These activities were developed to assist with students' understanding of how primary productivity varies throughout the year in the Southern Ocean, and examines how multiple abiotic factors correlate with primary production.
This collection consists of 2 sets of activities.
Part One is focused on the Concept Invention phase of the Learning Cycle. The Concept Invention phase introduces abiotic factors, including light levels, nutrient concentrations and temperature, that may influence primary productivity. This set of data includes a six-month period spanning July 2019 to October 2019 . Students are able to view patterns in primary productivity in conjunction with single abiotic factors to find patterns and make connections between the parameters.
Part Two is focused on the Application phase of the Learning Cycle. The Application phase prompts students to use the knowledge gained in the Concept Invention phase to predict how two abiotic factors will vary over a three year period of primary productivity data.
After engaging with this Data Exploration a student will be able to:
These data explorations were designed for implementation in an introductory oceanography course (majors and/or non-majors). These activities would be appropriate for use in learning how to read graphs and interpret the data within graphs, as well as examining patterns of primary productivity in the Southern Ocean and understanding the abiotic factors that affect primary production.
Students will need to be familiar with concepts and terms from earlier in the semester including: the definition of primary productivity, use of chlorophyll a concentration as a proxy for primary production, nitrate is one of multiple nutrients required for primary production.
In upper division courses (300/400-level college courses) student knowledge may be enhanced with an introduction to how a fluorometer collects chl a data, the use of chl a as a proxy for primary production, and the caveats for this type of proxy. Students may also benefit from information on the different forms of nitrogen in the ocean and their bioavailability to different organisms. Students may want to explore variations in other nutrients, such as phosphate, that are not included in this dataset. Students' broader understanding of these concepts could be extended by looking at vertical profiles of these factors.
The Data Exploration activities require access to an internet-ready computer or tablet. Ideally each student group would have a computer or tablet to use to engage with the activity together. Alternatively, if no internet access is available for students, graphs of the specific time periods of interest and variables could be printed onto plastic overlays for each student or group of students.
Note, the Data Explorations use authentic raw data. Many of the datasets have been downsampled for simplicity and to ensure that the interactives load quickly in your browser. However, this means that many of the datasets retain their natural variability and some sampling side-effects. The goal of these activities is for students to analyze authentic data, not smooth averages. Effort has been taken to maintain as much of the data and to keep the variation of the data as true as possible, but make the activity user-friendly and browser-friendly.
Consider doing one or more of the following to engage the students in the data activities to follow, to access their prior knowledge and make connections. These opportunities will also help to increase their interest in figuring out the interactions that explain patterns of primary production
At the end of each exercise, once the students have had a chance to explore it and formulate answers to the questions, bring the class back together and ask them questions about what they discovered or learned.
Introduction to Oceanography
Undergraduate students in Introduction to Oceanography courses (for either marine science majors or non-science majors)
Our scope is exploring ways to use professionally-collected data in our teaching:
Most of the quantitative reasoning in this exercise revolves around reading and interpreting graphs.
By examining the chlorophyll-a data, students should observe primary productivity is low in early December but increases throughout the month and into January. Chlorophyll-a levels peak in mid-January and decline to low levels by early February and stay low through the end of October 2019, when the last data was recorded. Many students will hypothesize temperature is the main factor affecting primary productivity. By using the data exploration and toggling on the temperature data, they should realize the chlorophyll-a peak in January occurs prior to the warmest water temperatures. Chlorophyll-a (as a proxy for primary production) in fact declines rapidly while temperature is still rising. Temperature, therefore, is not the main factor affecting primary productivity.
Students can then explore other factors that may impact primary production by selecting one parameter at a time to compare with chlorophyll-a. When students toggle on light, they should observe a slightly delayed correlation between increasing light levels in the summertime (December and January) that lead to a spike in chlorophyll-a, likely due to elevated primary productivity in the water from a phytoplankton bloom. When phytoplankton density is high, light penetration depth decreases because the phytoplankton chloroplasts absorb some wavelengths of the light and change the color the water. This in turn, could impact the sensor readings on the OOI instrumentation, showing decreased light levels during a bloom of phytoplankton. For students or researchers downloading the data from the OOI, this question could be explored further by examining specific wavelength ranges individually. Light levels continue to decrease after the bloom is over as this region in the Southern Ocean heads into winter and receives much less solar radiation.
By toggling on the nutrient levels, students should observe that nutrient levels are consistently high in high latitudes (polar regions) because year-round there is sufficient water column mixing due to winds, storm events, thermohaline circulation, and a general lack of a thermocline. When the chlorophyll-a levels peak in January, the exponential growth of phytoplankton populations causes a decrease in nutrients as the phytoplankton use the nutrients for growth and reproduction. Once the bloom of phytoplankton is over (primary productivity decreases), nutrient levels increase again.
To summarize, by working through this data exploration, students should understand the mechanism of how light and nutrient levels interact to facilitate primary production. Nutrient levels in surface waters are naturally high in high latitudes (polar regions) because the water column is well mixed, so phytoplankton populations are not nutrient-limited as they are in many regions the students may be familiar with. Light levels are low in high latitudes throughout the winter (June, July, and August in the Southern Hemisphere) but increase through the fall and peak in December. This increase in light triggers the growth of phytoplankton and causes primary productivity (as represented by chlorophyll-a concentrations) to increase and peak in January. The peak of primary productivity means there is a great deal of phytoplankton in the water that absorbs the light and uses up the nutrients in the water, so both light and nutrient levels decrease after the phytoplankton bloom. The depletion of nutrients along with the decreasing light levels as summer ends, causes the phytoplankton growth to slow and ends the peak in primary productivity in this region.