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

Many species' life cycles are strongly influenced by temperature, but other cues, like day length and precipitation, can also trigger life cycle changes. Phenology is a way of recording the time when events, like bud break or insect emergence, occur, and these events can be important for everything from predicting the timing of disease or insect outbreaks to predicting the impacts of climate change on particular species. This activity explores the question: which species will be most affected by temperature changes, and how will changes in the phenology of one species affect its interaction with others as the climate warms.

Strengths of Module

This activity was used as a precursor to reading some scientific papers: Bartomeus et al., 2011, PNAS, and Kudo and Cooper, 2019, Proc. R. Soc. B. Students should be able to interpret figures in the papers similar to the ones they've made, to compare the R² values and think more about data reliability.

What does success look like

Through this module, students should develop data analysis skills that help them to evaluate the relationship between a variety of temperature-related environmental cues and a taxa's phenology. In the context of climate change, they will be able to make an argument using data about whether changing temperatures are likely to impact the phenology of a particular species of interest. They will compare the results using different subsets of a large dataset and make decisions about how to create subsets of data for the analyses they plan to complete. Students will able to compare the strength of the association between temperature/climate-related variables and phenology for different species. To achieve these goals, students will develop abilities to generate, read, and evaluate scatterplots and regressions between sets of variables. They will also develop capabilities to select and download data for their species of choice from the National Phenology Network (NPN) and organize the data for analysis.

Context for Use

Description and Teaching Materials

Why this Matters:

Quick outline/overview of the activities in this module

• Pre-module work: Orientation to phenology, the national phenology network, and regression.
• Activity A: Determine whether there is a detectable trend in bumblebee emergence date in the Spring over time.
• Activity B: Compare the date of bumblebee emergence with a variety of temperature-related site traits, including: latitude, elevation, and Winter and Spring max/min temperatures using scatterplots and regressions.
• Activity C: Choose a species of interest to you, select data from the NPN network, and identify which variables are most predictive of emergence date. Compare your results with those from other species to predict which species are likely to be most susceptible to temperature changes and to consider whether interacting species will respond asynchronously or in parallel.

Activity A

In this lesson, students manipulate data to make and interpret scatterplot graphs and regressions about the phenology of bumblebees and other organisms. They will make decisions about which data to use, and evaluate their confidence in their conclusions given the nature of the available data.

Activity B

In activity A, students tested change over time, it is uncertain if changing climate is responsible for the patterns observed. In activity B, students use environmental data recorded for each site to identify how much variation in bumblebee emergence phenology is explained by temperature or other climate-related variables.

Activity C

In activity C, students use a species of interest to them, identify the variables that are predictive of emergence date, then compare with other species to determine which is most susceptible to changing temperatures and if and how species interactions will be influenced.

Teaching Materials:

• Instructor's Manual -- educator-only file

• Instructor's Power point (PowerPoint 2007 (.pptx) 6.2MB Jan4 21)
• Pre-Module Handout (Microsoft Word 2007 (.docx) 16kB Jan4 21)
• Student Handout (Word) (Microsoft Word 2007 (.docx) 74kB Jan4 21) / Student Handout (PDF) (Acrobat (PDF) 123kB Jan4 21)
• Dataset
  • Data for Activity A: Phenology_v_time.xlsx (Excel 2007 (.xlsx) 13kB Jan4 21)
  • Data for Activity B: Phenology Regression.xlsx (Excel 2007 (.xlsx) 105kB Jan4 21)

Teaching Notes and Tips

Workflow of this module:

Type how the activity is laid out -- e.g.

1. Assign any pre-class readings
2. Give students their handout when they arrive to class
3. Instructor gives brief PowerPoint presentation with background material. Discussion of the readings can be integrated into this presentation or done before.
4. Students can then work through the module activities.

Notes on the student handout:

Potential pre-class readings:

Measures of Student Success

Success is shown if:

• Students can create, compare, and interpret scatterplots and correlations between pairs of variables.
• Students can select, download, clean, and analyze data from the NPN network that is relevant for answering their questions.
• Students can articulate the relationship between temperature, environmental cues, and a taxon's phenology, and use these relationships to predict how the taxon will be affected by climate change.

Cite this work