WEBVTT - Ep. 219: Snake Oil 0:00:08.960 --> 0:00:13.320 This is me eater podcast coming at you shirtless, severely 0:00:13.440 --> 0:00:18.599 bog bitten in my case, underwear listening podcast. You can't 0:00:18.600 --> 0:00:22.680 predict anything presented by on X. Hunt creators are the 0:00:22.680 --> 0:00:26.479 most comprehensive digital mapping system for hunters. Download the Hunt 0:00:26.520 --> 0:00:29.680 app from the iTunes or Google play store. Nor where 0:00:29.680 --> 0:00:37.120 you stand with on X. All right, folks, before I 0:00:37.159 --> 0:00:40.720 even introduce what we're um, this question is going to reveal. 0:00:40.920 --> 0:00:44.080 This question will reveal what we're talking about. But before 0:00:44.120 --> 0:00:47.040 I introduced who we're talking about it with, I just 0:00:47.080 --> 0:00:49.120 gotta get one of these. I gotta get something out 0:00:49.120 --> 0:00:54.640 of the way. Um, Dr Bob Reid, Is it true 0:00:54.840 --> 0:00:58.960 that a Burmes that day? Is this really? They found 0:00:58.960 --> 0:01:03.560 a Burmese python on that had the remains of three 0:01:04.080 --> 0:01:09.920 different deer and its lower GI tract that was That's 0:01:09.959 --> 0:01:13.560 probably the publication I'm proudest of because I got an 0:01:13.760 --> 0:01:19.360 entire peer reviewed publication out of a single poop. And yeah, 0:01:19.400 --> 0:01:21.120 so this was a This was a python that was 0:01:21.160 --> 0:01:25.720 picked up. It was about a forty eight kilo python, 0:01:25.840 --> 0:01:30.120 so a little over a hundred pounds, and it had 0:01:31.200 --> 0:01:35.959 a fourteen pound poop inside it. And in that poop 0:01:35.959 --> 0:01:39.720 were the hoofs of three different deer. Um, and my 0:01:39.760 --> 0:01:43.280 buddy Scott bo back we we uh, he had his 0:01:43.319 --> 0:01:46.200 buddies collect deer legs and he made a graph of 0:01:46.319 --> 0:01:48.880 hoof size of the deer that his friends were shooting 0:01:48.920 --> 0:01:51.120 and correlated with the cuff size to the tier that 0:01:51.160 --> 0:01:53.440 we're in the poop. So we figured out how big 0:01:53.480 --> 0:01:56.800 they were and how many had eaten and uh yeah, um, 0:01:57.440 --> 0:02:00.880 one dough and two fons all in one python poop 0:02:00.960 --> 0:02:05.240 from the everglades. Do they feel that that one python 0:02:07.240 --> 0:02:11.520 had been carrying those like to the hooves last a 0:02:11.560 --> 0:02:15.160 long time? Like maybe it'd be like if you opened 0:02:15.200 --> 0:02:17.160 up an alligator and found a bunch of old dog 0:02:17.200 --> 0:02:21.160 collars because they just never moved through the tract. Yeah, 0:02:21.200 --> 0:02:23.360 so is that it's like is that a life's collection 0:02:23.440 --> 0:02:26.680 of deer or is that last week's dear it so 0:02:26.840 --> 0:02:30.800 carroton doesn't get digested and we you know we pass 0:02:30.880 --> 0:02:34.360 hair too, um, so hair and hooves get past. But 0:02:35.240 --> 0:02:39.080 it looks like this snake was actually impacted. That it 0:02:39.120 --> 0:02:44.560 had eaten a dough that was of its own body mass, 0:02:44.560 --> 0:02:49.520 followed by two fonds that we estimate with thirty of 0:02:49.560 --> 0:02:53.839 its body mass and Basically it just got plugged with hair, 0:02:54.440 --> 0:02:57.320 and so we think this thing was probably gonna die. 0:02:58.040 --> 0:03:03.480 But based on the fawning period in Florida and when 0:03:03.480 --> 0:03:06.720 the snake was found, we think that have been in 0:03:06.760 --> 0:03:10.239 there for a maximum of about six months. So that's 0:03:10.280 --> 0:03:14.040 about maybe six months worth of eating deer, including during 0:03:14.080 --> 0:03:17.760 the fawning period. Alright, with that cover, because I had 0:03:17.760 --> 0:03:21.160 to get that out of the way, tell everyone to 0:03:21.320 --> 0:03:23.799 tell tell everyone what you what you do. We've had 0:03:23.840 --> 0:03:26.960 other fellers from the We've had other fellers from the 0:03:27.040 --> 0:03:29.840 U s G S. On. I think you're our third 0:03:29.919 --> 0:03:34.240 U s GS guest. Alright, was that right? Honest? Yeah, 0:03:34.280 --> 0:03:38.120 I was gonna say, at least Brant Mixel U s 0:03:38.160 --> 0:03:42.839 G S does research on waterfowl. Yeah, Bran, Brant took 0:03:42.840 --> 0:03:45.920 me salmon fishing last summer. Okay, so you guys run 0:03:45.920 --> 0:03:48.240 in a pack, and I feel I feel like we 0:03:48.280 --> 0:03:50.800 had another U s G S guy on. We've had 0:03:50.840 --> 0:03:56.760 two more the no Steve's he's Wildlife Services. Who you're 0:03:56.800 --> 0:04:01.480 thinking of is our c w D expert Brian Richards, 0:04:02.640 --> 0:04:08.400 he's USGS. So go ahead, Bob, all right, Um, while 0:04:08.440 --> 0:04:11.320 I'm with US Geological Survey based in Fort Collins. I'm 0:04:11.400 --> 0:04:15.240 the chief of the Invasive Species science branch. We've got 0:04:15.240 --> 0:04:19.560 a bunch of researchers who work on everything from invasive 0:04:19.640 --> 0:04:25.440 vertebrates to invasive plants. But my history and expertise is 0:04:25.480 --> 0:04:29.640 in snake biology, and I've done a lot of work 0:04:29.680 --> 0:04:33.120 and overseen a lot of work on Burmese pythons in 0:04:33.160 --> 0:04:36.760 Florida and the brown tree snake on Guam. That's actually 0:04:36.800 --> 0:04:39.640 where the majority of our staff are is out on Guam, 0:04:39.680 --> 0:04:43.039 and then we're we dabble in other invasives. Were working 0:04:43.080 --> 0:04:46.040 on big old tegue lizards that are in southern Florida 0:04:46.080 --> 0:04:50.159 as well, and invasive water snakes from the Eastern US 0:04:50.240 --> 0:04:54.200 that are introduced into the Western US. But a big 0:04:54.279 --> 0:04:58.159 part of our work has focused on invasive pythons in 0:04:58.200 --> 0:05:01.359 the Everglades for the last decade. Can you can you 0:05:01.400 --> 0:05:06.839 tell people about the limits of what you're allowed to 0:05:06.839 --> 0:05:12.400 talk about? Um? Sure? So, like, which I guess encompasses 0:05:12.839 --> 0:05:15.359 you know what your mandate, what your professional mandate is. 0:05:15.480 --> 0:05:17.840 I don't want to put it in terms of a negative, 0:05:18.000 --> 0:05:19.920 but we could sell it as a positive, like what 0:05:20.320 --> 0:05:23.640 is your mandate as a researcher? So the U s 0:05:23.680 --> 0:05:27.000 Geological Survey is the research arm of the Department of 0:05:27.000 --> 0:05:30.920 the Interior. So we do the science, and we stick 0:05:30.960 --> 0:05:34.200 to the science. And then it's the job of agencies 0:05:34.240 --> 0:05:36.600 like the U S. Fish and Wildlife Service to take 0:05:36.640 --> 0:05:40.440 the science and turn it into regulation um and policy. 0:05:40.880 --> 0:05:44.200 And so we try to keep those two shops really 0:05:44.240 --> 0:05:51.119 separate so that the policymakers aren't unduly influencing the researchers 0:05:51.160 --> 0:05:54.320 and vice versa. And so I can talk about anything 0:05:54.320 --> 0:05:59.400 in regards to biology or research results, but I can't say, 0:05:59.440 --> 0:06:03.000 for example, that the State of Florida should engage in 0:06:03.120 --> 0:06:07.520 some particular policy because that's not related to the science. 0:06:08.720 --> 0:06:11.719 Would you be able to say something like Janice should 0:06:11.760 --> 0:06:18.560 cut that mohawk off. You know, the headphones help with it, 0:06:19.960 --> 0:06:23.520 the help help keep it down. Otherwise it would look 0:06:23.560 --> 0:06:26.760 like some punk rocker from London And like seventy two. 0:06:28.000 --> 0:06:31.599 The log cabin kind of throws it off too, that 0:06:31.680 --> 0:06:34.080 he's sitting in a little log cabin with it just 0:06:34.200 --> 0:06:37.120 makes I'll just get real mixed signals from that haircut. 0:06:37.200 --> 0:06:39.600 I can't stop talking about it. I'm all mixed up. 0:06:41.279 --> 0:06:44.159 Oh you know what, I just have another USGS guy, 0:06:44.600 --> 0:06:47.960 Yanni do you remember the Grizzly bear, the guy that 0:06:47.960 --> 0:06:53.720 did the population modeling for Yellowstone Grizzlies. He was USGS. Oh, 0:06:53.800 --> 0:06:57.880 there was the lead of the inter agency team, Frank. Frank, 0:06:58.480 --> 0:07:01.840 help me out, Bob, you know what I'm talking about. 0:07:01.839 --> 0:07:04.120 You're you're putting me on the spot. Now I'm blanking. 0:07:05.040 --> 0:07:08.400 I work with chat Dickinson, um who does grizzly work, 0:07:08.480 --> 0:07:13.960 but he's also the U s g S Firearms program manager. Uh. Yeah, 0:07:14.080 --> 0:07:15.760 that was a great show. People to want to go 0:07:15.880 --> 0:07:18.520 want to want to learn a lot about bears, should 0:07:18.560 --> 0:07:20.880 go back and find that episode. Um, all right, so 0:07:20.960 --> 0:07:23.120 let's keep let's keep plugging along. Here's here's my here's 0:07:23.160 --> 0:07:26.119 my next Burmese python question. And now for people listening. 0:07:26.840 --> 0:07:29.640 When you're scrolling through social media and all of a 0:07:29.640 --> 0:07:32.200 sudden you find a picture like eight dudes staying in 0:07:32.240 --> 0:07:35.640 the road holding a giant snake, you're probably looking at 0:07:35.880 --> 0:07:39.520 a picture from Florida from the Everglades of Burmese pythons. 0:07:39.600 --> 0:07:45.240 It's like it's just the same. The media like certain 0:07:45.280 --> 0:07:48.640 stories about it, where you'll see on social media a 0:07:48.720 --> 0:07:52.280 Burmese python gagging on something giant that is trying to 0:07:52.320 --> 0:07:56.720 eat that's a popular one about someone catching one that 0:07:56.840 --> 0:07:59.920 was bigger, the biggest so far biggest, this biggest thing 0:08:00.320 --> 0:08:05.760 is a popular story, and people staying in the role 0:08:05.800 --> 0:08:09.000 to holding up a big one is a popular story. 0:08:09.120 --> 0:08:12.960 And so people, I think, have this this awareness of 0:08:13.120 --> 0:08:21.960 how these giant snakes are colonizing, taking over impacting a 0:08:22.080 --> 0:08:25.840 large swath of Florida. But we're gonna dive in here 0:08:25.920 --> 0:08:30.240 to sort of what's really going on. How did it 0:08:30.280 --> 0:08:33.120 come to be, how bad is it? Is there an 0:08:33.200 --> 0:08:37.719 end in sight? Is this normal now? Um? And and 0:08:38.679 --> 0:08:41.520 get into some of that. But my first question laying 0:08:41.559 --> 0:08:44.160 this out, and this is I'm always puzzled by this. 0:08:46.360 --> 0:08:49.480 How do we not know exactly where they came from 0:08:49.480 --> 0:08:52.440 and how they got cut loose? If you can look 0:08:52.480 --> 0:08:58.520 at the genetics, can't you trace it to a population 0:08:58.600 --> 0:09:00.880 bottleneck of one or two snakes? Or is it more 0:09:00.920 --> 0:09:05.599 complicated than that? Um, it's it's a little more complicated 0:09:05.640 --> 0:09:09.160 than that, but maybe not that much. So one of 0:09:09.160 --> 0:09:12.440 the problems is that there hasn't been any good range 0:09:12.480 --> 0:09:17.280 wide genetic analysis from the Native range, so we can 0:09:17.360 --> 0:09:20.320 say that you tell us about the Native ranges. The 0:09:20.400 --> 0:09:24.760 Native range is a big swath of Asia from UM 0:09:24.840 --> 0:09:28.400 Indonesia up to southern China and then all the way 0:09:28.440 --> 0:09:35.560 over through northern India, um barely into Pakistan. So it's 0:09:35.559 --> 0:09:39.480 a really wide ranging species, lots of different habitats, and 0:09:39.640 --> 0:09:42.240 no one's really gone through to sample from that whole 0:09:42.360 --> 0:09:47.920 range to figure out UM where the Florida pythons specifically 0:09:47.920 --> 0:09:50.600 are from, although we can say that they're almost certainly 0:09:50.600 --> 0:09:55.800 from Southeast Asia based on the site's import records explain 0:09:55.880 --> 0:10:03.240 that UM well so UM all boas and pythons are 0:10:03.320 --> 0:10:07.720 on the sights to list, which means that countries that 0:10:07.760 --> 0:10:11.520 are trading them have to report the numbers. And that's 0:10:11.520 --> 0:10:15.080 because python skins are such a big commodity. And then 0:10:15.120 --> 0:10:19.200 they extend that to UM live animals as well, and 0:10:19.280 --> 0:10:23.760 we imported tens of thousands of pythons from Southeast Asia, UH, 0:10:24.080 --> 0:10:28.439 mostly during the eighties and early nineties dead or live, 0:10:28.960 --> 0:10:32.559 live live. We brought in UM I think a hundred 0:10:32.559 --> 0:10:37.080 and fifty thousand between what was it nineteen eighty and 0:10:37.160 --> 0:10:43.480 about nineteen No, about two thousand five for what for 0:10:43.520 --> 0:10:49.120 the pet trade, So hundred and fifty thousand, yeah, yeah, 0:10:49.200 --> 0:10:51.640 these wereld So that's where it just gets more complicated. 0:10:51.840 --> 0:10:55.040 These were one of the most popular snakes during that 0:10:55.080 --> 0:11:00.520 time period, and it's partially because they are cheap as 0:11:00.559 --> 0:11:03.199 hell and they're impressive. You know, it's a really it's 0:11:03.200 --> 0:11:07.880 a gorgeous snake. And I've got to admit that when 0:11:07.920 --> 0:11:12.240 I was a sophomore in college, I bought a hashling 0:11:12.280 --> 0:11:15.760 Burn's Python and so you're part of the You're part 0:11:15.800 --> 0:11:19.440 of the problem absolutely. I mean I was the last 0:11:19.559 --> 0:11:23.199 person you want buying a Python that's going to get 0:11:23.240 --> 0:11:26.360 that big, because I was not doing it for good reasons. 0:11:26.360 --> 0:11:29.280 So yeah, I like snakes a lot, but um, I 0:11:29.320 --> 0:11:31.160 was doing it because it was going to be impressive 0:11:31.480 --> 0:11:34.560 and it would probably get girls to my dorm room. 0:11:34.720 --> 0:11:41.200 And yeah, but I mean, like of what caliber? I mean, well, 0:11:41.600 --> 0:11:43.800 I mean this was Berkeley, so you know there it's 0:11:43.840 --> 0:11:47.920 pretty uniformly high. I'm not saying it. I'm not saying 0:11:47.960 --> 0:11:51.400 it worked. But you had a theory that if you 0:11:51.400 --> 0:11:53.960 could say, would you like to come up and see Um, 0:11:54.440 --> 0:11:57.600 I don't even want to say it. Yeah, at that 0:11:57.679 --> 0:12:02.920 point I was as weill had to try anything. You're desperate, 0:12:02.920 --> 0:12:08.400 you got a big party thought. Yeah. So anyway, Um, 0:12:08.440 --> 0:12:10.800 we know we brought lots of Mover, and we know 0:12:10.880 --> 0:12:13.080 that there were also lots of importers based in the 0:12:13.120 --> 0:12:17.120 Miami area, and I gotta, we gotta, we gotta back. 0:12:17.120 --> 0:12:21.080 I can't leave that hanging them. What did you take 0:12:21.120 --> 0:12:23.079 yours down and let it go on the Everglades or 0:12:23.240 --> 0:12:25.400 died of old age, or you sold it like what happened? 0:12:25.800 --> 0:12:29.240 I had mine all the way through my master's degree 0:12:29.280 --> 0:12:32.560 at Arizona State, and when I left Arizona State to 0:12:32.559 --> 0:12:37.520 start my PhD at auburn Um, I gave it to 0:12:37.600 --> 0:12:40.400 a friend of mine whose garage had just burned down 0:12:40.400 --> 0:12:43.600 and he lost his whole snake collection. So you're helping 0:12:43.720 --> 0:12:47.199 that rebuilt. Yeah. By that point she was about fourteen 0:12:47.240 --> 0:12:51.400 and a half feet, about pounds, and I had to 0:12:51.400 --> 0:12:54.280 go out in the desert and shoot jack rabbits for 0:12:54.320 --> 0:12:57.240 her um because she was just eating me out of 0:12:57.280 --> 0:13:02.320 house and home. Huh okay, So go on. So Florida, Yeah, so, 0:13:02.320 --> 0:13:05.600 So Southern Florida was an epicenter for both importing and breeding. 0:13:06.440 --> 0:13:10.960 And there's a lot of controversy about how the snakes 0:13:11.000 --> 0:13:15.680 became established, and so some people say that it was 0:13:15.960 --> 0:13:20.760 individual snakes that were released by pet owners in the Everglades, 0:13:20.800 --> 0:13:23.760 you know, trying to find them a nice home after 0:13:23.800 --> 0:13:27.400 they got too big for their their cages. And then 0:13:27.400 --> 0:13:31.880 there's people who say that Hurricane Andrew knocked down a 0:13:31.880 --> 0:13:35.000 bunch of these importer and breeder facilities and released snakes 0:13:35.000 --> 0:13:39.199 into the Everglades. That that was reported widely, including in 0:13:39.240 --> 0:13:42.480 the in the New Yorker. Yep, yep. And I've been 0:13:42.520 --> 0:13:47.000 looking for evidence of that for a decade and there's 0:13:47.040 --> 0:13:49.960 so far I found no one who can provide eyewitness 0:13:50.040 --> 0:13:55.000 accounts of these facilities that got down, that got knocked down, 0:13:55.040 --> 0:13:58.440 and lots of snakes are known to have escaped. Couldn't 0:13:58.440 --> 0:14:03.200 have happened, absolutely, But it's interesting because some of the 0:14:03.280 --> 0:14:08.880 folks who um are advocates for pet owners say, hey, 0:14:08.920 --> 0:14:12.280 don't blame us, it was Hurricane Andrew knocking down the importers. 0:14:13.480 --> 0:14:17.679 But I just think it's a really silly dichotomy because 0:14:18.000 --> 0:14:20.320 we know the reason they were there. They were there 0:14:20.400 --> 0:14:25.120 because we imported them and bred them, and by one 0:14:25.200 --> 0:14:28.440 means or another, they got out. So there could have 0:14:28.520 --> 0:14:36.520 been not could have been, probably was, but potentially dozens 0:14:36.520 --> 0:14:41.320 of release occurrences. Yeah, it's possible. Um, there's a paper 0:14:41.480 --> 0:14:44.280 that a couple of friends of mine put out recently 0:14:44.360 --> 0:14:49.320 showing that there's actually, uh, potentially two different populations that 0:14:49.400 --> 0:14:52.560 were established, one that started in the southern Everglades, one 0:14:52.560 --> 0:14:57.040 that started closer to Naples that got slight differences um 0:14:57.160 --> 0:15:03.760 in d na um. But again they're still probably from 0:15:03.760 --> 0:15:07.840 Southeast Asia, and we know that we brought them in intentionally. 0:15:09.120 --> 0:15:14.920 What was the first what year was the first known 0:15:15.000 --> 0:15:29.200 instance of natural wild reproduction? Two thousands? So um uh. 0:15:29.280 --> 0:15:33.280 There's a paper out there that models generational times and 0:15:33.360 --> 0:15:35.960 it suggests that they might have been established in the 0:15:36.000 --> 0:15:39.880 mid eighties at low numbers in the Everglades, and then 0:15:39.920 --> 0:15:42.760 if so, then Hurricane Andrew would have just augmented it 0:15:42.840 --> 0:15:46.400 a little bit. But the first hatchlings were found not 0:15:46.600 --> 0:15:51.760 until two thousand and even then there were people who 0:15:51.800 --> 0:15:54.000 were trying to say that, oh, that those are just 0:15:54.080 --> 0:16:01.040 individual releases, and that was true for most pythons until 0:16:01.240 --> 0:16:04.960 about two thousand three two four, when they started finding more. 0:16:05.120 --> 0:16:08.720 Up until that point, it was easier for folks to say, oh, 0:16:08.760 --> 0:16:13.080 that we found a python, But pythons are from tropical 0:16:13.080 --> 0:16:17.120 areas and they can't survive in Florida, and so this 0:16:17.200 --> 0:16:23.280 must be a recent release or escape, Tell me why, 0:16:23.640 --> 0:16:25.120 and you can go on as long as you want. 0:16:26.600 --> 0:16:31.200 Who cares about these snakes, Like like, why is it 0:16:31.360 --> 0:16:36.840 such a big issue that they got caught loose? Well, 0:16:36.840 --> 0:16:41.080 it's not. It's not like legitimately a human safety issue. No, no, 0:16:41.280 --> 0:16:45.040 we we've actually reviewed that, and the risks to humans 0:16:45.200 --> 0:16:51.360 are extremely low. Um. We collected reports of so called 0:16:51.400 --> 0:16:55.000 python attacks from free ranging pythons over the course of 0:16:55.000 --> 0:17:00.760 a decade, and we found five instance is where people 0:17:00.800 --> 0:17:04.120 had seen a python strike at a human. The python 0:17:04.160 --> 0:17:08.359 only made contact on two of those occasions, only broke 0:17:08.400 --> 0:17:11.200 the skin on one, didn't try to constrict on any 0:17:11.280 --> 0:17:16.919 of them. And all of those attacks were on professional 0:17:16.960 --> 0:17:20.520 biologists who are walking through flooded areas in the Everglades, 0:17:21.240 --> 0:17:25.119 And generally that's not something we'd want the public to 0:17:25.160 --> 0:17:28.080 be doing anyway, in a place that's full of gators 0:17:28.080 --> 0:17:34.119 and cotton mouths. So the chances of some visitor to Everglades, 0:17:34.160 --> 0:17:36.920 and there's a million of them a year, being attacked 0:17:36.920 --> 0:17:41.399 and killed by a python is extremely low. It's not 0:17:41.440 --> 0:17:44.719 to say it couldn't ever happen, but in the scope 0:17:44.760 --> 0:17:47.840 of potential risk to humans, it's pretty much a non factor. 0:17:48.359 --> 0:17:54.159 So yeah, I mean in twenty years there's bad. I mean, 0:17:54.200 --> 0:17:57.440 in twenty years of known wild reproduction, there's been zero 0:17:57.560 --> 0:18:02.160 human fatalities, no human fata. Is not even a human attack, 0:18:02.880 --> 0:18:06.080 um that I'd consider serious. Now. You know, during that 0:18:06.119 --> 0:18:09.920 time period, there have been people killed by captive Burmese pythons, 0:18:09.920 --> 0:18:13.679 but still not many of those, and those are spread 0:18:13.680 --> 0:18:16.199 throughout the U. S. And Canada. Yeah. Yeah, And he's 0:18:16.240 --> 0:18:19.879 got a question for you. He was we need to 0:18:19.880 --> 0:18:21.480 back up a little bit because he's got a good 0:18:21.560 --> 0:18:25.280 question for you. All right. UM, My question was if 0:18:26.040 --> 0:18:28.919 is the pet trade and then the affinity for the 0:18:29.000 --> 0:18:32.080 snake hides is big in the snake's native range as 0:18:32.119 --> 0:18:38.879 it is here in the United States. Um, So let's see, 0:18:39.440 --> 0:18:41.919 the great majority of the trade and snake skins has 0:18:42.000 --> 0:18:46.800 reticulated pythons, and that trade is in the you know, 0:18:47.320 --> 0:18:53.960 million skins per year range um globally, and Burmese pythons 0:18:54.040 --> 0:18:59.680 are in much less demand for the skin trade. Um. 0:18:59.720 --> 0:19:03.199 But it sort of just I'm gonna loop back to 0:19:03.280 --> 0:19:06.399 the human attacks things. So the reticulated python versus Burmese 0:19:06.440 --> 0:19:10.560 python question. Reticulated pythons are actually known to attack humans 0:19:10.680 --> 0:19:14.040 regularly in the native range, whereas even Burmese pythons in 0:19:14.080 --> 0:19:18.439 the native range aren't. They're very different animals. There is 0:19:18.440 --> 0:19:23.159 a study of a tribe in the Philippines and of 0:19:23.200 --> 0:19:27.119 the adult males reported being attacked by reticulated pythons, they 0:19:27.160 --> 0:19:32.360 were multiple instances of fatalities, and so that there are 0:19:32.480 --> 0:19:36.960 sort of personality differences among these giant snake species. Um, 0:19:37.040 --> 0:19:39.840 we can only find two records of a Burmese python 0:19:40.040 --> 0:19:44.840 ever even eaten any kind of primate, whereas reticulated they 0:19:44.920 --> 0:19:49.840 just consider a biped as another suitable prey atom. So 0:19:51.400 --> 0:19:53.040 go back to your question, let me know if I 0:19:53.240 --> 0:19:58.840 answered it. Okay, Well, no, the hides, you're talking about 0:19:58.840 --> 0:20:01.399 the hides. That was that answers the hides. But is 0:20:01.440 --> 0:20:04.840 there a pet trade as well over there in its 0:20:04.920 --> 0:20:08.640 native range for those snakes. Well, what's happened is that 0:20:10.240 --> 0:20:13.280 there there's still a pretty big trade in people who 0:20:13.800 --> 0:20:17.919 catch pythons opportunistically in the fields, and then these animal 0:20:17.960 --> 0:20:21.240 traders will come around periodically and buy them from them, 0:20:21.280 --> 0:20:23.399 and those animals might go into the pet trade, might 0:20:23.440 --> 0:20:25.239 go into the skin trade, depending on where they can 0:20:25.280 --> 0:20:28.120 get more money. But they've also found that they can 0:20:28.160 --> 0:20:33.840 farm pythons for both skins and meat, and they've come 0:20:33.920 --> 0:20:38.840 up with really intensive production of pythons in the last 0:20:38.880 --> 0:20:43.160 few years. Um. And they can get them to eat 0:20:43.240 --> 0:20:46.359 things with some amount of training as juveniles that they 0:20:46.359 --> 0:20:49.560 wouldn't eat in the wild. So things like you know, 0:20:50.240 --> 0:20:54.280 chicken necks that are waste products. Um, they can get 0:20:54.280 --> 0:20:58.520 the pythons to eat those. They're they're making giant sausages 0:20:59.800 --> 0:21:05.119 and feeding these things too pythons and getting really high production. 0:21:05.520 --> 0:21:08.359 I mean, that might be another Western hook up, but 0:21:08.520 --> 0:21:13.000 I'm not sure. Man, that sounds like a horror moving 0:21:13.320 --> 0:21:16.879 movie location in the making. Right there at the place 0:21:16.920 --> 0:21:19.400 I don't want to go see is the python factory. 0:21:19.560 --> 0:21:21.600 Oh yeah, I know, it's just like it Just it's 0:21:21.680 --> 0:21:24.120 kind of the more you think about, the less advertising 0:21:24.160 --> 0:21:26.960 it becomes. Man. Yeah. Well, the you know, the traditional 0:21:26.960 --> 0:21:32.919 way um was definitely um, not great. They would they 0:21:32.920 --> 0:21:36.159 would take a pretty big snake, stick a hose in 0:21:36.200 --> 0:21:39.679 his mouth and basically fill it up with water and 0:21:39.720 --> 0:21:41.919 then stick a rubber band around its head and it 0:21:41.920 --> 0:21:46.159 would suffocate and the water stretches the skin out and 0:21:46.280 --> 0:21:50.119 makes it easier to skin afterwards. So it was you know, 0:21:51.119 --> 0:21:54.040 definitely inhumane, would not pass any kind of animal care 0:21:54.320 --> 0:21:59.520 laws um around here. But apparently they're now going to 0:21:59.720 --> 0:22:03.520 much more humane methods of euthanizing animals for the skin trade. 0:22:06.400 --> 0:22:08.440 So tell me why. Okay, it's not a people thing. 0:22:09.119 --> 0:22:14.720 Explain what the real problem is. So the real problem 0:22:14.880 --> 0:22:22.480 is that snakes are phenomenally efficient predators. And one thing 0:22:22.520 --> 0:22:25.080 that people don't realize is that snakes can exist at 0:22:25.200 --> 0:22:28.080 very high densities. And we don't realize that because they've 0:22:28.119 --> 0:22:32.560 got low individual detection probabilities. That means we don't see them. 0:22:32.600 --> 0:22:35.800 So in your backyard on any given day, you might 0:22:35.840 --> 0:22:39.520 see the same damn squirrel over and over again. That 0:22:39.640 --> 0:22:45.199 squirrel is a biological exhibitionist. He's letting you see most 0:22:45.240 --> 0:22:50.960 aspects of his life. But meanwhile, that's a that's a 0:22:50.960 --> 0:22:56.200 great term, man. Yeah, I mean look, I mean, come on, um, yeah, 0:22:56.200 --> 0:22:59.320 he's like here, I am a barking at you. In 0:22:59.440 --> 0:23:04.439 most part to the US, there are twenty snakes for 0:23:04.480 --> 0:23:09.040 every score at least, but how many of them do 0:23:09.080 --> 0:23:12.919 you see? In Kansas? There can be over a thousand 0:23:13.080 --> 0:23:18.480 ringneck snakes per hector. Really, yeah, and that's one species 0:23:18.520 --> 0:23:22.879 of snake. And so when you look at the total 0:23:22.960 --> 0:23:28.560 number of snakes in an ecosystem, they can exhibit massive 0:23:28.680 --> 0:23:36.399 top down effects on pray species. And in a regular ecosystem, 0:23:36.440 --> 0:23:38.880 those prey have evolved with those snakes, and so there's 0:23:38.880 --> 0:23:40.440 a trade off. You know, you don't have those pray 0:23:40.520 --> 0:23:44.000 species going extinct usually because of snake predation, because they've 0:23:44.000 --> 0:23:47.120 got behaviors that allow them to escape it. But when 0:23:47.160 --> 0:23:50.159 you take something like a Burmese python and dump it 0:23:50.160 --> 0:23:52.960 in the everglades with animals that don't have those kinds 0:23:53.000 --> 0:23:58.720 of adaptations to a large ambush foraging snake, um you 0:23:58.720 --> 0:24:02.960 can have really big effects. So UM, I just got 0:24:03.000 --> 0:24:07.600 some data from Christina and Romagosa. There's a colleague at 0:24:07.640 --> 0:24:11.200 the University of Florida, and we've been sending her all 0:24:11.240 --> 0:24:15.800 of the stomach examples from the two thousand one pythons 0:24:15.840 --> 0:24:21.440 that our staff have dissected, and as of now, we're 0:24:21.480 --> 0:24:25.720 at seventy one native species that have been identified from 0:24:25.960 --> 0:24:32.159 python guts. Oh it's it's it's forty five birds, twenty 0:24:32.200 --> 0:24:36.760 four mammals, two reptiles. It's everything from rends to alligators. 0:24:37.680 --> 0:24:42.120 And do they cannabalize each other? No? Now, the only 0:24:42.160 --> 0:24:44.280 way that a python is gonna need another python is 0:24:44.320 --> 0:24:47.879 if they start at opposite ends of the same prey 0:24:47.920 --> 0:24:53.439 item and then basically they keep going. Really that happens, Yeah, 0:24:53.440 --> 0:25:00.200 it with that spaghetti noodle hold on. This is then 0:25:00.280 --> 0:25:04.000 known occurrence. It mostly happens in captivity. I mean I've 0:25:04.040 --> 0:25:06.880 had it happened with with captive snakes that I've had. 0:25:07.720 --> 0:25:09.520 They got so they got a rabbit and they start 0:25:09.560 --> 0:25:11.480 eating the rabbit. Then they meet and then one of 0:25:11.560 --> 0:25:15.520 them just keeps eating and eats the other one too. Yeah. Basically, 0:25:15.560 --> 0:25:21.919 when a snake starts eating, they keep going. Yeah. Um, discussing, 0:25:22.160 --> 0:25:24.200 I mean, the the range of the range of species 0:25:24.520 --> 0:25:28.000 is is pretty phenomenal. I mean, you've got the things 0:25:28.080 --> 0:25:33.800 you'd expect, like rabbits and raccoons, um, most of the herons, 0:25:34.400 --> 0:25:38.600 but then they eat surprising numbers of rails. And a 0:25:38.720 --> 0:25:41.360 rail is another bird that we don't see that often, right, 0:25:41.400 --> 0:25:44.439 you know, they're really good at hiding, but snakes are 0:25:44.480 --> 0:25:47.520 able to find them easily. Um. There's some records that 0:25:47.560 --> 0:25:49.680 are just bizarre. They got a frigate bird out of 0:25:49.720 --> 0:25:52.000 a python that was in the middle of the everglades. 0:25:52.440 --> 0:25:56.360 Even though frigate birds don't land on the mainland in Florida. 0:25:56.480 --> 0:26:00.200 They only land on the offshore Mangrove Islands. So how 0:26:00.240 --> 0:26:02.000 this snake ended up with a frigate bird in it 0:26:02.680 --> 0:26:06.680 three kilometers from the coast is a mystery. Um. They 0:26:06.680 --> 0:26:10.399 can eat very large meals. So the biggest meal is 0:26:10.440 --> 0:26:14.439 a fawn from a python over near Naples, and the 0:26:14.480 --> 0:26:18.320 fawn was a hundred and of the snake's body mass. 0:26:18.960 --> 0:26:23.359 What so it is successfully ate it? Oh yeah, yeah, 0:26:23.440 --> 0:26:26.880 so that's that's like you know, me eating a two 0:26:27.200 --> 0:26:31.160 pound cheeseburger. It's like you eating Janice yep with with 0:26:31.200 --> 0:26:40.520 no hands and one sitting. Yeah. So they're there, ah there, disgusting, 0:26:40.840 --> 0:26:45.480 phenomenally efficient. You have such a freaking ENDOTHERM bias man, dude, 0:26:45.520 --> 0:26:50.560 real bad, real bad, real bad man. You wouldn't even understand. 0:26:51.160 --> 0:26:55.879 It's like real bad. Can you explain when an ENDOTHERM biases? Please? 0:26:57.280 --> 0:27:00.960 It means Steve's scared of scaling and slimy things. I think, No, 0:27:01.160 --> 0:27:08.320 it's not scared, it's repulsion. I have repulsion about Like 0:27:08.520 --> 0:27:11.240 I'll tell you where it came from real quick. You know, 0:27:11.280 --> 0:27:15.439 in high school and you gotta dissect frogs, yep. I 0:27:15.520 --> 0:27:19.560 opened my frog up and I found a giant mouse 0:27:19.640 --> 0:27:24.080 inside my frog and it had like psychological impact. Yeah, 0:27:24.160 --> 0:27:29.440 I had a psychological impact. I've never recovered. Wow, never recovered, Bob. 0:27:29.480 --> 0:27:32.840 I think we should keep going down the diet alright, 0:27:32.920 --> 0:27:36.080