This lesson is taken from NASA's Phytopia: Discovery of the Marine Ecosystem written in partnership with Bigelow Laboratory for Ocean Science with funding from the National Science Foundation.

This StoryMap lesson plan allows students to explore global phytoplankton distribution using chlorophyll concentration data in a 5 E-learning cycle. Students will investigate the processes that allow phytoplankton populations to thrive, as well as how their role in the carbon cycle impacts the other spheres of the Earth System. 

Teachers, are you looking for resources to help you engage students in data analysis related to Global Phytoplankton Distribution?

Check out the monthly 2018 images featuring two science variables related to Phytoplankton Distribution: Chlorophyll Concentration (milligrams per cubic meter)  & Monthly Flow of Energy into Surface by Shortwave Radiation (watts per square meter)

Students use Phytopia: Exploration of the Marine Ecosystem, a computer-based tool, to investigate various phytoplankton species and topics relating to phytoplankton biology. 

The Earth System Satellite Images help students observe and analyze global Earth and environmental data, understand the relationship among different environmental variables, and explore how the data change seasonally and over longer timescales.  

Students observe seasonal images of Monthly Leaf Area, looking for any changes that are occurring throughout the year.

Students will analyze a graph showing the amounts of peak energy received at local noon each day over the year changes with different latitudes. 

Students will analyze the monthly seasonal chlorophyll concentration images in our global oceans for the four different months of 2024, and then answer the following questions.

In this activity, you will use an inexpensive spectrophotometer* to test how light at different visible wavelengths (blue, green, red) is transmitted, or absorbed, through four different colored water samples.

Students observe monthly images of changing vegetation patterns, looking for seasonal changes occurring throughout 2017. These data can be used by students to develop their own models of change.