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.
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: Based on observations of bumblebee phenology, are bumblebees in the western United States behaving differently from 2011 to 2019? What climate variables may help explain bumblebee activity? (Only Part A and B)
What does success look like
Through this module, students explore 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 climate variables are likely to impact bumblebee phenology. Students compare the strength of the association between temperature/climate-related variables and bumblebee phenology. To achieve these goals, students will develop abilities to generate, read, and evaluate scatterplots and regressions between sets of variables.
Context for Use
Description and Teaching Materials
Quick outline/overview of the activities in this module
- Pre-module work: Orientation to phenology, the national phenology network, and regression. (In this adaptation, I did this through direct instruction in our large lecture setting).
- Activity A: Determine whether there is a detectable trend in bumblebee emergence date in the Spring over time. (In this adaptation, I created a dataset from the National Phenology Network that included states in the west.)
- 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. (In this adaptatoin, students used CODAP https://codap.concord.org/ to explore the dataset through scatterplots).
- 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. (In this adaptation, this was an optional assignment students could choose to do on their own).
In this lesson, students manipulate data to make and interpret scatterplot graphs and regressions about the phenology of bumblebees. They will make inferences from their evidence, and evaluate their confidence in their conclusions given the nature of the available data.
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.
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.
Adapted Teaching Materials:
Pre-Module Slides for Lecture class meeting
Student Assignment (Part A and Part B)
Dataset for student assignment
Optional Assignment (Part C)
Teaching Notes and Tips
Workflow of this module:
*This adaptation was implemented in the last week of the semester during the COVID-19 pandemic, which strongly shaped what this implementation looked like*
- Pre-module presentation with slides during lecture class meeting
- Assign the out of class assignment to students
- Answer questions about assignment at next class meeting
Measures of Student Success
Success is shown if:
- Students can create, compare, and interpret scatterplots and correlations between pairs of variables.
- 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.
I squeezed this module into an introductory biology course where it didn't really fit - so I squeezed it into the very last week of the semester. This was also during the COVID-19 pandemic which affected my teaching context. Because of our very limited time on the concepts and the restrictions of the classroom structure, this adaptation includes modifications of Part A and Part B. Part C was optional and I have no information on whether and how students engaged with the optional Part C. The uploaded resources include the presentation slides I adapted to introduce the concepts and the assignment students were asked to complete out of class.
Cite this work
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