This investigation is part of the NASA: Mission Geography Module "What are the causes and consequences of climate change?" that guides students through explorations in climatic variability and evidence for global climate change.
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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.
In this lesson, students investigate and identify various phytoplankton using images that were previously taken with a compound microscope. Credit: This lesson is modified from a lesson of the same name created by The Center for Microbial Oceanography: Research and Education 
Students use Phytopia: Exploration of the Marine Ecosystem, a computer-based tool, to investigate various phytoplankton species and topics relating to phytoplankton biology.
Students analyze historic plant growth data (i.e., Peak Bloom dates) of Washington, D.C.’s famous cherry blossom trees, as well as atmospheric near surface temperatures as evidence for explaining the phenomena of earlier Peak Blooms in our nation’s capital.
In this lesson, Observing Earth’s Seasonal Changes, students observe patterns of average snow and ice amounts as they change from one month to another, as well as connect the concepts of the tilt and orbit of the Earth (causing the changing of seasons) with monthly snow/ice data from January 2008
This story map 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.
Students watch a visualization video and answer questions on the potential of increasing megadroughts in the southwest and central United States from 1950-2095 using models created by soil moisture data.
The Earth System Satellite Images, help the learner visualize how different Earth system variables change over time, establish cause and effect relationships for a specific variable, identify patterns, and determine relationships among variables over one year.