Data explorations in ecology: salt pollution as a case study for teaching data literacy.
Does working with first- and second-hand ecological data improve
students' knowledge of ecological ideas, motivation and engagement
in science, data exploration, and citizenship skills (students'
ability to make informed decisions)? We have been exploring this
question with high school science teachers in New York State for the
past year using a framework that targets key concepts and skills in data
exploration. Here, we share one curriculum unit as a model for
integrating quantitative reasoning skills into the ecology classroom.
Key Words: Pollution; data exploration; salt; investigation.
|Article Type:||Case study|
Ecology (Study and teaching)
Literacy (Study and teaching)
Literacy (New York)
Berkowitz, Alan R.
|Publication:||Name: The American Biology Teacher Publisher: National Association of Biology Teachers Audience: Academic; Professional Format: Magazine/Journal Subject: Biological sciences; Education Copyright: COPYRIGHT 2012 National Association of Biology Teachers ISSN: 0002-7685|
|Issue:||Date: Sept, 2012 Source Volume: 74 Source Issue: 7|
|Topic:||Computer Subject: CD-ROM catalog; CD-ROM database; Database|
|Geographic:||Geographic Scope: New York Geographic Code: 1U2NY New York|
We all know that students enjoy doing hands-on experiments, going outside to collect data, and working in small groups to answer a scientific question. There is also a lot of research to support doing just that--with benefits including improved student engagement, motivation, and content knowledge (Taylor et al., 2001; Powers, 2004; Louv, 2005; Taylor & Kuo, 2009). However, there are a variety of limitations to conducting classroom (or outdoor) investigations in the regular science classroom, making it challenging for students to draw informed conclusions based on sufficient evidence (Gruenewald, 2003). Specifically in ecology classes, students often conduct investigations that tell them about the health of a stream, a forest, or a field through a "snapshot" of data, because time, the structure of the school day, and funds often limit teachers' ability to carry out long-term, large-scale investigations (Samuel, 1993; Grandy & Duschl, 2007; Hume & Coll, 2008). We may ask students to consider what they would do if they had more time or money to conduct a more scientifically sound study, but when students complete a lab report based on their work, they are left with inadequate amounts of evidence and often draw sweeping generalizations that cannot be supported by their data. Data analysis becomes equated with visually interpreting graphs instead of focusing on key components of data interpretation, such as how variability affects one's ability to support a claim. Using second-hand data, increasingly available for many environmental parameters and in many locations, provides teachers with the possibility of extending first-hand data for improved validity and confidence.
For the past year, we have been working in a collaborative team of teachers, educators, and scientists to examine whether using a combination of first- and second-hand data in ecology lessons improves students' learning, motivation, and citizenship (the ability of students to make informed decisions), and whether students can use specific data-analysis skills to make and evaluate claims. "First-hand data" refers to data that students themselves have collected, while secondhand data comes from outside sources (Hug & McNeill, 2008). In order to help students understand how to move from collecting data to making or critiquing a claim, we have designed a unit that walks students through well-defined steps of data exploration, integrating second-hand data. When scientists conduct research, they move along a continuum from raw data to arguments, integrating analysis of their own data and consideration of others' data and representations along the way (Figure 1). Students, however, usually jump back and forth along this data pathway without a clear understanding of the benefits and limitations of their own, or of others', work. Our approach with teachers and students is to be clear and explicit about where you are along this pathway at any given stage of inquiry or critique. In this article, we explain our curriculum unit and our current efforts to integrate data literacy into an ecology context.
* Why Salt Pollution?
We chose to focus our unit on the problem of salt pollution in aquatic ecosystems, because the Cary Institute has been involved in a long-term study to monitor the increase of sodium chloride in our local stream over the past 25 years (Figure 2). Sodium is less of a problem for organisms, but chloride can be more harmful. Unfortunately, chloride levels have increased in local streams throughout our region, and in many parts of the country, as municipalities treat increasing numbers of roadways with salt during the winter months. Sodium chloride accumulates in groundwater over time and is released into streams even during the summer, when groundwater plays a crucial role in supplying water flow. So, despite the fact that salt is spread in the winter, it is a problem all year, and if current trends continue, many parts of the Northeast will have streams with water that is unfit for human consumption and is toxic to freshwater life within the next century (Kaushal et al., 2005). In addition to being a compelling environmental story, testing for conductivity as a measurement for chloride is relatively easy for students with a PASCO or Vernier probe, and samples can be taken from water bodies and stored conveniently for testing at a later date. Long-term data on chloride levels in a number of streams in our region made it possible to provide second-hand data for the Salt Pollution Unit. However, this unit can also be completed with local conductivity measurements, which are often more readily available than chloride data. This unit is a multiday emersion in data exploration that weaves together outdoor (first-hand) data collection, evaluating second-hand data, a laboratory investigation, and support for student learning and assessment. The unit follows the 5E (Engage, Explore, Explain, Extend, and Evaluate) curriculum format and is described in the corresponding sections.
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For a list of all of the materials used in this unit, please see the complete lesson-plan packet (listed in Resources).
To begin the unit, pass around a jar of water from your school's tap, and ask students whether they think the water is clean or dirty many refuse to drink school water because they think it is "dirty" or "tastes bad." Ask students to explain how they know a water sample is polluted if it is clear--does a color, smell, or taste indicate a problem? Pointing out that students swim in the ocean but don't drink it encourages them to think more clearly about pollution and the fact that you can't always "see" polluted water, and at the same time allows for a discussion about tolerance levels for organisms adapted to live in different types of water bodies. Frame the unit by telling students they will be investigating whether local streams are polluted by salt, and ask them to brainstorm ways in which salt might enter into waterways.
It is best to go outside with students to test for conductivity at a local stream, pond, or lake (Figure 3). Ideally, conduct multiple and repeated tests, considering your sampling design and the idea of replication. If you can't go outside, students can bring in water samples from home. At this point, students may not understand what they are testing for, or why, but this initial step encourages inquiry by asking students to make sense of the investigation. Back in the classroom, allow students time to test bottled water or water from their home taps for conductivity, and try "spiking" water with different amounts of salt to see how conductivity responds. There are some readings and activities in the lesson materials to help students gain background knowledge in salt pollution and conductivity. Students use an equation to convert from conductivity to chloride that was derived for each stream (you can also use a standard conversion equation, although this may affect your end result; see Figure 4). Using a table (we call it the Salt Tolerance Reference Table, and it is available in the student handouts in Resources) that generalizes the consequences of different levels of conductivity and chloride, students can make claims about whether the stream they tested is dangerous to aquatic life.
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Instruct students to graph both their individual and class data, and use the lesson prompts to discuss the variability around the class average, sources of error, sampling effects and limitations, and scale. We have found that focusing on sources of error, both natural (from the ecosystem) and induced (human error, sampling error, etc.), helps clarify the sources of variability for students. Students are challenged to answer the questions, "What is our best estimate of the current chloride level in the water body we sampled?", "How confident are we in this estimate?", and "Can we use these results to estimate chloride levels in other parts of the water body and/or other sampling times?"
Now students are ready for secondary data, ideally from the same waterbody and watershed from which their original samples came. By comparing their data with scientists' data, students begin to think about the reasons why the two data sets might be different, what sort of trend (if any) is evident in the longer data set, and where their individual data fit. Stop at this point and ask students to explain the importance of long-term data. Long-term data sets allow us to see both slow trends and rare but sudden ones, and help us see patterns when there is a lot of variability. If students are unclear about the benefits, there are some examples available (see Resources section) such as the Keeling curve or the changes in the response of populations in the Hudson River to the zebra mussel invasion. The data collected over the years at Mauna Loa, called the Keeling curve, demonstrates the way in which patterns emerge despite variability if enough data are collected, and the Hudson River data explore the importance of observing changes in a population over a long period. We have noticed that variability is a difficult, and often overlooked, component of exploring data. "Cherry picking" of scientific data often occurs in the popular media, which results in claims based on incomplete evidence, and we hope that drawing attention to the importance of variability will help students pay attention to this problem.
Next, students conduct a toxicity bioassay using either duckweed or Daphnia magna (Figure 5) to learn how much salt can be tolerated by aquatic organisms. Not only does this give students another opportunity to collect, display, and analyze their own data, it also gives them time to think about how interpretation of graphs changes when you graph all your data versus an average. Remind students of the Salt Pollution Reference Table used in the first lesson, which will help them evaluate the range of toxicity present in their investigation as well as in freshwater ecosystems.
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In the final lesson, students explore the ways in which groundwater levels change across the seasons, comparing summer and winter data. Using the secondary data that highlight this seasonal change, help students see that they can look at chloride data over various time scales--over multiple years, as they did earlier, and over seasons. Visuals help show that lower streamflow in the summer can contribute to higher concentrations of sodium chloride, which seems counterintuitive at first. Because many students don't realize why there is less water in streams in the summer, check for this understanding by asking, "In our region, why is streamflow lower in the summer?" Students usually think there is less rainfall, but when given data that show there is more rainfall in the summer in the Northeast, they can come to understand that transpiration by trees and other vegetation results in reduced run-off and groundwater recharge, leading to lower streamflows (Figure 6).
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Groundwater is a difficult concept for students, so check for understanding about groundwater movement and try one of the demonstrations if students are unable to explain how water moves through soil (see Figure 7). After discussing streamflow changes during the course of a year, students think about why sodium chloride levels might increase in the summer. Students familiar with saltwater aquaria may recognize that as water evaporates from the tank, the salinity of the water will go up. A simple demonstration can help students visualize this idea (see Figure 7).
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Once students have investigated groundwater and salt accumulation in groundwater, they use an aerial photo from the watershed they studied (from Google Earth) along with an aerial photo of a comparison watershed to estimate development in each watershed. From the readings and discussions earlier in the unit, students already have some ideas about where salt pollution comes from. In our unit, we use the East Branch of the Wappinger Creek as our comparison watershed because we have a long-term record of chloride in the stream (Figure 2) and have access to land-use data for the watershed (see Figure 8). Maps and statistics about development and impervious surfaces are available online for the entire Hudson River Watershed, and for many other watersheds around the United States (see Resources).
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Students hypothesize about the impact of development on water quality, specifically as related to salt pollution, and discuss how the increase in roads and impermeable surfaces might be affecting the changes observed in chloride. Salt pollution doesn't come only from roads, but also from leaking septic systems, water softeners, and natural weathering. Finally, students compare land-use data from several watersheds in our region with chloride changes, and discuss whether the amount of impervious surfaces in each watershed may be related to the observed changes in chloride. Although the watershed with the highest percentage of impervious surfaces had the highest chloride levels, as expected, there were large increases in most watersheds over the past 50 years (Figure 9) that reflect increases in impervious surfaces region-wide. Students are asked to think critically about the information that is presented to them, to consider issues such as sampling effort and frequency, and to predict changes in chloride levels in the future.
More advanced students can calculate a sodium chloride budget for the Wappinger Creek, since we have both input values to the watershed and export values from the stream. This quantitative extension demonstrates that there is a lot more salt going into the watershed (based on estimates of road salt applications, sewage leakage, and water softener use) than is measured in the stream itself, indicating that some of the sodium chloride is stored in groundwater. This extension is included in the AP lesson materials available on the website.
Students' thinking and growth are assessed throughout the lesson for various key concepts of data exploration, such as the implications of variability, sources of error, the strengths and limitations of different kinds of graphs, and the tradeoffs with sampling effort and extent. We have posted examples of specific assessment questions on our website, and many of these questions can be revised for use in any science investigation. As students finish the salt pollution module, we ask them to predict what will happen to salt levels in local streams over the course of the next 50 years, and whether local governments should try to reduce the use of salt on our roads. As with many environmental problems, salt is almost impossible to remove from an ecosystem once it is there, and we hope that this lesson encourages students to think about the consequences of adding a substance to the environment that may have long-lasting, and unintended, consequences.
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One school we worked with used the salt pollution module as a jumping-off place for a student action project that ultimately won the group a prize in the 2011-2012 Lexus Land/Water Environmental Challenge. Students continued to measure their local stream over time, documented high levels of chloride, contacted local authorities to suggest alternatives to road salt, and met with their school's director of buildings and grounds, who was ultimately convinced to switch from using road salt on the parking lots of the school building to using more environmentally friendly products (Figure 10). We encourage everyone using or adapting our model to consider challenging students to make this kind of application to solving real-world problems.
This work is funded by the National Science Foundation's Discovery K-12 Exploratory research program, NSF Award 1020186. We thank Vicky Kelly for assistance in creating the PowerPoint slides and providing data for the lesson. Stuart Findlay and Dave Strayer also assisted in providing data and reviewing materials. Maribel Pregnall and her students at Arlington High School piloted the first version of this curriculum and provided the photos for this article.
** The current version of this lesson and accompanying materials (including sample student assessment questions and examples of long-term data sets) can be found at https://sites.google.com/ site/teachingecosystemliteracy/Home/deep.
** The MetEd website has great visuals on understanding the hydrological cycle, groundwater, and watersheds: https://www. meted.ucar.edu/.
** Land-use data for the entire Hudson River watershed is available online at http://www.hudsonwatershed.org/atlas/index. html.
** The U.S. Geological Survey has data for many places around the country, showing both surface-water and groundwater discharge and contaminants: http://wdr.water.usgs.gov/adrgmap/.
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CORNELIA HARRIS is Education Program Leader, ALAN R. BERKOWITZ is Head of the Education Program, and ANGELITA ALVARADO is Program Leader for Ecology Education Research, all at the Cary Institute of Ecosystem Studies, PO Box AB, 2801 Sharon Turnpike, Millbrook, NY 12545-0178.
Figure 4. Conversion from conductivity to chloride. The conversion equation between conductivity (measured in [micro]S/cm) and chloride (mg/L) varies between locations, so the best method for developing an accurate equation is to obtain a water sample and use calibrated conductivity and chloride probes to determine a standard relationship. Although you can simply measure conductivity and use that to conduct the entire activity, most scientific studies evaluate chloride. Chloride test kits are also available. An example equation for a local stream system is as follows: chloride = (conductivity * 0.334) - 151.27
Figure 7. Understanding salt pollution and groundwater. Groundwater is difficult for students to understand. In addition to the following demonstration, we often show visuals from the MetEd website (see Resources), or use a groundwater model. Add water to a pot of soil (make sure the pot doesn't have a hole in the bottom), and ask students to diagram what happens to the water that falls on the surface of the soil. Diagrams can be done on individual whiteboards or in students' notebooks; however, check to make sure that students illustrate both infiltration and evaporation pathways. Then ask students to use a different colored pen to diagram what happens if salt water is added to the soil. Students should recognize that when the water evaporates, the salt is left behind in the salty water that is now "groundwater." Ask students to pretend that the pot of soil is the ground, and ask them to imagine what happens when water is continuously added to the system. This is "groundwater," which adds to stream flow. Ask students to think about what happens to the salt that is in groundwater--where does it go? How does the salty water move from the groundwater into the stream?
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