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Speaker 1: This is Me Eat podcast coming in you shirtless, severely

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Speaker 1: bug bitten in my case underwear listening Hunt podcast. You

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Speaker 1: can't predict anything presented by on X. Hunt creators are

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Speaker 1: the most comprehensive digital mapping system for hunters. Download the

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Speaker 1: Hunt app from the iTunes or Google play store. Nor

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Speaker 1: where you stand with on X. All right, super special

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Speaker 1: guest Larry Todd. Larry, tell everybody what you do. Um, well,

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Speaker 1: I'm trained as an anthropologist archaeologist, but actually what I

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Speaker 1: do more than that is something called taff onom me,

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Speaker 1: which is the study of what happens to dead things. So, um,

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Speaker 1: my real passion when I started archaeology was looking at

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Speaker 1: bison kill sites. And to study a bison kill site,

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Speaker 1: you can't just look at the patterns you see when

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Speaker 1: you have excavated and say, well, people did this, and

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Speaker 1: people did that and people did the other. You've got

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Speaker 1: to look at what the carnivores did after the people

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Speaker 1: left the site, and what the decay of the bones

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Speaker 1: did to dispersal of things, and what um the rate

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Speaker 1: of deposition does to what bones are preserved, and looking

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Speaker 1: at all those sorts of things that happened after the

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Speaker 1: death of an animal until it enters the laboratory. Is

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Speaker 1: the field of taffonomy. We say, when you say kill sites,

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Speaker 1: I mean places where ancient people killed large groups of animals.

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Speaker 1: I specialized mostly in big bison kill sites, but I

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Speaker 1: also did a couple of mammoth sites, and did sites

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Speaker 1: where people suspected that horses had been killed, and a

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Speaker 1: variety of sorts of things. I was sort of a

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Speaker 1: um taffonymous for higher. Can you break down the word taffonomy,

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Speaker 1: It's it's from the Greek and um taff is death.

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Speaker 1: Anonomy is study of So a word that's similar that

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Speaker 1: you may have heard is epitaph, the words that are

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Speaker 1: on a tombstone. So um. The original definition was the

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Speaker 1: study of death and burial. Do you got your epitaff

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Speaker 1: figured out yet? No? I don't do you? No, man,

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Speaker 1: I don't have one yet. About mcwayen, I didn't think

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Speaker 1: of it either, said he already knows what he wants.

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Speaker 1: Make a good t shirt too. Once you got to

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Speaker 1: wear it on your shirt and then have him put

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Speaker 1: it on your tombstone. So taffonomy, am I saying? Right? Yeah, taffy.

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Speaker 1: So what's a large kill site like? What at what

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Speaker 1: point do you get what at what point do you

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Speaker 1: get interested? Oh? I get interested, um with a single animal.

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Speaker 1: But the ones that you focus on the most because

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Speaker 1: there's the highest information potential are ones that have anywhere

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Speaker 1: from can to I've worked on sites where there's close

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Speaker 1: to eight hundred to a thousand animals single sort of

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Speaker 1: cliff jumps um cliff jump. Well. One of the sites

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Speaker 1: that I spent about eleven years on is a site

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Speaker 1: in on the Nebraska National Forest called the Hudson Man Site,

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Speaker 1: and there's probably eight hundred bison there from the little

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Speaker 1: bit we saw of it. And one of the interesting

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Speaker 1: questions there and on many of the early sites, the

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Speaker 1: payment about ten thousand years ago. Uh, And one of

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Speaker 1: the interesting questions is how they died and whether it

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Speaker 1: was a kill. And there's a whole series of things

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Speaker 1: like that that go into the taff onomy step one

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Speaker 1: as you find a bunch of bones and is it

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Speaker 1: a natural death or is it a kill site? Um.

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Speaker 1: But one of the interesting things about you know, your

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Speaker 1: question about jumping over a cliff is many of the

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Speaker 1: early sites, the earliest sites in North America, the ones

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Speaker 1: from about thirteen thousand, tell about eight thousand, aren't associated

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Speaker 1: with jumps. UM, but they hadn't started that strategy. Maybe

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Speaker 1: they hadn't started it, or maybe they didn't need it. UM.

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Speaker 1: I think that UM. Probably the early people's in the

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Speaker 1: America were such specialists in bison behavior that they probably

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Speaker 1: made our PhDs new is zoology and ecology seemed like

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Speaker 1: kindergarteners of knowing what vice are going to do given

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Speaker 1: any given situation, the cloud cover, the bugs, the wind

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Speaker 1: direction when it's last reigned. They could probably use the

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Speaker 1: bison behavior to help get them into a place where

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Speaker 1: they could kill them, regardless of whether there was a

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Speaker 1: jump there. And so some of them are in big

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Speaker 1: open areas with no cliffs, no arroyo, UM, no obvious

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Speaker 1: sort of containment. And they probably at that time, UM,

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Speaker 1: they're probably encowering groups that haven't had a lot of

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Speaker 1: human pressure. Perhaps, Yeah, very definitely. They probably there The

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Speaker 1: animals that they were praying upon would have been used

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Speaker 1: to the way wolves would hunt them or other social

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Speaker 1: predators were, and all of a sudden you have this

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Speaker 1: different sort of social predator shows up on the scene.

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Speaker 1: And UM, something we might talk about a little further

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Speaker 1: on is one of the things I'm really worrying about

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Speaker 1: now is thinking about how that animal memory of kill

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Speaker 1: events feeds into how you can hunt inner region and

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Speaker 1: how often you can work through in mountain areas where

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Speaker 1: I'm working now, how often you can effectively run a

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Speaker 1: mountain sheep trap. Do you have to wait till the

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Speaker 1: next generation of mountain sheep shows up? Or is there

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Speaker 1: going to be somebody there in the herd that's gonna

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Speaker 1: you know, don't go up that ridge, you know, if

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Speaker 1: these sort of conditions, Yeah, yeah, to wait till their

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Speaker 1: memory faded before he came back, which is um. As

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Speaker 1: an anthropologist, it's both sort of interesting and almost heretical

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Speaker 1: to talk about that, because if you're talking about memory

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Speaker 1: and information being passed down from and stored in the

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Speaker 1: group from one generation to the next, you're talking about

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Speaker 1: what we usually classify as culture. And we usually when

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Speaker 1: we talk culture, UM, we usually say that's ours. You know,

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Speaker 1: humans are defined by culture and everybody else nana, Nana

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Speaker 1: doesn't have it. And so I'm trying to really think

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Speaker 1: about in terms of hunting and landscapes of multiple cultures

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Speaker 1: colliding human cultures versus the game, animal cultures information. If

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Speaker 1: you spend much time talking to um uh Kaufman, the

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Speaker 1: migration researcher a little bit. I'm working. I'm working more

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Speaker 1: with Arthur Middleton, who uh did the elk migration stuff

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Speaker 1: from Cody into the Yellows, because what you get into

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Speaker 1: there is what's interesting about their work with tracking collars

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Speaker 1: on modern animals. As you see, um, what like what

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Speaker 1: level of exposure like a newborn has when you have

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Speaker 1: a fawn or a calf hit the ground and it

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Speaker 1: is taken somewhere by its mother. Its ability to retain

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Speaker 1: that information after the death of the mother, and like

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Speaker 1: how well it can retrace routes and it's pretty stunning. Man.

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Speaker 1: As a matter of fact, I'm spending next week in

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Speaker 1: Berkeley with Middleton to talk about how we can better

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Speaker 1: integrate uh my archaeological data from the High elevation. So

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Speaker 1: I'm working in some of the same areas that he

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Speaker 1: has the Elk GPS color data on UM in terms

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Speaker 1: of answering questions that he's interested in, like, um, what's

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Speaker 1: the long term fidelity of these migration quarters? How long

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Speaker 1: do they go back in time? And UM I'm interested

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Speaker 1: in whether the corridors that the elk are using today

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Speaker 1: um My, my expectation is they're using sort of the

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Speaker 1: least cost path across the landscape. Um, that may have

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Speaker 1: been used by elk, and we know it's used by elk,

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Speaker 1: that it may have been used by bison that are

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Speaker 1: going into high country in the past, mountain sheep and humans.

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Speaker 1: So the the elk migration quarters may be giving us

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Speaker 1: a clue to what the past archaeology or the past

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Speaker 1: human landscape of high elevations was, and the archaeology can

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Speaker 1: also help um the wildlife people, uh, potentially see how

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Speaker 1: long those quarters have been there. Yeah, let me let

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Speaker 1: me do this from it, just to help people go

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Speaker 1: up speed. Uh, you start talking about the main site.

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Speaker 1: You can talk about that one or pick um sort

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Speaker 1: of your favorite site that you can think of like

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Speaker 1: a big kill site from from the from a very

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Speaker 1: old big kill site, and lay out what the body

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Speaker 1: of evidence is that you wind up working with to

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Speaker 1: ascertain what happened there, because because I would just I

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Speaker 1: would automatically think, like, wouldn't it just be that you

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Speaker 1: look for spear points and if there's spear points, then

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Speaker 1: it must have been people killing them. Explain how it

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Speaker 1: gets more complicated. That was sort of the assumption, and

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Speaker 1: I probably will stick with Hudson May because some recent

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Speaker 1: sites in the news, like there's a big mammoth site

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Speaker 1: down in Mexico that was okay. UM. So the uptell

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Speaker 1: about nineteen seventy or late nineteen sixties when people approached

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Speaker 1: the big kill sites that starting with Fulsome right on

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Speaker 1: up through the others. The sites themselves were pretty much

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Speaker 1: thought of as being quarries, UH that you'd extract the

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Speaker 1: bones from for exhibit, and then you'd also extract the

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Speaker 1: points from. But they didn't really do a lot of

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Speaker 1: work to kind of try and tie the two together

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Speaker 1: like it is coming and sift all the dirt out

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Speaker 1: and look washed them with water on some UH. Around

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Speaker 1: nineteen in the late nineteen sixties, a researcher down in Colorado,

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Speaker 1: UH named Joe Ben Wheat excavated a site called the

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Speaker 1: Olsen Chubbuck site. What he did there that was sort

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Speaker 1: of remarkable, as he started mapping and recording every bone

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Speaker 1: in the site, sort of like you'd have a jigsaw puzzle.

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Speaker 1: And he came up with the idea and he tried

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Speaker 1: to do the analysis that the site itself, the bone

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Speaker 1: bed itself, is a key artifact that in looking at

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Speaker 1: the distribution of where the cows are and the calves are,

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Speaker 1: and which how the carcasses are cut up and dispersed,

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Speaker 1: and that sort of stuff can give you a tremendous

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Speaker 1: amount of information. So and then several years after that,

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Speaker 1: UM George Frizzen from Wyoming followed up with a site

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Speaker 1: called the Casper Site where he kind of took that

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Speaker 1: perspective into account as well the site as an artifact

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Speaker 1: and then tried to plug in bison paleo ecology of

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Speaker 1: how they lived on the landscape and what had happened

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Speaker 1: after it. Explain your term whether the site is an artifact? Okay, Um,

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Speaker 1: we all when we think of you talked about you

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Speaker 1: find the points with the bones. We all know that

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Speaker 1: a nice piece of stone. That's been the definition of

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Speaker 1: an artifact. Oh, an artifact humanly produced, humanly creative. Like

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Speaker 1: if you could pick up if you pick up a

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Speaker 1: bone and it has cut mark, you pick up an

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Speaker 1: ancient bone. Is the bone the mini has cut marks

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Speaker 1: on it, it's an artifact. And the idea of the

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Speaker 1: bone bed is artifact is that just like the individual

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Speaker 1: flake scars on a flake, piece of stone have to

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Speaker 1: be looked at altogether to understand it. You don't just

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Speaker 1: have that individual bone with a cut mark on it,

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Speaker 1: but you need to know how it's positioned next to

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Speaker 1: this one and that one, and where it is um

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Speaker 1: within the bone bed, and that you need to look

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Speaker 1: at the whole picture rather than individual pieces. So the site,

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Speaker 1: the bone bed, that pile of dead animals um could

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Speaker 1: be conceived of as an artifact. Yeah, you know a

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Speaker 1: thing we talked about um that we talked with the

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Speaker 1: David Melzer ones and we're talking about the full sume site.

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Speaker 1: An interesting thing like like you're getting at with the

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Speaker 1: full sum site is uh, I think the ribs slabs

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Speaker 1: are not there, which suggests that when they butchered those

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Speaker 1: things whatever twelve thou years ago, when they butchered them,

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Speaker 1: they hauled out the ribs on the bone because it's

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Speaker 1: not in the bone bed. So that's like that they're

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Speaker 1: the absence of something. Is the absence of something becomes interesting? Huh,

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Speaker 1: Well that's and that's where you start looking at both

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Speaker 1: what's there and what's missing. So we're up to the

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Speaker 1: nineteen sixties and that was sort of the in seventies.

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Speaker 1: That was respective of, um, these bone beds are artifacts,

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Speaker 1: and then this caff onomy stuff sort of reared its

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Speaker 1: ugly head. And one of the things that taffonomy does

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Speaker 1: is it's sort of the wait a minute, let's take

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Speaker 1: another look at this science. Uh, it's sort of often

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Speaker 1: points out what you don't know and why you don't

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Speaker 1: know it, rather than as the way the way we

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Speaker 1: normally think of science as accumulating information. Uh, Taffonomic analysis

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Speaker 1: more often than not leaves you with, well, we're not

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Speaker 1: sure about that, we don't know that or the other.

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Speaker 1: So go back to that bone bed. As an artifact,

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Speaker 1: everything in it is telling you something about human behavior.

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Speaker 1: And so that if a bone's missing, people took it away.

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Speaker 1: If your carcasses are completely disarticulated, people cut them into

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Speaker 1: little butchering units and depositive than they're quartering it out. Yeah,

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Speaker 1: And if bones were broken, human broke. Humans broke them

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Speaker 1: to get out the marrow. So from the bone bed

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Speaker 1: is artifact perspective. Everything there was telling you about human

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Speaker 1: behavior to give you a really rich picture of what

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Speaker 1: was going on there. And where the taffonomy comes in

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Speaker 1: is going Now, wait a minute, we start looking at

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Speaker 1: some of these bones and they've got wolf tooth marks

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Speaker 1: on them. Uh, don't you suppose the wolves were taking

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Speaker 1: away some of the bones as well when they were

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Speaker 1: coming in after the humans were there. You start looking

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Speaker 1: at other the bones and yeah, they're broken, but they're

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Speaker 1: broken with the center part pushed down into the ground

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Speaker 1: as if something had stepped on it later. So you

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Speaker 1: can't just look at the frequency of bone breakage and say, um,

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Speaker 1: humans broke every bone. Um. Just because carcass is not

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Speaker 1: completely all together in a skeleton doesn't mean that humans

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Speaker 1: had taken it apart into those individual parts. We've all

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Speaker 1: walked across the landscape and seeing dead things, and more

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Speaker 1: often than not, they're not all completely together, scattered, there's

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Speaker 1: a there's a shin bone, and yeah, I wonder where

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Speaker 1: the skull is. You never find them. But for a

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Speaker 1: while when we were doing archaeology, we sort of forgot

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Speaker 1: about that. We'd look at the site as if any

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Speaker 1: of those processes happened or stopped happening just as soon

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Speaker 1: as humans left way and it was frozen in time.

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Speaker 1: And so the taffonomic study tries to bring all those

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Speaker 1: other factors into account of how many of the bones

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Speaker 1: do have the carnivore tooth marks. What percentage of them

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Speaker 1: have cut marks relative to tooth marks. What breakage appears

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Speaker 1: to have happened um paramortem soon soon after death as

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Speaker 1: opposed to long after death, where so you can maybe

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Speaker 1: separate out um the human breakage from the trampling breakage

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Speaker 1: from the dry bone breakage later um scattering. One of

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Speaker 1: the studies I spent did my doctoral dissertation work on

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Speaker 1: is I spent a lot of time looking at how

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Speaker 1: recently dead cows would get dispersed across the landscape and

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Speaker 1: measuring the distance from for example, a hip to where

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Speaker 1: the femur went and how that changed and started going.

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Speaker 1: Because you can do and you can do it with

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Speaker 1: a known individual, and then when you go to an

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Speaker 1: archaeological site, you can start measuring the bones and start

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Speaker 1: begin recognizing the bones of individual animals and see how

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Speaker 1: they get dispersed, and see if the dispersal patterns you

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Speaker 1: see within the bone beds differs from what you see naturally.

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Speaker 1: So part of what taffonomy does is tries to establish

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Speaker 1: some of those natural patterns uh without assuming that every Again,

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Speaker 1: one of the strange things that archaeologists do is we

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Speaker 1: tend to have this idea that humans create patterns in

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Speaker 1: the world and everything else creates chaos and randomness. And

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Speaker 1: we all know by looking at for example, away streams

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Speaker 1: move cobbles around. Uh, they sort them by sizes, they

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Speaker 1: sort them by shapes. We're not We're just one of

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Speaker 1: many pattern creating creatures. So you can use as your

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Speaker 1: standard basic methodology of if you see a pattern, we

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Speaker 1: did it. And so taffonomy tries to understand all those

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Speaker 1: other sorts of patterns that can go into it. And

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Speaker 1: as I mentioned before, that sort of gets you into

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Speaker 1: that Hey wait a minute, Wait a minute, Wait a minute.

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Speaker 1: So you asked me to talk about a specific site

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Speaker 1: and the side um that I said. I spent eleven

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Speaker 1: years on the Hudson Man bison kill site. It was

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Speaker 1: called the Hudson Wing buy some kill site when we

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Speaker 1: got there. Uh, and there's close to eight animals. You're

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Speaker 1: not gonna tell me this buzz kill story, right, I

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Speaker 1: don't want to be a kill site. Yeah, well, we

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Speaker 1: don't know. My bottom line now is after you do

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Speaker 1: the taphonomic analysis, you get to the well, it could

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Speaker 1: be a kill site. Um, but there's a lot of

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Speaker 1: things that don't necessarily mean there's some points there. Um,

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Speaker 1: does that mean that the people killed the animals. There's

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Speaker 1: twenty three points and eight hundred animals, so sort of

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Speaker 1: as a and that's doesn't fit the pattern we see

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Speaker 1: If okay, these eight hundred animals are stretched out of

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Speaker 1: what size patch of ground they're oh, in the size

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Speaker 1: of this room, you know, um, thirty by twenty ft,

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Speaker 1: there's probably like no, no, they're over hughes area. But

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Speaker 1: in the size of this room there could be the

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Speaker 1: remains of fifteen to twenty animals. It's just a solid

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Speaker 1: sea of bone, bone on bone on So they cover

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Speaker 1: oh maybe seventy by fifty so a little less than

301
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Speaker 1: the size of a square football field. And in the

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Speaker 1: US were spread out over how much time looks like

303
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Speaker 1: almost instantaneously you can look at if you can assess

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Speaker 1: time of death by looking at tooth eruption and wear patterns.

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Speaker 1: And so if there's um mass kill, a mass death, UM,

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Speaker 1: there's going to be a snapshot of the age structure

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Speaker 1: of the population. And since um bison are birth pole species,

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Speaker 1: they have most of their calves within about a two

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Speaker 1: week period in the spring, and the biological schedule of

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Speaker 1: when the teeth erupt and when they start wearing from

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Speaker 1: chewing on grass is predictable. You can look at the

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Speaker 1: jaws of the calves in a sight like that and

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Speaker 1: tell how old they were at the time. So, um,

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Speaker 1: you can all these calves that all have the same

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Speaker 1: Hudson man looks like they were like four months old. Um,

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Speaker 1: so sort of middle of the summer, late summer so

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Speaker 1: and then and then you know in the age structure,

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Speaker 1: then you'll have a gap in the age structure. And

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Speaker 1: then you'll have animals that are a year and four

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Speaker 1: months old and two years and four months old. And

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Speaker 1: when you get that nice discrete um sets of age structures,

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Speaker 1: that tells you you've got a catastrophic a mass depth

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Speaker 1: of all those animals dying at once in the twenty

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Speaker 1: six points, how I forget the exact how like, how

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Speaker 1: directly affiliated are they with the bones stuck into them? No,

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Speaker 1: some are um, some are associated in the same stratigraphic

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Speaker 1: level as the bone, some are slightly above it, some

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Speaker 1: are slightly below it. Um. There's one point that was

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Speaker 1: reported to have been stuck into a bone. But when

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Speaker 1: we went back through the collections, the point and the

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Speaker 1: bone that's associated with have different catalog numbers and say

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Speaker 1: they're from different parts of the site and someone pulled

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Speaker 1: it out well, or that somewhere in the recording process

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Speaker 1: it wasn't recorded in a way that we can today

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Speaker 1: go back to it and say, yeah, we're a hundred

336
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Speaker 1: share of that bone was stuck in that. So when

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Speaker 1: we record a bone on a site like that, and

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00:19:07,560 --> 00:19:10,480
Speaker 1: like I said, there's um two hundred some bones and

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Speaker 1: the skeleton of a bison and eight hundred bison, getting

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Speaker 1: sort to do the work and imagine how many bones

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00:19:15,359 --> 00:19:19,480
Speaker 1: might be there when we recorded site today, UM, with

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Speaker 1: this taffonomic perspective on the in in mind. Before we

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Speaker 1: remove it from the ground, we record about twenty nine

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Speaker 1: separate observations on each individual bone that goes into a

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Speaker 1: massive data set. So you don't have that that problem

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Speaker 1: down the line of which bone was where it's like, um,

347
00:19:37,640 --> 00:19:40,200
Speaker 1: Digging a site like a bone bed is like taking

348
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Speaker 1: apart a hugely complex jigsaw puzzle that you're wanting to

349
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Speaker 1: be able to tell somebody in the future how to

350
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Speaker 1: put it back together exactly like it was. So you

351
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Speaker 1: don't just say there's blue pieces over here and red

352
00:19:51,240 --> 00:19:54,200
Speaker 1: pieces over there. Every piece of that puzzle has an

353
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Speaker 1: inventory number and its exact location is is pinpointed, so

354
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Speaker 1: that no the way you think of execrating a site.

355
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Speaker 1: So at Hudson May we went in. I was thrilled

356
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Speaker 1: to go into being able to dig the largest known

357
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Speaker 1: paleo Indian bison kill site in North America. And one

358
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Speaker 1: of the things that the original researchers noted were that

359
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Speaker 1: there were no skulls there, that they've been taken somewhere else.

360
00:20:21,040 --> 00:20:25,080
Speaker 1: Ud skulls gone, eight hundred skulls gone, um, which led

361
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Speaker 1: to an interpretation if there must have been some sort

362
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Speaker 1: of ceremonial thing, you know, because this we gotta add

363
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Speaker 1: we laughed all this all time. Everything they can't understand

364
00:20:35,520 --> 00:20:40,040
Speaker 1: become ceremony exactly. That's that's in there with um. Only

365
00:20:40,119 --> 00:20:42,359
Speaker 1: humans create patterns, and if we don't see a pattern

366
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Speaker 1: that we recognize, it must be a ceremony there. It's

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Speaker 1: a corollary to that. It's like everything, like you know,

368
00:20:47,800 --> 00:20:52,880
Speaker 1: there's three skulls lined up, must been ceremonials. Sometimes you'll

369
00:20:52,880 --> 00:20:57,520
Speaker 1: get to two. Yeah, ceremonial. You see, my kids do

370
00:20:57,600 --> 00:21:02,399
Speaker 1: stuff so they're not they line everything up their Halloween candy.

371
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Speaker 1: Is it ceremonial. I don't know, it's just lining. Shut up.

372
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Speaker 1: So that was one of the interpretations of you know,

373
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Speaker 1: the skulls were missing as a matter of fact, when

374
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Speaker 1: I first started working there with the Forest Service, and

375
00:21:14,520 --> 00:21:16,960
Speaker 1: they had this idea to kind of attract funding and

376
00:21:16,960 --> 00:21:23,960
Speaker 1: attractive skin attention to call it the Lost Skull Learning Center. No, yeah, yeah, okay, okay,

377
00:21:24,119 --> 00:21:27,159
Speaker 1: keep going. So I keep like interject because here's the

378
00:21:27,240 --> 00:21:29,040
Speaker 1: problem in talking to me. Then the problem with you

379
00:21:29,119 --> 00:21:32,240
Speaker 1: talking to me is, I know, like I've heard of

380
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Speaker 1: all this stuff. I don't really know what goes on

381
00:21:35,240 --> 00:21:37,919
Speaker 1: behind the scene story. Yeah, like I know the version

382
00:21:38,200 --> 00:21:40,199
Speaker 1: that it was like that they slaughtered eight hunter him

383
00:21:40,200 --> 00:21:42,040
Speaker 1: in a giant pile. Yeah, I didn't know that. Then

384
00:21:42,119 --> 00:21:46,040
Speaker 1: later that story maybe became more complicated. So so we

385
00:21:46,119 --> 00:21:49,040
Speaker 1: got we got missing skulls. The other argument that was

386
00:21:49,160 --> 00:21:53,040
Speaker 1: used early on was that all the animals were completely disarticulated,

387
00:21:53,080 --> 00:21:56,359
Speaker 1: cut into bits and pieces. Um. The other argument is

388
00:21:56,640 --> 00:21:59,719
Speaker 1: even though there wasn't one there now, there had been

389
00:21:59,760 --> 00:22:04,640
Speaker 1: a cliff there in the past that's been filled with sediment.

390
00:22:04,840 --> 00:22:08,159
Speaker 1: Oh the sink whole, Well, it's it's a it's natural cliff.

391
00:22:08,400 --> 00:22:12,639
Speaker 1: There's other sides sinkholes. So you've got a cliff on

392
00:22:12,640 --> 00:22:17,080
Speaker 1: one side, and then about seventy potential cliff area about

393
00:22:17,080 --> 00:22:20,000
Speaker 1: seventy away, you've got this pile of bones. And so

394
00:22:20,040 --> 00:22:22,320
Speaker 1: they're saying, well, the animals went over a cliff, they

395
00:22:22,320 --> 00:22:24,679
Speaker 1: cut them apart, they drugged these bones over here for

396
00:22:24,720 --> 00:22:27,400
Speaker 1: the secondary processing. So that's what I thought was going

397
00:22:27,440 --> 00:22:30,960
Speaker 1: on there when we started recording the site, and one

398
00:22:31,000 --> 00:22:32,680
Speaker 1: of the first things we noted is when we got

399
00:22:32,720 --> 00:22:37,200
Speaker 1: down into the bone bed, there weren't complete skulls, sure enough,

400
00:22:37,560 --> 00:22:40,199
Speaker 1: but there were lots of maxillary tooth throws up her

401
00:22:40,240 --> 00:22:42,840
Speaker 1: tooth throws. There were lots of the petros portion, the

402
00:22:42,880 --> 00:22:45,720
Speaker 1: big hard portion of the in the inside of the head,

403
00:22:45,760 --> 00:22:48,480
Speaker 1: there was uh, the occipitals the base of the skull.

404
00:22:48,520 --> 00:22:52,200
Speaker 1: There's lots of portions of skulls, but no complete skulls really,

405
00:22:52,520 --> 00:22:56,960
Speaker 1: And then you start thinking, uh, one time we killed

406
00:22:57,119 --> 00:23:01,000
Speaker 1: h I brother killed elk and we quartered it out

407
00:23:02,840 --> 00:23:05,800
Speaker 1: and it was a cow. I love the head lander.

408
00:23:06,280 --> 00:23:08,040
Speaker 1: Week later we went back to see what the grizzlies

409
00:23:08,040 --> 00:23:10,560
Speaker 1: did to it. I guess what was left. Not They

410
00:23:10,600 --> 00:23:12,760
Speaker 1: started right at the nose and work their way back,

411
00:23:12,920 --> 00:23:16,720
Speaker 1: was that ball of like that ball of bone. That's

412
00:23:16,720 --> 00:23:20,080
Speaker 1: funny one the other because you're now you're peaking my interest.

413
00:23:20,480 --> 00:23:23,399
Speaker 1: So um. One of the things we record is if

414
00:23:23,440 --> 00:23:26,000
Speaker 1: you imagine a bone laying on the ground and it's

415
00:23:26,000 --> 00:23:28,520
Speaker 1: not laying completely flat. Well, let's say we've got a

416
00:23:28,560 --> 00:23:31,400
Speaker 1: bone laying on the ground and it's flat. I talked

417
00:23:31,400 --> 00:23:33,920
Speaker 1: about those twenty nine attributes to record on each bone,

418
00:23:33,960 --> 00:23:36,920
Speaker 1: and one of them record we record is the degree

419
00:23:37,000 --> 00:23:40,000
Speaker 1: of weathering. You know, when you first expose a bone

420
00:23:40,040 --> 00:23:44,440
Speaker 1: after an animal dies, it's nice and clean and solid

421
00:23:44,480 --> 00:23:46,560
Speaker 1: surface and all that sort of stuff. Go back and

422
00:23:46,560 --> 00:23:48,919
Speaker 1: look at that bone two years later, and it's starting

423
00:23:48,920 --> 00:23:52,000
Speaker 1: to crack and the pieces of it are starting to

424
00:23:52,119 --> 00:23:56,080
Speaker 1: chew up, and there's becomes porous and linear fractures through

425
00:23:56,119 --> 00:24:00,600
Speaker 1: it and all that. We've developed coating systems to describe weathering,

426
00:24:01,119 --> 00:24:04,959
Speaker 1: and so we record the weather degrees of weathering. Uh.

427
00:24:05,359 --> 00:24:08,240
Speaker 1: One of the sets of attributes to record are the

428
00:24:08,320 --> 00:24:10,679
Speaker 1: weathering on the top surface of the bone and the

429
00:24:10,720 --> 00:24:13,359
Speaker 1: weathering on the bottom surface of the bone, with the

430
00:24:13,400 --> 00:24:15,399
Speaker 1: idea being if the bones laying there on the ground

431
00:24:15,440 --> 00:24:18,399
Speaker 1: surface and not being moved, there's a good chance that

432
00:24:18,400 --> 00:24:20,520
Speaker 1: it's going to be weathered more intensively on the top

433
00:24:20,560 --> 00:24:23,840
Speaker 1: and the bottom, like like a year old drop antler. Yeah,

434
00:24:24,080 --> 00:24:28,600
Speaker 1: you'll like exactly, yeah, and then you know it's like

435
00:24:28,800 --> 00:24:30,960
Speaker 1: it's been there, but it hasn't been there that long.

436
00:24:31,160 --> 00:24:34,680
Speaker 1: So imagine that going on in this pile of eight bison,

437
00:24:35,119 --> 00:24:39,080
Speaker 1: and you're starting to get some sand and sediments blowing in.

438
00:24:40,080 --> 00:24:42,040
Speaker 1: It's going to start covering up the basis of some

439
00:24:42,119 --> 00:24:44,840
Speaker 1: of those bones, and they're gonna start kept in place.

440
00:24:44,920 --> 00:24:48,400
Speaker 1: They're sort of um, not glued down, but they're held

441
00:24:48,440 --> 00:24:51,360
Speaker 1: in place by the sediments and it's not blowing in.

442
00:24:51,359 --> 00:24:54,080
Speaker 1: And one huge nineteen thirties dust storm, you know, it's

443
00:24:54,119 --> 00:24:56,480
Speaker 1: accumulating a little bit by a little bit, by a

444
00:24:56,520 --> 00:24:58,840
Speaker 1: little bit by a little bit. That it may take

445
00:24:59,280 --> 00:25:03,280
Speaker 1: fift wenty years for a foot of sentiment to build up.

446
00:25:03,960 --> 00:25:07,080
Speaker 1: Think of how big a bison skull is. It'll stand,

447
00:25:07,160 --> 00:25:09,479
Speaker 1: you know, a foot and half from the teeth up

448
00:25:09,480 --> 00:25:11,879
Speaker 1: to the top of it above the ground surface. So

449
00:25:12,000 --> 00:25:15,360
Speaker 1: while many bones of the skeleton can be completely buried

450
00:25:15,440 --> 00:25:17,760
Speaker 1: within a few years, they're still going to be the

451
00:25:17,760 --> 00:25:20,879
Speaker 1: tops of those skulls sticking up above the ground, continuing

452
00:25:20,920 --> 00:25:24,119
Speaker 1: to weather. Continuing to be trampled on, continuing to be

453
00:25:24,200 --> 00:25:27,080
Speaker 1: broken into bits and pieces. So unless you have very

454
00:25:27,160 --> 00:25:30,000
Speaker 1: rapid sedimentation across the site, you're not going to find

455
00:25:30,000 --> 00:25:34,040
Speaker 1: the skulls. Yeah. So um so that came into play.

456
00:25:34,040 --> 00:25:36,960
Speaker 1: And then we stuff combined non on them. Yeah, or

457
00:25:37,119 --> 00:25:39,320
Speaker 1: the next herd of bison that runs across that area

458
00:25:39,400 --> 00:25:42,760
Speaker 1: trampling on it. Um. All those sorts of things can

459
00:25:42,840 --> 00:25:48,439
Speaker 1: reduce the skulls to lots of not the sort of

460
00:25:48,440 --> 00:25:51,359
Speaker 1: hang on your wall quality skulls, but they're still were

461
00:25:51,800 --> 00:25:55,720
Speaker 1: there their bits and pieces. So that sort of took

462
00:25:56,200 --> 00:25:59,600
Speaker 1: the law Skull Learning Center out of the category of

463
00:25:59,640 --> 00:26:03,040
Speaker 1: being not just silly, but maybe maybe the eroded school

464
00:26:03,160 --> 00:26:06,040
Speaker 1: learning center. Yeah. That we got that ruin the wrong

465
00:26:06,160 --> 00:26:09,600
Speaker 1: learning center, which is what learning is all about, isn't it. Um.

466
00:26:09,800 --> 00:26:13,240
Speaker 1: Then we started looking at things like um, as I said,

467
00:26:13,240 --> 00:26:16,479
Speaker 1: we record each individual bone and start doing measurements of

468
00:26:16,880 --> 00:26:19,200
Speaker 1: the articular surfaces, and you can match those to the

469
00:26:19,280 --> 00:26:21,520
Speaker 1: other bones they go to. And so rather than saying

470
00:26:21,520 --> 00:26:24,600
Speaker 1: these animals have all been brought from point A to

471
00:26:24,640 --> 00:26:29,080
Speaker 1: point B as little discrete groups, it looks like each

472
00:26:29,119 --> 00:26:32,159
Speaker 1: carcass is kind of scattered within a couple of meter area.

473
00:26:32,440 --> 00:26:34,520
Speaker 1: You know, it's what happens if you kind of be

474
00:26:34,640 --> 00:26:37,840
Speaker 1: there and fall apart and get scattered. It's not everything

475
00:26:37,920 --> 00:26:41,600
Speaker 1: is randomly dispersed, and here and there the carcasses are

476
00:26:41,720 --> 00:26:44,280
Speaker 1: in the point where the unless people are dragging complete

477
00:26:44,320 --> 00:26:47,639
Speaker 1: bison carcasses across the landscape for seventy there in the

478
00:26:47,640 --> 00:26:50,760
Speaker 1: position where they died. Well, I gotta pause you from

479
00:26:50,800 --> 00:26:57,800
Speaker 1: it now that you're deconstructing, like the initial hypothesis, what

480
00:26:57,920 --> 00:27:01,120
Speaker 1: like I honestly like, how did someone like what size

481
00:27:01,200 --> 00:27:05,480
Speaker 1: group of individuals would they postulate would have even been

482
00:27:05,520 --> 00:27:11,919
Speaker 1: capable of butchering eight hundred bison? Eight hundred bison in

483
00:27:12,400 --> 00:27:15,560
Speaker 1: the mid to late summer. I mean sort of incorporating

484
00:27:15,600 --> 00:27:17,919
Speaker 1: idea that we're talking about groups of individuals that might

485
00:27:17,960 --> 00:27:20,679
Speaker 1: have been ten to thirty individuals roaming around, yeah, to

486
00:27:21,160 --> 00:27:26,320
Speaker 1: the labor force to butcher that many animals as completely

487
00:27:26,400 --> 00:27:29,760
Speaker 1: as they were argued to be butchered, would be boy,

488
00:27:29,960 --> 00:27:31,399
Speaker 1: you know, we could call out half the town of

489
00:27:31,440 --> 00:27:34,640
Speaker 1: Bozeman for a weekend and maybe get it done. Yeah,

490
00:27:34,760 --> 00:27:37,840
Speaker 1: six to ten people per animal. Yeah, right, and then

491
00:27:38,000 --> 00:27:40,239
Speaker 1: we're talking about and they're not just in a summertime, right,

492
00:27:40,240 --> 00:27:42,159
Speaker 1: They're not just stripping the meat off. The argument was

493
00:27:42,240 --> 00:27:44,919
Speaker 1: they were um then cutting him into segments. They were

494
00:27:44,960 --> 00:27:47,919
Speaker 1: moving him across the landscape. Then it has brought a

495
00:27:48,000 --> 00:27:53,479
Speaker 1: hunter butcher over there had been like bullshit man the summertime, right,

496
00:27:53,880 --> 00:27:57,200
Speaker 1: Well that's yeah, what's the tooth eruption? And where they're

497
00:27:57,200 --> 00:28:00,119
Speaker 1: gonna be going bad? Quick, bad? I mean yeah, it's

498
00:28:00,119 --> 00:28:03,520
Speaker 1: not like you're gonna be um. You talked about looking

499
00:28:03,560 --> 00:28:07,199
Speaker 1: at the grizzly gnawing on the skull. Imagine what's going

500
00:28:07,280 --> 00:28:09,600
Speaker 1: to happen to the grizzlies and the wolves and everybody

501
00:28:09,600 --> 00:28:12,120
Speaker 1: else there when you've got eight hundad hearts. It's gonna

502
00:28:12,119 --> 00:28:14,560
Speaker 1: be whol like when a whale washes up on the

503
00:28:14,560 --> 00:28:16,400
Speaker 1: beach in Alaska, you know. And I realized they got

504
00:28:16,400 --> 00:28:19,240
Speaker 1: like thirteen polar bears. So it's gonna be a dangerous

505
00:28:19,240 --> 00:28:21,840
Speaker 1: place to be if you're you're a hunter and gathered family,

506
00:28:21,880 --> 00:28:24,240
Speaker 1: you're not gonna wait around there. So there are all

507
00:28:24,240 --> 00:28:28,119
Speaker 1: sorts of things. And then eventually, uh, we got in

508
00:28:28,520 --> 00:28:31,720
Speaker 1: the big equipment, the heavy equipment, and exavated some big

509
00:28:31,760 --> 00:28:34,400
Speaker 1: trenches back to where the cliff was supposedly because if

510
00:28:34,800 --> 00:28:37,119
Speaker 1: you know, again, you're always trying to evaluate the models

511
00:28:37,119 --> 00:28:40,440
Speaker 1: of Okay, it's not looking like a jump over a cliff,

512
00:28:40,480 --> 00:28:42,040
Speaker 1: but let's go to the base of the cliff and

513
00:28:42,080 --> 00:28:44,840
Speaker 1: see what's going on there. And what we found is, yeah,

514
00:28:44,840 --> 00:28:49,719
Speaker 1: there's a bedrock um cliff there. But you can follow

515
00:28:50,360 --> 00:28:53,920
Speaker 1: the buried soils um from where the bone bed is

516
00:28:54,440 --> 00:28:57,080
Speaker 1: back towards the cliff, and as they approached the cliff

517
00:28:57,120 --> 00:29:00,040
Speaker 1: they form a gentle surface. That cliff was already be

518
00:29:00,160 --> 00:29:04,520
Speaker 1: buried at the time the animals died. And just looking

519
00:29:04,520 --> 00:29:08,360
Speaker 1: at this like the sediment whatever the sediment lines, you're

520
00:29:08,440 --> 00:29:11,400
Speaker 1: you're reconstructing what the old land surface looking. So then

521
00:29:11,440 --> 00:29:13,680
Speaker 1: for a while, UM, the crew would joke about things

522
00:29:13,720 --> 00:29:15,719
Speaker 1: and well, maybe it isn't a bison jump, maybe it's

523
00:29:15,720 --> 00:29:18,880
Speaker 1: a bison stumble they were running down the hill, or

524
00:29:18,880 --> 00:29:23,480
Speaker 1: what about they got burned up. That's um, that's we

525
00:29:23,520 --> 00:29:26,760
Speaker 1: don't see um, and that's we And we talked about

526
00:29:26,760 --> 00:29:28,480
Speaker 1: taff On. I mean the things taff On I must

527
00:29:28,520 --> 00:29:32,600
Speaker 1: get excited about is research opportunities, like boy, a grass

528
00:29:32,600 --> 00:29:34,640
Speaker 1: fires killed a cow. Let's go look at it to

529
00:29:34,680 --> 00:29:37,200
Speaker 1: see what happens, to know what parts of the skelet

530
00:29:37,200 --> 00:29:40,000
Speaker 1: and how badly they get burned. We don't see any

531
00:29:40,040 --> 00:29:42,959
Speaker 1: of that kind of burning in the bone bed itself.

532
00:29:42,960 --> 00:29:44,920
Speaker 1: And remind me to talk about burning in the bone

533
00:29:44,920 --> 00:29:46,520
Speaker 1: bed in a minute. And they couldn't have got stuck

534
00:29:46,560 --> 00:29:48,680
Speaker 1: in the mud. Now there's not you know, if you

535
00:29:48,680 --> 00:29:50,320
Speaker 1: get stick in the stuck in the mud. We've got

536
00:29:50,360 --> 00:29:52,120
Speaker 1: some sites like that and you find things like the

537
00:29:52,160 --> 00:29:56,040
Speaker 1: feet and the toes and the limbs down in the mud. Uh,

538
00:29:56,200 --> 00:29:58,400
Speaker 1: you know they were so damn get out and there

539
00:29:58,400 --> 00:30:01,920
Speaker 1: can be a foot and half difference between the elevations

540
00:30:01,920 --> 00:30:03,640
Speaker 1: of the feet and the rest of the body where

541
00:30:03,640 --> 00:30:06,480
Speaker 1: it finally comes to life. These are smeared across one

542
00:30:06,560 --> 00:30:09,440
Speaker 1: land surface. So lightning strike couldn't do that. Could maybe

543
00:30:09,520 --> 00:30:12,120
Speaker 1: if they're all that's one of our suggestions that is

544
00:30:12,320 --> 00:30:16,320
Speaker 1: potentially if they're um heard it, they're together, you know,

545
00:30:18,000 --> 00:30:20,880
Speaker 1: the one lightning strike could do it. What about when

546
00:30:21,040 --> 00:30:25,120
Speaker 1: tornadoes them not in tornado country young in Nebraska. We're

547
00:30:25,120 --> 00:30:29,360
Speaker 1: in northwestern Nebraska, so tornadoes could be possible and I

548
00:30:29,440 --> 00:30:33,920
Speaker 1: don't know they're there. Again, what things you wish for?

549
00:30:34,080 --> 00:30:35,920
Speaker 1: Wouldn't it be fun to find a hurt of cows

550
00:30:35,920 --> 00:30:39,360
Speaker 1: have been killed by a tornado. Well, I don't know

551
00:30:39,400 --> 00:30:42,160
Speaker 1: whether I'm sure they get killed, but um, in that

552
00:30:42,240 --> 00:30:44,440
Speaker 1: sort of number, they probably get killed one, two, three

553
00:30:44,480 --> 00:30:46,920
Speaker 1: at a time. Do that Does it aggregate them in

554
00:30:46,960 --> 00:30:50,000
Speaker 1: the tornado or does it scatter them across the landscape?

555
00:30:50,120 --> 00:30:54,200
Speaker 1: Don't know? Um. You ask about fire, um, and we

556
00:30:54,280 --> 00:30:56,800
Speaker 1: don't see evidence of direct burning on the animals. But

557
00:30:56,840 --> 00:30:59,160
Speaker 1: they're down below where this cliff was and sort of

558
00:30:59,160 --> 00:31:02,120
Speaker 1: a swale next to a damp area where you might

559
00:31:02,160 --> 00:31:05,600
Speaker 1: aggregate it a prairie fires burning. And one of the

560
00:31:05,640 --> 00:31:08,120
Speaker 1: things that happens in fires when they burn over areas

561
00:31:08,160 --> 00:31:10,720
Speaker 1: like that is they'll often suck the oxygen out of

562
00:31:10,760 --> 00:31:14,600
Speaker 1: low lying areas, so they may have asphyxiated. So by

563
00:31:14,600 --> 00:31:17,520
Speaker 1: the time we got done at Hudson Man, the original

564
00:31:17,520 --> 00:31:22,520
Speaker 1: excavator was really sort of irritated at it um. And

565
00:31:22,600 --> 00:31:24,840
Speaker 1: we never said that it wasn't a kill site. Did he?

566
00:31:25,200 --> 00:31:28,720
Speaker 1: Did he double down? You know? I'm reading a book

567
00:31:28,760 --> 00:31:33,080
Speaker 1: by I read a book by an entomologist that's going

568
00:31:33,120 --> 00:31:37,040
Speaker 1: to come on the show named Justin Schmidt, and he

569
00:31:37,360 --> 00:31:41,640
Speaker 1: studies UH insect toxins. But he has a early in

570
00:31:41,680 --> 00:31:44,440
Speaker 1: his book, he has a thing he's pointing out like, uh,

571
00:31:44,920 --> 00:31:46,720
Speaker 1: this is no offense to you. He says. The reason

572
00:31:46,760 --> 00:31:51,240
Speaker 1: all the great discoveries are made by young scientists is

573
00:31:51,240 --> 00:31:55,240
Speaker 1: because they don't give a shit about what everybody thinks.

574
00:31:55,640 --> 00:31:57,320
Speaker 1: And then you come up with something, and then most

575
00:31:57,360 --> 00:31:59,080
Speaker 1: of them then spend the rest of their life trying

576
00:31:59,120 --> 00:32:03,640
Speaker 1: to defend their initial idea and encircle their initial idea

577
00:32:03,680 --> 00:32:05,600
Speaker 1: because they're really reluctant to be that they were wrong.

578
00:32:05,840 --> 00:32:09,320
Speaker 1: Uh huh, and like that. That's like the Java sciences,

579
00:32:09,480 --> 00:32:11,320
Speaker 1: to not fall in love with the idea in the

580
00:32:11,320 --> 00:32:14,880
Speaker 1: first place, and to continually be trying to figure out

581
00:32:16,560 --> 00:32:18,680
Speaker 1: how you could be wrong. And again, that's why I

582
00:32:18,760 --> 00:32:21,720
Speaker 1: like the field of taffonomy, because that's sort of its goal.

583
00:32:21,760 --> 00:32:25,400
Speaker 1: You're always asking that, well, we don't understand all the

584
00:32:25,400 --> 00:32:29,680
Speaker 1: things that create and every side I've dug um, you've

585
00:32:29,720 --> 00:32:32,360
Speaker 1: got sort of your textbook, what's you go about taffonomy on?

586
00:32:32,760 --> 00:32:34,840
Speaker 1: But then you realize that it's in a slightly different

587
00:32:34,880 --> 00:32:37,480
Speaker 1: situation where it is on the land surface. Um, you

588
00:32:37,520 --> 00:32:40,240
Speaker 1: know it's in shade, Is it in where snow drift forms?

589
00:32:40,640 --> 00:32:42,959
Speaker 1: Is it in an area where if we haven't studied

590
00:32:43,000 --> 00:32:44,600
Speaker 1: those taff on And you realize you need to go

591
00:32:44,680 --> 00:32:47,160
Speaker 1: back to the modern world or come to the modern

592
00:32:47,200 --> 00:32:49,840
Speaker 1: world and study those processes again to make sure that

593
00:32:49,880 --> 00:32:53,640
Speaker 1: you understand them. So you're continually in that cycle of

594
00:32:53,640 --> 00:32:56,000
Speaker 1: of saying, this is what we think we know, but

595
00:32:56,120 --> 00:32:59,680
Speaker 1: then yeah, but what about this. I think one of

596
00:32:59,720 --> 00:33:02,280
Speaker 1: the most embarrassing things that ever happened to me was

597
00:33:02,480 --> 00:33:06,480
Speaker 1: I was giving this sort of presentation years ago, soon

598
00:33:06,520 --> 00:33:08,680
Speaker 1: after I got married, and I had my wife, my

599
00:33:08,800 --> 00:33:11,480
Speaker 1: arm around my new wife, and I said something to

600
00:33:11,520 --> 00:33:16,160
Speaker 1: the crowd like yeah and I embrace ignorance. Um. That

601
00:33:16,200 --> 00:33:19,520
Speaker 1: didn't go over very well, because the point is, you know,

602
00:33:19,560 --> 00:33:22,080
Speaker 1: if you really want to learn something, step one is

603
00:33:22,120 --> 00:33:24,560
Speaker 1: to say yeah, I don't know that, or what are

604
00:33:24,560 --> 00:33:27,920
Speaker 1: the alternatives. So in the Hudson Man case, UH, we

605
00:33:28,040 --> 00:33:31,200
Speaker 1: came away from it saying, yeah, these animals died, and

606
00:33:31,240 --> 00:33:35,200
Speaker 1: there's indications that humans were in the area, maybe soon after,

607
00:33:35,360 --> 00:33:40,440
Speaker 1: maybe a little after. But whether it's a functional association,

608
00:33:40,440 --> 00:33:45,040
Speaker 1: we can't say for sure, because there's always always unexplained

609
00:33:45,640 --> 00:33:49,280
Speaker 1: um patterns that may not have anything to do with

610
00:33:49,320 --> 00:33:53,640
Speaker 1: a kill event. So we took a perfectly good story

611
00:33:54,200 --> 00:33:59,200
Speaker 1: and turned it into uh, who knows, which means there's

612
00:33:59,400 --> 00:34:02,920
Speaker 1: it opens the door for new research. I I always yeah,

613
00:34:02,960 --> 00:34:05,640
Speaker 1: like it's just as interesting now. I always root for

614
00:34:05,680 --> 00:34:08,239
Speaker 1: everything to be a kill site, human kill site. We

615
00:34:08,400 --> 00:34:11,520
Speaker 1: do because that's really that's fun. That's but it is.

616
00:34:11,800 --> 00:34:14,359
Speaker 1: It does bring up like, if not that, what then

617
00:34:14,480 --> 00:34:17,720
Speaker 1: how does eight eight? Like if you're seeing eight hundred

618
00:34:17,760 --> 00:34:19,680
Speaker 1: or something in the field, that's a lot of that's

619
00:34:19,680 --> 00:34:21,640
Speaker 1: a lot of lot of big animals. But you look

620
00:34:21,640 --> 00:34:24,920
Speaker 1: at um, you know, go to the museum Rockies here, Um,

621
00:34:24,960 --> 00:34:29,240
Speaker 1: there's big piles of dead dinosaurs in single bone beds.

622
00:34:29,320 --> 00:34:31,759
Speaker 1: They don't always occur as one to their sites where

623
00:34:31,760 --> 00:34:34,759
Speaker 1: there's in the tens to twenties to thirty animals in

624
00:34:34,760 --> 00:34:37,160
Speaker 1: the same place. Um, And they make a good another

625
00:34:37,200 --> 00:34:39,759
Speaker 1: good control to study if you can't in that case

626
00:34:39,800 --> 00:34:43,480
Speaker 1: say well it's a human kill site. Something. There are

627
00:34:43,520 --> 00:34:46,440
Speaker 1: processes that killed large groups of animals over and over

628
00:34:46,480 --> 00:34:48,680
Speaker 1: again without having humans on the scene. So what's your

629
00:34:48,719 --> 00:34:50,360
Speaker 1: best guests Like, let's I know you guys don't like

630
00:34:50,400 --> 00:34:52,319
Speaker 1: to do this in your business, but what's your like

631
00:34:52,520 --> 00:34:56,279
Speaker 1: why are there seven whatever? Like, why are those as

632
00:34:56,320 --> 00:34:59,560
Speaker 1: it projectile points or scrapers or projectile points? There's some

633
00:34:59,600 --> 00:35:03,319
Speaker 1: scrape what are they there? For they could have if

634
00:35:03,360 --> 00:35:06,160
Speaker 1: the animals died. Humans could you know, we're great scavengers

635
00:35:06,160 --> 00:35:10,200
Speaker 1: as well as good hunters. Um they also it's by

636
00:35:10,200 --> 00:35:12,680
Speaker 1: a spring, there's and I said there were points both

637
00:35:12,680 --> 00:35:15,640
Speaker 1: in the bones below the bones above the bones hell.

638
00:35:15,680 --> 00:35:18,880
Speaker 1: They could have come there twenty years later and camp

639
00:35:19,000 --> 00:35:21,160
Speaker 1: next to that spring where most of the bison were

640
00:35:21,200 --> 00:35:24,560
Speaker 1: completely buried. There's lots of ways you can get close

641
00:35:24,600 --> 00:35:28,680
Speaker 1: associations and and settlements across landscapes without being It could

642
00:35:28,680 --> 00:35:33,719
Speaker 1: have just been a good hunting spots there. And yeah,

643
00:35:33,719 --> 00:35:36,200
Speaker 1: I saw eight hundred to something. I'd probably come back

644
00:35:36,200 --> 00:35:39,239
Speaker 1: and check it a year later, going on a lot

645
00:35:39,239 --> 00:35:41,279
Speaker 1: of the planes. Any place where there's a water source

646
00:35:41,320 --> 00:35:43,080
Speaker 1: and there's a spring right there is going to be

647
00:35:43,120 --> 00:35:46,719
Speaker 1: one of your hunting locations over and over and over again. Yeah,

648
00:35:47,080 --> 00:35:51,440
Speaker 1: you know, I'm sure you've been to the labraa target

649
00:35:51,760 --> 00:35:55,319
Speaker 1: l A. Yeah, like there you have. I don't know,

650
00:35:55,440 --> 00:35:59,520
Speaker 1: I mean, I like hundreds and hundreds hund FireWolves and

651
00:35:59,560 --> 00:36:01,960
Speaker 1: that whole Yeah, there's like, yeah, there's a wall of

652
00:36:02,040 --> 00:36:04,719
Speaker 1: like forty some diables that came out of that thing.

653
00:36:04,760 --> 00:36:08,799
Speaker 1: But it was active. It was like collecting carcasses over

654
00:36:09,800 --> 00:36:12,400
Speaker 1: so much time I remember seeing that. I remember like

655
00:36:12,440 --> 00:36:15,239
Speaker 1: someone was postulate and like there's so many bones, Like

656
00:36:15,280 --> 00:36:17,239
Speaker 1: what was going on here? How could there be so

657
00:36:17,280 --> 00:36:22,200
Speaker 1: many bones? When someone said, like one event in that vicinity,

658
00:36:22,600 --> 00:36:26,560
Speaker 1: one event per decade, would account for all of these bones.

659
00:36:27,239 --> 00:36:33,600
Speaker 1: Meaning a mammoth calf get stuck in the tar, uh,

660
00:36:33,719 --> 00:36:36,719
Speaker 1: saber tooth or some scavenger goes out to eat it

661
00:36:37,000 --> 00:36:40,080
Speaker 1: get stuck in the tar, A few birds come down

662
00:36:40,120 --> 00:36:42,600
Speaker 1: to scavenge, they get stuck in the tar. If that

663
00:36:42,680 --> 00:36:47,840
Speaker 1: happens every decade over the whatever that that thing is

664
00:36:47,880 --> 00:36:51,279
Speaker 1: collecting things. When it's all said and done, you open

665
00:36:51,320 --> 00:36:53,040
Speaker 1: it up and it looks like like it looks like

666
00:36:53,560 --> 00:36:55,799
Speaker 1: a got dumped out inside there, you know. But it's

667
00:36:55,840 --> 00:36:59,040
Speaker 1: just like a gradual But but the eight D and

668
00:36:59,080 --> 00:37:01,960
Speaker 1: one pile is so like intriguing, Yeah, it is, especially

669
00:37:01,960 --> 00:37:04,400
Speaker 1: when you see like like if you were to look

670
00:37:04,440 --> 00:37:10,839
Speaker 1: at eight hundred cattle in a pasture sunk, that's gonna

671
00:37:10,880 --> 00:37:12,960
Speaker 1: be you know, like I say, almost a football field

672
00:37:13,160 --> 00:37:17,880
Speaker 1: full of dead animals. Oh man, the stanch, Oh yeah,

673
00:37:18,040 --> 00:37:20,759
Speaker 1: the stanch. But again, um and one of the things

674
00:37:20,760 --> 00:37:23,160
Speaker 1: that I I don't like to call bone piles like

675
00:37:23,200 --> 00:37:26,640
Speaker 1: that kill sites because even if we can demonstrate unambiguously

676
00:37:27,040 --> 00:37:29,680
Speaker 1: that people kill them, if you really want to take

677
00:37:29,680 --> 00:37:33,320
Speaker 1: full advantage research advantage of them, you can also study

678
00:37:33,480 --> 00:37:39,080
Speaker 1: them as um other predator and scavenger food sources, and

679
00:37:39,320 --> 00:37:42,799
Speaker 1: how does those kill sites produced by humans feed into

680
00:37:42,840 --> 00:37:45,520
Speaker 1: the ecology of the other scavengers in the environment. So

681
00:37:45,560 --> 00:37:48,360
Speaker 1: you can really start trying to reconstruct an ecology of

682
00:37:48,360 --> 00:37:50,719
Speaker 1: the area if you approach the site, not just by

683
00:37:50,760 --> 00:37:52,800
Speaker 1: trying to learn about people. Yeah, you know that that

684
00:37:52,920 --> 00:37:54,720
Speaker 1: that's the thing that when I was talking about Librey,

685
00:37:54,760 --> 00:37:56,239
Speaker 1: I forgot what the point I was going to get at.

686
00:37:56,920 --> 00:38:00,560
Speaker 1: When you look through the Hudson mang do you find

687
00:38:00,560 --> 00:38:03,640
Speaker 1: were there all kinds of like wolf bones and bare

688
00:38:03,680 --> 00:38:06,120
Speaker 1: bones mixed in, like stuff that had gotten killed while

689
00:38:06,160 --> 00:38:08,440
Speaker 1: they're in their scavenge And no, but there are um

690
00:38:08,640 --> 00:38:11,400
Speaker 1: bones that have the tooth marks of the scavenger. So

691
00:38:11,920 --> 00:38:15,120
Speaker 1: unlike LaBrea, where if you're a scavenger that's trying to

692
00:38:15,160 --> 00:38:18,399
Speaker 1: get that tasty, dead, smelly, rotting thing and you fall

693
00:38:18,440 --> 00:38:20,879
Speaker 1: into the tar and you get trapped yourself here, there

694
00:38:20,920 --> 00:38:23,840
Speaker 1: wasn't that natural trap just come and eat your fill,

695
00:38:24,320 --> 00:38:27,399
Speaker 1: or unless a grizzly came and you were a coy

696
00:38:27,480 --> 00:38:29,680
Speaker 1: out and it killed you too. Potentially within a few

697
00:38:29,680 --> 00:38:32,320
Speaker 1: months all the meat was gone. Yeah. Uh, so we

698
00:38:32,400 --> 00:38:34,360
Speaker 1: study you know, talked about taffono me and all the

699
00:38:34,440 --> 00:38:38,040
Speaker 1: meats gone. We study things like, um, what happens through

700
00:38:38,080 --> 00:38:42,000
Speaker 1: times as maggots consumed carcasses and and what parts can

701
00:38:42,080 --> 00:38:44,439
Speaker 1: get and you see things. Well, one of the really

702
00:38:44,440 --> 00:38:48,719
Speaker 1: fun patterns at Hudson Man that we see, um, the kneecaps,

703
00:38:49,080 --> 00:38:53,560
Speaker 1: the patela's are often in place at the lower end

704
00:38:53,600 --> 00:38:55,399
Speaker 1: of the femur and the proxy. You know, they're right

705
00:38:55,440 --> 00:38:58,040
Speaker 1: there where they belong in the skeleton. How does that

706
00:38:58,080 --> 00:39:00,000
Speaker 1: happen even though they lay in loose ones everything rob

707
00:39:00,000 --> 00:39:02,239
Speaker 1: It's a way. Yeah, but think if you've watched an

708
00:39:02,239 --> 00:39:05,960
Speaker 1: animal rod um and I've spent more time doing that

709
00:39:06,040 --> 00:39:10,279
Speaker 1: than it's probably healthy. Um. The lower legs up through

710
00:39:10,320 --> 00:39:13,160
Speaker 1: at least the knee. When the meat rots away, the

711
00:39:13,239 --> 00:39:16,799
Speaker 1: hide often contracts and holds it down around it. So

712
00:39:17,320 --> 00:39:20,200
Speaker 1: seeing things like a kneecap in place on a carcass

713
00:39:20,280 --> 00:39:23,000
Speaker 1: that you found in an archaeological site is probably a

714
00:39:23,000 --> 00:39:27,600
Speaker 1: pretty good indicator that that animal wasn't skinned. Oh so,

715
00:39:27,640 --> 00:39:29,600
Speaker 1: if it wasn't skinned, it's really hard to get to

716
00:39:29,600 --> 00:39:31,360
Speaker 1: the meat because it could have been in case, it

717
00:39:31,400 --> 00:39:35,040
Speaker 1: could have been into the dirt by the time, yeah,

718
00:39:35,080 --> 00:39:39,400
Speaker 1: by the time that the because of your very burying

719
00:39:39,520 --> 00:39:44,239
Speaker 1: incrementally that dried hide around. It's almost like armor, you know,

720
00:39:44,280 --> 00:39:47,200
Speaker 1: it's it's raw hide. It's tougher than hell, and it's

721
00:39:47,200 --> 00:39:49,240
Speaker 1: going to hold that in place through a long period

722
00:39:49,280 --> 00:39:51,480
Speaker 1: of time on on some of those did you see

723
00:39:51,480 --> 00:39:54,160
Speaker 1: that thing recently came out? This is over in Europe.

724
00:39:54,480 --> 00:39:56,719
Speaker 1: I can't remember what country is in where they found

725
00:39:56,760 --> 00:40:01,000
Speaker 1: where guys have been stashing uh, not even like shank

726
00:40:01,120 --> 00:40:04,920
Speaker 1: like the meat used to make just forearms, like the

727
00:40:05,280 --> 00:40:10,000
Speaker 1: like the station those in a cave. Yeah, or what

728
00:40:10,040 --> 00:40:13,680
Speaker 1: they found was bones in a cave and they were

729
00:40:13,719 --> 00:40:16,279
Speaker 1: wondering why they had to scrape the hide off them

730
00:40:16,480 --> 00:40:19,480
Speaker 1: because instead of just stripping it off, and someone postulated

731
00:40:19,520 --> 00:40:22,320
Speaker 1: that they dried and they were throwing them in the cave.

732
00:40:22,560 --> 00:40:24,600
Speaker 1: That they always threw the from the hoof to the

733
00:40:24,640 --> 00:40:27,600
Speaker 1: knee in a cave just a story in there, and

734
00:40:27,680 --> 00:40:29,880
Speaker 1: later they'd go and scrape it and you've got to

735
00:40:29,960 --> 00:40:33,279
Speaker 1: scare the dry hide off to get the mary because

736
00:40:33,280 --> 00:40:35,360
Speaker 1: they're like, why else would they need to have scraped

737
00:40:36,360 --> 00:40:38,680
Speaker 1: knife that away when on a fresh amimy you just

738
00:40:39,440 --> 00:40:42,560
Speaker 1: back yeah, like a like a banana. And that's if

739
00:40:42,600 --> 00:40:44,719
Speaker 1: you'd read that study. It's kind of that's sort of

740
00:40:44,760 --> 00:40:47,600
Speaker 1: taking Taffenen taff onomy to an extreme. I don't think

741
00:40:47,640 --> 00:40:50,200
Speaker 1: i'd do this, and that they were saying, boy, after

742
00:40:50,280 --> 00:40:52,359
Speaker 1: a week or so, it starts to taste a little rank.

743
00:40:52,440 --> 00:40:55,719
Speaker 1: They were actually tasting it themselves. The marrow starts to

744
00:40:55,760 --> 00:40:58,440
Speaker 1: taste wheat rank after week. One of the things that

745
00:40:58,520 --> 00:41:00,880
Speaker 1: I had a student who was a biochemist a few

746
00:41:00,960 --> 00:41:05,319
Speaker 1: years ago, and I had another student that was an archaeologist,

747
00:41:05,320 --> 00:41:09,719
Speaker 1: and we were watching carcasses rot and he started questioning

748
00:41:09,840 --> 00:41:13,160
Speaker 1: whether if you've seen a big carcass rot during the

749
00:41:13,200 --> 00:41:16,760
Speaker 1: middle of the summer and the maggots infested, they start

750
00:41:17,360 --> 00:41:21,799
Speaker 1: piling out, you could collect quarts of maggots. And he's saying, well,

751
00:41:21,840 --> 00:41:24,880
Speaker 1: I wonder if people would eat those maggots. You know,

752
00:41:25,200 --> 00:41:29,200
Speaker 1: they're probably little fatty. I'm sure they're good for you. Well,

753
00:41:29,239 --> 00:41:31,880
Speaker 1: what what the student who was the biochemist did. We

754
00:41:31,880 --> 00:41:35,319
Speaker 1: started collecting tissue samples from carcasses that died during the

755
00:41:35,320 --> 00:41:38,680
Speaker 1: winter and found out that once the magots infested and

756
00:41:38,719 --> 00:41:42,479
Speaker 1: throughout the winter that it would be okay to eat.

757
00:41:42,840 --> 00:41:45,480
Speaker 1: When the maggots infested, they start bringing in a bunch

758
00:41:45,520 --> 00:41:48,480
Speaker 1: of other toxins, so the toxicity of the meat once

759
00:41:48,520 --> 00:41:53,320
Speaker 1: it's maggot infested goes up. Really, so probably the maggot

760
00:41:53,320 --> 00:41:56,480
Speaker 1: harvesters of the high Plains wouldn't be a very very

761
00:41:56,480 --> 00:41:59,280
Speaker 1: good subsistent strategy. You know, it's a good taffonomy story

762
00:41:59,320 --> 00:42:03,080
Speaker 1: for you. Uh. One time my old man um when

763
00:42:03,080 --> 00:42:05,440
Speaker 1: we were kids, my dad like hit a buck with

764
00:42:05,480 --> 00:42:10,160
Speaker 1: his bow and he killed it quick, but we never

765
00:42:10,160 --> 00:42:11,920
Speaker 1: found it. We didn't realize it when it ran into

766
00:42:11,960 --> 00:42:13,640
Speaker 1: a corn field, and we later realized we must have

767
00:42:13,640 --> 00:42:16,000
Speaker 1: stumbled it over ten times without finding it. But he

768
00:42:16,120 --> 00:42:18,440
Speaker 1: hit it like the arrow came down high straight below

769
00:42:19,680 --> 00:42:22,719
Speaker 1: puncture along but didn't make an exit hole. So it

770
00:42:22,800 --> 00:42:25,880
Speaker 1: runs off and we don't know how, but we missed it.

771
00:42:26,080 --> 00:42:28,600
Speaker 1: I mean we were like probably had have walked over

772
00:42:28,640 --> 00:42:31,799
Speaker 1: in a field, but we would go check on it later.

773
00:42:32,680 --> 00:42:34,400
Speaker 1: And one time we're out there rabbit hunting and we

774
00:42:34,400 --> 00:42:37,240
Speaker 1: go to check on you know, Dad's dead deer because

775
00:42:37,239 --> 00:42:40,520
Speaker 1: by the time he found it was rotten um and

776
00:42:40,760 --> 00:42:42,640
Speaker 1: there's a hole in its ribs. There's a hole in

777
00:42:42,680 --> 00:42:45,600
Speaker 1: its side, and I peered down in that hole and

778
00:42:45,600 --> 00:42:49,400
Speaker 1: there's a possum living in there, and actually hauled him

779
00:42:49,400 --> 00:42:51,200
Speaker 1: out by the tail. But you can imagine if like

780
00:42:51,239 --> 00:42:55,239
Speaker 1: that possum would have died and then it gets the case.

781
00:42:55,320 --> 00:43:00,680
Speaker 1: It looked like it was like a fetus. This was

782
00:43:00,719 --> 00:43:04,960
Speaker 1: the deer's last meal. Yeah, like no one would ever

783
00:43:05,000 --> 00:43:06,920
Speaker 1: be like, oh, you know, it probably haven't a possum

784
00:43:06,920 --> 00:43:09,040
Speaker 1: crawled in there and died. You know, this wouldn't be

785
00:43:09,080 --> 00:43:11,439
Speaker 1: what came to mind. Uh. You know, there's a site

786
00:43:11,440 --> 00:43:16,160
Speaker 1: in Colorado. I don't hopefully I can explain enough. You

787
00:43:16,239 --> 00:43:18,040
Speaker 1: know what I'm talking about. There's a site in Colorado

788
00:43:18,040 --> 00:43:20,319
Speaker 1: where there's a lot of debate about whether it was

789
00:43:20,360 --> 00:43:23,480
Speaker 1: a mammoth kill site or whether it was a spot

790
00:43:23,520 --> 00:43:27,520
Speaker 1: that a few mammoths got washed up in a gravel bar.

791
00:43:28,200 --> 00:43:31,120
Speaker 1: You know what I'm talking about. North I think it's

792
00:43:31,160 --> 00:43:34,040
Speaker 1: like between Denver and Fort Collins and there the dance site,

793
00:43:34,080 --> 00:43:37,040
Speaker 1: the one out by Greeley. Maybe what's the dance site.

794
00:43:37,320 --> 00:43:39,640
Speaker 1: It's um one of the It's like one where people

795
00:43:39,680 --> 00:43:42,239
Speaker 1: can't tell if they died or got killed. It was

796
00:43:42,280 --> 00:43:46,040
Speaker 1: the site where it was first excavated with mammoths and

797
00:43:46,200 --> 00:43:50,000
Speaker 1: points that were eventually called Clovis Sitte points before the

798
00:43:50,040 --> 00:43:53,880
Speaker 1: Clovis site was and the association wasn't really established, and

799
00:43:53,920 --> 00:43:56,800
Speaker 1: it was so that might be the one, but it

800
00:43:56,880 --> 00:43:58,960
Speaker 1: was like the idea was here. Let me tell you

801
00:43:58,960 --> 00:44:03,120
Speaker 1: the one last detail. Remember it was the people that

802
00:44:03,160 --> 00:44:05,800
Speaker 1: are arguing there was a kill site. We're arguing that

803
00:44:05,920 --> 00:44:09,040
Speaker 1: somehow they were crossing a river and then going and

804
00:44:09,120 --> 00:44:10,560
Speaker 1: you know, how do you get like a little cut

805
00:44:10,760 --> 00:44:12,839
Speaker 1: You'll have a high bluff or a high cut bank,

806
00:44:13,160 --> 00:44:14,680
Speaker 1: but now you find like a little gap, like a

807
00:44:14,719 --> 00:44:17,719
Speaker 1: little washout, and animals will use that to get through

808
00:44:17,760 --> 00:44:20,200
Speaker 1: the thing. There was the idea that they had somehow

809
00:44:20,280 --> 00:44:24,160
Speaker 1: ambushed these mammoths coming up through that thinking it was

810
00:44:24,160 --> 00:44:26,640
Speaker 1: a good spot to get them, and so over time

811
00:44:27,920 --> 00:44:30,239
Speaker 1: maybe they had killed a couple there. But then someone

812
00:44:30,320 --> 00:44:33,400
Speaker 1: later was like, how how do we know it's is

813
00:44:33,440 --> 00:44:36,480
Speaker 1: not a place where carcasses would wash up on the

814
00:44:36,480 --> 00:44:38,600
Speaker 1: beach or whatever. I'm not wish I could do a

815
00:44:38,640 --> 00:44:40,640
Speaker 1: better job. I'm not familiar with that one, but I

816
00:44:40,680 --> 00:44:43,360
Speaker 1: am familiar with a site where that was a question.

817
00:44:43,480 --> 00:44:46,720
Speaker 1: We um there's a site in Wyoming near Wherland, Wyoming

818
00:44:46,800 --> 00:44:49,439
Speaker 1: called the Colby Mammoth site. I've heard of that where

819
00:44:49,480 --> 00:44:52,920
Speaker 1: there's um seven mammoths and a lot of the bones

820
00:44:52,920 --> 00:44:57,480
Speaker 1: occur in two piles. And when George Frison originally excavated

821
00:44:57,560 --> 00:45:02,320
Speaker 1: and reported on the site in Science magazine, he hypothesized

822
00:45:02,360 --> 00:45:06,320
Speaker 1: that those piles were areas where people killed mammoths or

823
00:45:06,360 --> 00:45:09,200
Speaker 1: scavenged mammoths and then taking some of the bones and

824
00:45:09,200 --> 00:45:12,920
Speaker 1: piled over the meat that was left there, packed snow

825
00:45:12,960 --> 00:45:15,480
Speaker 1: and stuff in to put it into sort of freezing

826
00:45:16,080 --> 00:45:19,200
Speaker 1: um storage to where he'd come back later. So he

827
00:45:19,239 --> 00:45:22,480
Speaker 1: saw the bone piles as being meat caches, and he

828
00:45:22,560 --> 00:45:25,320
Speaker 1: published that in Science magazine, you know, one of the

829
00:45:25,800 --> 00:45:29,920
Speaker 1: top scientific journals in the world, as being this Science

830
00:45:29,960 --> 00:45:35,279
Speaker 1: and Nature. Yeah, published it in Science um as being

831
00:45:35,280 --> 00:45:38,360
Speaker 1: a paloon Indian meat cash. And one of their responses

832
00:45:38,400 --> 00:45:40,320
Speaker 1: to it was and they were in the bottom of

833
00:45:40,360 --> 00:45:42,920
Speaker 1: an arroyo where the piles were. One of the responses

834
00:45:42,960 --> 00:45:47,360
Speaker 1: to it, by a fairly well respected researcher was sort of, well, George,

835
00:45:47,360 --> 00:45:49,359
Speaker 1: how do you know that those piles aren't just like

836
00:45:49,400 --> 00:45:52,320
Speaker 1: what you're talking about sort of the mammoth bone pile

837
00:45:52,360 --> 00:45:56,160
Speaker 1: equivalent of driftwood. If you've got water moving down a

838
00:45:56,239 --> 00:45:59,440
Speaker 1: winding arroyo, aren't bones going to accumulate in some areas

839
00:45:59,440 --> 00:46:02,560
Speaker 1: in big miles. And one of the things that I

840
00:46:02,640 --> 00:46:07,759
Speaker 1: really respect people like George prison Um about is rather

841
00:46:07,800 --> 00:46:11,240
Speaker 1: than taking that defensive position that you were um talking

842
00:46:11,239 --> 00:46:14,440
Speaker 1: about before, his response to say, well, yet could be

843
00:46:14,600 --> 00:46:17,200
Speaker 1: how do we figure that out? So he and I

844
00:46:17,600 --> 00:46:20,680
Speaker 1: um the university that was at the University of Wyoming,

845
00:46:20,719 --> 00:46:23,399
Speaker 1: and I was working on my PhD on collections there.

846
00:46:23,960 --> 00:46:28,759
Speaker 1: Um they had a mammoth skeleton or an elephant skeleton

847
00:46:29,080 --> 00:46:33,200
Speaker 1: in their bone comparative collection. So we took the elephant

848
00:46:33,320 --> 00:46:37,000
Speaker 1: skeleton out to one of the streams north of Laramie

849
00:46:37,400 --> 00:46:40,640
Speaker 1: where we could damn up the stream, lay the elephant

850
00:46:40,680 --> 00:46:44,600
Speaker 1: bones in the bottom of the stream, record their positions, UM,

851
00:46:44,840 --> 00:46:49,719
Speaker 1: release the water, record the current velocity, UM, damn up

852
00:46:49,719 --> 00:46:52,239
Speaker 1: the stream again, come back and measure which bones had

853
00:46:52,239 --> 00:46:54,640
Speaker 1: moved and how far they moved. And we did that

854
00:46:54,719 --> 00:46:57,480
Speaker 1: a number of times so that for each bone in

855
00:46:57,520 --> 00:47:00,319
Speaker 1: the elephant skeleton we could develop what we call a

856
00:47:00,400 --> 00:47:04,080
Speaker 1: fluvial transport index. The same stream will deposit rocks get

857
00:47:04,200 --> 00:47:07,080
Speaker 1: towards the headwaters. Big rocks you get down towards the mouth,

858
00:47:07,120 --> 00:47:10,479
Speaker 1: and some bones light bones will float on while the

859
00:47:10,520 --> 00:47:13,760
Speaker 1: other role. So we developed this index of which bones

860
00:47:13,880 --> 00:47:16,960
Speaker 1: would be most likely to be transported by flowing water,

861
00:47:17,600 --> 00:47:19,880
Speaker 1: and then we went back to the Colby bone piles

862
00:47:19,920 --> 00:47:24,280
Speaker 1: to see if they matched um, that sort of transport profile,

863
00:47:24,320 --> 00:47:27,440
Speaker 1: and they didn't did not, So you can you can

864
00:47:27,480 --> 00:47:30,560
Speaker 1: take things like that, are these bones transported by water

865
00:47:31,280 --> 00:47:33,640
Speaker 1: or not? In any your next step is how do

866
00:47:33,680 --> 00:47:36,799
Speaker 1: we develop the methods to assess that? So what do

867
00:47:36,800 --> 00:47:38,919
Speaker 1: they think happen at what was the leading theory about

868
00:47:38,920 --> 00:47:41,279
Speaker 1: what happened at that side? I think we're still into

869
00:47:41,320 --> 00:47:46,680
Speaker 1: the prison's original interpretation of meat cash is probably most likely.

870
00:47:46,920 --> 00:47:48,799
Speaker 1: It looks like one of them may have been where

871
00:47:48,800 --> 00:47:51,120
Speaker 1: they did that, pile the stuff on and came back

872
00:47:51,200 --> 00:47:53,839
Speaker 1: later and opened it up and got the meat back. Uh.

873
00:47:53,920 --> 00:47:56,680
Speaker 1: Second one doesn't look like they ever did that. But again,

874
00:47:56,680 --> 00:48:00,279
Speaker 1: if you're highly mobile people across the landscape, UM, you're

875
00:48:00,280 --> 00:48:03,640
Speaker 1: probably gonna cash food wherever you can as a backup

876
00:48:03,680 --> 00:48:08,960
Speaker 1: strategy if things go wrong, and even the bone piles

877
00:48:09,000 --> 00:48:11,640
Speaker 1: and sites during the winter where they don't necessarily put

878
00:48:11,680 --> 00:48:14,080
Speaker 1: them in cash piles, you're gonna know that next spring,

879
00:48:14,120 --> 00:48:16,479
Speaker 1: if you're hungry, you can go back to that site

880
00:48:16,480 --> 00:48:19,360
Speaker 1: where you killed the fifty bison in December and it

881
00:48:19,480 --> 00:48:21,239
Speaker 1: might not be the tastiest stuff in the world, but

882
00:48:21,280 --> 00:48:23,759
Speaker 1: there's a food source there. So yeah, like if you

883
00:48:23,800 --> 00:48:27,800
Speaker 1: read uh, I always thought about Stephenson the articles Bloorer

884
00:48:28,200 --> 00:48:30,640
Speaker 1: when he was traveling in the Canadian Hierarchtic and he

885
00:48:30,680 --> 00:48:33,759
Speaker 1: was usually traveling with Intuit hunters did kill everything they

886
00:48:33,800 --> 00:48:37,439
Speaker 1: ran across and put it, they put in a pile

887
00:48:37,440 --> 00:48:38,919
Speaker 1: and keep going because and then they had in their

888
00:48:38,920 --> 00:48:42,000
Speaker 1: head just where all this stuff was. And I was

889
00:48:42,040 --> 00:48:44,520
Speaker 1: just we just interviewed another guests who just finished the

890
00:48:44,520 --> 00:48:48,200
Speaker 1: book about the Greely Polar Expedition, and yeah, every point

891
00:48:48,960 --> 00:48:50,520
Speaker 1: you just would go because that you're in your boat,

892
00:48:50,800 --> 00:48:53,359
Speaker 1: you just go and drop stuff every point because then

893
00:48:53,520 --> 00:48:56,800
Speaker 1: if you both say, create a sort of like travel

894
00:48:56,840 --> 00:48:59,759
Speaker 1: line that you knew you could rely on your bread

895
00:48:59,800 --> 00:49:02,680
Speaker 1: cry ms of safety, and they would and you'd leave cashes,

896
00:49:02,680 --> 00:49:04,680
Speaker 1: and they'd always leave a note in there and a

897
00:49:05,160 --> 00:49:08,359
Speaker 1: container saying like there's this at this point, this at

898
00:49:08,400 --> 00:49:11,040
Speaker 1: this point, so that other people could find it and

899
00:49:11,120 --> 00:49:15,560
Speaker 1: go about sort of recovering these surplus food sources. That

900
00:49:15,600 --> 00:49:16,840
Speaker 1: you didn't want to have with you because it was

901
00:49:16,840 --> 00:49:19,879
Speaker 1: too vulnerable to have it with you. One of my professors,

902
00:49:20,040 --> 00:49:22,120
Speaker 1: Um Louis Binford, spent a lot of time with the

903
00:49:22,160 --> 00:49:24,880
Speaker 1: nunimut Xs to brow up by in the Brooks Range,

904
00:49:25,600 --> 00:49:27,919
Speaker 1: and they talked. He talked about how you could talk

905
00:49:27,920 --> 00:49:30,640
Speaker 1: to the old Nunimute and they could tell you where

906
00:49:30,680 --> 00:49:34,319
Speaker 1: things were cashed pretty much all over Alaska. They may

907
00:49:34,440 --> 00:49:37,640
Speaker 1: never have been there themselves, but you've been there, and

908
00:49:37,680 --> 00:49:40,000
Speaker 1: you left something in this little dry spot, and when

909
00:49:40,040 --> 00:49:41,920
Speaker 1: you came back to camp, you tell these things that

910
00:49:42,160 --> 00:49:45,440
Speaker 1: liked us would seem like really boring stories, like there's

911
00:49:45,719 --> 00:49:48,160
Speaker 1: three sticks of wood in this cave down by that river.

912
00:49:48,440 --> 00:49:51,919
Speaker 1: And so the greatest quote from that was he said

913
00:49:51,960 --> 00:49:54,920
Speaker 1: one of the one of his informants, said, you know,

914
00:49:55,360 --> 00:49:59,160
Speaker 1: lou every dead Eskimo, remember something he didn't pick up

915
00:49:59,200 --> 00:50:01,239
Speaker 1: and put in a cat when he should have. Yeah,

916
00:50:01,960 --> 00:50:05,480
Speaker 1: that's interesting. Yeah, Um, I mentioned you before. I think

917
00:50:05,480 --> 00:50:07,160
Speaker 1: it was before we started recording. I mentioned you, Mike

918
00:50:07,200 --> 00:50:11,439
Speaker 1: cons Yeah, he found a he you know, he when

919
00:50:11,440 --> 00:50:12,799
Speaker 1: he was doing his work up in the North Silpe

920
00:50:12,800 --> 00:50:15,160
Speaker 1: of the Brooks Range. They were looking for like the

921
00:50:15,200 --> 00:50:16,920
Speaker 1: goal would be that you'd find evidence of the very

922
00:50:16,920 --> 00:50:18,759
Speaker 1: first Americans that would you know, would have been in

923
00:50:18,760 --> 00:50:22,400
Speaker 1: western Alaska after crossing from Siberia. UM. But one of

924
00:50:22,400 --> 00:50:26,000
Speaker 1: the things he found was an old cash of trapping

925
00:50:26,040 --> 00:50:30,320
Speaker 1: equipment and Russian made a Russian made shotgun, very old.

926
00:50:30,760 --> 00:50:32,640
Speaker 1: You know that someone had whatever put it there and

927
00:50:32,680 --> 00:50:34,759
Speaker 1: figured it'd come back and never got back to it. Yeah,

928
00:50:34,800 --> 00:50:37,719
Speaker 1: but you know that that's UM. Today we think of

929
00:50:37,760 --> 00:50:41,280
Speaker 1: our lifestyles if we cash stuff in our closets, um,

930
00:50:41,320 --> 00:50:43,000
Speaker 1: you know, when we put our winter clothes up and

931
00:50:43,040 --> 00:50:45,440
Speaker 1: get our summer clothes out. But if you're mobile across

932
00:50:45,440 --> 00:50:48,080
Speaker 1: the landscape, there's a lot of stuff that you don't

933
00:50:48,160 --> 00:50:51,160
Speaker 1: need all year long. You're gonna be cashing stuff for emergencies,

934
00:50:51,400 --> 00:50:53,839
Speaker 1: but you're also going to be cashing your summer gear

935
00:50:53,920 --> 00:50:55,920
Speaker 1: when you're going into your winter range, and you know,

936
00:50:56,000 --> 00:50:58,400
Speaker 1: you don't pack everything, so that a lot of the

937
00:50:58,480 --> 00:51:02,319
Speaker 1: archaeological record is not only stuff people lost intentionally, but

938
00:51:02,360 --> 00:51:04,840
Speaker 1: stuff you put up and may not get back to.

939
00:51:05,239 --> 00:51:08,080
Speaker 1: And so those are really spectacular if you can find them.

940
00:51:08,120 --> 00:51:10,040
Speaker 1: Have you ever found a mountain Man cash like they

941
00:51:10,080 --> 00:51:12,520
Speaker 1: used to make. No, there's been a few of those

942
00:51:12,520 --> 00:51:14,759
Speaker 1: have been recovered over the years beaver hides and yeah,

943
00:51:14,800 --> 00:51:18,600
Speaker 1: and you you read accounts of like where they dug

944
00:51:18,640 --> 00:51:20,239
Speaker 1: their cash bits and put the stuff in it and

945
00:51:20,239 --> 00:51:22,759
Speaker 1: then they couldn't get back because they got killed or

946
00:51:22,800 --> 00:51:24,960
Speaker 1: this that would be really fun to dig. Yeah, yeah,

947
00:51:25,440 --> 00:51:27,440
Speaker 1: like they had a way they could sort of make

948
00:51:27,480 --> 00:51:31,320
Speaker 1: a like a safe storage place for for traps and

949
00:51:31,400 --> 00:51:35,759
Speaker 1: dry beaver highs of those. I want to squeeze one

950
00:51:35,800 --> 00:51:38,360
Speaker 1: in before we leave the hunt, Hudson Man, didn't you

951
00:51:38,360 --> 00:51:39,360
Speaker 1: say it to be a game that one of the

952
00:51:39,400 --> 00:51:41,080
Speaker 1: reasons they thought that it was a kill site was

953
00:51:41,160 --> 00:51:43,920
Speaker 1: because of the way that the animals were cut up

954
00:51:43,920 --> 00:51:46,879
Speaker 1: and quartered. And so now that you think that that

955
00:51:47,080 --> 00:51:50,120
Speaker 1: wasn't the case, what's the explanation of that. Well, they

956
00:51:51,040 --> 00:51:55,359
Speaker 1: dead things fall apart, and if you were to look

957
00:51:55,440 --> 00:51:58,359
Speaker 1: down on the bone bed, it looks like just this

958
00:51:58,480 --> 00:52:01,719
Speaker 1: jumble of scattered bone. But then if you start, like

959
00:52:01,760 --> 00:52:05,720
Speaker 1: I mentioned before, recording dimensions of articular surfaces and stuff

960
00:52:05,800 --> 00:52:08,680
Speaker 1: like this, the things that look like they're totally random

961
00:52:08,800 --> 00:52:13,120
Speaker 1: are carcasses that have dispersed within a fairly small area. Yeah,

962
00:52:13,160 --> 00:52:17,760
Speaker 1: the bones aren't completely articulated, but if you were setting

963
00:52:17,800 --> 00:52:23,160
Speaker 1: on that it wasn't very like organized like butchering shoulders

964
00:52:23,160 --> 00:52:26,160
Speaker 1: over here hands. If all four of us were to

965
00:52:26,239 --> 00:52:29,120
Speaker 1: die in this room and be left to decay um

966
00:52:29,200 --> 00:52:33,640
Speaker 1: with the natural disperse, my femur might be over next year. Cranium.

967
00:52:33,680 --> 00:52:38,359
Speaker 1: That didn't mean a damn thing about Yeah, and and

968
00:52:38,360 --> 00:52:40,600
Speaker 1: they must you got whacked in the head with my

969
00:52:40,680 --> 00:52:44,640
Speaker 1: femer would be sort of that. Yeah, alright, Hey, tell

970
00:52:44,719 --> 00:52:47,799
Speaker 1: us about what's going on with the I don't think

971
00:52:47,800 --> 00:52:50,680
Speaker 1: it's been fully published yet, but a lot of people

972
00:52:50,719 --> 00:52:53,879
Speaker 1: have been sending me the articles, and I've been reading

973
00:52:53,880 --> 00:52:58,680
Speaker 1: everything I can find about the what might be you're

974
00:52:58,680 --> 00:53:00,480
Speaker 1: you're probably gonna go down there and has killed the

975
00:53:00,520 --> 00:53:05,160
Speaker 1: whole thing. But what might be mammoth traps north of

976
00:53:05,320 --> 00:53:14,320
Speaker 1: Mexico City, uh tilte Pec mammoth tilte Pec two mammoth site. Um.

977
00:53:14,360 --> 00:53:16,839
Speaker 1: This is a new thing, right, it's um. Yeah, they've

978
00:53:16,840 --> 00:53:19,480
Speaker 1: been working there for about ten months. It's the second

979
00:53:19,520 --> 00:53:22,680
Speaker 1: mammoth that was discovered there. And m December of two

980
00:53:22,680 --> 00:53:26,600
Speaker 1: thousand and fifteen, they're putting a water pipeline about two

981
00:53:26,680 --> 00:53:29,880
Speaker 1: kilometers north where this recent find was and they found

982
00:53:30,080 --> 00:53:33,640
Speaker 1: a nearly complete mammoth skeleton. No, no, I'm talking about

983
00:53:34,160 --> 00:53:37,759
Speaker 1: Yeah there's one they're digging. Yeah, this is that got

984
00:53:37,800 --> 00:53:42,000
Speaker 1: their their antenna's up for mammoths might be in this area.

985
00:53:42,000 --> 00:53:44,520
Speaker 1: And they they reconstructed that when they built a hall

986
00:53:44,560 --> 00:53:47,880
Speaker 1: of mammoths and use them to dispose. Yeah, okay, I

987
00:53:47,920 --> 00:53:51,240
Speaker 1: don't know what happened that one um at the time.

988
00:53:51,280 --> 00:53:54,360
Speaker 1: Their story was it got bogged in the swampy ground

989
00:53:54,400 --> 00:53:57,560
Speaker 1: next to a lake. And so they were putting in

990
00:53:57,880 --> 00:54:01,960
Speaker 1: a new landfill, Reese digging the big pit for the landfill,

991
00:54:02,560 --> 00:54:05,799
Speaker 1: and they started noticing mammoth bones coming out and they

992
00:54:05,800 --> 00:54:08,440
Speaker 1: were they were intentionally looking for them because of this

993
00:54:08,560 --> 00:54:12,000
Speaker 1: previous fine, so they were cutting into the lake sediments

994
00:54:12,239 --> 00:54:14,320
Speaker 1: and they thought, well, we found mammoths here before, we

995
00:54:14,360 --> 00:54:16,680
Speaker 1: should look at that. And sure enough they started seeing

996
00:54:16,719 --> 00:54:22,399
Speaker 1: mammoth bones and this is this a wooly mammoth. It's

997
00:54:22,440 --> 00:54:27,680
Speaker 1: a Colombian man was bigger than bigger. Pretty impressive credit.

998
00:54:27,760 --> 00:54:30,480
Speaker 1: So they're more of a southerly warmer climate man. Yeah.

999
00:54:31,680 --> 00:54:36,920
Speaker 1: So um, they were fortunate that they had people on

1000
00:54:37,120 --> 00:54:41,520
Speaker 1: site to look for the mammothbones. Uh. They after they

1001
00:54:41,520 --> 00:54:43,600
Speaker 1: were exposed in the cut bank there, they could go

1002
00:54:43,640 --> 00:54:49,000
Speaker 1: in and do some excavations and they uncovered remarkable sets

1003
00:54:49,000 --> 00:54:51,720
Speaker 1: of mammoth bones. I think the wellness I've been reading

1004
00:54:51,719 --> 00:54:55,879
Speaker 1: through the press release that they put out last week. Um,

1005
00:54:56,160 --> 00:54:59,600
Speaker 1: the things that I can say about the site that

1006
00:54:59,680 --> 00:55:04,440
Speaker 1: are observations that are facts are that their salvage excavations

1007
00:55:04,520 --> 00:55:08,520
Speaker 1: uncovered bones. Most of them were mammoths, but there was

1008
00:55:08,560 --> 00:55:11,400
Speaker 1: also a couple of camel bones, there was a horse tooth.

1009
00:55:12,200 --> 00:55:15,920
Speaker 1: And they're deposited in finally bedded deposits. Some of them

1010
00:55:15,920 --> 00:55:18,960
Speaker 1: are clay layers and some of them are volcanic ash layers.

1011
00:55:19,719 --> 00:55:23,200
Speaker 1: And those finally bedded deposits are in set into older

1012
00:55:23,280 --> 00:55:26,439
Speaker 1: lake deposits. So that's what we know about it. That's

1013
00:55:26,440 --> 00:55:29,480
Speaker 1: what from my reading of it I was take away

1014
00:55:29,560 --> 00:55:34,000
Speaker 1: as observations from that. The whole set of interpretations that

1015
00:55:34,080 --> 00:55:37,799
Speaker 1: kind of roll out in the press release are that

1016
00:55:37,880 --> 00:55:40,799
Speaker 1: there were fourteen mammoths there, that they were found in

1017
00:55:40,920 --> 00:55:46,320
Speaker 1: two large excavated pits, that there were systematic, regular hunting

1018
00:55:46,360 --> 00:55:49,760
Speaker 1: of them, that it was intensive use of the mammoths

1019
00:55:49,800 --> 00:55:53,120
Speaker 1: that were there. For example, we say, uh, the mandibles

1020
00:55:53,120 --> 00:55:55,960
Speaker 1: the jawbones are turned upside down, so obviously they were

1021
00:55:55,960 --> 00:55:59,440
Speaker 1: cutting the tongues out of the mandibles are upside downs. No,

1022
00:56:01,040 --> 00:56:03,680
Speaker 1: that's what I was curious about. Uh, no bone because

1023
00:56:03,680 --> 00:56:06,800
Speaker 1: the press is even being like and their tongues wounds

1024
00:56:07,280 --> 00:56:09,719
Speaker 1: twelve kilo tongues, and they would have been yeah, just

1025
00:56:09,800 --> 00:56:16,680
Speaker 1: because and again, what's the likelihood that if you're laying

1026
00:56:16,680 --> 00:56:18,319
Speaker 1: on the ground your jaw bones is going to turn

1027
00:56:18,400 --> 00:56:22,319
Speaker 1: this way as opposed to you know, it's fun fun.

1028
00:56:23,160 --> 00:56:26,719
Speaker 1: So that was just because it was upside down. It

1029
00:56:26,920 --> 00:56:30,000
Speaker 1: was just again someone getting the tongue. Easy access to

1030
00:56:30,040 --> 00:56:31,960
Speaker 1: the tongue from the bottom. You know, when you cut

1031
00:56:32,000 --> 00:56:34,000
Speaker 1: into a bison to get its tongue out, if it's

1032
00:56:34,320 --> 00:56:36,239
Speaker 1: if it's fresh, you can open up and get the

1033
00:56:36,239 --> 00:56:38,239
Speaker 1: tongue out. But even when I cut tongues out of stuff,

1034
00:56:38,239 --> 00:56:40,239
Speaker 1: I can't tell you what way I leave the head. No,

1035
00:56:40,880 --> 00:56:43,799
Speaker 1: and the way you leave it stuck. So let's leave

1036
00:56:43,840 --> 00:56:46,560
Speaker 1: the tongues for a minute. Um. The bones weren't fully

1037
00:56:46,640 --> 00:56:49,160
Speaker 1: articulated in these new areas. Again, they were scattered, like

1038
00:56:49,200 --> 00:56:52,600
Speaker 1: we talked about it, Hudson may um. So that's obvious.

1039
00:56:52,760 --> 00:56:58,759
Speaker 1: Butchering um. They said that they found well, uh in

1040
00:56:58,880 --> 00:57:04,040
Speaker 1: one area they found six right scapulus um no left

1041
00:57:04,080 --> 00:57:08,040
Speaker 1: scapulus shoulder blades, so obviously people must have taken the

1042
00:57:08,120 --> 00:57:11,840
Speaker 1: left scapulus. Well, that's pretty good. Let me that's the

1043
00:57:11,880 --> 00:57:15,719
Speaker 1: tasty one. Let me give you, let me give you

1044
00:57:15,800 --> 00:57:18,920
Speaker 1: one bad taphonomic joke, and then um we'll get back

1045
00:57:18,960 --> 00:57:22,200
Speaker 1: to the real world. UM. I would say it's anomalist

1046
00:57:22,200 --> 00:57:24,920
Speaker 1: to find all, right, scapulus because we usually find the

1047
00:57:24,960 --> 00:57:28,920
Speaker 1: scapulus from the other side, because if they weren't left, tada,

1048
00:57:29,080 --> 00:57:35,120
Speaker 1: you wouldn't find them. That's good, that's um. So the

1049
00:57:35,160 --> 00:57:37,400
Speaker 1: whole series of things there, let's go back to sort

1050
00:57:37,400 --> 00:57:40,000
Speaker 1: of down the list for well, okay, yeah, because there's

1051
00:57:40,000 --> 00:57:42,680
Speaker 1: a there's one that they felt was laid out ceremonially

1052
00:57:42,840 --> 00:57:45,200
Speaker 1: because they had been injured in the past. Well, it's

1053
00:57:45,280 --> 00:57:49,080
Speaker 1: it's tusk had been broken in the past and um,

1054
00:57:49,160 --> 00:57:51,400
Speaker 1: and they honored it by laying it out ceremonial. They

1055
00:57:51,920 --> 00:57:55,720
Speaker 1: moved its scapulus or its pelvis up by its head.

1056
00:57:56,240 --> 00:58:01,080
Speaker 1: There was another um uh tusk from another animal is

1057
00:58:01,080 --> 00:58:04,120
Speaker 1: placed around it. It's sort of one of those classic

1058
00:58:04,200 --> 00:58:07,440
Speaker 1: examples of there's patterns and the piles of these bones,

1059
00:58:08,120 --> 00:58:12,360
Speaker 1: and the only explanation that's grasp at is humans must

1060
00:58:12,400 --> 00:58:16,000
Speaker 1: have done it. So I think it's a fabulous site. Um.

1061
00:58:16,040 --> 00:58:19,800
Speaker 1: Every one of their sort of um things that they've interpreted.

1062
00:58:20,760 --> 00:58:24,600
Speaker 1: I see his research questions rather than answers of it's

1063
00:58:24,640 --> 00:58:30,680
Speaker 1: a stuff the press. Well, the press do, but I

1064
00:58:30,720 --> 00:58:33,160
Speaker 1: think in this case, and I don't want to sound

1065
00:58:33,640 --> 00:58:39,040
Speaker 1: derogatory about this, the excavators may have as well, because think,

1066
00:58:39,040 --> 00:58:42,920
Speaker 1: if you're faced with this amazing quantity of mammoth bones

1067
00:58:43,480 --> 00:58:48,040
Speaker 1: in an area where people are digging a landfill, and

1068
00:58:48,080 --> 00:58:51,120
Speaker 1: you know it's an important research thing, and you go

1069
00:58:51,200 --> 00:58:53,160
Speaker 1: to the press, you're gonna want to make it sound

1070
00:58:53,280 --> 00:58:56,440
Speaker 1: as important as possible to be sure it doesn't get destroyed.

1071
00:58:56,920 --> 00:58:59,720
Speaker 1: I would do that, you know, Um, here's here's this

1072
00:59:00,000 --> 00:59:03,480
Speaker 1: abulous site and you're talking. You've got to make it

1073
00:59:04,280 --> 00:59:08,040
Speaker 1: a site that is worthy of preservation and further research

1074
00:59:08,120 --> 00:59:10,400
Speaker 1: so that next time something's found. So I'm not saying

1075
00:59:10,440 --> 00:59:13,000
Speaker 1: they necessarily did that, but in the back of if

1076
00:59:13,040 --> 00:59:16,160
Speaker 1: I were faced with a pile of mammoth bones that

1077
00:59:16,240 --> 00:59:19,600
Speaker 1: and pressing, I'd be really worried about the preservation of

1078
00:59:19,680 --> 00:59:22,000
Speaker 1: them in future areas of the site and trying to

1079
00:59:22,000 --> 00:59:26,200
Speaker 1: get everything I could for preservation and protection and funding

1080
00:59:26,320 --> 00:59:28,520
Speaker 1: and start running the coolest version to start running the

1081
00:59:28,560 --> 00:59:31,640
Speaker 1: coolest could maybe be true. So I don't think at

1082
00:59:31,640 --> 00:59:37,280
Speaker 1: present and on this site, there's no scientific publication associated

1083
00:59:37,280 --> 00:59:41,360
Speaker 1: with it. There's one sometime, but right now it's one

1084
00:59:41,480 --> 00:59:44,360
Speaker 1: like four page press release that every one of the

1085
00:59:44,360 --> 00:59:48,320
Speaker 1: newspaper articles have been taking this one press release and

1086
00:59:48,600 --> 00:59:51,880
Speaker 1: spending it a little different. Would you would you welcome

1087
00:59:51,920 --> 00:59:53,600
Speaker 1: an opportunity to go down there and have a look.

1088
00:59:56,640 --> 01:00:01,640
Speaker 1: I'm retired and I would love to, But to do

1089
01:00:02,360 --> 01:00:06,160
Speaker 1: a site like that effectively need somebody with a lot

1090
01:00:06,160 --> 01:00:08,640
Speaker 1: of energy and a lot of time. It'd be Oh,

1091
01:00:08,680 --> 01:00:10,360
Speaker 1: I'd love to look at it. I would be on

1092
01:00:10,400 --> 01:00:12,680
Speaker 1: a plane in a minute just to go drool on

1093
01:00:12,720 --> 01:00:15,960
Speaker 1: a site like that. Um, just because as they sort

1094
01:00:16,000 --> 01:00:19,640
Speaker 1: of mentioned in some of the press releases, and this

1095
01:00:19,680 --> 01:00:21,480
Speaker 1: is where I get to like an Hudson Man and

1096
01:00:21,480 --> 01:00:24,680
Speaker 1: a lot of others in terms of really understanding the

1097
01:00:24,720 --> 01:00:27,560
Speaker 1: past of these landscapes we live on. At one level,

1098
01:00:27,560 --> 01:00:29,800
Speaker 1: it doesn't matter whether it's a human kill site or not.

1099
01:00:30,280 --> 01:00:34,440
Speaker 1: Understanding the past ecology and life ways of the mammoths

1100
01:00:34,480 --> 01:00:36,880
Speaker 1: in that environment that we know that in some instances,

1101
01:00:36,920 --> 01:00:41,000
Speaker 1: in what fourteen fifteen sites, humans were preying on mammoths

1102
01:00:41,000 --> 01:00:45,360
Speaker 1: directly understanding the biology and the coology of those mammoths

1103
01:00:45,440 --> 01:00:49,440
Speaker 1: is key. So regardless of whether the site has human involvement,

1104
01:00:49,800 --> 01:00:54,760
Speaker 1: it's a key site. Are they finding human are they

1105
01:00:54,800 --> 01:00:59,080
Speaker 1: finding artifacts? Report no stone tools from it, which again

1106
01:00:59,120 --> 01:01:01,760
Speaker 1: is sort of surprising. If you've got fourteen mammoths and

1107
01:01:02,480 --> 01:01:06,080
Speaker 1: you never once re sharpen a stone tools disposable to

1108
01:01:06,680 --> 01:01:10,160
Speaker 1: um and you never lose one, you know, think about

1109
01:01:10,200 --> 01:01:13,040
Speaker 1: all the huge piles of guts and gore and just

1110
01:01:13,280 --> 01:01:15,640
Speaker 1: bloody stuff that you're gonna be dropping tools and losing.

1111
01:01:15,920 --> 01:01:21,120
Speaker 1: How could you not lose something? So I'm buzz killing.

1112
01:01:21,400 --> 01:01:24,680
Speaker 1: I'm skeptical about the site. Um. And another thing that

1113
01:01:24,680 --> 01:01:28,120
Speaker 1: I'm skeptical about is that they're excavated pits. Uh. They

1114
01:01:29,040 --> 01:01:33,200
Speaker 1: talk about the site six deep holes. Oh my kid.

1115
01:01:33,240 --> 01:01:35,160
Speaker 1: I just sold my kid this morning about this. They

1116
01:01:35,200 --> 01:01:37,160
Speaker 1: would tell me how they actually do it. He says,

1117
01:01:37,160 --> 01:01:38,720
Speaker 1: they put sharp sticks in the bottom. I don't know

1118
01:01:38,720 --> 01:01:43,080
Speaker 1: where you got that you do that? Um? The geology, well,

1119
01:01:43,120 --> 01:01:45,240
Speaker 1: they don't talk about the geology of the site. They

1120
01:01:46,760 --> 01:01:50,160
Speaker 1: I know it's radio So I brought in some good pictures. Um,

1121
01:01:50,200 --> 01:01:52,320
Speaker 1: this is what the site looks like. There's a pile

1122
01:01:52,360 --> 01:01:54,960
Speaker 1: of bones. You can see there's sentiments here and then

1123
01:01:55,040 --> 01:01:56,840
Speaker 1: right over here. This is the sort of drop off

1124
01:01:57,000 --> 01:02:00,760
Speaker 1: there is are indeed strop steep drop offs adjacent to

1125
01:02:00,800 --> 01:02:03,920
Speaker 1: the bone. They think that natural. They think that's the

1126
01:02:03,960 --> 01:02:07,520
Speaker 1: cut that was at looks like no man like a ledge,

1127
01:02:07,600 --> 01:02:10,560
Speaker 1: like a like a imagine a six ft high cut bank. Well,

1128
01:02:10,560 --> 01:02:13,680
Speaker 1: they talk cut bank real high potential. They talk about

1129
01:02:13,720 --> 01:02:16,640
Speaker 1: in the article that at the time the site was forming,

1130
01:02:17,400 --> 01:02:21,600
Speaker 1: the lake that it was forming around was its level

1131
01:02:21,720 --> 01:02:24,080
Speaker 1: was dropping. It was drying up. So as a light

1132
01:02:24,200 --> 01:02:26,640
Speaker 1: level is dropping, any water that's running into it is

1133
01:02:26,680 --> 01:02:30,880
Speaker 1: going to cut in channels into it. So first they're

1134
01:02:30,880 --> 01:02:33,640
Speaker 1: gonna have to tell me that these aren't erosional channels

1135
01:02:33,920 --> 01:02:38,320
Speaker 1: cutting into that lower light level. UM jumping to the

1136
01:02:38,320 --> 01:02:42,880
Speaker 1: conclusion that you've got um more recent sediments, UM in

1137
01:02:43,080 --> 01:02:45,400
Speaker 1: older sediments, and the only way that can happen as

1138
01:02:45,520 --> 01:02:48,880
Speaker 1: humans digging a hole. Uh, that's a that's quite elite.

1139
01:02:48,960 --> 01:02:51,640
Speaker 1: We've all eaten a lot of the bison kill sites.

1140
01:02:51,640 --> 01:02:54,280
Speaker 1: We found find that our inner ryos have the same

1141
01:02:54,280 --> 01:02:58,280
Speaker 1: sort of sedimentation old drainage. Bison killed in the bottom

1142
01:02:58,280 --> 01:03:00,960
Speaker 1: of it, sediment builds up over it. People didn't dig

1143
01:03:00,960 --> 01:03:05,480
Speaker 1: the drainage. Um, I don't know. The pits is a

1144
01:03:05,560 --> 01:03:08,280
Speaker 1: stretch for me. Um, just to get You were talking

1145
01:03:08,320 --> 01:03:11,720
Speaker 1: earlier about how many people it would take to butcher

1146
01:03:12,920 --> 01:03:15,360
Speaker 1: eight hundred bison. How many people is it gonna take

1147
01:03:15,840 --> 01:03:20,000
Speaker 1: to dig a what is it? Eighty long by wide

1148
01:03:20,040 --> 01:03:24,920
Speaker 1: hole two deep? Um, you know that's half the size

1149
01:03:24,920 --> 01:03:29,680
Speaker 1: of a football. That's some Egyptian grade business. Was gonna Yeah,

1150
01:03:30,120 --> 01:03:33,840
Speaker 1: and um, why are you going to invest that much

1151
01:03:33,960 --> 01:03:37,960
Speaker 1: labor where you're not out hunting in an environment with

1152
01:03:38,000 --> 01:03:41,080
Speaker 1: that supposedly fairly rich in mammoths. Yeah, it's gonna You're

1153
01:03:41,080 --> 01:03:43,640
Speaker 1: gonna be sure you're gonna get them if they're right there.

1154
01:03:44,400 --> 01:03:47,360
Speaker 1: But we talked about one of the things that I've

1155
01:03:47,400 --> 01:03:50,320
Speaker 1: been worrying about recently a lot. Well, let me ask

1156
01:03:50,640 --> 01:03:53,440
Speaker 1: stop from it. Why did you not like, okay, when

1157
01:03:53,480 --> 01:03:55,880
Speaker 1: this comes out? Why do you not right so it

1158
01:03:55,920 --> 01:03:58,200
Speaker 1: comes I was reported in the New York Times, why

1159
01:03:58,240 --> 01:04:00,400
Speaker 1: do you not write a letter? Do you just waste

1160
01:04:00,440 --> 01:04:02,800
Speaker 1: your time? Like? Why did you not write a letter

1161
01:04:03,320 --> 01:04:09,920
Speaker 1: to the editor saying like here a minute and kind

1162
01:04:09,920 --> 01:04:12,320
Speaker 1: of like layout, Why do you let the why why

1163
01:04:12,320 --> 01:04:14,000
Speaker 1: did why do you guys let the whole thing run

1164
01:04:14,040 --> 01:04:15,960
Speaker 1: and catch on fire, and guys like me telling their

1165
01:04:16,000 --> 01:04:20,520
Speaker 1: kids all about it. Good question, Um preservation, like he said, well,

1166
01:04:21,200 --> 01:04:26,640
Speaker 1: um laziness. Um uh, you know that it's not my problem.

1167
01:04:26,640 --> 01:04:30,760
Speaker 1: I'm retired. Um. Um, we've heard these stories. I don't

1168
01:04:31,120 --> 01:04:36,000
Speaker 1: good questions. It doesn't burn you up at this stage.

1169
01:04:36,000 --> 01:04:37,880
Speaker 1: It sort of runs off the back. We've heard that

1170
01:04:38,200 --> 01:04:42,240
Speaker 1: over and over and over and over and over again. Um.

1171
01:04:42,400 --> 01:04:45,320
Speaker 1: You often get this buzz of of press and then

1172
01:04:45,360 --> 01:04:47,800
Speaker 1: you start looking at the story a little deeper and

1173
01:04:47,880 --> 01:04:51,320
Speaker 1: you find out, well, it's not that simple. I find

1174
01:04:51,520 --> 01:04:54,680
Speaker 1: that's the thing is because I like to follow anthropology.

1175
01:04:55,040 --> 01:04:58,240
Speaker 1: It is like I do find that the stories generally

1176
01:04:58,280 --> 01:05:04,600
Speaker 1: get less interested with the exception of the woman's skull

1177
01:05:04,640 --> 01:05:08,720
Speaker 1: they found out in the Yuktahan underwater. Oh, I'm not

1178
01:05:08,760 --> 01:05:12,919
Speaker 1: familiar with that. Better. I thought that one got better.

1179
01:05:13,800 --> 01:05:15,480
Speaker 1: It's the old I mean, I think it was one

1180
01:05:15,520 --> 01:05:17,720
Speaker 1: of the one of the oldest pieces of human remains

1181
01:05:17,720 --> 01:05:20,160
Speaker 1: in the New World. And how did it get better?

1182
01:05:21,200 --> 01:05:24,760
Speaker 1: Oh because they found all the stuff that it was with. Yeah,

1183
01:05:24,880 --> 01:05:27,240
Speaker 1: all the other bones that were down in there, and

1184
01:05:27,240 --> 01:05:29,720
Speaker 1: and um, you know, like there was they were able

1185
01:05:29,720 --> 01:05:32,560
Speaker 1: to term as like a young woman and like injuries

1186
01:05:32,640 --> 01:05:36,160
Speaker 1: and yeah, and stuff that was just wanted being good.

1187
01:05:36,320 --> 01:05:38,680
Speaker 1: And then that dude that they've had seven thousand ye

1188
01:05:38,680 --> 01:05:42,520
Speaker 1: old dude they found in Europe, the Iceman. Yeah, that story.

1189
01:05:42,640 --> 01:05:46,080
Speaker 1: You know, here's something that's really interesting about Aussie that's

1190
01:05:46,480 --> 01:05:51,320
Speaker 1: not related to Ausi at all. Uh but he's about

1191
01:05:51,320 --> 01:05:54,000
Speaker 1: three thousand years old, four thousand years killed by an arrow.

1192
01:05:54,440 --> 01:05:56,920
Speaker 1: Well it died, but yeah he has it was carrying

1193
01:05:57,000 --> 01:05:59,440
Speaker 1: arrow in them and there they can reconstruct his diet

1194
01:05:59,520 --> 01:06:01,880
Speaker 1: based on what's in his stomach. They were looking at

1195
01:06:02,000 --> 01:06:05,280
Speaker 1: the lichens that were growing just amazing tricked out boots.

1196
01:06:05,280 --> 01:06:07,480
Speaker 1: They had three different kinds of hides on him and stuff.

1197
01:06:08,920 --> 01:06:11,880
Speaker 1: The fun thing right here, um, in this area of

1198
01:06:11,920 --> 01:06:15,640
Speaker 1: the world to know about is the oldest article artifact

1199
01:06:15,680 --> 01:06:18,160
Speaker 1: from an ice patch anywhere in the world comes from

1200
01:06:18,160 --> 01:06:22,000
Speaker 1: the Beartooth Mountains here. Yeah, that's a ten thousand years old,

1201
01:06:22,400 --> 01:06:25,680
Speaker 1: so about three times the age of Aussy. Really is

1202
01:06:25,720 --> 01:06:28,960
Speaker 1: something that Yeah, there's uh add a laddle a dark

1203
01:06:29,000 --> 01:06:33,920
Speaker 1: shaft researcher here in Bozeman. Craig Lee founded a few

1204
01:06:33,960 --> 01:06:37,280
Speaker 1: years ago radiocarbon dated He's been working on these high

1205
01:06:37,280 --> 01:06:40,480
Speaker 1: elevation ice patches that are melting out and exposing the

1206
01:06:40,480 --> 01:06:44,600
Speaker 1: stuff that was trapped in. So right here, yeah, right,

1207
01:06:44,680 --> 01:06:46,680
Speaker 1: But I remember the guy there was a dude. I

1208
01:06:46,720 --> 01:06:48,680
Speaker 1: remember two things like this in Canada. But I know

1209
01:06:48,760 --> 01:06:54,320
Speaker 1: something fun of the old birch, I believe, but don't

1210
01:06:54,400 --> 01:06:57,240
Speaker 1: quote me. It was still armed. No, it's just got

1211
01:06:57,240 --> 01:06:58,880
Speaker 1: the shaft and the point is not it and it's

1212
01:06:58,920 --> 01:07:01,080
Speaker 1: kind of warped from being it's got the marks on it,

1213
01:07:01,120 --> 01:07:02,600
Speaker 1: and it's got the notch where the point would have

1214
01:07:02,600 --> 01:07:05,000
Speaker 1: went in it was it was a decorative at all. Well,

1215
01:07:05,000 --> 01:07:06,560
Speaker 1: it has a couple of marks on it that he

1216
01:07:06,640 --> 01:07:09,320
Speaker 1: thinks maybe ownership marks. If you know, if you've got

1217
01:07:09,360 --> 01:07:11,840
Speaker 1: a dart and several darts end up in an animal

1218
01:07:11,880 --> 01:07:13,720
Speaker 1: and you want to say, well my dart got it. No,

1219
01:07:13,880 --> 01:07:16,560
Speaker 1: that's my dart, So you do occasionally put marks on

1220
01:07:16,560 --> 01:07:20,240
Speaker 1: it to be like everybody uses different fletching and the arrows. Yeah, ship,

1221
01:07:20,440 --> 01:07:22,440
Speaker 1: So I don't know, just I like to bring that

1222
01:07:22,520 --> 01:07:25,120
Speaker 1: up just because we start talking about all the fabulous stuff.

1223
01:07:25,160 --> 01:07:27,760
Speaker 1: And I do a lot of work with kids. Um

1224
01:07:27,840 --> 01:07:31,120
Speaker 1: and I grew up in a small town called Matici, Wyoming,

1225
01:07:31,120 --> 01:07:32,760
Speaker 1: where you think you're in the back of nowhere, and

1226
01:07:32,760 --> 01:07:34,960
Speaker 1: there's nothing neat going on there. So when I work

1227
01:07:35,000 --> 01:07:36,800
Speaker 1: with kids in this area, I try and bring up

1228
01:07:36,800 --> 01:07:38,760
Speaker 1: things like that, did you know the oldest one of

1229
01:07:38,760 --> 01:07:40,560
Speaker 1: those in the world comes from right here in the

1230
01:07:40,920 --> 01:07:44,080
Speaker 1: backyard I find people. I was telling someone this morning

1231
01:07:44,160 --> 01:07:48,840
Speaker 1: about how you know where Wilsol is? I mean, drive there,

1232
01:07:49,080 --> 01:07:52,200
Speaker 1: you know, be there in time for lunch. For a

1233
01:07:52,200 --> 01:07:54,560
Speaker 1: long time. That was the oldest human remains and new

1234
01:07:54,640 --> 01:07:58,200
Speaker 1: roles oft. Yeah, a little boy named a zik one. Yeah,

1235
01:07:58,720 --> 01:08:02,760
Speaker 1: so as I write down the road, it's picture. Uh,

1236
01:08:03,120 --> 01:08:05,560
Speaker 1: let me lay at like a bigger idea, a bigger

1237
01:08:05,680 --> 01:08:11,200
Speaker 1: notion on you. Do you feel that? Um? Do you

1238
01:08:11,240 --> 01:08:15,120
Speaker 1: feel that? For a while, we really had this idea

1239
01:08:15,200 --> 01:08:19,480
Speaker 1: that early humans, that the earliest Americans, the first Americans,

1240
01:08:20,280 --> 01:08:26,000
Speaker 1: where he's hard hitting, very successful, big game hunters, and

1241
01:08:26,000 --> 01:08:29,920
Speaker 1: they're going around slam mammoths left and right, killing all

1242
01:08:30,000 --> 01:08:32,519
Speaker 1: kinds of big stuff, wiping animals off to you know,

1243
01:08:32,600 --> 01:08:37,520
Speaker 1: wiping all the mega faun off the face of the earth. Um.

1244
01:08:37,560 --> 01:08:42,080
Speaker 1: And then my like, like my my casual observational following

1245
01:08:42,120 --> 01:08:47,439
Speaker 1: of anthropology is that that narrative has become disrupted and

1246
01:08:47,560 --> 01:08:51,639
Speaker 1: that it's like they were eating lots of other stuff. Um,

1247
01:08:51,920 --> 01:08:54,200
Speaker 1: places that we thought they'd killed them, they weren't actually

1248
01:08:54,280 --> 01:08:57,040
Speaker 1: killing them. They had a lot of clams, they ate

1249
01:08:57,040 --> 01:08:59,360
Speaker 1: a lot of turtles, they had a lot of seeds

1250
01:08:59,360 --> 01:09:02,400
Speaker 1: and nuts and yeah maybe now and then they got

1251
01:09:02,479 --> 01:09:06,160
Speaker 1: lucky and found a crippled up mammoth and killed it

1252
01:09:06,200 --> 01:09:08,679
Speaker 1: and ate it. Like like, where do you sit on that?

1253
01:09:09,600 --> 01:09:11,639
Speaker 1: On the extremes? And I know that this stuff bounces

1254
01:09:11,680 --> 01:09:14,439
Speaker 1: in extremes, right, it'd be like all they was mammoth

1255
01:09:14,479 --> 01:09:18,400
Speaker 1: and someone's gonna probably counter that with, yeah, they're all

1256
01:09:18,479 --> 01:09:21,439
Speaker 1: vegan and in somewhere, right, how do you feel about

1257
01:09:21,520 --> 01:09:24,200
Speaker 1: do you think that that's true, that that flow of

1258
01:09:24,439 --> 01:09:27,880
Speaker 1: that perception is going through a change, and where do

1259
01:09:27,960 --> 01:09:31,560
Speaker 1: you what version is? Right? Okay you um prefas that

1260
01:09:31,640 --> 01:09:33,519
Speaker 1: was saying you wanted to look at a little bigger,

1261
01:09:33,560 --> 01:09:37,160
Speaker 1: sort of broader question. And I agree with that sort

1262
01:09:37,200 --> 01:09:42,920
Speaker 1: of perspective entirely, and um, for years I was fascinated

1263
01:09:42,960 --> 01:09:44,960
Speaker 1: with the peopling of America's that was one of those

1264
01:09:45,000 --> 01:09:47,400
Speaker 1: things that just that's why I looked at these early

1265
01:09:47,479 --> 01:09:49,680
Speaker 1: kill sites and mammoth sites and bison sized try and

1266
01:09:49,720 --> 01:09:52,400
Speaker 1: understand you know why, because it is the most fascinating

1267
01:09:52,439 --> 01:09:55,200
Speaker 1: thing in the universe. Oh and it's um like playing this,

1268
01:09:55,720 --> 01:09:57,679
Speaker 1: it's not even debatable, it's not even a debatable point.

1269
01:09:57,720 --> 01:10:00,760
Speaker 1: And excavating them is those It's just like playing this

1270
01:10:00,840 --> 01:10:03,040
Speaker 1: wonderful game of pickup sticks. It's just the most fun

1271
01:10:03,040 --> 01:10:05,000
Speaker 1: you can have doing So I was fascinated by it,

1272
01:10:06,880 --> 01:10:10,120
Speaker 1: and in the last twenty years I become much less

1273
01:10:10,160 --> 01:10:14,760
Speaker 1: fascinated with the peopling of the America's question because that

1274
01:10:15,000 --> 01:10:18,879
Speaker 1: isn't the question. The question is why did we leave Africa?

1275
01:10:19,439 --> 01:10:22,560
Speaker 1: The people in America's is we ended up everywhere in

1276
01:10:22,600 --> 01:10:26,000
Speaker 1: the globe. We people the planet. Yeah, we're the biggest

1277
01:10:26,040 --> 01:10:30,400
Speaker 1: invasive species, so because of people everywhere. So why is

1278
01:10:30,439 --> 01:10:34,160
Speaker 1: it that we started expanding out of Africa in the

1279
01:10:34,160 --> 01:10:39,000
Speaker 1: first place? And why do you move away from home? Curious? Curious,

1280
01:10:39,040 --> 01:10:41,320
Speaker 1: But there's also I think, getting back to the specifics

1281
01:10:41,360 --> 01:10:44,600
Speaker 1: of your question. We're working on a site in northwestern

1282
01:10:44,600 --> 01:10:48,600
Speaker 1: Ethiopia at about seventy thousand years of age, trying to

1283
01:10:48,640 --> 01:10:50,879
Speaker 1: answer that question of what was going on with humans

1284
01:10:50,880 --> 01:10:53,839
Speaker 1: in terms of our ecology right before we left African

1285
01:10:53,920 --> 01:10:58,920
Speaker 1: expanded into the rest of the world, and traditionally, when

1286
01:10:58,920 --> 01:11:03,439
Speaker 1: people have looked at human evolution and human movement into Europe,

1287
01:11:03,680 --> 01:11:06,240
Speaker 1: just like in the People of America's they focused on

1288
01:11:06,320 --> 01:11:09,799
Speaker 1: that big game hunter. You know that we can expand

1289
01:11:09,840 --> 01:11:14,120
Speaker 1: because we're the apex predator into every environment we go into.

1290
01:11:14,680 --> 01:11:17,679
Speaker 1: One of the things we're seeing on our seventy thousand

1291
01:11:17,720 --> 01:11:21,040
Speaker 1: year old Middlestone age site on the tributaries of the

1292
01:11:21,040 --> 01:11:26,280
Speaker 1: Blue Nile is that it's um northwestern Ethiopia. UM So

1293
01:11:26,439 --> 01:11:28,880
Speaker 1: right around the time when we think that like anatomically

1294
01:11:29,200 --> 01:11:32,479
Speaker 1: with the anatomically modern human split, right before we started

1295
01:11:32,479 --> 01:11:35,920
Speaker 1: that diaspora, And what we're seeing is, yeah, there's a

1296
01:11:35,960 --> 01:11:39,479
Speaker 1: few big game animals there, but there's also every other

1297
01:11:39,600 --> 01:11:44,559
Speaker 1: damn thing that crawled, swam, wiggled, walked um. I think

1298
01:11:44,760 --> 01:11:47,439
Speaker 1: one of the things that makes us effective is not

1299
01:11:47,640 --> 01:11:50,040
Speaker 1: the big game hunting per se, but that we are

1300
01:11:51,040 --> 01:11:55,400
Speaker 1: just so plastic in our diet. We are the classic omnivores,

1301
01:11:55,479 --> 01:11:58,240
Speaker 1: which means that you can move into any environment out

1302
01:11:58,240 --> 01:12:00,679
Speaker 1: there and you're gonna find something to eat. Julie, I've

1303
01:12:00,720 --> 01:12:02,240
Speaker 1: just heard the other day the eight I think it's

1304
01:12:02,400 --> 01:12:06,320
Speaker 1: eighties some percent of the animals on the planet are carnivorous.

1305
01:12:07,240 --> 01:12:09,519
Speaker 1: It's the dominant form because you've got to go in

1306
01:12:09,600 --> 01:12:12,160
Speaker 1: like all the fish and stuff. Yeah, it's the dominant,

1307
01:12:12,160 --> 01:12:14,560
Speaker 1: the dominant way to be. So if you conivores or

1308
01:12:14,600 --> 01:12:18,120
Speaker 1: a small minority which which gives you, that opens up

1309
01:12:18,160 --> 01:12:20,840
Speaker 1: all those other niches. So I think the people of

1310
01:12:20,880 --> 01:12:23,000
Speaker 1: the America's that the answer to the people in of

1311
01:12:23,040 --> 01:12:26,360
Speaker 1: the America's um. The timing we still don't have down,

1312
01:12:26,680 --> 01:12:29,240
Speaker 1: but it's that we're just flexible and what we can

1313
01:12:29,280 --> 01:12:31,439
Speaker 1: eat and what we can do. And when you plug

1314
01:12:31,520 --> 01:12:34,599
Speaker 1: that into like we left because we could. We left

1315
01:12:34,600 --> 01:12:38,840
Speaker 1: because we could and we had um uh. If you

1316
01:12:38,840 --> 01:12:41,000
Speaker 1: can eat anything, you can go any damn where you want.

1317
01:12:42,600 --> 01:12:45,040
Speaker 1: You know, as you said, you plug in curiosity to

1318
01:12:45,120 --> 01:12:48,400
Speaker 1: that you plug in even marginal population growth to where

1319
01:12:48,840 --> 01:12:52,680
Speaker 1: if um, oldest kid, you know, why don't you go

1320
01:12:52,720 --> 01:12:55,600
Speaker 1: over in that next valley? Like not like not propelled

1321
01:12:55,720 --> 01:12:59,280
Speaker 1: by the need to go kill thousand pounds, because that

1322
01:12:59,439 --> 01:13:02,400
Speaker 1: constantly ning out of thousand pound mammals that might sometimes

1323
01:13:02,439 --> 01:13:04,720
Speaker 1: pull you, but um at other times. That One of

1324
01:13:04,720 --> 01:13:07,479
Speaker 1: the things we're seeing along the Blue Nile is that

1325
01:13:07,960 --> 01:13:10,960
Speaker 1: the tributary we're on is a seasonal river. It has

1326
01:13:11,160 --> 01:13:13,840
Speaker 1: you know, a hundred meters wide twenty deep during the

1327
01:13:13,920 --> 01:13:16,080
Speaker 1: rainy season, but then during the dry season it ends

1328
01:13:16,160 --> 01:13:19,519
Speaker 1: up into these little puddles, and those little puddles are

1329
01:13:19,560 --> 01:13:21,920
Speaker 1: where the game's attracted to. You can walk out into

1330
01:13:21,960 --> 01:13:25,680
Speaker 1: those puddles and you pick up um meter long catfish. Um.

1331
01:13:25,760 --> 01:13:28,160
Speaker 1: You know, there's just so the dry seasons and this

1332
01:13:28,240 --> 01:13:31,880
Speaker 1: run's countered to the ways and it's yeah, but in

1333
01:13:31,920 --> 01:13:35,479
Speaker 1: the past, there no we well, we've we fish to

1334
01:13:35,520 --> 01:13:38,479
Speaker 1: collect the fish, to bury them in the ground, to

1335
01:13:38,520 --> 01:13:42,320
Speaker 1: collect their bones put into our comparative collection. The locals

1336
01:13:42,320 --> 01:13:44,160
Speaker 1: give give us that sort of luck if you're doing

1337
01:13:44,200 --> 01:13:47,360
Speaker 1: what with that? Um, Like, this guy's got it all wrong.

1338
01:13:48,640 --> 01:13:52,200
Speaker 1: But anyway, it's looking like in terms of resource predictability

1339
01:13:52,200 --> 01:13:54,919
Speaker 1: in the past, models of when people left Africa suggested

1340
01:13:54,960 --> 01:13:57,360
Speaker 1: we did it during the wetter phases of where you

1341
01:13:57,360 --> 01:13:59,000
Speaker 1: can make it through the Sahara and down along the

1342
01:13:59,080 --> 01:14:01,719
Speaker 1: Nile Valley. That obviously you're gonna do it when it's wetter.

1343
01:14:02,320 --> 01:14:04,519
Speaker 1: But what we're seeing on this side is when it's

1344
01:14:04,760 --> 01:14:07,200
Speaker 1: during the rainy seasons and during the high moisture season

1345
01:14:07,560 --> 01:14:09,200
Speaker 1: is a really tough time to get away because the

1346
01:14:09,240 --> 01:14:12,519
Speaker 1: game's dispersed. Uh, it's tough to fish in the rivers.

1347
01:14:12,560 --> 01:14:14,640
Speaker 1: You can't get the mollish, you can't get the fish.

1348
01:14:14,720 --> 01:14:18,160
Speaker 1: But the dry seasons are where the resources become predictable

1349
01:14:18,160 --> 01:14:20,800
Speaker 1: because they're around those few remaining water holes, and so

1350
01:14:20,920 --> 01:14:22,840
Speaker 1: you could move from water hole to water hole to

1351
01:14:22,840 --> 01:14:26,840
Speaker 1: water hole around these small resources rather than the bit,

1352
01:14:26,920 --> 01:14:29,960
Speaker 1: you know, following the big game. You're following the catfish

1353
01:14:29,960 --> 01:14:32,519
Speaker 1: and the mollusk from one water hole like pearls on

1354
01:14:32,560 --> 01:14:34,479
Speaker 1: a string down the river. It's just gonna suck you

1355
01:14:34,520 --> 01:14:37,639
Speaker 1: down the river draining during the time of year when

1356
01:14:37,920 --> 01:14:39,479
Speaker 1: you know, again we've thought of it in the past,

1357
01:14:39,640 --> 01:14:41,120
Speaker 1: you're not gonna be out there in the middle desert

1358
01:14:41,200 --> 01:14:44,120
Speaker 1: during the dry season. It might make it the most predictable,

1359
01:14:44,160 --> 01:14:47,640
Speaker 1: the most likely. Not only the small stuff, but if

1360
01:14:47,640 --> 01:14:50,000
Speaker 1: there's game animals in the area, they're gonna be coming

1361
01:14:50,000 --> 01:14:53,120
Speaker 1: there to water. So you're gonna know that several times

1362
01:14:53,120 --> 01:14:55,280
Speaker 1: a day there's gonna be game animals there as well.

1363
01:14:55,680 --> 01:14:59,160
Speaker 1: You know. Uh. We've been fortunate enough to travel a

1364
01:14:59,200 --> 01:15:03,080
Speaker 1: little bit on rivers down in South America with Amerindians,

1365
01:15:03,800 --> 01:15:07,880
Speaker 1: and they really like the dry season because the fishing

1366
01:15:07,920 --> 01:15:09,880
Speaker 1: is phenomenal, and they always thought about when the dry

1367
01:15:09,880 --> 01:15:12,200
Speaker 1: season dry seas dry season, they like it. They like

1368
01:15:12,280 --> 01:15:15,880
Speaker 1: the dry season to travel because everything gets concentrated and

1369
01:15:16,040 --> 01:15:18,519
Speaker 1: the depole wet season it's it's muddy and it's awful.

1370
01:15:18,560 --> 01:15:21,800
Speaker 1: It's terrible and you set around in your get rained

1371
01:15:21,840 --> 01:15:23,640
Speaker 1: on and it's miserable. Yeah. The only thing that like

1372
01:15:23,680 --> 01:15:25,000
Speaker 1: that they talked about the only thing like about the

1373
01:15:25,000 --> 01:15:28,600
Speaker 1: wet season is if it gets so wet that you

1374
01:15:28,680 --> 01:15:32,120
Speaker 1: have small little hills that become like refuge you and everything,

1375
01:15:32,560 --> 01:15:34,000
Speaker 1: and you can go there and you can go there

1376
01:15:34,000 --> 01:15:35,320
Speaker 1: and get a lot of You can go there and

1377
01:15:35,560 --> 01:15:37,599
Speaker 1: animals will have to get up on those and then

1378
01:15:37,640 --> 01:15:39,280
Speaker 1: you just pull up and kill them. That's fun. That's

1379
01:15:39,280 --> 01:15:41,200
Speaker 1: the flip side of our dry season. You know, there's

1380
01:15:41,200 --> 01:15:44,000
Speaker 1: there's two times a year when you've got these these

1381
01:15:44,040 --> 01:15:47,720
Speaker 1: sort of landscape scale grocery stores because everything's there there,

1382
01:15:47,840 --> 01:15:49,920
Speaker 1: your big costco. Yeah, they talk about it. You go

1383
01:15:49,960 --> 01:15:51,479
Speaker 1: out if it gets like that, they would go out

1384
01:15:51,479 --> 01:15:54,599
Speaker 1: in their boats and it's cleaning exactly where where everybody

1385
01:15:54,600 --> 01:15:56,200
Speaker 1: likes to hang out. But yeah, they always talk about

1386
01:15:56,200 --> 01:15:59,320
Speaker 1: the dry season being when you want to fish. Yeah. Um,

1387
01:16:00,160 --> 01:16:03,479
Speaker 1: so what's your like, uh, what's your theory on the

1388
01:16:03,960 --> 01:16:05,799
Speaker 1: I mean, like where do you stand on the blitz

1389
01:16:06,240 --> 01:16:09,240
Speaker 1: the blitz creak hypothesis idea in North America the humans

1390
01:16:09,760 --> 01:16:13,840
Speaker 1: that that that humans came in, I mean just the

1391
01:16:13,840 --> 01:16:17,680
Speaker 1: ideas of popular and seven and maintained remain popular for

1392
01:16:17,680 --> 01:16:20,000
Speaker 1: a while. Humans came in and killed everything and that's

1393
01:16:20,040 --> 01:16:21,760
Speaker 1: why the mammoths are gone because people killed him in

1394
01:16:21,800 --> 01:16:24,320
Speaker 1: an them all? Are you are? Do you sort of

1395
01:16:24,360 --> 01:16:26,840
Speaker 1: go against the grain on that? Or I don't know, Well,

1396
01:16:26,840 --> 01:16:28,840
Speaker 1: what what is the grain on that now? I think

1397
01:16:28,840 --> 01:16:30,800
Speaker 1: the grain on it now? Is this bullshit? I think

1398
01:16:30,840 --> 01:16:33,680
Speaker 1: I would say that the scholarly consensus. Let's let's go

1399
01:16:33,760 --> 01:16:35,880
Speaker 1: back to you know, we've been talking about Hudson Man.

1400
01:16:36,160 --> 01:16:39,280
Speaker 1: We left that story with killing might be one potential

1401
01:16:39,320 --> 01:16:43,000
Speaker 1: of it. Um when you look at plis the scene extinctions,

1402
01:16:43,720 --> 01:16:47,040
Speaker 1: I'm sure that having a new novel predator on the

1403
01:16:47,080 --> 01:16:49,680
Speaker 1: scene had something to do with it. But if you've

1404
01:16:49,680 --> 01:16:52,400
Speaker 1: got a climate change, if you've got vegetation change, if

1405
01:16:52,439 --> 01:16:55,240
Speaker 1: you've got water source change, if you've got maybe new

1406
01:16:55,280 --> 01:16:58,280
Speaker 1: diseases on the scene, it's hard to say which one

1407
01:16:58,320 --> 01:17:03,800
Speaker 1: of them is the the killing stroke that. Uh, I

1408
01:17:03,840 --> 01:17:05,760
Speaker 1: don't think you can say that humans had nothing to

1409
01:17:05,800 --> 01:17:08,479
Speaker 1: do with it. Anyway you could. You know, you can't

1410
01:17:08,520 --> 01:17:11,639
Speaker 1: put wolves back into Yellowstone and Novel Predator and say

1411
01:17:11,640 --> 01:17:14,440
Speaker 1: they don't have something to do with game population numbers.

1412
01:17:14,479 --> 01:17:16,240
Speaker 1: So humans had something to do with it. But I

1413
01:17:16,240 --> 01:17:19,480
Speaker 1: don't think the blitz Creek model. I think it's too simplistic.

1414
01:17:19,920 --> 01:17:22,320
Speaker 1: I think it's um goes back to where we started.

1415
01:17:22,640 --> 01:17:25,360
Speaker 1: It falls back to that if there's a pattern all

1416
01:17:25,400 --> 01:17:28,320
Speaker 1: these animals dying within a couple hundred year period, we

1417
01:17:28,400 --> 01:17:34,080
Speaker 1: must have done it, because nothing else creates patterns. Uh,

1418
01:17:34,360 --> 01:17:37,439
Speaker 1: here's no one for you. I was saying. I was

1419
01:17:37,479 --> 01:17:40,080
Speaker 1: saying to someone the other day, their day, Yanni was there.

1420
01:17:40,760 --> 01:17:44,040
Speaker 1: We were out doing a little arrowheadhunting on a buddy's

1421
01:17:44,120 --> 01:17:46,439
Speaker 1: ranch because there was a spot where there's like a hill.

1422
01:17:48,120 --> 01:17:51,400
Speaker 1: He's got a barn up above his barn, there's a

1423
01:17:51,439 --> 01:17:55,280
Speaker 1: little Benjy hill right above a creek, and there's sort

1424
01:17:55,280 --> 01:17:58,000
Speaker 1: of this little erosion line that kind of marches its

1425
01:17:58,040 --> 01:18:01,040
Speaker 1: way up the hill. And so one of the guys

1426
01:18:01,040 --> 01:18:02,720
Speaker 1: out there that works on the ranch was saying, you

1427
01:18:02,760 --> 01:18:05,080
Speaker 1: know a cool place to look is every year I'll

1428
01:18:05,120 --> 01:18:07,439
Speaker 1: go up and look at that little erosion line. You'll

1429
01:18:07,439 --> 01:18:11,320
Speaker 1: find a lot of flakes stone flakes. Um. And we

1430
01:18:11,360 --> 01:18:12,599
Speaker 1: went up there and had to look around and found

1431
01:18:12,600 --> 01:18:15,200
Speaker 1: a bunch of stone flakes and found one little small

1432
01:18:15,320 --> 01:18:18,559
Speaker 1: little um. I mean like a little point the tip

1433
01:18:18,640 --> 01:18:22,600
Speaker 1: was missing, but a little point the size of your thumbnail. Uh.

1434
01:18:22,680 --> 01:18:24,920
Speaker 1: I was explaining to everybody, I don't know if you're needed.

1435
01:18:25,120 --> 01:18:27,120
Speaker 1: If he wasn't ear shot, but I was because he

1436
01:18:27,160 --> 01:18:29,559
Speaker 1: was off looking around too. I was explaining every like man,

1437
01:18:29,600 --> 01:18:32,559
Speaker 1: all the low hanging fruits gone. And I was saying,

1438
01:18:32,600 --> 01:18:35,080
Speaker 1: like you read about arrowhead hunting in like the thirties,

1439
01:18:36,400 --> 01:18:37,960
Speaker 1: because for a long time, no one gave it, no,

1440
01:18:37,960 --> 01:18:39,680
Speaker 1: no one cared like he's no one picked it up.

1441
01:18:39,720 --> 01:18:41,800
Speaker 1: Then all a sudden it became interesting. And then you

1442
01:18:41,920 --> 01:18:44,080
Speaker 1: got all these guys like sheep herders from the thirties

1443
01:18:44,120 --> 01:18:46,280
Speaker 1: and forties that would fill five gallon buckets full of

1444
01:18:46,600 --> 01:18:50,600
Speaker 1: arrowheads and now saying there's nothing left. But before we

1445
01:18:50,640 --> 01:18:55,320
Speaker 1: started our recording conversation here, you were talking about the

1446
01:18:55,640 --> 01:18:58,960
Speaker 1: kind of like stunning amount of sights you're still able

1447
01:18:58,960 --> 01:19:06,320
Speaker 1: to identify when you go out looking. Um. Touch on that, like,

1448
01:19:06,360 --> 01:19:08,519
Speaker 1: I guess like different avenues of approach that I would

1449
01:19:08,520 --> 01:19:11,439
Speaker 1: like you to take would be one how like like,

1450
01:19:11,960 --> 01:19:14,559
Speaker 1: how much stuff is out there? Do you agree that

1451
01:19:14,640 --> 01:19:18,439
Speaker 1: all the everything's been picked over and it's all gone? Now?

1452
01:19:18,960 --> 01:19:22,719
Speaker 1: Have we not even scratched the surface on human old

1453
01:19:22,800 --> 01:19:26,120
Speaker 1: human sights? You just opened up a whole warring of

1454
01:19:26,280 --> 01:19:29,920
Speaker 1: rabbit holes. I'm trying to which one to go down.

1455
01:19:30,439 --> 01:19:33,720
Speaker 1: Um okay, let me A lot of a lot of

1456
01:19:33,760 --> 01:19:38,240
Speaker 1: areas have been very heavily picked over, which from an

1457
01:19:38,360 --> 01:19:43,759
Speaker 1: archaeological perspective is just devastating, which means you can find

1458
01:19:43,880 --> 01:19:46,200
Speaker 1: an archaeological site, there will be a few flakes there,

1459
01:19:46,680 --> 01:19:48,840
Speaker 1: and all you can say about it is people were

1460
01:19:48,840 --> 01:19:51,920
Speaker 1: here sometime in the last thirteen thousand years, which we

1461
01:19:51,960 --> 01:19:55,800
Speaker 1: knew before that when it was just like little chips. Yeah. Uh,

1462
01:19:56,240 --> 01:19:58,840
Speaker 1: if the points are there, those are like like we

1463
01:19:58,880 --> 01:20:02,080
Speaker 1: talked about, well, like a GPS puts a time stamp

1464
01:20:02,240 --> 01:20:05,160
Speaker 1: on every time you're in a spot. If you've got

1465
01:20:05,200 --> 01:20:07,280
Speaker 1: a point there, you've got a time stamp of when

1466
01:20:07,400 --> 01:20:11,240
Speaker 1: people were there. So unfortunately, for years I grew up

1467
01:20:11,360 --> 01:20:13,600
Speaker 1: hunting arrowheads. My grandpa took me out. That's sort of

1468
01:20:13,600 --> 01:20:16,560
Speaker 1: what got me fascinated with it. People have been collecting

1469
01:20:17,080 --> 01:20:21,720
Speaker 1: arrowheads in particular, which means they've been sort of erasing

1470
01:20:21,920 --> 01:20:25,800
Speaker 1: time from the surface archaeological record, because unless you know,

1471
01:20:25,880 --> 01:20:28,759
Speaker 1: like we talked about an individual bone in a site,

1472
01:20:28,760 --> 01:20:31,200
Speaker 1: knowing where it comes from as a puzzle piece, unless

1473
01:20:31,200 --> 01:20:33,400
Speaker 1: you know where each one of those points come from,

1474
01:20:33,479 --> 01:20:36,320
Speaker 1: it just has turned into a nice little piece of

1475
01:20:36,400 --> 01:20:39,880
Speaker 1: rock rather than being a piece of the puzzle. So, um, yeah,

1476
01:20:40,040 --> 01:20:43,599
Speaker 1: things have been picked over real severely. Uh, and it

1477
01:20:43,640 --> 01:20:46,800
Speaker 1: means it makes our job even harder as an archaeologist

1478
01:20:46,880 --> 01:20:51,680
Speaker 1: to try and understand human use of landscapes. Um. I

1479
01:20:52,000 --> 01:20:54,639
Speaker 1: was talking to you a little bit about the things

1480
01:20:54,680 --> 01:20:58,040
Speaker 1: that we find in remote areas away from where people

1481
01:20:58,040 --> 01:21:01,559
Speaker 1: get in the high elevations of wilderness area is and

1482
01:21:01,880 --> 01:21:05,840
Speaker 1: we do find points there. Uh. Most of what we

1483
01:21:05,880 --> 01:21:10,200
Speaker 1: find are the small flakes. I think I mentioned in

1484
01:21:10,200 --> 01:21:13,560
Speaker 1: the last um twenty years, we found close to a

1485
01:21:13,600 --> 01:21:15,920
Speaker 1: little over two hundred thousand artifacts. Most of them are

1486
01:21:15,960 --> 01:21:19,439
Speaker 1: the small flakes. And even in the remote areas, you know,

1487
01:21:19,520 --> 01:21:25,519
Speaker 1: twenty miles from a trailhead, back in the wilderness areas, um,

1488
01:21:25,560 --> 01:21:27,439
Speaker 1: we've been picking up Folks have been picking up the

1489
01:21:27,479 --> 01:21:30,400
Speaker 1: points for the last hundred to a hundred and fifty years.

1490
01:21:30,439 --> 01:21:36,639
Speaker 1: So even back there there um sparse and the record

1491
01:21:36,920 --> 01:21:42,040
Speaker 1: is terribly degraded, got quite a collection of points, and

1492
01:21:42,160 --> 01:21:44,960
Speaker 1: his strategy almost hesitates say what his strategy is. His

1493
01:21:45,040 --> 01:21:49,800
Speaker 1: strategy is high mountain passes. Uh huh, it's um we

1494
01:21:49,960 --> 01:21:51,960
Speaker 1: get remind me to get back to that here in

1495
01:21:51,960 --> 01:21:55,679
Speaker 1: a minute. Um. And I need to make this point.

1496
01:21:55,920 --> 01:21:59,760
Speaker 1: High mountain passes means they're on forest service property, which

1497
01:21:59,760 --> 01:22:03,280
Speaker 1: means he's probably got enough points to make it a

1498
01:22:03,320 --> 01:22:10,920
Speaker 1: real easy felony offense. At this point, it's it's you're

1499
01:22:11,000 --> 01:22:14,599
Speaker 1: asking a lot of somebody, which means no, let me.

1500
01:22:14,880 --> 01:22:18,080
Speaker 1: Let me go down the UK. I we do catch

1501
01:22:18,080 --> 01:22:21,160
Speaker 1: and release archaeology up there. We found these two thousand things,

1502
01:22:21,200 --> 01:22:24,320
Speaker 1: and damn you're all of them are there? Did you

1503
01:22:24,360 --> 01:22:26,880
Speaker 1: talk him in him on the surface. I'm not going

1504
01:22:26,920 --> 01:22:29,240
Speaker 1: to damage to the archaeological record by changing. Yeah, but

1505
01:22:29,240 --> 01:22:31,280
Speaker 1: then some other chimp's gonna find him. I I often

1506
01:22:31,320 --> 01:22:33,080
Speaker 1: get that down in the bar if you don't pick

1507
01:22:33,080 --> 01:22:35,040
Speaker 1: it up, some other s O B will and I say,

1508
01:22:36,120 --> 01:22:38,280
Speaker 1: my aspiration has never been one of those s O

1509
01:22:38,320 --> 01:22:46,040
Speaker 1: B s. It's we talked him all into the mass. Um.

1510
01:22:46,600 --> 01:22:48,720
Speaker 1: You jabbed it as close as where you found it.

1511
01:22:48,800 --> 01:22:51,520
Speaker 1: You just tucked it into the mall. We we um.

1512
01:22:51,640 --> 01:22:54,760
Speaker 1: We use high precision g N S S receivers. We

1513
01:22:54,800 --> 01:22:57,760
Speaker 1: have its location down to within ten centimeters, so if

1514
01:22:57,800 --> 01:23:00,080
Speaker 1: we tucked it in, we could come back and find it.

1515
01:23:01,080 --> 01:23:06,599
Speaker 1: But when I work with students, I see the archaeological record.

1516
01:23:06,680 --> 01:23:10,320
Speaker 1: One of my jobs is to leave it as much

1517
01:23:10,400 --> 01:23:13,040
Speaker 1: on changed by me as possible, so that they can

1518
01:23:13,080 --> 01:23:16,160
Speaker 1: come back later and demonstrate why that old s ob

1519
01:23:16,320 --> 01:23:19,479
Speaker 1: Todd was wrong in his interpretations. If I start pushing

1520
01:23:19,520 --> 01:23:22,599
Speaker 1: things down into the sod that far into a bone

1521
01:23:22,640 --> 01:23:24,920
Speaker 1: on accident, or if they come back and start excavating

1522
01:23:24,960 --> 01:23:27,960
Speaker 1: that site and the elevation of that point is five

1523
01:23:27,960 --> 01:23:30,840
Speaker 1: centimeters different than everything else on it, uh, they're going

1524
01:23:30,920 --> 01:23:33,840
Speaker 1: to say, well, these are two different occupations. Todd was wrong.

1525
01:23:33,960 --> 01:23:38,360
Speaker 1: That point isn't associate. So my I see archaeology as

1526
01:23:38,400 --> 01:23:41,320
Speaker 1: sort of like medicine. The first rule is do no harm,

1527
01:23:42,000 --> 01:23:44,720
Speaker 1: leave it as impact as possible. See an old lady

1528
01:23:44,800 --> 01:23:49,600
Speaker 1: drop her purse, drop her drop her driver's license or

1529
01:23:49,640 --> 01:23:52,519
Speaker 1: credit card, right whatever she drops, five bucks would be like, yeah,

1530
01:23:52,520 --> 01:23:55,200
Speaker 1: I'm gonna take that five bucks because now I wouldn't,

1531
01:23:55,479 --> 01:23:58,200
Speaker 1: but someone else would Yeah, exactly. And one of the

1532
01:23:58,200 --> 01:24:00,720
Speaker 1: things that I as I get older I had now

1533
01:24:00,760 --> 01:24:04,479
Speaker 1: have grandchildren, and I'm waiting for the day they're the

1534
01:24:04,479 --> 01:24:06,759
Speaker 1: oldest one is three now where I can start taking

1535
01:24:06,800 --> 01:24:09,679
Speaker 1: them back onto the landscape and showing them where these

1536
01:24:09,720 --> 01:24:13,080
Speaker 1: points are in their natural habitat. Not only does that

1537
01:24:13,120 --> 01:24:16,760
Speaker 1: make me super grandpa, but it connects the people that

1538
01:24:16,960 --> 01:24:19,480
Speaker 1: you know, get to find that point with that landscape

1539
01:24:19,479 --> 01:24:21,640
Speaker 1: in a different way. It's not just you know, this

1540
01:24:21,760 --> 01:24:25,120
Speaker 1: open hillside, it's that hillside where these where I found

1541
01:24:25,200 --> 01:24:28,800
Speaker 1: that point. So I think just that leaving him there

1542
01:24:29,760 --> 01:24:33,280
Speaker 1: has that opportunity to connect people with a landscape in

1543
01:24:33,280 --> 01:24:36,360
Speaker 1: a way they don't otherwise. Half let's step back from

1544
01:24:36,360 --> 01:24:39,200
Speaker 1: it further. Um. One of the reasons we don't see

1545
01:24:40,080 --> 01:24:42,720
Speaker 1: or that we don't envision wilderness areas is having a

1546
01:24:42,760 --> 01:24:46,280
Speaker 1: lot of archaeology. Is by time the fur trader fur

1547
01:24:46,320 --> 01:24:48,880
Speaker 1: trappers came into the mountains, a lot of the Native

1548
01:24:48,880 --> 01:24:51,839
Speaker 1: Americans have been living there, had been killed by disease,

1549
01:24:52,240 --> 01:24:54,520
Speaker 1: or they've been pulled out of the mountains to the

1550
01:24:54,560 --> 01:24:58,520
Speaker 1: trading post down in lower elevations. It was an underpopulated landscape,

1551
01:24:59,040 --> 01:25:02,240
Speaker 1: and so we've brought that that notion into the present

1552
01:25:02,320 --> 01:25:06,120
Speaker 1: of high mountain areas. The passes and they were depopulated,

1553
01:25:06,280 --> 01:25:08,320
Speaker 1: or you don't think of them like that historically, you

1554
01:25:08,320 --> 01:25:11,240
Speaker 1: think that people were up there hunting. Yeah, we see, um,

1555
01:25:11,360 --> 01:25:13,479
Speaker 1: we see, I get that idea. We'll be way up

1556
01:25:13,479 --> 01:25:15,000
Speaker 1: in the mountains, no wonder if they every woe have

1557
01:25:15,120 --> 01:25:16,920
Speaker 1: left the river valleys and even gone up in there.

1558
01:25:17,080 --> 01:25:21,120
Speaker 1: We see, Um, we've got tepee ring sites, habitation sites

1559
01:25:21,200 --> 01:25:25,519
Speaker 1: at over eleven thousand feet. We've got sites UM in

1560
01:25:25,560 --> 01:25:30,679
Speaker 1: the high elevation where we find um April to March

1561
01:25:31,560 --> 01:25:34,080
Speaker 1: Mountain sheep fetuses. They were up there in late winter.

1562
01:25:34,200 --> 01:25:38,320
Speaker 1: We find um sites where there's bison fetuses from near

1563
01:25:38,520 --> 01:25:41,320
Speaker 1: full term back to just beginning at high ele but

1564
01:25:41,400 --> 01:25:44,240
Speaker 1: they were there year round. And we see sites that

1565
01:25:44,280 --> 01:25:48,200
Speaker 1: are not Let me get back to my people were

1566
01:25:48,240 --> 01:25:51,519
Speaker 1: there much more than we think in the past. So

1567
01:25:52,040 --> 01:25:56,439
Speaker 1: getting back to the idea of wilderness depopulated, no people,

1568
01:25:57,600 --> 01:26:00,880
Speaker 1: we eradicated the people from there. And so if we're

1569
01:26:00,920 --> 01:26:04,080
Speaker 1: back into that same area picking up the artifacts the

1570
01:26:04,200 --> 01:26:08,320
Speaker 1: arrowheads that demonstrate their presence, we're taking that one step

1571
01:26:08,360 --> 01:26:11,960
Speaker 1: further by erasing their physical presence. And that just bothers

1572
01:26:12,000 --> 01:26:15,439
Speaker 1: me that I'm with you that approaches to Yeah, we've

1573
01:26:15,479 --> 01:26:18,920
Speaker 1: already killed vast numbers of them, and now we're going

1574
01:26:18,960 --> 01:26:23,520
Speaker 1: to erase their presence by removing those artifacts from that landscape.

1575
01:26:23,800 --> 01:26:26,760
Speaker 1: You know, I'm kinstantly trying to do self improvement, Like

1576
01:26:26,800 --> 01:26:30,000
Speaker 1: I'm really I'm exploring this idea right now of if

1577
01:26:30,080 --> 01:26:35,400
Speaker 1: you're hunting on a tag, like I'm sorry, if I

1578
01:26:35,439 --> 01:26:37,599
Speaker 1: was a perfect person and I did this once this year,

1579
01:26:37,920 --> 01:26:39,880
Speaker 1: If I was a perfect person, you're hunting on a

1580
01:26:39,960 --> 01:26:43,200
Speaker 1: hunting tag and you wound something and you feel that

1581
01:26:43,240 --> 01:26:46,960
Speaker 1: you wounded it mortally but didn't recovery, you would not

1582
01:26:47,120 --> 01:26:49,760
Speaker 1: you tag. Right. What I'm gonna try to do is

1583
01:26:49,800 --> 01:26:53,600
Speaker 1: like it would be very very difficult for me, but

1584
01:26:53,720 --> 01:26:58,040
Speaker 1: to see a point for a half a point and

1585
01:26:58,160 --> 01:27:00,920
Speaker 1: believe it that to be hard. One of the things

1586
01:27:00,920 --> 01:27:04,320
Speaker 1: we do is we take um latex molding material in

1587
01:27:04,439 --> 01:27:06,920
Speaker 1: that country with us. We find that perfect point, we

1588
01:27:06,960 --> 01:27:10,120
Speaker 1: may make a mold of it, catching release, catching release,

1589
01:27:10,160 --> 01:27:12,080
Speaker 1: you put the point back, you come back, and you

1590
01:27:12,120 --> 01:27:14,439
Speaker 1: can make a cast that mold. You've got that three

1591
01:27:14,439 --> 01:27:18,760
Speaker 1: dimensional memory right there. And I thought, um, wouldn't it

1592
01:27:18,800 --> 01:27:22,000
Speaker 1: be great if outfitters caught onto that that you could

1593
01:27:22,000 --> 01:27:23,920
Speaker 1: take people into the back country and rather than having

1594
01:27:23,920 --> 01:27:26,800
Speaker 1: that person collect that point once and take it back

1595
01:27:26,840 --> 01:27:28,720
Speaker 1: with him and give you a little tip. If every

1596
01:27:28,800 --> 01:27:31,320
Speaker 1: year we went back and a new hunter, you can say, well,

1597
01:27:31,400 --> 01:27:34,559
Speaker 1: let's look around here for some arrowheads. They find that arrowhead,

1598
01:27:34,640 --> 01:27:36,920
Speaker 1: you make a mold of it, and the arrowhead goes

1599
01:27:36,960 --> 01:27:38,720
Speaker 1: back in its place, and the hunter gets to go

1600
01:27:38,760 --> 01:27:41,800
Speaker 1: back home with his memory. It's another sort of you know,

1601
01:27:41,880 --> 01:27:44,479
Speaker 1: catching release, but of an economic value to the folks

1602
01:27:44,520 --> 01:27:47,760
Speaker 1: that do often encourage the picking him up. I don't

1603
01:27:47,760 --> 01:27:49,200
Speaker 1: want to I don't want you to think that I'm

1604
01:27:49,240 --> 01:27:52,040
Speaker 1: like ap plying you for trade secrets so that I

1605
01:27:52,040 --> 01:27:58,479
Speaker 1: can go and ransact of federal lance. But uh, as

1606
01:27:58,560 --> 01:28:03,000
Speaker 1: much as you're comfortable, like when you're scouting, just rolling

1607
01:28:03,000 --> 01:28:05,760
Speaker 1: through the mountains, scouting around, do you sort of have

1608
01:28:05,840 --> 01:28:07,760
Speaker 1: you developed a sense of like this would be a

1609
01:28:07,800 --> 01:28:09,280
Speaker 1: good place to look or do you have to treat

1610
01:28:09,320 --> 01:28:11,080
Speaker 1: everything equal because you didn't know what it used to

1611
01:28:11,120 --> 01:28:14,120
Speaker 1: be like? Or are you looking for you look like

1612
01:28:14,160 --> 01:28:16,160
Speaker 1: you see stone flakes, you kind of know your eye

1613
01:28:16,200 --> 01:28:18,800
Speaker 1: knows what to see for tent rings? Like how do

1614
01:28:18,840 --> 01:28:21,680
Speaker 1: you sort of navigate if you're if you're trying to

1615
01:28:21,760 --> 01:28:25,560
Speaker 1: look through it through human eyes? Right? From thousands of

1616
01:28:25,640 --> 01:28:28,479
Speaker 1: years ago, what are you imagining when you walk through

1617
01:28:28,479 --> 01:28:30,840
Speaker 1: the mountains? Let me give you and I'm gonna try

1618
01:28:30,840 --> 01:28:35,479
Speaker 1: and work through three answers to that. UM. A couple

1619
01:28:35,479 --> 01:28:38,479
Speaker 1: of years ago, I was down talking to some elders

1620
01:28:38,479 --> 01:28:41,760
Speaker 1: on the Shoshone reservation in Wyoming about this catch and

1621
01:28:41,760 --> 01:28:45,320
Speaker 1: release archaeology and they like that idea. And then I

1622
01:28:45,360 --> 01:28:48,840
Speaker 1: asked him another question, which was, you know, every time

1623
01:28:48,880 --> 01:28:50,920
Speaker 1: I'm in the mountains and I put my tent down,

1624
01:28:51,280 --> 01:28:53,439
Speaker 1: and I start looking around where my tent as I

1625
01:28:53,439 --> 01:28:59,040
Speaker 1: start finding flakes, and um, do you think or would

1626
01:28:59,120 --> 01:29:01,479
Speaker 1: you be more comfortable with my leaving my tent there?

1627
01:29:01,520 --> 01:29:04,080
Speaker 1: Or should I move it off your ancestral site? And

1628
01:29:04,120 --> 01:29:05,760
Speaker 1: the guy I was talking to you thought about it

1629
01:29:05,800 --> 01:29:09,000
Speaker 1: for a minute and he said, you know, if I

1630
01:29:09,040 --> 01:29:11,880
Speaker 1: didn't see those flakes, I'd move your damn tent because

1631
01:29:12,000 --> 01:29:16,679
Speaker 1: something's wrong with that place. So UM, sort of answer

1632
01:29:16,720 --> 01:29:19,160
Speaker 1: one is good places to camp in the past or

1633
01:29:19,200 --> 01:29:23,599
Speaker 1: good places to camp today, And so that's that's one.

1634
01:29:23,800 --> 01:29:27,400
Speaker 1: Second one is you sort of as you're spending more time,

1635
01:29:27,680 --> 01:29:30,639
Speaker 1: like with anything else, you start to get that innate

1636
01:29:30,720 --> 01:29:33,160
Speaker 1: feel for places that should have stuff. You know, it

1637
01:29:33,240 --> 01:29:35,280
Speaker 1: just has that ping to it the right sort of

1638
01:29:35,320 --> 01:29:39,040
Speaker 1: stuff and so rely on that a little. But again,

1639
01:29:39,080 --> 01:29:42,360
Speaker 1: since UM we always want to evaluate our ideas rather

1640
01:29:42,400 --> 01:29:44,880
Speaker 1: than just saying I know where stuff is. I've been

1641
01:29:44,880 --> 01:29:48,680
Speaker 1: working with UM several people who are sort of UH.

1642
01:29:49,160 --> 01:29:52,040
Speaker 1: One of my former students, Paul Burnett, is sort of

1643
01:29:52,080 --> 01:29:57,000
Speaker 1: a g I. S. Modeling whiz, and we've developed probability

1644
01:29:57,040 --> 01:29:59,760
Speaker 1: models based on where we've looked in the past, on

1645
01:30:00,320 --> 01:30:04,880
Speaker 1: where there's the greatest probability of finding things in present.

1646
01:30:05,120 --> 01:30:08,920
Speaker 1: We've got about ten variables of landscape dimensions that go

1647
01:30:09,000 --> 01:30:13,519
Speaker 1: into this linear probability model and gives a probability model

1648
01:30:13,560 --> 01:30:17,040
Speaker 1: for every ten by ten mem area across the forest

1649
01:30:17,400 --> 01:30:21,040
Speaker 1: of from zero to off you're going to find something? There?

1650
01:30:21,160 --> 01:30:27,280
Speaker 1: Is there something no we're at it's well like to

1651
01:30:27,320 --> 01:30:29,679
Speaker 1: give you an example of and we've reworked this model

1652
01:30:29,800 --> 01:30:33,000
Speaker 1: a couple of times. UM. One of the variables when

1653
01:30:33,040 --> 01:30:35,559
Speaker 1: we first hit the model of where we didn't find

1654
01:30:35,560 --> 01:30:39,320
Speaker 1: things was in heavily timbered areas. So heavily timbered areas

1655
01:30:39,640 --> 01:30:42,639
Speaker 1: UM low probability of finding stuff. And then we started

1656
01:30:42,680 --> 01:30:45,840
Speaker 1: doing post fire archaeology and you know it's not a

1657
01:30:45,880 --> 01:30:48,439
Speaker 1: big gee whiz. MR Science one of the reasons that

1658
01:30:48,600 --> 01:30:50,639
Speaker 1: you don't see things in areas where there's that much

1659
01:30:50,720 --> 01:30:54,840
Speaker 1: duff under the trees is you can't see the damn ground. Um.

1660
01:30:55,000 --> 01:31:00,400
Speaker 1: So we start doing work after fires and UM we

1661
01:31:00,439 --> 01:31:02,360
Speaker 1: start saying stuff there, so you throw the tree cover

1662
01:31:02,479 --> 01:31:05,439
Speaker 1: out of your model. UM, And we keep revising the

1663
01:31:05,479 --> 01:31:08,439
Speaker 1: model and we go out every year and work with it. Yeah.

1664
01:31:08,520 --> 01:31:11,040
Speaker 1: When I was, when I was spent that ten days

1665
01:31:11,120 --> 01:31:13,640
Speaker 1: hunting narrowheads with guys that are really good, like anthropologists

1666
01:31:13,640 --> 01:31:17,400
Speaker 1: on the north slope. Um. The first thing was open ground,

1667
01:31:19,000 --> 01:31:21,200
Speaker 1: it's if it's if it's moss, don't waste your time.

1668
01:31:21,680 --> 01:31:23,280
Speaker 1: And the second thing was that they liked is like

1669
01:31:23,800 --> 01:31:26,439
Speaker 1: great place of the camp. And they found that in

1670
01:31:26,479 --> 01:31:31,280
Speaker 1: that country. Um, confluences of rivers and they make that

1671
01:31:31,360 --> 01:31:34,120
Speaker 1: sort of v, that v of land where they come

1672
01:31:34,160 --> 01:31:37,720
Speaker 1: together and you'd find like flat benches on a nice

1673
01:31:37,720 --> 01:31:41,880
Speaker 1: little rise above those confluences, good visibility that you're out.

1674
01:31:41,920 --> 01:31:43,799
Speaker 1: You're camped on that bench, you can see the valleys

1675
01:31:43,840 --> 01:31:47,080
Speaker 1: around you, pretty flat ground, access to water, and they

1676
01:31:47,320 --> 01:31:50,160
Speaker 1: love those spots. Well, yeah, you've let that cat out

1677
01:31:50,160 --> 01:31:53,559
Speaker 1: of the bag. Yes, Confluences is one of the ten

1678
01:31:53,680 --> 01:31:57,720
Speaker 1: variables we look at still today though. Man, oh yeah

1679
01:31:57,880 --> 01:32:02,200
Speaker 1: when you're floating down the rivers great place. Yeah yeah, Uh,

1680
01:32:02,320 --> 01:32:04,519
Speaker 1: you're retired, but you still work. So what what makes

1681
01:32:04,560 --> 01:32:11,040
Speaker 1: being retired? Like how to find retired? No, no pesky paycheck? Um,

1682
01:32:11,280 --> 01:32:15,679
Speaker 1: that's retirement, Yeah, I I say, And it's sort of joking,

1683
01:32:15,680 --> 01:32:18,840
Speaker 1: but it's sort of true. Is I no longer have

1684
01:32:19,000 --> 01:32:22,480
Speaker 1: that damn job getting in the way of my work? Um?

1685
01:32:22,520 --> 01:32:28,040
Speaker 1: So I spend Yeah, and being a university faculty member

1686
01:32:28,400 --> 01:32:33,240
Speaker 1: means administrative stuff and you know, endless things that are

1687
01:32:33,880 --> 01:32:37,360
Speaker 1: draining your time. Uh. And what drainer doesn't drain your

1688
01:32:37,360 --> 01:32:41,000
Speaker 1: time is in a university professors, interactional students. I really

1689
01:32:41,000 --> 01:32:44,320
Speaker 1: missed that. Um. But just all the other sort of

1690
01:32:44,360 --> 01:32:46,519
Speaker 1: things have build up. So since I've retired and what

1691
01:32:46,680 --> 01:32:51,240
Speaker 1: university did you retire from? Colorado State and Fort Collins. Um.

1692
01:32:51,280 --> 01:32:54,920
Speaker 1: Since I've retired, I've spent two to three months most

1693
01:32:54,960 --> 01:32:58,080
Speaker 1: winners working on the projects in Ethiopia like I'm talking

1694
01:32:58,120 --> 01:33:00,840
Speaker 1: about talked about. Then that's what we do in our

1695
01:33:00,880 --> 01:33:04,200
Speaker 1: winter and that's their dry season and in the summer

1696
01:33:04,640 --> 01:33:09,520
Speaker 1: I've been focusing on and again this is when I retired.

1697
01:33:10,600 --> 01:33:13,320
Speaker 1: I wanted to get away from the data intensive things

1698
01:33:13,400 --> 01:33:16,240
Speaker 1: like bison bone bit. I wanted to retire, and I thought,

1699
01:33:16,920 --> 01:33:18,840
Speaker 1: what I'd really like to do in retirement is go

1700
01:33:18,960 --> 01:33:22,360
Speaker 1: backpacking in the mountains, and so I decided to start

1701
01:33:22,400 --> 01:33:25,400
Speaker 1: focusing on high elevation archaeology with this notion in the

1702
01:33:25,400 --> 01:33:27,439
Speaker 1: back of my head that I'm not going to find

1703
01:33:27,520 --> 01:33:31,280
Speaker 1: much and therefore I can still be doing archaeology, but

1704
01:33:31,320 --> 01:33:33,320
Speaker 1: I won't have those huge data sets to deal with.

1705
01:33:34,240 --> 01:33:36,479
Speaker 1: The first year, I went up there with students, UM,

1706
01:33:36,720 --> 01:33:40,879
Speaker 1: we were gonna survey twenty miles along the Forest Service

1707
01:33:41,000 --> 01:33:44,479
Speaker 1: Trail quarter UM in a ten day period, and I thought, boy,

1708
01:33:44,520 --> 01:33:46,720
Speaker 1: we can do that easy. We made it a mile

1709
01:33:46,840 --> 01:33:51,479
Speaker 1: and a half and recorded six thousand artifacts, and I thought,

1710
01:33:52,479 --> 01:33:54,839
Speaker 1: this isn't this We hit We had the hot spot

1711
01:33:55,680 --> 01:33:59,479
Speaker 1: and that's gone on and on and on and on,

1712
01:34:00,000 --> 01:34:03,000
Speaker 1: and right now are cumulative data set is over two

1713
01:34:03,200 --> 01:34:07,000
Speaker 1: d thousand artifacts. So I'm again back in this huge data,

1714
01:34:07,240 --> 01:34:11,479
Speaker 1: big data, lots of attributes. Um, oh my god, did

1715
01:34:11,520 --> 01:34:14,040
Speaker 1: I get that wrong sort of thing. But it's it's

1716
01:34:14,080 --> 01:34:17,360
Speaker 1: exciting because the areas where we're working in the wilderness

1717
01:34:17,400 --> 01:34:21,080
Speaker 1: areas in the Greater Yellowstone Ecosystem are one of those

1718
01:34:21,120 --> 01:34:24,640
Speaker 1: blank spots on the archaeological map of knowledge. So not

1719
01:34:24,680 --> 01:34:27,639
Speaker 1: only do I get to embrace that ignorance again, here's

1720
01:34:27,640 --> 01:34:30,240
Speaker 1: something we don't know about, and so every time we

1721
01:34:30,280 --> 01:34:33,680
Speaker 1: go out, we're finding new and interesting things. And one

1722
01:34:33,680 --> 01:34:36,280
Speaker 1: of the projects I'm working on now as sort of

1723
01:34:36,400 --> 01:34:39,040
Speaker 1: to dovetail with that, is I've been working with some

1724
01:34:39,080 --> 01:34:42,479
Speaker 1: of the people who have been doing the migration studies

1725
01:34:43,000 --> 01:34:46,599
Speaker 1: of GPS coloring animals and following them and looking at

1726
01:34:46,600 --> 01:34:50,160
Speaker 1: how they move across the landscape, and we've been beginning

1727
01:34:50,200 --> 01:34:54,559
Speaker 1: to collaborate on whether those quarters that the game animals

1728
01:34:54,560 --> 01:34:57,360
Speaker 1: are using may well have been quarters that people would

1729
01:34:57,360 --> 01:35:01,200
Speaker 1: have used. So not only have I um failed in

1730
01:35:01,320 --> 01:35:05,600
Speaker 1: retirement in getting something that is a lot more complex

1731
01:35:05,600 --> 01:35:08,240
Speaker 1: than I thought, but you keep realizing that you can't

1732
01:35:08,280 --> 01:35:10,559
Speaker 1: just do the archaeology to understand it. You need to

1733
01:35:10,560 --> 01:35:13,759
Speaker 1: start worrying about the biology of all the other credits

1734
01:35:13,960 --> 01:35:17,000
Speaker 1: that are using those landscape simultaneously. I like that you're

1735
01:35:17,000 --> 01:35:19,120
Speaker 1: filling in the map like that, because I feel like

1736
01:35:19,160 --> 01:35:22,680
Speaker 1: that that would wind up being helpful when people want

1737
01:35:22,720 --> 01:35:25,680
Speaker 1: to develop pristine ecosystems, that you could talk about how

1738
01:35:25,720 --> 01:35:28,600
Speaker 1: there's a lot of cultural sites there. I know, you

1739
01:35:28,600 --> 01:35:31,040
Speaker 1: probably can't say like, oh yeah, but like from my

1740
01:35:31,160 --> 01:35:34,080
Speaker 1: respect of you could weaponize that stuff and use it

1741
01:35:34,080 --> 01:35:37,519
Speaker 1: to protect wilderness. It well, it has that's a double

1742
01:35:37,640 --> 01:35:42,600
Speaker 1: edged sword. Even that some people who are anti wilderness

1743
01:35:42,960 --> 01:35:45,559
Speaker 1: will make the argument, well, if you're saying that people

1744
01:35:45,560 --> 01:35:49,360
Speaker 1: have been there forever, why should we keep people out today.

1745
01:35:49,439 --> 01:35:52,400
Speaker 1: So you've got to watch how you make that just

1746
01:35:52,439 --> 01:35:58,919
Speaker 1: because there's the other there's a real difference between weaponiss

1747
01:35:59,280 --> 01:36:02,320
Speaker 1: between protect So people were all over here all the time,

1748
01:36:02,400 --> 01:36:07,760
Speaker 1: and you're saying they were a major component of the environment. Okay,

1749
01:36:07,880 --> 01:36:10,320
Speaker 1: let's put the road in there and get the ski area,

1750
01:36:10,479 --> 01:36:13,400
Speaker 1: let's get everybody back up in there. Yeah, let's yeah.

1751
01:36:13,439 --> 01:36:16,000
Speaker 1: It's like, um, we're talking about mammoths and all the

1752
01:36:16,000 --> 01:36:18,759
Speaker 1: people that want to do the DNA and recreate mammoth.

1753
01:36:18,880 --> 01:36:21,000
Speaker 1: You know, you could make that same argument and folks

1754
01:36:21,120 --> 01:36:25,120
Speaker 1: might say, well, let's read people the wilderness. Yeah, and

1755
01:36:25,520 --> 01:36:30,960
Speaker 1: I'm not all out Well, you've got to, um, that's

1756
01:36:31,000 --> 01:36:33,160
Speaker 1: one of those arguments that it's going to be there

1757
01:36:33,520 --> 01:36:36,559
Speaker 1: anytime you start talking about finding archaeology in the wilders.

1758
01:36:36,560 --> 01:36:39,400
Speaker 1: And I've had people say that to me seriously as well,

1759
01:36:39,640 --> 01:36:43,479
Speaker 1: then why do we have wilderness. It's it's not that

1760
01:36:43,560 --> 01:36:45,120
Speaker 1: the concept I got to think about it for a

1761
01:36:45,120 --> 01:36:48,160
Speaker 1: minute'll come up with. It's just it's the law was

1762
01:36:48,240 --> 01:36:51,599
Speaker 1: poorly written when it says worried man is only a visitor.

1763
01:36:52,120 --> 01:36:54,280
Speaker 1: It might, you know, we might just reword the lot

1764
01:36:54,400 --> 01:36:57,400
Speaker 1: where um contemporary use of it is only transient or

1765
01:36:57,479 --> 01:37:01,360
Speaker 1: something like that. Yeah, I got you, Yeah, anybody got

1766
01:37:03,640 --> 01:37:07,040
Speaker 1: It's been great. It's a lot to take in. Um,

1767
01:37:07,479 --> 01:37:09,240
Speaker 1: we should ask Phil if he's got anything he wants

1768
01:37:09,240 --> 01:37:11,000
Speaker 1: to say to Sure, we can do that, and throw

1769
01:37:11,080 --> 01:37:12,840
Speaker 1: to Phil af you do years, or Phil going in

1770
01:37:12,920 --> 01:37:16,920
Speaker 1: you can do years. I don't have a whole lot.

1771
01:37:16,960 --> 01:37:19,000
Speaker 1: I just, um, you steal a lot of arrowheads, fill

1772
01:37:19,080 --> 01:37:22,559
Speaker 1: off the federal d never found one, never looked, never

1773
01:37:22,600 --> 01:37:26,080
Speaker 1: looked though, So you have some hot tips today. I'm

1774
01:37:26,120 --> 01:37:28,360
Speaker 1: going to use it to abuse the law, not at all,

1775
01:37:28,800 --> 01:37:30,880
Speaker 1: at least I won't say well in front of Larry,

1776
01:37:31,120 --> 01:37:32,880
Speaker 1: But it would be really bad if you did. Yeah.

1777
01:37:33,000 --> 01:37:35,519
Speaker 1: I find a lot of discomfort and uncertainty, and I

1778
01:37:35,520 --> 01:37:38,320
Speaker 1: guess I could. Uh, and so I that's a foolish

1779
01:37:38,320 --> 01:37:41,320
Speaker 1: way to live. I understand that. But I I love

1780
01:37:41,360 --> 01:37:44,120
Speaker 1: talking or listening to people like you. Who seem to

1781
01:37:44,160 --> 01:37:49,439
Speaker 1: relish in it. Um. I you know, I'm sort of

1782
01:37:49,439 --> 01:37:53,000
Speaker 1: one of those almost O C D organizing things when

1783
01:37:53,040 --> 01:37:55,000
Speaker 1: we go into the back country. For example, I've got

1784
01:37:55,000 --> 01:38:00,080
Speaker 1: a spreadsheet, UM that tells people their calorie out it

1785
01:38:00,200 --> 01:38:03,120
Speaker 1: per day for the entire time for my food shopping list.

1786
01:38:03,200 --> 01:38:07,519
Speaker 1: You know, I'm I don't like uncertainty, but unfortunately that's

1787
01:38:07,560 --> 01:38:09,800
Speaker 1: the way the world is. And unless you want to

1788
01:38:09,840 --> 01:38:13,680
Speaker 1: live in a delusional world, UM, you've sort of got

1789
01:38:13,680 --> 01:38:16,920
Speaker 1: to embrace it. So the things that you can I

1790
01:38:16,960 --> 01:38:19,519
Speaker 1: can control how many calories I take into the mountains

1791
01:38:19,560 --> 01:38:22,200
Speaker 1: for twenty three days. I can't control what happened in

1792
01:38:22,200 --> 01:38:25,280
Speaker 1: the past, and I uncomfortable with that. You deal with

1793
01:38:25,320 --> 01:38:27,840
Speaker 1: the things that you you can put in some little

1794
01:38:27,880 --> 01:38:33,559
Speaker 1: boxes and archaeology. One of the reasons I really love

1795
01:38:33,600 --> 01:38:36,840
Speaker 1: it is because of that uncertainty. UM, I would hate

1796
01:38:36,840 --> 01:38:40,160
Speaker 1: it to be in a field or a job. When

1797
01:38:40,160 --> 01:38:42,760
Speaker 1: you retired, you say, well, I know everything I need

1798
01:38:42,840 --> 01:38:45,400
Speaker 1: to know about this. I can just go fishing for

1799
01:38:45,439 --> 01:38:47,360
Speaker 1: the rest. Not to say fishing is a bad thing,

1800
01:38:47,360 --> 01:38:49,960
Speaker 1: but you can just play golf. I think you want

1801
01:38:49,960 --> 01:38:53,240
Speaker 1: to talk about something you can never figure out? Fishing, Yeah,

1802
01:38:54,040 --> 01:38:57,759
Speaker 1: it's the same thing. If you're an avid fisher person,

1803
01:38:58,120 --> 01:39:04,400
Speaker 1: you're gonna be working for that forever and you don't

1804
01:39:04,400 --> 01:39:06,240
Speaker 1: know if you if you do it right, it's always

1805
01:39:06,280 --> 01:39:08,800
Speaker 1: slapping in the face with what you don't know. Wake

1806
01:39:08,920 --> 01:39:11,439
Speaker 1: up and pay better attention and think about it this way.

1807
01:39:11,720 --> 01:39:14,720
Speaker 1: And so to me it makes me feel more like

1808
01:39:14,760 --> 01:39:17,200
Speaker 1: a kid all the time because you're always sort of curious.

1809
01:39:17,360 --> 01:39:21,240
Speaker 1: You're asking why, why, why, like kids always do um,

1810
01:39:21,360 --> 01:39:23,439
Speaker 1: rather than saying, I've got the answers. You know who

1811
01:39:23,439 --> 01:39:25,479
Speaker 1: didn't cope with that? Well, uh, not that you would

1812
01:39:25,520 --> 01:39:28,320
Speaker 1: know him. My father didn't cope with that. Well, my father,

1813
01:39:28,600 --> 01:39:33,599
Speaker 1: uh didn't. He never you know, he didn't finish high

1814
01:39:33,600 --> 01:39:36,240
Speaker 1: He didn't like formally finished high school. Right, but um,

1815
01:39:36,400 --> 01:39:41,200
Speaker 1: he never fell in love with the h the journey

1816
01:39:41,240 --> 01:39:48,320
Speaker 1: of knowledge, and would be dismissive of entire fields of

1817
01:39:48,360 --> 01:39:51,519
Speaker 1: inquiry because they were always, as he put it, changing

1818
01:39:51,560 --> 01:39:55,679
Speaker 1: their story. He didn't like it, so be that instead

1819
01:39:55,680 --> 01:39:57,720
Speaker 1: of saying it would be really interesting to understand, like

1820
01:39:57,760 --> 01:40:01,400
Speaker 1: why mammoths when extincton guy floats an idea and people like, oh,

1821
01:40:01,400 --> 01:40:03,320
Speaker 1: that's a great idea, and then later someone pokes and

1822
01:40:03,400 --> 01:40:07,160
Speaker 1: holes in it. It wouldn't be that he remained interested.

1823
01:40:07,640 --> 01:40:11,680
Speaker 1: He would be they don't you know, they must they

1824
01:40:11,680 --> 01:40:13,280
Speaker 1: don't know what they're talking about. And he would get

1825
01:40:13,360 --> 01:40:18,679
Speaker 1: like angry about it and condemned the whole question because

1826
01:40:18,680 --> 01:40:21,840
Speaker 1: they were changing their story again, So you can imagine

1827
01:40:21,880 --> 01:40:25,200
Speaker 1: how you feel about like I think, like the African diaspora, right,

1828
01:40:25,760 --> 01:40:27,200
Speaker 1: that changes all the time. And he would just get

1829
01:40:27,240 --> 01:40:28,880
Speaker 1: where he didn't want to hear about it. It was

1830
01:40:28,920 --> 01:40:32,599
Speaker 1: all hogwash. It can't be right if they're if additional

1831
01:40:32,640 --> 01:40:35,080
Speaker 1: black and white? Yeah, which is he wanted to know

1832
01:40:35,120 --> 01:40:39,000
Speaker 1: the damn answer now. If not, they're all stupid. No

1833
01:40:39,040 --> 01:40:41,160
Speaker 1: one should even wonder about it sort of. Um, My

1834
01:40:41,280 --> 01:40:43,680
Speaker 1: dad was a lot the same way. You know, he

1835
01:40:43,720 --> 01:40:47,680
Speaker 1: never finished high school. He was a rancher, he you know, uh,

1836
01:40:47,720 --> 01:40:50,120
Speaker 1: And he was real skeptical when I started talking about

1837
01:40:50,160 --> 01:40:52,160
Speaker 1: going into this archaeology stuff. But first of all, why

1838
01:40:52,160 --> 01:40:55,040
Speaker 1: don't you get a real job? Um? And secondly, year

1839
01:40:55,080 --> 01:40:56,599
Speaker 1: you can ever get paid to do it? And then

1840
01:40:56,840 --> 01:40:59,320
Speaker 1: I got the university jobs and I started getting paid,

1841
01:40:59,360 --> 01:41:01,200
Speaker 1: and I started, you know, being an African and being

1842
01:41:01,200 --> 01:41:05,040
Speaker 1: in France and extricating these bison sites. And he put

1843
01:41:05,120 --> 01:41:07,519
Speaker 1: up with it because it brought the money in, and

1844
01:41:07,600 --> 01:41:11,360
Speaker 1: it wasn't until that legitimized it. That legitimized it. But

1845
01:41:11,439 --> 01:41:15,040
Speaker 1: it wasn't till he was almost gone. And I went

1846
01:41:15,080 --> 01:41:19,120
Speaker 1: in to talk to him the night before he died,

1847
01:41:20,160 --> 01:41:21,800
Speaker 1: and I was telling him about how it was going

1848
01:41:21,840 --> 01:41:23,720
Speaker 1: to shift careers and go into the mountains and try

1849
01:41:23,720 --> 01:41:25,800
Speaker 1: and understand what was going on there and trying to

1850
01:41:25,840 --> 01:41:28,920
Speaker 1: see how the people in the game animals interacted and

1851
01:41:29,000 --> 01:41:31,439
Speaker 1: get up there and start looking for nobody had never looked.

1852
01:41:31,560 --> 01:41:33,760
Speaker 1: And he pulled off his oxygen masks and he said,

1853
01:41:34,080 --> 01:41:37,960
Speaker 1: it sounds like you're finally doing something worthwhile. So, you know,

1854
01:41:38,040 --> 01:41:40,120
Speaker 1: talk about another spur to to get out of the

1855
01:41:40,120 --> 01:41:42,880
Speaker 1: academic and get into that. You know that I finally

1856
01:41:42,920 --> 01:41:47,200
Speaker 1: got that. I got that stand got his piqued his curiosity.

1857
01:41:47,320 --> 01:41:49,679
Speaker 1: It didn't matter, you know that I was academic full

1858
01:41:49,680 --> 01:41:53,840
Speaker 1: professor at university. That was just you're finally, you're finally

1859
01:41:53,840 --> 01:41:57,000
Speaker 1: doing something that matters. What have you learned. It's been

1860
01:41:57,120 --> 01:42:01,760
Speaker 1: interesting in this post in retirement of like these mountain landscapes.

1861
01:42:01,840 --> 01:42:08,439
Speaker 1: These I just think how complex and how intensively they've

1862
01:42:08,439 --> 01:42:11,840
Speaker 1: been used, and that we've you know, we we for

1863
01:42:11,960 --> 01:42:14,640
Speaker 1: years the archaeologists have specialized in the areas where we

1864
01:42:14,640 --> 01:42:17,559
Speaker 1: can get to. It's like that we've specialized on bone

1865
01:42:17,560 --> 01:42:20,320
Speaker 1: beds because they're easy to see. We specialized in planes

1866
01:42:20,360 --> 01:42:22,400
Speaker 1: areas where you can drive a four wheel drive too.

1867
01:42:23,160 --> 01:42:26,479
Speaker 1: And there's this whole other world that we know almost

1868
01:42:26,560 --> 01:42:30,760
Speaker 1: nothing about. So when I was a kid, I wanted

1869
01:42:30,800 --> 01:42:33,639
Speaker 1: to be there an archaeologist or an astronaut. So this

1870
01:42:33,680 --> 01:42:36,320
Speaker 1: is sort of combining both of those because I'm in

1871
01:42:36,360 --> 01:42:41,920
Speaker 1: a new world doing archaeology and everything we find there's wow, Um,

1872
01:42:42,000 --> 01:42:45,479
Speaker 1: you know teep hearing stone circles at eleven thousand feet

1873
01:42:45,840 --> 01:42:48,800
Speaker 1: that have habitation to what are they doing up here?

1874
01:42:48,840 --> 01:42:52,240
Speaker 1: I you need you know, one of those thousand dollar

1875
01:42:52,800 --> 01:42:56,320
Speaker 1: Swedish tents. Plot told it in place. But they're up

1876
01:42:56,320 --> 01:42:59,000
Speaker 1: there in the high winds, they're doing things that So

1877
01:43:00,040 --> 01:43:04,040
Speaker 1: I think just that, oh my god, what's there's this

1878
01:43:04,080 --> 01:43:07,200
Speaker 1: world that I never knew existed is probably the most

1879
01:43:07,240 --> 01:43:10,479
Speaker 1: exciting thing I've ever seen. It's it's what keeps you,

1880
01:43:11,200 --> 01:43:14,599
Speaker 1: keeps you going. I wish I'd retired thirty years ago

1881
01:43:14,840 --> 01:43:18,080
Speaker 1: where I had better energy, better energy to be up there,

1882
01:43:18,439 --> 01:43:21,040
Speaker 1: like I said earlier, up for twenty three days, this summer,

1883
01:43:21,479 --> 01:43:23,519
Speaker 1: and after about ten days, I got this message on

1884
01:43:23,640 --> 01:43:26,320
Speaker 1: our in reach from our outfitter that said, do you

1885
01:43:26,400 --> 01:43:28,760
Speaker 1: need anything? And I think he thought we'd ask for

1886
01:43:28,800 --> 01:43:31,400
Speaker 1: a bottle of whiskey or some beef steaks or something

1887
01:43:31,439 --> 01:43:33,720
Speaker 1: like that, and I said, yeah, we're about how to

1888
01:43:33,800 --> 01:43:37,679
Speaker 1: ib profit to the age where you know, that becomes

1889
01:43:37,680 --> 01:43:40,519
Speaker 1: a real serious thing. So I wish I could have

1890
01:43:40,520 --> 01:43:44,320
Speaker 1: started into these unknown landscapes earlier. You know, it's funny, man,

1891
01:43:44,360 --> 01:43:47,720
Speaker 1: we're um My brother and I were up in the

1892
01:43:48,200 --> 01:43:51,240
Speaker 1: kind of like in the cell Alpine zone in some

1893
01:43:51,400 --> 01:43:53,960
Speaker 1: of the similar area of what you've been talking about

1894
01:43:54,600 --> 01:43:58,439
Speaker 1: and this, and had this conversation this September where we

1895
01:43:58,560 --> 01:44:04,240
Speaker 1: found a very improvable bowl little beaver. Damn. I was like, man, like,

1896
01:44:04,280 --> 01:44:05,640
Speaker 1: what the hell's that thing doing up here? And that

1897
01:44:05,760 --> 01:44:09,439
Speaker 1: led us to talking about during the mountain man era,

1898
01:44:10,640 --> 01:44:12,679
Speaker 1: like where are those guys whatever, like found this beaver

1899
01:44:13,320 --> 01:44:15,360
Speaker 1: when we were just scouring this place out And then

1900
01:44:15,360 --> 01:44:19,040
Speaker 1: that guy us talking about if you sat overlooking this

1901
01:44:19,160 --> 01:44:22,679
Speaker 1: meadow we were on, I was like, how many years

1902
01:44:22,760 --> 01:44:24,920
Speaker 1: would you had to sit here before someone strolled through?

1903
01:44:24,960 --> 01:44:27,200
Speaker 1: If you were here two thousand years ago, three thousand

1904
01:44:27,280 --> 01:44:30,080
Speaker 1: years ago, and we were like, as we're talking about this,

1905
01:44:30,160 --> 01:44:32,400
Speaker 1: we imagine like it must have been you could have

1906
01:44:32,439 --> 01:44:34,519
Speaker 1: sat here ten years and no one would have come by.

1907
01:44:34,760 --> 01:44:36,840
Speaker 1: I think, actually, but then maybe it's like maybe like

1908
01:44:36,880 --> 01:44:38,680
Speaker 1: you're saying, like you've been seeing someone every month come

1909
01:44:38,720 --> 01:44:44,320
Speaker 1: through there. I relish the isolation of being in the welders,

1910
01:44:44,400 --> 01:44:47,200
Speaker 1: not saying people. And one of the reasons I've quit

1911
01:44:47,360 --> 01:44:50,679
Speaker 1: hunting as much is by the time hunting season rolls around,

1912
01:44:50,760 --> 01:44:54,320
Speaker 1: my empty welderness starts to become repopulated. But I'll bet

1913
01:44:54,439 --> 01:44:56,960
Speaker 1: you that in the past, and what we're saying from

1914
01:44:56,960 --> 01:45:00,599
Speaker 1: the archaeological record is that the year round own number

1915
01:45:00,640 --> 01:45:03,040
Speaker 1: of people there was much higher than today. So rather

1916
01:45:03,080 --> 01:45:05,479
Speaker 1: than thinking of it at two thousand years ago, how

1917
01:45:05,520 --> 01:45:08,799
Speaker 1: long would you have had to set here until somebody

1918
01:45:08,840 --> 01:45:11,519
Speaker 1: walked by? It probably should be flipped on its head

1919
01:45:11,560 --> 01:45:14,280
Speaker 1: and said, how long would I be setting here before

1920
01:45:14,360 --> 01:45:17,240
Speaker 1: some other s ob came by and spooked the game? Yeah?

1921
01:45:18,200 --> 01:45:21,920
Speaker 1: Let me ask you. One of the things that I

1922
01:45:22,000 --> 01:45:25,360
Speaker 1: really get fascinated by, or what attracts me to the

1923
01:45:25,360 --> 01:45:28,240
Speaker 1: mountains is I've always got to get over that next

1924
01:45:28,240 --> 01:45:30,680
Speaker 1: pass or look at that next drainage, you know, it

1925
01:45:30,760 --> 01:45:33,960
Speaker 1: just especially get older, I go, God, will I ever

1926
01:45:34,000 --> 01:45:36,800
Speaker 1: get over that pass into that drainage? And we talked

1927
01:45:36,800 --> 01:45:40,000
Speaker 1: about people moving into areas and that curiosity has got

1928
01:45:40,000 --> 01:45:41,680
Speaker 1: to be part of it. You know, you want to

1929
01:45:41,720 --> 01:45:44,320
Speaker 1: tie the country together of what's over here and what's

1930
01:45:44,320 --> 01:45:47,519
Speaker 1: over there, And yeah, I got that problem real bad.

1931
01:45:48,800 --> 01:45:50,400
Speaker 1: There's a spot that's bugging the hell out of me

1932
01:45:50,479 --> 01:45:52,439
Speaker 1: up in Alaska or we always get up and look

1933
01:45:52,439 --> 01:45:55,040
Speaker 1: and you it's like we're in kind of this alpine

1934
01:45:55,040 --> 01:45:58,519
Speaker 1: area is real beautiful and there's this deep trough of

1935
01:45:58,600 --> 01:46:02,200
Speaker 1: like nasty looking timber. But then yeah, there's another one

1936
01:46:02,280 --> 01:46:03,720
Speaker 1: popping up and it's like there's no way to get

1937
01:46:03,720 --> 01:46:05,559
Speaker 1: in there. Like that's got to be the coolest place

1938
01:46:05,560 --> 01:46:07,439
Speaker 1: in the world, you know what that was? Like, No

1939
01:46:07,439 --> 01:46:14,640
Speaker 1: one's probably for three hundred years exactly at all in

1940
01:46:14,680 --> 01:46:18,880
Speaker 1: that camp that was recently discovered above Gunnison. That's a

1941
01:46:18,920 --> 01:46:22,160
Speaker 1: cool spot, the one up on the Folsom sites up there.

1942
01:46:22,280 --> 01:46:24,720
Speaker 1: You know, I just read about it, and they're doing

1943
01:46:24,720 --> 01:46:27,160
Speaker 1: some you know, fun stuff ten thousand feet above sea

1944
01:46:27,240 --> 01:46:31,280
Speaker 1: level winter camps or even and I'm pretty substantial structures Again,

1945
01:46:31,280 --> 01:46:34,200
Speaker 1: that's when those badass houses paved with rocks, and so

1946
01:46:34,400 --> 01:46:38,040
Speaker 1: we tend to think of we We've talked about biases

1947
01:46:38,160 --> 01:46:41,160
Speaker 1: like um, only humans great patterns, and another bias that

1948
01:46:41,200 --> 01:46:43,960
Speaker 1: feeds into things like that is the older something is

1949
01:46:44,640 --> 01:46:48,080
Speaker 1: the least sophisticated, the poorly more poorly made it is.

1950
01:46:48,360 --> 01:46:50,680
Speaker 1: And you know, we've got time and time again when

1951
01:46:50,680 --> 01:46:53,360
Speaker 1: you look at the archaeological record of North America, in

1952
01:46:53,400 --> 01:46:56,640
Speaker 1: many ways, the older stuff is often the most finely crafted,

1953
01:46:56,680 --> 01:47:00,160
Speaker 1: the most sort of the best product, and if you

1954
01:47:00,160 --> 01:47:02,680
Speaker 1: get more recent, it turns into the so that that

1955
01:47:02,760 --> 01:47:07,519
Speaker 1: notion that we have that old is crappy, UM modern

1956
01:47:07,720 --> 01:47:11,960
Speaker 1: is better, whether it's housing structures or um stone tool,

1957
01:47:12,000 --> 01:47:16,360
Speaker 1: projective point technology just doesn't hold. And I love getting

1958
01:47:16,400 --> 01:47:18,800
Speaker 1: back to that uncertainty, to take those things that we

1959
01:47:18,880 --> 01:47:21,880
Speaker 1: just assume we know and saying now, wait a minute,

1960
01:47:21,920 --> 01:47:24,519
Speaker 1: let's look at that a little differently. And and so

1961
01:47:24,600 --> 01:47:27,880
Speaker 1: for me, the the how do you know that? That again,

1962
01:47:27,920 --> 01:47:33,599
Speaker 1: it's like that young kids, daddy, why is sort of

1963
01:47:33,880 --> 01:47:36,840
Speaker 1: That's what drives my sort of curiosity is I've always

1964
01:47:36,840 --> 01:47:38,960
Speaker 1: got that sort of why, and and what if I

1965
01:47:39,000 --> 01:47:40,519
Speaker 1: what if I picked that up and thought about it

1966
01:47:40,560 --> 01:47:43,200
Speaker 1: from a different way, If I had one token to

1967
01:47:43,240 --> 01:47:47,800
Speaker 1: a time machine. There's like three things. Well, one would

1968
01:47:47,800 --> 01:47:49,360
Speaker 1: be that I would go with Daniel Boone over the

1969
01:47:49,400 --> 01:47:52,320
Speaker 1: Cumberland Gap whoever the hell I can't remember you it

1970
01:47:52,400 --> 01:47:56,479
Speaker 1: was pre Revolutionary war and do that little John with them? Um.

1971
01:47:57,040 --> 01:48:02,160
Speaker 1: One that I would go like uh out with, you know,

1972
01:48:02,880 --> 01:48:05,280
Speaker 1: like to hang out with some fulsome hunters twelve thousand

1973
01:48:05,360 --> 01:48:07,439
Speaker 1: years ago. And the other one that I would go

1974
01:48:07,520 --> 01:48:09,800
Speaker 1: to like out to Miles City twenty thousand years ago

1975
01:48:09,800 --> 01:48:11,080
Speaker 1: to see how long you got to sit there for

1976
01:48:11,080 --> 01:48:13,960
Speaker 1: a mammoth walks by? Like was there a bunch or

1977
01:48:14,000 --> 01:48:18,160
Speaker 1: not many? What was just like you glass up shiploads

1978
01:48:18,160 --> 01:48:19,680
Speaker 1: of them? Are you like you look and look and

1979
01:48:19,760 --> 01:48:21,320
Speaker 1: look and can't find one? I would love to know

1980
01:48:21,360 --> 01:48:26,120
Speaker 1: that thousand whatever, man, I would love to you. Well,

1981
01:48:26,160 --> 01:48:28,280
Speaker 1: that's why we're time machine stuff. Of you like people

1982
01:48:28,280 --> 01:48:29,760
Speaker 1: that would want to go back and watch them sign

1983
01:48:29,800 --> 01:48:31,720
Speaker 1: the Declaration in Dependence. I mean that's cool, but that's

1984
01:48:31,720 --> 01:48:35,839
Speaker 1: not other stuff. We're talking about that site in Mexico earlier. Um.

1985
01:48:35,880 --> 01:48:37,800
Speaker 1: That's when those sites where you know, with that many

1986
01:48:37,840 --> 01:48:40,080
Speaker 1: animals that well preserved, you can start trying to answer

1987
01:48:40,120 --> 01:48:42,680
Speaker 1: for at least for that area to where as I

1988
01:48:42,720 --> 01:48:45,760
Speaker 1: mentioned trying to answer those pale ecological questions as as

1989
01:48:45,840 --> 01:48:48,640
Speaker 1: interesting as trying to say how people interacted with them. So,

1990
01:48:49,080 --> 01:48:52,760
Speaker 1: you know, if I had my time machine, Um, one

1991
01:48:52,800 --> 01:48:54,720
Speaker 1: of the things we've been finding in the mountains here

1992
01:48:54,760 --> 01:48:57,320
Speaker 1: that I hadn't seen ever in the mountains or glass

1993
01:48:57,360 --> 01:49:01,599
Speaker 1: trade beachs, and we think glass beads for trade period.

1994
01:49:03,080 --> 01:49:05,839
Speaker 1: We've got one site where we've got glass trade beads

1995
01:49:06,000 --> 01:49:10,599
Speaker 1: and metal that they're cutting into arrow points and things

1996
01:49:10,640 --> 01:49:13,760
Speaker 1: like that that I submitted a butchered bison bone for

1997
01:49:13,920 --> 01:49:17,519
Speaker 1: radiocarbon date and got a radiocarbon date back of sixteen

1998
01:49:17,640 --> 01:49:21,840
Speaker 1: fifty And being an archeologically, that's wrong. We know that

1999
01:49:22,120 --> 01:49:25,519
Speaker 1: trade bead shouldn't be any metal points here. Yeah, And

2000
01:49:25,600 --> 01:49:29,559
Speaker 1: so we've submitted a couple more and they're coming into

2001
01:49:29,560 --> 01:49:34,960
Speaker 1: that mid to late six from Mexico summer, coming these

2002
01:49:35,200 --> 01:49:37,160
Speaker 1: by then, some of it coming in from the English

2003
01:49:37,200 --> 01:49:40,120
Speaker 1: and French fur traders on the East coast. So I

2004
01:49:40,160 --> 01:49:43,200
Speaker 1: would love to be in the mountains of northwest Wyoming

2005
01:49:44,160 --> 01:49:49,040
Speaker 1: late sixteen hundreds, you know, a hundred and fifty years. Yeah,

2006
01:49:49,120 --> 01:49:51,519
Speaker 1: And what's because that doesn't fit our picture at all,

2007
01:49:51,600 --> 01:49:53,760
Speaker 1: you know, we think of Lewis and Clark is coming

2008
01:49:53,760 --> 01:49:55,920
Speaker 1: through this area and being the first sort of interactions

2009
01:49:55,920 --> 01:49:58,920
Speaker 1: with the Native Americans here hundred and fifty years they

2010
01:49:58,920 --> 01:50:02,360
Speaker 1: were plugged into these hunting nettle wide trade networks. And again,

2011
01:50:02,439 --> 01:50:04,680
Speaker 1: I coming from a small town like MATIZI I like

2012
01:50:04,760 --> 01:50:07,880
Speaker 1: to highlight that of kid, you're from, not from the

2013
01:50:07,920 --> 01:50:10,160
Speaker 1: back of nowhere. You're in a place that's been connected

2014
01:50:10,200 --> 01:50:13,519
Speaker 1: with the rest of the continent forever. I've brought this up.

2015
01:50:13,520 --> 01:50:15,360
Speaker 1: This will this is my final thought. I've brought us

2016
01:50:15,360 --> 01:50:19,519
Speaker 1: a bunch of times where the historian Elliott West has

2017
01:50:19,520 --> 01:50:21,719
Speaker 1: a piece where he talks about when Lewis and Clark

2018
01:50:23,120 --> 01:50:28,200
Speaker 1: hit the Great Plains, there were Indians on the Great

2019
01:50:28,240 --> 01:50:33,719
Speaker 1: Plains who had gone to Europe, met the King of France,

2020
01:50:34,200 --> 01:50:40,440
Speaker 1: and come back again. So in terms of like discovering

2021
01:50:40,560 --> 01:50:43,519
Speaker 1: you know what I mean, Yeah, it's a calm, it's

2022
01:50:43,560 --> 01:50:45,640
Speaker 1: a much more complex period. And a lot of us

2023
01:50:45,680 --> 01:50:48,439
Speaker 1: use that Lewis and Clark period is the baseline of

2024
01:50:48,479 --> 01:50:51,640
Speaker 1: whether it's how many grizzlies they show saw, or the

2025
01:50:51,640 --> 01:50:54,000
Speaker 1: bison populations and this and that and the other. And

2026
01:50:54,800 --> 01:50:57,960
Speaker 1: if you consider that I think was the Crow tribe

2027
01:50:58,240 --> 01:51:02,759
Speaker 1: in the late seventeen hundreds of their population from disease.

2028
01:51:03,880 --> 01:51:07,560
Speaker 1: What's you know, that's removing huge numbers of key predators

2029
01:51:07,600 --> 01:51:10,200
Speaker 1: from the environment. So by time Lewis and Clark's comes through,

2030
01:51:10,479 --> 01:51:13,120
Speaker 1: the environment's reorganized in a way it may have never

2031
01:51:13,200 --> 01:51:18,480
Speaker 1: been manipulated. Yeah, it's it's not um well or under manipulated.

2032
01:51:18,640 --> 01:51:20,560
Speaker 1: You know, you all of a sudden, it's like manipulated,

2033
01:51:20,560 --> 01:51:23,640
Speaker 1: meaning like impact of impact of man A lot of

2034
01:51:23,640 --> 01:51:27,479
Speaker 1: our ideas of managing wilderness areas or management game is

2035
01:51:27,520 --> 01:51:30,479
Speaker 1: to try and get back to that baseline that probably

2036
01:51:30,520 --> 01:51:33,840
Speaker 1: never existed. That baseline of when Lewis and Clark came

2037
01:51:33,840 --> 01:51:37,480
Speaker 1: through was probably artificial, and that it has been depopulated.

2038
01:51:37,960 --> 01:51:42,320
Speaker 1: The ecology had been reorganizing for the last years into

2039
01:51:42,360 --> 01:51:46,160
Speaker 1: something it may never have been. So it's it's and again,

2040
01:51:46,280 --> 01:51:48,879
Speaker 1: how do you deal with that if you're a wildlife manager.

2041
01:51:48,920 --> 01:51:51,720
Speaker 1: I don't know. It's just sort of throws a lot

2042
01:51:51,760 --> 01:51:55,240
Speaker 1: of but it's one of those we probably need to

2043
01:51:55,240 --> 01:51:58,840
Speaker 1: think about it. Yeah, my operating idea instead of trying

2044
01:51:58,840 --> 01:52:01,280
Speaker 1: to pin it to a certain year, I just like

2045
01:52:01,400 --> 01:52:06,520
Speaker 1: to operate on I would like to see more wildlife

2046
01:52:06,600 --> 01:52:10,280
Speaker 1: tomorrow in more places than we have it today and

2047
01:52:10,320 --> 01:52:14,040
Speaker 1: in better conditions. Yeah, it's like, I'm not gonna attempt

2048
01:52:14,040 --> 01:52:16,080
Speaker 1: to tie it to what I'm trying to match. I

2049
01:52:16,160 --> 01:52:18,080
Speaker 1: just want I can tell you one thing, I'd like

2050
01:52:18,160 --> 01:52:20,840
Speaker 1: more of it in more places, and we certainly don't

2051
01:52:20,840 --> 01:52:23,720
Speaker 1: want ship decline. Well, thank you very much for coming on. Man,

2052
01:52:23,760 --> 01:52:25,760
Speaker 1: it has been great. Oh, thank you. This has been fun.

2053
01:52:26,000 --> 01:52:26,439
Speaker 1: Thank you,