1 00:00:06,840 --> 00:00:10,520 Speaker 1: Welcome to Creature Feature Production of iHeartRadio. I'm your host 2 00:00:10,560 --> 00:00:15,320 Speaker 1: of Many Parasites, Katie Goolden. I studied psychology and evolutionary biology, 3 00:00:15,360 --> 00:00:20,400 Speaker 1: and today on the show, it's a Buggy Listener Questions episode. 4 00:00:21,200 --> 00:00:25,159 Speaker 2: I got a bunch of questions about insects, and I 5 00:00:25,160 --> 00:00:29,280 Speaker 2: thought i'd answer them all at once, so I. 6 00:00:29,080 --> 00:00:33,120 Speaker 1: Hope you enjoy. Let's get right into it. 7 00:00:33,159 --> 00:00:36,040 Speaker 2: Oh and remember, if you have a question that you 8 00:00:36,080 --> 00:00:38,520 Speaker 2: would like answered, you can write to me at Creature 9 00:00:38,560 --> 00:00:41,960 Speaker 2: Featurepod at gmail dot com. Doesn't have to be about insects, 10 00:00:42,040 --> 00:00:46,199 Speaker 2: but it certainly can be. So let's get right into it, Hi, Katie, 11 00:00:46,240 --> 00:00:50,000 Speaker 2: what do bugs c? Specifically, what do insects see, especially 12 00:00:50,080 --> 00:00:53,840 Speaker 2: the ones with large, elaborate compound eyes is like a 13 00:00:53,920 --> 00:00:57,840 Speaker 2: dragonflies individual eye segment directly connected to their brains. Does 14 00:00:58,000 --> 00:01:01,880 Speaker 2: eye size correlate with brain size and intelligence? Thanks love 15 00:01:01,920 --> 00:01:07,880 Speaker 2: the show, Juanito. Also some additional context from Juanito. This 16 00:01:08,040 --> 00:01:12,319 Speaker 2: question was prompted by reading Adrian Tchaikovski's Children of Time 17 00:01:12,560 --> 00:01:16,080 Speaker 2: novel and the book A species of jumping spider Portia 18 00:01:16,319 --> 00:01:21,160 Speaker 2: labiata gets accidentally uplifted to sentience and technology developing level. 19 00:01:21,560 --> 00:01:24,880 Speaker 2: The author's description of the iraqtid censorium is fascinating. And 20 00:01:24,959 --> 00:01:27,479 Speaker 2: you know what, all his books I've read so far 21 00:01:27,520 --> 00:01:32,520 Speaker 2: investigate crazy interesting biology, invented the aliens, worlds, or real 22 00:01:32,640 --> 00:01:38,039 Speaker 2: the cute little spider guys. I just discovered Adrian Tryikovsky 23 00:01:38,120 --> 00:01:40,679 Speaker 2: this year and I heartily recommend his books. He studied 24 00:01:40,760 --> 00:01:44,440 Speaker 2: zoology and psych before becoming an author. Wow, that sounds 25 00:01:44,440 --> 00:01:47,400 Speaker 2: a lot like me, except I haven't written about super 26 00:01:47,440 --> 00:01:52,200 Speaker 2: intelligent jumping spiders, but that sounds very cool. Thank you 27 00:01:52,520 --> 00:01:56,200 Speaker 2: Juanito for the question and for the book recommendation. I'll 28 00:01:56,280 --> 00:02:01,360 Speaker 2: check that out. So this is a great question about eyesight. 29 00:02:02,000 --> 00:02:06,680 Speaker 2: How insects see the world, how compound eyes work, if 30 00:02:06,800 --> 00:02:10,240 Speaker 2: eye size correlates with brain size, and intelligence, all really 31 00:02:10,280 --> 00:02:15,200 Speaker 2: really good questions. So the broad answer in terms of 32 00:02:15,400 --> 00:02:18,760 Speaker 2: insect vision is that it really depends on the insect. 33 00:02:19,160 --> 00:02:22,160 Speaker 2: Different insects have different kind of eyes. Even insects who 34 00:02:22,200 --> 00:02:26,280 Speaker 2: have compound eyes can have different types of compound eyes 35 00:02:26,320 --> 00:02:29,360 Speaker 2: in different ways. Those are wired to the brain. But 36 00:02:29,480 --> 00:02:34,400 Speaker 2: let's break down first the components of how vision is processed. 37 00:02:34,919 --> 00:02:38,400 Speaker 2: You have the hardware, aspects of the eye, the lens, 38 00:02:38,520 --> 00:02:41,520 Speaker 2: the shape of the eye, the retina, whether the animal 39 00:02:41,600 --> 00:02:46,040 Speaker 2: has rods, cones or both, or simply light sensitive cells 40 00:02:46,080 --> 00:02:48,320 Speaker 2: that can tell the difference between dark and lights. So 41 00:02:48,360 --> 00:02:52,040 Speaker 2: there's a lot of hardware to the eye that will 42 00:02:52,080 --> 00:02:55,960 Speaker 2: determine how the light goes into the eye and where 43 00:02:55,960 --> 00:02:59,240 Speaker 2: it goes to. And then the information has to reach 44 00:02:59,280 --> 00:03:04,360 Speaker 2: the brain, usually through some sort of nerve cluster, and 45 00:03:04,360 --> 00:03:07,040 Speaker 2: then the brain has to process the raw visual data, 46 00:03:07,480 --> 00:03:10,160 Speaker 2: and after that other parts of the brain interpret those 47 00:03:10,280 --> 00:03:14,600 Speaker 2: findings and those get sent down to other nerves that 48 00:03:14,760 --> 00:03:19,680 Speaker 2: control muscles and reactions. So there are multiple points from 49 00:03:19,800 --> 00:03:23,760 Speaker 2: the light hitting the eye to the organism's experience where 50 00:03:23,800 --> 00:03:27,919 Speaker 2: that light is being transformed, both physically by the structure 51 00:03:27,919 --> 00:03:31,079 Speaker 2: of the eye, by like the lens being directed into 52 00:03:31,120 --> 00:03:34,840 Speaker 2: the eye, and then once it's inside, how it's hitting 53 00:03:35,040 --> 00:03:38,440 Speaker 2: the back of the eye, what it's hitting, the sensory cells, 54 00:03:38,480 --> 00:03:40,920 Speaker 2: the structures inside the eye that are funneling the light, 55 00:03:42,440 --> 00:03:46,000 Speaker 2: and then also how that data is perceived, So both 56 00:03:46,040 --> 00:03:48,400 Speaker 2: how it goes from the eye to the brain, the 57 00:03:48,440 --> 00:03:54,440 Speaker 2: wiring of the neurons that transfer that data, and then 58 00:03:54,480 --> 00:03:58,680 Speaker 2: how the brain process is it. So in terms of 59 00:03:59,000 --> 00:04:04,600 Speaker 2: what something sees, it's a very interestingly subjective experience, even 60 00:04:04,640 --> 00:04:08,760 Speaker 2: for us humans. We might think our site shows completely 61 00:04:08,800 --> 00:04:12,160 Speaker 2: objective reality, but if you've ever seen an optical illusion, 62 00:04:12,280 --> 00:04:14,920 Speaker 2: you'll realize our brains do a lot of funny business 63 00:04:15,160 --> 00:04:17,760 Speaker 2: with that light hitting our eyes. There's a lot that 64 00:04:17,839 --> 00:04:21,039 Speaker 2: happens between that and getting processed in our brain to 65 00:04:21,040 --> 00:04:23,440 Speaker 2: the point where you can look at an optical illusion 66 00:04:24,000 --> 00:04:27,760 Speaker 2: and see something very strange, because that's your brain working 67 00:04:27,920 --> 00:04:31,000 Speaker 2: to try to interpret these signals and adding things in 68 00:04:31,040 --> 00:04:36,640 Speaker 2: that may not actually be there. So let's also explore 69 00:04:36,680 --> 00:04:41,239 Speaker 2: this question of eye size and intelligence. So ie size 70 00:04:41,279 --> 00:04:45,440 Speaker 2: and brain size are not always correlated, and brain size 71 00:04:45,640 --> 00:04:49,840 Speaker 2: isn't always correlated with superior intelligence. You have some things 72 00:04:49,839 --> 00:04:53,159 Speaker 2: that might have really big brains and not necessarily be 73 00:04:53,200 --> 00:04:55,800 Speaker 2: as intelligent as something that has a smaller brain. Right, 74 00:04:56,560 --> 00:04:59,800 Speaker 2: we certainly don't have the largest brains in the world, 75 00:05:00,000 --> 00:05:04,360 Speaker 2: but we're very intelligent. But in general, the general trend 76 00:05:04,880 --> 00:05:09,440 Speaker 2: is that brain size can and does correlate with intelligence. 77 00:05:09,480 --> 00:05:12,640 Speaker 2: It's just not a hard rule. There's many, many exceptions, 78 00:05:13,040 --> 00:05:16,400 Speaker 2: and a similar thing happens with brain and ee size, 79 00:05:16,600 --> 00:05:21,080 Speaker 2: or say like sensitive sensory organs and brain size. So 80 00:05:21,880 --> 00:05:24,560 Speaker 2: there are some studies that find that eye size is 81 00:05:24,720 --> 00:05:28,440 Speaker 2: positively correlated with brain size, though it's highly dependent on 82 00:05:28,560 --> 00:05:32,159 Speaker 2: the type of animal. There's been some research on frogs 83 00:05:32,200 --> 00:05:36,599 Speaker 2: that find eye size and brain size are linked, but 84 00:05:36,920 --> 00:05:40,919 Speaker 2: studies done in guppies the fish found that eye size 85 00:05:40,920 --> 00:05:44,279 Speaker 2: and brain size were positively correlated, but it did not 86 00:05:44,400 --> 00:05:54,279 Speaker 2: actually predict better visual acuity or necessarily intelligence. So the 87 00:05:54,320 --> 00:05:57,080 Speaker 2: idea behind brain size and eye size or eye complexity 88 00:05:57,160 --> 00:06:00,520 Speaker 2: being related is a good one. Naturally, bigger eyes and 89 00:06:00,560 --> 00:06:04,599 Speaker 2: more complex visual processing should require more space in the 90 00:06:04,640 --> 00:06:08,480 Speaker 2: brain are at least more complex brain folds. We do 91 00:06:08,520 --> 00:06:12,440 Speaker 2: actually see this kind of correlation in dolphins who have 92 00:06:12,760 --> 00:06:16,480 Speaker 2: massive auditory processing parts of their brains to help with 93 00:06:16,560 --> 00:06:20,880 Speaker 2: the complex task of echolocation, and in humans we have 94 00:06:21,040 --> 00:06:25,320 Speaker 2: huge visual processing areas of the brain and complex large 95 00:06:25,320 --> 00:06:30,640 Speaker 2: eyes and very complex vision. But some counter examples. You 96 00:06:30,720 --> 00:06:33,920 Speaker 2: have the tarsiir, which is a tiny primate who has 97 00:06:34,040 --> 00:06:38,240 Speaker 2: disproportionately large eyeballs. They're so big that they can barely 98 00:06:38,279 --> 00:06:41,520 Speaker 2: fit in its head. They can't turn in their sockets, 99 00:06:41,560 --> 00:06:43,240 Speaker 2: so if it wants to look around, it has to 100 00:06:43,320 --> 00:06:47,320 Speaker 2: move its whole head rotate its head around, and its 101 00:06:47,400 --> 00:06:49,919 Speaker 2: brain is not that big. In fact, its brain is 102 00:06:49,960 --> 00:06:53,479 Speaker 2: smaller than one of its giant eyeballs. Also, its brain 103 00:06:53,560 --> 00:06:58,520 Speaker 2: is relatively smooth, and so the trade off seems to 104 00:06:58,520 --> 00:07:00,760 Speaker 2: be that it has ditched a lot of its other 105 00:07:00,839 --> 00:07:06,120 Speaker 2: brain mass, say like olfactory brain mass or other you know, 106 00:07:06,839 --> 00:07:11,440 Speaker 2: parts of the brain in favor of a disproportionately large 107 00:07:11,600 --> 00:07:15,320 Speaker 2: visual cortex, which is still small but enough to take 108 00:07:15,360 --> 00:07:18,360 Speaker 2: in the visual data from those giant eyeballs, which are 109 00:07:18,400 --> 00:07:22,680 Speaker 2: designed to see at night for feeding on nocturnal insects. 110 00:07:22,680 --> 00:07:26,240 Speaker 2: Speaking of nocturnal insects, they have managed to develop a 111 00:07:26,360 --> 00:07:30,840 Speaker 2: keen night vision despite often having small eyes and small brains. 112 00:07:31,240 --> 00:07:35,040 Speaker 2: They manage this with clever trade offs. Instead of seeing clear, 113 00:07:35,200 --> 00:07:39,760 Speaker 2: crisp images like we do, they see very slow course 114 00:07:39,800 --> 00:07:44,960 Speaker 2: images with high contrast. So this allows them to react 115 00:07:45,000 --> 00:07:48,080 Speaker 2: to threats at in the night in the darkness, or 116 00:07:48,120 --> 00:07:51,160 Speaker 2: to find mates while everything kind of looks like an 117 00:07:51,240 --> 00:07:55,160 Speaker 2: overexposed black and white image that has been repeatedly compressed 118 00:07:55,240 --> 00:07:59,280 Speaker 2: until it's a grainy bunch of pixels moving in sort 119 00:07:59,320 --> 00:08:05,680 Speaker 2: of delay slow motion. Other insects have very different visual experiences. 120 00:08:05,920 --> 00:08:08,680 Speaker 2: Fruit Flies have eyes and brains that work together to 121 00:08:08,720 --> 00:08:12,480 Speaker 2: allow for very rapid responses to visual information with sharp 122 00:08:12,600 --> 00:08:16,960 Speaker 2: crisp edges, so kind of quite different from these nocturnal insects. 123 00:08:17,240 --> 00:08:20,920 Speaker 2: Many insects see colors that we can't perceive, like those 124 00:08:21,080 --> 00:08:24,080 Speaker 2: in the ultraviolet range, which allow them to zero in 125 00:08:24,120 --> 00:08:27,960 Speaker 2: on flowers who signal to them with secret colorful runways 126 00:08:27,960 --> 00:08:32,959 Speaker 2: to aid in pollination. And this is the case for dragonflies, 127 00:08:32,960 --> 00:08:36,439 Speaker 2: who can either be pollinators, they can also be predators, 128 00:08:37,240 --> 00:08:41,920 Speaker 2: but they have those big, impressive compound eyes. Compound eyes 129 00:08:41,920 --> 00:08:45,559 Speaker 2: are made up of a bunch of distinct units called omatidia, 130 00:08:45,960 --> 00:08:49,520 Speaker 2: which each one comes with a lens, a cornea, and 131 00:08:49,679 --> 00:08:55,000 Speaker 2: photoreceptive cells. So they are these like individual units of vision. 132 00:08:55,200 --> 00:08:58,040 Speaker 2: Whereas you compare it to our e we have one lens, 133 00:08:58,600 --> 00:09:01,040 Speaker 2: one cornea, and then a now with a bunch of 134 00:09:01,120 --> 00:09:04,320 Speaker 2: photoreceptive cells at the back. They have just like a 135 00:09:04,400 --> 00:09:07,360 Speaker 2: bunch of these units. Each one has a lens, in 136 00:09:07,400 --> 00:09:11,840 Speaker 2: acornea and photoreceptive cells. There can be tens of thousands 137 00:09:11,920 --> 00:09:15,600 Speaker 2: of these on a single eye. Different insects have different 138 00:09:15,600 --> 00:09:18,760 Speaker 2: ways in which these compound eyes are connected to the brain, 139 00:09:19,440 --> 00:09:23,080 Speaker 2: different methods of resolving the mass of tens of thousands 140 00:09:23,120 --> 00:09:28,320 Speaker 2: of single units of information. Sometimes individual units are clustered 141 00:09:28,320 --> 00:09:33,640 Speaker 2: together in processing for a more sensitive but lower resolution image. 142 00:09:34,120 --> 00:09:37,360 Speaker 2: Others are more complex with an increase in neural wiring 143 00:09:37,559 --> 00:09:42,400 Speaker 2: for higher resolution and still sensitive vision. The reason not 144 00:09:42,559 --> 00:09:47,920 Speaker 2: all the eyes maximize resolution and sensitivity is because this 145 00:09:48,000 --> 00:09:52,319 Speaker 2: precise wiring is a higher neural load, so some insects 146 00:09:52,360 --> 00:09:55,360 Speaker 2: will trade off for less neural processing for a lower 147 00:09:55,440 --> 00:10:01,679 Speaker 2: resolution image whatever is needed most for survival. Dragonflies specifically 148 00:10:01,720 --> 00:10:05,240 Speaker 2: have eyes that are highly sensitive to color, even more 149 00:10:05,280 --> 00:10:08,400 Speaker 2: so than human eyes. They also have three hundred and 150 00:10:08,440 --> 00:10:12,319 Speaker 2: sixty degree vision with about two hundred images per second, 151 00:10:12,840 --> 00:10:16,559 Speaker 2: meaning that they see in bullet time, basically slow motion. 152 00:10:18,200 --> 00:10:21,840 Speaker 2: Most of their brain is dedicated to visual processing, like 153 00:10:21,920 --> 00:10:25,360 Speaker 2: eighty percent of their brain, so they see a highly 154 00:10:25,480 --> 00:10:31,520 Speaker 2: colorful world with ultraviolet and polarized light. It maybe being 155 00:10:31,760 --> 00:10:34,120 Speaker 2: a dragonfly would sort of be like taking in a 156 00:10:34,160 --> 00:10:38,960 Speaker 2: slow motion movie at an IMAX theater that's really brightly 157 00:10:39,080 --> 00:10:43,040 Speaker 2: colored all around you. But again, it's kind of hard 158 00:10:43,040 --> 00:10:45,360 Speaker 2: to say how they actually experience this, right, Like, we 159 00:10:45,400 --> 00:10:49,319 Speaker 2: can't avatar into a dragonfly brain. We've got our human 160 00:10:49,360 --> 00:10:52,800 Speaker 2: brains with our human feelings and thoughts about what we 161 00:10:52,920 --> 00:10:56,480 Speaker 2: see in our visions, so it's very hard to know 162 00:10:56,559 --> 00:10:59,840 Speaker 2: what they actually experience, but we can kind of say 163 00:11:00,320 --> 00:11:03,800 Speaker 2: this is what the information that is reaching their brain 164 00:11:04,240 --> 00:11:09,240 Speaker 2: is very interesting, A very different way of viewing the world. 165 00:11:09,360 --> 00:11:13,360 Speaker 2: Sounds very trippy. Onto the next listener question. Hi, Katie. 166 00:11:13,400 --> 00:11:16,320 Speaker 2: After the first rain of the season, ants began appearing 167 00:11:16,360 --> 00:11:20,200 Speaker 2: in my house. Luckily, I have indoor ant traps, so 168 00:11:20,360 --> 00:11:26,000 Speaker 2: I am not expecting any ant ant ant mageddon happening. However, 169 00:11:26,120 --> 00:11:29,280 Speaker 2: as I was observing the hapless creatures harvesting the poison 170 00:11:29,320 --> 00:11:31,240 Speaker 2: in the ant trap, I began to wonder would the 171 00:11:31,240 --> 00:11:34,880 Speaker 2: colony ever evolve to become aware of the man made poison, 172 00:11:35,320 --> 00:11:37,559 Speaker 2: like how some species of ants are aware if one 173 00:11:37,559 --> 00:11:40,839 Speaker 2: of their own is carrying the Cordyceps spores and would 174 00:11:40,840 --> 00:11:43,560 Speaker 2: take action to get rid of the infected ant. The 175 00:11:43,600 --> 00:11:45,520 Speaker 2: ant traps are designed so the ant would carry the 176 00:11:45,559 --> 00:11:48,600 Speaker 2: poison back to the nest and henceforth killing the whole 177 00:11:48,640 --> 00:11:51,920 Speaker 2: colony by sharing the poisonous food. At this point, I'm 178 00:11:52,040 --> 00:11:53,680 Speaker 2: at the edge of a rabbit hole that I'm hoping 179 00:11:53,720 --> 00:11:56,240 Speaker 2: not to fall into because I started reading the ingredients 180 00:11:56,240 --> 00:11:58,320 Speaker 2: of the ant trap, which is point zero one percent 181 00:11:58,360 --> 00:12:01,680 Speaker 2: avermect and B and ninety nine percent sent other ingredients 182 00:12:01,679 --> 00:12:04,760 Speaker 2: and I definitely don't know what any of that really means. Anyways, 183 00:12:05,080 --> 00:12:06,679 Speaker 2: I would love to hear your thoughts before I get 184 00:12:06,679 --> 00:12:11,000 Speaker 2: too carried away. Thanks Jessec Hi Jesse, this is an 185 00:12:11,040 --> 00:12:16,920 Speaker 2: amazing question. First, let me just give some context. She mentions. First, 186 00:12:17,040 --> 00:12:21,920 Speaker 2: let me give some context. Courtceps are mentioned. The courdyceps 187 00:12:21,920 --> 00:12:26,679 Speaker 2: are spores of a fungus that can infect various arthropods, 188 00:12:26,720 --> 00:12:31,680 Speaker 2: including ants, and so ants have learned to identify an 189 00:12:31,720 --> 00:12:34,559 Speaker 2: infected individual and carry them far away from the colony 190 00:12:34,679 --> 00:12:37,120 Speaker 2: so they don't infect the rest of the colony. So 191 00:12:37,440 --> 00:12:42,080 Speaker 2: there are two ways ants might thwart threats or poison 192 00:12:42,880 --> 00:12:47,640 Speaker 2: evolution or learning. So evolution is a very slow process 193 00:12:47,640 --> 00:12:51,400 Speaker 2: over many hundreds thousands, hundreds of thousands, or even millions 194 00:12:51,440 --> 00:12:56,160 Speaker 2: of years. So for ants to develop an innate instinctive 195 00:12:56,200 --> 00:13:00,480 Speaker 2: behavior towards, say, human ant bait traps, we would probably 196 00:13:00,520 --> 00:13:03,880 Speaker 2: need to co evolve with them for quite a while, 197 00:13:04,200 --> 00:13:08,680 Speaker 2: but it would be possible. Some evolutionary traits already seem 198 00:13:08,720 --> 00:13:13,560 Speaker 2: to act as potential protection against poisoning. So some ant 199 00:13:13,600 --> 00:13:18,480 Speaker 2: species have worker ants that act as living larders. These 200 00:13:18,480 --> 00:13:22,440 Speaker 2: are usually older workers who consume some food source and 201 00:13:22,480 --> 00:13:24,800 Speaker 2: just kind of stand around and offer it to other 202 00:13:24,880 --> 00:13:28,880 Speaker 2: ants via regurgitation, kind of like a living vending machine. 203 00:13:29,760 --> 00:13:34,160 Speaker 2: This could potentially help dilute toxins or simply kill off 204 00:13:34,240 --> 00:13:39,319 Speaker 2: the ant that has ingested all of these toxins, and 205 00:13:39,840 --> 00:13:44,760 Speaker 2: so it may act as a kind of buffer between 206 00:13:44,880 --> 00:13:49,400 Speaker 2: these ants that have these sort of living larger members 207 00:13:49,480 --> 00:13:51,640 Speaker 2: of the colony eating a bunch of food and then 208 00:13:51,960 --> 00:13:55,360 Speaker 2: offering it to other workers after it's already been diluted 209 00:13:55,400 --> 00:13:58,760 Speaker 2: in its gut. But it's not a strategy that has 210 00:13:58,760 --> 00:14:03,040 Speaker 2: evolved specifically for ant traps or ant poison or toxins, 211 00:14:03,080 --> 00:14:06,600 Speaker 2: but it may be a separate benefit. This is a 212 00:14:06,640 --> 00:14:11,800 Speaker 2: behavior that's evaulved for things like surviving famine, for economizing 213 00:14:12,240 --> 00:14:15,400 Speaker 2: food gathering, things like that, but it could have the 214 00:14:15,440 --> 00:14:20,360 Speaker 2: impact of helping them survive human traps. But ants do 215 00:14:20,760 --> 00:14:25,640 Speaker 2: have the capacity to learn, particularly as a colony, and 216 00:14:25,760 --> 00:14:28,800 Speaker 2: this is a faster process than evolution. You can have 217 00:14:28,840 --> 00:14:35,120 Speaker 2: a colony adapt to some threat or something within a 218 00:14:35,240 --> 00:14:41,520 Speaker 2: matter of a single generation just by learning. So Argentine 219 00:14:41,600 --> 00:14:44,400 Speaker 2: ants have shown signs that as a colony they are 220 00:14:44,440 --> 00:14:48,160 Speaker 2: capable of learning about poison bait and change their behavior 221 00:14:48,280 --> 00:14:51,960 Speaker 2: in response to it. So the cleverness of ant bait 222 00:14:52,480 --> 00:14:55,440 Speaker 2: is that it has a delayed response, so the ant 223 00:14:55,480 --> 00:14:59,640 Speaker 2: eats it, it doesn't immediately die, which gives it time 224 00:14:59,720 --> 00:15:03,600 Speaker 2: to you lay down pheromone trails to alert other ants 225 00:15:03,640 --> 00:15:06,560 Speaker 2: about what seems like tasty food. Bring it back to 226 00:15:06,640 --> 00:15:09,040 Speaker 2: the colony. All these ants come and they gather a 227 00:15:09,040 --> 00:15:12,120 Speaker 2: bunch of it, bring it back. Still hasn't killed them yet, 228 00:15:12,400 --> 00:15:14,720 Speaker 2: and then finally it starts to set in and kill 229 00:15:14,800 --> 00:15:19,600 Speaker 2: them off. And by then, you know, hopefully for you 230 00:15:19,680 --> 00:15:22,880 Speaker 2: and sadly for the ants, it's too late. They've already 231 00:15:22,920 --> 00:15:25,280 Speaker 2: brought it in and so a lot of them die. 232 00:15:27,120 --> 00:15:30,160 Speaker 2: But yeah, so this is very insidious. It's a very 233 00:15:30,200 --> 00:15:34,120 Speaker 2: clever way to kill ants. But researchers have found that 234 00:15:34,240 --> 00:15:37,800 Speaker 2: argentine ants, which are one of the most common ant 235 00:15:37,840 --> 00:15:43,240 Speaker 2: species in the world, they are highly invasive, incredibly durable, 236 00:15:43,920 --> 00:15:46,120 Speaker 2: really hard to get rid of if you've ever had 237 00:15:46,120 --> 00:15:49,520 Speaker 2: an argentine ant invasion. So this might be one reason 238 00:15:49,560 --> 00:15:54,120 Speaker 2: why so argentine ants seem to be able to learn 239 00:15:54,200 --> 00:16:01,040 Speaker 2: to abandon toxic food sources and human beita traps. So 240 00:16:02,080 --> 00:16:05,640 Speaker 2: one of the studies authors that was looking into this 241 00:16:05,800 --> 00:16:13,320 Speaker 2: Argentina ant behavior entomologist Roxanna Johnson's happened upon this when 242 00:16:13,440 --> 00:16:16,640 Speaker 2: she was trying to help a pediatric hospital get rid 243 00:16:16,680 --> 00:16:20,160 Speaker 2: of their Argentine ant problem with baited traps and noticed 244 00:16:20,680 --> 00:16:24,440 Speaker 2: that the ants simply abandoned the traps without poisoning the 245 00:16:24,480 --> 00:16:28,480 Speaker 2: whole colony. So she got some argentine ants, put them 246 00:16:28,480 --> 00:16:31,480 Speaker 2: in the lab, offered out some food sources, some that 247 00:16:31,640 --> 00:16:34,360 Speaker 2: was just benign sugar water and some that had boric 248 00:16:34,400 --> 00:16:38,120 Speaker 2: acid in it, which is an ingredient that's found in 249 00:16:38,360 --> 00:16:45,440 Speaker 2: these ant ant traps or ant poison baits. And so 250 00:16:45,600 --> 00:16:50,600 Speaker 2: what they found is that these ants learned to abandon 251 00:16:51,040 --> 00:16:57,720 Speaker 2: the poisoned bait after about six hours, and in fact 252 00:16:57,920 --> 00:17:03,680 Speaker 2: they had not managed to consume enough of it and 253 00:17:03,720 --> 00:17:06,639 Speaker 2: bring back enough of it to destroy the rest of 254 00:17:06,680 --> 00:17:09,680 Speaker 2: the ants. Of a few individual died, but not the 255 00:17:09,840 --> 00:17:15,880 Speaker 2: entire laboratory colony. So the interesting thing is, we don't 256 00:17:15,920 --> 00:17:19,640 Speaker 2: know how they know how to do this. So clearly 257 00:17:19,680 --> 00:17:24,480 Speaker 2: there is some sort of algorithm happening where the ants 258 00:17:24,720 --> 00:17:27,520 Speaker 2: go to the tainted food less and less and the 259 00:17:27,560 --> 00:17:32,119 Speaker 2: pheromone trail weekends, whereas it strengthens for the food source 260 00:17:32,160 --> 00:17:36,400 Speaker 2: that's safe but the researchers don't know how they're determining 261 00:17:37,640 --> 00:17:42,439 Speaker 2: the tainted food source is unsafe. So still plenty of 262 00:17:42,440 --> 00:17:44,760 Speaker 2: research that needs to be done on how these ants 263 00:17:44,800 --> 00:17:48,560 Speaker 2: are learning to avoid the ant bait. But we know 264 00:17:48,840 --> 00:17:51,879 Speaker 2: that at least argentine ants and possibly other species of 265 00:17:51,920 --> 00:17:55,399 Speaker 2: ants do have strategies to counter it and can learn 266 00:17:55,960 --> 00:18:00,760 Speaker 2: to avoid it. So yeah, so that is I would 267 00:18:00,800 --> 00:18:04,440 Speaker 2: say learning is something that is it's not quite evolving 268 00:18:05,640 --> 00:18:09,600 Speaker 2: to counter a threat, because evolution, that's that's a longer 269 00:18:09,680 --> 00:18:15,679 Speaker 2: process that implies a fundamental intrinsic sort of change in 270 00:18:15,720 --> 00:18:21,680 Speaker 2: the ants biology and species. But learning is of course 271 00:18:22,080 --> 00:18:27,080 Speaker 2: something that's really really interesting, and you could absolutely have 272 00:18:27,240 --> 00:18:32,480 Speaker 2: ants eventually adapt and evolve to counter ant poison human 273 00:18:32,760 --> 00:18:35,639 Speaker 2: made ant poison if it is, oh, if we co 274 00:18:35,720 --> 00:18:42,200 Speaker 2: evolve with them for long enough. All right on to 275 00:18:42,560 --> 00:18:47,320 Speaker 2: the next listener question. Hi, Katie and or whomever reads this. 276 00:18:47,480 --> 00:18:49,439 Speaker 2: It was me and my dog, that's who read it. 277 00:18:49,640 --> 00:18:52,240 Speaker 2: I was recently listening to the episode with Janet Varney 278 00:18:52,280 --> 00:18:57,480 Speaker 2: where you discussed bugs as alternative food sources and invasive 279 00:18:57,520 --> 00:19:00,520 Speaker 2: species from the pet trade. I always want wondering if 280 00:19:00,560 --> 00:19:03,919 Speaker 2: there have been any studies about the impact of industrial 281 00:19:04,000 --> 00:19:07,480 Speaker 2: bug farming. You discussed animals from the pet trade becoming 282 00:19:07,520 --> 00:19:10,720 Speaker 2: issues in an ecosystem. I guess I have several questions. 283 00:19:10,800 --> 00:19:14,000 Speaker 2: Is there an industrial bug farm, what does it look like? 284 00:19:14,119 --> 00:19:16,880 Speaker 2: And could a breach cause harmful spikes in a population 285 00:19:17,080 --> 00:19:20,800 Speaker 2: to the flora and fauna. Thank you, Laura, Hi Laura, 286 00:19:20,920 --> 00:19:25,120 Speaker 2: this is a fantastic question. I actually do know someone 287 00:19:25,200 --> 00:19:28,880 Speaker 2: who researches crickets and has poked around cricket farms where 288 00:19:28,920 --> 00:19:31,679 Speaker 2: they're raised as food. I'll try to get her on 289 00:19:31,720 --> 00:19:34,879 Speaker 2: the show someday to talk more about both crickets and 290 00:19:34,920 --> 00:19:38,040 Speaker 2: her experience checking out the cricket farm. So, in answer 291 00:19:38,080 --> 00:19:41,480 Speaker 2: to your question, could is there this threat of insects 292 00:19:41,560 --> 00:19:46,040 Speaker 2: being invasive if you're doing an insect farm? Absolutely yes, 293 00:19:46,240 --> 00:19:51,240 Speaker 2: So all farm animals and plants can become invasive, and 294 00:19:51,320 --> 00:19:56,120 Speaker 2: this could be absolutely true of insects already. There are 295 00:19:56,440 --> 00:19:59,840 Speaker 2: insect farms, some used as food, like crickets being turned 296 00:19:59,880 --> 00:20:04,280 Speaker 2: in into cricket meal or meal worms being turned into meal. 297 00:20:04,720 --> 00:20:09,160 Speaker 2: Some farms use them as animal feed rather than human feed. 298 00:20:09,359 --> 00:20:13,399 Speaker 2: Some farms use maggots like black fly larvae to break 299 00:20:13,440 --> 00:20:18,760 Speaker 2: down food waste into frass, which is a nicer term 300 00:20:18,840 --> 00:20:21,920 Speaker 2: for maggot poop that can then be used as a fertilizer. 301 00:20:22,240 --> 00:20:26,800 Speaker 2: So we do already have bug farms, but a large 302 00:20:27,280 --> 00:20:31,480 Speaker 2: bug farming industry doesn't really exist yet, not in the 303 00:20:31,480 --> 00:20:37,160 Speaker 2: way that other industrial farms exist. So as you probably 304 00:20:37,600 --> 00:20:42,040 Speaker 2: kind of instinctively understand, like, insects are very prolific, they're tiny, 305 00:20:42,320 --> 00:20:47,680 Speaker 2: they're perfect candidates for becoming an invasive species. So they 306 00:20:47,720 --> 00:20:51,680 Speaker 2: often become invasive just by hitching a ride in cargo 307 00:20:51,840 --> 00:20:55,480 Speaker 2: and accidentally getting dropped off somewhere they don't belong. And 308 00:20:55,520 --> 00:20:59,760 Speaker 2: they're so fecunned, they produce so much so many offspring, 309 00:21:00,840 --> 00:21:05,760 Speaker 2: and they are highly adaptable typically that they're great at 310 00:21:05,960 --> 00:21:10,639 Speaker 2: being invasive species. So a farm where you have a 311 00:21:10,680 --> 00:21:14,199 Speaker 2: bunch of insects, potentially insects that have been selectively bred 312 00:21:14,440 --> 00:21:21,400 Speaker 2: to endure harsh conditions or to breed more prolifically, Yeah, 313 00:21:21,400 --> 00:21:24,600 Speaker 2: that would be a prime spot for there to be 314 00:21:24,840 --> 00:21:30,960 Speaker 2: an invasive event, right, that could certainly pose a risk. 315 00:21:32,280 --> 00:21:35,159 Speaker 2: In fact, we kind of already see that. We have 316 00:21:35,200 --> 00:21:38,000 Speaker 2: a big example of that, which is honey bees. So 317 00:21:38,119 --> 00:21:41,119 Speaker 2: honey bees, as cute and wonderful as they are, they 318 00:21:41,119 --> 00:21:45,879 Speaker 2: are not native to the Americas. We imported them to 319 00:21:46,119 --> 00:21:49,840 Speaker 2: make honey for us, for farms and to pollinate crops. 320 00:21:50,359 --> 00:21:54,320 Speaker 2: The problem is that they can actually out compete native 321 00:21:54,359 --> 00:21:57,560 Speaker 2: species of bees, which can both be harmful to the 322 00:21:57,760 --> 00:22:01,639 Speaker 2: native bees themselves and also to the plants and the 323 00:22:01,680 --> 00:22:06,040 Speaker 2: flowers that the native bees pollinate. Because you don't always 324 00:22:06,240 --> 00:22:10,359 Speaker 2: just replace one pollinator with another, you can have a 325 00:22:10,400 --> 00:22:14,560 Speaker 2: really specific relationship between say a wildflower, and a native 326 00:22:14,600 --> 00:22:18,520 Speaker 2: species of bees who have co evolved with a wildflower, 327 00:22:18,560 --> 00:22:23,280 Speaker 2: and they are a specific size, exhibit a specific behavior 328 00:22:23,680 --> 00:22:27,200 Speaker 2: that the flower has co evolved with, and so their 329 00:22:27,240 --> 00:22:31,800 Speaker 2: whole pollination structure is based on this species of bee 330 00:22:32,640 --> 00:22:35,280 Speaker 2: and not necessarily based on the behavior of a honeybe. 331 00:22:35,800 --> 00:22:40,520 Speaker 2: So you could, if you say, threaten a species of 332 00:22:40,600 --> 00:22:43,199 Speaker 2: native bees because the honey bees are outcompeting them. You 333 00:22:43,200 --> 00:22:48,000 Speaker 2: could also threaten native plants as well. So honey bees, 334 00:22:48,400 --> 00:22:50,160 Speaker 2: I mean, I love them, right, and I love honey, 335 00:22:50,200 --> 00:22:54,040 Speaker 2: but yeah, they are actually an example of what you're 336 00:22:54,040 --> 00:22:57,920 Speaker 2: talking about. Bees that are used in large scale farming 337 00:22:58,960 --> 00:23:02,560 Speaker 2: who have become invain because you can't really how do 338 00:23:02,560 --> 00:23:04,639 Speaker 2: you keep how do you keep a honey bee in 339 00:23:04,680 --> 00:23:09,040 Speaker 2: a cage? You don't they go around, and yeah, they 340 00:23:09,080 --> 00:23:14,520 Speaker 2: have caused issues for the environment. Also, Laura, your question 341 00:23:15,000 --> 00:23:19,200 Speaker 2: is so important. It is actually being asked by ecologists 342 00:23:20,280 --> 00:23:24,840 Speaker 2: now as we're having more and more of these discussions 343 00:23:24,920 --> 00:23:31,720 Speaker 2: and sort of proposals for having industrial scale insect farms. 344 00:23:31,760 --> 00:23:36,280 Speaker 2: So the ideas that insects are more ecologically friendly because 345 00:23:36,440 --> 00:23:43,680 Speaker 2: the sort of feed to waste to protein output ratios 346 00:23:43,760 --> 00:23:47,280 Speaker 2: are much better than say a beef farm. So like 347 00:23:47,400 --> 00:23:52,160 Speaker 2: cows are pretty wasteful when you consider sort of their 348 00:23:52,240 --> 00:23:54,960 Speaker 2: waste and the amount of energy you have to put 349 00:23:55,000 --> 00:23:59,800 Speaker 2: in per unit of cow meat, whereas insects are a 350 00:23:59,800 --> 00:24:05,159 Speaker 2: lot more efficient in that respect. But there are a 351 00:24:05,160 --> 00:24:08,080 Speaker 2: lot of questions that ecologists are raising because we don't 352 00:24:08,119 --> 00:24:13,840 Speaker 2: actually have these large scale industrial bug farms that are 353 00:24:14,520 --> 00:24:17,960 Speaker 2: similar in scale to other types of industrial farms that 354 00:24:18,000 --> 00:24:22,479 Speaker 2: we have currently. So there is an article in Trends 355 00:24:22,480 --> 00:24:27,600 Speaker 2: and Ecology and Evolution called Approaching Ecological Sustainability in the 356 00:24:27,640 --> 00:24:36,320 Speaker 2: Emerging Insects as Food Industry. So your question is essentially 357 00:24:36,359 --> 00:24:41,000 Speaker 2: the subject of this paper by concerned ecologists who are 358 00:24:41,320 --> 00:24:44,879 Speaker 2: asking the same questions as you and pointing out a 359 00:24:45,000 --> 00:24:48,080 Speaker 2: lack of research on the risk factors of large scale 360 00:24:48,119 --> 00:24:53,720 Speaker 2: insects farms and the many unknowns of environmental impacts of 361 00:24:53,760 --> 00:24:56,199 Speaker 2: insects farms. One of the points they bring up is 362 00:24:56,240 --> 00:25:00,480 Speaker 2: the invasiveness aspect, the fact that these insects could get out, 363 00:25:00,560 --> 00:25:03,720 Speaker 2: that these could be heartier than native species because we 364 00:25:03,800 --> 00:25:06,679 Speaker 2: might breed them that way, and that they could cause 365 00:25:07,680 --> 00:25:14,919 Speaker 2: destruction to the local ecology. And there's also other questions 366 00:25:14,960 --> 00:25:17,640 Speaker 2: like even though we do know that they're more efficient 367 00:25:17,640 --> 00:25:21,919 Speaker 2: in terms of like feed in protein out, there's not 368 00:25:22,119 --> 00:25:24,600 Speaker 2: a lot of data on how you actually how do 369 00:25:24,640 --> 00:25:28,239 Speaker 2: you house that many insects? Right, Like I do know 370 00:25:28,280 --> 00:25:34,000 Speaker 2: from my friend the one he studies crickets that answers 371 00:25:34,080 --> 00:25:38,040 Speaker 2: are very sensitive to things like heat, so in temperature, 372 00:25:38,200 --> 00:25:40,879 Speaker 2: so you have to you might have to have really 373 00:25:40,920 --> 00:25:46,040 Speaker 2: specific temperature controls for that many insects, both to make 374 00:25:46,080 --> 00:25:49,760 Speaker 2: sure that they're eating and breeding and growing things like that. 375 00:25:50,960 --> 00:25:54,520 Speaker 2: So also you know, just like how do you how 376 00:25:54,560 --> 00:25:59,320 Speaker 2: do you prevent there from being say like disease that 377 00:25:59,400 --> 00:26:02,719 Speaker 2: wipes out all of the insects. All sorts of questions 378 00:26:03,160 --> 00:26:06,679 Speaker 2: in terms of how sustainable would they be and what 379 00:26:06,720 --> 00:26:09,639 Speaker 2: are the risks to the environment that we don't really know. 380 00:26:09,920 --> 00:26:13,360 Speaker 2: I mean, I would still say that it's very promising, right, 381 00:26:13,520 --> 00:26:17,919 Speaker 2: like the I think it's something that is worth looking 382 00:26:17,960 --> 00:26:23,000 Speaker 2: into because our current industrial farming situation is not good. 383 00:26:23,600 --> 00:26:26,480 Speaker 2: You know, it's not it is bad for the environment. 384 00:26:26,920 --> 00:26:33,400 Speaker 2: It tends to be very wasteful. Also, you know, there's 385 00:26:33,480 --> 00:26:36,680 Speaker 2: a lot of ethical concerns in terms of the treatment 386 00:26:36,720 --> 00:26:42,560 Speaker 2: of animals. So you know, I think having insects as 387 00:26:42,600 --> 00:26:45,399 Speaker 2: a potential alternative food source and looking into it is 388 00:26:45,760 --> 00:26:49,320 Speaker 2: really important. But it's also not something to just be 389 00:26:49,440 --> 00:26:54,240 Speaker 2: done without actually considering things that you've brought up, like 390 00:26:54,320 --> 00:26:57,879 Speaker 2: the invasiveness aspect and what are the what are the 391 00:26:57,920 --> 00:27:03,199 Speaker 2: other potential implications of an industrial sized insect form and 392 00:27:03,240 --> 00:27:08,360 Speaker 2: it's an impact on the environment. So fantastic question. Uh, 393 00:27:08,440 --> 00:27:12,240 Speaker 2: you could you could? You could be an ecologist because 394 00:27:12,280 --> 00:27:16,760 Speaker 2: you're asking the very questions that they are asking. H Well, 395 00:27:16,800 --> 00:27:20,040 Speaker 2: thank you guys so much for your extremely thoughtful and 396 00:27:20,200 --> 00:27:24,359 Speaker 2: intelligent questions. I always enjoy them. It makes me do 397 00:27:24,480 --> 00:27:27,080 Speaker 2: a little bit of homework that I really like to 398 00:27:27,119 --> 00:27:30,440 Speaker 2: do because it keeps me sort of I guess, more 399 00:27:30,520 --> 00:27:34,080 Speaker 2: up to date with uh, with research and stuff that 400 00:27:34,720 --> 00:27:37,560 Speaker 2: I might not think to look into, but you guys do, 401 00:27:37,640 --> 00:27:40,439 Speaker 2: and so I look into it and it's great. We 402 00:27:40,520 --> 00:27:43,760 Speaker 2: all learn. We're all learning together. If you want to 403 00:27:43,800 --> 00:27:45,280 Speaker 2: send me a question, you can write to me at 404 00:27:45,320 --> 00:27:50,000 Speaker 2: Creature Future pod at gmail dot com. Thank you, guys 405 00:27:50,040 --> 00:27:55,200 Speaker 2: so much for listening, and thank you to the Space 406 00:27:55,240 --> 00:27:59,080 Speaker 2: Classics for their super awesome song Exolumina. Creature features a 407 00:27:59,080 --> 00:28:02,280 Speaker 2: production of iHeart Radio. For more podcasts like the one 408 00:28:02,320 --> 00:28:05,560 Speaker 2: you just heard, visit the iHeartRadio app Apple Podcasts, or Hey, 409 00:28:05,600 --> 00:28:08,640 Speaker 2: guess what wherever you listen to your favorite shows. I'm 410 00:28:08,680 --> 00:28:10,920 Speaker 2: not your mother. I can't tell you what to do, 411 00:28:11,920 --> 00:28:15,600 Speaker 2: but yeah, before starting a cricket farm with a bunch 412 00:28:15,640 --> 00:28:20,560 Speaker 2: of mutated super crickets, do think about whether they will 413 00:28:20,600 --> 00:28:26,800 Speaker 2: take control of your local government and install a cricket autocracy. 414 00:28:27,760 --> 00:28:30,320 Speaker 2: You know, consider it. See you next Wednesday.