1 00:00:06,559 --> 00:00:09,840 Speaker 1: Welcome to Creature Feature production of My Heart Radio. I'm 2 00:00:09,880 --> 00:00:13,600 Speaker 1: your host of Many Parasites, Katie Golden. I studied psychology 3 00:00:13,600 --> 00:00:16,680 Speaker 1: and evolutionary biology, and today on this show it's another 4 00:00:16,840 --> 00:00:21,160 Speaker 1: listener questions episode. That's the official song that I've seen 5 00:00:21,320 --> 00:00:24,400 Speaker 1: exactly the same way every single time. Uh. Yeah, you 6 00:00:24,480 --> 00:00:28,080 Speaker 1: guys sent me your questions and I try to answer 7 00:00:28,120 --> 00:00:31,280 Speaker 1: them either through email or right here on this show. 8 00:00:31,800 --> 00:00:34,440 Speaker 1: And as you're listening and you're thinking, Hey, I've got 9 00:00:34,440 --> 00:00:37,639 Speaker 1: a question and I want that answered. Uh, you can 10 00:00:37,680 --> 00:00:40,240 Speaker 1: send it to me at Creature Feature plot at gmail 11 00:00:40,360 --> 00:00:44,920 Speaker 1: dot com any kind of evolutionary biology related question. I 12 00:00:45,000 --> 00:00:48,400 Speaker 1: may not immediately know the answer, but I certainly can 13 00:00:48,520 --> 00:00:52,080 Speaker 1: look stuff up and use my background to give you 14 00:00:52,120 --> 00:00:55,440 Speaker 1: the best answer that I can. So let's get right 15 00:00:55,600 --> 00:00:59,280 Speaker 1: into it. So, first email, in response to you. In 16 00:00:59,440 --> 00:01:03,200 Speaker 1: my episode on cute animal names, the listener writes in, 17 00:01:03,200 --> 00:01:06,200 Speaker 1: in addition to pufflings, baby puffins, might I add the 18 00:01:06,240 --> 00:01:10,680 Speaker 1: Australian marsupials quacas whose baby is a bub Wooli's booties 19 00:01:10,680 --> 00:01:13,759 Speaker 1: and pouderous. By the way, these creatures all have something 20 00:01:13,760 --> 00:01:17,280 Speaker 1: in common. They sacrifice their young as a defensive mechanism. 21 00:01:17,319 --> 00:01:20,760 Speaker 1: If they are attacked, the muscles surrounding their patch pouches relax, 22 00:01:20,920 --> 00:01:24,040 Speaker 1: releasing the babies and letting the parents escape their fate. 23 00:01:24,400 --> 00:01:26,560 Speaker 1: Are there other animals that give up their children. It's 24 00:01:26,560 --> 00:01:30,280 Speaker 1: a way to evade death. Michael, Hi, Michael, so really 25 00:01:30,360 --> 00:01:34,319 Speaker 1: fascinating information about these marsupials. It is true that quacas, 26 00:01:34,440 --> 00:01:37,120 Speaker 1: and it seems like the other marsupials you also mentioned, 27 00:01:37,400 --> 00:01:40,360 Speaker 1: abandoned their young who will fall out of the pouch 28 00:01:40,480 --> 00:01:44,560 Speaker 1: as the mother flees, and that little baby will make 29 00:01:44,640 --> 00:01:49,320 Speaker 1: this noise that attracts predators. So this idea is based 30 00:01:49,360 --> 00:01:54,880 Speaker 1: on observational research where researchers found that these marsupials, their quaccas, 31 00:01:54,920 --> 00:01:58,440 Speaker 1: are these little they look like a cross between a 32 00:01:58,520 --> 00:02:00,840 Speaker 1: teddy bear and a hamps there and they're about the 33 00:02:00,840 --> 00:02:04,200 Speaker 1: size of a teddy bear. And they when they are 34 00:02:04,400 --> 00:02:07,960 Speaker 1: caught in this human research trap, a humane trap, they 35 00:02:07,960 --> 00:02:10,400 Speaker 1: were in no real danger, but for the quaca quite 36 00:02:10,440 --> 00:02:14,400 Speaker 1: a an alarming experience. Um these quacas would drop their 37 00:02:14,440 --> 00:02:17,840 Speaker 1: babies out of their pouch, so the muscles in their 38 00:02:17,880 --> 00:02:20,880 Speaker 1: pouch would relax and the baby would kind of flop 39 00:02:20,919 --> 00:02:25,400 Speaker 1: out and the baby would start squeaking. So the Researchers 40 00:02:25,520 --> 00:02:29,119 Speaker 1: speculate that this may be intentional or at least an 41 00:02:29,120 --> 00:02:33,000 Speaker 1: involuntary response on the part of the quaca mother, given 42 00:02:33,040 --> 00:02:36,359 Speaker 1: that the pouch has a number of highly controllable muscles. 43 00:02:36,400 --> 00:02:39,079 Speaker 1: So in a sense, it maybe kind of like how 44 00:02:39,200 --> 00:02:43,000 Speaker 1: we will peeer pants when we're scared. The quaca might 45 00:02:43,040 --> 00:02:46,120 Speaker 1: not be consciously doing this, but maybe, you know, the 46 00:02:46,240 --> 00:02:50,519 Speaker 1: involuntary reaction to high stress, high fear like that might 47 00:02:50,560 --> 00:02:55,680 Speaker 1: be releasing this baby out of her pouch. And the 48 00:02:55,800 --> 00:02:59,240 Speaker 1: baby is called a joey, So this joey kind of 49 00:02:59,240 --> 00:03:03,000 Speaker 1: flops out out. And I think what's interesting about this 50 00:03:03,160 --> 00:03:06,280 Speaker 1: specific situation is it's been observed when the quak is 51 00:03:06,320 --> 00:03:10,000 Speaker 1: actually in a trap, and I think it may be 52 00:03:10,200 --> 00:03:13,400 Speaker 1: indicative that the quaker really only does this as a 53 00:03:13,560 --> 00:03:17,760 Speaker 1: last resort, so not when she's just kind of scared, 54 00:03:18,600 --> 00:03:23,400 Speaker 1: but when she really feels trapped, and the thinking, or 55 00:03:23,440 --> 00:03:26,560 Speaker 1: at least even if it's not like an intentional thinking 56 00:03:26,560 --> 00:03:30,560 Speaker 1: on the part of the quaca, the evolutionary strategy maybe 57 00:03:30,800 --> 00:03:33,919 Speaker 1: that it's better that she gets away to rear more 58 00:03:34,040 --> 00:03:37,640 Speaker 1: young than they both get eaten. So giving up your 59 00:03:37,680 --> 00:03:41,160 Speaker 1: own babies to avoid death is not a super common 60 00:03:41,200 --> 00:03:44,160 Speaker 1: strategy in the animal kingdom, but it is more common 61 00:03:44,160 --> 00:03:48,360 Speaker 1: than you would think. So in the case of these marsupials, 62 00:03:48,480 --> 00:03:53,400 Speaker 1: the mother avoiding death likely leads to more successfully reared 63 00:03:53,440 --> 00:03:57,320 Speaker 1: offspring than saving one individual Joey. Even though that sounds 64 00:03:57,400 --> 00:04:01,720 Speaker 1: kind of callous, evolution doesn't have a moral compass. Really, 65 00:04:01,720 --> 00:04:04,960 Speaker 1: it only cares if you're able to pass on your jeans. 66 00:04:05,200 --> 00:04:08,800 Speaker 1: So Quacas can give birth to around seventeen babies over 67 00:04:08,800 --> 00:04:13,080 Speaker 1: their lifespans. So in the Quacas case, if the mother 68 00:04:13,400 --> 00:04:17,640 Speaker 1: is eaten, that's gonna reduce her chances of you know, 69 00:04:17,720 --> 00:04:21,400 Speaker 1: rearing a successful offspring passing on her jeans to zero, 70 00:04:21,480 --> 00:04:25,760 Speaker 1: whereas if one Joey is lost, that's only one of 71 00:04:25,839 --> 00:04:31,080 Speaker 1: her reproductive potential lost there. So another common strategy is 72 00:04:31,279 --> 00:04:35,800 Speaker 1: abandoning offspring that you don't have resources for, or even 73 00:04:35,839 --> 00:04:39,839 Speaker 1: eating offspring when you need the extra calories or you 74 00:04:39,880 --> 00:04:44,520 Speaker 1: have too many offspring. Uh. Sometimes it's the opposite, such 75 00:04:44,560 --> 00:04:49,040 Speaker 1: as the fantail darter fish males who will actually eat 76 00:04:49,080 --> 00:04:53,200 Speaker 1: their entire brood if the number of offspring is too small, 77 00:04:53,320 --> 00:04:55,320 Speaker 1: which seems strange. Why would you eat your brood if 78 00:04:55,360 --> 00:04:59,600 Speaker 1: you have too few of them? Well, apparently that investment 79 00:04:59,600 --> 00:05:02,520 Speaker 1: in per until care is only worth it if you 80 00:05:02,600 --> 00:05:06,240 Speaker 1: have economies of size of baby fish, So like he 81 00:05:06,320 --> 00:05:09,520 Speaker 1: doesn't have enough baby fish, so it's not worth his time, 82 00:05:09,560 --> 00:05:11,839 Speaker 1: so he just eats them all and tries again for 83 00:05:11,920 --> 00:05:17,559 Speaker 1: a larger brood. It's very much and economics, uh, sort 84 00:05:17,560 --> 00:05:22,520 Speaker 1: of way of rearing fish offspring um. Another interesting one 85 00:05:22,600 --> 00:05:25,359 Speaker 1: is the long tailed skink, which is a lizard that 86 00:05:25,440 --> 00:05:28,560 Speaker 1: lives in Taiwan, who will try to find off predators 87 00:05:28,760 --> 00:05:31,280 Speaker 1: who threatened to eat her eggs. But if there are 88 00:05:31,320 --> 00:05:35,560 Speaker 1: too many predators or if their intrusions are too frequent 89 00:05:35,640 --> 00:05:39,320 Speaker 1: for her to properly defend her eggs, she would actually 90 00:05:39,440 --> 00:05:41,560 Speaker 1: rather be the one to eat her own eggs, so 91 00:05:41,640 --> 00:05:45,360 Speaker 1: she will actually turn around and eat her entire clutch. 92 00:05:46,360 --> 00:05:50,640 Speaker 1: It's a very it seems spiteful, like if I can't 93 00:05:50,680 --> 00:05:52,920 Speaker 1: have my eggs and you're gonna eat my eggs, well 94 00:05:52,960 --> 00:05:55,080 Speaker 1: I'll just be the one to eat them. But when 95 00:05:55,080 --> 00:05:57,880 Speaker 1: you think about it, it is a good evolutionary strategy 96 00:05:57,920 --> 00:06:01,679 Speaker 1: because she's basically at the point where she realizes she's 97 00:06:01,720 --> 00:06:04,479 Speaker 1: not going to be able to protect her eggs from 98 00:06:04,560 --> 00:06:09,040 Speaker 1: these predators, so she just lets the predators eat these eggs, 99 00:06:09,080 --> 00:06:12,760 Speaker 1: she loses her entire clutch anyways, and she gets nothing 100 00:06:12,800 --> 00:06:16,039 Speaker 1: out of it, whereas if she eats the eggs now, 101 00:06:16,160 --> 00:06:18,960 Speaker 1: she gets a boost in calories, a boost and fuel 102 00:06:19,000 --> 00:06:22,640 Speaker 1: which may help her go out, you know, and maybe 103 00:06:22,680 --> 00:06:26,120 Speaker 1: start a new clutch. So it is it's a grim calculation, 104 00:06:26,600 --> 00:06:31,040 Speaker 1: um one that I guess Thomas Swift as modest proposal 105 00:06:31,279 --> 00:06:35,960 Speaker 1: would cringe at that satire, but it is something that 106 00:06:36,120 --> 00:06:40,880 Speaker 1: is actually employed in nature, and you know, it does work, 107 00:06:41,000 --> 00:06:47,200 Speaker 1: even though it kind of defies our human morals. Now 108 00:06:47,320 --> 00:06:51,000 Speaker 1: onto a question I got from the writings. Someone left 109 00:06:51,120 --> 00:06:53,760 Speaker 1: a question where they would leave a rating, and I 110 00:06:53,800 --> 00:06:56,479 Speaker 1: actually love that, so thank you for that. And here's 111 00:06:56,520 --> 00:06:59,920 Speaker 1: the question. Are there more eyes or legs in the world? 112 00:07:00,400 --> 00:07:05,040 Speaker 1: From my name is Mud? And that is a deceptively 113 00:07:05,160 --> 00:07:09,840 Speaker 1: tough question. So to answer it, first, let's look at 114 00:07:09,880 --> 00:07:13,480 Speaker 1: some of the most numerous animals in the world. And 115 00:07:13,520 --> 00:07:16,960 Speaker 1: then instead of counting all their eyes and legs, which 116 00:07:17,240 --> 00:07:20,080 Speaker 1: I simply don't have the time to do, we will 117 00:07:20,120 --> 00:07:21,840 Speaker 1: just kind of look at them in general and see 118 00:07:21,880 --> 00:07:25,320 Speaker 1: if they typically have more eyes or more legs. So 119 00:07:26,960 --> 00:07:29,040 Speaker 1: this is all guests work on my part, sort of 120 00:07:29,280 --> 00:07:33,120 Speaker 1: our educated guesswork. So I don't know. I'm not wolf 121 00:07:33,200 --> 00:07:36,920 Speaker 1: Ram Alpha, I'm not a supercomputer, but this I've given 122 00:07:36,960 --> 00:07:39,680 Speaker 1: it my best go. So the most populous organisms that 123 00:07:39,720 --> 00:07:43,560 Speaker 1: would have i'd say, what we would identify as eyes 124 00:07:43,600 --> 00:07:46,720 Speaker 1: and legs. I'm dis counting things like flagella, like, let's 125 00:07:46,800 --> 00:07:50,200 Speaker 1: let's be serious, those aren't really legs. Uh. So with 126 00:07:50,320 --> 00:07:54,400 Speaker 1: true eyes and legs, I would say are probably insects. 127 00:07:54,440 --> 00:07:59,520 Speaker 1: So according to the Smithsonian Institution, uh, there's estimated to 128 00:07:59,520 --> 00:08:04,600 Speaker 1: be around ten quintillion insects on Earth right now. So 129 00:08:04,680 --> 00:08:09,240 Speaker 1: a quintillion is a little bit hard to fathom. It 130 00:08:09,400 --> 00:08:14,720 Speaker 1: is a billion billions. So there are ten billion billion 131 00:08:14,840 --> 00:08:19,680 Speaker 1: insects on Earth, and that's a lot. That is a lot. Uh. 132 00:08:19,800 --> 00:08:24,320 Speaker 1: There are also microscopic animals, such as tartar grades, who 133 00:08:24,440 --> 00:08:29,560 Speaker 1: can be found in quantities of like nine thousand individuals 134 00:08:29,640 --> 00:08:34,520 Speaker 1: per gallon of water in marine or freshwater sediment. I 135 00:08:34,559 --> 00:08:39,160 Speaker 1: was unable to find like a estimated global population of 136 00:08:39,240 --> 00:08:41,959 Speaker 1: tartar grades. And it's not as simple as like figuring 137 00:08:41,960 --> 00:08:44,160 Speaker 1: out how much water there is in the world, because 138 00:08:44,200 --> 00:08:46,520 Speaker 1: the number of tartar grades is going to be different 139 00:08:46,600 --> 00:08:51,000 Speaker 1: based on like what where that water is how nutrient 140 00:08:51,360 --> 00:08:54,959 Speaker 1: rich it is. But suffice it to say there's probably 141 00:08:55,240 --> 00:09:01,120 Speaker 1: just an enormously huge amount of tartar grades. So there's 142 00:09:01,120 --> 00:09:04,520 Speaker 1: gonna be a lot of many many invertebrates like the 143 00:09:04,880 --> 00:09:09,760 Speaker 1: like insects, arthropods and tarte grades things like that. UM. 144 00:09:09,840 --> 00:09:12,600 Speaker 1: So let's look at these guys and see if, on 145 00:09:12,760 --> 00:09:17,480 Speaker 1: average they tend to have more legs or more eyes. UM. 146 00:09:17,640 --> 00:09:20,400 Speaker 1: First of all, let's talk about what an I is like. 147 00:09:20,480 --> 00:09:23,920 Speaker 1: How do we define an eye? If we define an 148 00:09:23,960 --> 00:09:28,680 Speaker 1: eye as like a single lens, dragonflies have around twenty 149 00:09:28,720 --> 00:09:33,880 Speaker 1: eight thousand lenses per compound I. I kind of don't 150 00:09:34,360 --> 00:09:37,920 Speaker 1: like this, though. I generally think that that would be 151 00:09:37,960 --> 00:09:42,199 Speaker 1: regarded as a single compound I, not twenty thousand eyes. 152 00:09:42,240 --> 00:09:47,400 Speaker 1: That's just that's the number of lenses on that compound. IE. 153 00:09:48,679 --> 00:09:51,560 Speaker 1: So if you counted each lens as and I, I 154 00:09:51,679 --> 00:09:56,040 Speaker 1: think eyes would win over legs in this game. But personally, 155 00:09:56,120 --> 00:09:59,640 Speaker 1: I don't think a compound I should be counted as 156 00:09:59,679 --> 00:10:02,280 Speaker 1: twenty eight thousand eyes just because it has so many lenses. 157 00:10:02,520 --> 00:10:04,360 Speaker 1: I think it should be a single eye with a 158 00:10:04,360 --> 00:10:09,760 Speaker 1: bunch of lenses. So let's move on to uh, spiders. 159 00:10:09,800 --> 00:10:13,160 Speaker 1: So spiders are Arthur pods. Uh, they can have around 160 00:10:13,320 --> 00:10:17,040 Speaker 1: eight eyes um, which is a lot of eyes, But 161 00:10:17,120 --> 00:10:20,439 Speaker 1: they also have eight legs, so that kind of cancels 162 00:10:20,480 --> 00:10:23,000 Speaker 1: out in the eyes to legs contests, so they just 163 00:10:23,120 --> 00:10:27,600 Speaker 1: you know, fraction zero essentially or one. I don't know, 164 00:10:28,000 --> 00:10:31,640 Speaker 1: I'm I'm clearly not a math person, but I'm gonna 165 00:10:31,760 --> 00:10:36,240 Speaker 1: say that those things cancel out in spiders. Uh, we can't. 166 00:10:36,360 --> 00:10:39,920 Speaker 1: We can't factor their them into our eyes and legs 167 00:10:39,960 --> 00:10:46,640 Speaker 1: calculations as well. So insects typically have more legs than eyes. 168 00:10:47,440 --> 00:10:50,280 Speaker 1: Insects will all will often have a pair of compound 169 00:10:50,440 --> 00:10:52,960 Speaker 1: eyes on either side of their head. They may also 170 00:10:53,040 --> 00:10:57,280 Speaker 1: have one to three simple eyes called ocelli that detect 171 00:10:57,400 --> 00:11:00,800 Speaker 1: movement and simple light but don't see in the way 172 00:11:00,880 --> 00:11:03,600 Speaker 1: that eyes do. But even if we count all of 173 00:11:03,640 --> 00:11:09,760 Speaker 1: these o'celli, they technically have around five eyes um, while 174 00:11:10,160 --> 00:11:15,440 Speaker 1: insects typically have like six legs, So the legs would 175 00:11:15,440 --> 00:11:19,320 Speaker 1: still win, especially if you add in little animals like 176 00:11:19,320 --> 00:11:22,760 Speaker 1: the tartar grades which I mentioned earlier, who have eight 177 00:11:22,840 --> 00:11:28,199 Speaker 1: legs and only two simple eye spots. So, based on 178 00:11:28,400 --> 00:11:33,960 Speaker 1: my clearly very very deep mathematical calculations, uh, my guess 179 00:11:34,040 --> 00:11:36,920 Speaker 1: is that there are more legs than eyes in the 180 00:11:36,960 --> 00:11:40,760 Speaker 1: world just because of the sheer volume of insects tartar 181 00:11:40,760 --> 00:11:44,959 Speaker 1: grades these other very small animals invertebrates. But we do 182 00:11:45,080 --> 00:11:49,040 Speaker 1: have some animals who possess a shocking number of eyes, 183 00:11:49,600 --> 00:11:54,959 Speaker 1: like ocean dwelling kitans. So kitans are oval shaped mollusks 184 00:11:55,000 --> 00:12:00,440 Speaker 1: with a tough, flat plated shell. Certain types of kitan 185 00:12:00,880 --> 00:12:06,200 Speaker 1: can have thousands and thousands of simple o'celli eyes. Scallops 186 00:12:06,320 --> 00:12:10,800 Speaker 1: also have a shocking number of eyes. Scalops are bivalves 187 00:12:11,160 --> 00:12:15,360 Speaker 1: who can have over two hundred bright blue little eyeballs 188 00:12:15,400 --> 00:12:19,360 Speaker 1: that look like tiny beads which ready around their mantle, 189 00:12:19,800 --> 00:12:24,319 Speaker 1: peeking out from their shells. So I would say that 190 00:12:24,840 --> 00:12:28,880 Speaker 1: given if you're to ask me, like, what is the 191 00:12:28,920 --> 00:12:32,360 Speaker 1: maximum number of eyes versus legs something could have, I'd say, like, 192 00:12:32,960 --> 00:12:36,320 Speaker 1: you can have an animal that has more. Well, I 193 00:12:36,360 --> 00:12:38,920 Speaker 1: guess it depends on how you define legs though, because 194 00:12:38,920 --> 00:12:42,959 Speaker 1: there are these tiny little tentacle legs on things like starfish, 195 00:12:42,960 --> 00:12:45,040 Speaker 1: and if you counted each one of those as legs, 196 00:12:45,080 --> 00:12:47,800 Speaker 1: that'd be a lot of legs. It gets a little 197 00:12:47,800 --> 00:12:51,080 Speaker 1: funky depending on how you define a leg, how you 198 00:12:51,120 --> 00:12:54,840 Speaker 1: define an eye, but I think I still think that 199 00:12:54,920 --> 00:12:58,400 Speaker 1: there's probably way more legs than there are eyes in 200 00:12:58,440 --> 00:13:01,400 Speaker 1: the world. But if you disagree, you have some other 201 00:13:01,440 --> 00:13:04,800 Speaker 1: evidence right to me at Creature Future pot at gmail 202 00:13:04,840 --> 00:13:07,960 Speaker 1: dot com. I want to hear your arguments. Onto the 203 00:13:08,000 --> 00:13:12,040 Speaker 1: next listener question, do you think the t rex was 204 00:13:12,080 --> 00:13:16,679 Speaker 1: a scavenger or a predator or maybe something else altogether? 205 00:13:16,920 --> 00:13:20,640 Speaker 1: And this is from Corman. So the research on t 206 00:13:20,880 --> 00:13:24,640 Speaker 1: Rex has flip flopped a little bit historically. For a 207 00:13:24,760 --> 00:13:28,160 Speaker 1: while in the ninety nineties, it was a popular theory 208 00:13:28,200 --> 00:13:31,920 Speaker 1: that t Rex was just a scavenger, because the idea 209 00:13:32,000 --> 00:13:35,000 Speaker 1: that such a massive monster would have just been meekly 210 00:13:35,120 --> 00:13:39,000 Speaker 1: nibbling on dead prey was really surprising and there for 211 00:13:39,040 --> 00:13:42,400 Speaker 1: a fun thing to write about. So this idea was 212 00:13:42,520 --> 00:13:47,440 Speaker 1: mostly the brain child of paleontologist Jack Horner, who claimed 213 00:13:47,480 --> 00:13:49,920 Speaker 1: that t rex couldn't be a hunter given that its 214 00:13:50,080 --> 00:13:53,560 Speaker 1: arms were shorter than typical predators and that it was 215 00:13:53,679 --> 00:13:58,319 Speaker 1: too big and bulky to run quickly in chase after prey. 216 00:13:58,360 --> 00:14:03,120 Speaker 1: It also had large factory bulbs, which are the um 217 00:14:03,400 --> 00:14:08,280 Speaker 1: sensory organs of smell, and so his idea was that, well, 218 00:14:08,480 --> 00:14:11,280 Speaker 1: if they had this really keen sense of smell when 219 00:14:11,320 --> 00:14:15,160 Speaker 1: they used that to find carrion. Also, their teeth could 220 00:14:15,160 --> 00:14:19,400 Speaker 1: crush bone and thus perhaps they could extract marrow from carrion. 221 00:14:19,560 --> 00:14:23,120 Speaker 1: So maybe they were just the garbage disposals of the 222 00:14:23,200 --> 00:14:27,720 Speaker 1: dinosaur world. But the thing is that many paleontologists back 223 00:14:27,840 --> 00:14:31,240 Speaker 1: then already started disagreeing with Horner. But it was such 224 00:14:31,280 --> 00:14:34,520 Speaker 1: a fun and shocking idea that t Rex didn't actually 225 00:14:34,640 --> 00:14:37,760 Speaker 1: murder things it was just a scavenger that many media 226 00:14:37,800 --> 00:14:42,600 Speaker 1: outlets just kind of ran with that idea. But today 227 00:14:42,760 --> 00:14:46,360 Speaker 1: it's more definitive that t Rex was not just a 228 00:14:46,400 --> 00:14:51,640 Speaker 1: scavenger but hunted as well. So, first thing, Horner's evidence 229 00:14:51,760 --> 00:14:57,280 Speaker 1: was not super solid. It's an interesting idea and something 230 00:14:57,320 --> 00:15:01,040 Speaker 1: that would merit looking into, but you look into it, 231 00:15:01,040 --> 00:15:03,360 Speaker 1: it does kind of fall apart a little bit. So 232 00:15:03,520 --> 00:15:07,200 Speaker 1: his evidence doesn't really rule out hunting at all. There 233 00:15:07,240 --> 00:15:10,560 Speaker 1: are many carnivores that don't use their forearms to hunt, 234 00:15:10,680 --> 00:15:13,440 Speaker 1: so like the short t rex arms would not prevent 235 00:15:13,800 --> 00:15:17,920 Speaker 1: t Rex from hunting. So an example is secretary birds, 236 00:15:17,920 --> 00:15:21,400 Speaker 1: which are those beautiful long legged birds with those wonderful 237 00:15:21,480 --> 00:15:25,920 Speaker 1: crests and those long, luxurious eye eyelashes. They look like 238 00:15:26,000 --> 00:15:29,560 Speaker 1: runaway models, and they will actually stomp on their prey 239 00:15:29,640 --> 00:15:34,120 Speaker 1: to death like snails or lizards or snakes in and 240 00:15:34,160 --> 00:15:37,360 Speaker 1: it's they don't need arms in order to pound their 241 00:15:37,440 --> 00:15:41,880 Speaker 1: prey into oblivion. Also, having teeth that are capable of 242 00:15:41,920 --> 00:15:45,560 Speaker 1: crushing bone doesn't mean that they exclusively fed on bone. 243 00:15:46,320 --> 00:15:50,640 Speaker 1: And when paleontologists compared t rex teeth to something like 244 00:15:50,680 --> 00:15:55,240 Speaker 1: a hyena, who is much more um specialized for carry 245 00:15:55,240 --> 00:15:59,000 Speaker 1: on eating, it seems like the highness teeth are quite 246 00:15:59,000 --> 00:16:01,480 Speaker 1: a bit different from the t rex's teeth and quite 247 00:16:01,520 --> 00:16:06,720 Speaker 1: a bit more specialized for bone crunching than t Rex um. 248 00:16:06,800 --> 00:16:10,800 Speaker 1: So the thing that to me is really indicative that 249 00:16:10,920 --> 00:16:13,400 Speaker 1: t Rex was a hunter is that there has been 250 00:16:13,480 --> 00:16:17,640 Speaker 1: fossil evidence showing t rex teeth embedded in the flesh 251 00:16:17,760 --> 00:16:22,040 Speaker 1: of other dinosaurs like the duck bill dinosaur, and then 252 00:16:22,200 --> 00:16:26,120 Speaker 1: further evidence of tissue healing around the tooth, meaning that 253 00:16:26,240 --> 00:16:30,440 Speaker 1: t Rex took a bite out of this attempted victim 254 00:16:30,920 --> 00:16:33,960 Speaker 1: while it was still alive, it got away and then 255 00:16:34,000 --> 00:16:40,040 Speaker 1: healed around the wound. So the current theory is that 256 00:16:40,200 --> 00:16:45,880 Speaker 1: t Rex was like many modern predators who hunted but 257 00:16:46,240 --> 00:16:48,880 Speaker 1: would happily carry in if they were lucky enough to 258 00:16:48,920 --> 00:16:55,080 Speaker 1: find it in time. Um. The other part of Jack horners, 259 00:16:55,320 --> 00:16:59,120 Speaker 1: I'm just realizing that Jack Horner is like the name 260 00:16:59,200 --> 00:17:01,720 Speaker 1: of some kind of isn't there Isn't there that like 261 00:17:01,880 --> 00:17:04,399 Speaker 1: fairytale rhyme. That's like little Jack Horner sat in a 262 00:17:04,480 --> 00:17:09,879 Speaker 1: corner eating a something pie. Anyways, whatever, he was a 263 00:17:09,920 --> 00:17:13,800 Speaker 1: real guy apparently. So back on track, Jack Horner was 264 00:17:13,840 --> 00:17:17,359 Speaker 1: saying like t Rex was too big, too lumbering, and 265 00:17:17,400 --> 00:17:20,160 Speaker 1: ponderous to be able to run and chase down prey. 266 00:17:20,240 --> 00:17:23,480 Speaker 1: And in terms of t Rex is speed. Scientists have 267 00:17:23,560 --> 00:17:27,080 Speaker 1: really waffled back and forth on this. So for a 268 00:17:27,080 --> 00:17:30,040 Speaker 1: while they were saying that they could reach pretty decent 269 00:17:30,119 --> 00:17:34,359 Speaker 1: running speed. More recent computer models estimated their running speed 270 00:17:34,480 --> 00:17:37,720 Speaker 1: a little bit slower, around twelve miles per hour or 271 00:17:37,880 --> 00:17:42,080 Speaker 1: nineteen kilometers per hour, which a human, like a fast 272 00:17:42,160 --> 00:17:46,880 Speaker 1: human and a fleet footed animal would be able to outrun. Um. 273 00:17:46,920 --> 00:17:51,040 Speaker 1: But that doesn't mean that t Rex couldn't hunt or 274 00:17:51,160 --> 00:17:54,800 Speaker 1: chase things down, because there were certainly slower dinosaurs that 275 00:17:54,880 --> 00:17:58,760 Speaker 1: the t Rex would have been able to chase down. Um. Also, 276 00:17:59,359 --> 00:18:03,359 Speaker 1: speed isn't only necessary for chasing prey. So this idea 277 00:18:03,480 --> 00:18:07,200 Speaker 1: that if you're slow, you want to be a carryon 278 00:18:07,320 --> 00:18:10,880 Speaker 1: eater rather than a prey chaser. Is a little bit 279 00:18:11,000 --> 00:18:16,640 Speaker 1: strange because carrion also favors fast animals who can quickly 280 00:18:16,800 --> 00:18:21,920 Speaker 1: track down and get to the buffet first. So when 281 00:18:21,960 --> 00:18:24,760 Speaker 1: you have an all you can eat carrion buffet in 282 00:18:24,800 --> 00:18:27,359 Speaker 1: the wild, you really want to be the first ones 283 00:18:27,400 --> 00:18:29,600 Speaker 1: to get there, because if you're not, it might be 284 00:18:29,640 --> 00:18:33,200 Speaker 1: all gone by the time you arrive. Uh, and you 285 00:18:33,240 --> 00:18:36,720 Speaker 1: would have a lot of smaller animals. Like a pack 286 00:18:36,800 --> 00:18:41,159 Speaker 1: of smaller animals that descend on carrion and tear it 287 00:18:41,200 --> 00:18:43,920 Speaker 1: apart with many mouths may be able to get all 288 00:18:43,920 --> 00:18:47,040 Speaker 1: the usable meat far more quickly than something like a 289 00:18:47,119 --> 00:18:51,159 Speaker 1: t rex could, Like if it's lumbering over by the 290 00:18:51,160 --> 00:18:54,120 Speaker 1: time it gets to the carrying it might be too late. 291 00:18:54,280 --> 00:18:57,040 Speaker 1: And remember, like the floor is not littered with carrion, 292 00:18:57,480 --> 00:18:59,800 Speaker 1: there are a lot there are many more like living 293 00:19:00,000 --> 00:19:03,120 Speaker 1: animals out there at a given time than like rod 294 00:19:03,200 --> 00:19:05,879 Speaker 1: and carrion just left out, And so carrion is going 295 00:19:05,920 --> 00:19:09,680 Speaker 1: to be a more rare encounter than a living animal. 296 00:19:09,960 --> 00:19:14,920 Speaker 1: So it's very very highly competitive. It's why you see 297 00:19:14,920 --> 00:19:18,320 Speaker 1: like when you when you have scavengers fighting over carrion. 298 00:19:18,960 --> 00:19:23,680 Speaker 1: It's very it's not easy pickings to be a scavenger. 299 00:19:23,760 --> 00:19:25,800 Speaker 1: This idea that like, well, if you can't hack it 300 00:19:25,800 --> 00:19:27,800 Speaker 1: as a hunter, you gotta hack it as a scavenger 301 00:19:27,880 --> 00:19:30,160 Speaker 1: is kind of not not really the case, Like you've 302 00:19:30,200 --> 00:19:32,439 Speaker 1: got to have skills to be a scavenger. So this 303 00:19:32,520 --> 00:19:36,000 Speaker 1: idea that t Rex was too slow to chase down prey, 304 00:19:36,040 --> 00:19:41,040 Speaker 1: even larger dinosaurs, but somehow fast enough to quickly locate 305 00:19:41,160 --> 00:19:44,959 Speaker 1: carrion whenever it would happen to fall to the ground, 306 00:19:45,960 --> 00:19:50,160 Speaker 1: is a little bit suspect. So I think that, yeah, 307 00:19:50,400 --> 00:19:52,840 Speaker 1: when when this is all put together, I think that 308 00:19:52,960 --> 00:19:56,480 Speaker 1: t Rex would have had to rely on every tool 309 00:19:56,480 --> 00:19:59,560 Speaker 1: at its disposal to get enough meat to be that 310 00:19:59,680 --> 00:20:02,320 Speaker 1: huge size. So would it turn its snows up at Karen. No, 311 00:20:02,520 --> 00:20:06,080 Speaker 1: I don't think it would. Uh, just like modern day predators, 312 00:20:06,119 --> 00:20:09,360 Speaker 1: they often will eat Karen if it's there, if they're 313 00:20:09,440 --> 00:20:11,760 Speaker 1: lucky enough to find it and lucky enough to get 314 00:20:11,800 --> 00:20:15,400 Speaker 1: there first, Yeah, they will definitely eat it. Um. But 315 00:20:15,640 --> 00:20:19,040 Speaker 1: I feel like it can't be that it relied on Karrien. 316 00:20:19,119 --> 00:20:22,240 Speaker 1: It had to have been hunting as well to be 317 00:20:22,400 --> 00:20:26,520 Speaker 1: able to sustain its mass like that, And it seems 318 00:20:26,640 --> 00:20:30,200 Speaker 1: quite well built for hunting, and I just don't think 319 00:20:30,240 --> 00:20:34,760 Speaker 1: that Jack Horner's arguments were very convincing and ruling out 320 00:20:34,840 --> 00:20:38,639 Speaker 1: hunting and then coupling that with the fossil evidence showing 321 00:20:38,720 --> 00:20:42,440 Speaker 1: tooth marks inside, like what we knew was a dinosaur 322 00:20:42,480 --> 00:20:45,680 Speaker 1: that was alive and then healed over that Bye, Yeah, 323 00:20:45,920 --> 00:20:49,760 Speaker 1: I think it was a predator. So, you know, definitely 324 00:20:49,800 --> 00:20:52,520 Speaker 1: not something you would want to run into in the wild. 325 00:20:52,560 --> 00:20:55,879 Speaker 1: But then again, if the most recent computer models are correct, 326 00:20:56,080 --> 00:20:58,480 Speaker 1: maybe we could outrun t rex. I wouldn't want to 327 00:20:58,520 --> 00:21:09,040 Speaker 1: try it. Onto The next listener question kind of related 328 00:21:09,600 --> 00:21:12,840 Speaker 1: which prehistoric animals would make the best pets. There are 329 00:21:13,080 --> 00:21:16,400 Speaker 1: far too many candidates for worst pets. There are two 330 00:21:16,400 --> 00:21:19,639 Speaker 1: in particular. I've read about the bare dog of the 331 00:21:19,680 --> 00:21:22,400 Speaker 1: family emphas Cian a Day. It's sort of a bear 332 00:21:22,480 --> 00:21:25,520 Speaker 1: like dog. And then there's Hemmy Scion the dog Bear. 333 00:21:25,720 --> 00:21:27,960 Speaker 1: It is a dog like bear. I'm guessing the bare 334 00:21:28,040 --> 00:21:31,520 Speaker 1: dog would be a little bit better as a pet. Stephen, Hi, Stephen. 335 00:21:31,840 --> 00:21:35,600 Speaker 1: So both those animal families are very interesting. They are 336 00:21:35,720 --> 00:21:42,280 Speaker 1: early carnivorous mammals. Um Emphasion a Day is more sort 337 00:21:42,320 --> 00:21:46,680 Speaker 1: of like just related to a bunch of modern day carnivores, 338 00:21:47,200 --> 00:21:50,479 Speaker 1: whereas the himmy scions seem to be more related to 339 00:21:50,560 --> 00:21:54,920 Speaker 1: the bear family, so amphis cian a day uh that 340 00:21:55,040 --> 00:21:58,639 Speaker 1: family would have I do agree that I think they 341 00:21:58,640 --> 00:22:02,960 Speaker 1: would have been more were potentially more species in that 342 00:22:03,040 --> 00:22:06,719 Speaker 1: family that could have become pets, maybe after some unnatural 343 00:22:06,760 --> 00:22:10,720 Speaker 1: selection on humanities part like we did with wolves. Uh. 344 00:22:10,840 --> 00:22:14,080 Speaker 1: So amphacian a day were a family of species of 345 00:22:14,119 --> 00:22:18,439 Speaker 1: mammalian carnivores, and while some were quite big like the 346 00:22:18,480 --> 00:22:21,960 Speaker 1: size of a bear, some were tiny, under eleven pounds 347 00:22:22,040 --> 00:22:26,560 Speaker 1: or five kilograms so preust ark Chihuahua's. I would rather 348 00:22:26,560 --> 00:22:29,760 Speaker 1: try my luck with the tiny ones personally. But then again, 349 00:22:29,800 --> 00:22:33,760 Speaker 1: we did domess kate wolves, which are quite huge and scary, 350 00:22:33,840 --> 00:22:37,480 Speaker 1: and kudos to those early humans that had the canes 351 00:22:37,520 --> 00:22:42,719 Speaker 1: to do that. So the Himmision family or sub family 352 00:22:42,920 --> 00:22:45,680 Speaker 1: I think is the most current understanding, seems to be 353 00:22:46,640 --> 00:22:49,800 Speaker 1: more of an extinct ancestor of modern bears or a 354 00:22:49,800 --> 00:22:52,920 Speaker 1: cousin extinct cousin of modern bears. And I honestly they 355 00:22:53,119 --> 00:22:56,879 Speaker 1: look pretty fierce. Yes, they do look like a cross 356 00:22:56,920 --> 00:22:58,639 Speaker 1: between a dog and a bear, and I don't think 357 00:22:58,680 --> 00:23:02,399 Speaker 1: i'd want to tangle with them person only uh and go. 358 00:23:02,680 --> 00:23:05,600 Speaker 1: Continuing with the theme that I am a big weenie, 359 00:23:06,400 --> 00:23:10,760 Speaker 1: the best extinct pet, in my opinion, would be the teeniest, tiniest, cutest, 360 00:23:10,960 --> 00:23:15,800 Speaker 1: most harmless of extinct mammals, the battodninetes, a shrew like 361 00:23:15,880 --> 00:23:18,920 Speaker 1: animal who lived over forty million years ago in North 362 00:23:18,960 --> 00:23:23,560 Speaker 1: America and was probably the smallest mammal ever to have lived. 363 00:23:24,040 --> 00:23:27,840 Speaker 1: It likely weighed only about a gram and could comfortably 364 00:23:27,920 --> 00:23:32,479 Speaker 1: fit on top of a pencil racer. For comparison, an 365 00:23:32,480 --> 00:23:37,520 Speaker 1: adult house mouse weighs around twenty grams, so that's like 366 00:23:37,720 --> 00:23:41,520 Speaker 1: twenty times the size of this little guy. So the 367 00:23:41,560 --> 00:23:45,399 Speaker 1: current smallest mammals are the bumblebee bat and the etruscan shrew, 368 00:23:45,880 --> 00:23:49,720 Speaker 1: who are tiny and way around two grams each, So 369 00:23:49,800 --> 00:23:53,320 Speaker 1: that is still twice as big as the batto done nineties. 370 00:23:53,960 --> 00:23:57,159 Speaker 1: So I really love these teeny tiny guys. Wish they 371 00:23:57,160 --> 00:23:59,719 Speaker 1: were still around so I could fit like a hundred 372 00:23:59,720 --> 00:24:03,560 Speaker 1: of them in my pocket. Onto the next listener question. 373 00:24:03,880 --> 00:24:06,720 Speaker 1: Just finished watching an episode of the detective show Monk 374 00:24:06,840 --> 00:24:09,119 Speaker 1: in which an elephant is used as a murder weapon. 375 00:24:09,520 --> 00:24:12,600 Speaker 1: The elephants trainer placed his head under the elephant's foot, 376 00:24:12,640 --> 00:24:15,640 Speaker 1: and the murderer commanded the elephant to press down via 377 00:24:15,680 --> 00:24:19,600 Speaker 1: a walkie talkie taped behind its ears. My question is, 378 00:24:19,720 --> 00:24:23,720 Speaker 1: given their documented intelligence and compassion for other species, would 379 00:24:23,720 --> 00:24:26,720 Speaker 1: an elephant understand the outcome of crushing a person's head. 380 00:24:27,080 --> 00:24:29,199 Speaker 1: If so, does this mean that the elephant in this 381 00:24:29,280 --> 00:24:32,679 Speaker 1: show is actually an accomplish instead of a murder weapon. 382 00:24:33,080 --> 00:24:35,760 Speaker 1: This is from Gretchen. Also she showed me peanut butter 383 00:24:35,800 --> 00:24:38,960 Speaker 1: and jelly beans, who are two adorable kiddies. Thank you 384 00:24:39,000 --> 00:24:43,199 Speaker 1: for that great question. Um, there's not great research on 385 00:24:43,280 --> 00:24:47,199 Speaker 1: whether elephants understand murder, given how unethical it would be 386 00:24:47,240 --> 00:24:50,120 Speaker 1: to try to get a bunch of elephants to murder people. Uh. 387 00:24:50,160 --> 00:24:53,879 Speaker 1: That being said, let's look into elephants and killing and 388 00:24:54,200 --> 00:24:56,439 Speaker 1: what their thoughts might be about such a thing. So, 389 00:24:57,359 --> 00:24:59,919 Speaker 1: there is a history of elephants being used in execution 390 00:25:00,359 --> 00:25:04,600 Speaker 1: in ancient Rome, Carthage, South and Southeast Asia and Africa. 391 00:25:05,080 --> 00:25:08,159 Speaker 1: It was a very public, sort of lamboyant way to 392 00:25:08,280 --> 00:25:11,800 Speaker 1: execute someone, as was the idea like we can control 393 00:25:12,200 --> 00:25:15,320 Speaker 1: this huge animal and get them to smash you, and 394 00:25:15,359 --> 00:25:18,040 Speaker 1: so it was supposed to inspire fear in awe of 395 00:25:18,160 --> 00:25:22,440 Speaker 1: the ruler. Um. So in these cases, the elephants were 396 00:25:22,520 --> 00:25:25,320 Speaker 1: under the control of a writer, and they could be 397 00:25:25,400 --> 00:25:29,199 Speaker 1: trained to either kill the convict or to spare the 398 00:25:29,280 --> 00:25:33,480 Speaker 1: prisoners if there was a last call for mercy. So 399 00:25:33,640 --> 00:25:36,840 Speaker 1: sometimes the elephants were trained not to kill the victims 400 00:25:36,880 --> 00:25:39,159 Speaker 1: but to kind of rough them up, which I suppose 401 00:25:39,240 --> 00:25:43,800 Speaker 1: at the time was considered more humanitarian. So could the 402 00:25:43,840 --> 00:25:47,399 Speaker 1: elephants understand the moral implications here? I think first we 403 00:25:47,560 --> 00:25:51,119 Speaker 1: need to know if elephants even understand the concept of death, 404 00:25:51,600 --> 00:25:55,320 Speaker 1: which is incredibly difficult to study. Researchers have gone through 405 00:25:55,440 --> 00:25:59,080 Speaker 1: videos of elephants responses to other dead elephants, and there 406 00:25:59,119 --> 00:26:02,480 Speaker 1: does seem to be pattern of behavior that indicates they 407 00:26:02,480 --> 00:26:06,080 Speaker 1: since something is off and are upset in some way. 408 00:26:06,119 --> 00:26:09,879 Speaker 1: They have the body language that indicates distress. But this 409 00:26:10,000 --> 00:26:14,120 Speaker 1: doesn't necessarily indicate they understand death fully, just that they're 410 00:26:14,160 --> 00:26:18,159 Speaker 1: distressed that this other elephant is not behaving in the 411 00:26:18,160 --> 00:26:22,439 Speaker 1: way that they want so, namely by being dead. So 412 00:26:22,480 --> 00:26:27,399 Speaker 1: there has been anecdotal evidence of elephants being careful around humans. 413 00:26:27,440 --> 00:26:30,919 Speaker 1: So one such is the story of which is kind 414 00:26:30,920 --> 00:26:33,200 Speaker 1: of hard to verify. I don't know if this is true. 415 00:26:33,240 --> 00:26:35,720 Speaker 1: It sounds like it could be, but it was the 416 00:26:35,760 --> 00:26:38,760 Speaker 1: story of an elephant crashing into a couple's home, then 417 00:26:38,800 --> 00:26:41,639 Speaker 1: stopping when it started to hear a baby crying and 418 00:26:41,800 --> 00:26:44,440 Speaker 1: moving some of the debris off of the baby's crib 419 00:26:44,640 --> 00:26:49,360 Speaker 1: before leaving. And um. There are also, though a lot 420 00:26:49,400 --> 00:26:52,960 Speaker 1: of stories of elephants kind of mowing people down, you know, 421 00:26:53,040 --> 00:26:57,920 Speaker 1: trampling tourists, trampling people and killing them. And I don't 422 00:26:58,000 --> 00:27:01,920 Speaker 1: know whether this is like intentional murder or not if 423 00:27:01,920 --> 00:27:06,080 Speaker 1: they fully understand I mean, like clearly when they do 424 00:27:06,400 --> 00:27:09,760 Speaker 1: trample people, I think they're distressed and they're you know, 425 00:27:09,840 --> 00:27:15,880 Speaker 1: trying to defend their territory there or defend themselves. Um, 426 00:27:15,920 --> 00:27:19,159 Speaker 1: even if the human poses no threat to them, the 427 00:27:19,200 --> 00:27:23,879 Speaker 1: elephant doesn't necessarily know that, so researchers. Although there is 428 00:27:23,960 --> 00:27:27,920 Speaker 1: research showing that elephants can distinguish sometimes between humans that 429 00:27:27,960 --> 00:27:30,520 Speaker 1: are more dangerous in humans that may not harm them. 430 00:27:31,080 --> 00:27:33,399 Speaker 1: Researchers have found that elephants seem to be able to 431 00:27:33,400 --> 00:27:36,719 Speaker 1: tell the difference between groups of people based on smell 432 00:27:36,880 --> 00:27:40,199 Speaker 1: and accent, and react more defensively to the sounds and 433 00:27:40,240 --> 00:27:43,920 Speaker 1: smells of groups of people who typically hunt them. It's 434 00:27:43,920 --> 00:27:47,160 Speaker 1: a long story short. I don't really know if elephants 435 00:27:47,160 --> 00:27:50,359 Speaker 1: could grasp the implications of smashing a human's head. My 436 00:27:50,520 --> 00:27:53,960 Speaker 1: sense is that they may have some understanding of cause 437 00:27:53,960 --> 00:27:57,399 Speaker 1: and effect um, because they are quite intelligent and they 438 00:27:57,440 --> 00:28:02,680 Speaker 1: are highly social. UM. An elephant raised in captivity, like 439 00:28:02,720 --> 00:28:06,120 Speaker 1: a circus elephant, or one of these elephants used in 440 00:28:06,160 --> 00:28:09,959 Speaker 1: these like ancient executions, I don't know if they'd be 441 00:28:10,000 --> 00:28:14,320 Speaker 1: properly socialized to kind of learn elephant ethics, because there 442 00:28:14,359 --> 00:28:17,960 Speaker 1: may be some like elephant culture of teaching elephants like 443 00:28:18,040 --> 00:28:20,640 Speaker 1: gentleness and things. So it's kind of hard to know, 444 00:28:21,280 --> 00:28:26,280 Speaker 1: based on like your fictional monk Um example or the 445 00:28:26,320 --> 00:28:31,520 Speaker 1: real life historical examples, whether that's typical elephant behavior, or 446 00:28:31,560 --> 00:28:34,520 Speaker 1: whether an elephant in the wild would be more hesitant 447 00:28:34,600 --> 00:28:39,000 Speaker 1: to do something like that um, because like in captivity, 448 00:28:39,040 --> 00:28:41,920 Speaker 1: an elephant might just associate that crushing with getting a 449 00:28:42,000 --> 00:28:46,280 Speaker 1: reward that reinforced that behavior sword so that elephants, if 450 00:28:46,280 --> 00:28:48,760 Speaker 1: an elephant is capable of having a sense of morality, 451 00:28:48,840 --> 00:28:50,920 Speaker 1: it would be very messed up by being in a 452 00:28:50,960 --> 00:28:54,960 Speaker 1: circus UM. So I do think that elephants who have 453 00:28:55,040 --> 00:28:58,040 Speaker 1: a normal social life in the wild probably do learn 454 00:28:58,120 --> 00:29:01,680 Speaker 1: some cause and effect of their actions, and they probably 455 00:29:01,720 --> 00:29:05,240 Speaker 1: have some understanding of that they can cause harm by 456 00:29:05,240 --> 00:29:09,880 Speaker 1: trampling something. UM, And I think they do understand something 457 00:29:09,960 --> 00:29:13,320 Speaker 1: is wrong when an individual dies when it stops moving. 458 00:29:13,400 --> 00:29:16,000 Speaker 1: They exhibit a lot of distress when it comes to that, 459 00:29:16,200 --> 00:29:20,479 Speaker 1: So I'm not I'm not um convinced that they fully 460 00:29:20,520 --> 00:29:24,680 Speaker 1: grasp death, but I do think they have some understanding 461 00:29:24,760 --> 00:29:28,160 Speaker 1: of cause and effect harm as well as when something 462 00:29:28,280 --> 00:29:32,760 Speaker 1: is dead that's not normal and that there's something off 463 00:29:32,800 --> 00:29:36,600 Speaker 1: about that and it upsets them. So not quite at 464 00:29:36,640 --> 00:29:40,720 Speaker 1: the point of upgrading your monk elephant to accomplice, but uh, 465 00:29:40,800 --> 00:29:45,240 Speaker 1: you know, maybe somewhat he might have an understanding that 466 00:29:45,280 --> 00:29:47,960 Speaker 1: this may not quite be right. But I wouldn't arrest 467 00:29:48,000 --> 00:29:51,120 Speaker 1: that elephant. Free that elephant, get him a lawyer. Thank 468 00:29:51,160 --> 00:29:54,080 Speaker 1: you guys so much for listening. And if you have 469 00:29:54,160 --> 00:29:56,280 Speaker 1: a listener question you want to ask, you can write 470 00:29:56,280 --> 00:29:59,680 Speaker 1: to me a Creature feature pot at gmail dot com. 471 00:30:00,040 --> 00:30:02,840 Speaker 1: Um And you know, if you enjoy the show, if 472 00:30:02,840 --> 00:30:05,320 Speaker 1: you want more of these listener questions episodes, you can 473 00:30:05,360 --> 00:30:07,600 Speaker 1: leave me feedback. You can leave a rating or review, 474 00:30:08,320 --> 00:30:11,520 Speaker 1: and hey, happy holidays everyone. I'll be back next week 475 00:30:11,560 --> 00:30:15,240 Speaker 1: with a brand new spanking episode. Of Creature feature and 476 00:30:15,600 --> 00:30:18,160 Speaker 1: thank you so much for listening. Thanks to the Space 477 00:30:18,240 --> 00:30:21,600 Speaker 1: Classics for their super awesome song Exo Alumina. Creature features 478 00:30:21,600 --> 00:30:24,520 Speaker 1: a production of I Heart Radio. For more podcasts like 479 00:30:24,600 --> 00:30:27,000 Speaker 1: the one you just heard, visit the I Heart Radio app, 480 00:30:27,040 --> 00:30:29,360 Speaker 1: Apple Podcast, or Hey, guess what marve you listen to 481 00:30:29,360 --> 00:30:34,400 Speaker 1: your favorite shows to see you next Wednesday.