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Speaker 1: Okay, welcome to the crime Page. A binding does a podcast.

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I'm here with Allan Rockefeller, my friend Allan Rockefeller, the mycologist,

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and we're in Ecuador at an elevation of thirty seven

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hundred feet in the Upper Amazon. And am I leaving

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out any other pertinent information? Allen?

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Speaker 2: Yeah, we're in the in the Puyoh area, so pu Yo. Yeah,

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so a little little town called mara Uh.

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Speaker 1: And I was excited when you invited me to come

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down here. I was like, Fuck, I don't know if

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I can do it. I'm getting back from Chile, got

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a lot of work to do. But then I'm really

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glad that I said yes because it turned out to

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be pretty incredible and I've learned so much. I've never

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really been into tropical botany before, but because I had

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no experience with it, but now it's it's a whole

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other world. And on the mushroom side of things, well,

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tell me, tell me what's going on here mycologically.

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Speaker 2: Yeah, there's a lot of really cool mushrooms here in

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this area. There's not a lot of ect microouzal hosts,

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so it's mostly sapatrophs. So you see a whole lot

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of Mycena marasmius, just all sorts of things that decay

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the leaf litter. But rarely you'll see just like a

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Russola or a Romeria something mic urhyzol just way out

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in the middle of the rainforest and there's so many

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trees around you can't really tell what tree they're associated with. Yeah,

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I don't think we saw any micrhyzol stuff for the

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whole ten days we've been here.

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Speaker 1: No, but there is a lot of am fungy the

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glomero miceats, and with those you get a lot of

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those cool micoheterotrophs like the Voi rhea and the gymnociphon

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which gymnosiphons bermanniac voirieas gets a gent and ac. But

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so it's mostly probably am micro or postcular mic rhyzol fungi.

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Speaker 2: Yeah, exactly. So with the am fungi, you never see

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anything directly, but they help out the plants. And yeah,

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we have been seeing some micro heterotrophs. I got really

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cool focus stacked photos of the gymno siphon yesterday.

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Speaker 1: Fuck I'm jealous. I didn't go with you, guys.

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Speaker 3: I saw my I saw Voi voi Ria though, so

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that was Yeah. Those are really cool too. Those are

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really pretty. And we also saw about an hour from

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here the tiputinia. It was Tiputinia foatita, So that one

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was described from Ecuador.

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Speaker 1: What is that? What do you know what family that's in?

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Speaker 2: Oh, we'd have to look it out.

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Speaker 1: You guys saw that yesterday?

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Speaker 2: No, no, it was last year. But it's really crazy.

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It smells like rotting flesh and it's like a little

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brown flower that just comes right out of the ground,

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no leaves or anything, and looks like completely unlike anything

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I've ever seen before. But if you just if you

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look it up on an I naturalist, you can you

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can see the pictures. There's not very many observations of it.

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But it's a really crazy looking thing. I p U

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T I N I A.

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Speaker 1: P u. Oh yeah, oh feeted it? Oh shit?

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Speaker 2: Yeah, so this thing and you know it attracts flies

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with its odor, so fly pollinated.

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Speaker 1: Yeah. I think most of these little mico heterotrusts are

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probably pollinated by little fungus gnats or smaller flies. I mean,

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like the voiriea that I saw was two inches tall.

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If that so? Oh Jesus, Oh yeah, there's only four observations. Yeah,

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that thing's wild.

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Speaker 2: Yeah, it's it's very rare, and it's also really hard

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to spot, so you know, you're walking by at full speed,

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it's almost impossible to see. It's not as tiny as

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gymnaside things.

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Speaker 1: Me Acy, it looks like me ac Herbermanniac. Now yeah, okay,

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Jesus God, that's a it's a tropical tropical parasite the

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family Jesus christ Man.

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Speaker 4: Yeah.

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Speaker 2: So it's got the brown petals and the orange center.

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Speaker 1: Wow, that's wild. Tip U tinia t I p u

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t i n i A. Check it out on ain

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answer list if if you can't. That was a cruise found.

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The crews saw this.

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Speaker 2: I hag fur Hat spotted it first.

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Speaker 1: God the damn Yeah. Okay, Well, botanically, it's been really

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it's really disorient thing because you'll see something and you'll

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see I've been taking pictures of leaves, which I don't

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normally do because they're not the best identifying factors, so

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you really have to focus on like extremely subtle stuff

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like pettiole length, presence of hairs, opposite of alternate leaves,

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of course, which is like the first thing, leaf shape,

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texture all that kind of shit, and then you'll see

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something flowering and then it kind of gives you a

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better idea. But but everything is yeah, mostly way up

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in the canopy, like what's that that that tree member

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of polygate Ac that we saw, species name is Comingiana,

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but that was you know, that was I could and

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get photos of it. And then I found the flowers

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all over the ground on a really rainy and they're

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really rainy day when I was cursing a lot tripleeris Comingiana, yeah,

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and then I saw the flowers and figured out it

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was dioecious that the trees or their male or female.

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But but botanically, it's really interesting because these these are

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mostly plants that I only saw prior to this in

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like horticulture, you know, like in a conservatory where God forbid,

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like a fucking you know office like mall indoor, you know,

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plant type situation, but to see where they grow and

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like the incredible humidity and and it's not it's surprisingly

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it's not that hot here. Like the climate's much different

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from what I thought it would be. I thought it

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would be hotter.

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Speaker 2: Well, the course still Ecuador is really hot and muggy,

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but you know, up here at a thousand meters, it's

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really comfortable almost all the time. But yeah, sometimes you're

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walking along the forest and you just see, like the

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ground littered with flowers, and you can't see where they're

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coming from. They're coming from some epiphyte way up in

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the tree. But you know, occasionally a branch will fall

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and you'll see it, and most of the stuff, you know,

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it's pretty confusing. I'll usually only photograph something if it

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has flowers, unless it's got some crazy corrugated leaves or

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something like that, they would make it distinctive. But you know,

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sometimes you'll see these beautiful variegated leaves and you'll take

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good pictures of it and put it all over the

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plant identification forums and igh naturalists and people will just

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be like, no, there's no idea to identify that without flowers.

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But those are a few things that I keep seeing

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over and over that I really like. Like that Pallacoria tomentosa.

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That thing is super distinct.

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Speaker 1: Yeah, it used to be psychoatry, I guess, but.

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Speaker 2: Yeah, I think four years back then put it into palakoria.

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But that thing is really distinctive, and I looked it

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up it turns on it. I saw it in Wahaka,

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just a little bit north of Wahaca City, which is

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the very north end of its range.

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Speaker 1: Oh, the same species relative.

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Speaker 2: Yeah, the same thing, the Pellachoria tomentosa. It actually looked

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kind of different than the Palachoria tomentosa. We get around

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here and then it kind of goes down in through

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middle Brazil. But that that's probably the easiest plant to

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identify around here because it's so bright and distinctive and

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you just can't mistake it for anything.

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Speaker 1: Yeah, it's super common too. Yeah, with those red bracts.

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It's I don't know what's going on. If it's like

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because the flowers are yellowish or white and then the

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two red bracts are really conspicuous. I don't know. If

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it's like trying to make hummingbird pollination with fly pollination too.

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I don't know, but a lot of hummingbird pollinated stuff here,

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like a lot like that. All its nereads, the tons

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of rubac, tons of the the larient. They see the

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tropical missletoes, which is another thing that you'll only see

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the flowers on the ground because the comparasites, like you know,

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fifty feet up in the the trees, the giant bamboo.

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I wasn't expect thing that, Go ahead, do it. And gustafolia.

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Speaker 2: Yeah, that bamboo is kind of an interesting thing because

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there's this fungus that grows on the scale insects of

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the bamboo, and so it's called called asco polipperis, and

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asco polipperis, you know, starts out this like a little

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white ball on the bamboo and then it turns like

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bright orange and I threw it in my tackle box

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next morning. There was like this big white spore print

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where I put it. But it's just like this round

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thing and you cut it open. It's all gelatinous in

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the inside. But it's in the Corticipitacea, so related to cortuceps,

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and you know, like the other things in the Corticipitacea,

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it grows on insects, so scale insects in this case,

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but you only see it in bamboo, and those bamboos

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we kind of watch out for them because they're covered

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in you know, really long thorns.

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Speaker 1: The lateral branches have these yeah dines on them really.

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Speaker 2: Yeah, they're like two three inches long sometimes and if

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you get stuck with them, usually you get, you know,

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pretty any bad infections because they're just like you. They're

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the opposite of sterile being.

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Speaker 1: Because it's humid as a nutsack down here too, and

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what is the rain Like five to seven meters, so

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that's like fifteen to twenty one feet depending on where

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you are. The interesting thing about the bambooo is like

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it's so fucking big. It's it's literally eighty feet tall.

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This is literally like a nearly thirty meter tall bamboo.

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I mean you can't really see the top in some places,

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and it forms these massive colonies and then you'll just

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see this like six foot tall new shoot popping out

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of the ground. And then the the leg ules and

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the protective bracts are covered in these tiny kind of

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like burgundy colored hairs that feel like a shark skin

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or like a cat tongue or something. It's the most

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bizarre thing. Yeah, I had no idea that was here.

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I thought that was like invasive when I first saw.

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Speaker 2: Yeah, see how it belongs here?

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Speaker 1: Yeah, yeah, that was crazy stuff. So, but corticipitasy and

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then there's Ophio cordyceps.

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Speaker 3: Those are related, well, they're both in the hypocialities order,

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but they're not closely related, they're kind of kind of

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distantly related families.

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Speaker 1: Is this probably independent evolution of insect Yeah.

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Speaker 2: The insects have a lot of you know, nutrition and

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you know, things that fungi elect to metabolize, so they're

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they're really good substrate for fungi. So you know, the

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actually entomopathogens have evolved like six or seven times, and

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they are really widely dispersed. If you look at the

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phylogenetic tree, there's some that are kind of over by

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penicillium and other branches of fungi. The pine never heard

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of because they don't really make anything resembling a mushroom,

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but they are very widely distributed. So yeah, that's that's

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evolved a lot of sense.

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Speaker 1: So this is I mean, because there's so many insects here.

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Once you if you're a fungus and you evolve the

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capability to digest insects and infect them, and you know,

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affect infect them efficiently by spore production, I mean, you've

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you've captured a whole niche.

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Speaker 2: So that's yeah, And a lot of these entimapathogens are

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very very picky about which insects, like the Corterceps. They'll

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only grow on one species of insect, and so like

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a lot of the ones we've been seeing, there's a

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few common ones. We've been seeing a lot of opiod

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Corterceps crook courially on them, and that one grows on weavils.

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See I always see that weavil with a long snout

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coming out of that. And they've got another one, Corterceps australis,

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which you're on these really big they kind of look

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like carpenter ants. And then there's the ophiod Cordyceps melolonthe,

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which grows on the Melanthona beetles the larvae of that,

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and that's probably the biggest quarterceps. And then you get

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the bright red one Corterceps needest and that only grows

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on trap door spiders. So you find that and you

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excavate it and they'll be a spider do on that

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and if you do it real carefully you can actually

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get the trap door and everything.

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Speaker 1: And that was the one that you saw in that cave.

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Speaker 2: Yeah, that one we found growing in the cave. And

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there's there's always a lot of court Sepitacea in the cave,

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but we've never seen just a courterceps fruiting body like that.

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Usually we just kind of find them growing out of

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the sides of trails.

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Speaker 1: I was so glad nobody came down with a zoonatic

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disease in the cave yet, because the bats were everywhere.

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Speaker 2: Yeah. Yeah, we go into the caves a lot, and

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getting sick is really rare, but there's a ton of

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bats in there, so we're always a little bit careful

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with the mud.

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Speaker 1: Everybody was wearing masks, except for you because he didn't

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because he didn't have one, but you're.

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Speaker 2: Okay, Yeah, No, somebody had a mask for me, and

236
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I just couldn't find them when he went into the cave.

237
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So I've been in those caves a ton of times

238
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without masks and a couple of times with masks, and

239
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it didn't didn't seem to really, it's not usually a problem.

240
00:12:45,840 --> 00:12:48,039
There's some other caves that are deeper and have even

241
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more bats, and we're a little bit more serious about

242
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wearing masks and in those other caves. This cave was

243
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pretty big, had a lot of ventilation, and so I

244
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wasn't too worried about it, but I would have warned

245
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it if I had it.

246
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Speaker 1: Yeah, yeah, I mean, god, there was so much cool

247
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shit in there. It's it's its own ecosystem. There's these

248
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crickets that I presume are eating baguano and then they

249
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serve as the base of the ecosystem kind of. I mean,

250
00:13:12,440 --> 00:13:16,279
there was the the whip scorpion, that massive whip scorpion

251
00:13:16,320 --> 00:13:20,759
we saw on there, and then there's pseudoscorpions, what other

252
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what else was it?

253
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Speaker 2: There's also just a regular plane all scorpions. Yeah, we

254
00:13:26,720 --> 00:13:28,279
didn't see them this year, but last year in the

255
00:13:28,320 --> 00:13:31,799
same cave system, we got some pretty cool photos of

256
00:13:32,000 --> 00:13:37,320
just scorpions. And there's fish in there that you know,

257
00:13:37,399 --> 00:13:42,120
don't really have eyes. There's cave lizards, and then there's

258
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all those fossils, you know, just embedded in the cave walls.

259
00:13:45,879 --> 00:13:50,879
I saw a bunch of shells this year, you know,

260
00:13:51,039 --> 00:13:53,759
just like ancient clams and stuff. But sometimes you also

261
00:13:53,799 --> 00:13:57,279
see like cranoid stems. And in one of the caves

262
00:13:57,279 --> 00:14:00,399
about a mile from there, there's there's a whole just

263
00:14:00,440 --> 00:14:03,519
a big starfish, just like right there, embedded in the wall.

264
00:14:04,080 --> 00:14:05,759
Speaker 1: Jesus, how big is it?

265
00:14:05,879 --> 00:14:08,960
Speaker 2: Pretty big? Like five inches across? Oh yeah, it's on one.

266
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Speaker 1: I wonder what the age of the limestone is, if

267
00:14:11,759 --> 00:14:13,679
it's cretaceous or if it's earlier or what.

268
00:14:14,000 --> 00:14:16,639
Speaker 2: I'm sure Alex knows. He studies those caves for a living.

269
00:14:16,960 --> 00:14:19,320
Speaker 1: Yeah, yeah, that was I guess that Cave two was

270
00:14:19,399 --> 00:14:22,000
used as munition storage during the war with Peru.

271
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Speaker 2: So yeah, I think Peru and Ecuador have kind of

272
00:14:26,320 --> 00:14:30,279
been battling over territory for a while, and so yeah,

273
00:14:30,320 --> 00:14:33,240
they would the army used to be all over that

274
00:14:33,399 --> 00:14:35,799
and then they settled out and they haven't been around

275
00:14:35,840 --> 00:14:36,440
there for a while.

276
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Speaker 1: But there was a there was a cool bogonia growing epiphetically.

277
00:14:41,559 --> 00:14:43,720
I mean, there's so much shit here, it's nuts. There

278
00:14:43,799 --> 00:14:47,120
was what was the zygo micey thing that was growing

279
00:14:47,159 --> 00:14:51,159
on the cliff wall above the cave entrance. It just

280
00:14:51,200 --> 00:14:53,000
looked like insulation.

281
00:14:53,240 --> 00:14:56,600
Speaker 2: It looked like, yeah, I call them pin molds. But

282
00:14:57,240 --> 00:14:59,320
you know, those things are pretty hard to identify. And

283
00:14:59,360 --> 00:15:01,240
they're hard to because if you put it in a

284
00:15:01,240 --> 00:15:03,840
tackle box that kind of gets banged around, it turns

285
00:15:03,879 --> 00:15:05,879
into a pile of slimes. So you kind of have

286
00:15:06,000 --> 00:15:09,399
to wrap it up in a leaf for something, and

287
00:15:09,440 --> 00:15:11,559
then put it on the dehydrator. As soon as you

288
00:15:11,639 --> 00:15:15,279
get back to get a good collection of that kind

289
00:15:15,320 --> 00:15:15,639
of thing.

290
00:15:15,919 --> 00:15:19,279
Speaker 1: I don't know anything about that group with a claye

291
00:15:19,279 --> 00:15:19,840
of fungi.

292
00:15:20,639 --> 00:15:24,879
Speaker 2: Yeah, it was super diverse, very understudied. The most common

293
00:15:24,919 --> 00:15:27,679
one that you see around is called Ficho Mice's Blake's

294
00:15:27,759 --> 00:15:31,080
leanis and that's the one that you see on dog

295
00:15:31,159 --> 00:15:35,000
shit and it's like I seen before, yeah a million times,

296
00:15:35,039 --> 00:15:37,759
Like you know, just like every dog turd that's not

297
00:15:37,879 --> 00:15:39,600
in the in the woods for a couple of weeks,

298
00:15:39,600 --> 00:15:41,759
how's it growing on there? But that one it was

299
00:15:41,799 --> 00:15:45,559
described like in the nineteen twenties, and it was named

300
00:15:45,600 --> 00:15:50,320
after doctor Blakesley, And so the guy that described it

301
00:15:50,360 --> 00:15:53,120
hated doctor Blakesley. Nobody can figure out why, and so

302
00:15:53,240 --> 00:15:55,399
he named his dogshit fungus after him.

303
00:15:55,440 --> 00:15:56,960
Speaker 1: It's it's so fucking petty man.

304
00:15:57,080 --> 00:15:59,919
Speaker 2: Yeah, one of the few disparagingly named fungi.

305
00:16:00,360 --> 00:16:02,320
Speaker 1: It's kind of funny. How did you end up coming

306
00:16:02,519 --> 00:16:04,840
down here? Like, well, you came down here during COVID

307
00:16:04,919 --> 00:16:06,000
or during twenty twenty or what.

308
00:16:06,200 --> 00:16:09,159
Speaker 2: Yeah, first time I came was February twenty twenty. And

309
00:16:09,320 --> 00:16:11,399
when I first came down, I was like, Ah, this

310
00:16:11,519 --> 00:16:13,440
COVID thing is nothing. It's not going to be a

311
00:16:13,480 --> 00:16:16,000
big deal. It's just the media being silly. And by

312
00:16:16,000 --> 00:16:18,320
the time I left, I'm like, Okay, yeah, it seems

313
00:16:18,360 --> 00:16:22,039
like it's actually a real thing. Turns out maybe the

314
00:16:23,480 --> 00:16:26,720
former thing was a little bit more accurate, because you know,

315
00:16:26,799 --> 00:16:28,559
now there's more COVID than there was at the height

316
00:16:28,559 --> 00:16:30,200
of the pandemic and nobody cares.

317
00:16:30,399 --> 00:16:32,360
Speaker 1: But I think it's probably become a little bit less

318
00:16:32,440 --> 00:16:34,000
virulent too. Yeah.

319
00:16:34,080 --> 00:16:36,080
Speaker 2: Yeah, trains, they're not so bad.

320
00:16:36,200 --> 00:16:37,519
Speaker 1: It wiped a bunch of people out.

321
00:16:37,639 --> 00:16:39,919
Speaker 2: Oh yeah, a lot of people like Anne Shulgan is

322
00:16:39,919 --> 00:16:44,080
one of them. Who is it the wife the chemist?

323
00:16:44,159 --> 00:16:49,919
Speaker 1: Yeah, oh brutal, Yeah, Billy Turner, Texas Bonnas died of COVID,

324
00:16:49,919 --> 00:16:52,679
I think. But yeah, it was mostly getting old people,

325
00:16:52,720 --> 00:16:55,440
I guess. But but still, I don't know. Maybe we'll

326
00:16:55,480 --> 00:16:57,679
have another pandemic now that Trump's in office again.

327
00:16:57,799 --> 00:17:00,320
Speaker 2: So I'm sure there's more coming, just as more and

328
00:17:00,360 --> 00:17:04,039
more travel and more people kind of like encroaching in

329
00:17:04,599 --> 00:17:08,839
these areas and less public health. But yeah, one thing

330
00:17:08,880 --> 00:17:12,559
about that pandemic is that it was like impossible to stop.

331
00:17:12,640 --> 00:17:14,839
Remember they had all those mask laws, like you couldn't

332
00:17:14,880 --> 00:17:17,079
go into a store without wearing a mask, right, and

333
00:17:17,119 --> 00:17:20,039
that didn't even start to slow it down like that,

334
00:17:20,079 --> 00:17:22,880
Like they took counties that had mask laws and the

335
00:17:23,039 --> 00:17:26,400
adjacent county had no mask laws and just knowing wearing

336
00:17:26,440 --> 00:17:28,759
masks in public places, and they had the same spread.

337
00:17:28,839 --> 00:17:31,720
Like the masks weren't even sewing them down. So like

338
00:17:31,880 --> 00:17:34,880
if there was a pandemic that actually did something really

339
00:17:34,880 --> 00:17:37,799
bad like ebola, we'd basically be screwed.

340
00:17:37,839 --> 00:17:39,759
Speaker 1: Yeah, we'd be fucked. I was really into the masks

341
00:17:39,759 --> 00:17:41,440
at first because I was like, yeah, this is fucking nasty.

342
00:17:41,480 --> 00:17:43,240
I don't want to be breathing. You know, you're on

343
00:17:43,240 --> 00:17:44,720
a plane or someone. I don't want to be breathing

344
00:17:44,720 --> 00:17:48,440
these nasty motherfuckers viral particle was. But then I you know,

345
00:17:48,839 --> 00:17:50,559
I got sick when I was I was in the

346
00:17:50,640 --> 00:17:52,400
New York subway and I was still wearing a mask.

347
00:17:52,480 --> 00:17:55,079
It was twenty two and I was like, because you're

348
00:17:55,160 --> 00:17:57,920
packed asket neek in a subway and I still got COVID.

349
00:17:57,960 --> 00:18:00,160
I mean it was just so such a dense.

350
00:18:01,000 --> 00:18:03,920
Speaker 2: Yeah, I mean masks work a little bit, but not

351
00:18:04,039 --> 00:18:06,119
like in real life just like yeah, you know, if

352
00:18:06,119 --> 00:18:08,599
you're like a doctor or something, yeah, they definitely work.

353
00:18:09,119 --> 00:18:11,720
But just like in real life, you know, just like

354
00:18:11,799 --> 00:18:13,920
you never really breathe through it. And if you were

355
00:18:13,920 --> 00:18:17,359
wearing one of those masks that actually filter is enough

356
00:18:17,359 --> 00:18:19,319
to stop you from getting sick, then nobody can hear

357
00:18:19,359 --> 00:18:20,200
what you're saying.

358
00:18:20,200 --> 00:18:23,799
Speaker 1: Right exactly exactly. I think they probably stop like ten

359
00:18:23,880 --> 00:18:27,440
or twenty percent maybe or help your chances that much

360
00:18:27,480 --> 00:18:29,119
if it's but if you if you're in like a

361
00:18:29,160 --> 00:18:31,720
packed subway car or some shit, it's not gonna yeah

362
00:18:32,400 --> 00:18:34,680
do anything. And probably just the like if you're on

363
00:18:34,720 --> 00:18:38,119
an airplane just having the fucking fans on, you know,

364
00:18:38,160 --> 00:18:40,559
if that's filtered air and it's blowing at you, that's

365
00:18:40,599 --> 00:18:43,119
gonna do more than a mask most likely.

366
00:18:43,279 --> 00:18:43,720
Speaker 2: Probably.

367
00:18:44,160 --> 00:18:47,240
Speaker 1: Yeah. Yeah, it's wow. I still see people wearing masks.

368
00:18:47,279 --> 00:18:49,839
It's it became this crazy thing for some people. It's

369
00:18:49,920 --> 00:18:52,839
nuts man like out outside and shit like people still

370
00:18:52,880 --> 00:18:53,640
wearing masks.

371
00:18:53,720 --> 00:18:55,079
Speaker 2: Yeah, the whole political things.

372
00:18:55,319 --> 00:18:58,000
Speaker 1: Yeah, yeah, it became really politically charged. But now I

373
00:18:58,119 --> 00:19:01,680
just I don't know, I think it became this obsessive

374
00:19:01,839 --> 00:19:05,519
thing for some people, like, oh, look, that person's mentally ill.

375
00:19:06,559 --> 00:19:08,799
You know, that's normally where I go. There's always exceptions,

376
00:19:08,839 --> 00:19:13,680
of course, but I'm anyway. So okay, So so you

377
00:19:13,759 --> 00:19:15,559
sort of coming down here in twenty twenty, and then

378
00:19:15,759 --> 00:19:17,519
were you coming down here every year since? I mean,

379
00:19:17,559 --> 00:19:19,920
what was that? What was the main attractive for you

380
00:19:20,480 --> 00:19:25,480
in terms of tropical mycology as opposed to temperate zone

381
00:19:25,519 --> 00:19:27,039
mycology like you've been doing before.

382
00:19:27,559 --> 00:19:29,920
Speaker 2: Yeah. Well, I'd always heard that there was really cool

383
00:19:30,000 --> 00:19:34,279
mushrooms in Ecuador, but you know, I never knew exactly

384
00:19:34,319 --> 00:19:37,279
where to go. But this guy, for hat, he built

385
00:19:37,279 --> 00:19:40,160
an eco resort about an hour from here called think

386
00:19:40,200 --> 00:19:43,279
of Himatlos I think a change in name now to

387
00:19:43,440 --> 00:19:46,480
High Matt Loos Amazon launch. But he is somebody that

388
00:19:46,799 --> 00:19:49,599
I've known on Facebook for a long time. He's one

389
00:19:49,599 --> 00:19:52,640
of the sharpest mushroom identifiers on Facebook. He's in like

390
00:19:52,720 --> 00:19:56,279
every group. And so I came down to visit him

391
00:19:56,319 --> 00:20:00,200
in twenty twenty and it was really good.

392
00:20:01,079 --> 00:20:01,200
Speaker 1: You know.

393
00:20:01,240 --> 00:20:03,680
Speaker 2: I was here for like two weeks and stayed at

394
00:20:03,680 --> 00:20:06,720
his place, and there was just you know, things that

395
00:20:06,759 --> 00:20:09,680
I had never seen, and you know, just every inch

396
00:20:10,240 --> 00:20:13,039
of the forest is covered in cool stuff. I mean

397
00:20:13,039 --> 00:20:16,240
you could stop and just like look at one square

398
00:20:16,319 --> 00:20:18,559
meter of woods and like, you know, spend an hour

399
00:20:19,240 --> 00:20:21,839
looking there and not even see all of it. And

400
00:20:21,920 --> 00:20:24,000
so when you're walking at like a good speed, you're

401
00:20:24,000 --> 00:20:28,400
missing like ninety nine point nine nine percent of the stuff.

402
00:20:28,519 --> 00:20:30,319
But you know, no matter what speed you walk, you

403
00:20:30,359 --> 00:20:31,359
see so much.

404
00:20:31,440 --> 00:20:33,480
Speaker 1: So you came down here and you saw, you saw

405
00:20:33,519 --> 00:20:35,119
that it was hyper diverse for funny.

406
00:20:35,400 --> 00:20:37,759
Speaker 2: Yeah, so I kind of started coming back every year

407
00:20:37,839 --> 00:20:38,319
since then.

408
00:20:38,799 --> 00:20:40,400
Speaker 1: I guess it makes sense. It's wet and there's a

409
00:20:40,440 --> 00:20:43,160
shit ton of organic material and so everything is just

410
00:20:43,240 --> 00:20:44,720
you need a lot of decomposers.

411
00:20:44,960 --> 00:20:48,319
Speaker 2: Yeah, Like the forest here is just really full of life,

412
00:20:48,440 --> 00:20:53,880
much more so than a temperate forest. Things grow really fast,

413
00:20:54,119 --> 00:20:57,519
a huge amount of rain, and just like huge amount

414
00:20:57,519 --> 00:21:00,000
of competition. So it was kind of like the evolue

415
00:21:00,480 --> 00:21:03,599
that happens everywhere is happening in overdrive here.

416
00:21:04,160 --> 00:21:06,160
Speaker 1: In tons of insect diversity too.

417
00:21:06,519 --> 00:21:11,279
Speaker 2: Yeah, so much. Yeah, Like it ferhats Eco Resort to

418
00:21:11,319 --> 00:21:13,960
have a permanent moth light there, and it's just like

419
00:21:14,000 --> 00:21:17,599
some really bright lights shining on a white board. And

420
00:21:17,680 --> 00:21:19,880
if you zoom in to the ten feet around the

421
00:21:19,880 --> 00:21:23,119
white board on I naturalist, there's like thirty five hundred

422
00:21:23,160 --> 00:21:27,119
species in this ten foot area, like you know, a

423
00:21:27,119 --> 00:21:29,880
couple of thousand of them are lepidopter of the different

424
00:21:29,920 --> 00:21:34,519
moths and butterflies, all kinds of bugs and just everything else.

425
00:21:35,240 --> 00:21:38,480
But yeah, if you pay close attention, it's just really

426
00:21:38,599 --> 00:21:41,680
hyper diverse. And the closer you look, the more you see.

427
00:21:42,000 --> 00:21:44,480
Speaker 1: There was a cool cicada on the moth light last night.

428
00:21:44,519 --> 00:21:47,599
When I got back, I was I was stoked to

429
00:21:47,720 --> 00:21:50,640
find it, to see it there because I've heard them,

430
00:21:50,680 --> 00:21:52,920
but I love cicada diversity. You can hear them, but

431
00:21:53,519 --> 00:21:55,799
I hadn't caught or been able to see me. And

432
00:21:55,880 --> 00:21:57,400
then there was one right on the moth Like that

433
00:21:57,440 --> 00:21:59,759
doesn't fuck if it's on all the time, it doesn't

434
00:21:59,799 --> 00:22:01,720
fuck with the moths too much, right, You're not, like,

435
00:22:03,640 --> 00:22:04,720
what is the downside?

436
00:22:04,880 --> 00:22:07,480
Speaker 2: No, I don't know what the downside too mothlight is,

437
00:22:07,519 --> 00:22:10,480
but I mean there's like street lights in every city,

438
00:22:10,519 --> 00:22:13,759
and so if there's a downside, they're screwed. Yeah, and

439
00:22:13,759 --> 00:22:14,319
I'm sure.

440
00:22:14,200 --> 00:22:16,000
Speaker 1: Yeah, yeah, yeah, it's like.

441
00:22:16,279 --> 00:22:19,160
Speaker 2: Wasting light isn't going to do very much compared to

442
00:22:19,160 --> 00:22:19,599
all the city.

443
00:22:19,880 --> 00:22:21,799
Speaker 1: Well, just a twenty four to seven months light. But

444
00:22:21,839 --> 00:22:24,119
that's also kind of cool. I suppose it, you know.

445
00:22:24,279 --> 00:22:25,559
Speaker 2: I mean that's what street lights do.

446
00:22:25,960 --> 00:22:28,160
Speaker 1: Yeah, well, you know, what I'm sure it becomes when

447
00:22:28,240 --> 00:22:29,920
once the day comes and they fly off.

448
00:22:30,119 --> 00:22:32,440
Speaker 2: Yeah, they fly off when it gets light again.

449
00:22:32,599 --> 00:22:35,799
Speaker 1: You know it's it's still they'll be fine. But is

450
00:22:35,839 --> 00:22:37,400
it a UV light he's got going on there?

451
00:22:37,440 --> 00:22:42,480
Speaker 2: No, there's regular white lights. They like UV too. They

452
00:22:42,599 --> 00:22:45,559
like three ninety five better than three sixty five nanometer,

453
00:22:45,680 --> 00:22:48,920
but you actually get different things with different spectra. When

454
00:22:48,960 --> 00:22:51,119
I'm out camping, I just use the headlights from my

455
00:22:51,200 --> 00:22:54,279
car and just shine my head headlights on bright, just

456
00:22:54,319 --> 00:22:57,319
pointed at like a white sheet or just anything, and

457
00:22:57,319 --> 00:22:59,480
they all come and land on my car. And that

458
00:22:59,559 --> 00:23:02,599
works really well for attracting all sorts of insects.

459
00:23:02,960 --> 00:23:05,599
Speaker 1: The three sixty five that's what you use mostly.

460
00:23:06,119 --> 00:23:08,920
Speaker 2: Yeah, So for ultraviolet lights, I use three sixty five

461
00:23:09,000 --> 00:23:11,839
nanometer because your eyes can see from four hundred to

462
00:23:11,880 --> 00:23:14,519
eight hundred, you know, four hundred being purple, eight hundred

463
00:23:14,559 --> 00:23:17,960
being red. So three ninety five is the black lights

464
00:23:17,960 --> 00:23:20,720
that most people are familiar with. That's those the party

465
00:23:20,799 --> 00:23:23,519
lights that look kind of purplish. But three sixty five

466
00:23:23,640 --> 00:23:26,559
just a little bit farther outside of what you can see.

467
00:23:26,839 --> 00:23:29,559
So when you use a three sixty five nanometer flashlight,

468
00:23:30,000 --> 00:23:33,920
all you're seeing is the fluorescence. You're not seeing any

469
00:23:33,960 --> 00:23:37,440
of the actual lights. So stuff lights up really well.

470
00:23:37,880 --> 00:23:40,880
And what's happening is you shine some of this ultraviolet

471
00:23:40,920 --> 00:23:44,359
light and a lot of materials they will kind of

472
00:23:44,440 --> 00:23:46,759
trap the photon for a second and then re emit

473
00:23:46,839 --> 00:23:51,480
it at a longer wavelength, so you see just basically

474
00:23:51,519 --> 00:23:54,359
every color of the spectrum can be emitted. And what

475
00:23:54,400 --> 00:23:57,279
it is, it's like a chemical sensor, so you can

476
00:23:57,359 --> 00:24:01,759
sense a lot of chemicals. Just like all the substances

477
00:24:01,759 --> 00:24:05,079
in nature have different colors, they also have different fluorescences.

478
00:24:05,720 --> 00:24:08,720
And you know, sometimes it's really good for taxonomy. Like

479
00:24:08,720 --> 00:24:11,000
you shine an ultraviolet light at a log and what

480
00:24:11,119 --> 00:24:13,519
looks like one species of lichen. You shine the black

481
00:24:13,599 --> 00:24:15,200
light on there, and all of a sudden, you notice

482
00:24:15,240 --> 00:24:19,440
there's fifteen different species of lichens because they're all different chemically.

483
00:24:19,559 --> 00:24:22,599
Speaker 1: Yeah, that's a really good use of it. It's a

484
00:24:22,640 --> 00:24:25,720
lot you said, A lot of stuff is fluorestas under

485
00:24:25,799 --> 00:24:28,079
UV here, much more so than especially in a place

486
00:24:28,079 --> 00:24:28,680
like a desert.

487
00:24:29,160 --> 00:24:31,640
Speaker 2: Yeah, exactly. So if you shine a black light around

488
00:24:31,640 --> 00:24:34,720
in the desert, you don't see much other than minerals

489
00:24:34,720 --> 00:24:37,559
because all of the plants are getting full sun, they

490
00:24:37,559 --> 00:24:40,079
have to have a lot of protection from ultraviolet, so

491
00:24:40,079 --> 00:24:43,000
they have that thick cuticle. And part of what those

492
00:24:43,319 --> 00:24:45,920
chemicals and the cuticle do is they stop the ultra

493
00:24:46,000 --> 00:24:49,160
violet light because the ultra violet will just dnature the DNA.

494
00:24:49,359 --> 00:24:50,480
Speaker 1: They're UV blockers.

495
00:24:50,799 --> 00:24:54,039
Speaker 2: Yeah, but then when you're in a deep rainforest, then

496
00:24:54,519 --> 00:24:57,960
very little UV reaches the ground, so plants don't need

497
00:24:58,000 --> 00:25:01,920
any like UV protections. So that may that everything is

498
00:25:02,079 --> 00:25:06,400
really fluorescent. And you know, the chlorophyll fluoresces this deep

499
00:25:06,680 --> 00:25:10,799
blood red. It's a super beautiful shade of red. And

500
00:25:10,839 --> 00:25:13,440
then you know a lot of the insects, especially like

501
00:25:13,680 --> 00:25:18,000
orb weavers and crab spiders, they fluoresce really bright. And

502
00:25:18,039 --> 00:25:21,680
then about ten percent of mushrooms are super fluorescent as well.

503
00:25:21,759 --> 00:25:23,720
So a lot of times we'll run a black light

504
00:25:23,759 --> 00:25:26,920
over the table at a fungus fair and the rusolla

505
00:25:26,960 --> 00:25:31,839
table always lights up like crazy. Uh, they just have

506
00:25:31,920 --> 00:25:35,400
some kind of chemicals in them. Any anything that's a

507
00:25:35,400 --> 00:25:39,279
purple rusola will look electric blue black light, and then

508
00:25:40,480 --> 00:25:44,279
hyphalomas light up like crazy. And then some stuff doesn't

509
00:25:44,319 --> 00:25:46,359
light out very much, but the light you do get

510
00:25:46,440 --> 00:25:50,440
looks really cool, like silosity only the gill edges light

511
00:25:50,519 --> 00:25:52,200
up and a little bit of the stem, and that's

512
00:25:52,240 --> 00:25:57,319
probably the beta carbulines in them. But carbilines, beta carbulines

513
00:25:57,400 --> 00:26:01,920
are molecules. A lot of them are m a O inhibitors.

514
00:26:01,960 --> 00:26:03,839
So you have an enzyme in your body, it's called

515
00:26:03,960 --> 00:26:05,680
m a O and if you inhibit the m a

516
00:26:05,759 --> 00:26:08,880
O and then a lot of chemicals don't break down.

517
00:26:09,160 --> 00:26:11,720
So the m O inhibitor is what's in the ayahuasca

518
00:26:11,759 --> 00:26:15,200
vine that makes the d M t orally active. But

519
00:26:15,440 --> 00:26:17,599
you know, these chemicals are pretty common in nature, Like

520
00:26:17,680 --> 00:26:20,160
that's the chemicals that make a scorpion light up and

521
00:26:20,240 --> 00:26:24,079
ultra violet light. Beta beta carbal carbilins. Yeah, and so what's.

522
00:26:23,920 --> 00:26:27,599
Speaker 1: The connection between beta carbalings any m a O so.

523
00:26:27,680 --> 00:26:30,440
Speaker 2: Beta carbalines, If you eat them, they inhibit m a

524
00:26:30,519 --> 00:26:33,720
O for a f they are MAO inhibitors, So you

525
00:26:33,759 --> 00:26:35,720
have m a O in your body. And that's just

526
00:26:35,799 --> 00:26:38,880
something that breaks down. You know a lot of things,

527
00:26:39,720 --> 00:26:43,240
you know, including psychoactive substances. So if you eat pure

528
00:26:43,359 --> 00:26:46,079
d MT, nothing will happen unless you take an ma

529
00:26:46,079 --> 00:26:49,799
AO inhibitor and then and then you get the psychedelic effent.

530
00:26:50,160 --> 00:26:53,519
Speaker 1: So the is beta carbaling. Is that probably what's in

531
00:26:53,720 --> 00:26:55,319
the paganem harmala.

532
00:26:55,440 --> 00:27:00,160
Speaker 2: Yeah, they have harmine, those are a few other So

533
00:27:00,240 --> 00:27:00,640
it's a.

534
00:27:00,559 --> 00:27:02,240
Speaker 1: Class of compounds basically.

535
00:27:02,559 --> 00:27:06,480
Speaker 2: And then those things are super fluorescent. Like if you

536
00:27:06,559 --> 00:27:09,039
take an ayahuasca vine and cut into it and just

537
00:27:09,039 --> 00:27:10,519
find the black lane on it, you can see the

538
00:27:10,599 --> 00:27:14,440
beta carbilines in there. And if you have like extracted

539
00:27:14,519 --> 00:27:19,000
crystals from the penguam harmala, they're super super fluorescent and

540
00:27:19,039 --> 00:27:20,440
they look really beautiful.

541
00:27:20,480 --> 00:27:23,799
Speaker 1: So the Banistereopsis has a lot of big beta carblines exactly.

542
00:27:23,839 --> 00:27:26,319
And then the DMT is in the Pellicorea or the.

543
00:27:26,319 --> 00:27:31,519
Speaker 2: Psychotria psychotria or around here they use diplopteris more than psychotria.

544
00:27:31,599 --> 00:27:34,079
Speaker 1: What is diplopterus another rubiac thing?

545
00:27:34,519 --> 00:27:39,680
Speaker 2: Yeah, well no, Diplopterus lung giolata is in the malpiggy Aca.

546
00:27:40,319 --> 00:27:43,359
Oh it's got those really cool flowers.

547
00:27:44,240 --> 00:27:47,079
Speaker 1: I have not seen flowers on any of the banistereopses

548
00:27:47,119 --> 00:27:47,880
that I saw.

549
00:27:47,880 --> 00:27:51,039
Speaker 2: Or yeah they're not. You don't really see the flowers

550
00:27:51,079 --> 00:27:53,920
very often because they're usually way up in the canopy.

551
00:27:54,559 --> 00:27:58,559
But I got some really cool photos of the flowers

552
00:27:59,519 --> 00:28:02,359
when I was visiting a farm in Hawaii, somebody was

553
00:28:02,400 --> 00:28:07,680
growing a whole bunch of the Diplopteris. And when I

554
00:28:07,720 --> 00:28:10,079
was in Colombia a few months back, we got some

555
00:28:10,160 --> 00:28:15,079
really cool malpiggy aca flowers. But yeah, they those things

556
00:28:15,079 --> 00:28:18,720
they got like five petals and they're just beautiful, distinctive

557
00:28:18,799 --> 00:28:20,039
flowers they've got.

558
00:28:20,240 --> 00:28:23,119
Speaker 1: Yeah, all the malepigs have those prominent I think they're

559
00:28:23,160 --> 00:28:25,680
oil glands at the base of the flower. They look

560
00:28:25,759 --> 00:28:26,720
like little teeth.

561
00:28:27,880 --> 00:28:30,920
Speaker 2: Yeah. Yeah, they looks like nothing else. But if you

562
00:28:30,920 --> 00:28:33,440
look up my photos on I Naturalist, I got really

563
00:28:33,559 --> 00:28:37,319
nice focused decked photos on a black background. And then

564
00:28:37,359 --> 00:28:43,319
there's some definitely some toxinomic confusion about these ayahuasca plants

565
00:28:43,799 --> 00:28:48,279
because you know, most people they call it diplopteris. What's

566
00:28:48,319 --> 00:28:49,000
the common name.

567
00:28:49,039 --> 00:28:53,240
Speaker 1: They've got samorrow like fruits. They look like maple fruits. Jesus,

568
00:28:53,960 --> 00:28:56,680
let me see if I can find your observation of filters,

569
00:28:56,759 --> 00:29:01,839
Alan Rockefeller. We should talk about that new species. What

570
00:29:02,039 --> 00:29:05,000
is a possibly new species of silasso be that you

571
00:29:05,119 --> 00:29:06,359
found up in the Permo too.

572
00:29:07,000 --> 00:29:10,799
Speaker 2: Yeah, I mean this area is really diverse for silasib

573
00:29:12,319 --> 00:29:14,920
We got we saw a beautiful cluster of Silasi B

574
00:29:15,079 --> 00:29:17,720
young Genzis the other day. So that's one that was

575
00:29:17,720 --> 00:29:20,720
described from the youngest region of Bolivia, and it's the

576
00:29:20,759 --> 00:29:23,880
main one that grows directly from wood out here. And

577
00:29:23,920 --> 00:29:27,160
then we've been seeing a bunch of Silasi by hoogchigini

578
00:29:27,240 --> 00:29:30,759
i the sharpest nipple, the one with a really sharp

579
00:29:30,839 --> 00:29:33,240
nipple and kind of a stem that's really dark in

580
00:29:33,319 --> 00:29:37,599
color and slowly expands towards the base. Donalin turns out

581
00:29:37,599 --> 00:29:40,240
to be really closely related to silasap mexicana, so it

582
00:29:40,279 --> 00:29:44,599
has a really strong cucumber oder. And then we typically

583
00:29:44,599 --> 00:29:47,400
see a lot of silasib moserai, which is a lower

584
00:29:47,519 --> 00:29:50,880
elevation Zapata chorum relative. I don't think we've seen any

585
00:29:50,920 --> 00:29:54,039
of this trip, but where we're going next week it's

586
00:29:54,119 --> 00:29:57,480
it's super common over there. And then we saw some

587
00:29:57,519 --> 00:30:00,200
silasab Zappa de korum in a few places, which is

588
00:30:00,240 --> 00:30:05,680
the most potent wild silasity that's known. Another landslide mushroom

589
00:30:06,200 --> 00:30:09,240
that has the really thick stem and can get really big.

590
00:30:09,359 --> 00:30:12,200
They can be like a foot tall sometimes, but you

591
00:30:12,400 --> 00:30:14,920
usually see them like near landslides or creeks.

592
00:30:15,559 --> 00:30:20,200
Speaker 1: They need that landfall to basically create a fresh open

593
00:30:20,480 --> 00:30:22,039
substrate for them to fruit in.

594
00:30:22,440 --> 00:30:25,440
Speaker 2: They don't need it, but they do much better when

595
00:30:25,799 --> 00:30:27,960
they have it. So I think it just kind of

596
00:30:28,079 --> 00:30:30,839
changes how how the different You know, when you have

597
00:30:30,880 --> 00:30:33,559
a landslide, you know, it turns a whole bunch of

598
00:30:33,640 --> 00:30:37,599
organic material in and it changes, you know, the dynamics

599
00:30:37,599 --> 00:30:39,720
and the competition, and all of a sudden, the species

600
00:30:39,759 --> 00:30:44,160
like silosity several lessons and zapat decorum can really easily

601
00:30:44,200 --> 00:30:48,000
outcompete all the other fungi when you have disturbed grounds.

602
00:30:48,279 --> 00:30:52,480
Several lessons is another one that we've we've been seeing

603
00:30:52,519 --> 00:30:56,519
around over by the caves. That's a larger one, right,

604
00:30:56,599 --> 00:30:59,079
like the ones that we saw this trimp were kind

605
00:30:59,079 --> 00:31:02,880
of small, but they can get really big. They can

606
00:31:02,920 --> 00:31:05,359
be like five inches across that can grow in clusters

607
00:31:05,359 --> 00:31:07,400
of one hundred if they have a lot of substrate.

608
00:31:08,960 --> 00:31:12,160
But that's another one that's kind of related to Mexicana

609
00:31:12,200 --> 00:31:15,960
and has the really strong cucumber roder and then the

610
00:31:16,079 --> 00:31:18,519
Zappa tachorum ones. You know, they kind of smell a

611
00:31:18,640 --> 00:31:22,319
cucumber and radish at the same time. But then a

612
00:31:22,319 --> 00:31:24,240
couple of days ago we went up to thirty five

613
00:31:24,319 --> 00:31:28,640
hundred meters elevation, so up you know, above eleven thousand feet,

614
00:31:28,920 --> 00:31:32,559
and the plants up there were completely different than the

615
00:31:32,599 --> 00:31:34,400
fungi were completely.

616
00:31:33,839 --> 00:31:37,400
Speaker 1: Dire were I noticed many more affinities with temperate zone

617
00:31:37,680 --> 00:31:38,720
plants up there.

618
00:31:38,960 --> 00:31:41,759
Speaker 2: Yeah, it gets cold up there. It never snows, but

619
00:31:42,359 --> 00:31:45,000
it's gets kind of close sometimes.

620
00:31:45,279 --> 00:31:48,599
Speaker 1: So twelve thousand foot elevation at zero degrees latitude, they

621
00:31:48,599 --> 00:31:51,519
were roughly zero degrees latitude. Maybe it was like zero

622
00:31:51,559 --> 00:31:53,079
point five south.

623
00:31:53,279 --> 00:31:55,720
Speaker 2: Hey, we might be about one and a half degrees

624
00:31:56,079 --> 00:32:01,960
around here. But yeah, it's uh, super unique habitat. And

625
00:32:02,079 --> 00:32:03,960
one of the most common things we solved there was

626
00:32:04,000 --> 00:32:08,680
silasab and so these things they looked a lot like

627
00:32:08,960 --> 00:32:13,680
Silasi be zepticorum, but in this they grew more like

628
00:32:14,039 --> 00:32:17,160
in the habitat of Silasi by molecula. So Silosa by

629
00:32:17,240 --> 00:32:22,039
maleucula described from Mexico at really high elevation, and so

630
00:32:22,119 --> 00:32:25,640
it's a landslide mushroom that really likes these high elevation

631
00:32:25,920 --> 00:32:26,960
volcanic soils.

632
00:32:27,039 --> 00:32:29,599
Speaker 1: Do you think it was molecula.

633
00:32:29,079 --> 00:32:32,720
Speaker 2: No, because the stem texture was different. So silosavy millercola

634
00:32:32,880 --> 00:32:36,640
has the same stem texture as several lessons, where the

635
00:32:36,680 --> 00:32:41,000
bottom half has these kind of rough band squamulose bands

636
00:32:41,039 --> 00:32:44,680
of mycillium, and then the top half is prurunos with

637
00:32:44,759 --> 00:32:49,160
the callosastidia, and so the silasav mallercola has that same

638
00:32:49,240 --> 00:32:56,440
stem texture. What are colossdia our cells that are bottle

639
00:32:56,440 --> 00:32:58,160
shaped and they're on the stem.

640
00:32:58,599 --> 00:33:00,799
Speaker 1: What is there? No one? What is the function?

641
00:33:01,160 --> 00:33:02,960
Speaker 2: I don't think anybody knows the function.

642
00:33:03,200 --> 00:33:04,359
Speaker 1: But they're not reproductive.

643
00:33:04,839 --> 00:33:08,039
Speaker 2: No, the only reproductive cells are the basidia. That's what

644
00:33:08,119 --> 00:33:11,359
makes the spores and the gills. But mushrooms, not all

645
00:33:11,400 --> 00:33:14,720
of them, but many mushrooms are covered in substidia, and

646
00:33:14,759 --> 00:33:17,960
they're kind of sometimes they're shaped like bottles, like a

647
00:33:17,960 --> 00:33:21,440
coke bottle, or sometimes they're like larger or more inflated,

648
00:33:21,640 --> 00:33:24,559
or shaped like real sharp like a harpoon. But these

649
00:33:24,599 --> 00:33:27,599
cells are just all over the gills sometimes the top

650
00:33:27,640 --> 00:33:27,880
of the.

651
00:33:27,839 --> 00:33:33,880
Speaker 4: Cat, so kilosastidia the gill edge, callosastidia on the stem,

652
00:33:34,880 --> 00:33:38,880
frosastidia on the gill faces, pylosistidia on the top of

653
00:33:38,920 --> 00:33:40,079
the top of the cat.

654
00:33:41,480 --> 00:33:44,759
Speaker 1: But the carlosstidia. All these cells could be diagnostic.

655
00:33:45,079 --> 00:33:47,279
Speaker 2: Yeah, they're all really diagnostic. If you're trying to figure

656
00:33:47,279 --> 00:33:49,200
out what you have because you know a lot of

657
00:33:49,720 --> 00:33:53,720
little brown mushrooms. They look pretty much pretty similar, and

658
00:33:53,839 --> 00:33:56,519
once you get really familiar with them, you can tell

659
00:33:56,559 --> 00:33:59,640
them apart without a microscope. Until you really know them well,

660
00:34:00,440 --> 00:34:02,599
you need a microscope to tell a lot of these things.

661
00:34:02,599 --> 00:34:07,200
Speaker 1: And if people might have bioways, say this silosophy species,

662
00:34:07,400 --> 00:34:10,039
this new one, was there any effect that you heard

663
00:34:10,199 --> 00:34:11,320
people talking about or what?

664
00:34:11,840 --> 00:34:15,719
Speaker 2: Yeah, so silosity sections Zapaticorum is a pretty diverse section,

665
00:34:15,880 --> 00:34:18,159
and all the species in that section tend to be

666
00:34:18,199 --> 00:34:21,079
pretty potent, so they're all quite a bit more potent

667
00:34:21,159 --> 00:34:21,960
than kubensus.

668
00:34:22,880 --> 00:34:25,440
Speaker 1: What were the comments, what were the what was the

669
00:34:25,440 --> 00:34:27,280
commentary like that people described?

670
00:34:29,440 --> 00:34:31,800
Speaker 2: I didn't really ask for a lot of details, but

671
00:34:32,760 --> 00:34:35,320
I know, I know a few people definitely tried them

672
00:34:35,679 --> 00:34:40,119
and they said they they said that they definitely felt

673
00:34:40,119 --> 00:34:42,760
something and they didn't you know, they said that it

674
00:34:42,800 --> 00:34:44,559
worked and they didn't have to eat a whole lot

675
00:34:44,599 --> 00:34:49,079
of them. So yeah, they're definitely pretty strong.

676
00:34:49,320 --> 00:34:51,760
Speaker 1: But either way, these things are up there decomposing and

677
00:34:51,960 --> 00:34:55,239
just growing in this describe what the habitat was like.

678
00:34:55,320 --> 00:34:59,320
It was it was dominated by this tree Esclonium or tilioides.

679
00:34:59,840 --> 00:35:01,760
You and then there was a little shrub that I

680
00:35:01,800 --> 00:35:05,239
thought was more tasty before I could before I should

681
00:35:05,280 --> 00:35:07,280
have known from the spines that had that it was

682
00:35:07,599 --> 00:35:10,840
rose family rose asy, but it was Hesperomile's and two sofolia,

683
00:35:11,440 --> 00:35:13,840
and those were like the two dominant woody plants there.

684
00:35:14,760 --> 00:35:17,440
Speaker 2: Don one was so cool. I love the flowers of that.

685
00:35:17,880 --> 00:35:19,559
Speaker 1: Yeah, they were fucking wild man.

686
00:35:19,760 --> 00:35:21,400
Speaker 2: Yeah, like nothing I ever seen before.

687
00:35:21,599 --> 00:35:24,519
Speaker 1: Multiple stamens, little nectar disk style in the center of

688
00:35:24,760 --> 00:35:28,599
five distinct petals. But the weirdest is up where this

689
00:35:28,880 --> 00:35:31,440
pilosophy was growing was.

690
00:35:31,360 --> 00:35:35,519
Speaker 2: Like a habitat because they were just under the Peramo.

691
00:35:35,719 --> 00:35:38,119
So we wanted to go visit the Paramo, but we

692
00:35:38,159 --> 00:35:40,519
couldn't drive all the way up there because the road

693
00:35:40,599 --> 00:35:43,599
stopped before we got to the paramouth. So we you know,

694
00:35:43,760 --> 00:35:45,920
parked and walked a couple of miles up the hill

695
00:35:46,559 --> 00:35:48,719
to get to the paramot. And on the way there

696
00:35:48,880 --> 00:35:51,760
is where we saw the most fungal diversity. And so

697
00:35:51,760 --> 00:35:53,760
there were kind of like these little patches of forest,

698
00:35:53,800 --> 00:35:56,719
and being so high elevation, it wasn't very tall trees.

699
00:35:56,760 --> 00:35:59,280
They were like a little bigger than shrubs, but you know,

700
00:35:59,440 --> 00:36:02,239
maybe twenty feet tall. Most of them, but you can

701
00:36:02,320 --> 00:36:04,360
still get under there and have a lot of leaf litter.

702
00:36:04,760 --> 00:36:06,880
Speaker 1: And there was a groundcover though too. There was that

703
00:36:07,480 --> 00:36:10,280
there was a rose family member which was let me

704
00:36:10,280 --> 00:36:12,360
see if I can pull it up really quick, I forget.

705
00:36:12,400 --> 00:36:15,239
It looked like a little almost like in Aquina with

706
00:36:15,280 --> 00:36:17,119
these kind of peltate leaves, but it was acting like

707
00:36:17,159 --> 00:36:23,880
a groundcover al camia or bagiolata or al camilla or baguolata.

708
00:36:24,239 --> 00:36:26,199
There was so much good shit, I mean it was.

709
00:36:26,239 --> 00:36:26,880
Speaker 2: It took us.

710
00:36:27,039 --> 00:36:29,920
Speaker 1: It took me six hours to go two miles out

711
00:36:29,960 --> 00:36:31,000
and two miles.

712
00:36:30,679 --> 00:36:32,400
Speaker 2: Back, and that was going fast.

713
00:36:32,800 --> 00:36:35,440
Speaker 1: Yeah, that was like not taking as much time as

714
00:36:35,480 --> 00:36:37,760
I would have liked to look at everything and observe

715
00:36:37,840 --> 00:36:42,360
and take notes and observe it, and shit, what the

716
00:36:42,400 --> 00:36:45,559
fuck else, let's see what else did we see? That

717
00:36:45,679 --> 00:36:49,920
whole habitat was nuts. There was so much air casey, Yeah,

718
00:36:50,000 --> 00:36:56,400
tons of air casey. There was a siretto stemma. There

719
00:36:56,480 --> 00:36:59,880
was diister rig or dice, yeah, dister rig what is it?

720
00:37:00,320 --> 00:37:02,400
Let me get somebody. I'm gonna fuck these up. I'm

721
00:37:02,400 --> 00:37:05,000
like trying to hold too much.

722
00:37:04,840 --> 00:37:07,400
Speaker 3: In Iceterigma as one of the most beautiful flowers that

723
00:37:07,400 --> 00:37:09,639
we see down at low elevations and.

724
00:37:09,639 --> 00:37:12,079
Speaker 1: Pet yeah, and most of them are epiphytes. We saw

725
00:37:12,119 --> 00:37:16,880
those Dieisterigma near the river here. That was I mean

726
00:37:16,960 --> 00:37:19,280
it was like a ten foot long pendant.

727
00:37:19,519 --> 00:37:23,760
Speaker 2: Oh yeah, just like hanging down with tiny white berries.

728
00:37:23,800 --> 00:37:26,519
Speaker 1: The notable thing about it is unlike most air casey flowers,

729
00:37:26,519 --> 00:37:30,239
that's only had four corolla lobes, not five. There was

730
00:37:30,280 --> 00:37:35,840
Gultheria mrsinoides up there, Gultheria erect the vaccinium I think

731
00:37:35,880 --> 00:37:39,519
it was Flora bundum. There was a really cool epify.

732
00:37:39,880 --> 00:37:42,360
Half the ship is epiphytic, if not more, even in

733
00:37:42,440 --> 00:37:44,920
the parama. All the all the airicacious stuff, all the

734
00:37:44,920 --> 00:37:47,880
air casey down here is epiphytic. Up there, there were

735
00:37:48,000 --> 00:37:50,800
a couple of shrubs and then a few epiphytes. But

736
00:37:51,199 --> 00:37:55,800
some of these epiphytes had big woody, uh tuberous roots

737
00:37:55,880 --> 00:37:58,159
even though they were epiphytes still, which was crazy. You

738
00:37:58,280 --> 00:37:59,920
just see like this will looked like a big base

739
00:38:00,039 --> 00:38:04,559
ball sized gull hanging off of this vining thing that

740
00:38:04,760 --> 00:38:06,920
was not even a vine. It was like it's like

741
00:38:07,000 --> 00:38:10,000
literally like a shrub that's growing on another tree, but

742
00:38:10,079 --> 00:38:13,800
it's growing kind of leggy uh spherro sperm and bucks

743
00:38:13,840 --> 00:38:17,360
of folium with the bright purple little blueberry fruits was

744
00:38:17,400 --> 00:38:20,960
growing down below. But most of this stuff is adapted

745
00:38:21,000 --> 00:38:26,880
to hummingbird pollination. I was not expecting so many members

746
00:38:26,880 --> 00:38:28,960
of Eric Casey up here. It was fucking nuts. There

747
00:38:29,000 --> 00:38:32,760
was that azarella to pedunculata that was abundant as a

748
00:38:32,760 --> 00:38:37,280
groundcover that was growing with the silossope. Let's see what

749
00:38:37,320 --> 00:38:40,639
the hell else? I mean, it's overwhelming. That's why I

750
00:38:40,760 --> 00:38:42,719
like when when you're doing these trips, I feel like

751
00:38:43,920 --> 00:38:45,960
you because you want to use every day to go out,

752
00:38:46,000 --> 00:38:47,920
but you need. For me, I need like a day

753
00:38:48,320 --> 00:38:50,480
off every five days to process stuff.

754
00:38:51,239 --> 00:38:56,360
Speaker 2: Yeah, to get to do a good job with my photos,

755
00:38:56,400 --> 00:38:58,320
I need as much time as I spend out in

756
00:38:58,360 --> 00:39:00,840
the field in front of the computer just to process

757
00:39:00,880 --> 00:39:04,039
all the photos, get everything up identified and uploaded. And

758
00:39:04,079 --> 00:39:06,400
you never really have that much time because we're usually

759
00:39:06,480 --> 00:39:08,239
out for six to eight hours every day and you

760
00:39:08,280 --> 00:39:10,079
don't have six to eight hours on the computer in

761
00:39:10,119 --> 00:39:13,599
the evening, so it all piles up. But that's okay.

762
00:39:13,719 --> 00:39:16,719
What I do now is every time I see something interesting,

763
00:39:16,760 --> 00:39:18,800
I'll always take a quick cell phone photo and then

764
00:39:18,800 --> 00:39:21,840
I'll make the igh naturalist observation right there, right right

765
00:39:21,880 --> 00:39:24,519
while I'm standing there. You don't forget, Yeah, that way,

766
00:39:24,559 --> 00:39:26,519
I don't forget. And then you have that notes field,

767
00:39:26,559 --> 00:39:28,400
so I can add a whole bunch of notes. And

768
00:39:28,760 --> 00:39:30,519
you know, if you just take pictures of something, you're

769
00:39:30,559 --> 00:39:33,679
gonna forget what it tasted like, what it smelled like,

770
00:39:34,199 --> 00:39:37,920
the nearby trees, the textures, all anything that doesn't come

771
00:39:37,920 --> 00:39:39,760
through in the photo. You're gonna forget all that stuff.

772
00:39:39,760 --> 00:39:43,559
But if I make the observation right there, then you know,

773
00:39:43,679 --> 00:39:46,119
you put all that in the notes. And then if

774
00:39:46,159 --> 00:39:48,480
I never get back to my pictures to process the

775
00:39:48,519 --> 00:39:51,440
photos off my camera, I still have like a cell

776
00:39:51,480 --> 00:39:54,800
phone quality, you know image. And it's also really nice

777
00:39:54,800 --> 00:39:56,400
because you don't have to spend any time at the

778
00:39:56,440 --> 00:39:57,800
end of the day. Just as soon as you get

779
00:39:57,840 --> 00:40:00,320
back to cell phone service, it all just uploads out.

780
00:40:00,360 --> 00:40:03,159
Speaker 1: Do you ever what if in crashes or something while

781
00:40:03,199 --> 00:40:05,719
you're uploading, like you had one hundred things in the

782
00:40:05,800 --> 00:40:08,079
queue to upload, and they don't get it. They don't get.

783
00:40:08,519 --> 00:40:10,679
Speaker 2: That has not happened to me since that day that

784
00:40:10,719 --> 00:40:13,400
we went out and saw that and Celia Revenge, I

785
00:40:13,440 --> 00:40:16,400
was with you. Yeah, I had like that was one

786
00:40:16,400 --> 00:40:18,400
of my most prolific days. I think I had one

787
00:40:18,480 --> 00:40:22,599
hundred and forty I actually observations, and it kept going

788
00:40:22,840 --> 00:40:26,159
slower and slower and slower, and I lost all them.

789
00:40:26,199 --> 00:40:28,639
I still have all of the photos and my Google

790
00:40:29,320 --> 00:40:33,199
Google Photos, but they don't have GPS tags on them,

791
00:40:33,239 --> 00:40:35,679
I don't think. So it's just like I don't think

792
00:40:35,719 --> 00:40:36,679
I'll ever go back and up.

793
00:40:36,679 --> 00:40:39,360
Speaker 1: Do you use Google Photos but then you also use

794
00:40:39,440 --> 00:40:41,440
something else I've used to because.

795
00:40:41,199 --> 00:40:42,760
Speaker 2: I used to have a Pixel but now I switched

796
00:40:42,760 --> 00:40:46,719
to Samsung. But I do, and I think I'm full

797
00:40:46,800 --> 00:40:49,400
on my Google storage space. And they want like a

798
00:40:49,440 --> 00:40:51,960
lot of money for them, uh you know, like like

799
00:40:52,039 --> 00:40:54,119
more more than one hundred bucks a year for the

800
00:40:54,159 --> 00:40:56,760
next next tier up. I think I give them like

801
00:40:56,760 --> 00:40:59,519
twenty bucks a year now, which is reasonable. But I

802
00:40:59,519 --> 00:41:01,199
think all to do is going and delete on my

803
00:41:01,320 --> 00:41:02,880
videos a lout of my Google Photos and then I

804
00:41:02,880 --> 00:41:05,480
can use it again. But I really like Google Photos

805
00:41:05,519 --> 00:41:07,920
because you can search it really well, Like you can

806
00:41:07,920 --> 00:41:10,760
search for certain places. You can search for dates. Oh,

807
00:41:10,800 --> 00:41:13,039
it's amazing people and the places.

808
00:41:13,599 --> 00:41:15,760
Speaker 1: So the places thing is so because I'll never remember

809
00:41:15,880 --> 00:41:18,480
dates but I'll remember a place and then I can

810
00:41:18,559 --> 00:41:21,840
just zoom maps. Yeah, phenomenal, but yeah, it's a lot

811
00:41:21,840 --> 00:41:24,599
of money and I don't use all the ship all

812
00:41:24,639 --> 00:41:26,199
the space that I have either.

813
00:41:26,440 --> 00:41:29,599
Speaker 2: Worth it though, But if I used to delete all

814
00:41:29,599 --> 00:41:31,079
my videos because I don't I don't really need my

815
00:41:31,199 --> 00:41:33,320
videos on my Google Photo. But if I delete that,

816
00:41:33,360 --> 00:41:35,480
I'll have a ton of room and then I can

817
00:41:35,519 --> 00:41:36,119
just have all my.

818
00:41:36,280 --> 00:41:38,440
Speaker 1: Back Blaze was the other thing you recommend it though.

819
00:41:38,639 --> 00:41:40,760
Speaker 2: Yeah, the black Blaze is really cool. I did a

820
00:41:40,760 --> 00:41:44,320
lot of research on backup solutions, but you know, unless

821
00:41:44,360 --> 00:41:47,280
you back up your data regularly, you don't really own

822
00:41:47,320 --> 00:41:50,440
your data, you know, one dropped hard drive or fire

823
00:41:50,559 --> 00:41:53,519
or away from losing all your data. So back Blaze

824
00:41:53,559 --> 00:41:55,920
it's really cool. Zipping incident exactly.

825
00:41:56,000 --> 00:41:58,039
Speaker 1: Yeah, live in a Bay area or LA, and it's

826
00:41:58,039 --> 00:42:00,559
a big thing about back Blaze.

827
00:42:00,599 --> 00:42:02,679
Speaker 2: You know, costs seven dollars a month. And then this

828
00:42:02,760 --> 00:42:05,239
program just runs in the background on your computer and

829
00:42:05,320 --> 00:42:08,599
whenever you have Internet, it's just uploading anything that's changed

830
00:42:08,639 --> 00:42:11,079
in the background. So you know, if you have to

831
00:42:11,159 --> 00:42:14,239
make a presentation you don't save, it doesn't matter. It's

832
00:42:14,440 --> 00:42:18,000
automatically uploaded there and like this time I went over.

833
00:42:18,199 --> 00:42:21,599
We went to that remote research station. You know, it's

834
00:42:21,679 --> 00:42:23,599
kind of way out in the jungle, that place.

835
00:42:25,480 --> 00:42:27,599
Speaker 3: Because you can't even drive up to it and park there,

836
00:42:27,800 --> 00:42:30,400
like you drive you drive up and you still got

837
00:42:30,440 --> 00:42:33,519
a hike like fifteen to twenty minutes, and there were jungle.

838
00:42:33,280 --> 00:42:36,239
Speaker 1: Were to get Sarawia species there, which is the Kiwi

839
00:42:36,239 --> 00:42:39,960
family act in eighty Ac were so cool, fucking delicious fruits.

840
00:42:40,079 --> 00:42:43,159
Speaker 2: Yeah. But when we were at Sumac, you know, I

841
00:42:43,199 --> 00:42:45,400
wanted to give a presentation, but I didn't bring my

842
00:42:45,480 --> 00:42:48,119
laptop with me, so I was able just to log

843
00:42:48,159 --> 00:42:50,920
into my back Blaze account and download any file that

844
00:42:51,000 --> 00:42:52,880
was on my laptop. So I was able to download

845
00:42:52,920 --> 00:42:56,400
my Mushroom photography presentation and I was able to give

846
00:42:56,440 --> 00:42:59,639
the photography talk, you know, at that remote research station.

847
00:43:00,480 --> 00:43:03,840
Speaker 1: So when you're basically when we're going out and doing

848
00:43:03,920 --> 00:43:06,440
all this field work, we're just collecting massive amounts of

849
00:43:06,519 --> 00:43:08,639
data and then but it still has to be processed,

850
00:43:08,679 --> 00:43:12,400
turned into barium labels or photos or uploaded that even

851
00:43:12,480 --> 00:43:15,719
like just putting dumb shit on social media so people

852
00:43:15,760 --> 00:43:18,280
can see it and get excited about it. That's still

853
00:43:18,400 --> 00:43:20,760
important at the end. Of the day do you how

854
00:43:20,840 --> 00:43:24,320
much time do you save? Like basically, you go out

855
00:43:24,400 --> 00:43:26,159
on these trips, which is I'm sure is the same

856
00:43:26,199 --> 00:43:28,599
for me, collect a shit ton of data, and then

857
00:43:28,840 --> 00:43:31,199
when you get back, you're processing it for the next

858
00:43:31,679 --> 00:43:33,639
few months, like just going.

859
00:43:33,559 --> 00:43:35,880
Speaker 2: Well more often I just going on another trip and

860
00:43:35,920 --> 00:43:38,320
it never gets processed. But you know, a lot of times,

861
00:43:38,320 --> 00:43:41,199
what I'll do is if it turns out to be

862
00:43:41,320 --> 00:43:44,639
something really cool, either an expert comes along and recognize

863
00:43:44,719 --> 00:43:46,920
it and it was like, wow, this is these are

864
00:43:46,960 --> 00:43:49,519
like the only photos of this organism, then I'll go

865
00:43:49,639 --> 00:43:52,320
back and be like, oh, I do have pictures from

866
00:43:52,320 --> 00:43:54,920
that time, because I take all my photos and just

867
00:43:54,920 --> 00:43:56,639
put them in the lightroom, and that way I can

868
00:43:56,679 --> 00:43:59,719
search by date and in final name and all this

869
00:43:59,760 --> 00:44:01,880
differ stuff. So I can just be like, oh, okay,

870
00:44:01,920 --> 00:44:04,280
I have a few hundred photos of this and process

871
00:44:04,360 --> 00:44:08,880
my images and then you know, I've been using that

872
00:44:08,960 --> 00:44:13,440
label making program and I just printed about three hundred

873
00:44:13,519 --> 00:44:15,559
labels for all the fungry that we collected on here.

874
00:44:15,599 --> 00:44:17,360
Speaker 1: We've got to tell people about that too.

875
00:44:17,559 --> 00:44:20,320
Speaker 2: Yeah, so that you know, it's a Python program that

876
00:44:20,400 --> 00:44:24,079
I wrote almost a year ago now, and I keep

877
00:44:24,159 --> 00:44:26,639
like refining it and making it better. But what I

878
00:44:26,679 --> 00:44:27,679
did just now.

879
00:44:27,599 --> 00:44:29,960
Speaker 1: Oh, I tell everybody what it is. It's images that

880
00:44:30,320 --> 00:44:33,880
mushroom observer dot org forward slash labels.

881
00:44:34,199 --> 00:44:37,920
Speaker 2: Yeah, so images dot mushroom observer dot org slash labels is.

882
00:44:37,960 --> 00:44:41,559
The is called a flask front end. And so the

883
00:44:41,599 --> 00:44:44,679
program I wrote is really a Python program that you

884
00:44:44,760 --> 00:44:45,920
call from the command line.

885
00:44:46,000 --> 00:44:46,719
Speaker 1: What is Python?

886
00:44:46,880 --> 00:44:51,920
Speaker 2: Python's a programming language. But in this case, I made

887
00:44:51,920 --> 00:44:54,039
this little front end for it so it can be

888
00:44:54,079 --> 00:44:55,679
on the web server. So you don't need to know

889
00:44:55,719 --> 00:44:58,440
the command line. You don't have to know any programming

890
00:44:58,519 --> 00:45:01,079
or anything. You just go to this web page and

891
00:45:01,119 --> 00:45:03,960
you type in the I Naturalist number and as soon

892
00:45:04,000 --> 00:45:06,280
as you type it in, then it comes up on

893
00:45:06,320 --> 00:45:09,480
your screen and it shows you what kind of organism,

894
00:45:09,519 --> 00:45:11,400
whether it's a plant or you know, the name of

895
00:45:11,440 --> 00:45:13,679
the organism and the person who observed it. So if

896
00:45:13,679 --> 00:45:17,079
you mistype one of the numbers, you'll notice right away

897
00:45:17,079 --> 00:45:20,000
because you won't recognize the name the user name on there.

898
00:45:21,000 --> 00:45:23,280
But you can just type in, you know, up to

899
00:45:23,400 --> 00:45:25,920
like one hundred different I Naturalist numbers on there and

900
00:45:25,880 --> 00:45:28,480
then hit print labels. And what it does is it

901
00:45:28,519 --> 00:45:31,760
goes into the I Naturalist website using the API, and

902
00:45:31,800 --> 00:45:35,760
it downloads all this information about it. So it downloads

903
00:45:35,760 --> 00:45:40,880
the scientific name, the GPS coordinates, the GPS accuracy, who

904
00:45:41,000 --> 00:45:44,920
observed it, all the observation notes, and then it encodes

905
00:45:44,960 --> 00:45:48,840
the I Naturalist URL in theo QR code and makes

906
00:45:48,880 --> 00:45:51,400
a really nice professional looking printed label.

907
00:45:51,760 --> 00:45:54,239
Speaker 1: So the label, the obarium label ends up having a

908
00:45:54,280 --> 00:45:55,000
QR code on it.

909
00:45:55,039 --> 00:45:59,320
Speaker 2: They all have QR codes. And recently I got a

910
00:45:59,400 --> 00:46:02,519
QR code scanner and they're only like twenty bucks on Amazon,

911
00:46:03,199 --> 00:46:06,039
and you just plug it into the USB port and

912
00:46:06,079 --> 00:46:08,360
then you just point the skin. You know, it's the

913
00:46:08,400 --> 00:46:11,159
same thing, same exact thing people use when they're checking

914
00:46:11,159 --> 00:46:13,760
out at a store, and you pointed it to QR

915
00:46:13,840 --> 00:46:16,800
code and it basically types in the number. The scanner

916
00:46:16,920 --> 00:46:20,719
is basically just an extra USB keyboard and so it

917
00:46:20,800 --> 00:46:23,559
types in the you know, the I natural STRL and

918
00:46:23,639 --> 00:46:26,119
hits enter. So if you've got a whole bunch of

919
00:46:26,159 --> 00:46:28,159
these labels and you want to make a spreadsheet with

920
00:46:28,239 --> 00:46:30,559
everything you have, all you got to do is point

921
00:46:30,559 --> 00:46:32,519
the scanner at every bag and press the trigger and

922
00:46:32,519 --> 00:46:35,239
you can just make you know, really accurate spreadsheet you know,

923
00:46:35,280 --> 00:46:37,480
in just minutes instead of having to type in all

924
00:46:37,519 --> 00:46:38,360
those numbers.

925
00:46:38,360 --> 00:46:40,679
Speaker 1: My question, so if you're's like a lot of bondists,

926
00:46:40,679 --> 00:46:42,920
if you use it, So this is dependent on I'm

927
00:46:42,960 --> 00:46:45,719
using I naturalis, which everybody should do in the first way.

928
00:46:45,760 --> 00:46:48,000
Like all I'm friends with people that shit on it.

929
00:46:48,039 --> 00:46:49,679
I don't know why. It's stupid.

930
00:46:49,679 --> 00:46:51,559
Speaker 2: It's like it's they just don't understand.

931
00:46:51,679 --> 00:46:53,800
Speaker 1: They just don't understand. Like I use it for myself.

932
00:46:53,840 --> 00:46:56,519
I'm not posting for other people. I mean I'm posting

933
00:46:56,519 --> 00:46:58,199
for other people so they can learn or so that

934
00:46:58,199 --> 00:46:59,840
they can have a record or they can have a

935
00:47:00,000 --> 00:47:04,960
photograph of flower morphology. I'll even you know, edit photos

936
00:47:05,119 --> 00:47:07,920
with text showing what part, Like I did that with

937
00:47:07,960 --> 00:47:11,079
that with that fragment Pedium puerci, Like what's the stigma,

938
00:47:11,159 --> 00:47:14,719
what's the anther, what is the staminode, et cetera. In

939
00:47:14,719 --> 00:47:16,800
case anyone's curious, like what the fuck am I looking

940
00:47:16,840 --> 00:47:20,960
at in this complex flower? But uh, but I use

941
00:47:20,960 --> 00:47:22,880
it for my I mean it's it's so useful. It's

942
00:47:22,920 --> 00:47:24,920
such a fucking educational tool and you can map what

943
00:47:25,000 --> 00:47:28,800
you've got. But a lot of people will obscure their coordinates,

944
00:47:28,800 --> 00:47:30,679
like I do with everything because I'm in a lot

945
00:47:30,719 --> 00:47:33,559
of places I don't want people whatever you know, and

946
00:47:33,599 --> 00:47:35,800
then I'll let you or like mad or someone else

947
00:47:36,119 --> 00:47:37,840
be able to look at my location data. If you're

948
00:47:37,840 --> 00:47:40,280
doing that and creating an urbarium file, but your location

949
00:47:40,400 --> 00:47:44,800
data is obscured, could you still create a file or

950
00:47:44,800 --> 00:47:46,960
like a word document and then just go in there

951
00:47:46,960 --> 00:47:49,679
and put the location data in for the herbarium label.

952
00:47:50,039 --> 00:47:52,880
Speaker 2: Yeah. In fact, you can download your own data, and

953
00:47:52,960 --> 00:47:55,840
so if you export ther naturalist data as a CSV,

954
00:47:56,280 --> 00:47:59,559
then it just lows right into Excel and since you're

955
00:47:59,639 --> 00:48:01,719
the user or that's downloading the data, then you can

956
00:48:01,800 --> 00:48:04,719
see all your own obscured coordinates. So you can you

957
00:48:04,760 --> 00:48:05,639
can do it that way.

958
00:48:05,760 --> 00:48:08,639
Speaker 1: How do I translate and Excel file into like a DOCU?

959
00:48:08,639 --> 00:48:10,519
Because I do I print on my REBARM labels on

960
00:48:10,559 --> 00:48:11,239
Google Docs.

961
00:48:12,360 --> 00:48:15,440
Speaker 2: So the way I do it is I just download

962
00:48:15,679 --> 00:48:18,760
only the IGH Naturalist observation number and then I feed

963
00:48:18,760 --> 00:48:23,119
that into my program that makes the labels, and that

964
00:48:23,360 --> 00:48:24,840
that's a good way to do it. But you know

965
00:48:24,880 --> 00:48:27,400
the other thing you can do is download. When you

966
00:48:27,440 --> 00:48:29,760
download your data from IIG Naturalists, you can choose what

967
00:48:30,039 --> 00:48:34,320
fields and so you can choose to have like coordinate

968
00:48:34,440 --> 00:48:39,159
scientific name, common name if you're into those, all sorts

969
00:48:39,199 --> 00:48:40,119
of different.

970
00:48:39,920 --> 00:48:43,400
Speaker 1: Uh in notes too, Like if you get notes on

971
00:48:43,440 --> 00:48:45,320
the observation, that's another good thing to do. If you

972
00:48:45,400 --> 00:48:48,719
make in observations on our naturalists make notes what elevation?

973
00:48:48,840 --> 00:48:52,639
What was the habitat? Like we were the sympatric plant species,

974
00:48:52,679 --> 00:48:53,280
that kind of thing.

975
00:48:53,519 --> 00:48:55,679
Speaker 2: Yeah, absolutely so.

976
00:48:55,760 --> 00:48:57,840
Speaker 1: But if I use your program and I download it,

977
00:48:57,880 --> 00:48:59,880
then what can I what do I get? I get it?

978
00:49:00,000 --> 00:49:04,440
Speaker 2: So all my program does. It takes only the observation number,

979
00:49:05,000 --> 00:49:07,079
and so you just give it the observation number and

980
00:49:07,079 --> 00:49:09,400
it makes the label based on that, and what it

981
00:49:09,400 --> 00:49:11,679
gives you is an RTF file, which is called a

982
00:49:11,800 --> 00:49:15,079
rich text file, and you load that into Microsoft Word

983
00:49:15,320 --> 00:49:17,920
or Microsoft kind of sucks. So it's better to use

984
00:49:18,000 --> 00:49:20,480
like Libre Office, the free open source version of it,

985
00:49:20,519 --> 00:49:22,960
but either way they both work the same. And then

986
00:49:22,960 --> 00:49:25,000
it loads up these nice labels and then you can

987
00:49:25,079 --> 00:49:28,159
just edit that just like you're editing any any document.

988
00:49:28,280 --> 00:49:29,920
Speaker 1: Well, I'll still get all the text that you have,

989
00:49:29,960 --> 00:49:30,239
all the.

990
00:49:30,159 --> 00:49:32,400
Speaker 2: Text you can, like you can change anything before you

991
00:49:32,480 --> 00:49:32,960
hit print.

992
00:49:33,159 --> 00:49:36,960
Speaker 1: Oh cool, okay, great, damn, that's wild. Like but if

993
00:49:36,960 --> 00:49:39,199
you're obscuring location data, then I'll have to go in

994
00:49:39,239 --> 00:49:40,000
and put the.

995
00:49:40,159 --> 00:49:42,480
Speaker 2: Yeah, so if you're obscuring location data, then it goes

996
00:49:42,519 --> 00:49:46,599
in and then it's whenever it prints out the latitude

997
00:49:46,639 --> 00:49:49,000
longitude on your labels, it gives you a plus or

998
00:49:49,039 --> 00:49:52,599
minus just the accuracy, and if you hit obscurer, then

999
00:49:52,639 --> 00:49:57,199
that plus or minus is always twenty thousand meters. And

1000
00:49:57,280 --> 00:49:59,960
so you know, if you don't obscure it, it'll say

1001
00:50:00,199 --> 00:50:02,599
like plus or minus six meters or you know, whatever

1002
00:50:02,599 --> 00:50:06,800
the accuracy is on your GPS coordinates, but yeah, it'll

1003
00:50:06,840 --> 00:50:08,960
be twenty thousand meters. So if you obscure it, I

1004
00:50:09,000 --> 00:50:12,079
could probably change it so it uses an at API

1005
00:50:12,199 --> 00:50:15,840
key instead of going in there anonymously. And that way,

1006
00:50:15,840 --> 00:50:18,559
if you run it as a certain user, you could,

1007
00:50:19,119 --> 00:50:21,199
you know, have it grab there and you.

1008
00:50:21,159 --> 00:50:25,039
Speaker 1: Could give that user access to your location data. Is

1009
00:50:25,079 --> 00:50:26,320
that how it would work or how would it?

1010
00:50:27,280 --> 00:50:27,480
Speaker 4: Yeah?

1011
00:50:27,519 --> 00:50:30,599
Speaker 2: I think so, I think like you can. I know,

1012
00:50:30,679 --> 00:50:32,960
if I go to one of your observations and you've

1013
00:50:33,039 --> 00:50:36,840
obscured it, I still see the exact coordinates because you've

1014
00:50:36,880 --> 00:50:39,480
put my username in there to trust me with the coordinates,

1015
00:50:40,039 --> 00:50:42,320
and so you know, right, now it's just grabbing the

1016
00:50:42,400 --> 00:50:44,440
data as an anonymous user, but I could have it

1017
00:50:44,559 --> 00:50:47,960
log in with like my uh, you know, my username,

1018
00:50:48,000 --> 00:50:50,960
and then it would probably would be able to grab

1019
00:50:51,000 --> 00:50:53,480
the exact coordinates, which is real nice because you you know,

1020
00:50:53,480 --> 00:50:56,440
when you have a something for herbarium, you want to

1021
00:50:56,480 --> 00:50:58,159
be able to see exactly.

1022
00:50:58,239 --> 00:51:00,400
Speaker 1: It's such a great tool though, because I mean, it

1023
00:51:00,480 --> 00:51:02,800
saved so much time for creating your barriers.

1024
00:51:02,840 --> 00:51:05,440
Speaker 2: Oh yeah, Like I just made one hundred and seventeen

1025
00:51:05,519 --> 00:51:07,840
labels and just a couple of minutes. And what I

1026
00:51:07,840 --> 00:51:11,360
did is I just searched all of the fungi that

1027
00:51:11,440 --> 00:51:14,320
I found in Ecuador in the past two weeks, and

1028
00:51:14,360 --> 00:51:16,039
it just real quick gave me a list of one

1029
00:51:16,119 --> 00:51:20,400
hundred and seventeen I naturalist observation numbers, and I just

1030
00:51:20,440 --> 00:51:22,760
pasted that into the script and it made the labels,

1031
00:51:22,760 --> 00:51:24,840
and in just a couple of minutes, I had all

1032
00:51:24,920 --> 00:51:27,599
of the labels. And you know, that would have taken

1033
00:51:27,599 --> 00:51:29,960
me hours to handwrite it out, and I probably would

1034
00:51:29,960 --> 00:51:32,119
have made a couple of mistakes and numbers, and it

1035
00:51:32,400 --> 00:51:35,360
wouldn't have had all my notes and the locations. I mean,

1036
00:51:35,400 --> 00:51:37,440
that would take days if I had tried to write

1037
00:51:37,480 --> 00:51:38,679
all that out by hand.

1038
00:51:38,519 --> 00:51:40,360
Speaker 1: And all this stuff that we're collecting, this will all

1039
00:51:40,400 --> 00:51:42,519
go to Rosa at the herbarium in Keto.

1040
00:51:42,960 --> 00:51:47,039
Speaker 2: Yeah, so everything that we're collecting gets saved and goes

1041
00:51:47,119 --> 00:51:51,400
to the in a bio or barium in Quito, and

1042
00:51:51,559 --> 00:51:55,239
so yeah, I gets saved forever there. And we're going

1043
00:51:55,320 --> 00:51:57,599
to do some DNA bar coding on it too. So

1044
00:51:58,880 --> 00:52:01,960
we're going to a nanopore flow cell and a whole

1045
00:52:02,000 --> 00:52:06,239
bunch of PCR primers and you know, you can sequence

1046
00:52:06,280 --> 00:52:10,639
like nine hundred and sixty mushrooms with with one nanopore

1047
00:52:10,719 --> 00:52:14,519
flow cell. And actually got some primers in the mail

1048
00:52:14,639 --> 00:52:16,719
just a couple of weeks ago. It's a new one

1049
00:52:16,760 --> 00:52:19,159
called g I T S seven. So it's an i

1050
00:52:19,280 --> 00:52:22,239
TS primer, but the G means global and so it's

1051
00:52:22,519 --> 00:52:25,280
really good for fungi that are really hard to sequence,

1052
00:52:25,280 --> 00:52:28,480
but it's also really good for plants. So you can

1053
00:52:28,519 --> 00:52:30,760
see the I S. Yeah, you can see with the

1054
00:52:30,760 --> 00:52:33,639
I TS gene of plants really well with that primer.

1055
00:52:33,679 --> 00:52:35,800
And so you could do the same nanopore protocol that

1056
00:52:35,840 --> 00:52:39,679
we're doing for fungi and just you know, sequenced tons

1057
00:52:39,760 --> 00:52:40,039
of play.

1058
00:52:40,119 --> 00:52:41,800
Speaker 1: But you would just get that would just get the it.

1059
00:52:42,079 --> 00:52:47,119
Speaker 2: S only its that would be a separate PCR. Well

1060
00:52:47,119 --> 00:52:50,119
you can do is something called multiplex PCR. So instead

1061
00:52:50,119 --> 00:52:52,079
of just putting two primers in there, you can put

1062
00:52:52,079 --> 00:52:54,840
a whole pool of primers and then you're amplifying a

1063
00:52:54,840 --> 00:52:59,159
bunch of genes at once, and that that could work

1064
00:52:59,199 --> 00:53:02,840
to get you uh you know, because with fungi, you

1065
00:53:03,000 --> 00:53:06,440
sequence the its gene and just thought one gene can

1066
00:53:06,519 --> 00:53:10,960
identify more than ninety nine percent of fungi to species

1067
00:53:11,000 --> 00:53:13,440
and it does a really good job of separating the

1068
00:53:13,480 --> 00:53:16,599
species out. You know, one percent of the time you

1069
00:53:17,159 --> 00:53:19,360
won't really you know, you have like two fungi with

1070
00:53:19,360 --> 00:53:22,880
the same it won't won't be enough resolution. But it's

1071
00:53:22,920 --> 00:53:26,519
amazing how well it does work. But for plants it's

1072
00:53:26,599 --> 00:53:28,519
a lot more complicated. You kind of have to do

1073
00:53:28,760 --> 00:53:31,400
like four or five genes to get that kind of resolution.

1074
00:53:31,519 --> 00:53:35,440
With plants, gives ITS works. You know, it'll at least

1075
00:53:35,519 --> 00:53:38,400
gets you to species group one hundred percent of the time. Yeah,

1076
00:53:38,800 --> 00:53:42,280
but to really get species level of resolution, you got

1077
00:53:42,320 --> 00:53:45,559
to do matt K and TRN now and a couple

1078
00:53:45,599 --> 00:53:47,639
other ones. But you know, you can do this all

1079
00:53:47,639 --> 00:53:50,039
at home. You just need a PCR machines and primers

1080
00:53:50,079 --> 00:53:51,760
and pipets and a couple of chemicals.

1081
00:53:51,760 --> 00:53:55,039
Speaker 1: Nobody is doing what you're doing though with plants. Who's

1082
00:53:55,079 --> 00:53:59,519
not in academia? Like everyone who's sequencing plants isn't you know,

1083
00:53:59,639 --> 00:54:02,320
is an academia. No one's doing it from this. I

1084
00:54:02,360 --> 00:54:05,079
got to hate this fucking word citizens saience doing it

1085
00:54:05,119 --> 00:54:09,119
from like a citizen science background with plant material?

1086
00:54:09,639 --> 00:54:11,679
Speaker 2: Yeah, or these days we say can be any science

1087
00:54:11,719 --> 00:54:13,400
because we don't care if you're a citizen or not.

1088
00:54:13,719 --> 00:54:16,000
Speaker 1: Right, I mean I'm not even Yeah, I mean it's

1089
00:54:16,039 --> 00:54:16,880
just a stupid word.

1090
00:54:16,920 --> 00:54:20,280
Speaker 2: It's like I think of like I just call it science,

1091
00:54:20,719 --> 00:54:21,519
big citizen.

1092
00:54:21,639 --> 00:54:23,519
Speaker 1: It's like this night, I get this fucking imagery in

1093
00:54:23,519 --> 00:54:26,800
my head like some angry fucking boomer, you know, whining

1094
00:54:26,840 --> 00:54:28,239
about something inconsequential.

1095
00:54:28,320 --> 00:54:29,800
Speaker 2: No, I think I think the right word for it

1096
00:54:29,840 --> 00:54:33,000
is just regular science though, because I mean science. The

1097
00:54:33,000 --> 00:54:35,519
word science doesn't mean that you're getting paid to do

1098
00:54:35,599 --> 00:54:37,840
it or something, or that you have a piece of paper.

1099
00:54:38,119 --> 00:54:39,039
Speaker 1: You and I both have.

1100
00:54:39,039 --> 00:54:42,000
Speaker 2: No piece of a kind of degree science.

1101
00:54:42,239 --> 00:54:44,480
Speaker 1: You and I have no piece of paper. I never

1102
00:54:44,519 --> 00:54:47,639
even got a fucking any kind of college anything.

1103
00:54:48,159 --> 00:54:49,840
Speaker 2: No no, I didn't go to college either.

1104
00:54:51,119 --> 00:54:54,639
Speaker 1: Okay, well that brings me up. I mean, creating this program,

1105
00:54:54,719 --> 00:54:57,199
it's I want to talk about something else we do

1106
00:54:57,320 --> 00:54:59,280
really quick if we want to really quick ten minutes

1107
00:54:59,280 --> 00:55:02,840
when almost fucking again. But everyone's talking shit on AI,

1108
00:55:02,920 --> 00:55:04,559
and I get that there's it's going to be used

1109
00:55:04,599 --> 00:55:07,599
for terrible things. Partially, there's a lot of terrible things,

1110
00:55:07,639 --> 00:55:10,239
but there's also You're one of the few friends that

1111
00:55:10,360 --> 00:55:13,119
I have who's like, really sees a lot of potential

1112
00:55:13,119 --> 00:55:16,000
in it and is always talking about, you know, potential

1113
00:55:16,119 --> 00:55:19,119
uses that I never hear people other people, other friends

1114
00:55:19,119 --> 00:55:21,800
of mind talking about because I think they just don't know,

1115
00:55:21,840 --> 00:55:24,719
they don't see it. But you're very schooled in tech

1116
00:55:24,840 --> 00:55:27,320
and and all this shit, and you're kind of like,

1117
00:55:27,360 --> 00:55:29,519
who I go to for this kind of stuff? What

1118
00:55:29,679 --> 00:55:31,760
is your I guess talk about that. What's your opinion

1119
00:55:31,800 --> 00:55:35,400
on some of the benefits of AI that can that

1120
00:55:35,679 --> 00:55:38,000
people should be trying to use it for?

1121
00:55:38,400 --> 00:55:41,599
Speaker 2: Yeah? Well, you know, like anything AI is terrible and

1122
00:55:41,800 --> 00:55:45,360
awesome at the same time. You know, the terrible part

1123
00:55:45,519 --> 00:55:48,719
is like those stupid AI generated images that are flooding

1124
00:55:48,719 --> 00:55:49,559
social media.

1125
00:55:49,400 --> 00:55:54,719
Speaker 1: Or AI entire AI Instagram profiles where the whole profile

1126
00:55:54,840 --> 00:55:55,199
is fake.

1127
00:55:55,519 --> 00:55:58,400
Speaker 2: Yeah, it's not real. Yeah, that just kind of waste

1128
00:55:58,400 --> 00:56:00,679
people time and it's kind of annoying. And you know,

1129
00:56:00,719 --> 00:56:02,599
it used to be people would like, you know, write

1130
00:56:02,599 --> 00:56:05,000
web pages, and now they can just have AI do it,

1131
00:56:05,000 --> 00:56:07,519
So it fills the web with just this garbage that's

1132
00:56:07,599 --> 00:56:10,920
kind of regurgitated for a million other sources, so that stuff.

1133
00:56:11,000 --> 00:56:13,000
You know, it's kind of annoying, but it's also pretty

1134
00:56:13,039 --> 00:56:16,119
easy to avoid. You know, in the next few years,

1135
00:56:16,159 --> 00:56:19,719
a lot of people's jobs are going to be redundant

1136
00:56:19,719 --> 00:56:22,639
because of AI. And it's already happened to a lot

1137
00:56:22,639 --> 00:56:25,239
of jobs, but you know, in the next few years,

1138
00:56:25,559 --> 00:56:28,599
there'll probably be a lot of unemployed people out there.

1139
00:56:28,920 --> 00:56:30,840
So we're going to definitely need some sort of new

1140
00:56:30,880 --> 00:56:33,559
paradigm now that AI can do. You know, at least

1141
00:56:33,599 --> 00:56:37,760
half of people's jobs for us, How are people going

1142
00:56:37,800 --> 00:56:40,119
to make a living when they you know, when there's

1143
00:56:40,239 --> 00:56:43,920
so many unemployed people because AI has taken all their jobs.

1144
00:56:43,960 --> 00:56:47,159
So that's kind of interesting, and that's happening faster and faster,

1145
00:56:47,239 --> 00:56:50,760
and there's nothing anybody can do stop that. But I

1146
00:56:50,800 --> 00:56:53,880
think there's a lot of really cool things AI can

1147
00:56:53,920 --> 00:56:58,920
do as well. One thing that I really like is

1148
00:56:59,320 --> 00:57:01,719
if you like so you go on I Naturalists and

1149
00:57:01,719 --> 00:57:04,679
it gives you like a guess of three different species,

1150
00:57:05,000 --> 00:57:06,519
and you click on all three of them, and they

1151
00:57:06,559 --> 00:57:10,159
all look pretty similar, but you're like wondering, like, well,

1152
00:57:10,159 --> 00:57:12,400
what's the difference. You can go to like chu GPT

1153
00:57:12,679 --> 00:57:15,480
or perplexity or claud or any of these AI things

1154
00:57:15,519 --> 00:57:19,320
and say what are the physical differences between these different species,

1155
00:57:19,360 --> 00:57:21,719
and it'll spit out a list of all the differences

1156
00:57:22,000 --> 00:57:23,960
that you can use to tell the species apart.

1157
00:57:24,239 --> 00:57:26,079
Speaker 1: So what information is it referencing? A key?

1158
00:57:26,360 --> 00:57:30,440
Speaker 2: So these have indexed all of the publicly available information

1159
00:57:30,519 --> 00:57:34,280
on the Internet, so they basically just downloaded the whole Internet.

1160
00:57:34,840 --> 00:57:39,360
And actually recently Google got caught. They were they went

1161
00:57:39,400 --> 00:57:42,280
to lib gen and they downloaded all of lib gen.

1162
00:57:42,360 --> 00:57:44,840
So they basically pirated every book that's never been up

1163
00:57:46,039 --> 00:57:48,519
and used that to train the AI. And they tried

1164
00:57:48,519 --> 00:57:51,119
to keep it secret, but it came out because they

1165
00:57:51,119 --> 00:57:54,239
got subpoenaed and it came out in the depositions and

1166
00:57:54,280 --> 00:57:56,320
stuff that they did not And so.

1167
00:57:56,760 --> 00:57:58,360
Speaker 1: That would be a good I mean, that would be

1168
00:57:58,400 --> 00:58:01,519
cool if it wasn't Google. Like some kid did that, but.

1169
00:58:01,719 --> 00:58:04,920
Speaker 2: Yeah, exactly, but they're selling it, so they're basically taking

1170
00:58:04,960 --> 00:58:08,159
all this information that people wrote and then they're stealing

1171
00:58:08,199 --> 00:58:11,199
it and selling it for profit. And that's uh, you know,

1172
00:58:11,360 --> 00:58:16,960
piracy on a large corporate scale like that death unethical.

1173
00:58:17,280 --> 00:58:19,920
Speaker 1: Yeah, and it's and it's not like they're making the

1174
00:58:19,960 --> 00:58:22,400
information free or they're doing you know, they're yeah, they're

1175
00:58:22,440 --> 00:58:23,079
they're selling it.

1176
00:58:23,119 --> 00:58:26,039
Speaker 2: They're kind of free, but they're off of this so

1177
00:58:26,280 --> 00:58:29,440
they're very much profiting off of it. So definitely kind

1178
00:58:29,440 --> 00:58:31,840
of unethical. But it also means that you can like

1179
00:58:32,320 --> 00:58:35,119
ask it all these questions and it will answer, you know,

1180
00:58:35,280 --> 00:58:37,920
it can tell you the difference between two different species

1181
00:58:37,960 --> 00:58:41,079
of some obscure genus you've never heard of before.

1182
00:58:40,840 --> 00:58:43,159
Speaker 1: So like chand GPT or deep seek or what would you.

1183
00:58:43,159 --> 00:58:46,199
Speaker 2: Mean all of those? Yeah, deep Seek is kind of cool.

1184
00:58:46,239 --> 00:58:48,639
That's that new Chinese one that everyone's freaking out about.

1185
00:58:48,639 --> 00:58:51,480
And the reason that it's cool is because it shows

1186
00:58:51,519 --> 00:58:54,639
you it's it's steps when it's thinking, so it tells

1187
00:58:54,639 --> 00:58:57,039
you what it's thinking about, and that's kind of cool

1188
00:58:57,239 --> 00:59:00,920
for because it's like, you know, it's tea makes a mistake,

1189
00:59:01,000 --> 00:59:04,079
which happens pretty often you'll you have no insight into

1190
00:59:04,119 --> 00:59:06,519
why it made that mistake. Both deep seek you can

1191
00:59:06,559 --> 00:59:09,039
read it look into its thinking process and you see, oh,

1192
00:59:09,079 --> 00:59:10,679
I see where it went wrong. And then you can

1193
00:59:10,719 --> 00:59:13,280
refine your question to like explain a little bit more

1194
00:59:14,079 --> 00:59:15,559
and you know, I kind of like put it back

1195
00:59:15,559 --> 00:59:19,760
on the right track. But you know, these all of

1196
00:59:19,800 --> 00:59:23,360
these chot bots are really good for programming stuff. Like

1197
00:59:23,400 --> 00:59:25,239
if you write a thousand lines of code and you

1198
00:59:25,320 --> 00:59:28,000
run it and it just errs out because there's some

1199
00:59:28,000 --> 00:59:31,800
some some curly bracket missing. You can spend ninety minutes

1200
00:59:31,920 --> 00:59:34,599
looking for that missing curly bracket, or you can just

1201
00:59:34,639 --> 00:59:37,440
paste that code into chat chpt and ask it where's

1202
00:59:37,440 --> 00:59:39,079
the mistake and it'll just tell you in a couple

1203
00:59:39,119 --> 00:59:41,440
of seconds, like where the mistake is. And it can

1204
00:59:41,480 --> 00:59:43,639
also just write programs some scratch truck. If you've got

1205
00:59:43,760 --> 00:59:47,159
a whole bunch of hig naturalist data, it can like

1206
00:59:47,679 --> 00:59:50,000
you can just say, like here, take this eg naturalist

1207
00:59:50,079 --> 00:59:52,199
data and put it into this form and you can

1208
00:59:52,280 --> 00:59:54,480
just like have a process set and just do all

1209
00:59:54,519 --> 00:59:59,239
sorts of stuff. So really powerful for doing stuff like that.

1210
01:00:00,199 --> 01:00:02,000
Speaker 1: What are some other because you would mentioned a few

1211
01:00:02,000 --> 01:00:03,639
other uses to what are some of the uses that

1212
01:00:03,679 --> 01:00:04,199
people like you.

1213
01:00:04,239 --> 01:00:07,000
Speaker 2: And one other thing that I really like this AI

1214
01:00:07,159 --> 01:00:11,440
stuff for is for recipes because it's index like every

1215
01:00:11,519 --> 01:00:14,519
cookbook and every recipe on the internet, and it knows

1216
01:00:14,559 --> 01:00:17,599
what flavors go together. So one thing I did is

1217
01:00:17,679 --> 01:00:20,199
I just went through my kitchen and I just went

1218
01:00:20,239 --> 01:00:22,559
through my cupboards and just in order read all of

1219
01:00:22,559 --> 01:00:25,440
my ingredients and my cupboard, my fridge and my freezer

1220
01:00:25,760 --> 01:00:28,800
and told CHPT to remember it. And then when I

1221
01:00:28,880 --> 01:00:32,480
want to cook something, I can say like, what's the

1222
01:00:32,480 --> 01:00:35,639
most delicious thing that I can make with the ingredients

1223
01:00:35,639 --> 01:00:37,800
of my cupboard, and it'll like suggest like three or

1224
01:00:37,840 --> 01:00:41,440
four like really awesome dishes. And then you know, I

1225
01:00:41,440 --> 01:00:44,280
can be like, oh, I just got this new ingredient.

1226
01:00:44,400 --> 01:00:47,719
You know what's a really delicious thing that I can

1227
01:00:47,800 --> 01:00:51,280
make from this ingredient? And it'll like kind of go,

1228
01:00:51,400 --> 01:00:53,519
you know, knows exactly what I have in my cupboards

1229
01:00:53,559 --> 01:00:55,519
and knows what spices I have, and it'll make a

1230
01:00:55,559 --> 01:00:58,119
recipe based on that. And then if I'm like, oh,

1231
01:00:58,159 --> 01:01:00,679
I'm out a flower, what kind of substitute, It'll be like, oh,

1232
01:01:00,760 --> 01:01:03,880
you can substitute these other things. And then if it's

1233
01:01:03,920 --> 01:01:07,559
like sometimes I'm like, Okay, make a recipe. It's so

1234
01:01:07,679 --> 01:01:10,920
delicious that it would win a world class cooking competition

1235
01:01:11,199 --> 01:01:13,360
for this dish, and it'll like spice it up with

1236
01:01:13,440 --> 01:01:15,440
all these other things, and I'll take like half these

1237
01:01:15,480 --> 01:01:18,519
congestions and I'll be like, damn, this is good. You know,

1238
01:01:18,639 --> 01:01:19,480
is exactly what.

1239
01:01:19,480 --> 01:01:23,519
Speaker 1: Recipe that's like A that's like a PG. I would

1240
01:01:23,599 --> 01:01:26,599
probably be a maybe I could probably think of some

1241
01:01:26,920 --> 01:01:30,280
heinous shit there. Oh yeah, be ridiculous shit. What about

1242
01:01:30,280 --> 01:01:33,559
like for educational purposes, because I mean the thing I'm like,

1243
01:01:33,599 --> 01:01:35,880
this is going to be used for terrible ship, no doubt.

1244
01:01:36,239 --> 01:01:40,239
Speaker 3: Just like like a lot of guardrails on it.

1245
01:01:40,320 --> 01:01:42,119
Speaker 2: Like if you ask it like you know, how to

1246
01:01:42,159 --> 01:01:44,639
make a bomb, or you know, ask it to say

1247
01:01:44,639 --> 01:01:48,239
something racist, it'll be like, no, I'm not doing in general.

1248
01:01:48,320 --> 01:01:50,639
With deep Seek, they didn't put those guardrails in. They

1249
01:01:50,719 --> 01:01:52,960
put different guardrails. So if you ask you Seek like

1250
01:01:53,000 --> 01:01:55,639
what happened in tannam and Square, it'd be like, I

1251
01:01:55,679 --> 01:01:58,320
don't think I want to discuss that today. But if

1252
01:01:58,360 --> 01:01:59,920
you ask it like how to make a bomb, it'll

1253
01:02:00,039 --> 01:02:02,559
tell you exactly, but exactly how to do that.

1254
01:02:02,599 --> 01:02:04,440
Speaker 1: But with Ai though, I mean the point is, though

1255
01:02:04,440 --> 01:02:07,679
it's gonna the corporate overlords will no doubt use it

1256
01:02:07,760 --> 01:02:11,679
for some terrible things. What are some but there's also

1257
01:02:11,760 --> 01:02:15,400
this benefit while the ship is thinking that it can

1258
01:02:15,440 --> 01:02:20,159
be used for autodidactic purposes and yeah, imation.

1259
01:02:20,079 --> 01:02:23,760
Speaker 2: And the one that I use most often is just Perplexity,

1260
01:02:23,840 --> 01:02:25,960
And that's another one of those free chot bots. But

1261
01:02:26,000 --> 01:02:31,239
it's really good. It's like really really relevant information. They're

1262
01:02:31,280 --> 01:02:34,400
like current stuff, so you can say, like how much

1263
01:02:34,519 --> 01:02:38,599
rain or like what part of what's the place within

1264
01:02:38,679 --> 01:02:41,320
fifty miles that got the most rain in the past week,

1265
01:02:41,400 --> 01:02:42,840
and then you know where to go to find the

1266
01:02:42,840 --> 01:02:46,800
most mushrooms because it knows current stuff. But it's really

1267
01:02:46,840 --> 01:02:48,880
good at just explaining stuff to you. So like, you know,

1268
01:02:49,039 --> 01:02:50,960
three years ago, if I ever had a question, like

1269
01:02:50,960 --> 01:02:54,119
I'm just you know, just walking around our one, some

1270
01:02:54,159 --> 01:02:56,239
thought pops into my head. I'm like, oh, I wonder

1271
01:02:56,320 --> 01:02:58,400
like this or that I would have googled and then

1272
01:02:58,440 --> 01:03:00,000
you go to a page and then try to find

1273
01:03:00,079 --> 01:03:01,719
your answer on that web page. But now I just

1274
01:03:01,760 --> 01:03:06,320
ask Perplexity my question and it answers it. But then

1275
01:03:06,360 --> 01:03:08,440
it's got all these little references, so you can see

1276
01:03:08,440 --> 01:03:10,639
where I got it. It'll show you links and then

1277
01:03:10,639 --> 01:03:12,639
you click on the original sur especially if it says

1278
01:03:12,679 --> 01:03:14,880
something you're like, I don't I don't believe that.

1279
01:03:15,039 --> 01:03:17,039
Speaker 3: You can click on the source and then and then

1280
01:03:17,079 --> 01:03:17,760
you're like, oh.

1281
01:03:17,679 --> 01:03:21,360
Speaker 2: Yeah, this is some like woo woo web page written

1282
01:03:21,400 --> 01:03:24,239
by some fake doctor. This is ridiculous and that. But

1283
01:03:24,440 --> 01:03:26,280
or you can be like, oh damn, this is a

1284
01:03:26,320 --> 01:03:27,280
reputable source.

1285
01:03:27,719 --> 01:03:30,119
Speaker 1: So the but because Google will do that too. Now

1286
01:03:30,159 --> 01:03:33,000
sometimes if you ask it something, but it's using Gemini,

1287
01:03:33,119 --> 01:03:35,679
which is and it's not every time where you Google something,

1288
01:03:35,679 --> 01:03:36,159
it'll get you.

1289
01:03:36,159 --> 01:03:38,079
Speaker 2: Done so much of Google. But if you get tired

1290
01:03:38,079 --> 01:03:40,800
of that and you don't want Google to give you

1291
01:03:40,840 --> 01:03:43,320
that AI summary, all you have to do is put

1292
01:03:43,360 --> 01:03:46,159
a swear word into the question and then it doesn't

1293
01:03:46,159 --> 01:03:47,800
do any of the AI stuff and you get the

1294
01:03:47,840 --> 01:03:49,519
old school will starts yourself.

1295
01:03:49,599 --> 01:03:51,880
Speaker 1: Why does it only give you AI on some questions

1296
01:03:51,880 --> 01:03:52,800
and not on others?

1297
01:03:53,119 --> 01:03:54,679
Speaker 2: It just does it when it thinks it know it's

1298
01:03:54,719 --> 01:03:55,199
the answer.

1299
01:03:55,320 --> 01:03:58,039
Speaker 1: Mm hmmm. Yeah, it's weird. So what would you recommend

1300
01:03:58,159 --> 01:04:00,679
then for people if they want to use AI or

1301
01:04:00,719 --> 01:04:03,039
fuck around with it and see what the Some of the.

1302
01:04:03,000 --> 01:04:05,519
Speaker 2: Better it's kind of good to use all of them.

1303
01:04:05,880 --> 01:04:08,320
Speaker 1: Experiment with the deep seek or any of these.

1304
01:04:08,760 --> 01:04:12,039
Speaker 2: Yeah, Like the other day I was I had this

1305
01:04:12,159 --> 01:04:14,519
like long eye Naturalist r L, and it was this

1306
01:04:14,679 --> 01:04:17,800
big long ur L to find all the psilocybin mushrooms.

1307
01:04:17,840 --> 01:04:20,360
So you have like two hundred species of psilocybin mushrooms

1308
01:04:20,400 --> 01:04:23,400
in the world. So I made this long r L

1309
01:04:23,440 --> 01:04:25,679
where I could just point it in any country or

1310
01:04:25,719 --> 01:04:28,480
any state, any like, you know, any given air if

1311
01:04:28,599 --> 01:04:30,199
part of the world, and it would show me all

1312
01:04:30,239 --> 01:04:33,280
the psilocybin mushrooms. But you know it's all in this

1313
01:04:33,559 --> 01:04:36,960
the you know, with species without species and to Dakota

1314
01:04:37,000 --> 01:04:42,360
all that. I wrote a Python script using AI just

1315
01:04:42,400 --> 01:04:44,800
to like, you know, write this real quick script for

1316
01:04:44,880 --> 01:04:46,480
me and something that would have taken me an hour

1317
01:04:46,599 --> 01:04:49,400
to code and debug. You know, it did it in seconds.

1318
01:04:49,400 --> 01:04:53,239
But I asked chut GPT and Perplexity and deep Seek

1319
01:04:53,320 --> 01:04:54,760
just to write the script to give them the same

1320
01:04:54,800 --> 01:04:59,159
prompt and chant GPT. It just did not work. In

1321
01:04:59,239 --> 01:05:01,760
Perplexity did not work, and with the deep seque it

1322
01:05:01,840 --> 01:05:05,119
just worked on the first try. But it was real

1323
01:05:05,239 --> 01:05:07,639
nice because it just takes apart the URL tells me

1324
01:05:07,679 --> 01:05:10,239
exactly what it's looking for and lets me edit it

1325
01:05:10,360 --> 01:05:12,679
really easy, And that would have taken me, you know

1326
01:05:12,760 --> 01:05:14,880
forever to try to like look all that stuff up.

1327
01:05:14,960 --> 01:05:17,360
And you know, I was basically making sure that all

1328
01:05:17,400 --> 01:05:20,599
of the psilocybin mushrooms, even the ones that were recently discovered,

1329
01:05:20,880 --> 01:05:26,199
were in my URL. And and yeah, so but in

1330
01:05:26,239 --> 01:05:29,440
any case, Yeah, the different ais will do different things,

1331
01:05:29,440 --> 01:05:33,599
and it's best to use all of them. Another one

1332
01:05:33,639 --> 01:05:36,719
that people don't really talk about very much is called Claude,

1333
01:05:37,280 --> 01:05:39,760
and that one is really good for coding, but it's

1334
01:05:39,800 --> 01:05:43,400
also really good for like just like therapist type stuff.

1335
01:05:43,440 --> 01:05:45,920
So if you just like have a problem with somebody

1336
01:05:45,960 --> 01:05:47,840
and you can be like am I the asshole or

1337
01:05:47,920 --> 01:05:50,719
are they the al solely ass claud and it'll give

1338
01:05:50,719 --> 01:05:54,199
you like a really well thought out, like nuanced response.

1339
01:05:54,360 --> 01:05:57,159
Fuck it, they must. I don't know how they did it.

1340
01:05:57,199 --> 01:05:59,719
They must have trained it on like all of this stuff,

1341
01:05:59,719 --> 01:06:00,559
but like.

1342
01:06:00,760 --> 01:06:02,920
Speaker 1: It'll give you some insight. Maybe it'll give.

1343
01:06:02,840 --> 01:06:05,960
Speaker 2: Really good insight. And just like if you would like

1344
01:06:06,079 --> 01:06:10,239
hired like a really expensive therapist to you know, go

1345
01:06:10,320 --> 01:06:12,559
over your problems with, it'll like give you an answer

1346
01:06:12,679 --> 01:06:16,159
like on power better than that and it'll explain like, well,

1347
01:06:16,199 --> 01:06:18,599
maybe you were kind of like in the wrong and

1348
01:06:18,719 --> 01:06:21,320
this power and you should probably like explain this a

1349
01:06:21,320 --> 01:06:24,719
little better and apologize for this. But on the other hand,

1350
01:06:25,000 --> 01:06:27,840
this this thing, you know, they were definitely and you

1351
01:06:27,960 --> 01:06:30,119
got to set your boundary there. But in any case,

1352
01:06:30,159 --> 01:06:33,119
it's it's really cool if you ever have a problem

1353
01:06:33,400 --> 01:06:36,480
with like another person, just it's just go into Claude

1354
01:06:36,519 --> 01:06:39,039
and explain what happened to Claude and it'll give you, like,

1355
01:06:39,679 --> 01:06:42,800
you know, like a lot of insight and it's like

1356
01:06:43,000 --> 01:06:44,880
it's uncannily good.

1357
01:06:45,079 --> 01:06:47,599
Speaker 1: What do you think? Okay, now now let's talk about

1358
01:06:47,599 --> 01:06:49,199
the dark shit, because this is all cool stuff. But

1359
01:06:49,280 --> 01:06:52,639
like the flip side of the coin would be not

1360
01:06:52,760 --> 01:06:55,440
just job orradication, Like what are some other things I

1361
01:06:55,480 --> 01:06:58,079
mean like that this could be used for. I mean,

1362
01:06:58,199 --> 01:07:01,079
it could be used to create new to devise new

1363
01:07:01,119 --> 01:07:04,039
ways to extract money from people, create more of a

1364
01:07:04,039 --> 01:07:06,360
capitalist consumer healthscape than we are.

1365
01:07:06,519 --> 01:07:08,960
Speaker 2: People are always doing that are always doing they've been

1366
01:07:09,039 --> 01:07:11,679
doing that ever since the money got invented. Is how

1367
01:07:11,719 --> 01:07:16,719
to get more of it? But yeah, I mean, it's

1368
01:07:16,760 --> 01:07:19,119
definitely taking a lot of people's jobs. And one thing

1369
01:07:19,199 --> 01:07:21,280
is like you know, usually you call up somebody on

1370
01:07:21,320 --> 01:07:24,239
the phone and you talk to a real person, but

1371
01:07:24,400 --> 01:07:26,159
now a lot of times you're talking to an AI

1372
01:07:26,199 --> 01:07:28,320
and they've just cloned the voice of a real person.

1373
01:07:29,039 --> 01:07:33,119
And now you can just clone anybody's voice, and you know,

1374
01:07:33,159 --> 01:07:35,559
you can kind of tell now because there's a little

1375
01:07:35,559 --> 01:07:38,320
bit too much of a pause in between, So.

1376
01:07:38,199 --> 01:07:40,599
Speaker 1: There will be AI where it's almost hard to tell

1377
01:07:40,639 --> 01:07:41,800
that it's there already.

1378
01:07:41,920 --> 01:07:44,760
Speaker 2: Is. Yeah, you can't can't really tell if you're talking

1379
01:07:44,800 --> 01:07:47,239
to a real person or not. And you know that's

1380
01:07:47,280 --> 01:07:50,440
not really that terrible because you call up a customer

1381
01:07:50,480 --> 01:07:53,639
service representative and you know, if it's AI, then they

1382
01:07:53,760 --> 01:07:57,519
know like every problem in their knowledge base, which most

1383
01:07:57,559 --> 01:08:01,119
of these customer service representatives don't really, but if you

1384
01:08:01,159 --> 01:08:03,400
can't talk to a real person, that could get pretty

1385
01:08:03,400 --> 01:08:06,079
annoying if it's not really in their knowledge base. So

1386
01:08:06,400 --> 01:08:09,039
you know, how it's could be deployed well, or it

1387
01:08:09,039 --> 01:08:14,000
could be deployed badly. It just really depends. But you know,

1388
01:08:14,079 --> 01:08:17,039
it's definitely going to take half of the people's jobs.

1389
01:08:17,159 --> 01:08:19,399
And what happens if half of the people in the

1390
01:08:19,399 --> 01:08:21,479
world are unemployed, that's gonna.

1391
01:08:21,600 --> 01:08:25,479
Speaker 3: Really up not in a good way, because when you

1392
01:08:25,560 --> 01:08:28,680
have half of twice as many workers, then you you

1393
01:08:28,680 --> 01:08:30,560
don't have to pay anybody very much anymore.

1394
01:08:30,880 --> 01:08:32,079
Speaker 2: You got this so much surplus.

1395
01:08:32,199 --> 01:08:34,119
Speaker 1: Now you have this surplus populist and know you've got

1396
01:08:34,159 --> 01:08:35,640
to get rid of themselves. So you got to start

1397
01:08:35,640 --> 01:08:37,640
a war, you know, that's the potential.

1398
01:08:38,680 --> 01:08:42,039
Speaker 2: Yeah, I mean, worlds these days don't don't usually kill

1399
01:08:42,119 --> 01:08:45,000
enough people to really make a dent in the population.

1400
01:08:45,760 --> 01:08:48,239
Speaker 1: Yeah. Yeah, maybe you got to invent some sort of

1401
01:08:48,399 --> 01:08:49,960
I don't know, there's all sorts of humans are so

1402
01:08:50,039 --> 01:08:53,880
good at thinking a terrible shit too. Yeah, we're so

1403
01:08:54,119 --> 01:08:56,640
lost as a civilization. I feel like we're just like

1404
01:08:56,800 --> 01:09:01,399
flailing with only you know, a handful of religions to

1405
01:09:01,479 --> 01:09:04,680
guide us and give us any direction, and even those

1406
01:09:04,760 --> 01:09:08,359
I mean obviously gets so thoroughly corrupted and off off

1407
01:09:08,399 --> 01:09:12,600
the rails. Okay, well, I guess I guess we can

1408
01:09:12,640 --> 01:09:17,600
move on from that topic. But regarding the silosophy, there's

1409
01:09:18,039 --> 01:09:21,000
new species that would have been development since philosophy. In

1410
01:09:21,000 --> 01:09:23,000
the genus, there's a couple of new species been described,

1411
01:09:23,279 --> 01:09:26,439
and then it was it turns out that cyan essens

1412
01:09:26,479 --> 01:09:28,680
and azorescans and all these species that were in the

1413
01:09:28,720 --> 01:09:33,319
Northwest down to like northern California, Like this cluster of

1414
01:09:33,399 --> 01:09:35,680
species is quite likely Australian.

1415
01:09:36,560 --> 01:09:40,079
Speaker 2: Yeah, these things all probably came from Australia in the

1416
01:09:40,119 --> 01:09:43,439
last years. You could probably you could go call them

1417
01:09:43,439 --> 01:09:47,520
all suburuginosa. But you know, if you for anybody that's

1418
01:09:47,600 --> 01:09:50,319
actually hunting Salasa bey in the Northwest, it's pretty easy

1419
01:09:50,359 --> 01:09:53,800
to tell apart the Lennii, the Azores sens, the cia sense.

1420
01:09:53,920 --> 01:09:57,000
So you know, I think probably they'll end up being

1421
01:09:57,039 --> 01:10:00,720
described at the variety level, it all be varieties suburugenosa,

1422
01:10:00,840 --> 01:10:03,560
but you know, it's all the same same mushrooms as

1423
01:10:03,560 --> 01:10:05,560
however you want to call them. As kind of a

1424
01:10:05,560 --> 01:10:06,399
matter of personal part.

1425
01:10:06,520 --> 01:10:08,840
Speaker 1: With these different varieties, you think they're just ecotypes that

1426
01:10:08,840 --> 01:10:11,399
have evolved in the last two centuries or what I

1427
01:10:11,479 --> 01:10:12,359
would do, it's.

1428
01:10:12,199 --> 01:10:14,920
Speaker 2: Really hard to tell how long they've actually how long

1429
01:10:14,960 --> 01:10:17,760
ago they've actually evolved. They're definitely I would say it

1430
01:10:17,760 --> 01:10:22,319
a little longer, because they're they're definitely different, very consistently different.

1431
01:10:22,680 --> 01:10:26,039
And I think mushrooms evolved pretty slowly, Like it takes

1432
01:10:26,039 --> 01:10:29,560
a few thousand years for mushroom to evolve, and so

1433
01:10:30,439 --> 01:10:32,000
you know, at the very minimum.

1434
01:10:31,680 --> 01:10:34,159
Speaker 1: For populations to change exactly.

1435
01:10:34,399 --> 01:10:39,840
Speaker 2: Yeah, they don't. They don't change too rapidly. But there's

1436
01:10:40,880 --> 01:10:43,319
you know, there's there's more and more people are doing

1437
01:10:43,359 --> 01:10:46,000
more and more DNA bar coding. There's there's more and

1438
01:10:46,079 --> 01:10:50,680
more new species of every genus being discovered. Recently, when

1439
01:10:50,760 --> 01:10:53,880
turned up in southern California that people thought with silosabio

1440
01:10:53,960 --> 01:10:57,159
Vodio cystidiata, but it turns out that we're calling it

1441
01:10:57,279 --> 01:11:01,279
silosip species CO two now and it also turned up

1442
01:11:01,319 --> 01:11:05,279
in South Africa. So that's that's another one. It's going

1443
01:11:05,319 --> 01:11:10,600
to be published soon. There's there's a ton of new species.

1444
01:11:11,880 --> 01:11:14,520
There's bluing cornosibes or what they used to call it

1445
01:11:14,520 --> 01:11:17,399
blue or then more recently blueing filly of Tinas. They

1446
01:11:17,439 --> 01:11:21,279
got a new genus a few months back, so.

1447
01:11:21,359 --> 01:11:23,920
Speaker 1: Is that bluing psilocybin yah.

1448
01:11:24,680 --> 01:11:28,079
Speaker 2: So these are orange bort things and now they're called conasbula.

1449
01:11:29,000 --> 01:11:33,399
And there's a few species. I think the ones in

1450
01:11:33,600 --> 01:11:38,520
Europe are undescribed, but they call it kind of Sibulis cyanipus.

1451
01:11:38,560 --> 01:11:40,399
Speaker 1: But it did. But going back to this one in

1452
01:11:40,520 --> 01:11:43,960
South Africa and Southern California, a disjunction like that. It's

1453
01:11:44,000 --> 01:11:46,800
probably human transport obviously.

1454
01:11:46,560 --> 01:11:49,880
Speaker 2: Kari, but it's really hard to tell how things are transported.

1455
01:11:49,920 --> 01:11:52,039
And also like for wood lovers, one way that they

1456
01:11:52,039 --> 01:11:55,399
get transported a lot is just on driftwood. So you know,

1457
01:11:55,479 --> 01:11:58,159
a whole storm comes and washes a lot of wood

1458
01:11:58,159 --> 01:12:00,800
into the water in Australia, that'll wash up on beaches

1459
01:12:01,000 --> 01:12:04,199
all over the world and can move wood lovers like

1460
01:12:04,640 --> 01:12:08,600
sit like eight weeks or even longer of being inundated

1461
01:12:08,640 --> 01:12:10,560
withsault on. Yeah, it was in the middle of that

1462
01:12:10,720 --> 01:12:15,199
of the log. You know, it's pretty protected. So yeah,

1463
01:12:15,279 --> 01:12:17,640
driftwood is a really good way for fun dried across

1464
01:12:17,680 --> 01:12:18,119
the ocean.

1465
01:12:18,359 --> 01:12:20,800
Speaker 1: So many things have to happen though.

1466
01:12:21,159 --> 01:12:23,640
Speaker 2: Yeah, it's got to wash up, probably on another storm

1467
01:12:23,840 --> 01:12:26,199
wash up and kind of like getting get a good

1468
01:12:26,239 --> 01:12:28,119
foothold and in the new place.

1469
01:12:28,479 --> 01:12:31,399
Speaker 1: Because but with plants, it's I mean the only big

1470
01:12:31,920 --> 01:12:35,239
I mean, I guess there's the two methods that dispersal

1471
01:12:35,279 --> 01:12:38,680
are birds or which you know normally you can tell

1472
01:12:38,720 --> 01:12:41,239
from flight paths, I mean, like migration patterns. Like that's

1473
01:12:41,239 --> 01:12:44,760
why there's so many you know, South American and North

1474
01:12:44,800 --> 01:12:49,079
American disjunctions. You look at the migration patterns or yeah,

1475
01:12:49,159 --> 01:12:53,319
or debris rafts, but you know, most of the lineages

1476
01:12:53,439 --> 01:12:56,359
and like whole clades of plants with it. You know,

1477
01:12:56,399 --> 01:12:58,359
there's exceptions of everything, but for the most part, they've

1478
01:12:58,399 --> 01:12:59,960
been restricted to certain continents.

1479
01:13:01,479 --> 01:13:04,039
Speaker 2: Yeah, but you know, a hurricane comes, how many pieces

1480
01:13:04,079 --> 01:13:07,239
of drift would go into the ocean, probably a million. Yeah,

1481
01:13:07,279 --> 01:13:10,479
and if there's like one in ten thousands of them

1482
01:13:10,479 --> 01:13:13,039
actually take hold, that's a lot of introduction, don't just

1483
01:13:13,039 --> 01:13:16,760
get But usually when things get introduced, they don't take off.

1484
01:13:17,279 --> 01:13:20,199
Like a lot of people will take silosophy spores of

1485
01:13:20,279 --> 01:13:23,000
rare species, drop them in mail, and then somebody else

1486
01:13:23,039 --> 01:13:26,119
on another continent will cultivate it like in their garden outdoors,

1487
01:13:26,119 --> 01:13:29,600
and millions of spores of flying to the environment. But

1488
01:13:30,319 --> 01:13:34,399
you mushroom hunters in these areas don't start seeing the species.

1489
01:13:34,760 --> 01:13:39,039
Usually occasionally they do. Like there was the Golden oyster

1490
01:13:39,760 --> 01:13:42,760
is oyster from China and it started getting cultivated the

1491
01:13:42,840 --> 01:13:44,800
United States, and all of a sudden, it's all over

1492
01:13:44,880 --> 01:13:48,880
the east coast eastern United States. And it's kind of

1493
01:13:48,920 --> 01:13:51,479
one of those things kind of like a raspberry where yeah,

1494
01:13:51,520 --> 01:13:55,079
it's invasive, but also it's delicious, So it's hard to

1495
01:13:55,079 --> 01:13:58,520
be too bad at it, and the jury is really

1496
01:13:58,560 --> 01:14:01,720
out as to whether it's bad or how bad it is.

1497
01:14:02,760 --> 01:14:05,720
I think it probably does choke out some native species,

1498
01:14:05,760 --> 01:14:10,079
but compared to like leveling a forest to make a

1499
01:14:10,199 --> 01:14:12,439
parking lot or a shopping mall, I don't think it's

1500
01:14:12,520 --> 01:14:14,159
very bad at all with that.

1501
01:14:14,560 --> 01:14:16,439
Speaker 1: But some invasives can certainly be the.

1502
01:14:16,560 --> 01:14:20,000
Speaker 2: Yeah no, I'm talking about like invasive mushrooms. Yeah, yeah,

1503
01:14:20,239 --> 01:14:22,159
you know, I don't think it's really that bad. But

1504
01:14:22,159 --> 01:14:24,760
also it's really hard to tell how bad the invasive

1505
01:14:24,760 --> 01:14:28,640
fungi plant pathogens. Of course, they can be terrible because

1506
01:14:28,680 --> 01:14:32,600
it's the sudden oak death, the water, which yeah, basically

1507
01:14:33,840 --> 01:14:38,119
a lot of those things. Mushrooms are pretty benign by comparison.

1508
01:14:38,239 --> 01:14:40,880
Speaker 1: Fabola, what is that really invasive one?

1509
01:14:41,520 --> 01:14:46,119
Speaker 2: Yeah, the Fava calosera. It's you know, described from Madagascar,

1510
01:14:46,239 --> 01:14:47,920
but they call it a ping pong bat and it

1511
01:14:47,960 --> 01:14:51,760
looks like a bright, fluorescent orange ping pong padal with

1512
01:14:51,840 --> 01:14:56,199
little holes on the other side, beautiful mushroom. It's it

1513
01:14:56,279 --> 01:14:59,239
was super common in New Zealand where it's invasive, but

1514
01:14:59,279 --> 01:15:00,840
it's kind of hard to be mad at it because

1515
01:15:00,880 --> 01:15:04,560
it's such a beautiful photographic subject. But then for the

1516
01:15:04,600 --> 01:15:09,279
first time it was found in California, and so this

1517
01:15:09,359 --> 01:15:12,039
lady found it posted it on Facebook, and I'm like, hey,

1518
01:15:12,119 --> 01:15:14,000
can you show me the spot? And she showed me

1519
01:15:14,039 --> 01:15:16,920
where it was. There was this little powerk in San Bruno,

1520
01:15:17,079 --> 01:15:18,920
just south of San Francisco, and I went out there

1521
01:15:18,960 --> 01:15:21,760
and there was this one coast live oklog that was

1522
01:15:21,840 --> 01:15:26,680
covered in absolutely stunningly beautiful favolaci at Calisera and so

1523
01:15:26,720 --> 01:15:29,439
I got really nice, focused tacked pictures of it, and

1524
01:15:29,479 --> 01:15:33,119
I think it's my top most favorited I naturalist observation

1525
01:15:33,319 --> 01:15:36,960
now really. But it's the only time that favalacci has

1526
01:15:36,960 --> 01:15:38,319
been found in California.

1527
01:15:39,159 --> 01:15:40,960
Speaker 1: It's about to be found a lot more.

1528
01:15:41,239 --> 01:15:42,560
Speaker 2: Probably, yeah, I think.

1529
01:15:42,880 --> 01:15:44,520
Speaker 3: And we took it and we put it on augur

1530
01:15:44,600 --> 01:15:47,760
and it does grow on auger and stuff like that.

1531
01:15:48,039 --> 01:15:50,600
You know, I'm not going to introduce it more just

1532
01:15:50,640 --> 01:15:52,960
because you know, if it happens, it's going to happen

1533
01:15:53,000 --> 01:15:58,640
without my help. But yeah, it probably will take over California.

1534
01:15:58,760 --> 01:15:59,880
Speaker 1: But it's not pathogenic.

1535
01:16:00,119 --> 01:16:02,239
Speaker 2: Just I don't think it's too Palpa Johnni. It's just

1536
01:16:02,600 --> 01:16:05,319
kind of breaking down wood, turning wood into high quality

1537
01:16:05,399 --> 01:16:11,399
soil and it'll probably choke out a few native sapatrophs.

1538
01:16:11,600 --> 01:16:15,399
But you know, nothing on the scale of what humanity

1539
01:16:15,479 --> 01:16:17,359
does when when they build a new city.

1540
01:16:17,600 --> 01:16:20,199
Speaker 1: No, totally, but this is humanity. I mean humanity is

1541
01:16:20,239 --> 01:16:22,479
the reason it got there too at the same time, so.

1542
01:16:22,359 --> 01:16:25,800
Speaker 2: It's maybe though nobody I don't think anybody is cultivating that,

1543
01:16:26,439 --> 01:16:28,960
so you never really know. It could have come through

1544
01:16:28,960 --> 01:16:30,720
a bird, it could have come on drift wood, it

1545
01:16:30,720 --> 01:16:32,960
could have come on the bottom of somebody's shoes. Yeah,

1546
01:16:32,960 --> 01:16:35,199
it's just different international flights here all.

1547
01:16:35,119 --> 01:16:37,399
Speaker 1: This stuff for people at the Nine Basin. Like with plants,

1548
01:16:37,399 --> 01:16:39,319
it's all the time like, oh well it's they compare

1549
01:16:39,359 --> 01:16:41,479
it to you know, it's not as bad as this.

1550
01:16:41,640 --> 01:16:43,680
It's like, well it doesn't. That's like an that's a

1551
01:16:43,680 --> 01:16:46,880
whole other thing. It's like it it's different with funny

1552
01:16:46,920 --> 01:16:49,399
and it's different with this fable lash year. It's probably

1553
01:16:49,399 --> 01:16:51,720
not going to be that bad. But I've just seen

1554
01:16:52,079 --> 01:16:55,199
so much wreckage, you know, Like what we end up

1555
01:16:55,239 --> 01:16:59,000
approaching is like a homogenization of Earth's life forms.

1556
01:16:59,439 --> 01:17:03,039
Speaker 2: Yeah, it's not good, but it's also really hard to measure,

1557
01:17:03,119 --> 01:17:05,039
Like how do you how can you measure how bad

1558
01:17:05,079 --> 01:17:08,319
this mushroom is. You know, if it's not killing anything directly,

1559
01:17:08,800 --> 01:17:10,239
but it's this mushroom.

1560
01:17:10,319 --> 01:17:12,199
Speaker 1: No, I'm talking about just invasive.

1561
01:17:12,239 --> 01:17:16,520
Speaker 2: Invasive plants are a whole different thing than fungi. Like

1562
01:17:16,920 --> 01:17:18,800
you know, as far as picking goes, if you pick

1563
01:17:18,840 --> 01:17:20,680
a rare plant, then it's gone. You pick a rare

1564
01:17:20,760 --> 01:17:23,279
mushroom and it just really helps us spread around it.

1565
01:17:25,880 --> 01:17:29,399
But yeah, like the invasive species, all the invasive grasses

1566
01:17:29,439 --> 01:17:33,640
of choking out so many native how native species, and

1567
01:17:33,680 --> 01:17:36,159
it's really obvious you go there and there's just invasive

1568
01:17:36,239 --> 01:17:38,239
as far as you can see in the native ones

1569
01:17:38,359 --> 01:17:40,039
is barely poking through.

1570
01:17:40,760 --> 01:17:43,760
Speaker 1: Struggling to survive. That's why they require active management, which

1571
01:17:43,800 --> 01:17:45,479
is another thing people are like, oh, well, it's you're

1572
01:17:45,520 --> 01:17:47,159
never going to get all of it, and it's well,

1573
01:17:47,159 --> 01:17:48,479
if the point isn't they get all of it. It's

1574
01:17:48,520 --> 01:17:51,199
like the preserve a little bit of this piece of

1575
01:17:51,239 --> 01:17:54,760
the living machine. So until something can adapt and evolve

1576
01:17:54,880 --> 01:17:58,399
to maybe exploit the abundance of this invasive which will

1577
01:17:58,399 --> 01:18:00,920
happen eventually. It might take five thousand years, it might

1578
01:18:00,920 --> 01:18:02,359
take five thousand who knows, But.

1579
01:18:02,920 --> 01:18:04,800
Speaker 2: Yeah, we have a little group in elsa rito a

1580
01:18:04,880 --> 01:18:06,920
groat a couple times a week and cut the Scotch

1581
01:18:06,960 --> 01:18:09,439
broom from the hillside natural area. Oh yeah, that's a

1582
01:18:09,479 --> 01:18:11,239
bad one. There's a lot of it out there and

1583
01:18:11,279 --> 01:18:12,920
we'll never get all of it. But that's okay. It's

1584
01:18:13,199 --> 01:18:14,920
more fun. It's kind of fun just to hang out

1585
01:18:14,920 --> 01:18:16,960
with a bunch of people who like nature and free

1586
01:18:17,000 --> 01:18:17,960
exercise and so.

1587
01:18:18,239 --> 01:18:20,399
Speaker 1: And also I compare it to like cancer, Like there's

1588
01:18:20,439 --> 01:18:23,000
some cancers you can get that you can live with

1589
01:18:23,159 --> 01:18:25,760
and that will be you know, that can you can

1590
01:18:25,880 --> 01:18:30,039
keep subdued by medication. Would you tell someone who got

1591
01:18:30,159 --> 01:18:33,520
like a leukemia that's managable by medication, You're never gonna

1592
01:18:33,560 --> 01:18:36,000
get all of it, don't even try. And I say, well, no,

1593
01:18:36,119 --> 01:18:37,920
I can just take this pill and live with it

1594
01:18:37,960 --> 01:18:41,960
for another thirty years. It'll be fine. It's yeah, yeah,

1595
01:18:42,000 --> 01:18:44,520
it's it's it's wild though, but it's it's crazy to

1596
01:18:44,520 --> 01:18:47,199
see where this stuff pops up and how much human transport.

1597
01:18:47,880 --> 01:18:50,520
It really does kind of place the burden of responsibility

1598
01:18:50,520 --> 01:18:55,000
on human shoulders now to maintain and really like steward

1599
01:18:55,560 --> 01:18:59,000
some of these rare places that you know, can't compete

1600
01:18:59,039 --> 01:19:03,119
with these rare ecoisms and rare habitats that can't compete

1601
01:19:03,119 --> 01:19:06,199
with the invasives too much. And I wish there was

1602
01:19:06,359 --> 01:19:09,239
more of a program to do that, but you know,

1603
01:19:09,279 --> 01:19:11,960
there was more in the popular culture, in the zeitgeist.

1604
01:19:12,800 --> 01:19:15,199
Speaker 2: Yeah. I mean, if everyone who got a gym membership

1605
01:19:15,239 --> 01:19:18,159
instead just went out and pulled invasives and cut down

1606
01:19:18,199 --> 01:19:20,760
invasive stuff, you know, you get really good exercise, but

1607
01:19:20,920 --> 01:19:22,119
it could really make a dad.

1608
01:19:22,479 --> 01:19:25,000
Speaker 1: Yeah, yeah, easily, man, or just learn to identify it.

1609
01:19:25,159 --> 01:19:27,239
Just like. That's one thing that you do that I

1610
01:19:27,279 --> 01:19:29,640
love so much, is like you're so in You're such

1611
01:19:29,640 --> 01:19:33,319
a teacher. You're so into educating people and just taking

1612
01:19:33,359 --> 01:19:38,439
the time to teach fucking anybody anything about mushrooms or

1613
01:19:38,520 --> 01:19:42,199
any other facet of the living world that you know,

1614
01:19:42,359 --> 01:19:45,760
you you're knowledgeable about. And you've I think you've inspired

1615
01:19:45,800 --> 01:19:47,640
a shit ton of people. I mean, I know you have,

1616
01:19:48,560 --> 01:19:52,239
so it's pretty cool. I think you'll probably be doing

1617
01:19:52,239 --> 01:19:53,600
this for the rest of your life.

1618
01:19:54,000 --> 01:19:56,199
Speaker 2: Yeah, I don't. I don't think i'll stop anytime soon.

1619
01:19:58,479 --> 01:20:01,159
Speaker 1: Well, there, I could keep talking to you for another few hours.

1620
01:20:01,159 --> 01:20:02,720
I don't know. Is there anything else we should cover

1621
01:20:02,760 --> 01:20:03,960
before we dip out here?

1622
01:20:05,319 --> 01:20:07,720
Speaker 2: Well, I guess one thing we didn't mention is that

1623
01:20:07,880 --> 01:20:11,640
I Naturalist Project for our fore So you know, we

1624
01:20:11,800 --> 01:20:15,560
just did this week long foray in Ecuador, and we

1625
01:20:15,680 --> 01:20:19,399
set up an I Naturalist Project, so everybody who found

1626
01:20:19,520 --> 01:20:23,119
anything on this fora goes into the project, and so

1627
01:20:24,640 --> 01:20:26,600
you know, we could kind of keeps track of everything,

1628
01:20:26,680 --> 01:20:30,640
and so we got let's see, it was three hundred

1629
01:20:30,680 --> 01:20:34,439
and twenty six species of plants that we saw, and

1630
01:20:34,479 --> 01:20:39,399
that's that's probably mostly Joey just you know, with all

1631
01:20:39,399 --> 01:20:41,720
of those, but it's you know, those twenty five people

1632
01:20:41,840 --> 01:20:46,600
all kind of combined effort on everything. And you know

1633
01:20:46,680 --> 01:20:51,159
this week we had Andy Better, like can identify insects.

1634
01:20:50,920 --> 01:20:53,920
Speaker 1: He's in a tomology guy. Yeah, for mushrooms. How many

1635
01:20:53,960 --> 01:20:55,319
species of funny.

1636
01:20:55,079 --> 01:20:59,479
Speaker 2: One hundred and seventy three named species of fungiant probably

1637
01:20:59,520 --> 01:21:01,399
as many that don't have names.

1638
01:21:00,920 --> 01:21:02,640
Speaker 1: But a ton that are just down to genus or

1639
01:21:02,960 --> 01:21:07,319
family or whatever. Yeah, So what where I guess to

1640
01:21:07,319 --> 01:21:10,079
explain what this was? The people who wanted, like you're

1641
01:21:10,079 --> 01:21:11,560
gonna because you're gonna be doing this a couple of

1642
01:21:11,600 --> 01:21:12,560
times a year. Probably.

1643
01:21:13,159 --> 01:21:17,079
Speaker 2: Yeah. So you know, I came to Ecuador first in

1644
01:21:17,159 --> 01:21:19,720
twenty twenty and it was so cool that I wanted

1645
01:21:19,800 --> 01:21:23,079
to kind of invite people and teach people and be

1646
01:21:23,119 --> 01:21:27,079
able to kind of have like a trip that can

1647
01:21:27,159 --> 01:21:29,079
bring people down and teach them, show them all about

1648
01:21:29,119 --> 01:21:32,439
diversity here, and also like pay for my costs so

1649
01:21:32,479 --> 01:21:35,359
I can actually afford to do it. So this is

1650
01:21:35,439 --> 01:21:38,680
the third or fourth that I've done in Ecuador. We

1651
01:21:38,760 --> 01:21:41,479
did one in Colombia a few months back that was

1652
01:21:41,560 --> 01:21:44,439
really cool, and done a few in Mexico. And so

1653
01:21:44,560 --> 01:21:49,600
basically we invite the whole internet and you know, people

1654
01:21:49,640 --> 01:21:53,319
come and they send us some money and that covers

1655
01:21:53,359 --> 01:21:56,880
food and transportation and lodging for a week or ten days,

1656
01:21:57,319 --> 01:21:59,439
and then we just plan a trip where we visit

1657
01:21:59,720 --> 01:22:03,159
is any cool habitats as possible. This is the first

1658
01:22:03,199 --> 01:22:06,199
time that we got so many different experts. So, you know,

1659
01:22:06,239 --> 01:22:09,560
we brought Joey down to help us with plants, and

1660
01:22:09,560 --> 01:22:12,039
Andy to help us with insects, and we had Alex

1661
01:22:12,079 --> 01:22:15,880
and Zane who were reptile and amphibian experts, and so

1662
01:22:16,159 --> 01:22:18,960
you know, basically anything that we saw out there in

1663
01:22:19,000 --> 01:22:21,880
the forest, we had somebody that was an expert on

1664
01:22:22,840 --> 01:22:25,760
those sort of organisms. And you know, it turned out

1665
01:22:25,800 --> 01:22:28,199
really cool. The people that come in these trips are

1666
01:22:28,479 --> 01:22:30,720
you know, not a random cross section of people, but

1667
01:22:30,840 --> 01:22:33,840
you know, the people that know me well enough to

1668
01:22:33,880 --> 01:22:36,079
decide that they want to, you know, spend a week

1669
01:22:36,159 --> 01:22:39,159
or ten days in some other country with me. And

1670
01:22:39,960 --> 01:22:41,560
you know, I knew it would be really cool, but

1671
01:22:41,600 --> 01:22:43,800
it ended up being a whole lot cooler than I

1672
01:22:43,800 --> 01:22:47,079
thought it would be, you know, partly because it's like

1673
01:22:47,159 --> 01:22:49,439
Alex planned it so well and took us to so

1674
01:22:49,600 --> 01:22:52,800
many places because you know, he lives down here and

1675
01:22:52,840 --> 01:22:56,399
so he's he's a biologist that's been working down here

1676
01:22:56,439 --> 01:22:59,159
for years, so he knows so many cool habitats and

1677
01:22:59,159 --> 01:23:02,840
he knows the best places. And then a lot of

1678
01:23:02,880 --> 01:23:05,760
the experts that we brought in are people that he

1679
01:23:05,880 --> 01:23:08,520
introduced me to, and so it's kind of like, you know,

1680
01:23:08,560 --> 01:23:10,680
a lot of the best people in the whole world

1681
01:23:10,800 --> 01:23:12,640
all together on one trip.

1682
01:23:13,279 --> 01:23:17,079
Speaker 1: So I learned a ship ton about so much. I mean,

1683
01:23:17,119 --> 01:23:19,199
I I that's kind of what I do on you anyway,

1684
01:23:19,239 --> 01:23:20,760
Like I go out someplace, I'm just going to take

1685
01:23:20,760 --> 01:23:23,600
it in, note things, you know, and then research later

1686
01:23:23,640 --> 01:23:27,119
that night, make notes, take just collect again, just collecting

1687
01:23:27,119 --> 01:23:30,800
ship tons of data. But to have people who know,

1688
01:23:31,720 --> 01:23:34,279
especially with the reptile stuff, like doing a venom extraction

1689
01:23:34,399 --> 01:23:38,319
and you know, learning about the different ecologies of all

1690
01:23:38,319 --> 01:23:40,960
the reptiles and amphibians.

1691
01:23:41,520 --> 01:23:44,119
Speaker 2: Yeah, I missed that. What kind of snake was the

1692
01:23:44,199 --> 01:23:45,560
extracting from boutry?

1693
01:23:46,960 --> 01:23:47,119
Speaker 3: Oh?

1694
01:23:48,720 --> 01:23:52,399
Speaker 1: Yeah, like the size, Yeah, that was.

1695
01:23:52,039 --> 01:23:54,119
Speaker 2: A viper that we found out there by the cave.

1696
01:23:54,199 --> 01:23:55,840
Speaker 1: But he's got like a ship ton of venom from

1697
01:23:55,880 --> 01:23:57,159
this tiny live Yeah.

1698
01:23:57,239 --> 01:23:59,159
Speaker 2: Yeah. And that's one of the things that Alex does

1699
01:23:59,199 --> 01:24:01,720
for a living is to milk the venom out of

1700
01:24:01,720 --> 01:24:04,319
these snakes and then he freeze dries it with a

1701
01:24:04,439 --> 01:24:09,479
kind of this like homemade freeze dryer, and then sends

1702
01:24:09,520 --> 01:24:14,800
it off for analysis. They do, you know, GCMs analysis

1703
01:24:14,800 --> 01:24:18,119
and time of flight analysis and just to figure out

1704
01:24:18,119 --> 01:24:22,680
exactly how the proteins work and all of these venoms.

1705
01:24:23,439 --> 01:24:27,239
But yeah, that that was that was really cool. I

1706
01:24:27,279 --> 01:24:30,279
saw him milk a coral snake last time I was here.

1707
01:24:30,399 --> 01:24:38,760
Speaker 1: God, that's gonna be wow that the teeth are probably tiny.

1708
01:24:35,840 --> 01:24:39,039
Speaker 2: Barely bite you. I mean, he's been doing it for

1709
01:24:39,039 --> 01:24:41,159
a living for a long time, so he's got it

1710
01:24:41,199 --> 01:24:41,720
figured out.

1711
01:24:44,119 --> 01:24:46,880
Speaker 1: Well, how can people learn about this? Did you go

1712
01:24:46,960 --> 01:24:47,760
to mycena?

1713
01:24:48,560 --> 01:24:48,800
Speaker 4: Yeah?

1714
01:24:49,079 --> 01:24:53,399
Speaker 2: So the website is mycena dot llc. So we announced

1715
01:24:53,399 --> 01:24:55,520
trips on there and we have a mailing list, so,

1716
01:24:55,800 --> 01:24:57,800
you know, a real low traffic mailing list. You just

1717
01:24:57,840 --> 01:25:00,359
to get a couple of emails a year, but if

1718
01:25:00,359 --> 01:25:02,560
you sign up for that, then you'll hear about future

1719
01:25:02,600 --> 01:25:07,239
trips or if you follow me on Facebook, LinkedIn, Instagram,

1720
01:25:07,319 --> 01:25:09,680
blue sky, you know, any any of those things. I

1721
01:25:09,920 --> 01:25:12,399
post about these things a month or two in advance,

1722
01:25:14,199 --> 01:25:17,199
and that's that's probably the best way to kind of

1723
01:25:17,560 --> 01:25:20,880
keep in touch and know what we're doing next. I'd

1724
01:25:20,880 --> 01:25:25,920
really like to do something in Costa Rica. I know

1725
01:25:25,960 --> 01:25:28,439
a couple of good mycologists in Costa Rica that might

1726
01:25:28,520 --> 01:25:32,760
organize this with. And also Malaysia. I know some amazing

1727
01:25:32,840 --> 01:25:37,479
mushroom photographers and Malaysia that are interested in organizing a trip.

1728
01:25:37,640 --> 01:25:40,800
Speaker 3: So what interests you about Malaysia? Oh, the stuff there

1729
01:25:40,920 --> 01:25:43,439
is are so different. You know, one thing that is

1730
01:25:43,479 --> 01:25:44,439
tropical still right?

1731
01:25:44,560 --> 01:25:45,000
Speaker 2: Oh yeah.

1732
01:25:45,239 --> 01:25:47,359
Speaker 3: One thing I like about South America is it is

1733
01:25:47,640 --> 01:25:50,079
very different from North America, but it's still the same

1734
01:25:50,199 --> 01:25:53,640
land mosk. So it's not so different that it's like confusing.

1735
01:25:54,199 --> 01:25:56,880
It's like things are still you know, kind of like

1736
01:25:56,920 --> 01:25:59,640
a lot of the same families and lineages, whereas if

1737
01:25:59,680 --> 01:26:02,039
you go to Asia, you know, it's not connected at all,

1738
01:26:02,079 --> 01:26:04,239
and things are completely different.

1739
01:26:04,279 --> 01:26:06,840
Speaker 1: They've been separated a much longer period of time.

1740
01:26:07,039 --> 01:26:09,520
Speaker 2: Yeah, exactly, And like some of the fungi, they are

1741
01:26:09,600 --> 01:26:13,479
just absolutely stunning. You know, stuff that you would you

1742
01:26:13,520 --> 01:26:16,439
would never see here, and so I love to go

1743
01:26:16,560 --> 01:26:19,600
there and you know, start to figure out all of

1744
01:26:19,640 --> 01:26:20,640
that stuff.

1745
01:26:20,279 --> 01:26:23,199
Speaker 1: From a plant perspective. It's really interesting too, because I mean,

1746
01:26:23,239 --> 01:26:26,159
I'm sure you would see you see the same ecologies

1747
01:26:26,199 --> 01:26:29,800
and the same you see convergence in the same morphology,

1748
01:26:30,479 --> 01:26:33,039
you know, the way things look and also the ecologies,

1749
01:26:33,039 --> 01:26:35,039
but it's a completely different cast of species.

1750
01:26:35,079 --> 01:26:38,520
Speaker 3: And even exactly, yeah, you got the same ecological pressures,

1751
01:26:38,600 --> 01:26:40,680
so you still kind of have the same sort of

1752
01:26:41,479 --> 01:26:46,239
forces shaping the evolution, but completely different lineages. So you're

1753
01:26:46,279 --> 01:26:50,439
kind of starting with different, you know, very different starting material,

1754
01:26:50,520 --> 01:26:53,359
but getting to a similar place. And that's really interesting

1755
01:26:53,399 --> 01:26:55,119
how all those adaptations work.

1756
01:26:55,720 --> 01:26:58,239
Speaker 1: Okay, well, I guess, uh, I don't know until next

1757
01:26:58,239 --> 01:27:01,399
time when I have you on the podcast. Uh, you

1758
01:27:01,399 --> 01:27:03,159
go to my scene it at LLC if you want

1759
01:27:03,159 --> 01:27:07,920
to learn more about these forays and possibly hook up

1760
01:27:07,920 --> 01:27:12,039
for one, and and then what else? Working where else

1761
01:27:12,039 --> 01:27:15,119
can people read about your stuff? Just your social media?

1762
01:27:15,840 --> 01:27:18,520
Speaker 2: Yeah, you know, if you if you just search for

1763
01:27:18,640 --> 01:27:21,319
a name on YouTube, a whole bunch of different videos

1764
01:27:21,399 --> 01:27:25,439
come up, and some of them are pretty good. But

1765
01:27:25,600 --> 01:27:27,800
you know, generally, I'll make a post and I'll just

1766
01:27:28,000 --> 01:27:31,479
put the same post on Facebook and Instagram and LinkedIn

1767
01:27:31,640 --> 01:27:35,319
and blue Sky and all the other ones if I remember, So,

1768
01:27:35,920 --> 01:27:37,640
if you just follow me on one of those things,

1769
01:27:37,680 --> 01:27:39,479
you can kind of see where I'm at and what

1770
01:27:39,520 --> 01:27:42,159
I've been doing. You can even follow me on an

1771
01:27:42,239 --> 01:27:44,560
high Naturalist and then you get like a day by

1772
01:27:44,640 --> 01:27:47,079
day report from where I am and what I've been finding.

1773
01:27:48,880 --> 01:27:52,800
Speaker 1: But yeah, I Naturalist is really important.

1774
01:27:53,119 --> 01:27:55,199
Speaker 2: Yeah, I Naturalist is the most important thing.

1775
01:27:55,279 --> 01:27:55,439
Speaker 1: You know.

1776
01:27:55,479 --> 01:27:59,920
Speaker 2: The whole point of I Naturalist is too, is to

1777
01:28:00,119 --> 01:28:03,439
bring people closer to nature. And it's really good at that.

1778
01:28:03,920 --> 01:28:07,000
Like anytime I see a plant or an insect or

1779
01:28:07,279 --> 01:28:08,880
like in that I don't know what it is, I

1780
01:28:08,920 --> 01:28:12,119
put it on an I Naturalist, and you know, people

1781
01:28:12,720 --> 01:28:14,800
you know will identify it for me. And sometimes it

1782
01:28:14,840 --> 01:28:17,479
takes a couple of years before some expert comes along

1783
01:28:17,520 --> 01:28:19,960
and they're like, oh, that's super rare or that's a

1784
01:28:20,000 --> 01:28:22,720
really odd form of something common. But you know, it's

1785
01:28:22,720 --> 01:28:26,439
just really cool to be able to see, you know,

1786
01:28:26,560 --> 01:28:30,880
to keep track of all that stuff. And so you know,

1787
01:28:30,920 --> 01:28:33,560
I do a lot of identifications on there too, Like, well,

1788
01:28:33,600 --> 01:28:37,039
I'm here in Ecuador. I've been identifying all of the

1789
01:28:37,119 --> 01:28:39,880
mushrooms that are found in this country and reported to

1790
01:28:39,920 --> 01:28:43,760
h naturalists. So you know, identify a couple hundred mushrooms.

1791
01:28:43,960 --> 01:28:46,520
Speaker 1: Any identifications do you have on your inad? How many

1792
01:28:46,600 --> 01:28:49,000
have you done? It looks like three hundred thousands.

1793
01:28:49,119 --> 01:28:53,439
Speaker 2: Yeah, it's over three hundred thousand now, so I think, yeah.

1794
01:28:53,239 --> 01:28:54,479
Speaker 1: It's teaching right there.

1795
01:28:54,600 --> 01:28:56,560
Speaker 2: Yeah, we definitely fifty a day.

1796
01:28:56,960 --> 01:28:59,520
Speaker 1: We need more experts to use in ashers. When I

1797
01:28:59,520 --> 01:29:02,079
was in Brazil, it was such a bummer because no,

1798
01:29:02,079 --> 01:29:04,479
none of the botanists especially you've got all that diverse,

1799
01:29:04,760 --> 01:29:07,840
those diverse members of asteraci down there, really wild shit,

1800
01:29:08,239 --> 01:29:11,199
and none of the people that study those use are

1801
01:29:11,279 --> 01:29:13,960
only a few that study those groups go on I

1802
01:29:14,079 --> 01:29:17,840
naturalists and see what people have been looking at and logging,

1803
01:29:17,880 --> 01:29:21,399
and so because of that, the AI identifications are poor,

1804
01:29:22,239 --> 01:29:25,800
and there's just the whole wealth of knowledge that's not you.

1805
01:29:25,800 --> 01:29:28,760
Speaker 2: Have really good experts identifying stuff on I Naturalists, and

1806
01:29:28,920 --> 01:29:31,560
the AI becomes very smart and it's able to like

1807
01:29:31,680 --> 01:29:34,520
really nails a lot of time.

1808
01:29:34,560 --> 01:29:37,239
Speaker 1: Fongy identifications around here were like spot on.

1809
01:29:38,960 --> 01:29:40,960
Speaker 2: Well, you know, in this part of Ecuador, there's a

1810
01:29:41,000 --> 01:29:43,279
lot of biologists because we're the most one of the

1811
01:29:43,279 --> 01:29:47,199
most biodiverse parts of Ecuador, and the people around here

1812
01:29:47,239 --> 01:29:50,239
that are the biologists around here really care about what

1813
01:29:50,279 --> 01:29:52,880
they're seeing, so they're using our naturalists a lot. They're

1814
01:29:53,399 --> 01:29:57,479
taking the time to identify everything really well. And you know,

1815
01:29:57,479 --> 01:29:59,920
there's a lot of other people really interested in this area,

1816
01:30:00,199 --> 01:30:02,359
like Damon Tie has been here and made a lot

1817
01:30:02,359 --> 01:30:05,239
of really good observations. And so you know, in this

1818
01:30:05,399 --> 01:30:07,039
part of the world, if you take a picture of

1819
01:30:07,039 --> 01:30:09,279
something in nature and put it on I Naturalists, it's

1820
01:30:09,399 --> 01:30:11,399
very likely that the computer vision is going to be

1821
01:30:11,439 --> 01:30:13,560
able to tell you exactly what spaces.

1822
01:30:13,680 --> 01:30:15,840
Speaker 1: And you're making it better by going if you're if

1823
01:30:15,880 --> 01:30:18,039
you're an expert, you're making it better by going on

1824
01:30:18,039 --> 01:30:20,039
there and identifying stuff, even if you can just get

1825
01:30:20,039 --> 01:30:20,960
it to genus or something.

1826
01:30:21,000 --> 01:30:23,039
Speaker 2: Yeah, and so it's a really good use of time.

1827
01:30:23,079 --> 01:30:25,079
Speaker 3: If you got like a free five minutes of time,

1828
01:30:25,159 --> 01:30:27,680
and you're pretty good at some sort of thing. You

1829
01:30:27,720 --> 01:30:29,960
can go on there and you know, some people will

1830
01:30:30,079 --> 01:30:32,840
identify all the aerroids or all the cactus or all

1831
01:30:32,880 --> 01:30:35,479
the bees, and so you know, I can flip through

1832
01:30:35,800 --> 01:30:38,760
the mushrooms and just you know, flip them real quick

1833
01:30:38,800 --> 01:30:40,439
and just like can you know, identify a whole lot

1834
01:30:40,479 --> 01:30:42,239
of them very rapidly and it only takes me a

1835
01:30:42,239 --> 01:30:44,039
couple of minutes. But it really helps out a lot

1836
01:30:44,039 --> 01:30:46,239
of people, and it makes the AI smarter.

1837
01:30:46,399 --> 01:30:49,119
Speaker 2: And it also is good for me because I get

1838
01:30:49,159 --> 01:30:52,960
to see what's out there and then that can be like,

1839
01:30:53,000 --> 01:30:55,439
oh wow, it's really it's really good over in this mountain.

1840
01:30:55,439 --> 01:30:56,359
I'm going to check that out.

1841
01:30:56,680 --> 01:30:59,159
Speaker 1: And it brings more attention. It brings more attention to

1842
01:30:59,199 --> 01:30:59,960
these organisms.

1843
01:31:00,239 --> 01:31:02,760
Speaker 2: Yeah, and you people couragees more people to use our

1844
01:31:02,880 --> 01:31:06,119
naturalists when more people are identifying their stuff. And also,

1845
01:31:06,720 --> 01:31:09,720
you know, learning these organisms is really the same as

1846
01:31:09,800 --> 01:31:12,319
learning a foreign language. I think it uses the same

1847
01:31:12,359 --> 01:31:14,560
part of your brain. So if you're identifying stuff for

1848
01:31:14,640 --> 01:31:18,880
other people and just using the vocabulary more than it

1849
01:31:19,000 --> 01:31:20,640
just like is on the top of your mind, and

1850
01:31:20,680 --> 01:31:23,600
it makes it much easier when you see it in person.

1851
01:31:23,720 --> 01:31:25,640
Just to remember it because you've identified it, you know,

1852
01:31:25,680 --> 01:31:27,359
twenty times for people in the last year.

1853
01:31:27,800 --> 01:31:30,920
Speaker 1: Yeah, well man, all right, well we'll do this again

1854
01:31:31,000 --> 01:31:32,920
in the next few months. I'll probably just do it

1855
01:31:32,920 --> 01:31:35,800
over the phone or something. But unless we're out doing

1856
01:31:35,840 --> 01:31:38,479
this again. But thanks for being down to come on

1857
01:31:38,600 --> 01:31:42,520
and thanks for all that you do and everybody else

1858
01:31:43,039 --> 01:31:44,880
used to have a good risky day. You go. Fuck

1859
01:31:44,920 --> 01:31:45,439
you so back.

1860
01:32:02,000 --> 01:32:09,479
Speaker 2: I have been hustle playing. We have been that outside

1861
01:32:10,079 --> 01:32:10,760
looking at.

1862
01:32:10,880 --> 01:32:17,880
Speaker 1: Passed off that the mole super son outside fin