,080 --> 00:38:33,480
Speaker 1: implications on tracking. Right, if you shoot a deer, you

716
00:38:33,560 --> 00:38:36,080
Speaker 1: possibly could lose blood on a rainy day, So I

717
00:38:36,360 --> 00:38:39,839
Speaker 1: significantly reduced my range. You know, on a rainy day,

718
00:38:40,360 --> 00:38:42,880
Speaker 1: I wouldn't shoot anything like outside twenty yards, like it

719
00:38:42,920 --> 00:38:46,560
Speaker 1: has to be like a guaranteed pinwheel, perfect double long shop.

720
00:38:47,080 --> 00:38:50,000
Speaker 1: And then you know, if that deer runs off and

721
00:38:50,000 --> 00:38:52,880
Speaker 1: you don't feel confident with where you last saw him, Um,

722
00:38:52,920 --> 00:38:55,239
Speaker 1: that's the kind of situation where if it's legal in

723
00:38:55,239 --> 00:38:59,440
Speaker 1: your state, you know, plan on knowing where a tracking

724
00:38:59,480 --> 00:39:02,240
Speaker 1: dog is someone that has a tracking dog, because tracking

725
00:39:02,280 --> 00:39:05,680
Speaker 1: dogs can still easily track in rain, so you can

726
00:39:05,680 --> 00:39:08,799
Speaker 1: find these dear Obviously that's a must. You have to

727
00:39:08,800 --> 00:39:11,399
Speaker 1: recover that deer. If you don't think you recover that deer,

728
00:39:11,400 --> 00:39:13,880
Speaker 1: then then you shouldn't be hunting out there. But tracking

729
00:39:13,920 --> 00:39:16,239
Speaker 1: dogs can can definitely help you do that. And in

730
00:39:16,320 --> 00:39:19,919
Speaker 1: the case again referencing Andy, um killed that nice buck

731
00:39:19,920 --> 00:39:23,200
Speaker 1: October twelve, started raining just as like I can't started

732
00:39:23,280 --> 00:39:26,120
Speaker 1: rain just before you shot the deer just afterwards, um,

733
00:39:26,160 --> 00:39:28,239
Speaker 1: but he was worried about losing the blood trail. We

734
00:39:28,360 --> 00:39:30,440
Speaker 1: got another friend out there with a dog and walked

735
00:39:30,640 --> 00:39:33,920
Speaker 1: right to the buck. Um. So so those are my

736
00:39:34,120 --> 00:39:37,520
Speaker 1: long and rambling thoughts on rainy day deer. Do you

737
00:39:37,719 --> 00:39:41,719
Speaker 1: disagree or agree with any of that, Spencer, I, I

738
00:39:41,840 --> 00:39:44,919
Speaker 1: really don't have strong feelings one way or the other

739
00:39:44,960 --> 00:39:47,279
Speaker 1: when it comes to rain affecting deer movement. And I

740
00:39:47,280 --> 00:39:49,600
Speaker 1: think that's probably the case for a lot of guys,

741
00:39:49,960 --> 00:39:52,440
Speaker 1: you know, whereas you talk about like cold fronts that

742
00:39:52,800 --> 00:39:56,759
Speaker 1: can inspire some really heated debate. So you talk about acorns,

743
00:39:56,800 --> 00:39:58,800
Speaker 1: people are really passionate about how that can change to

744
00:39:58,840 --> 00:40:01,480
Speaker 1: your movement. But I would say for most hunters, uh

745
00:40:02,000 --> 00:40:06,560
Speaker 1: that there's probably just not enough evidence of our affected

746
00:40:07,000 --> 00:40:10,000
Speaker 1: some of their hunts. And so I don't put too

747
00:40:10,120 --> 00:40:12,640
Speaker 1: much stock and way or the other into if rain

748
00:40:12,800 --> 00:40:16,799
Speaker 1: is going to positively negatively affect dear movement. I'm it's

749
00:40:16,800 --> 00:40:20,600
Speaker 1: probably not going to a change like what my strategy

750
00:40:20,680 --> 00:40:23,080
Speaker 1: is for specific cont what stand I'm going to sit

751
00:40:23,120 --> 00:40:26,720
Speaker 1: in here, anything like that. So let's talk about something

752
00:40:26,800 --> 00:40:31,200
Speaker 1: else that does cause debate within the hunting community about

753
00:40:31,200 --> 00:40:33,480
Speaker 1: whether or not it impacts deer movement, and that is

754
00:40:34,040 --> 00:40:37,960
Speaker 1: the moon and um, this year, I feel like there

755
00:40:38,040 --> 00:40:41,640
Speaker 1: was a lot of talk around moon moon phase, moon times,

756
00:40:42,600 --> 00:40:49,120
Speaker 1: red moon, blue moon, green moon, um, running moon. We

757
00:40:49,239 --> 00:40:52,520
Speaker 1: both noticed this this year, right, there's there's some interesting

758
00:40:52,560 --> 00:40:57,080
Speaker 1: things around that this year. Uh. Yeah, I think that

759
00:40:57,239 --> 00:40:59,480
Speaker 1: what you're going to bring up here is probably your

760
00:40:59,600 --> 00:41:03,319
Speaker 1: number or one factor for the ut But carry on,

761
00:41:04,280 --> 00:41:06,359
Speaker 1: Yeah I didn't. I didn't crow like a bird, but yes,

762
00:41:06,400 --> 00:41:10,240
Speaker 1: this was probably this is probably the number one factor

763
00:41:10,320 --> 00:41:13,080
Speaker 1: as far as a standout time period during the year,

764
00:41:13,280 --> 00:41:17,640
Speaker 1: something that seemed to have a disproportionate impact on results. Um.

765
00:41:17,680 --> 00:41:21,200
Speaker 1: And it's a little bit surprising to me because I

766
00:41:21,200 --> 00:41:25,880
Speaker 1: have always looked at moon related things similarly to you, Spencer,

767
00:41:25,920 --> 00:41:29,160
Speaker 1: and that the science, the studies have always shown there's

768
00:41:29,200 --> 00:41:31,759
Speaker 1: not an impact on dear moment. Based off all these

769
00:41:31,760 --> 00:41:34,320
Speaker 1: different studies I've looked into, at least nothing substantial. I

770
00:41:34,680 --> 00:41:37,560
Speaker 1: have seen a handful that maybe say, okay, there's a

771
00:41:37,560 --> 00:41:39,040
Speaker 1: little bit of this, a little bit of that, but

772
00:41:39,120 --> 00:41:43,239
Speaker 1: nothing um that really would be worth hunters keying in on.

773
00:41:43,680 --> 00:41:47,680
Speaker 1: But you get all these hunters that claim that it

774
00:41:47,719 --> 00:41:50,080
Speaker 1: does make it make a difference. So you've got the

775
00:41:50,080 --> 00:41:53,520
Speaker 1: theories around the moon and the rut. Some people believe

776
00:41:53,640 --> 00:41:57,640
Speaker 1: that this rutting moon that happens it's the oh gosh,

777
00:41:57,680 --> 00:42:01,080
Speaker 1: she's it's the first full moon after the automacinox. Is

778
00:42:01,120 --> 00:42:05,320
Speaker 1: that right? Or the second full moon after automacinox. I'm

779
00:42:05,440 --> 00:42:08,200
Speaker 1: sounds right. I'm blanking on the on the first or

780
00:42:08,239 --> 00:42:11,399
Speaker 1: second forgive me for that um. But usually this moon

781
00:42:11,560 --> 00:42:15,799
Speaker 1: falls somewhere between late October and late November, and the

782
00:42:15,800 --> 00:42:18,960
Speaker 1: theory is that based on when that moon hits, it

783
00:42:19,040 --> 00:42:23,440
Speaker 1: will influence the kind of kickoff point of the rut,

784
00:42:24,160 --> 00:42:28,080
Speaker 1: and studies show that's just simply not true, at least

785
00:42:28,120 --> 00:42:32,319
Speaker 1: as far as the timing of actual breeding. Study after

786
00:42:32,360 --> 00:42:35,960
Speaker 1: study after study. When you look and see you measure fetuses,

787
00:42:36,040 --> 00:42:38,560
Speaker 1: you can back date when these deer were bred. You

788
00:42:38,600 --> 00:42:41,359
Speaker 1: can see it's every year. It's a pretty darn consistent

789
00:42:41,920 --> 00:42:45,120
Speaker 1: peak of breeding across most of the country and most

790
00:42:45,160 --> 00:42:48,040
Speaker 1: places across the country, Somewhere in mid November is your

791
00:42:48,040 --> 00:42:52,560
Speaker 1: peak breeding date meeting or excuse me, meaning that across

792
00:42:52,640 --> 00:42:54,839
Speaker 1: most of the country, the couple of weeks leading up

793
00:42:54,840 --> 00:42:56,640
Speaker 1: to that will be when you see a lot of

794
00:42:56,640 --> 00:43:00,239
Speaker 1: the chasing, the seeking, the daylight activity that we want

795
00:43:00,239 --> 00:43:04,160
Speaker 1: to see his deer hunters. So that's always made me think, well,

796
00:43:04,200 --> 00:43:06,160
Speaker 1: I'm not going to care about when the running moon

797
00:43:06,320 --> 00:43:09,960
Speaker 1: is too much um or another one. You hear folks

798
00:43:09,960 --> 00:43:14,640
Speaker 1: like Adam Hayes, even even Dan in fault Erdquisto. Different

799
00:43:14,640 --> 00:43:16,920
Speaker 1: folks talk about this red moon, which is when the

800
00:43:16,920 --> 00:43:21,319
Speaker 1: moon is directly overhead or directly under foot. Um. Those

801
00:43:21,400 --> 00:43:23,000
Speaker 1: happened a few times a year we get these red

802
00:43:23,000 --> 00:43:24,560
Speaker 1: moon dates. I have a couple of buddies who are

803
00:43:24,600 --> 00:43:26,960
Speaker 1: really big on the red moon. UM. And again I

804
00:43:27,040 --> 00:43:29,480
Speaker 1: kind of I've always been intrigued. I watch it, I

805
00:43:29,560 --> 00:43:32,400
Speaker 1: kind of pay attention to it, but I've never really,

806
00:43:33,000 --> 00:43:35,560
Speaker 1: you know, been too focused on kiing and on it.

807
00:43:35,920 --> 00:43:39,400
Speaker 1: Another moon related theory, UM is if the moon is

808
00:43:39,520 --> 00:43:41,560
Speaker 1: rising or setting during the last part of the day

809
00:43:41,680 --> 00:43:44,480
Speaker 1: or the beginning of the day. So all these different

810
00:43:44,480 --> 00:43:46,480
Speaker 1: moon theories out there, the one that's relevant to what

811
00:43:46,560 --> 00:43:48,720
Speaker 1: we're talking about here, and I probably should just focused

812
00:43:48,719 --> 00:43:51,000
Speaker 1: on that was the running moon one that I mentioned there.

813
00:43:51,320 --> 00:43:54,359
Speaker 1: And this this running moon this year was an early one.

814
00:43:54,800 --> 00:43:58,800
Speaker 1: It occurred October twenty fourth, or fifth, or six or seventh,

815
00:43:58,840 --> 00:44:01,080
Speaker 1: somewhere around there was when the running moon hit. So

816
00:44:01,120 --> 00:44:05,800
Speaker 1: the theory being, if the theory held true, Um, supposedly

817
00:44:06,200 --> 00:44:09,400
Speaker 1: you're supposed to see a pick up in running activity

818
00:44:09,840 --> 00:44:14,399
Speaker 1: much earlier this year. So supposedly late October, we're gonna

819
00:44:14,400 --> 00:44:17,520
Speaker 1: see this big burst of daylight activity from bucks starting

820
00:44:17,560 --> 00:44:19,560
Speaker 1: to get after doughs. There're gonna be some does coming

821
00:44:19,560 --> 00:44:22,720
Speaker 1: into EST's usually earlier than usual, and it was gonna

822
00:44:22,800 --> 00:44:25,879
Speaker 1: lead to this this earlier than usual run. I didn't

823
00:44:25,880 --> 00:44:28,680
Speaker 1: really give him much credit leading to the season. And

824
00:44:28,800 --> 00:44:32,920
Speaker 1: then I head out to Nebraska on October and I'm

825
00:44:32,960 --> 00:44:36,800
Speaker 1: hunting on the twenty and I see a big mature

826
00:44:36,800 --> 00:44:39,360
Speaker 1: buck cruising during daylight at three in the afternoon. And

827
00:44:39,360 --> 00:44:42,520
Speaker 1: then I see another big mature buck cruising at four

828
00:44:42,600 --> 00:44:44,839
Speaker 1: thirty or five in the afternoon. This is like three

829
00:44:44,880 --> 00:44:47,719
Speaker 1: or four hours before dark. Um. And then I get

830
00:44:47,760 --> 00:44:49,759
Speaker 1: home that night after shooting that buck, not home. I

831
00:44:49,760 --> 00:44:51,799
Speaker 1: get back to the tent that night and I pull

832
00:44:51,920 --> 00:44:54,239
Speaker 1: up my phone and I see that this guy killed

833
00:44:54,280 --> 00:44:55,879
Speaker 1: the big mature buck. And this guy killed the big

834
00:44:55,880 --> 00:44:57,600
Speaker 1: mature buck. And then the next day the same thing.

835
00:44:57,640 --> 00:45:00,080
Speaker 1: And over the next three to four days, three to

836
00:45:00,200 --> 00:45:05,400
Speaker 1: five days, maybe somewhere between that, maybe October to somewhere

837
00:45:05,400 --> 00:45:08,840
Speaker 1: in that ballpark. It was like it was it was

838
00:45:08,880 --> 00:45:11,799
Speaker 1: as if we were watching your Instagram feed in November eight.

839
00:45:12,400 --> 00:45:14,279
Speaker 1: You know, it's just like guy and girl and guy

840
00:45:14,280 --> 00:45:16,960
Speaker 1: and girl ganger. Everyone was just killing deer and and

841
00:45:17,040 --> 00:45:20,680
Speaker 1: big mature deer during that time period, way way earlier

842
00:45:20,719 --> 00:45:24,719
Speaker 1: than you usually see that kind of quantity. Um. That

843
00:45:24,800 --> 00:45:28,080
Speaker 1: was like the vibe I was picking up and and

844
00:45:28,120 --> 00:45:31,200
Speaker 1: you kind of saw the same thing too, right, Yeah,

845
00:45:31,360 --> 00:45:34,719
Speaker 1: I had probably like my best string of sits this

846
00:45:34,800 --> 00:45:41,319
Speaker 1: year was from I think like November, excuse me, October, Um,

847
00:45:41,640 --> 00:45:44,319
Speaker 1: I had like I think I had an encounter on

848
00:45:44,360 --> 00:45:47,200
Speaker 1: every single hunt with a mature buck. Um my trail

849
00:45:47,280 --> 00:45:49,640
Speaker 1: cameras like a few weeks later when I was able

850
00:45:49,680 --> 00:45:52,960
Speaker 1: to gather some of that data, that was like a

851
00:45:53,040 --> 00:45:55,960
Speaker 1: super hot time for them as far as mature bucks

852
00:45:56,040 --> 00:45:58,759
Speaker 1: being on their feet in daylight. That was even like

853
00:45:58,800 --> 00:46:01,640
Speaker 1: one of the few times I had Dan on camera

854
00:46:01,760 --> 00:46:05,799
Speaker 1: was October, I believe, um, like one of a few

855
00:46:05,800 --> 00:46:09,560
Speaker 1: times I had him on daylight on camera like throughout

856
00:46:09,680 --> 00:46:11,799
Speaker 1: the fall, even during the rut, and so just from

857
00:46:11,840 --> 00:46:14,560
Speaker 1: my personal encounters and my trail cameras and talking about

858
00:46:14,560 --> 00:46:17,160
Speaker 1: a few specific deer and then like you said, the

859
00:46:17,880 --> 00:46:22,520
Speaker 1: like social media big bucks that you saw hitting the ground. Uh,

860
00:46:22,800 --> 00:46:26,400
Speaker 1: it seemed like that gave him credence to the early

861
00:46:26,680 --> 00:46:32,600
Speaker 1: running moon. So now here's the question everything we're picking

862
00:46:32,680 --> 00:46:34,920
Speaker 1: up on again where we haven't don't quantify this in anyway.

863
00:46:34,960 --> 00:46:36,920
Speaker 1: I wish there was some way that you could. We

864
00:46:36,960 --> 00:46:40,000
Speaker 1: need to build an app, or we need to build

865
00:46:40,000 --> 00:46:45,839
Speaker 1: an algorithm that can measure dear related hashtags something like that,

866
00:46:45,920 --> 00:46:48,200
Speaker 1: like like b b D or something like that, and

867
00:46:48,280 --> 00:46:51,360
Speaker 1: measure the quantity of b b D hashtags on Instagram

868
00:46:51,360 --> 00:46:53,919
Speaker 1: and Facebook and then map that out over the course

869
00:46:53,920 --> 00:46:57,680
Speaker 1: of the season so you can see how that hashtag rises.

870
00:46:57,719 --> 00:47:01,720
Speaker 1: I bet you that actually would core relate to harvest.

871
00:47:02,120 --> 00:47:04,279
Speaker 1: You know, I think that'd be a really interesting thing.

872
00:47:04,280 --> 00:47:06,239
Speaker 1: If there's anyone out there who knows how to do that,

873
00:47:07,680 --> 00:47:09,279
Speaker 1: do it and send it to me, because I'm really

874
00:47:09,320 --> 00:47:12,080
Speaker 1: interested to see what that might look like. And then

875
00:47:12,120 --> 00:47:15,040
Speaker 1: compare that to several years and look and see like

876
00:47:15,080 --> 00:47:19,120
Speaker 1: how deer related hashtags like whatever, these whatever hashtags do

877
00:47:19,160 --> 00:47:22,080
Speaker 1: you think get applied to a a picture of a

878
00:47:22,200 --> 00:47:25,960
Speaker 1: of a dead deer like your your picture, How that

879
00:47:26,040 --> 00:47:28,600
Speaker 1: trends throughout the year. I gotta believe it would correlate

880
00:47:28,680 --> 00:47:31,440
Speaker 1: to something like this, or at least I'm curious to

881
00:47:31,440 --> 00:47:33,800
Speaker 1: see what it would And uh, I don't know. It

882
00:47:33,920 --> 00:47:36,000
Speaker 1: just it felt that way at least that this year

883
00:47:36,200 --> 00:47:39,840
Speaker 1: there was that that earlier than usual upticking. And so

884
00:47:40,000 --> 00:47:41,400
Speaker 1: so then when when I'm trying to get out of

885
00:47:41,400 --> 00:47:46,759
Speaker 1: here is does that change your view at all on

886
00:47:46,920 --> 00:47:50,880
Speaker 1: the impact of the moon on I'm not well, does it?

887
00:47:51,000 --> 00:47:52,640
Speaker 1: Does it change your view at all? Spencer, I'll give

888
00:47:52,680 --> 00:47:55,200
Speaker 1: you my thoughts in a second, but does it intrigue

889
00:47:55,200 --> 00:47:59,200
Speaker 1: you or change your thoughts anyway? So my thoughts before

890
00:47:59,239 --> 00:48:02,879
Speaker 1: this season have always been that I look at like

891
00:48:03,160 --> 00:48:08,359
Speaker 1: moon theories like i'd look at sasquatch or aliens like

892
00:48:08,560 --> 00:48:13,279
Speaker 1: I don't believe. So I don't believe in it, but

893
00:48:13,560 --> 00:48:16,600
Speaker 1: I am intrigued as hell when it comes to those things,

894
00:48:16,680 --> 00:48:19,960
Speaker 1: like if you have an alien story that you saw

895
00:48:20,000 --> 00:48:24,000
Speaker 1: an UFO, I gotta hear about it. Or if I'm

896
00:48:24,000 --> 00:48:27,719
Speaker 1: flipping through the channels and I come across a Bigfoot documentary,

897
00:48:28,239 --> 00:48:30,480
Speaker 1: I'm glued to the TV. So like, I love hearing

898
00:48:30,480 --> 00:48:33,160
Speaker 1: about it and I'm super interested in the subject. But

899
00:48:34,120 --> 00:48:36,680
Speaker 1: what it boils down to, is I still don't believe

900
00:48:36,719 --> 00:48:40,520
Speaker 1: in it now after this year, my thoughts on it

901
00:48:41,200 --> 00:48:45,040
Speaker 1: largely remain the same. Uh. I think that there maybe

902
00:48:45,160 --> 00:48:48,040
Speaker 1: was an uptick in deer killed, but I guess some

903
00:48:48,080 --> 00:48:51,439
Speaker 1: of the things we're maybe not considering are a whole

904
00:48:51,440 --> 00:48:54,399
Speaker 1: bunch of other factors like brahmic pressure and if there

905
00:48:54,520 --> 00:48:58,640
Speaker 1: was any some something certain with the weather or crop status.

906
00:48:58,760 --> 00:49:02,319
Speaker 1: Um so, I yes. Another part of it, too, is

907
00:49:02,440 --> 00:49:06,680
Speaker 1: why I think that's like I'm not so much buying

908
00:49:06,680 --> 00:49:09,080
Speaker 1: into the rutting moon as I am that early October

909
00:49:09,120 --> 00:49:11,400
Speaker 1: cold front, is because there are supposed to be a

910
00:49:11,400 --> 00:49:13,920
Speaker 1: lot of big deer killed at the end of October.

911
00:49:14,000 --> 00:49:17,640
Speaker 1: We would have seen that either way had that rutting

912
00:49:17,680 --> 00:49:19,719
Speaker 1: moon not been there. That's the time of year when

913
00:49:19,719 --> 00:49:22,160
Speaker 1: a lot of guys are killing target bucks because they're

914
00:49:22,160 --> 00:49:28,000
Speaker 1: making those more reckless walkabouts, but they're still patternable. So

915
00:49:28,160 --> 00:49:30,080
Speaker 1: that's the time of year we're supposed to see big

916
00:49:30,080 --> 00:49:34,279
Speaker 1: deer being killed. Whereas you know, in regards to that

917
00:49:34,320 --> 00:49:37,640
Speaker 1: early October cold front, we're not supposed to see giants

918
00:49:37,680 --> 00:49:40,759
Speaker 1: that are hitting the ground on like October you know,

919
00:49:41,160 --> 00:49:44,400
Speaker 1: twelve or thirteenth or whatever. That's the October law. And

920
00:49:44,400 --> 00:49:46,920
Speaker 1: now I'm not saying like that's that's always the case

921
00:49:47,120 --> 00:49:50,439
Speaker 1: and uh like that's that that's how the house has

922
00:49:50,480 --> 00:49:53,640
Speaker 1: to be. But that's why, like I think the cold

923
00:49:53,680 --> 00:49:58,760
Speaker 1: front was more important this year because that maybe inspired

924
00:49:58,800 --> 00:50:01,160
Speaker 1: people to kill more big de year than the rutting

925
00:50:01,200 --> 00:50:03,919
Speaker 1: mood would during a time of year when big dealer

926
00:50:03,920 --> 00:50:07,520
Speaker 1: would be killed. Anyway. Yeah, it was like the volume

927
00:50:08,640 --> 00:50:12,080
Speaker 1: on October ten is usually like a one, and this

928
00:50:12,160 --> 00:50:13,799
Speaker 1: year with that coal front, it got bumped up to

929
00:50:13,880 --> 00:50:16,839
Speaker 1: like a six or seven or something like that. So

930
00:50:16,880 --> 00:50:21,080
Speaker 1: that was pretty substantial difference. Now in late October with

931
00:50:21,120 --> 00:50:22,839
Speaker 1: this cold or not the coal front, but with this

932
00:50:22,920 --> 00:50:25,719
Speaker 1: moon thing, we're usually gonna have a rating of a

933
00:50:25,800 --> 00:50:29,080
Speaker 1: seven maybe anyways every year somewhere around that, but all

934
00:50:29,080 --> 00:50:31,359
Speaker 1: of a sudden, now it was like at ten. So

935
00:50:32,080 --> 00:50:35,040
Speaker 1: it was it was higher in this late October time period,

936
00:50:35,040 --> 00:50:36,800
Speaker 1: but it was only a difference from the usual of

937
00:50:37,040 --> 00:50:40,880
Speaker 1: maybe three. While maybe the volume was a little bit

938
00:50:40,920 --> 00:50:43,160
Speaker 1: lower early October, but the difference from the usual is

939
00:50:43,200 --> 00:50:45,959
Speaker 1: more substantial. I think is is kind of what you're saying,

940
00:50:45,960 --> 00:50:48,920
Speaker 1: and it's kind of what I felt too, Ueah, but

941
00:50:49,040 --> 00:50:51,200
Speaker 1: it's uh I don't know. It was. It was interesting,

942
00:50:51,239 --> 00:50:53,759
Speaker 1: and I would say that my thoughts on the moon

943
00:50:54,160 --> 00:50:57,799
Speaker 1: are largely similar to yours and that I don't put

944
00:50:57,800 --> 00:51:01,760
Speaker 1: too much into it. Um, I'm still hunt. It really

945
00:51:01,840 --> 00:51:06,319
Speaker 1: doesn't impact how I hunt. Um, I'm not. I'm not

946
00:51:06,440 --> 00:51:09,080
Speaker 1: really like choosing to go into a great spot or

947
00:51:09,120 --> 00:51:12,400
Speaker 1: not because of the moon being one way or another.

948
00:51:13,400 --> 00:51:15,480
Speaker 1: But it is something that I kind of just watch

949
00:51:15,719 --> 00:51:18,360
Speaker 1: and I'm intrigued with it. And if I happened, like

950
00:51:18,400 --> 00:51:20,480
Speaker 1: if I'm going into hunt a good spot because of

951
00:51:20,520 --> 00:51:24,280
Speaker 1: a weather related thing, cold fronts definitely do impact my hunting.

952
00:51:24,560 --> 00:51:26,960
Speaker 1: So let's say I'm heading in because of that, and

953
00:51:27,000 --> 00:51:28,879
Speaker 1: then I see that the bare metric pressure is high,

954
00:51:28,960 --> 00:51:30,719
Speaker 1: and then I also see that the moon is right

955
00:51:30,800 --> 00:51:33,120
Speaker 1: for one of these theories. It does give me maybe

956
00:51:33,120 --> 00:51:36,200
Speaker 1: a tiny bit more hope. Um, I'm like, Hey, this

957
00:51:36,239 --> 00:51:37,920
Speaker 1: thing's lined up, and this thing's lined up, and this

958
00:51:38,000 --> 00:51:41,080
Speaker 1: thing's lined up. That should be good. Hopefully it's gonna

959
00:51:41,120 --> 00:51:43,000
Speaker 1: be good. So so it might be one of those

960
00:51:43,040 --> 00:51:45,120
Speaker 1: self fulfilling prophecy things to where it just kind of

961
00:51:45,160 --> 00:51:47,200
Speaker 1: gives you a little bit more excitement and energy and

962
00:51:47,200 --> 00:51:52,400
Speaker 1: focus because of it. Um. But it was really interesting

963
00:51:52,400 --> 00:51:55,640
Speaker 1: to see this year, just how dramatic of of a

964
00:51:55,719 --> 00:51:58,840
Speaker 1: bump it seemed to or something whatever it was, something

965
00:51:58,880 --> 00:52:01,080
Speaker 1: caused a bump that was a little bit bigger than usual,

966
00:52:01,440 --> 00:52:04,080
Speaker 1: and it was it was intriguing, I guess is the

967
00:52:04,120 --> 00:52:06,960
Speaker 1: moral of the story for me, so big kind of

968
00:52:07,000 --> 00:52:08,799
Speaker 1: eye opener for me at the end of October. That

969
00:52:08,840 --> 00:52:11,120
Speaker 1: was interesting and I'm definitely gonna keep watching it. I've

970
00:52:11,160 --> 00:52:13,640
Speaker 1: been watching it for something like ten years now. I

971
00:52:13,680 --> 00:52:18,279
Speaker 1: still haven't, you know, been um convinced that that it's

972
00:52:18,320 --> 00:52:20,480
Speaker 1: something kind of some kind of game changer, but it's

973
00:52:21,200 --> 00:52:23,560
Speaker 1: it's interesting. I guess as someone who's interested in a

974
00:52:23,600 --> 00:52:25,960
Speaker 1: lot of things with dear, this is definitely one of

975
00:52:25,960 --> 00:52:30,440
Speaker 1: those interesting moments and uh an example that can continue

976
00:52:30,480 --> 00:52:34,000
Speaker 1: to keep as curious moving forward, I suppose, and that yes,

977
00:52:34,080 --> 00:52:36,160
Speaker 1: these two things we just talked about, that early October

978
00:52:36,200 --> 00:52:40,000
Speaker 1: cold front and the late October possible moon effect were

979
00:52:40,040 --> 00:52:44,560
Speaker 1: definitely my two biggest um eye openers, I suppose, like

980
00:52:45,440 --> 00:52:49,120
Speaker 1: very interesting. Um. The rest of the year, things kind

981
00:52:49,120 --> 00:52:52,200
Speaker 1: of trended normal as far as I'm concerned, but I

982
00:52:52,239 --> 00:52:54,520
Speaker 1: know there's a couple other things that were maybe worth

983
00:52:54,560 --> 00:52:57,400
Speaker 1: mentioning as far as trends or patterns, um that you

984
00:52:57,440 --> 00:53:00,239
Speaker 1: want to touch on. Yeah, so I think the next

985
00:53:00,239 --> 00:53:03,560
Speaker 1: one would be was the stagnant rutting weather that we

986
00:53:03,640 --> 00:53:08,000
Speaker 1: had once we got into November. Um, it seemed like

987
00:53:08,320 --> 00:53:11,400
Speaker 1: much of the country just had stagnant weather and we

988
00:53:11,480 --> 00:53:14,439
Speaker 1: never got those warm fronts or those cold fronts. So

989
00:53:15,040 --> 00:53:18,239
Speaker 1: if you were someone, for example, that loves hunting cold

990
00:53:18,280 --> 00:53:21,560
Speaker 1: fronts and you were looking to burn some vacation days

991
00:53:21,600 --> 00:53:23,680
Speaker 1: then and you know you were waiting on that cold

992
00:53:23,719 --> 00:53:26,399
Speaker 1: front and it never came, well, that probably changed how

993
00:53:26,440 --> 00:53:30,359
Speaker 1: you were hunting because that didn't factor into your decisions. UM.

994
00:53:31,280 --> 00:53:34,040
Speaker 1: And same thing if you were someone who had the

995
00:53:34,080 --> 00:53:37,160
Speaker 1: time to hunt, but I was picking and choosing what

996
00:53:37,280 --> 00:53:40,000
Speaker 1: stands you were hunting. And if you were again like

997
00:53:40,120 --> 00:53:42,239
Speaker 1: waiting for the cold front to come in for you

998
00:53:42,320 --> 00:53:45,960
Speaker 1: to get in that betting area stand and stay all day, Uh,

999
00:53:46,040 --> 00:53:48,680
Speaker 1: that never really came. So then you were more than

1000
00:53:48,719 --> 00:53:53,440
Speaker 1: likely just hunting basing that off of historical data that like, yeah,

1001
00:53:53,680 --> 00:53:58,120
Speaker 1: the best rutting is between November ninth and eleventh, because

1002
00:53:58,120 --> 00:54:00,280
Speaker 1: a bunch of the doughs get bred between life twelfth

1003
00:54:00,320 --> 00:54:03,040
Speaker 1: and fift or whatever that might be. UM, I guess

1004
00:54:03,080 --> 00:54:05,360
Speaker 1: what I'm getting at is that when we got to

1005
00:54:05,680 --> 00:54:09,520
Speaker 1: the best buck movement of the year, that trumped everything.

1006
00:54:09,520 --> 00:54:15,319
Speaker 1: And it's normal because there wasn't much of a weather factor. Yeah, yeah,

1007
00:54:15,360 --> 00:54:17,320
Speaker 1: I agree, and I think it was just a great

1008
00:54:17,360 --> 00:54:21,200
Speaker 1: reminder that when the rut is hitting, you just gotta

1009
00:54:21,239 --> 00:54:23,960
Speaker 1: be out there, regardless of weather. Um. I know I

1010
00:54:24,040 --> 00:54:26,120
Speaker 1: talked at some point this year. I told you the

1011
00:54:26,160 --> 00:54:28,800
Speaker 1: story of that one year we got these warm fronts

1012
00:54:28,840 --> 00:54:30,719
Speaker 1: during early November and it kept me out of the

1013
00:54:30,760 --> 00:54:33,040
Speaker 1: woods for a couple of days, and I had learned

1014
00:54:33,040 --> 00:54:34,799
Speaker 1: that that was a big mistake because like three of

1015
00:54:34,840 --> 00:54:38,200
Speaker 1: my friends all killed mature bucks three days in a row. Um. So,

1016
00:54:38,239 --> 00:54:39,840
Speaker 1: this was a year where was kind of the opposite

1017
00:54:39,840 --> 00:54:42,480
Speaker 1: and that we we just kind of had normal, steady

1018
00:54:42,600 --> 00:54:45,920
Speaker 1: weather in November and nothing really changed. But that didn't

1019
00:54:45,920 --> 00:54:49,600
Speaker 1: mean there wasn't still great hunting. Um So, I think

1020
00:54:49,640 --> 00:54:52,799
Speaker 1: to your point, it would have been a mistake if

1021
00:54:52,800 --> 00:54:54,719
Speaker 1: you were hold nowt for a coal frond. You kind

1022
00:54:54,719 --> 00:54:56,879
Speaker 1: of just gotta say, Okay, I'm going to be out

1023
00:54:56,880 --> 00:54:59,840
Speaker 1: there this chunk of time during November or where whatever

1024
00:55:00,000 --> 00:55:01,680
Speaker 1: I'm a period it is for you in your area,

1025
00:55:02,239 --> 00:55:04,880
Speaker 1: and if we get a great front or something like

1026
00:55:04,920 --> 00:55:09,120
Speaker 1: that passing through. Awesome, that's the day I maybe if

1027
00:55:09,120 --> 00:55:11,080
Speaker 1: I see it coming up on the forecast, that might

1028
00:55:11,120 --> 00:55:13,120
Speaker 1: be the day I hit the very very very best

1029
00:55:13,120 --> 00:55:16,479
Speaker 1: spot or whatever. But know that anything can happen during

1030
00:55:16,520 --> 00:55:20,560
Speaker 1: those couple of weeks of peak running type activity, and uh,

1031
00:55:20,719 --> 00:55:22,960
Speaker 1: you know you're not gonna able to take advantage unless

1032
00:55:23,000 --> 00:55:25,719
Speaker 1: you're out there, regardless of if it's sixty or twenty

1033
00:55:26,880 --> 00:55:30,760
Speaker 1: and with that stagment whether uh like this is something

1034
00:55:30,760 --> 00:55:32,640
Speaker 1: that can be very localized, but I'm sure much of

1035
00:55:32,680 --> 00:55:35,399
Speaker 1: the country felt it was that once we got into

1036
00:55:35,440 --> 00:55:39,600
Speaker 1: early November, because there were like no fronts moving through

1037
00:55:39,719 --> 00:55:42,640
Speaker 1: or any kind of weather patterns, we had some really

1038
00:55:42,680 --> 00:55:46,279
Speaker 1: steady wind directions, and so I had some stands like

1039
00:55:46,320 --> 00:55:48,959
Speaker 1: I was looking to haunt Lieutenant Dan where it only

1040
00:55:49,000 --> 00:55:51,560
Speaker 1: worked to haunt him on a south wind. But I

1041
00:55:51,640 --> 00:55:53,520
Speaker 1: remember looking at the forecast one day, and this is

1042
00:55:53,520 --> 00:55:57,080
Speaker 1: something we talked about on radio, and it had looked

1043
00:55:57,120 --> 00:55:59,359
Speaker 1: like there was like eight of ten days coming up

1044
00:55:59,360 --> 00:56:01,920
Speaker 1: in early November where it was just north winds. There

1045
00:56:01,920 --> 00:56:03,560
Speaker 1: were no south winds. I think two out of the

1046
00:56:03,560 --> 00:56:06,240
Speaker 1: ten days had south wind and so that was something

1047
00:56:06,280 --> 00:56:11,760
Speaker 1: that definitely changed. Uh, you know my rut hunting in November,

1048
00:56:11,840 --> 00:56:14,399
Speaker 1: And it's probably something that other people felt as well,

1049
00:56:14,400 --> 00:56:16,960
Speaker 1: that you really had to like look at that extended

1050
00:56:17,000 --> 00:56:19,839
Speaker 1: forecast and maybe like take out a piece of paper

1051
00:56:19,880 --> 00:56:22,680
Speaker 1: and write down, Okay, we have this win direction, this

1052
00:56:22,760 --> 00:56:26,600
Speaker 1: win direction, this win direction. Because there are like really

1053
00:56:26,640 --> 00:56:29,480
Speaker 1: really limited south winds. I gotta be aggressive and get

1054
00:56:29,560 --> 00:56:32,200
Speaker 1: in there and hunt that south windstand once I get it,

1055
00:56:32,239 --> 00:56:34,719
Speaker 1: because I might not have another chance. Yeah, that's a

1056
00:56:34,760 --> 00:56:36,839
Speaker 1: that's a huge, huge point. I think it's a really

1057
00:56:36,920 --> 00:56:39,920
Speaker 1: good thing to mention, and the fact that you know,

1058
00:56:40,040 --> 00:56:43,160
Speaker 1: in the postseason, think about that ahead of time and

1059
00:56:43,239 --> 00:56:46,080
Speaker 1: make sure that you know if you if you have

1060
00:56:46,600 --> 00:56:49,640
Speaker 1: lots of times, what I do is I'm planning on

1061
00:56:49,880 --> 00:56:54,200
Speaker 1: setting stands in certain regions based off the predominant winds. Somethinging. Okay, well,

1062
00:56:54,680 --> 00:56:58,040
Speaker 1: most of the time here in October or November, we're

1063
00:56:58,040 --> 00:57:01,279
Speaker 1: gonna have like a westerly wind or north west wind. Um,

1064
00:57:01,360 --> 00:57:02,960
Speaker 1: so lots of times I'll just end up setting a

1065
00:57:02,960 --> 00:57:05,600
Speaker 1: bunch of stands for that wind direction. But then what

1066
00:57:05,719 --> 00:57:08,600
Speaker 1: happens if your big rut vacation comes up and you've

1067
00:57:08,600 --> 00:57:11,319
Speaker 1: got seven straight days to hunt, and God forbid. All

1068
00:57:11,320 --> 00:57:14,279
Speaker 1: of a sudden, you have nothing but southeast winds, but

1069
00:57:14,360 --> 00:57:18,000
Speaker 1: all your stands are set up for northwest or west. Um,

1070
00:57:18,080 --> 00:57:19,680
Speaker 1: that's a situation you don't want to be in. So

1071
00:57:19,720 --> 00:57:23,320
Speaker 1: I would say the lesson learned for me. I had

1072
00:57:23,320 --> 00:57:25,120
Speaker 1: a yearly this last year where we had a bunch

1073
00:57:25,120 --> 00:57:28,040
Speaker 1: of southeast and easterly winds when everything else was set

1074
00:57:28,080 --> 00:57:30,360
Speaker 1: up for west, and I found myself in a pinch.

1075
00:57:31,320 --> 00:57:34,080
Speaker 1: What I would say is to try to make sure

1076
00:57:34,080 --> 00:57:37,280
Speaker 1: you account for that and have winds set up or sorry,

1077
00:57:37,360 --> 00:57:39,680
Speaker 1: have some stands. If you're in a situation where you

1078
00:57:39,680 --> 00:57:42,440
Speaker 1: can have stands hung and prepped, make sure you do

1079
00:57:42,560 --> 00:57:44,680
Speaker 1: have some prep work done for those funky winds that

1080
00:57:44,720 --> 00:57:46,440
Speaker 1: you're not really expecting, but you want to make sure

1081
00:57:46,480 --> 00:57:48,160
Speaker 1: you're not hung out to dry if it does show up.

1082
00:57:49,280 --> 00:57:52,960
Speaker 1: Or make sure that you are comfortable enough with a

1083
00:57:53,000 --> 00:57:55,480
Speaker 1: mobile set up, a running guns set up so that

1084
00:57:55,720 --> 00:57:57,680
Speaker 1: it doesn't matter that you don't have stands prepped. You're

1085
00:57:57,680 --> 00:57:59,400
Speaker 1: just gonna go and hang it that day, or just

1086
00:57:59,400 --> 00:58:01,400
Speaker 1: set up in the I add all that day. UM.

1087
00:58:01,440 --> 00:58:03,760
Speaker 1: I think one of those two things needs to be

1088
00:58:03,800 --> 00:58:06,600
Speaker 1: within your little toolkit to make sure that if you're

1089
00:58:06,640 --> 00:58:08,640
Speaker 1: in a snare like that, you're not stuck hunting the

1090
00:58:08,680 --> 00:58:11,240
Speaker 1: one spot over and over or you're stuck only having

1091
00:58:11,240 --> 00:58:14,720
Speaker 1: one stand for this wind. Um, you just got to

1092
00:58:14,760 --> 00:58:17,600
Speaker 1: make sure that you can be able to strike no

1093
00:58:17,600 --> 00:58:20,040
Speaker 1: matter what the conditions you need to have. You need

1094
00:58:20,040 --> 00:58:23,360
Speaker 1: to be ready for whatever variables come your way each season. Um,

1095
00:58:23,400 --> 00:58:26,160
Speaker 1: I think is what I'm trying to say. Yeah, and

1096
00:58:26,240 --> 00:58:29,840
Speaker 1: let's fast forward now from the rut to late season

1097
00:58:30,200 --> 00:58:32,520
Speaker 1: and last year I think we had like the tail

1098
00:58:32,560 --> 00:58:35,200
Speaker 1: of two late seasons. Something we talked about how there

1099
00:58:35,280 --> 00:58:37,280
Speaker 1: was like a stretch of really warm days and then

1100
00:58:37,320 --> 00:58:40,760
Speaker 1: there was a stretch of like really nasty, uh cold days.

1101
00:58:40,840 --> 00:58:43,200
Speaker 1: Now that's not something I think we necessarily had in

1102
00:58:43,600 --> 00:58:45,720
Speaker 1: like this December from much of the country, but there

1103
00:58:45,880 --> 00:58:50,760
Speaker 1: was still something really noticeable for and that was that

1104
00:58:50,840 --> 00:58:53,480
Speaker 1: there were a lot of bucks that have been shedding early,

1105
00:58:53,880 --> 00:58:57,280
Speaker 1: uh where you were seeing like it more of not

1106
00:58:57,400 --> 00:59:01,120
Speaker 1: an individual basis for bucks shedding early, but like a

1107
00:59:01,200 --> 00:59:03,440
Speaker 1: heard by her basis where you were seeing a lot

1108
00:59:03,480 --> 00:59:06,560
Speaker 1: of bucks that were dropping antlers sooner than they normally would.

1109
00:59:06,680 --> 00:59:09,560
Speaker 1: So most of the time bucks are going to be

1110
00:59:09,600 --> 00:59:14,440
Speaker 1: shedding like between January and March, but this year, um

1111
00:59:14,600 --> 00:59:17,480
Speaker 1: something that had shown up in some red fresh reports

1112
00:59:17,920 --> 00:59:20,840
Speaker 1: and then and something that had you know, people have

1113
00:59:20,960 --> 00:59:22,600
Speaker 1: reached out to me after I shot Dan. He she

1114
00:59:22,600 --> 00:59:25,520
Speaker 1: had an antler was that a lot more people were

1115
00:59:25,560 --> 00:59:29,080
Speaker 1: seeing bucks shed early this season. And so I was

1116
00:59:29,120 --> 00:59:32,120
Speaker 1: wondering if that was like a product of social media,

1117
00:59:32,240 --> 00:59:34,200
Speaker 1: just that we're more connected and it, you know, we're

1118
00:59:34,240 --> 00:59:37,160
Speaker 1: more aware when people are finding sheds earlier than normal,

1119
00:59:37,520 --> 00:59:39,320
Speaker 1: or if this was actually a trend. So I put

1120
00:59:39,320 --> 00:59:41,400
Speaker 1: out a call to people on Instagram and said, hey,

1121
00:59:41,440 --> 00:59:44,320
Speaker 1: if this is something you've seen this year where bucks

1122
00:59:44,320 --> 00:59:46,600
Speaker 1: have been shedding early side of my d M s,

1123
00:59:46,800 --> 00:59:50,080
Speaker 1: and a whole bunch of people did um where this

1124
00:59:50,320 --> 00:59:54,160
Speaker 1: seemed like a pattern that you know, people were telling

1125
00:59:54,160 --> 00:59:56,360
Speaker 1: me we've been seeing a lot of buck a lot

1126
00:59:56,440 --> 01:00:00,520
Speaker 1: of bucks shed earlier than normal. So I reached out

1127
01:00:00,720 --> 01:00:04,320
Speaker 1: to Kip Adams from q d M A. So, going

1128
01:00:04,360 --> 01:00:07,440
Speaker 1: into that conversation with Kip um a lot of the

1129
01:00:07,480 --> 01:00:10,680
Speaker 1: reports that I had received were out of like Ohio

1130
01:00:10,760 --> 01:00:15,920
Speaker 1: and New York, Illinois, Arkansas, the Dakotas, but like ground

1131
01:00:16,000 --> 01:00:19,240
Speaker 1: zero for this seemed to be Pennsylvania getting loads of

1132
01:00:19,280 --> 01:00:25,760
Speaker 1: reports of guys like shooting a dough that end up

1133
01:00:25,800 --> 01:00:29,240
Speaker 1: being a buck, or other people having experiences like I

1134
01:00:29,280 --> 01:00:31,200
Speaker 1: did where they shot a buck and he shed one

1135
01:00:31,280 --> 01:00:33,560
Speaker 1: or both antlers when they got him. Um, there were

1136
01:00:33,600 --> 01:00:37,280
Speaker 1: people like Martinic, who we've had on the podcast before

1137
01:00:37,320 --> 01:00:40,880
Speaker 1: to talk about deer movement in Pennsylvania. Um, him and

1138
01:00:40,960 --> 01:00:45,320
Speaker 1: his dad found ten sheds in December. WHOA, which is yeah,

1139
01:00:45,360 --> 01:00:48,000
Speaker 1: that's like unheard of. And so I reached out to

1140
01:00:48,040 --> 01:00:49,919
Speaker 1: Kip Adams to talk to him about this and see

1141
01:00:49,920 --> 01:00:52,800
Speaker 1: if this is, you know, really a thing that you

1142
01:00:52,840 --> 01:00:57,920
Speaker 1: can see like herds that shed rather than just you know,

1143
01:00:58,040 --> 01:01:01,040
Speaker 1: individual bucks shedding. And he said, yeah, that's a thing.

1144
01:01:01,280 --> 01:01:03,760
Speaker 1: And he's also based out of Pennsylvania, and this is

1145
01:01:03,800 --> 01:01:07,720
Speaker 1: something he's been hearing a bunch of in eighteen as well.

1146
01:01:07,880 --> 01:01:10,880
Speaker 1: And so the cause for this can go all the

1147
01:01:10,920 --> 01:01:14,960
Speaker 1: way back to the summer. And largely what you're seeing

1148
01:01:15,160 --> 01:01:19,520
Speaker 1: when you're seeing bucks shed early is that they are

1149
01:01:20,080 --> 01:01:24,200
Speaker 1: stressed or having like a nutritional deficit, and so they

1150
01:01:24,240 --> 01:01:27,520
Speaker 1: didn't get to put on like the fat reserves that

1151
01:01:27,560 --> 01:01:29,600
Speaker 1: they normally would. Him. This is these are from the

1152
01:01:29,640 --> 01:01:31,160
Speaker 1: words of kid when I talked to him a few

1153
01:01:31,200 --> 01:01:34,320
Speaker 1: days ago. UM. And so going into the fall, there's

1154
01:01:34,360 --> 01:01:38,000
Speaker 1: been metabolic studies that show that like adult deer can

1155
01:01:38,040 --> 01:01:41,200
Speaker 1: get half of their nutrition from stored fat, and so

1156
01:01:42,320 --> 01:01:45,200
Speaker 1: going all the way back to like July and August,

1157
01:01:45,320 --> 01:01:49,320
Speaker 1: if those deer didn't have a great food source, and

1158
01:01:49,320 --> 01:01:51,680
Speaker 1: then you know, all the way into October, right before

1159
01:01:51,680 --> 01:01:53,600
Speaker 1: the rut, same thing. If they didn't have great food

1160
01:01:53,600 --> 01:01:57,480
Speaker 1: source for a number of different reasons, that would bring

1161
01:01:57,520 --> 01:02:00,840
Speaker 1: them into the rotten into late season with less fat

1162
01:02:00,880 --> 01:02:04,000
Speaker 1: than normal, which would cause them to shed, you know,

1163
01:02:04,400 --> 01:02:08,840
Speaker 1: sooner than expected. And so keep it pointing to how

1164
01:02:09,160 --> 01:02:12,240
Speaker 1: like deer densities are also higher in the country than

1165
01:02:12,320 --> 01:02:15,120
Speaker 1: they have been in a while. In Pennsylvania, for example,

1166
01:02:15,480 --> 01:02:19,040
Speaker 1: is had like really high deer densities lately because they

1167
01:02:19,080 --> 01:02:22,880
Speaker 1: cut back on some annerless hunts. And so if this

1168
01:02:22,960 --> 01:02:26,360
Speaker 1: is something that you're seeing in your area heard shedding early,

1169
01:02:26,640 --> 01:02:29,480
Speaker 1: it's probably because there were, uh, you know, there was

1170
01:02:29,480 --> 01:02:32,280
Speaker 1: a nutrition to deficit from the summer and fall that

1171
01:02:32,440 --> 01:02:36,360
Speaker 1: is now led into them dropping their actors sooner. And

1172
01:02:36,400 --> 01:02:39,440
Speaker 1: it can also be because deer densities are higher than

1173
01:02:39,440 --> 01:02:42,360
Speaker 1: they've been in a while. Interesting, and that might even

1174
01:02:42,400 --> 01:02:45,000
Speaker 1: tie back to the whole E H D effect that

1175
01:02:45,040 --> 01:02:49,480
Speaker 1: we talked about. So two thirteen you had this significant

1176
01:02:49,480 --> 01:02:53,840
Speaker 1: reduction in dear population in some areas, and then you

1177
01:02:53,920 --> 01:02:57,480
Speaker 1: had all these deer now even more productive in the

1178
01:02:57,520 --> 01:03:00,720
Speaker 1: subsequent years because of that reduced competition. And now three

1179
01:03:00,760 --> 01:03:03,200
Speaker 1: or four or five years later, now you have maybe

1180
01:03:03,200 --> 01:03:06,440
Speaker 1: a higher deer density because you had this huge UM

1181
01:03:06,680 --> 01:03:10,000
Speaker 1: deficit that now flooded back in like the vacuum, all

1182
01:03:10,040 --> 01:03:12,960
Speaker 1: of a sudden flooded back in with um. You know,

1183
01:03:13,160 --> 01:03:15,160
Speaker 1: all these healthy deer that all of a sudden. Now

1184
01:03:15,160 --> 01:03:18,160
Speaker 1: maybe we're seeing the ramifications of that. Now we're getting

1185
01:03:18,200 --> 01:03:22,919
Speaker 1: over over dense, too much, too many deer, too few resources, um,

1186
01:03:23,240 --> 01:03:26,360
Speaker 1: nutritional deficit for bucks shedding early. And you know, like

1187
01:03:26,400 --> 01:03:28,560
Speaker 1: I told you, either last week or the week before,

1188
01:03:28,880 --> 01:03:32,120
Speaker 1: we I found I had a neighbor find a shed

1189
01:03:32,160 --> 01:03:34,000
Speaker 1: and give that to me over here on one of

1190
01:03:34,040 --> 01:03:37,400
Speaker 1: the properties I hunt. Um. I know another friend of ours,

1191
01:03:37,440 --> 01:03:40,360
Speaker 1: Ben Harshein, just saw his number one buck he was

1192
01:03:40,400 --> 01:03:43,480
Speaker 1: after a few days ago had shed. Um. Yeah, I

1193
01:03:43,480 --> 01:03:45,640
Speaker 1: mean it's all over. I saw someone Illinois shot about

1194
01:03:45,680 --> 01:03:48,240
Speaker 1: had the antlers fall off. So to your point, it

1195
01:03:48,400 --> 01:03:53,160
Speaker 1: is interestingly widespread this year. UM. And that's really interesting.

1196
01:03:53,200 --> 01:03:56,919
Speaker 1: Theories that Kip shared. So I asked, Kip, I asked

1197
01:03:57,000 --> 01:03:59,680
Speaker 1: him if this is like, if you can recall another

1198
01:03:59,760 --> 01:04:02,919
Speaker 1: year that he has seen this before, gotten these kinds

1199
01:04:02,920 --> 01:04:05,880
Speaker 1: of reports like he has in ten He said, the

1200
01:04:05,960 --> 01:04:09,320
Speaker 1: last time and it probably wasn't as extreme as this,

1201
01:04:09,400 --> 01:04:12,160
Speaker 1: he said, it was two thousand and twelve. UM two

1202
01:04:12,400 --> 01:04:16,280
Speaker 1: twelve was a drought year. That was when uh, you know,

1203
01:04:16,360 --> 01:04:19,040
Speaker 1: there was absolutely it was pretty obvious why there was

1204
01:04:19,080 --> 01:04:22,760
Speaker 1: anwntritional deficit because there was a poorer quality and crops

1205
01:04:23,000 --> 01:04:26,440
Speaker 1: uh and you know, less natural browns because there was

1206
01:04:26,480 --> 01:04:28,760
Speaker 1: hardly any rain, and so that led to deal with

1207
01:04:28,840 --> 01:04:32,680
Speaker 1: less back going into um going into the ruts. And

1208
01:04:32,720 --> 01:04:36,680
Speaker 1: then he also talked about how bucks shedding earlier that year,

1209
01:04:37,160 --> 01:04:39,840
Speaker 1: uh could have been e h D survivors And he said,

1210
01:04:39,840 --> 01:04:43,200
Speaker 1: in some parts of Pennsylvania had some cases of e

1211
01:04:43,400 --> 01:04:45,680
Speaker 1: h D this year, and those bucks could have been

1212
01:04:45,840 --> 01:04:48,120
Speaker 1: you know, e h D survivors as well as a

1213
01:04:48,160 --> 01:04:50,880
Speaker 1: combination of just not being very healthy to begin with.

1214
01:04:52,720 --> 01:04:57,040
Speaker 1: Very very interesting stuff with the with the early sheds. UM.

1215
01:04:57,120 --> 01:04:59,880
Speaker 1: I'm curious to hear now if more people hear the

1216
01:05:00,280 --> 01:05:02,600
Speaker 1: now that we're talking about it, if some more reports

1217
01:05:02,640 --> 01:05:04,720
Speaker 1: come in, I'd be. I'd be really interested to hear

1218
01:05:04,760 --> 01:05:06,920
Speaker 1: if this is more widespread even that we're than we're

1219
01:05:06,960 --> 01:05:10,800
Speaker 1: seeing right now. Um, you know, pivoting a little bit.

1220
01:05:10,840 --> 01:05:12,640
Speaker 1: The only other thing when it comes to late season

1221
01:05:12,640 --> 01:05:15,560
Speaker 1: I'd mentioned is that it has been, at least around

1222
01:05:15,560 --> 01:05:17,720
Speaker 1: me and in the Upper Midwest where I'm kind of

1223
01:05:17,720 --> 01:05:20,800
Speaker 1: tapped in the most, it has been a pretty mild

1224
01:05:21,160 --> 01:05:24,840
Speaker 1: late season, and I think because of that, late seasons

1225
01:05:24,880 --> 01:05:28,240
Speaker 1: success rates seem to be a little bit lower than usual.

1226
01:05:28,280 --> 01:05:30,440
Speaker 1: Maybe have you felt that to Spencer that we haven't

1227
01:05:30,440 --> 01:05:33,080
Speaker 1: had that big snowstorm cold front yet that we usually

1228
01:05:33,080 --> 01:05:37,360
Speaker 1: get in December that puts a bunch of big deer down. Yeah.

1229
01:05:37,560 --> 01:05:40,960
Speaker 1: I I did a lot more hunting November than I

1230
01:05:41,040 --> 01:05:43,439
Speaker 1: normally would have, and that was something I noticed as well,

1231
01:05:43,480 --> 01:05:46,320
Speaker 1: that we got a pretty good stretch of mild weather

1232
01:05:46,600 --> 01:05:49,600
Speaker 1: where it didn't force those deer to congregate in the

1233
01:05:49,680 --> 01:05:53,600
Speaker 1: obvious places like you know, a cut cornfield or a

1234
01:05:53,640 --> 01:05:56,720
Speaker 1: food plot. It makes sense a lot tougher this time

1235
01:05:56,760 --> 01:06:00,080
Speaker 1: of year. I mean, they're just they're already toun it

1236
01:06:00,200 --> 01:06:02,280
Speaker 1: for months on end. The pressure has been high on them.

1237
01:06:02,520 --> 01:06:06,200
Speaker 1: They're slowing down when you don't get that big coal

1238
01:06:06,240 --> 01:06:08,960
Speaker 1: front of the snowstorm in December January to to get

1239
01:06:09,000 --> 01:06:11,160
Speaker 1: him out there in front of you. This time, you

1240
01:06:11,280 --> 01:06:14,080
Speaker 1: can be pretty tough. So for late season, I think

1241
01:06:14,080 --> 01:06:16,000
Speaker 1: it has been a little bit more challenging for people.

1242
01:06:16,320 --> 01:06:21,800
Speaker 1: So and your So, your most important factor of the route,

1243
01:06:21,840 --> 01:06:25,080
Speaker 1: you would say was the early running moon. Correct, Well,

1244
01:06:25,560 --> 01:06:27,920
Speaker 1: I would say it's tied between that in that early

1245
01:06:27,960 --> 01:06:32,000
Speaker 1: coal front as far as like interesting things that popped

1246
01:06:32,080 --> 01:06:34,280
Speaker 1: for me this year. Those two, I don't know which one,

1247
01:06:34,600 --> 01:06:37,320
Speaker 1: but those are my top two. So I would say

1248
01:06:37,360 --> 01:06:39,600
Speaker 1: that it was the wet fall that we had. Um,

1249
01:06:39,840 --> 01:06:43,040
Speaker 1: I think that just like made such a big difference

1250
01:06:43,360 --> 01:06:46,560
Speaker 1: in short term and long term. Like short term as

1251
01:06:46,600 --> 01:06:50,720
Speaker 1: it can affect buck movement, uh, like you know, all

1252
01:06:50,720 --> 01:06:52,920
Speaker 1: of a sudden, there's a creek that flooded that's now

1253
01:06:52,960 --> 01:06:55,840
Speaker 1: impassable and you can't get to it, or maybe you're

1254
01:06:56,000 --> 01:06:59,520
Speaker 1: someone who haunts like minimal maintenance roads and you can't

1255
01:06:59,600 --> 01:07:01,760
Speaker 1: get too an area. You know, a lot of rain

1256
01:07:01,880 --> 01:07:04,720
Speaker 1: can also affect signmaking. This is something we've talked about

1257
01:07:04,720 --> 01:07:07,760
Speaker 1: before how a lot of people theorize that as you

1258
01:07:07,840 --> 01:07:10,640
Speaker 1: get like more rain, it forces those bucks to go

1259
01:07:10,800 --> 01:07:14,320
Speaker 1: check scrapes more often and then long term effects that

1260
01:07:14,400 --> 01:07:17,600
Speaker 1: it had. UM we like how it all food sources

1261
01:07:17,600 --> 01:07:21,680
Speaker 1: that kept crops in more UM. Something that I've've read

1262
01:07:21,720 --> 01:07:23,320
Speaker 1: about but again and I don't have a ton of

1263
01:07:23,360 --> 01:07:27,600
Speaker 1: experience with acorns, is how like a lot of precipitation

1264
01:07:27,960 --> 01:07:31,320
Speaker 1: can sour acorns. And so this is something I looked into,

1265
01:07:31,360 --> 01:07:35,200
Speaker 1: but I couldn't find any hard data on you know

1266
01:07:35,320 --> 01:07:37,600
Speaker 1: what's true and what's false here. But there's some different

1267
01:07:37,640 --> 01:07:40,760
Speaker 1: theories around that, like if you get a bunch of rain, um,

1268
01:07:41,040 --> 01:07:43,120
Speaker 1: and if there's acorns on the ground that they can

1269
01:07:43,200 --> 01:07:46,520
Speaker 1: make them like essentially go sour and deer are no

1270
01:07:46,560 --> 01:07:49,280
Speaker 1: longer interested in them. So if you were somebody in

1271
01:07:49,320 --> 01:07:52,640
Speaker 1: mid oct October who was focused on acorns and we've

1272
01:07:52,640 --> 01:07:55,040
Speaker 1: got all this rain and these acorns are now sitting

1273
01:07:55,480 --> 01:07:58,520
Speaker 1: in water, they're now sour and it forces those bucks

1274
01:07:58,520 --> 01:08:01,560
Speaker 1: to a different foods or some other theories around like

1275
01:08:01,640 --> 01:08:05,600
Speaker 1: rain and acorns, was that uh rain during that time

1276
01:08:05,600 --> 01:08:10,560
Speaker 1: of year, and like heep is more friendly to insects,

1277
01:08:10,600 --> 01:08:13,000
Speaker 1: I guess, and so you get some of those weevils

1278
01:08:13,040 --> 01:08:17,559
Speaker 1: that burrow into those acorns and that makes them rot out. Again,

1279
01:08:17,600 --> 01:08:19,360
Speaker 1: these aren't things that I know where could find add

1280
01:08:19,439 --> 01:08:22,439
Speaker 1: on just like theories that I found on the subject um.

1281
01:08:22,600 --> 01:08:25,920
Speaker 1: And then I recall an episode back in October when

1282
01:08:25,960 --> 01:08:28,439
Speaker 1: we were talking to Tyler Jones in Texas from the

1283
01:08:28,439 --> 01:08:33,040
Speaker 1: Element podcast where he had said, with all these rainstorms,

1284
01:08:33,080 --> 01:08:35,320
Speaker 1: we had a lot of times with that came wind,

1285
01:08:35,439 --> 01:08:37,679
Speaker 1: and that wind was knocking a lot of these acorns

1286
01:08:37,720 --> 01:08:41,200
Speaker 1: off the tree, uh like sooner, and it was bringing

1287
01:08:41,200 --> 01:08:44,920
Speaker 1: them a bit bault whoop rather than you know, some

1288
01:08:45,000 --> 01:08:47,160
Speaker 1: acorns coming down at certain times and them coming down

1289
01:08:47,280 --> 01:08:52,080
Speaker 1: other times. Um. So, anyway, the precipitation the acorns, I

1290
01:08:52,080 --> 01:08:55,599
Speaker 1: think was was a big thing. And then another long

1291
01:08:55,720 --> 01:08:58,599
Speaker 1: term factor that can be and this is gonna scare people,

1292
01:08:58,720 --> 01:09:02,640
Speaker 1: but uh be e h D. So most think of

1293
01:09:03,120 --> 01:09:05,800
Speaker 1: e h D. They think of a drought year that

1294
01:09:05,880 --> 01:09:09,600
Speaker 1: will kill a bunch of bucks. But what's more important,

1295
01:09:09,680 --> 01:09:12,759
Speaker 1: and this can happen on like super wet years as well.

1296
01:09:12,920 --> 01:09:16,920
Speaker 1: So you get these like isolated water holes and these

1297
01:09:17,000 --> 01:09:21,880
Speaker 1: long mudlines from when you have like a you know,

1298
01:09:22,000 --> 01:09:26,080
Speaker 1: a late wet season, which would be in we had

1299
01:09:26,120 --> 01:09:29,679
Speaker 1: this really wet fall and maybe all that water didn't disappear,

1300
01:09:29,720 --> 01:09:33,479
Speaker 1: and so we go into and uh say, we get

1301
01:09:33,520 --> 01:09:35,960
Speaker 1: some drought conditions, and maybe we don't even need a

1302
01:09:36,040 --> 01:09:39,320
Speaker 1: drought UM, and all of a sudden that creates a

1303
01:09:39,320 --> 01:09:43,519
Speaker 1: bunch of standing water holes that is perfect for those midges, uh,

1304
01:09:43,600 --> 01:09:47,280
Speaker 1: you know, to really thrive. And we could have another

1305
01:09:47,400 --> 01:09:51,120
Speaker 1: e h D breakout in just by looking at the

1306
01:09:51,200 --> 01:09:55,040
Speaker 1: really wet fall that we had in even if we

1307
01:09:55,080 --> 01:09:59,120
Speaker 1: don't necessarily have the drought h that perfect storm is

1308
01:09:59,360 --> 01:10:01,960
Speaker 1: kind of uh you know, that should be on everyone's

1309
01:10:02,000 --> 01:10:05,439
Speaker 1: mind as we go into the summer. What a wonderful

1310
01:10:05,439 --> 01:10:08,519
Speaker 1: way to end this episode. Thanks, thanks for the silver

1311
01:10:08,640 --> 01:10:10,479
Speaker 1: lining for us to all think about here heading into

1312
01:10:10,520 --> 01:10:15,600
Speaker 1: the new year. UM. That is interesting though, and and

1313
01:10:15,760 --> 01:10:20,280
Speaker 1: you're right that is those those muddy banks really do

1314
01:10:20,439 --> 01:10:23,920
Speaker 1: seem to to lead to issues of the midges and

1315
01:10:23,920 --> 01:10:26,200
Speaker 1: and typically it's around droughts. But it's an interesting point

1316
01:10:26,200 --> 01:10:28,000
Speaker 1: you're bringing up here as far as how the year

1317
01:10:28,040 --> 01:10:31,360
Speaker 1: before sometimes might impact things too. So something to keep

1318
01:10:31,360 --> 01:10:34,639
Speaker 1: an eye on UM for next year, no doubt about that.

1319
01:10:35,680 --> 01:10:38,320
Speaker 1: And if you think back to UM for a lot

1320
01:10:38,320 --> 01:10:42,200
Speaker 1: of areas, twenty eleven was a super wet year and

1321
01:10:42,240 --> 01:10:44,800
Speaker 1: so like I think about a lot of my properties,

1322
01:10:44,920 --> 01:10:47,839
Speaker 1: that there are some areas that sometimes have water sometimes

1323
01:10:47,880 --> 01:10:51,640
Speaker 1: don't um eleven areas flooded and then it left all

1324
01:10:51,640 --> 01:10:54,720
Speaker 1: these local spots with standing water or maybe you had

1325
01:10:54,720 --> 01:10:57,800
Speaker 1: a stock damn uh that came way out of its

1326
01:10:57,800 --> 01:11:01,040
Speaker 1: banks and then you go into and that water starts

1327
01:11:01,080 --> 01:11:03,720
Speaker 1: to receive because it was so hot and you had

1328
01:11:03,720 --> 01:11:06,960
Speaker 1: these drought conditions that it leaves these long stretches of

1329
01:11:06,960 --> 01:11:10,760
Speaker 1: of muddy areas and shallow water. And that was you know,

1330
01:11:10,880 --> 01:11:13,519
Speaker 1: created the perfect storm for much of the country to

1331
01:11:13,640 --> 01:11:16,120
Speaker 1: get d h D. And that's something that we could

1332
01:11:16,120 --> 01:11:21,160
Speaker 1: see again in now. Shifting away from e h D,

1333
01:11:21,439 --> 01:11:26,400
Speaker 1: but staying on this exercise that you just share with us,

1334
01:11:26,439 --> 01:11:30,120
Speaker 1: this idea of of looking at past years and using

1335
01:11:30,160 --> 01:11:32,240
Speaker 1: that to help predict the future. What you just did

1336
01:11:32,240 --> 01:11:36,479
Speaker 1: there that I think is my big takeaway from RUT

1337
01:11:36,560 --> 01:11:41,960
Speaker 1: radio this year as far as how RUT radio can

1338
01:11:42,000 --> 01:11:44,599
Speaker 1: be used as a tool, it's it's always it's it's

1339
01:11:44,600 --> 01:11:46,640
Speaker 1: helpful in the short term and that you know, we

1340
01:11:46,680 --> 01:11:49,080
Speaker 1: get to hear people that were out hunting a few

1341
01:11:49,160 --> 01:11:52,439
Speaker 1: days ago and hear what they're seeing and hear what

1342
01:11:52,479 --> 01:11:55,400
Speaker 1: they're thinking, and then use that for our future hunts

1343
01:11:55,400 --> 01:11:56,680
Speaker 1: in the next couple of days. Like that's how a

1344
01:11:56,720 --> 01:11:58,719
Speaker 1: lot of people are using these episodes of the podcast

1345
01:11:58,760 --> 01:12:03,120
Speaker 1: throughout the year. But I think maybe the secret sauce

1346
01:12:04,120 --> 01:12:06,080
Speaker 1: and I want to do this next year. Really do

1347
01:12:06,200 --> 01:12:08,719
Speaker 1: this next year is go back and listen to past

1348
01:12:08,840 --> 01:12:13,400
Speaker 1: years and look at what was predicted by these folks.

1349
01:12:13,439 --> 01:12:15,240
Speaker 1: What do they what was coming to them. So let's

1350
01:12:15,320 --> 01:12:20,519
Speaker 1: let's hypothetically say next year it's October one, I would

1351
01:12:20,520 --> 01:12:24,680
Speaker 1: recommend going back and listening to RUT Radio episodes from

1352
01:12:24,760 --> 01:12:28,240
Speaker 1: last year and the year before. Maybe that we're from

1353
01:12:28,240 --> 01:12:31,400
Speaker 1: the week before October one. So listen to people talking

1354
01:12:31,439 --> 01:12:35,000
Speaker 1: about what's coming for October one. So Joe blow Hunter says, well,

1355
01:12:35,040 --> 01:12:38,000
Speaker 1: this front is happening, or this weather condition is present,

1356
01:12:38,160 --> 01:12:40,679
Speaker 1: or this is how the acorn crops this year or whatever.

1357
01:12:41,479 --> 01:12:44,840
Speaker 1: Hear about what happened that year, and then listen to

1358
01:12:44,880 --> 01:12:48,040
Speaker 1: the following episode to find out what the impact was.

1359
01:12:48,400 --> 01:12:51,360
Speaker 1: So you heard that the acorn crops were pretty rough,

1360
01:12:51,840 --> 01:12:55,040
Speaker 1: maybe leading into October one of two thousand and sixteen,

1361
01:12:55,080 --> 01:12:58,400
Speaker 1: let's say, and Joe blow Hunter thought that was going

1362
01:12:58,439 --> 01:13:00,840
Speaker 1: to influence his hunting and this way, so he was

1363
01:13:00,840 --> 01:13:03,680
Speaker 1: gonna go and hunt in that way. Listen to the

1364
01:13:03,720 --> 01:13:06,840
Speaker 1: next week and you get to hear how people were

1365
01:13:07,280 --> 01:13:09,439
Speaker 1: hunting and what kind of success they ended up having

1366
01:13:09,479 --> 01:13:12,720
Speaker 1: on October one or October two based on those conditions.

1367
01:13:13,040 --> 01:13:16,400
Speaker 1: I think that's a really interesting way you can test

1368
01:13:16,560 --> 01:13:19,240
Speaker 1: theories and see how it ended up going. Um, if

1369
01:13:19,280 --> 01:13:22,520
Speaker 1: you went back and did that each year, So October one,

1370
01:13:22,680 --> 01:13:24,760
Speaker 1: go back and listen to the sixteen episode, go back

1371
01:13:24,760 --> 01:13:28,440
Speaker 1: and listen to the seventeen episode. That can then inform

1372
01:13:28,520 --> 01:13:31,639
Speaker 1: you for your two thou nineteen hunt. You can say, Okay, well,

1373
01:13:31,640 --> 01:13:33,479
Speaker 1: this is what was going on in sixteen, this is

1374
01:13:33,479 --> 01:13:35,080
Speaker 1: what was happening in seventeen, and this is how it

1375
01:13:35,120 --> 01:13:37,000
Speaker 1: all turned out. So what does that mean for me

1376
01:13:37,080 --> 01:13:39,599
Speaker 1: this year? Because now I have these conditions that were

1377
01:13:39,640 --> 01:13:42,320
Speaker 1: just like seventeen. So maybe I should try doing what

1378
01:13:42,400 --> 01:13:44,720
Speaker 1: Joe did in seventeen that worked for him. I think

1379
01:13:44,800 --> 01:13:48,559
Speaker 1: that is like the really unexpected way that RUT radio

1380
01:13:48,640 --> 01:13:50,759
Speaker 1: can help folks that when we started doing the Spencer,

1381
01:13:50,800 --> 01:13:52,920
Speaker 1: I never thought that was gonna be I never thought

1382
01:13:52,920 --> 01:13:55,840
Speaker 1: there was gonna be a long term value to it. Um.

1383
01:13:55,880 --> 01:13:57,840
Speaker 1: I thought it was gonna be just valuable this week.

1384
01:13:58,360 --> 01:14:00,960
Speaker 1: But now I'm starting to real lies like this is

1385
01:14:01,520 --> 01:14:04,400
Speaker 1: this is like the best kept hunting journal in the

1386
01:14:04,439 --> 01:14:07,240
Speaker 1: world now because we can go back and and and

1387
01:14:07,240 --> 01:14:10,040
Speaker 1: look at journal entries from three or four years now

1388
01:14:10,120 --> 01:14:12,920
Speaker 1: from hunters all across the country and and then use

1389
01:14:13,000 --> 01:14:15,559
Speaker 1: that to to to predict things in the future. I

1390
01:14:15,560 --> 01:14:17,800
Speaker 1: think that's that's like really cool. When I start to

1391
01:14:17,800 --> 01:14:19,400
Speaker 1: think about that, I don't know, have you thought about

1392
01:14:19,400 --> 01:14:21,960
Speaker 1: that at all? Uh, not too much. I guess a

1393
01:14:22,000 --> 01:14:24,519
Speaker 1: little more, not that we have the three seasons worth

1394
01:14:24,560 --> 01:14:26,679
Speaker 1: of data, But that's a good point. If you see

1395
01:14:27,120 --> 01:14:29,800
Speaker 1: like a cold front coming in early October next year,

1396
01:14:29,920 --> 01:14:32,120
Speaker 1: go back and listen to those episodes that we had

1397
01:14:32,120 --> 01:14:34,840
Speaker 1: in eighteen, or if you notice it's gonna be a

1398
01:14:34,880 --> 01:14:37,280
Speaker 1: massive acorn crap, go back and listen to some of

1399
01:14:37,280 --> 01:14:40,720
Speaker 1: those episodes from seventeen, because those same things are are

1400
01:14:40,760 --> 01:14:43,479
Speaker 1: definitely good going to apply to what you're going to

1401
01:14:43,560 --> 01:14:47,080
Speaker 1: see that fall. Yeah, we talk a lot about increasingly

1402
01:14:47,080 --> 01:14:48,679
Speaker 1: more of the last couple of years. I've been talking

1403
01:14:48,680 --> 01:14:50,519
Speaker 1: about it because I've been hearing from other guys that

1404
01:14:50,560 --> 01:14:53,240
Speaker 1: are doing this, the idea of like annual trends with

1405
01:14:53,320 --> 01:14:56,479
Speaker 1: buck behavior. You know, so buck a did this in

1406
01:14:56,479 --> 01:14:58,320
Speaker 1: two thousands sixteen, and he did it again in two

1407
01:14:58,320 --> 01:15:00,080
Speaker 1: thousands seventeen. He might do it again to in the

1408
01:15:00,080 --> 01:15:03,400
Speaker 1: eighteen Well, I think the same thing goes for not

1409
01:15:03,479 --> 01:15:07,800
Speaker 1: just buck behavior trends, but also how dear react to

1410
01:15:07,880 --> 01:15:12,639
Speaker 1: different circumstances. So how things go with a great acorn crop,

1411
01:15:12,680 --> 01:15:14,960
Speaker 1: how things going to cold front hits on October twelve,

1412
01:15:15,080 --> 01:15:16,800
Speaker 1: how things go when you have a certain moon and

1413
01:15:16,880 --> 01:15:19,960
Speaker 1: laid October, How things go when you get really warm

1414
01:15:20,040 --> 01:15:23,120
Speaker 1: days November four through seven, um, And now we have

1415
01:15:23,240 --> 01:15:25,960
Speaker 1: this data set we can look back on as a reference.

1416
01:15:26,360 --> 01:15:30,040
Speaker 1: So so I guess I bring all that up to say,

1417
01:15:30,800 --> 01:15:33,680
Speaker 1: this is a great year of Runt Radio Spencer. It

1418
01:15:33,800 --> 01:15:37,320
Speaker 1: was awesome. I've found it really interesting. I appreciate you

1419
01:15:37,360 --> 01:15:39,760
Speaker 1: taking the time to to reach out to folks and

1420
01:15:39,800 --> 01:15:42,760
Speaker 1: collect all of their their inputs and and join me

1421
01:15:42,800 --> 01:15:45,080
Speaker 1: every week to talk about them. It's been fun, it's

1422
01:15:45,120 --> 01:15:47,799
Speaker 1: been interesting, and uh I think now that we've finished

1423
01:15:47,840 --> 01:15:51,280
Speaker 1: three years of it, I'm just more excited than ever

1424
01:15:51,320 --> 01:15:53,080
Speaker 1: for next year because I think we have this, this

1425
01:15:53,240 --> 01:15:55,599
Speaker 1: really cool hunting journal to look back on each year,

1426
01:15:55,960 --> 01:15:57,800
Speaker 1: And uh, I think what I want to do in

1427
01:15:57,840 --> 01:16:01,280
Speaker 1: two as nineteen is start at ofly referencing things and

1428
01:16:01,320 --> 01:16:03,800
Speaker 1: then looking back. So next year on October one, I'm

1429
01:16:03,800 --> 01:16:06,080
Speaker 1: gonna be telling you, well, hey, Spencer, I listened to

1430
01:16:06,080 --> 01:16:08,880
Speaker 1: the two thousand fifteen one and the two thousand seventeen one.

1431
01:16:09,640 --> 01:16:12,200
Speaker 1: There wasn't fifteen, but you know what I mean, um,

1432
01:16:12,240 --> 01:16:13,920
Speaker 1: and see how that might help us in the future.

1433
01:16:14,120 --> 01:16:17,719
Speaker 1: So thank you, Spencer. This is cool, this is fun,

1434
01:16:17,960 --> 01:16:21,400
Speaker 1: and uh, I think and I hope and I'm pretty

1435
01:16:21,479 --> 01:16:25,400
Speaker 1: damn sure that we're helping people with this and that's

1436
01:16:25,400 --> 01:16:30,120
Speaker 1: that's exciting good. I I enjoy it. I legitimately look

1437
01:16:30,160 --> 01:16:33,240
Speaker 1: forward to talking to these people each week because I'm

1438
01:16:33,280 --> 01:16:35,920
Speaker 1: into this stuff, just like I hope the listeners are,

1439
01:16:36,040 --> 01:16:38,600
Speaker 1: so uh, you know, I'm investing in the podcast and

1440
01:16:38,760 --> 01:16:42,920
Speaker 1: I hope it's helping people. Yeah, So with that, I

1441
01:16:43,000 --> 01:16:45,400
Speaker 1: think we sure up this one. So thank you for listening.

1442
01:16:45,439 --> 01:16:48,280
Speaker 1: If you're still hunting, good luck. If you're done hunting,

1443
01:16:48,280 --> 01:16:50,720
Speaker 1: hopefully found this helpful as you look to review the

1444
01:16:50,760 --> 01:16:53,679
Speaker 1: past season and start your preparation for two thousand nineteen.

1445
01:16:54,040 --> 01:16:59,040
Speaker 1: And with that said, until next time, stay wired. T

1446
01:16:59,240 --> 01:17:00,720
Speaker 1: h M.