Paleoclimate and Ocean Biogeochemistry
Summary
This module guides students through an examination of how surface ocean productivity relates to global climate on glacial-interglacial timescales and how the availability of ocean nutrients can be correlated with changes in productivity. In Part A, students reflect on how nitrogen and phosphorous are distributed globally, and how patterns of primary productivity compare with those nutrient patterns. In Part B, students use statistical analysis to examine the influence of dust-borne iron on carbon export in two ocean regions. In Part C, students choose a data set to investigate the relationship between ocean carbon export and climate, formulate a hypothesis to test using that data set, and share their findings with peers.
The overarching question the module helps students answer is:
How does primary productivity influence global climate?
Strengths of Module
This activity has been designed using the Project EDDIE (Environmental Data-Driven Inquiry and Exploration) module framework. Thus, the module is focused on giving students an opportunity to use large, real-world data sets to improve their quantitative reasoning through self-directed inquiry.
This module uses published data sets that are fundamental to our understanding of Earth's biogeochemical and climate history. The module guides students through a descriptive and statistical analysis of these data sets that includes both spatial and temporal dimensions. Students also have the opportunity to develop a hypothesis about variables that have significance for global climate and test that hypothesis with data. The module structure requires students to work both independently and collaboratively, and provides clear opportunities for both self-assessment and instructor evaluation throughout.
What does success look like
By the end of the module students should be able to:
- Describe patterns of nitrogen (N), phosphorous (P) and primary productivity in the global oceans. Discuss regions where productivity aligns with expectations based on macronutrient availability and identify one region where they do not.
- Quantify the magnitude of glacial-interglacial changes in iron (Fe) delivery to the oceans via dust.
- Describe and evaluate the statistical evidence they obtained for relationships between dust and increased ocean productivity at two sites, and provide a hypothesis for why those relationships might be different.
- Describe the relationships between Southern Ocean carbon export and three paleoclimate data sets that reflect different dimensions of Earth's climate system.
Context for Use
This module was designed for use as part of an introductory undergraduate course on Earth's climate history. The module is also appropriate for use in introductory courses in oceanography, marine biology, and paleoclimatology. The module should take approximately 90 minutes to complete, including the presentation and discussion of the module PowerPoint. The activity requires that students have experience plotting quantitative data sets - both time series and scatter plots - and students need to know how to perform and interpret a linear regression. Module Activities A and B are designed to be completed individually; Activity C should be completed in collaborative teams.
How Instructors Have Used This Module
This module was featured in a webinar, which is available in the references and resources section below. You can also browse My EDDIE Experience Instructor Stories from users, provided below.
Using Project EDDIE modules in Climate and the Earth System
Alessandro Zanazzi
Alessandro Zanazzi, Utah Valley University About this Course Climate and the Earth System Lecture Course Upper Level Undergraduate Majors 5 students in the course Show Course Description HideThis course studies ...
Using the Project EDDIE Ocean Biogeochemistry and Paleoclimate Module in The Earth's Climate System
Allison Jacobel, Middlebury College
The Ocean Biogeochemistry and Paleoclimate module guided students in an introductory climate science course through activities that enabled them to answer the question "How does ocean primary productivity influence global climate." Along the way they gained skills in plotting and interpreting time series, and examining the correlation of datasets using linear regressions.
Using Project EDDIE modules in Hybrid Oceanography Lab
Karen Bridges, Howard Community College
Karen Bridges, Howard Comm About this Course Hybrid Oceanography Lab Laboratory Course Introductory Undergraduate Non-Majors 20 students in the course Show Course Description HideStudents will investigate the ...
Description and Teaching Materials
Why this Matters:
The deep ocean is the second largest reservoir of carbon, after carbonate rocks. The partitioning of carbon between the ocean and the atmosphere significantly impacts global climate on both modern and geologic timescales. Understanding the mechanisms of ocean carbon storage and release is therefore critical for understanding global climate past and present.
Marine primary productivity is one of the crucial mechanisms that influences the partitioning of carbon between the ocean and the atmosphere. The balance between surface export productivity (carbon removal from the ocean's surface) and the upwelling of respired carbon determines the net flux of CO2 into (or out of) the atmosphere. Surface export productivity is in turn largely controlled by the distribution of macro- and micro- nutrients. These nutrient patterns are also fundamental to our understanding of ocean ecosystems as photosynthetic organisms form the basis of the food web.
Quick outline/overview of the activities in this module
- Activity A: Examine and describe spatial patterns of nitrogen and phosphorus concentrations, N:P ratios, and primary productivity in the global oceans.
- Activity B: Investigate how the input of iron-bearing dust to the oceans varied during glacial and interglacial climates of the past and how that input affected primary productivity.
- Activity C: Students choose a climate data set (options below), formulate a hypothesis, and examine the relationship between Southern Ocean carbon export and that data set to test their prediction. They then connect with a group who chose a different climate data set and present their results.
A complete student handout containing the module components and guiding questions is available under Teaching Materials
Teaching Materials:
- Instructor Handout (Microsoft Word 2007 (.docx) 24kB Jun24 21)
- Module Powerpoint (PowerPoint 2007 (.pptx) 77.1MB Mar29 23)
- Student Handout (Microsoft Word 2007 (.docx) 30kB Mar29 23)
Data sets:
- Part A - Part_A_Maps.pdf (Acrobat (PDF) 1.6MB Jun16 21)
- Part B - PartB_Dust_Prod Data.xlsx (Excel 2007 (.xlsx) 94kB Mar29 23)
- Part C - PartC_Comparison_Data.xlsx (Excel 2007 (.xlsx) 66kB Jun10 21)
Teaching Notes and Tips
Please see the instructor's manual for details about prerequisite knowledge/skills, potential module sticking points, suggestions about potential variations to the module, and additional information that may enhance student learning and understanding. Plan for the module to take students ~90 minutes depending on their level of familiarity with their plotting software of choice.
Workflow of this module:
- Have students download excel and install the data analysis toolkit.
- Have students download the student handout.
- Instructor begins class by giving a brief presentation to introduce the module and the proxies used in Part C.
- Students download the data sets.
- Students work through module activities.
- Students turn in their completed handout with answers to the questions and the graphs they made.
Measures of Student Success
Students will self-assess throughout the exercise by answering the module questions. Additional opportunities for reflection are built into Part C, in which students develop testable hypotheses, discuss their results with their peers and integrate their peers' work into their own understanding of the climate system.
Instructors can assess student's progress towards the learning goals by evaluating their answers to the module questions.
Final Data Plots and Answer Key:
- Excel answer key (plots) -
- Student handout answer key -
References and Resources
Papers presenting the original data sets*, and reference articles/links
- Garcia, H. E., R. A. Locarnini, T. P. Boyer, J. I. Antonov, O.K. Baranova, M.M. Zweng, J.R. Reagan, D.R. Johnson, 2014. World Ocean Atlas 2013, Volume 4: Dissolved Inorganic Nutrients (phosphate, nitrate, silicate). S. Levitus, Ed., A. Mishonov Technical Ed.; NOAA Atlas NESDIS 76, 25 pp.
- Jacobel, A. W. et al. No evidence for equatorial Pacific dust fertilization. Nature Geoscience 12, 154–155 (2019).
- Lisiecki, L. E. & Raymo, M. E. A Pliocene-Pleistocene stack of 57 globally distributed benthic δ18O records. Paleoceanography 20, (2005).
- Loveley, M. R. et al. Millennial-scale iron fertilization of the eastern equatorial Pacific over the past 100,000 years. Nature Geoscience 22, 1 (2017).
- Lüthi, D. et al. High-resolution carbon dioxide concentration record 650,000–800,000 years before present. Nature 453, 379–382 (2008).
- Martínez-Garcia, A. et al. Iron Fertilization of the Subantarctic Ocean During the Last Ice Age. Nature 343, 1347-1350 (2014).
- Martínez-Garcia, A. et al. Southern Ocean dust-climate coupling over the past four million years. Nature 476, 312-315 (2011).
- NASA Goddard Space Flight Center, Ocean Ecology Laboratory, Ocean Biology Processing Group; (2018): Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Ocean Color Data, NASA OB.DAAC.
- Schlitzer, Reiner, Ocean Data View, https://odv.awi.de, 2021.
- Sigman, D. M., Hain, M. P. & Haug, G. H. The polar ocean and glacial cycles in atmospheric CO2 concentration. Nature 466, 47–55 (2010).
- Studer, A. S. et al. Antarctic Zone nutrient conditions during the last two glacial cycles. Paleoceanography 30, 845–862 (2015).
- Winckler, G., Anderson, R. F., Jaccard, S. L. & Marcantonio, F. Ocean dynamics, not dust, have controlled equatorial Pacific productivity over the past 500,000 years. Proceedings of the National Academy of Sciences 113, 6119–6124 (2016).
**Module last updated 3/29/23 to provide correct reference for the alkenone paleoproductivity data from Martínez-Garcia et al., 2014
*Note that these data sets are as presented by their original authors and do not contain the interpolated data sets as do the data sets attached directly to this module document.
View the September 17, 2021 Project EDDIE Meet the Author Event: Teaching Climate Change with data in your introductory course, featuring how this module was used: