What we can learn from squabbling bats

Egyptian fruit bat, Rousettus aegyptiacus. Photo by Eran Levin.

This week's paper is in Scientific Reports and comes from Yossi Yovel's group at Tel Aviv University, lead authored by Yosef Prat. If you have spent any time around bats, you are well aware that they do a lot of chattering. The Yovel group tackled the question of what is all that chattering about? To do this they video and audio recorded the behavior of 7 female Egyptian fruit bats, Rousettus aegyptiacus, (in a group of 22) over 75 days, totaling almost 15,000 individual vocalizations. They then used a machine learning approach to assess variation and information in bat calls. They were able to identify calling individuals with 71% accuracy, indicating that bats have enough variation in their calls to tell them apart. Now it starts to get really cool. Not only could the machine learning identify which individuals were calling, it could also detect differences in whom they were addressing. That is bats make slightly different calls when they are addressing different bats. Some of this variation is due to sex, they make different calls when they are talking to males versus to females, but also they are making slightly different calls when talking to different individuals within a sex. This means that an eavesdropping bat could potentially tell not only which bat is talking, but also which bat they are addressing. What the authors don't clarify is how repeatable these individual differences are across vocalizing bats. That is, are all of the bats referring to an individual using particularly vocal variants, like a name? Or do different bats use slightly different "names" for each of their roostmates? The authors notes that there was one bat who did not vary in their vocalizations depending on whom they were addressing. That one jerk who is yelling indiscriminately at everybody. 

The authors then looked at the contexts in which bats were making vocalizations and showed that bats make different calls in different types of arguments (apparently Egyptian fruit bats mostly argue). The vocalizations they make are different when squabbling about food, or sleep space, or when somebody is making unwelcome sexual advances. The authors are also able to predict from the vocalizations what the outcome of the squabble will be. It would be great to know more about this, are the calls of the bats who win the squabbles louder, deeper, more chaotic?

Regardless of my desire for more detail, this shows how much can be gained just from making lots and lots of careful observations.

Tradeoffs between learning and memory in mountain chickadees

Mountain chickadee, Poecile gambeli. Photo by Nick Athanas.

This week's paper is in Animal Behaviour and comes out of the Pravosudov lab at the University of Nevada at Reno, lead authored by Rebecca Croston. Mountain chickadees, Poecile gambeli, live in the Western USA and Canada where they occur from low elevations up into the Sierras. Previous research from the Pravosudov lab has shown that the high elevation chickadees (which experience harsher climates) have better spatial memory and larger hippocampi (the brain region associated with spatial memory), than low elevation chickadees. This is thought to be because high elevation chickadees must cache more food to make it through the winter, and therefore they must have better spatial memory to locate all those food caches. In this particular paper the authors examined the "cognitive flexibility" of high and low elevation chickadees. Chickadees were captured in the field and fitted with individual PIT tags. These PIT tags were registered by feeder boxes that identified and recorded the bird that landed, and determined whether that individual is allowed access to food. (As a side note, this PIT tag and feeder technology is such a cool way that field research on animal behavior is being transformed right now!) The authors put arrays of 8 feeder boxes out in the field, and chickadees only got food when they landed on their assigned "correct" box. They therefore couldn't follow each other to the correct feeder box, because the PIT tag system assigned the correct box to be different for each bird. After a bird learned the correct box, it was then tested for behavioral flexibility using a reversal task, in that the "correct" box was changed to a different box in the array.

The authors found that high and low elevation chickadees performed equally on the initial learning task (which is contrary to their previous reported results that high elevation chickadees perform better at spatial learning tasks), and high elevation chickadees are much worse at the reversal learning task. The authors suggest that selection for spatial memory abilities and the associated larger hippocampi, may be a trade-off with cognitive flexibility. Perhaps the high elevation birds are really good at remembering initial food cache locations, but this limits their ability to learn novel caches. I don't know that I buy this. The authors say that it was a harsher year than other years, as a potential explanation for the lack of a difference in initial learning between high and low elevation chickadees, which is incongruous with their previous research. It seems possible to me that this reduced reversal learning is also a consequence of some other factor. The concept that selection for memory may limit flexibility is, however, interesting. I hope the Pravosudov lab pursues this further to really pull apart what factors are at play. 

Associative Learning in Plants

Pea plant, Pisum sativum. Ink and watercolor by W. Giglioli. Hulton Fine Art Collection

Yes. That's right. You heard me. LEARNING IN PLANTS! And not just in some crazy special plant, but in the lowly garden pea! Although everybody else is talking about the feathery baby dinosaur tail discovered preserved in amber, I just desperately need to talk about learning in plants.  The paper is in Nature Scientific Reports led by Monica Gagliano from the University of Western Australia.

But first let's talk about learning in general. In animal behavior there are two categories of learning: associative learning, and non-associative learning. Associative learning is the formation of an association between a stimulus to which you previously had no response (called the conditioned stimulus, or CS) and a stimulus to which you have an innate response (the unconditioned stimulus, or US). The classic example is the work of a Russian physiologist Ivan Pavlov, who together with his assistant, Ivan Tolochinov, developed the concept of associative conditioning in 1901. The Ivans' experiments showed that when you present a dog with a dish of food (the US) they will salivate (called the unconditioned response, or UR). When the presentation of the US is consistently paired with another stimulus, such as a sound (apocryphally the ringing of a bell in the Ivans' experiments, the CS), eventually the dogs will salivate at the sound of the bell. They have formed an association. Non-associative learning includes other forms of learning such as habituation and sensitization. Habituation is when an animal decreases it's response to a stimulus over repeated exposure (you stop jumping at every firework explosion after listening to them for twenty minutes) and sensitization is an increase in response over repeated exposure. 

A 2014 paper also from Monica Gagliano demonstrated habituation in Mimosa pudica, which is often called "the sensitive plant". When touched, Mimosa folds its leaves down. There is a pretty silly video of people tickling these plants here. It has long been known that if you repeatedly touch a Mimosa plant it will stop responding, which is highly parallel with habituation learning in animals.

But associative learning??! In this new paper Gagliano and colleagues used garden peas, Pisum sativum. The unconditioned response was that plants grow towards light. The conditioned stimulus was the breeze from a fan. They put a little pea seedling in a split PVC pipe y-maze (see below). In one treatment the pea plant would have the fan blow on it from one side of the y-maze for 60 minutes, and then a light would come on on that same side. In a second treatment the fan would blow for 60 minutes on one side and then the light would come on on the opposite side. In both treatments the location of the fan is a predictable indictor of where the light is going to be (the same side as the fan, or the opposite side). They switched the sides that the stimuli were presented on for each training session. To test the plants they just gave them the fan from one side. 

"Figure 1. Training and testing protocol for associative learning in pea seedlings. (A) During training seedlings were exposed to the fan [F] and light [L] on either the same arm (i) or on the opposite arm (ii) of the Y-maze. The fan served as the conditioned stimulus (CS), light as the unconditioned stimulus (US). During testing with exposure to the fan alone two categories of responses were distinguished. Correct response: Seedlings growing into the arm of the maze where the light was “predicted” by the fan to occur [green arrow; iii (corresponding to scenario i) and iv (corresponding to scenario ii)]; Incorrect response: Seedlings growing into the arm of the maze where the light was not “predicted” by the fan to occur (black arrow; iii and iv). (B) Seedlings received training for three consecutive days before testing. Each training day consisted of three 2-h training sessions separated by 1-h intervals. The 90-min CS preceded the 60-min US by 60minutes so that there was a 30-min overlap. (i). During the 1-day testing session, seedlings were exposed to the fan alone for three 90-min sessions (ii). Seedlings of the control group were left undisturbed (no fan, no light; iii)." From Gagliano et al. 2016 .

The majority of plants grew in the direction they had been trained (toward the fan if the fan had been paired with light and away from the fan if the fan had been in the opposite arm from the light).  In a second experiment, Gagliano and colleagues showed that plants are only capable of this associative learning if they are trained during the "day" part of a light/dark cycle. That is, they can only learn to pair light with the fan cue during the time of day when they would normally be exposed to light. 

My mind is a bit boggled by this paper. In particular I am really curious about what the mechanism is. Also I wonder if we need some different vocabulary? I am generally for maintaining simplicity, and I think that using the same vocabulary across diverse systems can highlight interesting comparisons and similarities, but does it make sense to discuss learning, or even behavior, in an animal with no brain or even neurons? 

What do birds hear in bird song?

A female (left) and male (right) zebra finch, Taeniopygia guttata

This week's paper is a review in Animal Behaviour by Robert Dooling and Nora Prior on differences in human and bird perception of birdsong. It is broadly understood that we don't perceive the world and same way that other animals do. It's is hard for us to even wrap our heads around what it would be like to echolocate like a bat, or use electroreception like an electric fish. Even within the senses that are familiar to us, we know that we see flowers differently from bees, and dogs smell all kinds of things that we don't. So what about bird song? Apparently what birds are better at is what Dooling and Prior call "extremely fine temporal processing". In particular, this paper focuses on zebra finches which are the model organism for development and processing of bird song. In one of the studies they discuss Dooling tested "fine temporal processing", by creating artificial stimuli (called Schroeder complexes) composed of repeated harmonics that are either rising or falling. Then they created multiple stimuli in which the time interval between each rising or falling harmonic was shorter and shorter and shorter. Dooling then tested how short the intervals had to be before humans or birds could no longer distinguish the rising from the falling harmonics. 

I really wish that they had provided some audio files of the test stimuli in the supplement, because it is hard for me to grasp how different these positive and negative Schroeder complexes sound. Regardless, Dooling found that at short intervals zebra finches were much much better at distinguishing these two stimuli than humans. This review paper discusses other experiments that also demonstrate superior distinguishing of sounds over very short time intervals in birds compared to humans. These studies indicate that birds are likely able to detect stimuli, or variation in stimuli, in bird song that we simply cannot hear. 

The dung beetle microbiome

The gazelle scarab, Onthophagus gazella, with a dung ball in Victoria, Australia.

Dung beetles are an extraordinarily diverse group of insects, with more than 5,000 species in the subfamily Scarabaeinae. They eat mostly or exclusively dung, and thereby are important ecosystem members. Dung, however, especially the dung of large grazing mammals (which is what dung beetles mostly eat), is not an easy food. It is composed predominantly of the tough cellulose grass bits that have remained undigested even after passing through the multichambered stomachs of grazers. In order to digest this dung, it has long been thought that dung beetles are dependent on the bacteria in their own gut (their microbiota) to break the dung down into the sugars, amino acids, and vitamins that they need. Like many animals, humans included, dung beetles are believed to derive an important component of their microbiota from their mothers. This week's paper, in American Naturalist, examines the importance of maternally derived gut microbiota for dung beetle larval development. 

The gazelle scarab, Onthophagus gazella, is widespread African and Asian dung beetle. It was actually introduced to the US for management of livestock dung in pasture. Female O. gazella, (perhaps named because of their gazelle-like little horns?) tunnel into the ground underneath dung patties where they digs out brood cells, provision each brood cell with a ball of dung, poop, and lay on egg on top of their poop (called a "pedestal"). For clarification here, I am using "poop" to refer to the mother beetle's own feces, and "dung" to refer to the grazing mammal feces. 

Diagram of the brood cells of Onthophagous beetles. "Females lay several brood balls in each tunnel that would all be at the same developmental stage. However, for illustrative purposes all life stages are represented in one tunnel. These stages include the: (A) egg, (B) 1st larval instar, (C) 2nd larval instar, (D) 3rd larval instar, (E) pupa, and (F) an eclosing adult beetle that is tunneling toward the surface. The brood ball chamber is larger with each successive life stage as the larva feeds on the chamber walls within the brood ball. The top inset shows (G) the fecal pedestal the egg is positioned upon in brood ball. The bottom inset shows (H) the larval instar feeding on the walls of the brood ball chamber." From Estes et al. 2013.

In this week's paper, Daniel Schwab and colleagues from the University of Indiana show that the bacteria in the mother's poop enhances the total growth and the growth rate of developing dung beetles, and that these effects are amplified when the developing beetles are exposed to temperature or water stress. Interestingly, when they compared treatments in which developing beetles acquired microbiota either from the mother's poop or from the herbivore dung ball that the mother provided, there was no difference in the average total growth, or growth rate, of these beetles. But, beetles that acquired their microbiota from the herbivore dung were more variable in size and growth rate than beetles that acquired their microbiota from the mother's poop. This result highlights the complex interaction between microbiota, genetic variation, and environmental effects. 

Tool manufacture by cockatoos

This week's paper is in Biology Letters and comes from Alice Auersperg at the University of Vienna. Goffin's cockatoo, Cacatua goffiniana, is native to the Tanimbar Islands in Indonesia. The almost complete absence of publications on this species suggest that little is known about it, although it is common in the pet trade and listed by the IUCN as "near threatened" in the wild. Prof. Auersperg references "ongoing fieldwork" in this paper, so hopefully there will be more to come!

The authors of this paper do say that Goffin's cockatoo does not use tools in the wild, or make nests. Not making nests is important, because it could be that the manipulation of sticks for nest-building predisposed birds to use of sticks as tools (although as far as I can tell there is no evidence to support this hypothesis). Previous research with Goffin's cockatoo showed that birds can socially learn how to use tools from watching a demonstrator bird. Their demonstration was given by a particularly crafty cockatoo, Figaro, who had on his own figured out how to make tools by breaking off pieces of larch wood shingle and used them to get nuts that were out of reach past his cage bars. The watching cockatoos only learned if they watched Figaro, not if they watched a robotic demonstration of the tool use. What was particularly interesting about that study is that some of the birds who watched Figaro used the tool, then started making tools to use, without ever seeing a demonstration of tool-making. 

But back to the paper at hand. This study builds off the previous one by examining how flexible the cockatoos are in their tool-making. In particular, the authors wanted to know if the birds could make tools from a range of different materials that required different manufacturing techniques. They showed that not only can the cockatoos break of larch wood shingle splinters, they also can strip the leaves from beech twigs and use those, and clip out pieces of cardboard with their beaks to use (see the adorable video above). The authors additionally tried beeswax to see if cockatoos could mold tools out of it. Apparently this was a failure. The paper reads "All made a few attempts to mould the wax, which resulted in useless segments which stuck to their beaks, and they soon lost motivation to interact with this material". Also adorable. 

Chimpanzee grooming influenced more by mothers than conformity

Chimps exhibiting "palm to palm clasping" a type of socially learned grooming. Photo by Suzi Eszterhas. 

This week's paper comes from Richard Wrangham's lab at Harvard. They examined the grooming behavior of 18 wild chimpanzees in one group in Kibale National Park, Uganda. Wrangham and colleagues were interested in a very specific variant of grooming behavior. Chimps often exhibit "high-arm grooming", sometimes with clasped palms (photo above) and sometimes with just their wrists or forearms touching. There is observational evidence that high arm grooming style is learned socially. The researchers investigated why there is variation in palm clasping between individual chimps within a population. Some chimps rarely use palm clasping (6% of the time) and some frequently use it (68% of the time). Additionally, they show that there is no correlation between the number of years that an individual has been in a group and the difference between the percent of time an individual spends palm-clasping and the median percent of palm clasping in the population. They propose that if individuals were conforming, one might expect that with an increasing number of years in the population individuals would converge on the average percent of grooming bouts with palm-clasping. I am not sure I buy this, a chimp either palm-clasps or it doesn't in a grooming bout. I can imagine that a population would converge on all (or predominantly) palm-clasping, or not (or rarely) palm-clasping, but it doesn't make sense to me that they would conform on palm-clasping 35.1% of the time, as the authors propose. Unless, some particular grooming condition occurred 35.1% of the time and palm-clasping was always used in that case, but there appears to be no evidence for a particular grooming condition in which palm-clasping occurs. 

The authors show that the percentage of grooming bouts in which a chimp palm-clasps is clustered by matriline. Some matrilines of chimps (mothers and their children) palm-clasped often, and some almost never did. They therefore propose that whether or not a chimp palm-clasps is determined by what their mother did rather than the population median. In conclusion, the authors state that "when incentives are low, chimpanzees tend to maintain their first-learned strategy rather than conform to the group". 

I have some beef with this paper. First of all, it is one population containing 18 chimps (and only 14 for which they know the matriline). I know that research with chimps is incredibly difficult, but it seems dubious to make a general claim about population conformities (or lack thereof) when you only study one population. Secondly, as mentioned above, it is not clear to me that the expectations for conformity make sense. I would be interested to see if a chimp raised by a mother who did not palm-clasp and introduced to a population where the majority of individuals palm-clasped conformed to the population norm, or not. There just doesn't seem to be a population norm to conform to in this case. But regardless, it is interesting to consider the conditions in which social learning from a parent may outweigh social learning from other members in the community. 

Swifts remain airborne for 10 months at a time

Common swift, Apus apus. Photo by René Demoulin. 

The common swift looks like a torpedo with long thin wings. They occur throughout most of Europe in the summer where they make nests on the sides of cliffs and houses. These nests are constructed of material that they collect in flight and stick together with saliva. They migrate from Europe to sub-Saharan Africa in the winter, where they are observed foraging, but roost sites have never been found. In a paper last week in Current Biology a team of researchers lead by Anders Hedenström, attached accelerometers and geolocators to swifts caught in southern Sweden in the summer. They found that swifts spend the majority of the winter in flight, sometimes having only one 2 hour stop in the course of 10 months. This means that not only do they eat and drink on the wing, they also must be sleeping in flight. Previous research has shown that frigate birds, which remain in flight for 2 months at a time, sleep in flight with one half or even both halves of their brain. But when flying over the open ocean for 10 days, frigate birds only slept for about 40 minutes a day, which is much less than they usually sleep on land. It will be exciting to learn how much sleep swifts are actually getting in flight, as it is hard to imagine that they can subsist on 40 minutes a day for 10 months. But why do swifts do this? Why not find a nice place to roost for the night? Well roosting birds are sitting ducks, so to speak. A sleeping, roosting, bird is at its most vulnerable. The authors suggest that swifts may be particularly vulnerable because their adaptations for catching insects high in the sky, including their long thin wings and tiny feet, result in poor manueverability on or close to the ground. The best solution, therefore, is to stay aloft. 

As brains get bigger yawns get longer

New paper this week by Andrew Gallup and colleagues from SUNY Oneonta in Biology Letters. OK first of all, did you all know that one of the proposed functions of yawning is brain cooling?! I always thought it was increasing the amount of oxygen in the brain (debunked in 1987!), but some research has shown that yawning increases circulation to the skull to cool the brain down, arousing the brain and waking you up. In this week's paper the authors went on youtube and recorded the length of yawns of 24 different mammal taxa including foxes, elephants, camels, hedgehogs, walruses, and marmosets. They even have this gem of a quote: "one video with multiple yawning clips from a litter of kittens was excluded owing to the inability to distinguish between individuals". For each of these species they then used previously published data on brain size, encephalization quotient (how much larger the brain is than it is expected to be given the animal's body size), and number of cortical neurons. They found a strong correlation each of these brain size measurements and yawn duration. Primates have particularly high relative brain sizes and cortical neuron counts and accordingly had significantly longer yawn durations than other mammals. Interestingly, neither body size, skull size, nor jaw size predict yawn duration. The authors propose that longer yawns may be necessary to arouse larger brains, although the mechanism by which this might occur needs further study. What is novel about this paper is that there is consistent species variation in yawn length, and this correlation with brain size may be a potential explanation. 

How the platypus lost its teeth

The extraordinary duck-billed platypus. Photograph by Joel Sartore, National Geographic Photo Ark

In a paper this week in Science Advances, Masakazu Asahara and colleagues compared the skulls of the platypus we all know and love, Ornithorhynchus anatinus, with fossils of the extinct platypus genus Obdurodon. The most distinctive difference between our modern platypus and Obdurodon is that modern platypuses lose their teeth as they grow into adults, whereas Obdurodon retain their adult teeth. The modern platypus does eat crunchy things, such as crayfish, but they grind them up using the tough keratinized pads in their bills that you can see in the photo above. 

So why did the modern platypus lose its teeth? Asahara's paper shows that it was due to the development of the electroreceptive organ in the platypus bill. Platypuses forage for crayfish in the mud of murky freshwater rivers and pools in eastern Australia. Visibility in these conditions is very low. Platypuses therefore use mechanoreceptors (touch sensors) and electroreceptors on their bill to find crayfish in the mud.

All animals (including us humans) generate weak electric fields due to the activities of nerves and muscles. The ability to detect those electric fields, called electrolocation, is much less common. It occurs in some sharks, fishes, dolphins, and bees (the bee paper is super cool).  In biology there are two different types of electrolocation. Active electrolocation, such as in electric fish, is when the animal generates an electric field using an electric organ and then detects distortions in that electric field to localize obstacles or prey. Electric fish can also communicate through electrical signals and use them to paralyze their prey. In contrast, passive electrolocation, such as what occurs in the platypus, is when an animal uses an electroreceptive organ to detect electric fields, but is not generating its own electric fields with an electric organ. The platypus can use its electroreceptive bill to detect the weak electric fields generated by a crayfish in the mud. 

Asahara's paper demonstrates that Obdurodon had a more upturned bill that the modern platypus which leads them to propose that Obdurodon spent more time foraging in open water than in the mud on the bottom, and may therefore have had less need for electro and mechanoreception in its bill. In accordance with this, the space in the skull for the nerves to the bill is smaller in Obdurodon than in the modern platypus. As the nerves enlarged in the modern platypus, however, they took up the space needed for the roots of adult teeth. Over evolutionary time the platypus therefore appear to have traded their teeth for improved prey finding in murky water. 

If this tidbit peaks your interest in the platypus, this documentary has fantastic footage including foraging, courtship, and a cameo of a wombat in the snow.

Jumping Spiders Hear with their Furry Legs

The jumping spider Phidippus audax. Photo by Patrick Zephyr. 

New paper from the Hoy lab at Cornell! Paul Shamble, Gil Menda, and colleagues' paper came out in Current Biology this week. With behavioral and neurophysiological experiments they show that jumping spiders can detect airborne sound. You can watch Professor Hoy explain the findings in a video from Cell. This research is particularly cool because spiders have no tympanic membrane organ like our ears, or the ears of many insects. Although spiders have no ears they are very good at detecting substrate vibrations, as you can see if you gently touch a spider's web and the spider comes running. Additionally, many spiders can detect air disturbances through their body hairs, and use this to catch prey when they have no visual cues (that paper is here, but it's pretty tough going). This is like you being able to tell which way the wind is coming from by your hair blowing around, but much much more sensitive.

Spiders therefore, had previously been shown to be sensitive to substrate vibrations, and the movement of air particles at short range, but not to longer distance (3m) airborne sound. In this new paper the authors show that spiders freeze when low-frequency (80 Hz) sounds are played, even when they are placed on platforms that prevent them from detecting any substrate vibrations. Additionally, neural units in the spiders' brains were responsive to these frequencies. Given the sensitivity of spider hairs to air movement (and after all hair cells in our ears is how we hear), the authors suspected that spiders were hearing through the motion of their hairs. To test this they played sounds to a spider, found a neural unit that responded to that sound, and then moved single hair on the spider's leg and showed that the motion of the hair cell stimulated the same neural unit. It turns out that one of the main predators of jumping spiders are wasps, and wasps make a buzzing sound when they fly that is within the range of this spider's hearing. This auditory ability in spiders may therefore have evolved due to wasp predation. Jumping spiders are highly visual animals, which is not a surprise given their big eyes, and incredible courtship behaviors that include both visual and vibrational signals. I have always loved jumping spiders because when I one runs across my desk they always seem to stop and look me over, sizing me up. I admire their spunk. Now I will think about whether the sound of my typing was what rustled their leg hairs and made them look up. 

I will leave you with the courtship display of a peacock jumping spider, because even though it is not particularly relevant to this story, it is just gorgeous.

BUMBLEBEE DOUBLE-HEADER! SOCIAL LEARNING OF STRING-PULLING AND OPTIMISM

Two cool papers came out of the Chittka lab (Queen Mary University, London) this week and I can't help but talk about both of them. First, Sylvain Alem et al.'s paper in PLOS Biology demonstrates learning and social learning of string-pulling task in the European bumblebee, Bombus terrestris. Success at string-pulling tasks are a classic method of estimating intelligence in animals (especially birds) and have been used with ravens, keas (crazy smart parrots), dogs, and many more species. One of the big debates with string-pulling is whether the animal has the insight that pulling the string will bring the reward closer, or simply moves the string accidentally, which moves the treat closer (which is in itself rewarding), so they do it again, etc. One way to test for insight is to put the treat on the end of a line with lots of slack (a "coiled string") so that as the animal pulls the string the treat does not immediately move closer, but rather it takes insight to understand that if you keep pulling the string the treat will eventually move. Alem et al. show that bees fail the coiled string task, and rather learn to pull the string through matching each tug on the string with the rewarding blue flower moving closer to them. 

Next Alem et al. showed that naïve bees learn to solve this string-pulling task from watching experienced bees do it. This reminds me of the octopus that learns how to get crab treats out of puzzle boxes by watching another octopus do it (there is a totally hokey video). This string-pulling experiment raises the exciting possibility that one bee would learn a novel way to get food (and they did have some "innovator" bees in their tests), and then that method would spread through the bee colony or even across colonies of bees foraging in the same fields. Culture! It's for the bees. (Sorry about that, I couldn't resist). 

A Bombus terrestris with an optimistic outlook. Bee by Quiet Magpie. 

The second paper came out last Friday in Science. Perry et al. examined how experience of a reward affects how bees respond to novel situations. They used a "judgement bias paradigm" that is used in research on vertebrates. In this experimental design the animal is trained to associate one stimulus (a blue color in this case) with a reward, and another stimulus (green) with no reward. The theory is that animals in a positive emotional state (i.e. happy) will respond positively to an ambiguous stimulus (a teal or turquoise color). Similarly, a negative emotional state will make animals respond negatively to ambiguous stimuli. 

Makes you wonder what happiness really is, doesn't it? When you can't ask the bee if it is happy or not, and it does not smile or sigh contently, how could we ever determine if a bee is happy? Well, one possibility is to examine how humans that currently self-describe as happy respond to all kinds of different stimuli and situations and compare that to humans that currently say they are not happy. Wright and Bower (1992) demonstrated that people in happy moods expect more positive outcomes that people that are sad. A pessimistic outlook was previously demonstrated for honeybees by Wright et al. 2011, who shook the hell out of honeybees to put them in a bad mood and then showed they were pessimistic about future rewards. Who can blame them.

The recent Science paper showed that bumblebees that had been trained to associate entering a blue tube with sugar water and entering a green tube with water (no reward) were then offered the ambiguous teal/turquoise color. Bees that were fed some sugar water just before being presented with the teal color entered the teal tube faster than bees not given the sugar water. They performed control experiments to rule out that bees fed sugar first had more energy and so were just moving faster, or that they were generally more exploratory. Additionally, bees that were fed a drop of sugar water and then attacked by a robotic spider (!) started foraging again sooner than bees that were not fed a sugar water drop. So not only does a reward make bees more optimistic, it also makes them less afraid.

Dopamine is one of the human brain chemicals associated with a happy feeling. Your brain releases dopamine after you eat a cupcake, or, for that matter ingest some cocaine. When bees were given the sugar droplet but also a chemical that blocks their response to dopamine, they were afraid of the robotic spider for longer. This shows that dopamine is likely the brain chemical responsible for the optimistic behavior of these bees. 

Clearly we should all eat more cupcakes. And understand that the consumption of those cupcakes may make us irrationally unafraid of robotic spiders.

SOCIAL MONOGAMY AMONGST TINY CRABS THAT LIVE IN SEA TURTLE SHELLS

“A small crab, Planes minutus (Columbus crab), living on an individual of Caretta caretta (Loggerhead Sea Turtle)" by Maristella D'Addario.

This week's paper is from Biology Letters in which Pfaller and Gil examine resource use by tiny (<10 mm) crabs that live in the shells of loggerhead turtles. These "columbus crabs", Planes minutus, live in the tail area of the shell, which is likely why they were long assumed to feed on turtle poop. In the 1990's, however, John Davenport discovered that they really serve as minuscule roombas, eating other animals that attempt to colonize the turtle's shell such as barnacles and amphipods. (N.b. Although this is referred to as a symbiotic relationship, there is no data quantifying mutual benefits. It is possible that harboring a crab roomba is actually more costly than the barnacles would have been.) Pfaller and Gil were interested in whether crab population size on turtles or ocean flotsam (floating debris) was determined by the total surface area of the habitat (turtle or flotsam) or the available refuge area (space under the turtle's tail or area of flotsam covered by sheltering barnacles). They show that the refuge area is more important than the total surface area in predicting crab population size. The smaller refuge available on turtles resulted in predominantly one male-female pair of crabs living on a turtle, versus a large piece of flotsam might have up to 233 crabs. The behavior of turtle-cleaning might therefore also generate social monogamy in crabs, with all kinds of consequences for behavior and evolution. In all fairness this had been proposed previously by Thomas Dellinger, but this new paper supports Dellinger, and quantifies the refuse space.