News & Events | Data Nuggets

1.9.14

Data Nuggets at MSTA Annual Meeting

Data Nuggets will be presented at the Michigan Science Teacher Association (MSTA) 2014 Annual Meeting on March 7th.

To see the event on Facebook, click here.

1.9.14

Does a partner in crime make it easier to invade?

The invasive legume plant, hairy vetch, growing in the field.

The activities are as follows:

A mutualism is a relationship between individuals of two different species in which both partners benefit. One example exists between a type of plant, legumes, and a type of bacteria, rhizobia. Rhizobia live inside bumps on the roots of legumes, called nodules. There, they convert nitrogen from the air into a form that can be used by plants; in return, plants provide the rhizobia with food and protection in the root nodule.

Rhizobia nodules on plant roots. In exchange for carbon and protection in the nodules from plants, rhizobia provide fixed nitrogen for plants.

Mutualisms can affect what happens when a plant is moved to a location where that species hasn’t been before. Invasive plants have been transported by humans from one location to another and grow and spread quickly in their new location. For invasive legumes with rhizobia mutualists, there is a chance that the rhizobia will not be moved with it and the plant will have to form new relationships in the new location. These new partners might work well together or might not. Scientists predict that in their new ranges, invasive legumes will grow poorly at first, and then better and better over time. Over generations, invasive plants and their new rhizobia partners may coevolve to become more efficient mutualism partners.

Yi and Tomomi are scientists who tested this hypothesis using one invasive plant species, hairy vetch. They took soil samples from three different spots based on the invasion history: vetch had never been there (no invasion, 0 years), vetch arrived recently (new invasion, less than 3 years), and vetch invaded a long time ago (old invasion, more than 10 years). These soils had rhizobia in them, each with different histories with hairy vetch. Yi and Tomomi took these soils into the greenhouse, divided them into pots, and grew several hairy vetch plants in each soil type. When the plants had grown for some time in the soils, Yi and Tomomi dug them up and measured two things. First, they counted number of nodules on the roots of each plant, which is a way to see how well the mutualism between rhizobia and plants is going. Second, they dried and weighed the plants to measure biomass, which shows how much the plants were growing.

Featured scientists: REU Yi Liu and Tomomi Suwa from Michigan State University

Flesch–Kincaid Reading Grade Level = 8.2

If you are interested in performing your own classroom experiment using the plant-rhizobium mutualism, check out this paper published in the American Biology Teacher describing methods and a proposed experimental design: Suwa and Williamson 2014

1.8.14

Fair traders or freeloaders?

Measuring chlorophyll content in the greenhouse

The activities are as follows:

When two species do better when they cooperate than they would on their own, the relationship is called a mutualism. One example of a mutualism is the relationship between a type of bacteria, rhizobia, and legume plants. Legumes include plants like peas, beans, soybeans, and clover. Rhizobia live in bumps on the legume roots, where they trade their nitrogen for sugar from the plants. Rhizobia fix nitrogen from the air into a form that plants can use. This means that legumes that have rhizobia living in their roots can get more nitrogen than those that don’t.

Under some conditions, this mutualism can break down. For example, if one of the traded resources is very abundant in the environment. When the plant doesn’t need the nitrogen traded by rhizobia, it doesn’t trade as many sugars to the rhizobia. This could cause the rhizobia to evolve to be less cooperative as well. Less-cooperative rhizobia may be found where the soil already has lots of nitrogen. These less-cooperative bacteria are freeloaders: they fix less nitrogen, but still get sugars from the plant and other benefits of living in nodules on their roots.

Rhizobia nodules on plant roots. In exchange for carbon and protection in the nodules from plants, rhizobia provide fixed nitrogen for plants.

One very important legume crop species is the soybean. Soybeans are used to produce vegetable oil, tofu, soymilk, and many other food products. Soybeans trade with rhizobia for nitrogen, but often farmers add more nitrogen into the field as fertilizer. Since farms use a lot of nitrogen fertilizer, researchers at KBS were interested in how different types of farming affected the plant-rhizobia mutualism.

They grew soybean plants in a greenhouse and added rhizobia from three different farms: a high N farm, low N farm, and organic farm that used no N fertilizer. After four weeks, the researchers measured chlorophyll content of the soybean plants. Healthy plants that have lots of nitrogen will have high chlorophyll content, and plants with not enough nitrogen will have low chlorophyll content. Because high nitrogen could lead to the evolution of less-cooperative rhizobia, they expected that rhizobia from organic plots would be most cooperative. They predicted rhizobia from high N plots would be the least cooperative, and rhizobia from low N plots would fall somewhere in the middle. More-cooperative rhizobia provide more nitrogen, so the researchers expected plants grown with cooperative rhizobia to have higher chlorophyll content than plants receiving less-cooperative rhizobia.

Featured scientist: REU Jennifer Schmidt from the Kellogg Biological Station

Flesch–Kincaid Reading Grade Level = 10.1

For more information on the evolution of cheating rhizobia, check out these popular science articles:

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1.7.14

Cheaters in nature – when is a mutualism not a mutualism?

The activities are as follows:

Mutualisms are a special type of relationship in nature where two species work together and both benefit. Each partner trades with the other species, giving a resource and getting one in return. This cooperation leads to partner species doing better when the other is around, and without their partner, each species would have a harder time getting resources.

One important mutualism is between clover, a type of plant, and rhizobia, a type of bacteria. Rhizobia live in small bumps on the clovers’ roots, called nodules, and receive protection and sugar food from the plant. In return, the rhizobia trade nitrogen to the plant, which plants need to photosynthesize and make new DNA. This mutualism works well when soil nitrogen is rare, because it is hard for the plant to collect enough nitrogen on its own, and the plant must rely on rhizobia to get all the nitrogen it needs. But what happens when humans change the game by fertilizing the soil? When nitrogen is no longer rare, will one partner begin to cheat and no longer act as a mutualist?

Worldwide, the nitrogen cycle is off. Not that long ago, before farmers used industrial fertilizers and people burned fossil fuels, nitrogen was rare in the soil. Today, humans are adding large amounts of nitrogen to soils. The nitrogen that we apply to agricultural fields doesn’t stay on those fields, and nitrogen added to the atmosphere when we burn fossil fuels doesn’t stay by the power plant that generates it. The result is that today, more and more plants have all the nitrogen they need. With high nitrogen, plants may no longer depend on rhizobia to help them get nitrogen. This may cause the plant to trade less with the rhizobia in high nitrogen areas. In response, rhizobia from high nitrogen areas may evolve to try harder to get food from the plant, and may even cheat and become parasitic to plants. If this happens, both species will no longer be acting as mutualists.

When Iniyan was a college student, he wanted to study human impacts on the clover-rhizobia mutualism. To find out more, he contacted Jen Lau’s lab at the Kellogg Biological Station one summer, and joined a team of scientists asking these questions. For his own experiment, Iniyan chose two common species of clover: hybrid clover (Trifolium hybridum) and white clover (Trifolium pretense). He chose these two species because they are often planted by farmers. Iniyan then went out and collected rhizobia from farms where nitrogen had been added in large amounts for many years, and other farms where no nitrogen had been added.

Iniyan completed this research as an REU at KBS.

To make sure that there were no rhizobia already in the soil, Iniyan set up his experiment in a field where no clover had grown before. He then planted 45 individuals of each species in the field. He randomly assigned each plant to one of three treatments. For each species, he grew 15 individuals with rhizobia from high nitrogen farms, and 15 with rhizobia from low nitrogen farms. To serve as a control, he grew the remaining 15 individuals without any rhizobia. To add rhizobia to the plants he made two different mixtures. The first was a mix of rhizobia from high nitrogen farms and water, and the second was a mix of rhizobia from low nitrogen farms and water. He then poured one of these mixtures over each of the plants, depending on which rhizobia treatment they were in. The control plants just got water. No nitrogen was added to the plants.

After the plants grew all summer, Iniyan counted the number of leaves and measured the shoot height (cm) for each individual plant. He did not collect biomass because he wanted to let the plants continue to grow. He then averaged the data from each set of 15 individuals. Plants with fewer leaves and shorter shoots are considered less healthy. He predicted rhizobia that evolved in high nitrogen soils would be worse mutualists to plants, while rhizobia that evolved in low nitrogen soils would be good mutualists.

Featured scientist: REU (NSF Research Experience for Undergraduates) Iniyan Ganesan from the Kellogg Biological Station

Flesch–Kincaid Reading Grade Level = 9.5

For more information on the evolution of cheating rhizobia, check out these popular science articles:

1.7.14

Dangerously bold

An aquarium filled with young bluegill sunfish. Bluegills are a common type of fish that live in freshwater lakes in the eastern United States.

The activities are as follows:

Just as each person has her or his own personality, animals of the same species can behave very differently from one another! For example, pets, like dogs, have different personalities. Some have a lot of energy, some are cuddly, and some like to be alone. Boldness is a recognized behavior that describes whether or not an individual takes risks. Bold individuals take risks while shy individuals do not. The risks animals take have a big impact on their survival and the habitats they choose to search for food.

Bluegill sunfish are a type of fish that lives in freshwater lakes and ponds across the world. Open water and cover are two habitat types where young bluegill are found. The open water habitat in the center of the pond is the best place for bluegill to eat a lot of food. However, the open water is risky and has very few plants or other places to hide. Predators, like large birds, can easily find and eat bluegill in the open water. The cover habitat at the edge of the pond has many plants and places to hide from predators, but it has less food that is best for bluegill to grow fast. Both habitats have costs and benefits—called a tradeoff.

To determine their personality, Melissa observed bluegill sunfish in the aquarium lab.

Melissa is a scientist who is interested in whether differences in young bluegill behavior changes the habitats in which they choose to search for food. First, she looked at whether young bluegill have different personalities by bringing them into an aquarium lab and watching their behavior. Melissa observed that, just like in humans and dogs, bluegill sunfish have different personalities. She noticed that some bluegill took more risks and were bolder than others. Melissa wanted to know if these differences in behavior could also be observed in her experimental pond. She reasoned that being in open water is risky, but results in more access to food. Therefore, bold fish should take more risks and use the open water habitat more than shy fish, giving them more food, allowing them to grow faster and larger, but exposing them to more predation. Just the opposite should be true about shy fish: more time for them in the cover habitat of the pond exposing them to less predation, but also giving them less access to food and an overall smaller body size than bold fish. A tradeoff for both types of fish based on personality.

Melissa designed a study to test the growth and survival of bold and shy fish. When she was watching the fish’s behavior in the lab, she determined if a fish was bold or shy. If a fish took the risk of leaving the safety of the vegetation in a tank so that it could eat food while there was a predator behind a mesh screen, it was called bold. If it did not eat, it was called shy. She marked each fish by clipping the right fin if it was bold or the left fin if it was shy. She placed 100 bold and 100 shy bluegill into an experimental pond with two largemouth bass (predators). The shy and bold fish started the experiment at similar lengths and weights. After two months, she drained the pond and found every bluegill that survived. She recorded whether each fish that survived was bold or shy and measured their growth (length and weight).

Featured scientist: Melissa Kjelvik from Michigan State University

Flesch–Kincaid Reading Grade Level = 7.3

A view of the aquarium tank used to determine fish personality. A largemouth bass is placed to the left of the barrier, while 3 bluegill sunfish are placed to the right. If a sunfish swims out of the vegetation and eats a bloodworm dropped near the predator, it is considered bold.

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1.6.14

Do invasive species escape their enemies?

One of the invasive plants found in the experiment, Dianthus armeria

The activities are as follows:

Invasive species, like zebra mussels and garlic mustard, are species that have been introduced by humans to a new area. Where they invade they cause harm. For example, invasive species outcompete native species and reduce diversity, damage habitats, and interfere with human interests. Damage from invasive species costs the United States over $100 billion per year.

Scientists want to know, what makes an invasive species become such a problem once it is introduced? Is there something that is different for an invasive species compared to native species that have not been moved to a new area? Many things change for an invasive species when it is introduced somewhere new. For example, a plant that is moved across oceans may not bring enemies (like disease, predators, and herbivores) along for the ride. Now that the plant is in a new area with no enemies, it may do very well and become invasive.

Scientists at Michigan State University wanted to test whether invasive species are successful because they have escaped their enemies. They predicted invasive species would get less damage from enemies, compared to native species that still live near to their enemies. If native plants have tons of insects that can eat them, while an invasive plant has few or none, this would support enemy escape explaining invasiveness. However, if researchers find that native and invasive species have the same levels of herbivory, this would no support enemy escape. To test this hypothesis, a lab collected data on invasive and native plant species in Kalamazoo County. They measured how many insects were found on each species of plant, and the percent of leaves that had been damaged by insect herbivores. The data they collected is found below and can be used to test whether invasive plants are successful because they get less damage from insects compared to native plants.

Featured scientist: Elizabeth Schultheis from Michigan State University

Flesch–Kincaid Reading Grade Level = 11.3

For a lesson plan on the Enemy Release Hypothesis, click here.
The Denver Museum of Nature and Science has a short video giving background on invasive species, here.

1.6.14

Do insects prefer local or foreign foods?

One of the invasive plants found in the experiment, Centaurea stoebe.

The activities are as follows:

Insects that feed on plants, called herbivores, can have big effects on how plants grow. Herbivory can change the size and shape of plants, the number of flowers and seeds, and even which plant species can survive in a habitat. A plant with leaves eaten by insect herbivores will likely do worse than a plant that is not eaten.

Plants that naturally grow in an area without human interference are called native plants. When a plant is moved by humans to a new area and lives and grows outside of its natural range, it is called an exotic plant. Sometimes exotic plants become invasive, meaning they grow large and fast, take over habitats, and push out native species. What determines if an exotic species will become invasive? Scientists are very interested in this question. Understanding what makes a species become invasive could help control invasions already underway and prevent new ones in the future.

Because herbivory affects how big and fast a plant can grow, local herbivores may determine if an exotic plant thrives in its new habitat and becomes invasive. Elizabeth, a plant biologist, is fascinated by invasive species and wanted to know why they are able to grow bigger and faster than native and other exotic species. One possibility, she thought, is that invasive species are not recognized by the local insect herbivores as good food sources and thus get less damage from the insects. Escaping herbivory could allow invasive species to grow more and may explain how they become invasive.

To test this hypothesis, Elizabeth planted 25 native, 25 exotic, and 11 invasive species in a field in Michigan. This field was already full of many plants and had many insect herbivores. The experimental plants grew from 2011 to 2013. Each year, Elizabeth measured herbivory on 10 individuals of each of the 61 species, for a total of 610 plants. To measure herbivory, she looked at the leaves on each plant and determined how much of each leaf was eaten by herbivores. She then compared the area that was eaten to the total area of the leaf and calculated the proportion leaf area eaten by herbivores. Elizabeth predicted that invasive species would have a lower proportion of leaf area eaten compared to native and noninvasive exotic plants.

Featured scientist: Elizabeth Schultheis from Michigan State University

Flesch–Kincaid Reading Grade Level = 10.9

There is one scientific paper associated with the data in this Data Nugget. The citation and PDF of the paper is below, as well as a link to access the full dataset from the study:

Schultheis, E.H., A.E. Berardi, and J.A. Lau (2015). No release for the wicked: enemy release is dynamic and not associated with invasiveness. Ecology 96(9) 2446-2457.

Data available from the Dryad Digital Repository

For two lesson plans covering the Enemy Release Hypothesis, click here and here.

Aerial view of the experiments discussed in this activity:

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1.6.14

Data Nuggets: Small activities with big impacts for students

See the original article on the LTER webpage (reproduced below)

The landscape of science education is undergoing a fundamental shift. Updated standards, to be followed by all science teachers in Michigan, emphasize that science is an active process: instead of the memorization of facts in textbooks, students should be taught the ability to generate new knowledge by testing hypotheses and interpreting data. In other words, students should be taught how to use the scientific method and make arguments from evidence. However, with the scientific method comes uncertainty in results. Educators, like K-12 Partnership teacher Connie High (Delton-Kellogg High School), express concern that teachers and their students are not comfortable with the messy data that can result from inquiry, such as results that do not support a hypothesis, or data with lots of variability: “We often found that although lab experiences were fun for students, they lacked skills in summarizing the meaning or goal [of their research]… we needed some data sets for students to practice on.”

As graduate students, we have experienced our fair share of unexpected results and experiments gone awry, and have no problem reassuring teachers that this is nothing to be afraid of. Often, we learn more from data that goes against our original hypothesis, but this can be intimidating in a classroom setting with limited time or ability to conduct follow-up experiments. Because we cannot go into every classroom to share this message, we thought that it would benefit students to work with data collected by scientists, instead of just seeing the polished results presented in textbooks.

Along with other fellows in the K-12 Partnership at KBS, we developed an educational tool aimed to do just that. Data Nuggets are worksheets that give students the chance to work with real data – and all its complexities. Each Data Nugget includes a brief background to a scientist and their study system along with a small, manageable dataset. Students are then given the scientist’s hypothesis and must use the data to construct an argument as to whether the data does or does not support it. One of our priorities has been to provide resources for students of all ages and skill levels because we recognize that students are often overwhelmed with data interpretation. As such, we have created Data Nuggets for students ranging from grades K-16, with varying levels of difficulty. We hope providing this structure will allow teachers to build these skills throughout a student’s entire education, ultimately preparing them for a career in science.

As we present Data Nuggets in classrooms and at national conferences, we continue to get great feedback from teachers on ways to improve the Nuggets and how teachers see them as fitting into their classrooms. “As we get our students ready for ACT testing, Data Nuggets are wonderful sets to use in our classroom because they are relevant and introduce “real” research to our students who might not have this type of exposure otherwise.” (K-12 Partnership teacher Marcia Angle, Lawton Middle School).

Melissa and Liz presenting their research to elementary students.

As scientists, we also see Data Nuggets as a great way to share our research with the public. We have each created Nuggets from our own dissertation data (Liz – invasive species, Melissa – animal behavior). Because we believe Data Nuggets could be a great way for all researchers to communicate their work as scientists, our future plans are to hold workshops to help scientists make Data Nuggets of their own. Communicating science to broad audiences is a skill that is becoming increasingly desirable for acquiring jobs and grants. We think Data Nuggets will help develop these skills in scientists of all disciplines and help them to think broadly about the societal importance of what they do.

Data Nuggets are currently funded by NSF’s BEACON Center for the Study of Evolution in Action, and originated through MSU’s GK-12 program at the Kellogg Biological Station.

12.2.13

BEACON Researchers at Work: Addressing the Next Generation Science Standards

beacon_header

This post is by MSU postdocs Liz Schultheis and Melissa Kjelvik. See the original article on the BEACON webpage (reproduced below):

The current landscape of K-12 science education is shifting – moving away from memorization of science facts to an approach based on the scientific method where students are taught quantitative skills and how to construct arguments from evidence. These skills are increasingly important as technology increases our access to large pools of data that must be quickly interpreted – including hot science topics in the news, such as evolution and climate change. While teachers support the shift, they currently lack the classroom resources necessary to make the change in their classroom. Additionally, teachers are worried about addressing The Next Generation Science Standards (released April 2013) and preparing students according to the ACT Readiness Standards, as both have increased expectations of analytical and quantitative skills for K-12 students. At present, there is no resource available to teachers that allows them to reinforce these skills repeatedly throughout the school year and continuing grade levels, while also covering core content and hitting on all parts of the scientific process.

The BEACON Project has many overlapping goals with the new science standards, and is well situated to help teachers address their concerns. First, an understanding of evolution depends on a student’s analytical and quantitative skill set. Much disbelief about evolution comes, not from a lack of evidence, but the inability of the audience to understand the scientific process and synthesize evidence to make an argument. Second, a multidisciplinary approach is essential when addressing the new science standards, as quantitative skills must be brought to bear on all science topics and be used as a way of thinking, more than just one unit within the curriculum. Third, once students understand scientific principles, such as the evolutionary process or how to ask questions of the natural world, they will be more excited to pursue a scientific career than if they believe science is purely fact memorization. Students will be able to apply these skills to other careers as well – just as programmers and engineers in BEACON use principles of natural selection to design better software and products. To achieve the goals of BEACON and science standards, teachers need a multidisciplinary and versatile tool that closely resembles the actual practice of scientific research and quantitative analysis.

Data Nuggets give students the opportunity to work with real scientific data.

Introducing Data Nuggets

We are currently developing a tool that we think has the potential to address these curriculum changes and BEACON goals: Data Nuggets, which bring data collected by scientists into the classroom, thus giving students the chance to work with real data – and all its complexities. Data Nuggets are worksheets designed to help students practice interpreting quantitative information and make claims based on evidence. The standard format of each Nugget provides a brief background to a researcher and their study system along with a small, manageable dataset. Students are then challenged to answer a scientific question, using the dataset to support their claim, and are guided through the construction of graphs to facilitate data interpretation. Various graphing and content levels allow for differentiated learning for students with any quantitative or science background. Because of their simplicity and flexibility, Data Nuggets can be used throughout the school year and teachers can provide higher graphing levels as students build confidence in their quantitative skills.

Data Nugget History

Utilizing the unique teacher-graduate fellow partnership organized by the Kellogg Biological Station’s GK-12 program, Data Nuggets were created by graduate students in response to discussions with Michigan teachers who expressed concern about students’ ability to make claims based on evidence. When first designing Nuggets, GK-12 fellows held a teacher workshop at KBS to solicit feedback on the structure, organization, and content to make Data Nuggets a teacher and classroom friendly resource that could be used at all grade levels. Teacher feedback continues to be an invaluable component to the development of the Nuggets as we travel to conferences such as ESA Life Discovery and National Association of Biology Teachers. More recently, the Nugget network has expanded beyond GK-12 to include datasets from graduate students, faculty, teachers, and undergraduate researchers at KBS.

The Future of Data Nuggets: Integration of BEACON research

For the next year, we will be supported by BEACON funds to address both the challenges BEACON researchers face when communicating evolution to broad audiences and the lack of education resources available for teachers to teach quantitative skills. Utilizing BEACON’s network and resources we are excited to:

develop and implement an assessment tool documenting the ability of Data Nuggets to improve students’ quantitative skills and understanding of science
provide professional development for BEACON researchers by facilitating workshops at each institution to create Data Nuggets from their research
enhance accessibility of Data Nuggets by creating a user-friendly website and presenting Data Nuggets at teacher conferences.

Coming to a BEACON University Near You: Data Nugget Workshops

We anticipate Nuggets will be a popular tool for academics to share their research with broad audiences. The short, simple Nugget template facilitates the creation of additional worksheets by making the process quick and easy for faculty and graduate students in all disciplines. Researchers who create Nuggets will improve their science communication skills, important when giving talks, writing papers submitting grants. Additionally, graduate students involved in BEACON can make Nuggets on findings from multidisciplinary collaborations, such as connections between evolution and engineering.

We will be organizing workshops at BEACON-affiliated universities to provide the training necessary for BEACON researchers to create a Data Nugget of their own. We will walk through the basic components of the Data Nugget and provide feedback as to the appropriateness of their Nugget for specific grade levels. Additionally, we will reach out to K-12 teachers at schools near each institution to increase awareness of Data Nuggets and invite them to make Data Nuggets of their own.