1 00:00:01,480 --> 00:00:04,280 Speaker 1: Welcome to Stuff You Should Know, a production of I 2 00:00:04,360 --> 00:00:13,440 Speaker 1: Heart Radio. Hey you, and welcome to the podcast. I'm Josh. 3 00:00:13,560 --> 00:00:19,000 Speaker 1: There's Chuck, and this is Stuff you should Know about pythons. 4 00:00:19,520 --> 00:00:24,079 Speaker 1: Take it, Chuck, You mean take my two pythons to 5 00:00:24,160 --> 00:00:27,640 Speaker 1: the vet because I have two sick pythons. Do you 6 00:00:27,720 --> 00:00:31,159 Speaker 1: have two sick pythons? You never heard that joke? No, 7 00:00:32,320 --> 00:00:35,519 Speaker 1: but muscles? No, let's here. Well, I mean that's just 8 00:00:35,600 --> 00:00:37,199 Speaker 1: kind of it. It's just a not just way to 9 00:00:37,200 --> 00:00:40,000 Speaker 1: say you have big biceps, so you like, I need 10 00:00:40,159 --> 00:00:43,360 Speaker 1: a vet because I've got two sick pythons. Oh no, 11 00:00:43,560 --> 00:00:45,879 Speaker 1: I've never heard anything like that. I don't think that 12 00:00:45,960 --> 00:00:49,000 Speaker 1: joke even made it into The Hangover. It's like two 13 00:00:49,000 --> 00:00:51,600 Speaker 1: tickets to the gun show. Yeah, I've heard that one. 14 00:00:52,159 --> 00:00:56,040 Speaker 1: You haven't heard two sick pythons. No, no, No, that's terrible. 15 00:00:56,200 --> 00:00:58,440 Speaker 1: I think it was in The Hangover too. Oh I 16 00:00:58,480 --> 00:01:02,080 Speaker 1: never saw that one. It was not good. Was the 17 00:01:02,120 --> 00:01:05,800 Speaker 1: first one good? Yeah? It was. In fact, I just 18 00:01:05,840 --> 00:01:08,399 Speaker 1: watched some of that recently on a plane flight because 19 00:01:08,400 --> 00:01:11,640 Speaker 1: I just needed some comfort food and that movie was 20 00:01:11,800 --> 00:01:18,360 Speaker 1: really really funny. No, yeah, did you see it? Yeah? Oh, dude, 21 00:01:18,440 --> 00:01:22,080 Speaker 1: Zach Alifanakos was great. Ed Helms was great. Ken Uh, 22 00:01:22,680 --> 00:01:29,720 Speaker 1: what's his name? Ken Burns was awesome. No, main guy Ken, 23 00:01:29,920 --> 00:01:32,160 Speaker 1: the guy who's the doctor in real life, the Asian actor. 24 00:01:32,520 --> 00:01:39,880 Speaker 1: Oh Ken Jung, yeah Jung. He was hysterical. Yeah, he's funny. Okay, 25 00:01:40,280 --> 00:01:43,959 Speaker 1: Mike Tyson so funny. Tyson was funny that you know. 26 00:01:44,040 --> 00:01:46,039 Speaker 1: Actually he wasn't that good in it? Now, never mind, 27 00:01:46,040 --> 00:01:50,960 Speaker 1: I'm not gonna talk about that. Okay, correction wrong. I'll 28 00:01:51,040 --> 00:01:53,000 Speaker 1: let everyone guess who I didn't think was good out 29 00:01:53,000 --> 00:01:56,400 Speaker 1: of all the remaining characters. Oh, man, you're so hard 30 00:01:56,480 --> 00:01:58,800 Speaker 1: on that guy. Why what did you don't even know 31 00:01:58,800 --> 00:02:01,080 Speaker 1: what I'm talking about? I do too, of course I 32 00:02:01,160 --> 00:02:04,360 Speaker 1: know who you're talking about. Should we talk about pythons? 33 00:02:06,120 --> 00:02:08,440 Speaker 1: I think we should, And we're not talking about the muscles, 34 00:02:08,480 --> 00:02:12,119 Speaker 1: as the joke everybody knows goes. No. Instead, we're talking 35 00:02:12,120 --> 00:02:17,639 Speaker 1: about snakes, realize, snakes that will mess you up. Yeah. 36 00:02:17,880 --> 00:02:21,680 Speaker 1: I'm not so scared of pythons, no, uh, largely because 37 00:02:21,720 --> 00:02:25,560 Speaker 1: I'm never around them. But there's something my snake fear. 38 00:02:25,600 --> 00:02:27,400 Speaker 1: And I don't have that much of a snake fear, 39 00:02:27,480 --> 00:02:32,280 Speaker 1: but uh, my snake fears around having bangs of a 40 00:02:32,360 --> 00:02:36,280 Speaker 1: snake enter my body. But pythons are you know, they 41 00:02:36,360 --> 00:02:38,519 Speaker 1: have been known to kill people every once a while. 42 00:02:38,560 --> 00:02:41,320 Speaker 1: But from what I read, get this, chuck every single 43 00:02:41,440 --> 00:02:44,280 Speaker 1: person that's ever been killed in the United States by 44 00:02:44,280 --> 00:02:46,960 Speaker 1: a python, and take that with a grain of salt, 45 00:02:47,000 --> 00:02:50,760 Speaker 1: because they're not native to the United States. Um was 46 00:02:50,760 --> 00:02:53,400 Speaker 1: a cap was was it killed by their own by 47 00:02:53,440 --> 00:02:58,360 Speaker 1: a captive python? Usually it was their pet, and they 48 00:02:58,520 --> 00:03:01,680 Speaker 1: messed up by not fall following the proper procedures for 49 00:03:01,760 --> 00:03:05,000 Speaker 1: feeding it right, or they like went to sleep with 50 00:03:05,040 --> 00:03:07,600 Speaker 1: it wrapped around their neck yau they thought it was comforting, 51 00:03:07,960 --> 00:03:12,000 Speaker 1: or sadly they didn't keep their snake in an enclosure 52 00:03:12,040 --> 00:03:15,359 Speaker 1: like you're supposed to, and the python got ahold of 53 00:03:15,480 --> 00:03:19,160 Speaker 1: a kid in the house. That is, I can't I 54 00:03:19,200 --> 00:03:22,280 Speaker 1: can't even like put my mind there. Nightmare. But we 55 00:03:22,320 --> 00:03:24,440 Speaker 1: don't want to give python's bad name because UM in 56 00:03:24,480 --> 00:03:27,120 Speaker 1: a lot of cases there are definitely um plenty of 57 00:03:27,160 --> 00:03:31,880 Speaker 1: them that are pretty docile, nice friendly UM and UM 58 00:03:31,960 --> 00:03:33,720 Speaker 1: if they if a python does try to eat you, 59 00:03:33,800 --> 00:03:37,280 Speaker 1: it's probably a case of mistaken identity to begin with. 60 00:03:37,680 --> 00:03:41,680 Speaker 1: But also there's differences, UM that that make pythons seem 61 00:03:41,800 --> 00:03:45,000 Speaker 1: less threatening. They moved just like one mile an hour. 62 00:03:45,080 --> 00:03:53,680 Speaker 1: They're very slow. Um, they're not venomous. That's another big one, right, sure, yeah, 63 00:03:53,760 --> 00:03:56,680 Speaker 1: I think you know, Andy, I'm scared of any venomous steak, 64 00:03:57,440 --> 00:03:59,720 Speaker 1: like really scared of any venomous snake, not like a 65 00:04:00,320 --> 00:04:02,840 Speaker 1: phobia or anything. I think that's just like a legitimate fear, 66 00:04:03,280 --> 00:04:06,680 Speaker 1: that's right. Uh. They're found in Asia, Africa, and Australia. 67 00:04:06,720 --> 00:04:10,320 Speaker 1: They are Old World snakes and there are forty one 68 00:04:10,440 --> 00:04:14,840 Speaker 1: species of python. Um, we're going to concentrate on just 69 00:04:14,920 --> 00:04:19,120 Speaker 1: a few of these, but these are you know, they 70 00:04:19,200 --> 00:04:22,200 Speaker 1: along with the anaconda, which um, maybe we should do 71 00:04:22,240 --> 00:04:25,160 Speaker 1: like a shorty on anaconis at some point. But these 72 00:04:25,160 --> 00:04:28,320 Speaker 1: are these are the big daddies that are just amazing. 73 00:04:28,360 --> 00:04:31,200 Speaker 1: You can you can see a python that's twenty to 74 00:04:31,320 --> 00:04:35,679 Speaker 1: thirty ft long, and to see a snake that big 75 00:04:35,720 --> 00:04:38,200 Speaker 1: and that heavy, it's just it's it looks like a 76 00:04:38,240 --> 00:04:44,120 Speaker 1: holdover from ancient times. Yeah. Um, there are very small 77 00:04:44,160 --> 00:04:46,600 Speaker 1: pythons too, though. It turns out there's one called the 78 00:04:46,640 --> 00:04:49,360 Speaker 1: antil python. It's only about two feet long and it's 79 00:04:49,360 --> 00:04:53,760 Speaker 1: adult size. Um. But for the most part, if you're 80 00:04:53,760 --> 00:04:56,080 Speaker 1: talking about pythons. One of the ways to I think 81 00:04:56,080 --> 00:04:57,520 Speaker 1: this is probably one of the reasons why they do 82 00:04:57,560 --> 00:05:03,320 Speaker 1: seem so impressive too. They're bulk two length ratio is substantial, 83 00:05:03,360 --> 00:05:07,360 Speaker 1: which means they're like pretty big around. Even though they're 84 00:05:07,400 --> 00:05:10,600 Speaker 1: really long, they're also really big around. Um. So when 85 00:05:10,680 --> 00:05:13,599 Speaker 1: you see a snake like that, like, it definitely stands 86 00:05:13,600 --> 00:05:16,680 Speaker 1: out in your mind. Yeah. And even among big ones, 87 00:05:16,720 --> 00:05:21,000 Speaker 1: there's not the same um, the same color pattern or 88 00:05:21,000 --> 00:05:23,760 Speaker 1: anything there. They can really really differ depending on where 89 00:05:23,760 --> 00:05:27,640 Speaker 1: they are and what they need to camouflage themselves. Sometimes 90 00:05:27,680 --> 00:05:31,479 Speaker 1: you see those really pretty pattern scales that look almost 91 00:05:31,520 --> 00:05:34,880 Speaker 1: like a copper head in some ways. Uh. Sometimes they're 92 00:05:34,880 --> 00:05:37,880 Speaker 1: solid though. You've seen those big, gigantic bright green ones 93 00:05:38,000 --> 00:05:40,880 Speaker 1: or brown ones that are solid brown. Yeah, yeah, really 94 00:05:40,880 --> 00:05:44,000 Speaker 1: good looking snakes. Yeah, that's the green tree python, right, 95 00:05:44,440 --> 00:05:47,159 Speaker 1: that's right. Um. One thing I found, Chuck that I 96 00:05:47,160 --> 00:05:51,080 Speaker 1: found totally fascinating is um. A lot of python species 97 00:05:51,160 --> 00:05:57,440 Speaker 1: eat warm blooded um pray. Right. Yes, So they've developed 98 00:05:57,440 --> 00:06:00,520 Speaker 1: what are called labial pits, which are these little heat 99 00:06:00,600 --> 00:06:05,080 Speaker 1: sensing organs in their face around their mouth. Um, and 100 00:06:05,120 --> 00:06:08,880 Speaker 1: it allows them to sense uh. It's basically like the 101 00:06:08,960 --> 00:06:12,160 Speaker 1: predator remember UM, they would switch to what looked like 102 00:06:12,160 --> 00:06:16,080 Speaker 1: like thermal imaging. That's what those labial pits pick up. 103 00:06:16,440 --> 00:06:20,640 Speaker 1: But these UM snakes still also see visible light too, 104 00:06:20,640 --> 00:06:23,720 Speaker 1: so they use their eyes, but that the labial pit 105 00:06:23,880 --> 00:06:27,360 Speaker 1: information is transferred up their trigeminal nerve through their face 106 00:06:27,680 --> 00:06:30,560 Speaker 1: and eventually hits like their optics the optics center in 107 00:06:30,600 --> 00:06:33,080 Speaker 1: their brain. So and this is really tough to wrap 108 00:06:33,160 --> 00:06:37,440 Speaker 1: your head around. UM, but the the thermal imaging from 109 00:06:37,480 --> 00:06:41,640 Speaker 1: the labial pits and the visible information from their eyes 110 00:06:42,279 --> 00:06:45,920 Speaker 1: is superimposed so that they see in a way that 111 00:06:46,080 --> 00:06:49,080 Speaker 1: UM at this one site put It's impossible for us 112 00:06:49,080 --> 00:06:52,880 Speaker 1: to imagine. Isn't that awesome unless you've seen the movie Predator? 113 00:06:53,480 --> 00:06:56,720 Speaker 1: And that the um labial pits are so sensitive they 114 00:06:56,720 --> 00:07:00,800 Speaker 1: can detect changes in temperature of as little as point 115 00:07:01,080 --> 00:07:05,760 Speaker 1: zero zero one degree celsius. It's amazing, I think so too. 116 00:07:05,920 --> 00:07:09,000 Speaker 1: Good luck if you're a rabbit, I know you don't 117 00:07:09,000 --> 00:07:13,360 Speaker 1: stay in a chance. Sadly, no none, because if you 118 00:07:13,440 --> 00:07:16,320 Speaker 1: do get a python around a rabbit, they will grab 119 00:07:16,360 --> 00:07:19,040 Speaker 1: ahold of it with its triangular shaped head and they 120 00:07:19,120 --> 00:07:22,680 Speaker 1: have these sharp backward curving teeth. If you ever looked 121 00:07:22,680 --> 00:07:25,800 Speaker 1: at a Um, if you just look up pictures of 122 00:07:25,840 --> 00:07:29,520 Speaker 1: python teeth, they have a lot of sharp fangs that 123 00:07:29,520 --> 00:07:32,080 Speaker 1: are kind of pointing in the backwards direction. They don't 124 00:07:32,080 --> 00:07:35,480 Speaker 1: because they're not venomous. They don't have those two giant, 125 00:07:35,520 --> 00:07:39,280 Speaker 1: big daddy venom injectors at the front, which those are 126 00:07:39,280 --> 00:07:41,440 Speaker 1: the things that really scare me when it comes to snakes. 127 00:07:42,080 --> 00:07:45,880 Speaker 1: So pythons don't have those, but uh, they do, some 128 00:07:46,000 --> 00:07:51,920 Speaker 1: of them. Arboreal pythons have these prehensible tails that, um, 129 00:07:51,960 --> 00:07:54,760 Speaker 1: you know, there are legends of pythons like leaping from 130 00:07:54,800 --> 00:07:58,360 Speaker 1: trees to kill people or kill prey. That is not 131 00:07:58,400 --> 00:08:00,360 Speaker 1: true because that would hurt the snake to eat from 132 00:08:00,360 --> 00:08:03,640 Speaker 1: a tree. But they said in the articles I read, 133 00:08:03,640 --> 00:08:06,160 Speaker 1: they're like, well, they don't do that, but so don't worry. 134 00:08:06,200 --> 00:08:08,440 Speaker 1: But but they can really hang from the tree and 135 00:08:08,440 --> 00:08:11,480 Speaker 1: then come down and grab you. Right. They're famous for 136 00:08:11,600 --> 00:08:13,960 Speaker 1: wearing a hat and swinging down in front of your 137 00:08:13,960 --> 00:08:18,960 Speaker 1: face and going hello yeah. Basically, um, So there's some 138 00:08:19,040 --> 00:08:23,120 Speaker 1: other things about pythons that um stand out even amongst snakes. 139 00:08:23,160 --> 00:08:25,600 Speaker 1: One of the things that they have that most snakes 140 00:08:25,640 --> 00:08:29,560 Speaker 1: don't is two lungs, which is weird because it makes 141 00:08:29,600 --> 00:08:33,040 Speaker 1: them primitive. Then that seems odd we have two long 142 00:08:33,080 --> 00:08:35,880 Speaker 1: as we'd think, well, it's evolving towards humanity. Of course, 143 00:08:35,920 --> 00:08:40,040 Speaker 1: that's that's not primitive, that's the opposite. But apparently, um, 144 00:08:40,160 --> 00:08:43,839 Speaker 1: all snakes, or at least pythons I should say, evolved 145 00:08:44,120 --> 00:08:49,040 Speaker 1: from four legged, uh two long vertebrates of some sort 146 00:08:49,080 --> 00:08:53,360 Speaker 1: in the great distant past, and they just haven't evolved 147 00:08:53,400 --> 00:08:56,280 Speaker 1: into just a single lung like plenty of other snake 148 00:08:56,320 --> 00:08:59,760 Speaker 1: families have. That's right. And because of that evolution, they 149 00:08:59,760 --> 00:09:02,960 Speaker 1: all so have remnants of that stuff. They have remnants 150 00:09:02,960 --> 00:09:06,520 Speaker 1: of a pelvis and these little hind limbs and they're 151 00:09:06,520 --> 00:09:10,120 Speaker 1: called spurs located on the back, on the sides beside 152 00:09:10,160 --> 00:09:12,680 Speaker 1: the cloaca, and they use those for a bunch of 153 00:09:12,679 --> 00:09:14,680 Speaker 1: different things. But one of the things they do, and 154 00:09:14,679 --> 00:09:17,800 Speaker 1: we'll talk a little bit more about mating, they'll kind 155 00:09:17,800 --> 00:09:22,120 Speaker 1: of kind of stroke the ladies with the what's what's 156 00:09:22,240 --> 00:09:26,800 Speaker 1: left over of their vestigial limbs? I like that? Does 157 00:09:26,800 --> 00:09:33,320 Speaker 1: that creep you out? Yes? It does? It seems very sweet. So, um, 158 00:09:33,360 --> 00:09:36,760 Speaker 1: if you wanted to find a python in the wild, chuck, 159 00:09:36,800 --> 00:09:41,520 Speaker 1: where would you go? Well, already said Asia, Africa and Australia. 160 00:09:41,720 --> 00:09:45,360 Speaker 1: But what parts of those continents you would go to 161 00:09:45,360 --> 00:09:48,240 Speaker 1: where it's warm and wet. You would go maybe to 162 00:09:48,280 --> 00:09:52,800 Speaker 1: a rainforest, maybe in the woodlands or grasslands or the swamps. 163 00:09:53,920 --> 00:09:57,280 Speaker 1: They like to hide in under rocks and things. They 164 00:09:57,280 --> 00:10:00,360 Speaker 1: like to hide in little animal burrows. Like I said, 165 00:10:00,400 --> 00:10:05,040 Speaker 1: they can't hang from tree branches. Uh, this should scare everyone, 166 00:10:05,160 --> 00:10:06,800 Speaker 1: and we'll get a little bit more into how they've 167 00:10:07,360 --> 00:10:09,800 Speaker 1: made their way to Florida in the United States. But 168 00:10:10,160 --> 00:10:13,840 Speaker 1: when they are found in urban areas, they shelter in 169 00:10:14,280 --> 00:10:17,720 Speaker 1: urban debris. So you could, uh, you could pick up 170 00:10:17,720 --> 00:10:20,160 Speaker 1: a spare tire or turn over a wheelbarrow and find 171 00:10:20,160 --> 00:10:22,440 Speaker 1: a python into there. And if you were in the 172 00:10:22,960 --> 00:10:24,560 Speaker 1: in the wrong place at the wrong time, somewhere in 173 00:10:24,559 --> 00:10:30,880 Speaker 1: Florida right in the inner cities are littered with overturned wheelbarrows, 174 00:10:31,960 --> 00:10:36,000 Speaker 1: well you never know. So remember I said that python's 175 00:10:36,200 --> 00:10:38,760 Speaker 1: moved about one mile an hour. There's a reason for this. 176 00:10:39,400 --> 00:10:42,439 Speaker 1: That's really slow, just if you stop and think about it. 177 00:10:42,760 --> 00:10:45,439 Speaker 1: The reason they are so slow is because they're using 178 00:10:45,440 --> 00:10:49,800 Speaker 1: a form of movement called rectilinear progression um, which is 179 00:10:49,840 --> 00:10:54,079 Speaker 1: where they brace themselves on the ground with their ribs 180 00:10:54,760 --> 00:10:57,200 Speaker 1: and then lift their body up a little bit in 181 00:10:57,280 --> 00:11:00,240 Speaker 1: front and then push themselves forward and then just keep 182 00:11:00,320 --> 00:11:04,000 Speaker 1: repeating this. It's just kind of like, um uh, like 183 00:11:04,080 --> 00:11:09,000 Speaker 1: herky jerky moving forward in a herky jerky motion. Yeah. 184 00:11:09,240 --> 00:11:12,920 Speaker 1: I was looking at python movement and it looked like 185 00:11:12,960 --> 00:11:16,160 Speaker 1: a slither to me. It didn't stand out as much 186 00:11:16,200 --> 00:11:18,680 Speaker 1: as I thought it. What is looking really different? I 187 00:11:18,679 --> 00:11:21,680 Speaker 1: guess I should say, well, that's how they fool you. Well, 188 00:11:21,720 --> 00:11:23,719 Speaker 1: I guess so. I mean, they were definitely slow, but 189 00:11:24,160 --> 00:11:27,600 Speaker 1: I think I expected a lot more of a straight line, 190 00:11:28,040 --> 00:11:29,640 Speaker 1: and they do go in a straight line like as 191 00:11:29,679 --> 00:11:33,600 Speaker 1: opposed to like a really big S shaped slither. But 192 00:11:33,640 --> 00:11:36,199 Speaker 1: there was still some slither to their diather, you know 193 00:11:36,240 --> 00:11:39,800 Speaker 1: what I'm saying. Sure, I mean they are snakes after all. 194 00:11:39,920 --> 00:11:44,520 Speaker 1: To um they're also like frequently you can find them 195 00:11:44,520 --> 00:11:48,080 Speaker 1: in water. Apparently pythons can stay submerged in water for 196 00:11:48,160 --> 00:11:50,800 Speaker 1: up to half an hour. And one of the ways 197 00:11:50,840 --> 00:11:55,200 Speaker 1: that they they hunt is by basically hanging out in 198 00:11:55,280 --> 00:11:57,640 Speaker 1: water and waiting for something to come over to get 199 00:11:57,640 --> 00:12:00,240 Speaker 1: a little drinking and copal. And they're a will to 200 00:12:00,280 --> 00:12:05,840 Speaker 1: do this because they're um. Their their skin tones really 201 00:12:05,880 --> 00:12:09,720 Speaker 1: camouflaged well with like muddy mucky bottom. So it's really 202 00:12:09,800 --> 00:12:13,920 Speaker 1: tough to see a python, especially a Burmese python. Yeah, 203 00:12:13,920 --> 00:12:17,319 Speaker 1: there was a lot of alligators similarity. Uh, it's interesting 204 00:12:17,320 --> 00:12:20,000 Speaker 1: when I was studying this stuff. Hey, yeah, that hadn't 205 00:12:20,000 --> 00:12:23,480 Speaker 1: stuck out to me. But absolutely you're right, including how 206 00:12:23,520 --> 00:12:25,960 Speaker 1: to get away from him, which we'll get to, um, 207 00:12:25,960 --> 00:12:27,440 Speaker 1: But maybe we should take a break and we'll come 208 00:12:27,440 --> 00:12:30,040 Speaker 1: back and talk a little bit about uh they're hunting 209 00:12:30,040 --> 00:12:33,160 Speaker 1: and feeding and more detail right after this. Y yea, 210 00:13:02,320 --> 00:13:05,160 Speaker 1: so chok, we're talking about their hunting and feeding habits 211 00:13:05,440 --> 00:13:08,560 Speaker 1: and um. Like I said, they they sometimes hang out 212 00:13:08,640 --> 00:13:12,000 Speaker 1: underwater waiting for something to come up. They might also 213 00:13:12,120 --> 00:13:14,000 Speaker 1: just be hanging out on a tree branch. They might 214 00:13:14,000 --> 00:13:16,640 Speaker 1: just be hanging out under some brush. But what they're 215 00:13:16,640 --> 00:13:20,280 Speaker 1: doing every time they're hanging out is um performing the 216 00:13:20,320 --> 00:13:23,120 Speaker 1: type of hunting they do, which is ambush. They just 217 00:13:23,160 --> 00:13:25,240 Speaker 1: wait around for some prey to come and then come bout. 218 00:13:25,600 --> 00:13:29,439 Speaker 1: They get your alligators. Yeah, it is, it's like alligators. 219 00:13:29,520 --> 00:13:33,280 Speaker 1: You're right, man, Um, Please stop proving your point now. 220 00:13:34,760 --> 00:13:37,560 Speaker 1: But that's what they do. They ambush hunt, they bite, 221 00:13:37,960 --> 00:13:43,199 Speaker 1: and then they constrict bite and constrict back into the left. 222 00:13:43,880 --> 00:13:47,240 Speaker 1: That's right. If you're a little python, like the little 223 00:13:47,240 --> 00:13:48,920 Speaker 1: guys that are two or three ft long, you're gonna 224 00:13:48,920 --> 00:13:52,920 Speaker 1: eat mice and rats and things like that. Uh, lizards, 225 00:13:52,960 --> 00:13:55,120 Speaker 1: Maybe some birds might get in there if they're not 226 00:13:55,160 --> 00:14:01,880 Speaker 1: paying attention. If they're bigger, you name it man um, pigs, antelope, monkeys. 227 00:14:02,600 --> 00:14:06,800 Speaker 1: I think they found a rock python that had a 228 00:14:06,880 --> 00:14:11,480 Speaker 1: leopard in its stomach, A small leopard. Yeah, but that's 229 00:14:11,520 --> 00:14:14,920 Speaker 1: that's terrifying. That leopard doesn't win that battle. Well, So 230 00:14:15,040 --> 00:14:18,320 Speaker 1: that's something that pythons are known for, and we'll talk 231 00:14:18,400 --> 00:14:21,560 Speaker 1: more about it in a second. But they are capable 232 00:14:21,640 --> 00:14:24,480 Speaker 1: of eating things that are even bigger than they are, 233 00:14:24,560 --> 00:14:28,360 Speaker 1: which doesn't make sense even for snakes, Like that's really crazy. 234 00:14:28,440 --> 00:14:31,360 Speaker 1: Some of the stuff that they've eaten. Um. I saw 235 00:14:31,400 --> 00:14:34,720 Speaker 1: a picture, it's a really sad, terrible picture of a 236 00:14:34,720 --> 00:14:37,760 Speaker 1: python that tried to eat an alligator and it was 237 00:14:37,880 --> 00:14:41,520 Speaker 1: too big, and the python actually burst into in half 238 00:14:41,560 --> 00:14:45,600 Speaker 1: and the alligator was spilled out. But they are willing 239 00:14:45,640 --> 00:14:49,240 Speaker 1: to eat really large things because their body actually changes 240 00:14:49,360 --> 00:14:54,480 Speaker 1: to accommodate this huge um load of food that they've 241 00:14:54,520 --> 00:14:57,400 Speaker 1: just now taken on. It's got too big for a 242 00:14:57,480 --> 00:15:00,960 Speaker 1: stomach exactly, and now the body's like, now I gotta 243 00:15:01,120 --> 00:15:04,160 Speaker 1: change in adjust because this guy doesn't know his own size. 244 00:15:05,120 --> 00:15:08,360 Speaker 1: So you mentioned constriction. They are constrictors, and we'll talk 245 00:15:08,360 --> 00:15:10,200 Speaker 1: a little bit about how what they have in common 246 00:15:10,200 --> 00:15:14,160 Speaker 1: with BoA's a little bit later. But I think for many, 247 00:15:14,200 --> 00:15:17,960 Speaker 1: many years they thought that, um, well, they thought a 248 00:15:18,040 --> 00:15:20,800 Speaker 1: few things. Constriction. At first they thought was like they 249 00:15:20,800 --> 00:15:23,640 Speaker 1: were crushing their prey and like breaking their bones. That's 250 00:15:23,680 --> 00:15:26,240 Speaker 1: not true. Uh. Then for a while they thought that 251 00:15:26,280 --> 00:15:29,520 Speaker 1: they suffocated their prey and just like tightened up on 252 00:15:29,560 --> 00:15:32,280 Speaker 1: the lung so much that you can't breathe. That makes sense. 253 00:15:32,920 --> 00:15:34,400 Speaker 1: All of this sort of makes sense. But in two 254 00:15:34,440 --> 00:15:37,520 Speaker 1: thousand fifteen, uh, there was a scientific paper that came 255 00:15:37,560 --> 00:15:42,040 Speaker 1: out that basically said, hey, with boa constrictors, we now 256 00:15:42,120 --> 00:15:45,440 Speaker 1: know that what they do is they they don't suffocate you. 257 00:15:45,880 --> 00:15:48,320 Speaker 1: What they do is they cut off your brain or 258 00:15:48,400 --> 00:15:51,840 Speaker 1: your blood circulation basically, so you don't get any blood 259 00:15:51,840 --> 00:15:54,160 Speaker 1: to your brain and that's how you die. So it 260 00:15:54,280 --> 00:15:56,840 Speaker 1: may be true for pythons as well, because they are 261 00:15:56,880 --> 00:16:00,520 Speaker 1: also constrictors. Obviously, yeah, it would make a lot of sense. Um, 262 00:16:00,560 --> 00:16:03,560 Speaker 1: And that actually makes even more sense than than preventing 263 00:16:03,600 --> 00:16:06,560 Speaker 1: you from breathing, because you would lose consciousness much faster 264 00:16:06,680 --> 00:16:08,920 Speaker 1: if they can cut off the blood supply to your brain, 265 00:16:09,720 --> 00:16:12,800 Speaker 1: which is what you want to happen, because when they 266 00:16:12,800 --> 00:16:16,160 Speaker 1: when they capture you by biting your head like you're 267 00:16:16,200 --> 00:16:19,960 Speaker 1: eating head first by a python, you would probably hope, 268 00:16:20,040 --> 00:16:23,080 Speaker 1: no matter whether you're a person or a buddy, that 269 00:16:23,200 --> 00:16:25,600 Speaker 1: you have lost consciousness by the time it starts to 270 00:16:25,640 --> 00:16:31,120 Speaker 1: swallow you head first. Yeah. I saw a video of 271 00:16:31,200 --> 00:16:36,360 Speaker 1: someone feeding a dead bunny to this python on a 272 00:16:36,400 --> 00:16:42,240 Speaker 1: porch and it was, you know, it's just it was 273 00:16:42,720 --> 00:16:45,600 Speaker 1: it's just not fun to watch. I mean's super interesting, 274 00:16:46,400 --> 00:16:48,720 Speaker 1: but uh and again it wasn't a lie bunny. But 275 00:16:49,280 --> 00:16:51,480 Speaker 1: you know, when you when you see an animal consuming, 276 00:16:51,480 --> 00:16:54,920 Speaker 1: like unhinging that jaw and working this bunny's body into 277 00:16:54,960 --> 00:16:58,200 Speaker 1: its mouth, it's just it's amazing in a nature sense. 278 00:16:58,240 --> 00:17:01,200 Speaker 1: But I didn't watch at all, let's put it that way. 279 00:17:01,400 --> 00:17:05,119 Speaker 1: I don't blame you, so, Chuck, I think we should 280 00:17:05,160 --> 00:17:09,800 Speaker 1: talk about the studies of trying to figure out how 281 00:17:09,840 --> 00:17:13,680 Speaker 1: pythons can eat things that are so much bigger than it, 282 00:17:13,840 --> 00:17:17,440 Speaker 1: or just so enormous to begin with, not necessarily even 283 00:17:17,480 --> 00:17:21,000 Speaker 1: bigger than the snake, but way bigger than anything you 284 00:17:21,160 --> 00:17:25,240 Speaker 1: or I could eat proportionately, right, that's right. And they've 285 00:17:25,240 --> 00:17:30,720 Speaker 1: figured out thanks to um genetic sequencing, they see they 286 00:17:30,760 --> 00:17:35,119 Speaker 1: sequence the genome of the Burmese python um and found 287 00:17:35,160 --> 00:17:39,000 Speaker 1: out that it's actually their genes changed. The way that 288 00:17:39,040 --> 00:17:44,840 Speaker 1: their genes express um things like proteins or affect their metabolism. 289 00:17:45,080 --> 00:17:48,439 Speaker 1: All this stuff actually changes when they eat, and it 290 00:17:48,480 --> 00:17:52,040 Speaker 1: happens really fast, and the changes that it creates are 291 00:17:52,240 --> 00:17:56,040 Speaker 1: really really dramatic. Yeah, I mean the fact that this 292 00:17:56,160 --> 00:18:00,200 Speaker 1: was naturally selected over I mean they think that happenedically 293 00:18:00,240 --> 00:18:03,560 Speaker 1: as well, right, yeah, yeah, like the that during its 294 00:18:03,560 --> 00:18:07,359 Speaker 1: evolution it started picking up these these positive adaptations like 295 00:18:07,480 --> 00:18:09,760 Speaker 1: really fast. And the main thing they found out that 296 00:18:09,800 --> 00:18:11,919 Speaker 1: it was allows pythons to eat things that are as 297 00:18:11,960 --> 00:18:14,800 Speaker 1: big as they are is their their organs shrink when 298 00:18:14,800 --> 00:18:17,840 Speaker 1: they're eating to to make room in there, like their 299 00:18:17,880 --> 00:18:21,240 Speaker 1: liver and their kidneys and their intestines. They act in 300 00:18:21,280 --> 00:18:24,440 Speaker 1: their heart even get smaller while they're eating these things 301 00:18:24,440 --> 00:18:27,480 Speaker 1: to create space. And after like some of these things, 302 00:18:27,520 --> 00:18:30,080 Speaker 1: I think the liver actually doubles in mass in the 303 00:18:30,080 --> 00:18:33,600 Speaker 1: two days after they're done eating. Yeah, their heart actually 304 00:18:33,720 --> 00:18:38,399 Speaker 1: increases in size by about in the two days after 305 00:18:38,480 --> 00:18:42,639 Speaker 1: they eat, which is like that that is very unusual, 306 00:18:43,080 --> 00:18:47,520 Speaker 1: but it actually has to happen because the metabolism that's 307 00:18:47,520 --> 00:18:50,240 Speaker 1: required to eat this huge thing, because we didn't I 308 00:18:50,240 --> 00:18:52,239 Speaker 1: don't know if we said, like they'll go like a 309 00:18:52,240 --> 00:18:55,159 Speaker 1: week without eating, they'll eat once a week. So the 310 00:18:55,200 --> 00:18:57,680 Speaker 1: rest of the time they're their metabolism is just going 311 00:18:57,720 --> 00:19:00,560 Speaker 1: along doing whatever. Then all of a sudden it's presented 312 00:19:00,600 --> 00:19:03,160 Speaker 1: with this huge piece of food that it needs to digest. 313 00:19:03,359 --> 00:19:06,080 Speaker 1: So it's a huge increase in metabolic demand, and the 314 00:19:06,160 --> 00:19:10,439 Speaker 1: heart actually increases in size to accommodate that increase in 315 00:19:10,480 --> 00:19:14,679 Speaker 1: metabolic demand. It's amazing, it really is. And they figured 316 00:19:14,720 --> 00:19:18,320 Speaker 1: out that it's their genes just become super active and 317 00:19:18,520 --> 00:19:21,800 Speaker 1: start producing way more proteins and um just doing all 318 00:19:21,800 --> 00:19:24,880 Speaker 1: this stuff that under normal circumstances when they're not digesting 319 00:19:24,960 --> 00:19:28,800 Speaker 1: food just doesn't. It's just not how their genes behave. 320 00:19:29,720 --> 00:19:32,800 Speaker 1: And if you're wondering how they're breathing with a rabbit 321 00:19:32,920 --> 00:19:36,119 Speaker 1: stuff down their throats, they have a windpipe that opens 322 00:19:36,119 --> 00:19:37,840 Speaker 1: at the front of the mouth so they can breathe 323 00:19:37,840 --> 00:19:40,160 Speaker 1: while they're doing this stuff. Yeah, I saw it described 324 00:19:40,200 --> 00:19:45,200 Speaker 1: as kind of popping up like a periscope. Yeah, that's amazing. 325 00:19:46,040 --> 00:19:48,760 Speaker 1: So what about reproduction. I know that you really like 326 00:19:48,840 --> 00:19:51,040 Speaker 1: how they court. Do you want to talk some more 327 00:19:51,080 --> 00:19:54,280 Speaker 1: about that. Yeah. When they make kind of depends on 328 00:19:54,320 --> 00:19:57,359 Speaker 1: which species it is. It's not set in stone, but 329 00:19:57,480 --> 00:20:01,600 Speaker 1: they do. Those males use those spurs that were originally 330 00:20:01,680 --> 00:20:06,600 Speaker 1: limbs to stroke the female, and once they impregnate them, 331 00:20:06,680 --> 00:20:10,399 Speaker 1: the ladies they lay eggs. Actually, um, which is another 332 00:20:10,440 --> 00:20:13,760 Speaker 1: thing that's different than other boas even is that they 333 00:20:13,800 --> 00:20:18,080 Speaker 1: give birth to live young, but pythons give give birth 334 00:20:18,160 --> 00:20:20,359 Speaker 1: to little egg Well, I guess big eggs because some 335 00:20:20,400 --> 00:20:22,120 Speaker 1: of these things are a couple of feet long when 336 00:20:22,119 --> 00:20:23,960 Speaker 1: they come out when they hatch. I saw there about 337 00:20:24,040 --> 00:20:27,000 Speaker 1: the size of chicken eggs. Well, how could they be 338 00:20:27,080 --> 00:20:29,399 Speaker 1: two ft long? I don't know, crazy, I don't know, 339 00:20:31,000 --> 00:20:33,080 Speaker 1: I don't know. I guess maybe they eat themselves while 340 00:20:33,080 --> 00:20:39,840 Speaker 1: they're in the egg. Uh. They do provide most of 341 00:20:39,840 --> 00:20:42,720 Speaker 1: the time some parental care, and they make little nest 342 00:20:42,800 --> 00:20:46,680 Speaker 1: Mama does and keep some warm and like protected spaces 343 00:20:46,760 --> 00:20:49,680 Speaker 1: under logs and stuff like that, and you know, sort 344 00:20:49,680 --> 00:20:53,680 Speaker 1: of burrowed areas and they coil around them. Um. If 345 00:20:53,840 --> 00:20:57,639 Speaker 1: they since temperature changing whatever, the mother will sort of 346 00:20:58,240 --> 00:21:00,720 Speaker 1: flex her muscles and sort of can tracked in place 347 00:21:00,760 --> 00:21:03,240 Speaker 1: to heat up her own body to warm up the eggs. 348 00:21:03,800 --> 00:21:08,719 Speaker 1: That's called shivering thermogenesis. And they're not feeding when this 349 00:21:08,800 --> 00:21:11,520 Speaker 1: is going on. They're only leaving their nest if they 350 00:21:11,560 --> 00:21:13,880 Speaker 1: want to really warm up, and they call that basking, 351 00:21:14,280 --> 00:21:16,720 Speaker 1: just like we do. Yeah, and then the eggs hatch 352 00:21:16,760 --> 00:21:20,639 Speaker 1: and the mom says, see you, and that's that um. 353 00:21:20,720 --> 00:21:24,320 Speaker 1: And depending on the species, like they they will um 354 00:21:24,520 --> 00:21:29,360 Speaker 1: reproduce fairly frequently. I think a female snake um produces 355 00:21:29,359 --> 00:21:32,600 Speaker 1: about forty eggs every two years. They start breeding at 356 00:21:32,600 --> 00:21:36,960 Speaker 1: about three to four years old, so like they're you know, 357 00:21:37,000 --> 00:21:41,760 Speaker 1: a pretty successful family of snakes. They reproduce pretty frequently. 358 00:21:42,160 --> 00:21:44,800 Speaker 1: And then I guess because the hatchlings are so big 359 00:21:44,840 --> 00:21:47,280 Speaker 1: when they're born, they don't really need to be raised 360 00:21:47,359 --> 00:21:50,120 Speaker 1: or nurtured or protected. They're just on their own from 361 00:21:50,160 --> 00:21:52,639 Speaker 1: the moment they come out of the egg, and they 362 00:21:52,640 --> 00:21:56,280 Speaker 1: can live decades. They can live a long long time, 363 00:21:56,320 --> 00:21:59,439 Speaker 1: which is why a lot of snake enthusiasts love him 364 00:21:59,440 --> 00:22:01,920 Speaker 1: as pets. I think the San Diego zeus says about 365 00:22:01,960 --> 00:22:05,480 Speaker 1: thirty five years, which is that's a long time. Yeah, 366 00:22:05,520 --> 00:22:08,920 Speaker 1: that's at the tippy top. So, Chuck, I believe that 367 00:22:08,960 --> 00:22:13,200 Speaker 1: we should speak uh at length about the Burmese python 368 00:22:13,400 --> 00:22:17,080 Speaker 1: because this is as far as pythons go, it's very 369 00:22:17,160 --> 00:22:20,560 Speaker 1: very beautiful snake. It's actually highly prized for its skin. 370 00:22:20,760 --> 00:22:24,000 Speaker 1: Sad for the Burmese python, but it also has a 371 00:22:24,040 --> 00:22:30,359 Speaker 1: really interesting story here in the United States. That's right. Um. 372 00:22:30,480 --> 00:22:34,000 Speaker 1: They have pale tan, sort of gray bodies sometimes yellow brown. 373 00:22:34,520 --> 00:22:38,720 Speaker 1: They have these big sort of reddish splotches. Uh. And 374 00:22:38,720 --> 00:22:40,760 Speaker 1: they have their sort of um almost like they were 375 00:22:40,840 --> 00:22:44,320 Speaker 1: drawn around their outlined in different colors white or yellow usually, 376 00:22:44,359 --> 00:22:48,520 Speaker 1: and they are really pretty. And they are in Florida. Um, 377 00:22:48,560 --> 00:22:51,680 Speaker 1: just like uh, we were talking about the alligators. There's 378 00:22:53,119 --> 00:22:54,800 Speaker 1: I don't I mean, I guess you would call it 379 00:22:54,840 --> 00:22:57,800 Speaker 1: a python problem. In one sense, it's it's not as 380 00:22:57,880 --> 00:23:00,399 Speaker 1: much of a problem in that they're not really like 381 00:23:00,480 --> 00:23:04,120 Speaker 1: coming out of the wild and attacking people really um, 382 00:23:04,160 --> 00:23:07,520 Speaker 1: but they're they're make wreaking havoc on the local ecosystem 383 00:23:07,560 --> 00:23:10,520 Speaker 1: there as far as mammals go, it's an ecological disaster 384 00:23:10,880 --> 00:23:13,560 Speaker 1: as a matter of fact. Like it's if you're in 385 00:23:13,600 --> 00:23:16,720 Speaker 1: the Everglades and you care about biodiversity, you you have 386 00:23:16,840 --> 00:23:20,080 Speaker 1: a real problem with the Burmese python, which have been 387 00:23:20,119 --> 00:23:25,280 Speaker 1: really successful in setting up shop in the Everglades specifically. UM. 388 00:23:25,320 --> 00:23:28,320 Speaker 1: But they're an invasive species because they're not supposed to 389 00:23:28,359 --> 00:23:31,719 Speaker 1: be there. There haven't been snakes this large native to 390 00:23:31,800 --> 00:23:36,080 Speaker 1: the to the America's since long before humans were around. 391 00:23:36,560 --> 00:23:39,600 Speaker 1: So they came in and there they have no predators 392 00:23:39,920 --> 00:23:43,800 Speaker 1: there themselves, like an apex predator, and um, they've been 393 00:23:43,840 --> 00:23:47,119 Speaker 1: eating everything they can get their hands on, basically. And 394 00:23:47,200 --> 00:23:50,840 Speaker 1: the crazy thing about this is that they set up 395 00:23:50,920 --> 00:23:54,840 Speaker 1: shop in the Everglades because people started releasing them um 396 00:23:55,000 --> 00:23:58,160 Speaker 1: as pets. They were pets that got released and abandoned, 397 00:23:58,359 --> 00:24:02,399 Speaker 1: and now they're huge problem in Florida. Yeah. And and 398 00:24:02,520 --> 00:24:08,160 Speaker 1: not just like oh, you know there's been a decline 399 00:24:08,200 --> 00:24:11,320 Speaker 1: in in this roadent or this species. There was a 400 00:24:11,320 --> 00:24:14,120 Speaker 1: study and this is in twelve even Uh, the raccoon 401 00:24:14,320 --> 00:24:20,000 Speaker 1: population dropped nine three percent, possums almost extinct ninety eight 402 00:24:20,040 --> 00:24:24,399 Speaker 1: point nine percent, bobcats eighty seven point five percent, and 403 00:24:24,440 --> 00:24:29,639 Speaker 1: this from to two thousand twelve. Uh. And essentially foxes 404 00:24:29,800 --> 00:24:34,120 Speaker 1: and and rabbits have all but disappeared in the Everglades. Yeah, 405 00:24:34,400 --> 00:24:38,080 Speaker 1: so again that's an ecological catastrophe because not only is 406 00:24:38,080 --> 00:24:42,760 Speaker 1: it eating all of these important like um animals, they're 407 00:24:42,800 --> 00:24:46,000 Speaker 1: also competing with other larger stuff for food too, so 408 00:24:46,040 --> 00:24:48,760 Speaker 1: they're having an effect on like the local alligators and 409 00:24:48,880 --> 00:24:53,280 Speaker 1: other like probably the whatever panthers are down there. Um. 410 00:24:53,320 --> 00:24:56,200 Speaker 1: So it's a huge problem that they're there, and as 411 00:24:56,200 --> 00:25:00,720 Speaker 1: a result they're finding that um that Lord is basically 412 00:25:00,720 --> 00:25:03,919 Speaker 1: trying to figure out anything it can do to handle 413 00:25:03,960 --> 00:25:07,119 Speaker 1: this stuff. And I read that there's this thing called 414 00:25:07,160 --> 00:25:12,600 Speaker 1: the Python Challenge, the Annual Python Challenge, where they basically say, hey, 415 00:25:12,640 --> 00:25:15,879 Speaker 1: anybody and everybody who has a gun or a stick 416 00:25:16,320 --> 00:25:20,159 Speaker 1: or a knife or whatever you want to use to 417 00:25:20,280 --> 00:25:23,080 Speaker 1: kill a python, will give ten thousand dollars to the 418 00:25:23,080 --> 00:25:26,199 Speaker 1: person who kills the most pythons this year during this 419 00:25:26,280 --> 00:25:29,520 Speaker 1: Python Challenge. That's the level that Florida is at right now, 420 00:25:29,960 --> 00:25:34,240 Speaker 1: and it's having almost no effect because there's number one, 421 00:25:34,320 --> 00:25:37,000 Speaker 1: so many of them, but also because it is so 422 00:25:37,480 --> 00:25:41,200 Speaker 1: hard to see a python, even when you're basically standing 423 00:25:41,200 --> 00:25:44,360 Speaker 1: on top of it. It's that good. A Burmese python 424 00:25:44,480 --> 00:25:48,160 Speaker 1: is that good at camouflaging itself in the Everglades. Well, yeah, 425 00:25:48,200 --> 00:25:51,800 Speaker 1: that in the twenty eggs a year, right, Well that 426 00:25:51,880 --> 00:25:54,360 Speaker 1: was another thing to chuck is because the hatchlings are 427 00:25:54,400 --> 00:25:57,160 Speaker 1: so big. Do you remember when we talked about alligators 428 00:25:57,240 --> 00:25:59,919 Speaker 1: and how their numbers are kept in check because rack 429 00:26:00,040 --> 00:26:04,760 Speaker 1: coons will eat their hatchlings. Well, these Burmese pythons hatchlings 430 00:26:04,800 --> 00:26:07,919 Speaker 1: are so big. There's nothing in the Everglades that is 431 00:26:07,960 --> 00:26:11,959 Speaker 1: going to eat them. So they're incredibly successful at reproducing too. 432 00:26:12,040 --> 00:26:15,399 Speaker 1: That's a really good point. I'm trying to imagine something 433 00:26:15,440 --> 00:26:17,600 Speaker 1: thirty six inches long coming out of a chicken egg. 434 00:26:17,800 --> 00:26:20,240 Speaker 1: I know, even if it was, I guess it would 435 00:26:20,240 --> 00:26:23,400 Speaker 1: have to be the width of like a worm. Yeah, 436 00:26:23,480 --> 00:26:24,879 Speaker 1: it would be a little bit bigger, it would have 437 00:26:24,920 --> 00:26:27,080 Speaker 1: to be thin. But again, pythons are known for their 438 00:26:27,119 --> 00:26:29,600 Speaker 1: bulky nous, right, So I don't know. I just saw 439 00:26:29,640 --> 00:26:33,000 Speaker 1: I read a I believe it was a Smithsonian article 440 00:26:33,119 --> 00:26:36,399 Speaker 1: that was kind of the journalist was embedded with people who, 441 00:26:36,720 --> 00:26:39,919 Speaker 1: you know, hunt and track Burmese pythons in the Everglades. 442 00:26:40,000 --> 00:26:43,840 Speaker 1: Apparently there's an all women tracking team called the Everglades 443 00:26:43,840 --> 00:26:48,280 Speaker 1: Avengers um and like they somebody who knows what they're 444 00:26:48,280 --> 00:26:50,720 Speaker 1: talking about, describes it as the size of a chicken egg. 445 00:26:51,160 --> 00:26:54,199 Speaker 1: So that's where I got that from. So act if 446 00:26:54,240 --> 00:26:57,040 Speaker 1: I'm wrong, they were wrong. They look a little bigger, 447 00:26:59,440 --> 00:27:03,320 Speaker 1: but not much bigger. I guess they're just wrapped up. 448 00:27:03,680 --> 00:27:06,240 Speaker 1: They must just be really thin and bulk up really fast. 449 00:27:06,280 --> 00:27:08,680 Speaker 1: It goes stroying when they come out of their egg. 450 00:27:09,440 --> 00:27:12,640 Speaker 1: So you mentioned the Everglades. You're definitely all over the Everglades, 451 00:27:12,680 --> 00:27:17,600 Speaker 1: but they're expanding their territory. They're also in Big Cypress 452 00:27:17,680 --> 00:27:22,960 Speaker 1: National Preserve. They are in Collier Seminole State Forest. They 453 00:27:23,040 --> 00:27:27,119 Speaker 1: have been found in Miami, mh. They have been found 454 00:27:27,160 --> 00:27:31,359 Speaker 1: in the Florida Keys, which is means one of two things. 455 00:27:31,400 --> 00:27:34,600 Speaker 1: Either someone brought them there and release them there, or 456 00:27:35,080 --> 00:27:39,920 Speaker 1: they can tolerate saltwater. They were python swimming in the ocean. Yeah, 457 00:27:39,960 --> 00:27:43,000 Speaker 1: apparently that's been documented that they're you know, they're good 458 00:27:43,040 --> 00:27:46,719 Speaker 1: swimmers and they comp apparently tolerate saltwater, so it's entirely 459 00:27:46,720 --> 00:27:49,880 Speaker 1: possible they swim under the keys. Could you imagine doing 460 00:27:49,880 --> 00:27:54,399 Speaker 1: a little ocean swimming and seeing a freaking python. Yeah, 461 00:27:54,440 --> 00:27:56,359 Speaker 1: Because I mean these things get big, like in their 462 00:27:56,440 --> 00:28:00,320 Speaker 1: native habitat um in Southeast Asia. They it up to 463 00:28:00,359 --> 00:28:04,359 Speaker 1: about twenty six and two pounds. Apparently the ones in 464 00:28:04,440 --> 00:28:08,520 Speaker 1: Florida usually are average about eight to ten feet, so 465 00:28:08,840 --> 00:28:12,400 Speaker 1: that's still a very significant bulky snake that you would 466 00:28:12,400 --> 00:28:15,600 Speaker 1: see coming swimming at you while you're waiting in the water, 467 00:28:15,720 --> 00:28:20,160 Speaker 1: going how are you? I think those are I think 468 00:28:20,160 --> 00:28:23,720 Speaker 1: the ones in Miami those are African pythons are right, yes, 469 00:28:23,840 --> 00:28:28,280 Speaker 1: which apparently are almost indistinguishable from Burmese pythons to the 470 00:28:28,320 --> 00:28:33,200 Speaker 1: average person. So suburban and urban areas of Miami have pythons. Yeah, 471 00:28:33,200 --> 00:28:37,080 Speaker 1: they also have boa constrictors. Apparently there's a big iguana 472 00:28:37,160 --> 00:28:39,920 Speaker 1: problem down there as well, all from just jerks releasing 473 00:28:39,960 --> 00:28:43,400 Speaker 1: their pets that they don't want any longer because they 474 00:28:43,640 --> 00:28:46,480 Speaker 1: there's there's a really big problem with in scrupulous um 475 00:28:46,680 --> 00:28:51,080 Speaker 1: snake dealers, backyard breeders, people who actually have storefronts um 476 00:28:51,120 --> 00:28:55,120 Speaker 1: even like corporate chain pet stores selling snakes um and 477 00:28:55,120 --> 00:28:57,640 Speaker 1: and being like you have to kill a mouse to 478 00:28:57,760 --> 00:29:01,040 Speaker 1: feed this thing. Um. There's a lot of like this. 479 00:29:01,080 --> 00:29:03,640 Speaker 1: It's not just intuitive how to keep a snake happy 480 00:29:03,680 --> 00:29:06,560 Speaker 1: and healthy, and so people get overwhelmed by snakes and 481 00:29:06,800 --> 00:29:08,560 Speaker 1: they don't know what to do with them. So if 482 00:29:08,600 --> 00:29:11,160 Speaker 1: you're in Florida around Miami. You just release it in 483 00:29:11,160 --> 00:29:14,280 Speaker 1: your backyard and say see you later, and the snake 484 00:29:14,400 --> 00:29:17,240 Speaker 1: takes off and becomes a problem in the Everglades with 485 00:29:17,360 --> 00:29:20,960 Speaker 1: a tear rolling down its cheek. That's right through Pastco 486 00:29:21,320 --> 00:29:24,440 Speaker 1: Pasco and don't look back, right, and it turns around 487 00:29:24,440 --> 00:29:25,960 Speaker 1: and you have to punch a snake in the face 488 00:29:26,000 --> 00:29:31,360 Speaker 1: and go go right. I'd never liked you to begin with. Uh, 489 00:29:31,920 --> 00:29:33,960 Speaker 1: I think we need to take a second break, stol Right, yeah, 490 00:29:34,680 --> 00:29:36,800 Speaker 1: all right, let's do that, and we'll talk a little 491 00:29:36,840 --> 00:29:38,560 Speaker 1: bit more about what you can do if you do 492 00:29:38,600 --> 00:29:41,800 Speaker 1: see a python in the wild, and all about pet pythons, 493 00:29:41,880 --> 00:30:14,160 Speaker 1: the sweetest kind right after this. All right, we've established 494 00:30:14,200 --> 00:30:17,600 Speaker 1: that you're probably not in danger of being attacked by 495 00:30:17,640 --> 00:30:22,640 Speaker 1: a python in the wild in the United States. Um, 496 00:30:22,680 --> 00:30:24,600 Speaker 1: as far as we know, that has not happened. I 497 00:30:24,600 --> 00:30:28,560 Speaker 1: don't even think once. Right, that's my understanding. All right, good, 498 00:30:28,680 --> 00:30:31,880 Speaker 1: let's just keep that going. Let's keep that record intact. Uh, 499 00:30:31,920 --> 00:30:33,920 Speaker 1: if you do see a python in the wild, if 500 00:30:33,920 --> 00:30:36,880 Speaker 1: you're living in Florida, they have apps. Now, they have 501 00:30:37,000 --> 00:30:41,120 Speaker 1: hot lines. I've got one is the name of the program. 502 00:30:41,160 --> 00:30:46,360 Speaker 1: There's a hot line eight one or smartphone applications. I've 503 00:30:46,360 --> 00:30:47,880 Speaker 1: got one. You can just get that app if you 504 00:30:47,880 --> 00:30:50,240 Speaker 1: live in the area, and you just report that thing. 505 00:30:50,800 --> 00:30:52,480 Speaker 1: If you don't have the app, just go to the 506 00:30:52,560 --> 00:30:56,040 Speaker 1: National Park ranger say hey, I saw python over there. 507 00:30:56,040 --> 00:30:58,520 Speaker 1: By that time, it's probably way too late. Um, they're 508 00:30:58,520 --> 00:31:02,040 Speaker 1: probably out of there, but you should definitely report it 509 00:31:02,040 --> 00:31:05,240 Speaker 1: because it's a big, big issue and it's not you know, 510 00:31:05,960 --> 00:31:08,400 Speaker 1: I guess it sounds a little awful that they're just saying, 511 00:31:08,400 --> 00:31:10,880 Speaker 1: go kill as many as you can for ten thousand bucks. 512 00:31:10,920 --> 00:31:13,800 Speaker 1: But it is, like you said, it is wrecking the 513 00:31:13,840 --> 00:31:17,400 Speaker 1: ecosystem down there, and that's that's not good for anyone, know, 514 00:31:17,800 --> 00:31:21,000 Speaker 1: and the people like it's still sad for the Burmese pythons. 515 00:31:21,040 --> 00:31:23,280 Speaker 1: They're just doing their thing. They just happen to be 516 00:31:23,400 --> 00:31:27,320 Speaker 1: very successful. It's the people who released them that are 517 00:31:27,600 --> 00:31:30,720 Speaker 1: really at fault and deserve everyone's scorn. Sure, but we 518 00:31:30,720 --> 00:31:32,680 Speaker 1: should talk about the ball python, which and this is 519 00:31:32,720 --> 00:31:36,720 Speaker 1: sort of the uh, the the go to pet. If 520 00:31:36,760 --> 00:31:38,720 Speaker 1: you want a constrictor and you don't want to Boa, 521 00:31:39,240 --> 00:31:42,120 Speaker 1: you can go with the old ball python. Yeah, they're 522 00:31:42,160 --> 00:31:45,600 Speaker 1: a lot more docile, they're much smaller, they grow maybe 523 00:31:45,640 --> 00:31:48,920 Speaker 1: to five or six feet. They don't move around much. 524 00:31:48,960 --> 00:31:52,160 Speaker 1: They don't they're not super active, so they are as 525 00:31:52,160 --> 00:31:54,080 Speaker 1: if you're going to have a snake as a pet, 526 00:31:54,080 --> 00:31:57,400 Speaker 1: a ball python is a good way to go for sure. Yeah. 527 00:31:57,440 --> 00:32:01,040 Speaker 1: They've got little dark uh stripes a lot times on 528 00:32:01,080 --> 00:32:03,280 Speaker 1: their face. You have like through like through their eyes. 529 00:32:03,360 --> 00:32:06,800 Speaker 1: It's very pretty, Yeah, very pretty snake. Uh. They have 530 00:32:06,920 --> 00:32:10,360 Speaker 1: these again those dark blotches that are outlined in a 531 00:32:10,440 --> 00:32:15,120 Speaker 1: lighter color. Very attractive skins. And again it's very sad 532 00:32:15,120 --> 00:32:18,920 Speaker 1: that their skins are being used for you know, bipoachers 533 00:32:19,000 --> 00:32:24,240 Speaker 1: or whatever to sell. Uh. They there are albino pythons 534 00:32:24,280 --> 00:32:28,560 Speaker 1: as well, which has become such a favorite snake that 535 00:32:28,600 --> 00:32:33,040 Speaker 1: they're actually breeding this into them. Yeah, they don't have 536 00:32:33,120 --> 00:32:36,560 Speaker 1: albini is. Um, they have a melotint ism, a melan 537 00:32:36,840 --> 00:32:41,120 Speaker 1: a melan is ism they I think that proves that 538 00:32:41,200 --> 00:32:45,760 Speaker 1: doesn't have quite the ring though melanists DoSM whatever. But 539 00:32:46,000 --> 00:32:49,000 Speaker 1: one of the there's actually some types of ball pythons 540 00:32:49,080 --> 00:32:52,280 Speaker 1: that um, they'll have like a yellow body and then 541 00:32:52,320 --> 00:32:55,160 Speaker 1: their stripes are actually lacking in pigments so it looks 542 00:32:55,200 --> 00:32:58,600 Speaker 1: like yellow and white. Um. There's ones that have black 543 00:32:58,640 --> 00:33:00,880 Speaker 1: stripes but they're lacking pig men in their body, so 544 00:33:00,920 --> 00:33:04,120 Speaker 1: it's like this black and white the really gorgeous snakes 545 00:33:04,240 --> 00:33:07,520 Speaker 1: for sure. Yes, and like you said, they are docile. 546 00:33:07,960 --> 00:33:10,680 Speaker 1: They're good. If you have never even had a snake before, 547 00:33:10,720 --> 00:33:12,800 Speaker 1: it could be a good place to start if you've 548 00:33:12,880 --> 00:33:15,800 Speaker 1: never if you didn't even know snakes existed. The bald 549 00:33:15,800 --> 00:33:18,720 Speaker 1: python is a great place to start. It is. They're 550 00:33:18,720 --> 00:33:21,320 Speaker 1: called ball pythons because if they get threatened, they curl 551 00:33:21,400 --> 00:33:23,360 Speaker 1: up and roll up in a little ball. It's very cute. 552 00:33:23,600 --> 00:33:27,320 Speaker 1: It's very sensible too. So um, if you are going 553 00:33:27,360 --> 00:33:30,160 Speaker 1: to buy a snake, you probably do not want a 554 00:33:30,200 --> 00:33:34,320 Speaker 1: wild caught ball python because when they're caught, they don't 555 00:33:34,480 --> 00:33:37,080 Speaker 1: really want to leave their home in the wilderness and 556 00:33:37,120 --> 00:33:40,120 Speaker 1: come to your home, so they're going to be stressed out. Snakes, 557 00:33:40,200 --> 00:33:43,880 Speaker 1: like all other captive animals, who get bored and they're 558 00:33:43,920 --> 00:33:48,160 Speaker 1: not cared for, can just can um display zookosis and 559 00:33:48,240 --> 00:33:51,400 Speaker 1: other terrible habits. Um. So you would probably want to 560 00:33:51,400 --> 00:33:54,440 Speaker 1: get one from a breeder or a pet store or 561 00:33:54,480 --> 00:33:58,240 Speaker 1: something like that. But again you should consider um you're 562 00:33:58,280 --> 00:34:00,600 Speaker 1: taking something out of the wild, even if it wasn't 563 00:34:00,600 --> 00:34:02,440 Speaker 1: born in the wild, and keeping it in a little 564 00:34:02,480 --> 00:34:05,480 Speaker 1: twenty gallon aquarium in your house. So I think that 565 00:34:05,600 --> 00:34:10,560 Speaker 1: part through first. Yeah, and they don't, Um, it's not 566 00:34:10,680 --> 00:34:12,680 Speaker 1: mean to keep them in a smaller enclosure. They like 567 00:34:12,760 --> 00:34:16,120 Speaker 1: tight spaces, So you don't need to get this huge 568 00:34:16,239 --> 00:34:19,520 Speaker 1: thing for your ball python. Um no, you would, that 569 00:34:19,600 --> 00:34:21,799 Speaker 1: would be mean, actually is from what Yeah, I mean 570 00:34:21,800 --> 00:34:23,200 Speaker 1: they need a little bit of room, but they like 571 00:34:23,760 --> 00:34:27,680 Speaker 1: they're not real active again, and they like tight spaces. Uh. 572 00:34:27,680 --> 00:34:30,239 Speaker 1: They it has to be really secure because they are 573 00:34:30,280 --> 00:34:34,800 Speaker 1: great at getting out of those cages and exploring your apartment. 574 00:34:35,719 --> 00:34:38,160 Speaker 1: I think one of the reasons we talked about their lifespan. 575 00:34:38,200 --> 00:34:41,080 Speaker 1: I think one of the reasons people um release them 576 00:34:41,120 --> 00:34:44,760 Speaker 1: sometimes is even though they know this getting into it, 577 00:34:44,760 --> 00:34:47,520 Speaker 1: it's hard to make a thirty year commitment to something. 578 00:34:48,719 --> 00:34:51,440 Speaker 1: So if you're you know, if you're some forty to 579 00:34:51,560 --> 00:34:54,520 Speaker 1: fifty year old dude and you're like get into snakes 580 00:34:54,520 --> 00:34:56,560 Speaker 1: all of a sudden, you're not thinking about what's going 581 00:34:56,600 --> 00:34:59,680 Speaker 1: to be going on when you're eighty, Uh, you might 582 00:35:00,040 --> 00:35:02,000 Speaker 1: us away, your family may not know what to do 583 00:35:02,040 --> 00:35:04,160 Speaker 1: with it, and release it. So this is a long 584 00:35:04,360 --> 00:35:07,439 Speaker 1: term commitment that you really really need to think through, 585 00:35:07,760 --> 00:35:09,799 Speaker 1: right if you're going to do this, Let's say you're 586 00:35:09,840 --> 00:35:11,640 Speaker 1: under the age of fifty and you're like, I'm into 587 00:35:11,640 --> 00:35:14,759 Speaker 1: snakes now, Um, there are some things you want to do. Um. 588 00:35:14,880 --> 00:35:17,399 Speaker 1: You want to keep your snake nice and warm. Uh. 589 00:35:17,440 --> 00:35:20,000 Speaker 1: And in fact, you want to have basically dual climate 590 00:35:20,080 --> 00:35:23,800 Speaker 1: zones in your twenty gallon or thirty gallon aquarium, depending 591 00:35:23,800 --> 00:35:25,880 Speaker 1: on the size of the snake. Um. You want to 592 00:35:25,960 --> 00:35:29,920 Speaker 1: keep it somewhere in the neighborhood of seventy eight degrees 593 00:35:29,960 --> 00:35:32,080 Speaker 1: in the in the tank in general. And then you 594 00:35:32,120 --> 00:35:35,359 Speaker 1: want to fahrenheit thank you, Celsie's I think would melt 595 00:35:35,400 --> 00:35:38,560 Speaker 1: the snake. Um. And then you want to keep a 596 00:35:38,560 --> 00:35:42,319 Speaker 1: little area for basking even hotter. Remember you talked about 597 00:35:42,360 --> 00:35:45,759 Speaker 1: how snakes like to bask. Um this one. This is 598 00:35:45,760 --> 00:35:48,040 Speaker 1: going to be more like eight eight to ninety two 599 00:35:48,080 --> 00:35:50,759 Speaker 1: degrees fahrenheight, so the snake can be like, I'm gonna 600 00:35:50,760 --> 00:35:53,040 Speaker 1: go warm up over here on my nice little rock. 601 00:35:53,120 --> 00:35:56,479 Speaker 1: And Um. If you do that and you keep track 602 00:35:56,520 --> 00:35:58,600 Speaker 1: of your temperatures, like you have to really make sure 603 00:35:58,600 --> 00:36:01,160 Speaker 1: it stays like this, then it will be much happier 604 00:36:01,239 --> 00:36:04,879 Speaker 1: than otherwise. Yeah, but you want to screen those lights off. 605 00:36:04,920 --> 00:36:07,600 Speaker 1: You don't want it actually touching the bulb because that 606 00:36:07,640 --> 00:36:10,920 Speaker 1: can burn their little skin. And there was one of 607 00:36:10,960 --> 00:36:14,280 Speaker 1: the thing that um they really love is as branches. 608 00:36:14,320 --> 00:36:16,560 Speaker 1: They love to hang on tree branches. So if you 609 00:36:16,560 --> 00:36:19,319 Speaker 1: could outfit your aquarium, it's got to be sturdy. Don't 610 00:36:19,320 --> 00:36:21,959 Speaker 1: just put like some sort of lightweight limb from your yard. 611 00:36:22,480 --> 00:36:24,520 Speaker 1: But if you can affix like a really sturdy limb 612 00:36:24,960 --> 00:36:27,560 Speaker 1: in your your python cage, they're gonna be pretty happy 613 00:36:27,640 --> 00:36:30,080 Speaker 1: with you as an owner. And it will also probably 614 00:36:30,080 --> 00:36:31,840 Speaker 1: give them a place to hide too. They want to 615 00:36:31,840 --> 00:36:34,000 Speaker 1: have a place to hide UM so that they can 616 00:36:34,040 --> 00:36:36,880 Speaker 1: feel safe and secure. And then they also like to 617 00:36:36,960 --> 00:36:41,360 Speaker 1: soak too, apparently also when they're molting um shedding their skin, 618 00:36:41,800 --> 00:36:43,800 Speaker 1: they like to soak. So you want a little tub, 619 00:36:43,840 --> 00:36:45,879 Speaker 1: but they want to feel secure when they're in their 620 00:36:45,920 --> 00:36:48,600 Speaker 1: little tub of water too, So you probably want to 621 00:36:48,640 --> 00:36:51,840 Speaker 1: have like a lidded plastic container that you've cut a 622 00:36:51,880 --> 00:36:54,160 Speaker 1: hole out in the top and smooth the edges out. 623 00:36:54,200 --> 00:36:56,239 Speaker 1: You could be sure to do that UM so that 624 00:36:56,320 --> 00:36:59,040 Speaker 1: the snake can go inside it's little tub and soak 625 00:36:59,160 --> 00:37:04,760 Speaker 1: but also feel and closed in there too. Right And finally, uh, 626 00:37:04,960 --> 00:37:08,200 Speaker 1: part of being the owner of a constrictor that you've 627 00:37:08,200 --> 00:37:11,000 Speaker 1: got to feed these things. And when you have them 628 00:37:11,000 --> 00:37:14,759 Speaker 1: in your house and their domesticated, there's not snake food 629 00:37:15,280 --> 00:37:18,920 Speaker 1: that you shake out like a fish. Right as you 630 00:37:18,960 --> 00:37:21,239 Speaker 1: have this big can in just a bunch of mice 631 00:37:21,280 --> 00:37:24,759 Speaker 1: shake count Yeah, well that's what you gotta do, man, 632 00:37:24,800 --> 00:37:26,880 Speaker 1: You gotta you gotta feed them. Uh, they need to 633 00:37:26,880 --> 00:37:30,200 Speaker 1: be fed every week or maybe every two weeks, kind 634 00:37:30,200 --> 00:37:33,120 Speaker 1: of depending on their appetite. If they're young, you gotta 635 00:37:33,160 --> 00:37:35,600 Speaker 1: start out with a little tiny mice about every five 636 00:37:35,600 --> 00:37:38,399 Speaker 1: to seven days, and then as they get bigger, their 637 00:37:38,440 --> 00:37:40,239 Speaker 1: diet's gonna grow. So if you end up with a 638 00:37:40,320 --> 00:37:44,640 Speaker 1: six ft python, you're gonna have to feed it something 639 00:37:44,760 --> 00:37:48,560 Speaker 1: that will fill it up. In judging by this this 640 00:37:48,640 --> 00:37:52,880 Speaker 1: person feeding it this dead rabbit, it's not a fun task. 641 00:37:52,920 --> 00:37:54,719 Speaker 1: I'm sure they don't mind. They're up for that, but 642 00:37:55,360 --> 00:37:58,680 Speaker 1: I'm not sure. Um one of the other things too. 643 00:37:58,760 --> 00:38:01,719 Speaker 1: Like this is all if you have a bald python, 644 00:38:02,480 --> 00:38:04,640 Speaker 1: which is manageable and is not going to be able 645 00:38:04,680 --> 00:38:07,359 Speaker 1: to harm you even if it tried. But if you say, 646 00:38:07,400 --> 00:38:10,880 Speaker 1: have a Burmese python, there's entire steps that you have 647 00:38:11,000 --> 00:38:14,239 Speaker 1: to follow through that you wouldn't with other kinds of um, 648 00:38:14,520 --> 00:38:18,080 Speaker 1: smaller pythons, like, for example, when you're feeding it, you 649 00:38:18,239 --> 00:38:20,880 Speaker 1: never ever want to dangle its food in front of 650 00:38:20,920 --> 00:38:23,680 Speaker 1: your face, in front of its face with your hands, 651 00:38:24,239 --> 00:38:26,919 Speaker 1: because it might bite your hand and start to get 652 00:38:26,960 --> 00:38:30,480 Speaker 1: ahold of you. Um. Apparently, when it's feeding time and 653 00:38:30,520 --> 00:38:34,040 Speaker 1: they've sensed food, all of those genes start going crazy 654 00:38:34,320 --> 00:38:36,960 Speaker 1: and they like just they get a little bit of 655 00:38:36,960 --> 00:38:40,160 Speaker 1: like food fever, and they're not they're not behaving in 656 00:38:40,160 --> 00:38:43,399 Speaker 1: a way that you might expect them to. Write UM, 657 00:38:43,480 --> 00:38:45,399 Speaker 1: So you never want to dangle it with your bare 658 00:38:45,440 --> 00:38:47,000 Speaker 1: hands or your hands. You want to use like force 659 00:38:47,080 --> 00:38:50,120 Speaker 1: ups or something like that. And then also if you 660 00:38:50,160 --> 00:38:53,120 Speaker 1: have a Burmese python, you never feed it by yourself. 661 00:38:53,360 --> 00:38:55,400 Speaker 1: You always have to have at least one other adult 662 00:38:55,480 --> 00:38:58,640 Speaker 1: around with you, just in case something bad does happen. 663 00:38:58,960 --> 00:39:01,480 Speaker 1: It does happen from time to time. There's a guy 664 00:39:01,480 --> 00:39:04,640 Speaker 1: in the Bronx who was found dead in his apartment 665 00:39:05,040 --> 00:39:08,840 Speaker 1: and his pound eleven ft Burmese python was wrapped around 666 00:39:08,920 --> 00:39:12,920 Speaker 1: him still. He apparently had gone to feed it outside 667 00:39:12,920 --> 00:39:16,239 Speaker 1: of its cage a chicken that he had used his 668 00:39:16,360 --> 00:39:18,080 Speaker 1: hand to dangle in front of it, and it just 669 00:39:18,120 --> 00:39:21,600 Speaker 1: went bad. But that is extremely rare. But the point 670 00:39:21,680 --> 00:39:24,040 Speaker 1: is that can happen, so you have to be extra 671 00:39:24,120 --> 00:39:27,440 Speaker 1: safe and smart when you're feeding a Burmese python. Yeah, 672 00:39:27,520 --> 00:39:31,359 Speaker 1: it happens quick, like when this rabbit was dangled there. 673 00:39:31,400 --> 00:39:34,640 Speaker 1: There's such a chill sort of species, the way they 674 00:39:34,680 --> 00:39:36,680 Speaker 1: move around. And you know, we've all been to the 675 00:39:36,760 --> 00:39:39,359 Speaker 1: nature center and some people have held them and petted them. 676 00:39:39,600 --> 00:39:42,360 Speaker 1: They look very relaxed. But when that rabbit was dangled it, 677 00:39:42,760 --> 00:39:44,839 Speaker 1: when it popped at it and wrapped around it, it it 678 00:39:44,960 --> 00:39:48,560 Speaker 1: happened very very fast. And they will bite you too. 679 00:39:48,600 --> 00:39:51,680 Speaker 1: Even though it's not like a venomous bite. Um, it 680 00:39:51,800 --> 00:39:54,080 Speaker 1: still hurts, like their teeth can break off into your 681 00:39:54,080 --> 00:39:57,000 Speaker 1: hand or your arm or wherever. So it's not a 682 00:39:57,040 --> 00:40:00,080 Speaker 1: pleasant sensation from what I understand, even though it's not 683 00:40:00,160 --> 00:40:03,240 Speaker 1: going to kill you. That's right. And then finally, finally, 684 00:40:03,960 --> 00:40:07,120 Speaker 1: as far as endangerment goes, there are thirteen species on 685 00:40:07,160 --> 00:40:11,600 Speaker 1: the International Union of Conservation of Nature's Red List of 686 00:40:11,640 --> 00:40:16,040 Speaker 1: Threatened species, and I think the Ramsey's python is endangered. 687 00:40:16,560 --> 00:40:21,239 Speaker 1: The Burmese and the mean mar are vulnerable, so is 688 00:40:21,280 --> 00:40:24,839 Speaker 1: the Indian python too, apparently, but plentiful and Florida it 689 00:40:24,840 --> 00:40:27,520 Speaker 1: sounds like. Yeah, I was surprised that the Burmese pythons 690 00:40:27,560 --> 00:40:30,400 Speaker 1: still on that list for as good as it seeing Florida. 691 00:40:30,440 --> 00:40:32,880 Speaker 1: But maybe they're just thinking of the natural range of it. 692 00:40:33,480 --> 00:40:35,800 Speaker 1: That's right. And the biggest threat to pythons you guessed 693 00:40:35,800 --> 00:40:42,120 Speaker 1: it stars, Yes, not sharks. Ah you got anything else? 694 00:40:43,160 --> 00:40:45,880 Speaker 1: I don't have anything else. Thanks for putting this one together. 695 00:40:45,960 --> 00:40:50,040 Speaker 1: Shout out to definitely Live Science UM for that one 696 00:40:50,160 --> 00:40:53,319 Speaker 1: article about the guy who found out how you could 697 00:40:53,600 --> 00:40:56,399 Speaker 1: sequence the genes of pythons and just be amazed at 698 00:40:56,400 --> 00:40:58,719 Speaker 1: what you find. Yeah, thanks to Life Science. And there 699 00:40:58,719 --> 00:41:01,280 Speaker 1: were there were a bunch of different snake specialty websites 700 00:41:01,320 --> 00:41:04,239 Speaker 1: that we dug into for this sweet um. And if 701 00:41:04,239 --> 00:41:06,840 Speaker 1: you want to know more about pythons and just start 702 00:41:06,880 --> 00:41:10,560 Speaker 1: reading about pythons and think really long and hard before 703 00:41:10,600 --> 00:41:12,560 Speaker 1: you actually get one as a pet. But if you do, 704 00:41:12,920 --> 00:41:14,600 Speaker 1: take good care of it and tell it that we 705 00:41:14,640 --> 00:41:17,160 Speaker 1: said high. And since I said that, it's time for 706 00:41:17,239 --> 00:41:24,440 Speaker 1: listener mail, I'm gonna call this Salem Witch Family Trial 707 00:41:24,760 --> 00:41:27,799 Speaker 1: Family Connection. Hey, guys, have been listening to the show 708 00:41:27,800 --> 00:41:30,680 Speaker 1: for a few years, thoroughly enjoyed them. Recently listened to 709 00:41:30,680 --> 00:41:33,960 Speaker 1: Salem witchcraft trials and something towards the instruct me. You 710 00:41:33,960 --> 00:41:36,960 Speaker 1: mentioned that Salem was in Essex County. My mother's family 711 00:41:36,960 --> 00:41:40,000 Speaker 1: settled in Essex in the mid seventeenth century. So I 712 00:41:40,040 --> 00:41:42,680 Speaker 1: did a little research and found out that there was 713 00:41:42,719 --> 00:41:46,200 Speaker 1: an Elizabeth Morris in Newbury who was convicted of witchcraft 714 00:41:46,200 --> 00:41:49,640 Speaker 1: in eighteen I'm sorry, sixteen eighty. She was originally sentenced 715 00:41:49,640 --> 00:41:52,759 Speaker 1: to death, but that was changed to home confinement after 716 00:41:52,800 --> 00:41:55,160 Speaker 1: a second trial, and it turns out she is my 717 00:41:55,320 --> 00:41:59,480 Speaker 1: seventh great grandmother. Pretty cool. That was a bit of 718 00:41:59,480 --> 00:42:02,560 Speaker 1: fun family history to share with the Fens, with the 719 00:42:02,600 --> 00:42:05,319 Speaker 1: friends and family this Halloween season. And that is from 720 00:42:05,360 --> 00:42:09,480 Speaker 1: George Oaks. That is a great email, George Oakes. We 721 00:42:09,520 --> 00:42:12,360 Speaker 1: actually heard from a lot of people who were related 722 00:42:12,400 --> 00:42:15,520 Speaker 1: to people who were executed at the Salem witchcraft trials. 723 00:42:15,719 --> 00:42:18,240 Speaker 1: Did you know? I think we heard from a Corey 724 00:42:18,480 --> 00:42:20,880 Speaker 1: and a bunch of other people. So shout out to 725 00:42:20,920 --> 00:42:24,080 Speaker 1: all of you guys carrying the family lying on for 726 00:42:24,160 --> 00:42:29,440 Speaker 1: those old witches. But none of those matters, no, Now 727 00:42:29,840 --> 00:42:32,840 Speaker 1: they don't tell people. Um, well, if you want to 728 00:42:32,880 --> 00:42:35,960 Speaker 1: get in touch with us, you can Who was that 729 00:42:35,960 --> 00:42:38,320 Speaker 1: that wrote in George George Ookes If you want to 730 00:42:38,320 --> 00:42:40,160 Speaker 1: get in touch with us like George did, you can 731 00:42:40,239 --> 00:42:43,839 Speaker 1: send us an email like George did, to Stuff Podcasts 732 00:42:44,120 --> 00:42:49,400 Speaker 1: at iHeart radio dot com. Stuff you Should Know is 733 00:42:49,400 --> 00:42:52,880 Speaker 1: a production of iHeart Radio. For more podcasts my heart Radio, 734 00:42:53,080 --> 00:42:56,080 Speaker 1: visit the i heart Radio app, Apple Podcasts, or wherever 735 00:42:56,120 --> 00:42:57,560 Speaker 1: you listen to your favorite shows.