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Phenology Trends and Climate Change in Minnesota (Project EDDIE): A focus on American elm

Author(s): Kristine Hopfensperger

Northern Kentucky University

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Summary:
In this module, students will practice answering a specific question about how climate change has affected flowering date in American elm trees.

Description

Project EDDIE Environmental Data-Driven Inquiry & Exploration) is a community effort aimed at developing teaching resources and instructors that address quantitative reasoning and scientific concepts using open inquiry of publicly available data. Project EDDIE modules are designed with an A-B-C structure to make them flexible and adaptable to a range of student levels and course structures.

Summary

Seasonal events, for example flowering, fruiting, and the return of migrating birds, happen at particular times of the year. Some of these events happen in relation to climate, while others are dependent on other factors. As the climate changes, the timing of some events may change in some species. This exercise will help students evaluate how climate change has already affected species in Minnesota.

The American elm (Ulmus americana) is a deciduous species, and its range includes most of the eastern United States and a bit of southeast Canada. This elm is a hardy species and can grow to a considerable size. It grows well in urban areas, so it is common in many cities. Unfortunately, the species is also susceptible to Dutch elm disease and the tree populations can suffer from massive die offs. All of these characteristics have led naturalists to be interested in this species, so we have lots of data about its phenophases.

In this module, students will practice answering a specific question about how climate change has affected flowering date in American elm trees. Students will learn to manipulate the elm data set, build graphs, and analyze the data with a regression. 

Strengths of Module

Students with little experience with spreadsheets, data manipulation, and graphing find the module an accessible way to build confidence in these skills. It also allows them the chance to practice approximating trends and quantifying trends. Students practice quantitative skills and investigate the effects of climate change when they use figures they created.

What does success look like

Students should be able to:

  • formulate an answerable question from a given data set
  • demonstrate basic Excel skills (e.g. sort/filter, seek, graph)
  • analyze phenological data to determine trends
  • run a regression analysis between phenophase and temperature

Context for Use

This module is designed for an introductory-level course with major and non-major students. The exercise assumes no prior knowledge of spreadsheet manipulation, work with large data sets, nor extensive climate change knowledge. The module was designed for an introductory course in environmental science that serves as a gen ed science course and had covered the basics of climate change and reading figures. We used the module to focus on the impact of climate change on organisms.

The module is designed for one class period of 75 min. There was no pre-work assigned; however, students were provided all materials before class if they wanted to spend time reviewing before class. If you are teaching a longer class period or lab, you could introduce the data set the same day and may not need the pre-class assignment (the worksheet can stand alone from the pre-class homework). This adaptation focused on Activities A and B only.

If your institution has a set of computers available for classroom use, you can use those to ensure all students have access to the same software editions. The exercise is functional for those students on a PC or Mac, and for those using Excel or Google Sheets.

Description and Teaching Materials

Why this Matters:

Students will build skills and confidence with spreadsheet manipulation, data analysis and quantitative thinking. The activities also demonstrate how long term data sets are important and can help us determine trends that result from climate change. A focus on species in the state of Minnesota will also highlight that the effects of climate change are visible locally, not only in far off locations.

Quick outline/overview of the activities in this module

  • Pre-module mini lecture: It introduces what phenology is, where the data come from, and what information is contained in the data sets. 
  • Activity A: Determine changes in flowering date for American elm in Ramsey Co, MN
  • Activity B: Determine significance of changes in flowering date

A complete student handout containing the module components and guiding questions is available under Teaching Materials.

Activity A - Determine changes in flowering data for American elm in Ramsey Co

  • Brief discussion of phenology, American elm, formation of answerable questions.
  • Guided class activity to: use the data sheet, isolate data of interest, predict trends, determine trends, and create figures.

Activity B - Determine significance of changes in flowering date

  • Determine if there is a dependent relationship between flowering date and temperature (run regression analysis).
  • Determine how climate has affected the flowering date of American elm.

About the Data Sets:

The MN Phenological Network (https://mnpn.usanpn.org/home) downloadable data set is used with permission from the Minnesota Phenology Network (MNPN, 2020) and was available upon request. The full data set is available in the module. I thank the MNPN for supplying the data and the volunteer participants who gather data for the project.

The DNR website for historical observations from specific locations is: https://arcgis.dnr.state.mn.us/ewr/climatetrends/. Data for American elm and January temperatures (data for Activity A and B) is available in the module.

Teaching Materials:

Teaching Notes and Tips

Workflow of this module:

  1. Give students their handout when they arrive to class.
  2. Instructor gives brief PowerPoint presentation with background material. 
  3. Students work through Activity A.
  4. Instructor gives a primer on regression and students work on Activity B

Notes on the student handout:

The handout may appear long and intimidating to students, but the process is laid out step by step and asks students to repeat/practice certain skills (e.g. building a figure). The handout is a bit dense because it has language for PC and Mac users as well as Excel and Google Sheet users, but it should be accessible to all.

Potential pre-class readings:

Measures of Student Success

How do students self-assess?

How do teachers assess?

Activity A: Students manipulate data in Excel to create a figure of American elm data, and then determine a trend in the flowering date.

Activity B: Students determine if there is a dependent relationship between flowering date and temperature.

References and Resources

Minnesota Department of Natural Resources (DNR). 2020. Minnesota Climate Trends. Accessed [7.10.2020]. Available: https://arcgis.dnr.state.mn.us/ewr/climatetrends/ .

Minnesota Phenology Network (MNPN). 2020. Datasets. Accessed: [7.10.2020]. Available: http://mnpn.usanpn.org.

Notes

I implemented the module into a Intro to Environmental Science course that consists of mostly non-science majors and was taught online due to Covid. With over 50 students, we looked at data throughout the semester with all topics each week; however, the students did not have the opportunity to really play with data themselves in class. I enjoy teaching about climate change and thought this would be a perfect topic to incorporate a hands-on data activity. Most students were appreciative of the hands-on opportunity, but wished it would have been in person instead of online. 

The module was prefaced by several lectures on climate change and its impacts.

I remade the Powerpoint to be accessible to screen readers and I rewrote and reformatted the student instructions document to be more accessible and to fit the online teaching format of the course. 

  • I posted the entire activity ahead of time for students to try it out ahead of time or work ahead. Those students were still be required to attend the class. 

  • I worked through Activity A in class, on Zoom. I shared my screen and walked students through the exercise as they simultaneously complete it on their computers. 

  • Then after a short discussion we did the same for Activity B. For this, I added the temperature data to a worksheet within the master data file to save time and confusion for students.

  • I recorded the class, so students could go back and review. 

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