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The Stomata Lab. What the past can tell us about our future - using fossil and modern plants to model atmospheric carbon dioxide

Author(s): Gina Wesley1, Kelly Livernoche1, Sean McNamara2, William Gretes3, Allison Bell, Kiersten Newtoff1, Jeff Leips4, Richard Barclay5, Heather Killen5

1. Montgomery College 2. Community College of Baltimore County 3. Howard Community College 4. University of Maryland Baltimore County 5. Smithsonian National Museum of Natural History

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Summary:
Students will develop a mathematical model of the relationship between atmospheric CO2 and the number of stomata on a leaf (Stomata Index). They will evaluate the model graphically, statistically, and biologically, and then use it to estimate CO2…

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Students will develop a mathematical model of the relationship between atmospheric CO2 and the number of stomata on a leaf (Stomata Index). They will evaluate the model graphically, statistically, and biologically, and then use it to estimate CO2 levels in the distant past.

Licensed under CC Attribution 4.0 International according to these terms

Version 1.0 - published on 02 Nov 2023 doi:10.25334/WSN0-WS30 - cite this

Keywords

  1. introductory biology
  2. Quantitative reasoning
  3. interdisciplinary
  4. climate change
  5. regression
  6. Ecology and Evolution
  7. Stomata
  8. NIQB
  9. C2. Data and Graphs
  10. C4. mathematical models
  11. C3. Statistical Analysis
  12. Smithsonian

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Description

This module guides students through building a mathematical model of a biological relationship, evaluating the model, improving it, and then using the model. The biological context is global climate change and atmospheric CO2 levels today and in the deep past. The most rapid period of warming in Earth’s geologic history, until today, was during the Paleocene Eocene Thermal Maximum, 56 million years ago. Understanding this period is important to preparing for our future. In this lab, students use leaf stomata counts to estimate the atmospheric CO2 levels during this event. Students will collect data from samples used in published and ongoing research at the Smithsonian National Museum of Natural History and the Smithsonian Environmental Research Center. Students will use a regression to establish the mathematical relationship and evaluate it using the goodness of fit statistic, R2, the coefficient of determination. They will also evaluate the biological meaning of the model. The module is designed to be implemented in a two-hour laboratory session, but it can easily be broken up into smaller sessions.

This module was developed and implemented as part of the NEXUS Institute for Quantitative Biology (NIQB), which is a collaborative project funded by the National Science Foundation's Improving Undergraduate STEM Education (NSF-IUSE) initiative. NIQB is a collaboration between University of Maryland, Baltimore County (DUE-1821274), Anne Arundel Community College (DUE-1821179), Community College of Baltimore County (DUE-1821249), Howard Community College (DUE-1820903), and Montgomery College (DUE-1821169).

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