Biology of Climate Change – Instructor’s Guide

Goals of the Biology of Climate Change Investigation

Build student skills in:

  • interpreting graphical and statistical data,
  • understanding statistical significance and regression,
  • using software (Excel) to plot data and make basic statistical calculations,
  • giving effective oral group presentations,
  • constructing an argument from data.

Data Sets

This exercise is based on: weather and first sightings data collected by billy barr, RMBL accountant, since the early 1970s (view the data here) and the peer-reviewed journal article, Inouye, D.W., Barr, B., Armitage, K.B., and Inouye, B.D (2000) Climate change is affecting altitudinal migrants and hibernating species, Proceedings of the National Academy of Sciences, v. 97, p. 1630-1633 (download the paper here Inouye et al., 2000).

Teaching Strategies

Potential Additional Pre-Reading Assignments for Students

billy barr
billy barr

If you wish to assign some pre-lab reading, the following articles from The Rocky Mountain News may be of interest. A Change in the Airprovides non-technical background on the research in Inouye et al., 2000. In particular, it discusses the difficulty of “proving” that ecosystem change is driven by human-induced climate change. Solitude in the Name of Science provides background on how the daily weather observations and first sightings data were generated and introduces an interesting RMBL personality, billy barr.

Suggestions for Pre- or Post-assignment Lecture Topics and Tools

Explain basic statistics (mean, minimum, maximum, range) and regression analysis (what it is, r-squared, P) and the concept of “statistical significance”. Our page, A Bit About Statistics might help.

Check out the data visualization tool on the Data page – we’ve loaded it with all of billy barr’s first sightings observations as well as climate summaries. This tool could be useful as a demonstration during lecture or as a first step for students to become familiarized with the data.

Students have told us that the snow pack video was very interesting and gave them an improved sense of just how much snow really falls in this area!

If you decide to play the audio interview from Colorado Public Radio during class, you may wish to project a slideshow for a visual component. Try Sarah Rudeen’s slides (below) of RMBL plants, animals, and landscapes.

Also, consider using the Warming Meadow Experiment module as a follow up to the Biology of Climate Change.

Instructional Strategies Behind Activities

Part I, reproducing the plots in the paper with new data, is intended to get students familiar with Excel, seeing patterns in data, and using metadata. We recommend that you place students in small groups (2-3 students) because many introductory students are not proficient with Excel and may benefit from working with a partner. Also, working in small groups can help boost confidence in analyzing data and presenting to the class.

Part II, describing how new plots differ from the original plots, forces students to analyze data and link data to the natural and changing world. We recommend having the small groups report their findings to the class, which encourages students to take ownership of some part of the data. If students are assigned a written report, you could consider having each student evaluate and summarize the interpretations of all groups.

Before students get started on Part III, the more open-ended inquiry, instructors might lead students in thinking about some answerable questions (Socratic questioning). For example, do all migrating birds arrive in Gothic at same time? Will all hibernating rodents show the same relationship with snow melt date? Do all mammals near Gothic hibernate? The data visualization tool on the Data page could help students generate their own questions.

Again, for students with less experience in data analysis, students could work in small groups, presenting their graph(s), accompanying statistics, and interpretations to the class. Groups will benefit from assistance in interpreting their data and forming a sound scientific argument based on evidence.