At the end of 2016, a pilot reported that a volcano in Alaska called Bogoslof was erupting. Bogoslof had been quiet for 24 years, and there wasn’t any equipment on it that scientists could use to track its eruptions. But over the next 8 months, scientists were able to track at least 70 eruptions from Bogoslof. And they did so using something you might not expect: sound.
In this episode of Tiny Matters, we’ll cover what sound can tell us about events as big as volcanoes and ‘Swiftquakes’ and as small as the insect world, where researchers are using AI to track different insect species, leading to important discoveries that could help not just public health but agriculture and climate policy.
Transcript of this Episode
Deboki Chakravarti: At the end of 2016, a pilot reported that an Alaskan volcano called Bogoslof was erupting. The volcano had been quiet for 24 years, and there wasn’t any equipment on it that scientists could use to track the eruptions. The volcano continued erupting for 8 months. And during that time, scientists were able to track at least 70 eruptions from Bogoslof. So how did they do that? Well, they had a few tricks up their sleeves…including sound.
Welcome to Tiny Matters, I’m Deboki Chakravarti and I’m joined by my co-host Sam Jones. And I’m excited because today, we’re going to listen to a volcano! But this episode is about more than just volcanoes. It’s about sound and a few of the ways that scientists use it to study nature.
Sam: There are of course a lot of different ways that sound tells us about the world around us. So today, we’ll focus on sound on two very different scales. We’re going to start with the very big: volcanoes and a Taylor Swift concert. And then we’re going to move into the much smaller world of insect sounds.
Deboki: So to start, let’s get back to volcanoes with the help of Gabrielle Tepp, a staff seismologist at Caltech and the Southern California Seismic Network. As the staff seismologist, one of Gabrielle’s jobs is to make sure the data and analysis of earthquakes in the area is as high quality as they can make it.
Gabrielle Tepp: And then earthquake response, I get to do that. So whenever there's an earthquake, I get to talk to the media. So things like this are fun because it's actually a good thing that I'm talking about and people aren't hearing from me because there was an earthquake somewhere.
Sam: Seismologists study seismic waves, which are caused by the sudden movement of stuff in the Earth, like the movement along fault lines that can lead to earthquakes. One of the tools used to measure these waves are seismographs.
Deboki: Seismographs are mounted to the ground with a pendulum or some kind of mass on a spring. When the earth shakes, the seismograph also shakes. And by tracking the movement of the pendulum relative to the seismograph, you can track the motion of the ground.
Gabrielle: Your typical seismometers measure ground velocity. There's also accelerometers which measure, surprise, ground acceleration.
Deboki: The data from these tools is what allows seismologists to study earthquakes. Monitoring volcanoes can be a bit trickier though.
Gabrielle: There's actually a pretty small percentage of volcanoes worldwide that actually have permanent monitoring networks. Many volcanoes are in remote areas that are hard to reach or they're in countries that don't have the money to have large, very high quality state-of-the-art monitoring at all of their volcanoes. So you either have a permanent network or if you wanted to study a volcano, you go put the instruments out yourself.
Sam: You might be thinking, well, isn’t it pretty clear when a volcano is erupting? They’re not exactly subtle events. Well, yes, but also it’s a little more complicated. There are different types of volcanoes, like subaerial volcanoes, where the eruption happens out into the air4. But there are also underwater volcanoes, which are called submarine volcanoes. And it’s harder to monitor submarine volcanoes visually.
Gabrielle: Like subaerial volcanoes, you can put a satellite in orbit and take pictures of a volcano wherever you want. It doesn't matter how remote it is, you can still take a picture of it. Submarine volcanoes, you can't do that because water attenuates light very quickly, so you can't penetrate very deep with light.
Deboki: So for those submarine volcanoes, using an image-based satellite won’t work unless there’s some part of the eruption that gets to the sea surface.
Bogoslof is considered an emergent submarine volcano. The very top of it makes a small island, but the eruption occurs mainly in a submerged vent5. It’s also remote, and when it first began erupting in 2016, there weren’t instruments set up on it to monitor its activity. Seismometers on nearby islands were able to pick up the eruptions. But to track other aspects of Bogoslof’s activity, scientists needed more tools, including a device called the hydrophone.
Yes, that’s exactly what it sounds like: a microphone that works underwater. Most hydrophones are made with ceramic, and ceramic has this really neat property called piezoelectricity6. When you apply some kind of pressure on ceramic (like, for example, an acoustic signal), the ceramic will create a small electrical charge. By amplifying and recording those small voltage changes, you can get a recording of the ocean.
Sam: And Gabrielle told us that signals can travel really far in the water thanks in part to something called the SOFAR channel, which stands for the Sound Fixing and Ranging Channel.
The SOFAR channel is created by layers in the ocean that form due to differences in salinity and temperature. Low-frequency soundwaves—like the ones coming off volcanoes—can bounce off those layers, which help them travel long distances.
During World War II, scientists ran an experiment to test out how sound travels in the ocean7. They had a ship detonate an explosive beneath the ocean’s surface. A hydrophone near Woods Hole, Massachusetts was able to pick up the sound…from 900 miles away, all thanks to the SOFAR channel. And Gabrielle told us that hydrophones can pick up sounds from across ocean basins, which is really useful for monitoring submarine volcanoes.
Deboki: And that brings us to what I was most curious about: what does a volcano actually sound like? It’s pretty unique to each volcano. There’s so much going on, like different types of earthquakes that reflect different things happening in and around the volcano.
So Gabrielle took us on a little tour through a recording of Bogoslof made on June 30, 2017 on a hydrophone that was just 7 kilometers from the summit of the volcano. And before we listen, we should note that the audio has been sped up by 60, so one second of the recording is actually one minute of the explosion.
There are two big reasons for that. One is that the original audio file is 30 minutes, and that’s a long time. The second is that many of the frequencies in the original recording are below 20 Hertz, which is below what we humans can hear.
Gabrielle: So you'd be listening to a sound you could barely hear for 30 minutes, which would not be fun. So we speed it up so that it can go into the range of human hearing and so that we can listen to it in a reasonable amount of time.
Sam: We're going to play the audio first just so you can see if this sounds like what you think a volcano would sound like. And then we'll talk about it and Gabrielle will help us understand what we're listening to, and then we'll play it again.
[Bogoslof audio]
Deboki: When I first heard this, there were a few things that stood out to me. In the beginning you have those creaky door or windmill-like sounds, and then there’s this loud moment that sounds almost like someone blowing on a microphone. And that’s followed by a swooping noise and then some rumbles.
Gabrielle told us that the beginning creaky sound is the sound of weak earthquakes, and then the sudden loud blowing sound was a larger earthquake. These signals are coming underground, and they’re leading up to the actual eruption.
Gabrielle: So you have this nice earthquake and then you have this glide, which is kind of that like woo. So this could be one of my colleagues at the time, he called it the dying seal.
Sam: And that dying seal sound could be connected to a drop in pressure, which might happen with something like a drop in magma volume. And the rumbling after is the actual eruption, which created an ash plume.
So we’ll play the audio again so you can once more experience the earthquakes and dying seal sound.
[Bogoslof audio]
Deboki: There are more recordings from Bogoslof during that 8 month eruption period, and collectively they’re helping scientists understand more about how we can study volcanoes—even the remote ones.
But some of the techniques that Gabrielle used for understanding Bogoslof also came in handy when studying something very different from a volcano: The Eras Tour.
Sam: In the summer of 2023, various news sites reported that Seattle Swifties had caused their own sort of earthquake…a Swift Quake. And with the tour coming to SoFi Stadium in LA, there was a cool opportunity for Gabrielle and her colleagues to study the concert for themselves using monitors set up inside and outside the stadium. But it turns out that a Swift Quake is a bit different from an earthquake.
Gabrielle: So for the Swift Quakes, we don't have this typical earthquake where it's one impulse or where the energy is really concentrated. It's very spread out, it's blasting for the duration of a song, so a few minutes, it's kind of up and down and all over the place.
Deboki: So they looked at the energy magnitude, which in this case means looking at the energy released over a whole song. And they found that the strongest Swift Quake happened during the song Shake It Off, and this quake had a magnitude of about 0.85. Though remember again that this is the energy released over minutes, so it’s different from the way you might experience an 0.85 magnitude earthquake…though that would still be a fairly weak earthquake.
Sam: But there’s more to the seismology of Taylor Swift than just her energy magnitude. Scientists studying sound rely on visuals quite a bit for their work, including something called a spectrogram, which helps to visualize the audio frequencies in a signal over time.
And in the past, when people have looked at spectrograms from concert data, they’ve seen a pattern called harmonics. They actually look like straight lines in the spectrogram. But people weren’t sure exactly what was causing them. Was it the movement of the fans in the crowd? Or was it something about the music being played?
Gabrielle: And I was like, oh, well you know what? We could do an experiment. And so we put this experiment together, we borrowed the little portable PA system that the department has for outdoor events, and we went into the basement on a Sunday morning when no one was around and blasted Taylor Swift.
And so our plan was let's record the songs. And then I brought my bass guitar and I was like, I'm just going to record a very simple bass beat following a metronome and to make it as precise as possible. And then I did it once without a metronome. So that was the plan while we were playing the songs, they're very catchy poppy songs. And so I got to the final chorus and I looked at my coworker, I was like, let's jump.
Deboki: When they looked back on the signals from this experiment, they found that jumping produced the same kind of signal seen in the concert data, suggesting that it’s the movement of fans producing those interesting harmonic signals.
And you might be curious about how this compares to other shows. Luckily, Gabrielle also had data from Beyonce and Metallica concerts.
Gabrielle: So Beyonce and Taylor Swift especially were very nice, straight horizontal lines, and Metallica just sometimes it was kind of straight, sometimes it kind of went ‘woo,’ and sometimes it kind went ‘woo,’ and sometimes it just kind of did whatever, and it was like, okay, this is very strange.
So what causes that? Well, I have a few ideas. When I went to look up information for that concert, I found a number of complaints about sound quality. So it could just be that the audience was not as in sync about what was being played or what was going on. If somebody's having a hard time hearing it, they might think it's a different song and be jumping to whatever's in their head rather than what's actually being played. Another idea is just concert style. Beyonce and Taylor Swift, if you go watch their videos, it is very choreographed. They have lots of people involved, lots of moving parts. Everyone has to be in the right place at the right time, and so they very much have to keep to a beat. Metal bands on the other hand, if you've ever been to a metal concert, they're just kind of like, yeah, we're just going to have fun and run around the stage and do what feels right in the moment.
Deboki: I love this, and not just because I still remember spending 7 hours on my computer to get tickets to the Eras Tour. It’s really cool that there are so many different ways to process sound. Like there’s the sound you’re actually experiencing in the concert, but then there’s so much more buried in there.
Sam: Totally, and that’s a big part of our next story too, which is about the smaller side of sound. We’re recording this episode in spring, so there are a lot of noises going on right now. Sometimes there’s rain falling. Other times, there are birds chirping. And then of course, there are bugs. Lots and lots of bugs.
Laura Figueroa: Insects in many ways rule the world.
Sam: That's Laura Figueroa, an assistant professor in environmental conservation at Umass Amherst. Laura is an ecologist and entomologist who focuses in particular on bee conservation. Like she said, insects rule the world. And for many reasons…
Laura: Often the things that come to mind are the ways in which they're problematic for human society. We think about disease vectors, malaria, which kills many, many, many people, millions of people around the world. We can think about agricultural pests that result in the use of pesticides. We can think of forest pests which have decimated forests in the northeast and around the world.
So clearly there are some problematic species that influence society negatively, but there are innumerable ways in which insects are also deeply beneficial. Nutrient cycling, they are important pollinators, they're important for biological control. They're also really historically important for culture and art and people's sense of belonging and place.
Sam: So monitoring insect populations can help us to understand everything from potential disease outbreaks to how well conservation efforts are working. But how do scientists monitor insect populations? Well, it depends on the insect.
Laura: So some species, for example, nocturnal moths, often they can be monitored with lights on a sheet. You can put a light and take photos or do visual assessments of the moths that show up at the light.
For certain types of agricultural pests, there can be sticky traps where basically all the insects that crawl across this get stuck and then people can monitor the biomass.
Sam: There are many other types of traps too. But as Laura pointed out to us, many of these techniques kill the insect. Plus, they can require a lot of work.
But there is another way that scientists monitor insects: through the sounds they make. This is part of a larger field of science called bioacoustics, which is focused on the types of sounds produced by animals.
Deboki: Insects make a lot of different types of sounds, whether that’s through singing or moving or some other behavior. And the environment an insect is in can affect these sounds, which gives scientists a way to use insect populations to understand other things going on in their habitat. For example, scientists have monitored the sounds of honeybee colonies, and they’ve found that colonies can make distinct sounds based on the presence of different pollutants in the air.
Laura: And so the idea is that could you use sound that honeybee colonies make as an indicator, as a bio-indicator of air quality because potentially when there's a lot of pollutants, they'll make certain types of stress noises. […] And so I thought that was a really interesting assessment of sound behavior or physiological response, and then how humans could actually leverage that for understanding air quality in a non-toxic, non-chemical, less energy intensive way.
Sam: There are several advantages to being able to use bioacoustics to monitor insect populations.
Laura: So the benefit is that it can be standardized, it can be non-lethal because you can deploy these recorders and it can record for extended periods of time. You can basically record for 24 hours in many different places at the same time.
Sam: But there are some downsides too. Sometimes the differences between insect species might be too subtle to distinguish via sound. And some insect species don’t really make any sound at all.
Despite these challenges, scientists have still found clever ways to use insect sounds. For example, insects are huge pests when it comes to agriculture—not just out in the field where they can wreak havoc on plants, but also when people are storing what they harvested.
Laura: And so imagine that you have collected and harvested a bunch of grain, and if you're an insect, and there's a massive bin of grain, that's a lot of food available. And so what some researchers have found is they have put recorders of what it sounds like when there's just grain, which really sounds like nothing at all. It should have very particular sounds of no movement. But when you have insect infestation, those grains actually move around. And so they've actually trained the models to think about insect outbreaks, not necessarily based on the sounds of the insects themselves, but the sounds that they're making the grains make by moving and eating them around.
Deboki: When Laura refers to “models,” she’s talking about computational models that learn how to identify sounds—in this case, the sound of grains being moved by insects. We’re going to return to these models in a bit because they play an important role in bioacoustics. But first, let’s talk about how scientists get these sounds to begin with.
Laura works with undergraduate and graduate students whose jobs involve following bees.
Laura: We basically go into the garden, we find them and oh, there's a bee! [...] And then we just basically follow it just like you would if you're doing an interview, imagine you have for this podcast, you're interviewing the bee, you just follow it around. And sometimes they're very chill and sometimes they're very happy to be listened to and other times they can get frightened and fly away. But even if they're flying away, that's another second while it's flying away that you get to record them.
Sam: We’ll play two of the recordings that Laura’s group made. Some of the things that Laura said you might notice are the frequency of the sounds and the duration of them.
So first up, here’s one of their recordings of a two-spotted bumblebee [two-spotted bumble bee audio]. And this is a recording of a honeybee [honeybee audio].
Deboki: One of the things I noticed was that the bumblebee clip sounded deeper compared to the honeybee. I’ll be honest though, I don’t know how good I would be at identifying the bees out in my yard right now just by sound. But Laura has obviously been at this a lot longer than me.
Laura: As someone who's been working in the field for over a decade, you get to hear that certain bees make different sounds. And so actually right now in April and May, queen bumblebees are out. And so queen bumblebees tend to be a lot bigger than the workers and a lot bigger than many other species. And their size actually influences the kinds of sounds that they emit. And so at this time of year, when I go outside and I hear a queen, wow, even with my eyes closed, I can tell that it's a queen because it just sounds really much deeper. And you can really tell based on sound.
Sam: While it’s important to have scientists who can identify these sounds, we’re also living in a time where we can teach computers how to distinguish between different insect recordings, which is where we get back to those models.
Laura: So right now we are really living in an age of AI, of machine learning, of new changes that we can go beyond just people power.
Sam: AI and machine learning have been in the news a lot, and you can hear about it being used for everything from homework to drug discovery. Very briefly artificial intelligence is meant to help computers understand things, like say, for example, how to distinguish between the sounds of different insects.
Laura: If you hear a grasshopper, you know what kind of insect it is, that it's not a fly, you can put it in a bin in your mind based on the number of times that you've heard it. And so just like we get to bin, and if I say the sound cicada, if I say the sound that a bee makes, if I say buzzing of a fly though, all of those have different categories and we can basically train machine learning algorithms, to bin them in the same way.
Deboki: Very broadly, machine learning algorithms begin with data that’s meant to train the computer to learn something—in this case, the differences between insect sounds. Then an algorithm helps the computer learn to identify different patterns in the data. In this case, the training data comes in the form of spectrograms that scientists annotate to show what different types of insect sounds look like.
Sam: One of Laura’s recent review papers compares the different kinds of algorithms out there that help computers train on this data. But one of the things that’s important to remember is that no matter how good these algorithms get, they’re still dependent on the type of data we give them. So there’s a lot of learning on the human end on how to best do that.
Laura told us about one colleague who was creating a dataset of grasshopper sounds, using grasshoppers in the lab.
Laura: But what they didn't realize—because we are exposed to sounds all the time that we just kind of don't think about—and so there had been a refrigerator in the background that had this small background buzzing, but that we don't really think about, right? Often if you have a computer, it might be making some whirring sounds or if you have the AC, it might be making some sounds that your brain just kind of blocks out.
Sam: So the researchers trained their models, but when they went out into the field to see how it worked…well, it didn’t. The model had made connections based on these other sounds that researchers hadn’t intended to be there, and that affected the way it processed grasshopper sounds out in the wild. So when it came to building her own datasets, Laura made sure she was recording insects in a number of different contexts.
Laura: And so we've done it in multiple states, in different types of gardens when there's different levels of background noise, and we've explicitly trained with background noise as a category. So for example, when there's lawnmowers, when there's planes, when there's buses around, when there're human voices.
Deboki: When it comes to the future of bioacoustic monitoring, Laura said that one of the big issues is making sure these models are being presented in a way that can actually help people in a number of different contexts—an issue that’s especially challenging because many models don’t even have a user interface.
Laura: And so a lot of the people who might be interested in, again, controlling mosquito outbreaks or controlling agricultural outbreaks, we might be talking about people who work in public health, people who work on farms, or when we're talking about people interested in conservation, we might be talking about people in policy or NGOs who might not have an advanced computer science PhD who might not be able to delve through the equations and develop the model from scratch.
And so one of the things that I want moving forward is for there to be more integration with potential end users. So who's actually going to benefit and use these and how can we make platforms that are useful that promote uptake in the communities that actually really need it? Because it would just be such a shame for there to be time, money, investment in the development of algorithms that actually just never get used. Because we're in a time where we need all the help we can get for understanding insects and promoting pollinators, promoting the decomposers, promoting biological control, promoting the wellbeing of ecological health.
Deboki: But of course, we don’t need to be trying to solve the world’s biggest problems to appreciate insect sounds. So I asked Laura for ideas for any of you who might be motivated to try and take a closer listen to nature.
Laura: Next time that there is a beautiful day that the weather nice and wherever you live, if it's the spring or summer or fall, to go outside and to sit near nature if you can, even if you're in an urban center, if you could find a community garden, if you live more rural areas, there's a lot of nature all around us. And just to spend a few moments just sitting, listening, because I think it's so easy to take them for granted and to overlook them and often you’ll see it’s insects that are making a lot of those sounds.
Sam: It's tiny show and tell time.
Deboki: Sure is.
Sam: I can go first this time.
Deboki: Cool.
Sam: So Deboki, a little bit of T-Rex drama that I'd like to bring to you today.
Deboki: Yes.
Sam: So last year, there were some researchers who reported that the T-Rex probably had around 3.3 billion neurons in this one part of just the T-Rex’s forebrain alone. Essentially, the report was that we think T-Rex had way, way, way more neurons than we thought, so T-Rex is probably way smarter than we thought. And they actually said T-Rex's forebrain could be on par with modern baboons, which is actually very, very impressive. There were a lot of doubters. I don't want to say haters, but there were a lot of people who were like, "Hmm, that seems like too big of an improvement in terms of what we thought T-Rex's intelligence was." So there's been a lot of debate.
So now a different research team has come up with a more conservative neuron count. And you might be wondering, how the heck would we even calculate how many neurons are in the brain of this extinct species? This original study had calculated the ratio between brain size and body mass of around 30 dinosaurs and then compared them to modern birds and reptiles. And so the way they were actually doing this was sort of using current neuron densities of modern birds that are most closely related to theropods to try and make this calculation. So of course, whenever you're looking that far into the past, you're making a lot of assumptions, you're trying to make the best comparisons you can. But then this other research group that has come forward since has said that a lot of the assumptions that were made originally were flawed. And so what they did was they added a broader range of living birds to that comparison. And what that then did is brought T-Rex's number of neurons more in line with today's scaled reptiles, somewhere around the 300 million range. A lot lower.
Deboki: Oh, well, now they're just dumb.
Sam: There's still a little bit of drama here, right? So the original authors are like, "Okay, well, we're not completely convinced." This is still an ongoing debate, and I think whenever anything... Like I said, whenever anything is just that ancient, you incorporate a few more species, you... You know? There's so many potential variables that could be included or left out or whatever, and it's going to really dramatically change things.
Another point that someone made in this story is that even if T-Rex had more neurons than we thought, it's not necessarily an indicator of overall brain power. It's more complicated than that. It would be really cool if T-Rex had a neuron density that was on par with primates because that would just be crazy to consider, but it sounds like, more likely than not, that was an overestimation, and now people are saying the current is an underestimation. So I'm like, maybe we'll settle somewhere in between.
Deboki: Yeah. I think what that story is so good at showing is the way that science drama is mostly about how you got there. It's really about how people are using these other data sets and these other scientific discoveries and working with them to try to figure out... Like, we're never... I mean, I don't want to say never, but the likelihood we're going to ever have a definitive answer on how many neurons T-Rex had is very low. But I love that we still feel this compulsion to pursue that answer and to argue about it because how we go in search of these answers is so important to us.
Sam: Yeah. The search is the biggest part of science...
Deboki: For sure.
Sam: ... pretty much always. Maybe in six months I'll have another update for you. We'll just keep... I'm going to just checking in on the T-Rex drama and see where we're at.
Deboki: I feel like there's always T-Rex drama.
Sam: There is. Yeah.
Deboki: Sam, for my Tiny Show and Tell, there's kind of a similar vibe to it and it also feels like a little bit of an extension on another theme from this episode, which is clever ways to study volcanoes in remote locations. Only this time the location is Venus. And so, yeah. We've had a lot of indirect reasons to think that there are volcanoes erupting on Venus, but actually getting images of those eruptions is hard because Venus has this really opaque atmosphere. Again, how do you see the thing is one of the challenges. And so in the 1990s, the spacecraft Magellan spent two years mapping out around 98% of Venus's surface, and while the images are relatively low resolution, they're still probably our most detailed image of Venus, which is really cool, and it means that scientists are still finding ways to work with that data. And in this case, over the past year, they've now found their second direct evidence of recent volcanic activity on Venus.
So last year they were able to use the images to track changes to a volcano vent near Venus' equator. And this year scientists reported that they were looking at data from two particular volcano, so both in 1990 and again in 1992, and they found that the signal strength of the radar along these particular paths had increased, which suggested that new rocks had formed along those paths. And so they were looking at the way those paths moved and what they looked like overall, and they found that the best explanation is that the rock formation was due to lava flows, which makes this the second evidence of volcanic activity on Venus. So I just thought that was cool, like the ways, again, that we learn to work with data.
Sam: It is really cool to think that something so familiar to us on Earth is happening elsewhere and these planets that are hard to imagine kind of what they're like.
Deboki: Yeah, that's part of why it's also exciting for scientists, because Venus and Earth have a lot of similarities. They're both rocky, they're similar ages. The fact that we're also very different is very striking, and so maybe it's just kind of one of those little puzzle pieces that helps us start to understand a little bit more about the way Venus works so we can start to kind of understand those differences better too.
Sam: Yeah. We've done collections from Mars now, but how about Venus?
Deboki: Yeah. Venus is tough. I think I... I was going to go down a rabbit hole of the spacecrafts that have melted on Venus, but I forget, so I don't want to introduce that into the podcast, but maybe that'll be another episode in the future.
Sam: Yeah. Let's talk about Venus. What's the latest on Venus?
Thanks for tuning in to this week’s episode of Tiny Matters, a production of the American Chemical Society.
Deboki: This week’s script was written by me and was edited by Michael David and by Sam Jones, who is also our executive producer. It was fact-checked by Michelle Boucher. The Tiny Matters theme and episode sound design are by Michael Simonelli and the Charts & Leisure team.
Sam: Thanks so much to Gabrielle Tepp and Laura Figueroa for joining us. Just as a reminder, soon we’re introducing a new bonus series called “Tiny Show and Tell Us.” Write in to tinymatters@acs.org with science news you’re itching to share, a science factoid you love telling friends about, or maybe even a personal science story. Was there a place, event or maybe teacher who sparked your interest in science? We want to hear about it! You can find me on social at samjscience.
Deboki: And you can find me at okidokiboki. See you next time.
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