In this lesson, students complete a Myers-Briggs Type Inventory of their personality type as an introductory step to understanding what green jobs might suit their personal styles. From the information on this online tool, they look at different green jobs to explore possible careers.
In this video a scientist explains how DNA extracted from ancient tree remains provides insights about how trees/plants have adapted, over time, to changes in CO2 in the atmosphere. Her lab research investigates changes in plant genotypes under experimental conditions that simulate potential changes in CO2 levels in the future.
This short video is an excerpt from the longer video Acid Test: The Global Challenge of Ocean Acidification, produced by the National Resources Defense Council (NRDC). This short version summarizes the science of ocean acidification as well as the social implications.
In this activity, students will practice the steps involved in a scientific investigation as they learn why ice formations on land (and not those on water) will cause a rise in sea level upon melting. This is a discovery lesson in ice and water density and displacement of water by ice floating on the surface as it relates to global climate change.
This lesson plan has students working in small groups to research the Mountain Pine Beetle in Colorado and other inter-mountain Western states. Students identify the factors that control pine beetle population and research how warmer winters and decreasing spring snowpack allow the population of pine beetles to expand.
This multi-part activity introduces users to normal seasonal sea surface temperature (SST) variation as well as extreme variation, as in the case of El NiÃo and La NiÃa events, in the equatorial Pacific Ocean. Via a THREDDS server, users learn how to download seasonal SST data for the years 1982 to 1998. Using a geographic information system (GIS), they visualize and analyze that data, looking for the tell-tale SST signature of El NiÃo and La NiÃa events that occurred during that time period. At the end, students analyze a season of their own choosing to determine if an El NiÃo or La NiÃa SST pattern emerged in that year's data.