9.23.24

Did you hear that? Inside the world of fruit fly mating songs

The activities are as follows:

Communication comes in all forms – through sound, smell, sight, touch, or even taste. The purpose of communication is to share some form of message or information to another organism. One form of communication between humans is talking, which is when we make a variety of noises as we speak using language. Just like people, animals make all kinds of noises to communicate with one another.

The tiny fruit flies that live on the ripe banana in your kitchen communicate as well. They use a courtship song when they are ready to mate. The male fly shakes his wings to sing a song to the female fly. The female fly hears the song, her brain processes the sound, and then she responds. Her brain decides whether she likes him or not. She may then try to kick him away or let him get closer.

Emma is a neuroscientist who is really interested in studying how brains are able to understand all kinds of communication. She uses fruit flies to figure out how brains process communication through sounds. Even though the fly brain is very small, they work a lot like human brains, so studying tiny flies singing to each other can help us understand our own brains.

While researching what other scientists had already learned about fly song, Emma read studies that described an interesting behavior called chaining. Chaining is a behavior when males chase and sing to each other. The scientists first observed this behavior when they played a fly song through a speaker for a group of 6 male flies. Emma wanted to see if she could repeat this behavior in her own lab. An important part of science is repeating experiments to make sure the results are accurate and can be achieved again and again. Repeating experiments can also be a way to test that another scientist’s methods work in your lab.

Sound is played through the yellow speaker. Flies are put into the chambers and watched for chaining

There are lots of things in the lab environment that can impact how a fly reacts to a song. Emma wants to pick a few variables to test. The first variable she selected is the volume of the courtship song being played. Emma decided to test different volumes to see how loudly she should play the fly song to get a response.

Since Emma couldn’t ask the flies if they could hear the sounds she played through her speaker, she measured chaining behavior instead. If the flies heard the sound from her recordings, she expected to see more chaining behavior.

Volume isn’t the only variable she can explore though. Imagine you are listening to a song and the singer sings a word you haven’t heard before. Do you think you’d be able to understand the word? The same thing may apply to the flies. Emma wanted to know if flies would react differently if they had been around other flies that sing. To test this, Emma raised some flies alone and others in groups. That way, she could see if being around other flies before the test made the song easier to recognize.

To gather her data, Emma put 6 male flies into a chamber with a clear top. She placed the chamber in front of a speaker. She also set up a camera to take a video of the flies for a minute before the song played and for a minute after the song began. This two-minute video allowed her to compare the flies’ behavior in silence with their behavior when the song plays. Then, Emma watched the video back and counted the number of flies that were chasing each other every 3 seconds. She did this for one whole minute (20 observation points) to get a chaining index for each group of flies.

Featured scientist: Emma Droste (she/her) from North Carolina State University

Flesch–Kincaid Reading Grade Level = 7.2

Students can listen to this audio clip of fly song and think about what these sounds may be communicating. The audio clip was generated by having a mating pair directly over a very sensitive microphone to capture the audio since it is not audible to the human ear.

9.23.24

Too hot to help? Friendship in a changing climate

This coral has lost its algae partners, causing it to be bleached. (Photo by Coffroth Lab)

The activities are as follows:

When given emergency instructions on a flight, you’re told to put on your own oxygen mask before assisting others. This is because if you run out of oxygen, you won’t be able to help others. Turning to nature, this same idea may be true when we look at relationships between two species.

Coral and certain types of algae form a mutualism where both species benefit from the partnership. Coral provides a safe home for algae, and algae make food for coral through photosynthesis. However, climate change is causing warmer ocean temperatures that stress the relationship. If the water gets too hot for algae, they can’t make food for the coral anymore. To survive, the algae must help themselves before they can help the coral.

Casey is a biologist interested in studying the changing coral-algae mutualism. He wants to know whether different individuals of the same algae species do better than others in warming waters. Individuals of the same species can have different traits. For example, each human person belongs to the same species, but each of us has different traits. This is largely because of our genetic composition for these traits, or genotypes. Casey set out to test if different algae genotypes were capable of being better mutualists under warm temperatures. If he could identify these genotypes, then maybe that could help protect coral in the future.

Casey gets a sample of algae from a flask in his lab. (Photo by David J. Hawkins)

Casey and his graduate student, Richard, set up experiments to test algae genotypes to see how well they performed at different temperatures. Casey and Richard grew five different genotypes of the same algae species in the lab. They used a pipette to transfer 10,000 cells of each genotype and placed them in flasks at two different temperatures. The lower temperature treatment is one where corals and their algae are usually happy: 26 degrees Celsius. The higher temperature treatment is where coral’s relationship with algae starts to break down: 30 degrees Celsius. At that temperature, many corals lose their algae entirely, in a process called coral bleaching.

Casey and Richard measured two things – the total amount of photosynthesis and the total amount of respiration happening in each flask. They did this by tracking what happened to oxygen over time. When there is a lot of photosynthesis, oxygen goes up, and when there is a lot of respiration, oxygen goes down. Two conditions are best for the mutualism. First, a lot of photosynthesis means the algae produced more food that they can share with coral. Second, less respiration means the algae used less of the food for themselves and have more to share with the coral. In summary, when the algae is stressed it does less photosynthesis and more respiration, making it a worse trading partner for coral. The best algae partner is the genotype that can photosynthesize the most and respire the least. The net food available is how much of the food made through photosynthesis is available after subtracting the food used by respiration.

Featured scientists: Casey terHorst (he/him) and Richard Rachman (he/him)

from California State University Northridge

Flesch–Kincaid Reading Grade Level = 8.9

Additional teacher resources related to this Data Nugget

8.28.24

Guppies on the move

Guppies in the lab. Photo Credit: Eva Fischer.

The activities are as follows:

Animal parents often choose where to have their offspring in the place that will give them the best chance at success. They look for places that have plentiful food, low risk of predation, and good climate.

Even though parents pick out these spots, individuals often move away from their birthplace at some point in their lives. Why do animals move away? There are risks that come with moving from one place to another. It can be dangerous to go through unknown places – potentially stumbling into predators or being exposed to diseases. But there can also be benefits to moving, such as discovering a better spot to live as an adult, finding mates, and spreading out to reduce competition.

As someone who loves to travel and has lived in four different countries, Isabela can relate! Isabela likes to see new places, try new foods, and learn new languages. But there can be drawbacks, and occasionally she finds it hard to be in a completely new place. Sometimes people don’t understand her accent, or she can’t understand them. She also misses her family when she is away. Knowing that traveling and moving can have such highs and lows for herself, Isabela wanted to know more about what motivates animals to seek out new places.

To follow her curiosity, Isabela found a graduate advisor who was also interested in animal movement. She joined Sarah’s lab because she had already collected data on the movement of small tropical fish called guppies. Sarah is part of a large collaborative project, where researchers from all over the world come together in Trinidad to study these fish populations.

When Sarah first started collecting data in this system, she wanted to track how far guppies move from one place to the next. She used established protocols from previous work in this system to set up a study. With the help of a team, she captured every fish in two similar streams for replication. Every fish that was caught was marked with a small tattoo so the research team could recognize it if it was found again in the future. She did this same procedure every month for 14 months. Each time she sampled the fish, she recorded the individuals that she found and where they were found.

Isabela used this dataset to ask whether guppies benefit from moving from one place to another. In this study, she focused on one type of benefit: having a higher number of offspring. It is through reproduction that animals are able to pass on their genes, so the more offspring an individual fish has, the more successful it is.

First, Isabela used the existing dataset to find out how far each fish moved: if Fish 1 was captured in Portion A of a stream in February and then in Portion B of the same stream in March, Isabela knew it had to move from A to B. She could use the timepoints to estimate how far each individual had traveled that month.

Second, Isabela used genetics to find out how many offspring each fish had. She looked at genetic markers to determine familial relationships between individuals in each stream. For example, two fish that shared 50% of their genes were probably a parent and an offspring. In this case, the older individual would be marked as the parent. Isabela used the genetic information to build a pedigree, or a chart that documents each generation of a population. That way she could track how many offspring each parent had produced.

She used these data to answer her question on whether there are benefits to traveling more. Isabela also wanted to compare whether the potential benefits of dispersal differed across the sexes. Males have to compete for females in order to mate. Isabela wanted to know if males that moved more were able to mate with more females and have more offspring.

Featured scientists: Isabela Borges (she/her) and Sarah Fitzpatrick (she/her) from the Kellogg Biological Station at Michigan State University.

Flesch–Kincaid Reading Grade Level = 8.3

Additional teacher resources related to this Data Nugget include:

If you or your students are interested in accessing more of the data behind this Data Nugget, you can download the full dataset from Isabella’s research and have students create graphs in Excel, Google Sheets, or using other data visualization software.

If students would like to learn more about Isabela, check out this Exploring with Scientists video from her time at the Kellogg Biological Station.

For more on this system and the research Sarah did in this study system, check out this unit and video on Galactic Polymath:

8.24.24

Do urchins flip out in hot water?

Erin in the urchin lab at UC-Santa Barbara.

The Reading Level 1 activities are as follows:

The Reading Level 3 activities are as follows:

Teacher Resources:

Imagine you are a sea urchin. You’re a marine animal that attaches to hard surfaces for stability. You are covered in spikes to protect you from predators. You eat giant kelp – a type of seaweed. You prefer temperate water, typically between 5 to 16°C. But you’ve noticed that some days the ocean around you feels too hot. 

These periods of unusual warming in the ocean are called marine heatwaves. During marine heatwaves, water gets 2-3 degrees hotter than normal. That might not sound like much, but for an urchin, it is a lot. The ocean’s temperature is normally very consistent, so urchins are used to a small range of temperatures. Urchins are cold-blooded. This means they can’t control their own body temperature and rely on the water around them. Whatever temperature the ocean water is, they are too!

Erin is a scientist who studies how environmental changes, like temperature, affect organisms. Erin first got excited about urchins when she interned with a research lab. When she started graduate school, she learned more about their biology and started to ask questions about how urchins would react to marine heatwaves. Hot water can speed up animals’ metabolisms, making them move and eat more. However, warmer temperatures can also cause stress, potentially causing urchins to be clumsier and confused.

Erin getting ready to scuba dive to look for urchins off the California coast.

One summer, two science teachers, Emily and Traci, came to California to work in the same lab as Erin. Emily and Traci wanted to do science research so they can share their experience with their students.  As a team, they decided to test whether marine heat waves could be stressing urchins by looking at a simple behavior that they could easily measure. Healthy urchins have a righting instinct to flip over to orient themselves “the right way” using their sticky tube feet.

The research team predicted that urchins would be slower to right themselves in warmer temperatures. However, they also thought the response could depend on the temperature the urchins were used to living in. If the urchins had been acclimated to higher temperatures, they might not be as strongly affected by the heatwaves.

Together, Erin, Emily, and Traci took 20 urchins into her lab and split them into 2 groups. Ten were kept at 15°C, the ocean’s normal temperature in summer. The other ten were kept at 18°C, a marine heatwave temperature. They let the urchins acclimate to these temperatures for 2 weeks. They tested how long it took each urchin to right itself after being flipped over. They did this at three temperatures for each urchin: 15°C (normal ocean), 18°C (heatwave), and 21°C (extreme heatwave). They worked together to test the urchins three times at each temperature to get three replicates. Then they calculated the average of each urchin’s responses.

Featured scientists: Erin de Leon Sanchez (she/her) from University of California – Santa Barbara, Emily Chittick (she/her), and Traci Kennedy (she/her) from Milwaukee Public Schools.

Flesch–Kincaid Reading Grade Level = The Content Level 3 activity has a score of 7.9 ; the Level 1 has a score of 5.9

Additional teacher resources related to this Data Nugget include:

  • Here is a video of a parrotfish finding and eating an urchin. Show this video to emphasize how important it is for urchins to be able to right themselves!
Video of a trial where the researchers flipped over an urchin and timed how long it took the urchin to flip back over.
Watch how sea urchins use items from their environment to cover themselves.
8.2.24

A plant breeder’s quest to improve perennial grain

Hannah takes notes on the date of flowering in a Kernza® field in Southwest Minnesota.

The activities are as follows:

Kernza® is a new grain crop that is similar to wheat. It can be ground into flour and used in bread, cookies, crackers and more! Unlike wheat, the rest of the plant can be eaten by livestock such as cattle. Another difference is that Kernza® is a perennial, meaning it grows in the ground for multiple years, whereas annual wheat only grows for one year. However, the challenge is that annual wheat makes more grain and is easier to harvest and sell. This means farmers currently prefer growing annual wheat over Kernza®.

One way to address this mismatch between annual and perennial crops is through selective breeding. This is when humans select individual plants with traits that are desirable for a specific reason. This group of individuals are strategically bred together. The breeder’s goal is to shift the traits over generations. Scientists have only been working on breeding Kernza® for the past few decades; in comparison, humans started selecting annual wheat traits over 10,000 years ago! That is a lot of time to get the traits we are looking for.

Kernza® breeders are working on improving the same traits that have already been improved in annual wheat, including larger seed size. Kernza® scientists follow two main steps to breed plants 1) they select the best individuals from the population and 2) they intercross those individuals to create the next generation, or breeding cycle. With each breeding cycle, plant breeders see a slight improvement in the traits they selected.

Breeders can select plants based on phenotypes, genotypes, or both. Historically, plant breeders have selected based on desired phenotypes, or visible traits, only. Modern plant breeding can take advantage of the fact that we can now look at genotypes, or the genetic makeup, of individual plants quickly and at low costs. Scientists can use this information to make quicker breeding improvements, so we don’t have to wait another 10,000 years for high-yielding Kernza®!

A scientist pipettes DNA samples into an agarose gel to separate samples based on genotype using gel electrophoresis.

Hannah is a scientist currently working on Kernza®. Hannah’s passion for plant breeding was ignited during her high school years. She discovered the captivating world of genetics in her AP Biology class. It was then that she first realized the potential for breeding crop plants to make them more productive and viable for human consumption.

Hannah decided to join other scientists who work on Kernza® at the University of Minnesota. Here, scientists have completed four breeding cycles and are about to start the fifth. Hannah wanted to see whether different genetic makeups (genotypes) lead to differences in seed size (phenotypes). Her goal was to look at each plants’ phenotype and genotype for seed size.

To genotype a plant, scientists collect a small piece of leaf tissue, extract the DNA, and send the DNA to a lab for sequencing. This process tells scientists the genetic makeup that ultimately leads to the traits that we see. Specifically, sequencing data identifies nucleotides, or genetic building blocks of each plant’s DNA. Plants have thousands of genes, which are made up of the DNA nucleotides A, T, C, and G.

Sequencing data can be recorded in several ways. One common way is as SNP data, or Single Nucleotide Polymorphism data. You can think of SNP data as the recipe for proteins. In a SNP dataset, each SNP represents a difference in a nucleotide. Similar to using a different ingredient in a recipe, different nucleotides can result in a different phenotype.

By looking at SNP data, plant breeders can identify differences in genotypes that lead to certain phenotypes. Hannah started by evaluating 1,000 Kernza® plants from the first four breeding cycles. Data on phenotypes had already been recorded for these plants. Hannah then collected SNP data to determine their genotypes as well. She was looking for a pattern between genotypes and phenotypes. If she sees that different genotypes have different phenotypes, scientists can then rely on genotypes to select individuals to breed in future breeding cycles.

Featured scientist: Hannah Stoll (she/her) from the University of Minnesota

Flesch–Kincaid Reading Grade Level = 8.9

Additional teacher resources related to this Data Nugget include:

8.1.24

Poop, poop, goose!

Cackling Goose next to a pile of goose poop, or feces
Cackling Goose next to a pile of goose poop, or feces. Photo by Andrea Pokrzywinski.

The activities are as follows:

Each spring, millions of birds return to the Yukon-Kuskokwim Delta. This delta is where two of the largest rivers in Alaska empty into the Bering Sea. It is also one of the world’s most significant habitats for geese to breed and raise their young. 

With all these geese coming together in one area, they create quite a mess – they drop tons of poop onto the soil. So much poop in fact, that scientists wonder whether poop from this area in Alaska could have a global impact! Climate change is a worldwide environmental issue that is caused by too many greenhouse gasses being released into our atmosphere. Typically, we think of humans as the cause of this greenhouse gas release, but other animals can contribute as well. 

When poop falls onto the soil it is decomposed by bacteria. Bacteria release methane (CH4), a potent greenhouse gas. The more geese there are, the more poop they will produce and the more food there will be for soil bacteria. By increasing the amount of greenhouse gasses that are released by soil bacteria, geese might actually indirectly contribute to global climate change.

Trisha is an ecosystem ecologist who scoops goose poop for research projects. Her research is looking into whether animals, other than humans, can change the carbon cycle. Trisha teamed up with Bonnie, a fellow ecosystem ecologist. Bonnie studies how matter moves between the living parts of the environment, such as plants and animals, and the nonliving parts. She is especially interested in how bacteria in the soil play a role in the carbon cycle.

Together, the team designed a three-year project to figure out the effects of goose poop on the carbon cycle. Each summer, a large team of researchers spend 90 days camping on remote sites near the Yukon-Kuskokwim Delta. The team scooped up poop from nearby goose habitats to use in their experiments. They set up six control plots where they added no poop and six treatment plots where they added poop. From these twelve plots, the team measured methane emissions from the soil. Methane was measured as methane flux in micromoles, or µM. These data helped them determine how ecosystems respond to geese by measuring whether goose poop affects methane production by soil bacteria.  

Featured scientists: Trisha Atwood of Utah State University and Bonnie Waring of Imperial College. Written by Andrea Pokrzywinski.

Flesch–Kincaid Reading Grade Level = 8.7

Additional teacher resources related to this Data Nugget include:

7.17.24

Sink or source? How grazing geese impact the carbon cycle

Tricia (left) installing carbon dioxide plots in the field.

The activities are as follows:

“If it wasn’t for the geese, you and I would not be here today because our ancestors would not have made it. When long, hard winters emptied people’s food caches early, starvation loomed. Return of geese in April saved us.” – Chuck Hunt, born and raised on the Yukon-Kuskokwim Delta

Spring geese are an essential food source for subsistence communities like Chevak, Alaska. Elders in western Alaska Native communities have observed a decrease in geese returning to their villages over time. These changes affect the local communities and could also affect the local ecosystem.

One way geese change their environment is by eating grass. In the Yukon-Kuskokwim Delta in western Alaska, birds from every continent on Earth migrate to this sub-Arctic habitat to lay their eggs and raise their young. Once they arrive, geese eat a ton of grass. They graze only in specific areas, called grazing lawns, leaving the rest of the vegetation alone.

When geese graze on wetland plants, they remove plant matter, potentially decreasing the amount of carbon dioxide, or CO2, that is released during photosynthesis. As plants photosynthesize, they absorb CO2 from the atmosphere and turn it into glucose (a sugar) and oxygen. Gross primary production is the total amount of energy that plants capture from sunlight to grow and live before they use up some of that energy for themselves. Plants can slow climate change by removing CO2 from the atmosphere and turning it into plant matter, like leaves and roots.

A scientist mimics geese grazing by clipping the grass.

Trisha is a scientist who became interested in ways that animals can affect the carbon cycle through their interactions with the environment. She wondered whether fewer geese returning to western Alaska could have global consequences that extend beyond remote communities. She thought that if geese ate enough grass, they may limit photosynthesis. This is important because it could change whether this ecosystem is a carbon sink or a carbon source. An ecosystem is called a carbon sink if it absorbs more CO2 through photosynthesis than it releases through respiration. Alternatively, an ecosystem can be a carbon source if more CO2 is released than absorbed. We want ecosystems to be carbon sinks because then they keep CO2 out of the atmosphere, where it contributes to global warming.

To test her idea, Trisha teamed up with fellow scientists Bonnie, Karen, and Jaron to take a closer look at how grazing grass influences whether the Y-K Delta ecosystem is releasing or absorbing CO2. To do their experiment they had to get creative. They considered getting a lot of geese, bringing them to an ungrazed area, and letting them chow down. However, it’s hard to capture geese and get them to graze exactly where you want. So instead, the research team simulated the effects of geese by cutting the grass to mimic nibbling and then gently vacuuming the pieces of grass to remove them.

The “Carbon and Geese” scientist team.

The team set up six different experimental areas. Inside each area were two plots: one that was left ungrazed, and the other which was artificially grazed. The research team then used a piece of equipment called a LI-COR to measure the quantity of CO2 in the air above each plot. They recorded the CO2 levels during the day and night. The comparison from day to night is one way to look at gross primary production and respiration in a system. At night, when there is no light, plants can’t photosynthesize, so the detected CO2 will be from respiration. The levels during the day represent a combination of CO2 absorption by plants and release from respiration.

To assess whether the ecosystem is a carbon sink or source, we need to determine the difference between respiration and gross primary production, or net ecosystem exchange (NEE). A negative NEE means the ecosystem absorbs more CO2 than it emits. A positive NEE means the ecosystem is releasing more CO2 than it is absorbing. In this way, scientists classify an ecosystem as either a carbon sink that is storing carbon or a carbon source that is releasing carbon into the atmosphere.

Featured scientists: Trisha Atwood, Karen Beard, and Jaron Adkins from Utah State University and Bonnie Waring from Imperial College. Written by Andrea Pokrzywinski.

Flesch–Kincaid Reading Grade Level: 8.9

Additional teacher resources related to this Data Nugget:

Check out this website created by teacher Andrea who participated in the research and wrote this Data Nugget. You will find additional lesson plans, videos, slides, and articles to use in the classroom!

7.2.24

Helping students hear the stories that data tell

Article Highlights

High school students work with a Data Nuggets module.
High school students work with a Data Nuggets module. Credit: Paul Strode
  • Michigan State University’s Data Nuggets program is starting its third round of funding from the National Science Foundation to improve data literacy in K-16 students.
  • The program, operated by the Kellogg Biological Station, also introduces real STEM professionals through storytelling, helping students better relate to their projects and engage more deeply with the program’s content.
  • In collaboration with Auburn University, the newest NSF grant will help Data Nuggets further that engagement and introduce students to a greater diversity of scientists.

A data literacy program that’s also changing students’ relationships with science and scientists is entering its third round of funding with a new $1.5 million grant from the National Science Foundation.

In collaboration with Auburn University, the Data Nuggets program at the W.K. Kellogg Biological Station, or KBS, will work to identify factors that improve equity and success in undergraduate STEM education.

Launched by Michigan State University in 2011, Data Nuggets is a curriculum development project designed to help students better understand and use data. The program shows how professionals in science, technology, engineering and math really work with data by sharing their stories, which also enables students to relate on a much more personal level.  

Data Nuggets challenges students from kindergarten through undergraduate levels to answer scientific questions using data to support their claims. The questions and data originate from real research provided by scientists whose studies range from physics to ecology to animal behavior. 

To add the personal element, Data Nuggets is collaborating with Project Biodiversify — another education program started at MSU — to add the scientists’ bios, which include information like hobbies and their lives outside of science. This helps students relate to the researchers and see them less as strangers in lab coats and more as scientific role models. 

“We’ve found that it’s the scientists that are engaging students in the activities,” said Elizabeth Schultheis, co-leader of the Data Nuggets program. “If they connect to the role model, then you can get students to do the data literacy activities because they know, ‘Oh, this is a real person. I relate to this person. And I’m working with authentic, real data. I’m not just doing busy work.’” 

Schultheis, who earned her doctorate in plant biology from MSU, is also the education and outreach coordinator for the Long-Term Ecological Research, or LTER, program at KBS, which supports Data Nuggets. Schultheis and co-leader, Melissa Kjelvik, developed and run the program, forming partnerships to research and fund the program.

“With our current research, we’re trying to figure out what is the special thing that’s really resonating with students in terms of the role models,” Kjelvik said.

“Our research will investigate how and why role models are critically important for students,” said Cissy Ballen. Ballen is an associate professor in the Department of Biological Sciences at Auburn, the lead institution on the NSF grant, which builds on the past success of Data Nuggets and will help ensure its future impact.

“The theory behind this is that students must be able to see a scientist’s success as attainable to relate to that scientist,” Ballen said. “My prediction is that students will find success most relatable when they see some scientists, like them, have struggled with science, but then were able to overcome that struggle.” 

Elizabeth Schultheis (right) and Melissa Kjelvik (left) lead the Data Nuggets program at Michigan State University’s W.K. Kellogg Biological Station.
Elizabeth Schultheis (right) and Melissa Kjelvik (left) lead the Data Nuggets program at Michigan State University’s W.K. Kellogg Biological Station.

Making data talk

Many students’ eyes gloss over when they hear terms like “data” or “science.” 

Even Schultheis admits she didn’t appreciate the significance of data until she was a grad student collecting her own. The problem, she said, is that kids are often taught how to make a graph, for example, but not why.

“I never really learned to care until I understood the reason I make a graph is because I want to answer a question,” Schultheis explained. “I need to see the data, what it looks like. And that’s why I make a graph.” 

Data Nuggets doesn’t change the skills that are taught in conventional curricula. Students still learn how to make and label axes, for example, and then how to plot data to create graphs. But they also get a more immersive introduction into why real people use these skills.

“Our purpose with these Data Nuggets modules is that everything is always given real context and always in service of a scientific question,” Schultheis said. “It’s always: Here’s a scientist. Here’s the question that they really care about and the reason they collected this data is because they want to answer this question. And you make the graph to visualize it so that you can see what the data is telling you.”

Data Nugget activities come in four levels, so instructors can use the ones best suited for their specific classes. Level 4 activities are designed for high schoolers and undergraduates, while level 1 activities are appropriate for elementary schools and higher grades looking for a refresher after a summer break, for example.

Teachers also have flexibility with how to present an activity based on their goals. For example, instructors can choose activities with completed graphs so students can focus on interpreting what they see to answer questions.

Or students can be given blank grids to give them experience in creating useful representations of data from scratch.

Connie High, a science teacher at Delton Kellogg High School about five miles from KBS, calls Data Nuggets “a game changer.”  

She said that her students, when they’re new to Data Nuggets, can usually make claims and find supporting evidence. The challenge is learning how to articulate the connection between the two.

“They really struggle with how to link claim, evidence and reasoning. They tend to just restate the evidence again,” High said. 

“With Data Nuggets, we definitely see an improvement from the beginning of the year to the end.” 

Humanizing data 

The Data Nuggets program started 13 years ago as a grassroots collaboration between KBS researchers — including Schultheis and Kjelvik, who were then grad students at KBS — and K-12 teachers, including High. 

More than 120 scientists have contributed more than 120 data literacy activities since then. Tens of thousands of people regularly use the Data Nuggets website. Links to various Data Nuggets stories can even be found in science textbooks. 

“Long-term relationship building is why we got such good insights from teachers about what their students needed, because they already had trust with us, and we went into their classrooms and learned from them,” Schultheis said. “And building relationships with scientists who trust us to tell their stories correctly, who are giving their own stories for students to read and learn about, continues to be critical to our success.”

But exactly how to best package and present the data stories falls to Schultheis and her colleagues. Previous research has supported the idea that focusing on the scientist and why they collected the data is essential. After all, data is just numbers. It’s human interaction that puts numbers in perspective, gives the scientific question context and engages students in the activity.

“Humanizing the data is at the crux of this work,” Ballen said. “Data Nuggets is such a successful resource because of the way they humanize the data component and contextualize it within the science itself and show that it’s being done by relatable scientists. They do that really well.”

With its third round of NSF funding, Data Nuggets is attempting to fine-tune how to best present the scientist role models and the stories to improve student engagement with science even more.

The goal is not only to increase the portrayal of under-represented groups among scientist contributors, but also for students to see that they share some things in common with the scientists they see. 

“We used to ask students to draw what a scientist looks like, and they all would draw someone who looks like Albert Einstein,” High said. “It’s incredibly important that they see there are scientists who look like them.”

“You can imagine if you were a student sitting in a classroom you might get an activity that features a scientist from a prestigious university with awards and that sort of thing, and that might not be very relatable,” Ballen said. “Success might not be perceived as attainable.”

Data Nuggets is working to combat that perception.

For example, there’s a Data Nugget called “Trees and the City”, featuring a photo of a smiling University of Minnesota ecologist named Adrienne Keller wearing a bike helmet and sunglasses. A video shows Keller riding her bike through neighborhoods in the Twin Cities as she describes her interest in tree patterns. She poses her dataset’s main question: “Are there differences in the total canopy cover or the number of tree species planted in a neighborhood based on residents’ income level or percentage of BIPOC — Black, Indigenous, and People of Color — residents?”

Another Data Nugget was written by a community scientist from Bayfield, Wisconsin, located on the south shore of Lake Superior. He’s pictured wearing shorts and gym shoes as he stands on ice. 

For his Nugget, he used historical data to answer his question if the winters were getting shorter and changing the dynamics of how people could travel in the area. 

He also happened to be a high school student.

“That’s the dream outcome,” Schultheis said, “that students realize how powerful data are, and they can be advocates for themselves and their communities because they can actually go to the source of information and ask and answer questions.” 

This story was written by Lynn Waldsmith, and was originally posted on the Michigan State University, College of Natural Science website here.

6.7.24

Seagrass survival in a super salty lagoon

A researcher in the Dunton Lab measures seagrasses underwater using a mask, snorkel, and a white PVC quadrat.

The activities are as follows:

Seagrasses are a group of plants that can live completely submerged underwater. They grow in the salty waters along coastal areas. Seagrasses are important because they provide a lot of benefits for other species. Like land plants, seagrasses use sunlight and carbon dioxide to grow and produce oxygen in a process called photosynthesis. The oxygen is then used by other organisms, such as animals, for respiration. Other organisms use seagrasses for food and habitat. Seagrass roots hold sediments in place, creating a more stable ocean bottom. In addition, the presence of seagrasses in coastal areas slows down waves and absorbs some of the energy, protecting shorelines.

Unfortunately, seagrasses are disappearing worldwide. Some reasons include damage from boats, disease, environmental changes, and storms. Seagrasses are sensitive to changes in their environment because they have particular conditions that they prefer. Temperature and light levels control how fast the plants can grow while salinity levels can limit their growth. Therefore, it is important to understand how these conditions are changing so that we can predict how seagrass communities might change as well.

Ken is a plant ecologist who has been monitoring seagrasses in southern Texas for over 30 years! Because of his long-term monitoring of the seagrasses in this area, Ken noticed that some seagrass species seemed to be in decline. Kyle started working with Ken during graduate school and wanted to understand more about what environmental conditions might have caused these changes. 

Manatee grass (Syringodium filiforme) located within the Upper Laguna Madre.

Texas has more seagrasses than almost any other state, and most of these plants are found in a place called Laguna Madre. During his yearly seagrass monitoring, Ken noticed that from 2012 – 2014 one of the common seagrasses, called manatee grass, died at many locations across Laguna Madre. Since then, the seagrass has grown back in some places, but not others. Kyle thought this would be an opportunity to look back at the long-term dataset that Ken has been collecting to see if there are any trends in environmental conditions in years with seagrass declines.

Each year, Ken, Kyle, and other scientists follow the same research protocols to collect data to monitor Laguna Madre meadows. Seagrass sampling takes place 2 – 4 times a year, even in winter! To find the manatee grass density, scientists dig out a 78.5 cm2 circular section (10 cm diameter) of the seagrass bed while snorkeling. They then bring samples back to the lab and count the number of seagrasses. While they are in the field, they also measure environmental conditions, like water temperature and salinity. A sensor is left in the meadow that continuously measures the amount of light that reaches the depth of the seagrass.

Kyle used data from this long-term monitoring to investigate his question about how environmental conditions may have impacted manatee grass. For each variable, he calculated the average across the sampling dates to obtain one value for that year. He wanted to compare manatee grass density with salinity, water temperature, and light levels that reach manatee grass. He thought there could be trends in environmental conditions in the years that manatee grass had low or high densities.

Featured scientists: Kyle Capistrant-Fossa (he/him) & Ken Dunton (he/him) from the U-Texas at Austin

Flesch–Kincaid Reading Grade Level 9.8

Additional teacher resources related to this Data Nugget:

There is another Data Nugget that looks at these seagrass meadows! Follow Megan and Kevin as they look at how photosynthesis can be monitored through the sound of bubbles and the acoustic data they produce.

Follow this link for more information on the Texas Seagrass Monitoring Program, including additional datasets to examine with students.

There are articles in peer-reviewed scientific journals related to this research, including:

National Park Service information about the Gulf Coast Inventory and Monitoring.

Texas Parks and Wildlife information on seagrass:

5.1.24

Auburn and MSU collaborate on NSF IUSE grant to determine what makes an effective scientific role model

Members of the Auburn and MSU research team sharing a meal.

Scientific role models increase student success in their science courses as well as inspire students to pursue science careers. The Ballen Lab at Auburn University has completed significant research demonstrating that role models with diverse identities are lacking in undergraduate biology classrooms. Students with identities that are not represented in their undergraduate science courses do not have many opportunities to see themselves in science careers and as scientific leaders.

“I am excited to collaborate with researchers at Michigan State University to identify factors that improve equity and success in undergraduate STEM education. Our research will investigate how and why role models are critically important for students,” said Cissy Ballen, associate professor in the Department of Biological Sciences.

The collaborative team, led by Ballen at Auburn and Elizabeth Schultheis at MSU, was awarded $1.5 million from the National Science Foundation’s Division of Undergraduate Education.

Robin Costello, a postdoctoral scientist in the Ballen Lab working to understand the relationship between role models and successful student outcomes, explained, “Featuring relatable scientist role models in classroom materials is a low-cost and accessible way to increase the recruitment and persistence of students with identities historically and currently excluded from STEM.”

The research team’s recent research showed a direct correlation between relating to scientific role models and student engagement. “These results led to more questions about the critical features of scientist role models that make them effective and served as the foundation for the recently awarded project,” Ballen explained. “Theory makes several predictions about why and how role models are critical to student success. With this support from NSF, we will conduct critical research that tests theory on what makes an effective role model.”

Costello added, “Our research will specifically explore how to tell scientists role model stories in ways that improve student outcomes.” The project is entitled “Collaborative Research: Sharing Scientist Role Model Stories to Improve Equity and Success in Undergraduate STEM Education.”

“Several popular resources have been created to combat the pervasiveness of the stereotypical scientist in biology and STEM curricular materials,” Ballen added. An important long-term result of the project are free, open-source materials for educators to use in their classrooms to nurture more inclusive environments where students can learn from a wide array of STEM leaders to whom they can relate.

These resources will develop biology data literacy curricular materials that teach quantitative skills while simultaneously highlighting the diversity of scientists in STEM. These resources will be based on two well-known educational resources: Data Nuggets, resources that are developed in a partnership between scientists and teachers, and Project Biodiversify, a site that offers education tools for diversity and inclusion in biology classrooms.

Our team will be recruiting instructors to implement the activities in classrooms. If you are interested in participating in this project, please contact mjb0100@auburn.edu. For the original story, written by Maria Gebhardt, visit the Auburn page here.

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