Connections in Water Quality Indicators
Faculty Mentor
Tyler Cyronak
Location
Russell Union Ballroom
Type of Research
On-going
Session Format
Poster Presentation
College
College of Science & Mathematics
Department
Sustainability Science
Abstract
This project builds data literacy in middle school by using real-time water quality data to investigate ocean acidification and ecosystem health. Students will learn to create graphs in Excel, interpret patterns in data, and understand connections between scientific principles and environmental health. The students will use salinity, dissolved oxygen, water temperature, turbidity, Chl-a Fluorescence (RFU) and FDOM Fluorescence data from a buoy placed at the Tybee Island Oyster Farm to create graphs and make interpretations. The curriculum bridges a gap between environmental science and economic impact, illustrating how water quality can impact commercially important fisheries such as oyster farms. It is designed for middle school students in grades 6-8 and built on the Next Generation Science Standards (NGSS) MS-LS2-1 Ecosystems: Interactions, Energy, and Dynamics. The full lesson includes a PowerPoint presentation, an Excel-based data activity with accompanying worksheet, discussion questions to encourage students to share their interpretations, and a post-activity quiz with answer key. For local classes, the lesson can be paired with a field trip to Tybee Island Oyster Farm, allowing students to see firsthand how water quality affects a working fishery. Through graphing and interpretation, students should identify several core patterns in the data. These include tidal, daily, and seasonal variations in the data. Students will also connect chemical concepts, such as higher water temperature being associated with lower pH, and that dissolved oxygen tends to decrease as water temperature increases. Students will also observe that chlorophyll-a fluorescence and FDOM fluorescence show no strong statistical relationship with pH, water temperature, or dissolved oxygen in this dataset. More broadly, the lesson helps students understand how small environmental changes can scale up to affect ecosystems, local livelihoods, and the broader economy.
Program Description
n/a
Start Date
4-23-2026 2:00 PM
End Date
4-23-2026 4:00 PM
Recommended Citation
Frazier, Brianna, "Connections in Water Quality Indicators" (2026). GS4 Student Scholars Symposium. 225.
https://digitalcommons.georgiasouthern.edu/research_symposium/2026/2026/225
Connections in Water Quality Indicators
Russell Union Ballroom
This project builds data literacy in middle school by using real-time water quality data to investigate ocean acidification and ecosystem health. Students will learn to create graphs in Excel, interpret patterns in data, and understand connections between scientific principles and environmental health. The students will use salinity, dissolved oxygen, water temperature, turbidity, Chl-a Fluorescence (RFU) and FDOM Fluorescence data from a buoy placed at the Tybee Island Oyster Farm to create graphs and make interpretations. The curriculum bridges a gap between environmental science and economic impact, illustrating how water quality can impact commercially important fisheries such as oyster farms. It is designed for middle school students in grades 6-8 and built on the Next Generation Science Standards (NGSS) MS-LS2-1 Ecosystems: Interactions, Energy, and Dynamics. The full lesson includes a PowerPoint presentation, an Excel-based data activity with accompanying worksheet, discussion questions to encourage students to share their interpretations, and a post-activity quiz with answer key. For local classes, the lesson can be paired with a field trip to Tybee Island Oyster Farm, allowing students to see firsthand how water quality affects a working fishery. Through graphing and interpretation, students should identify several core patterns in the data. These include tidal, daily, and seasonal variations in the data. Students will also connect chemical concepts, such as higher water temperature being associated with lower pH, and that dissolved oxygen tends to decrease as water temperature increases. Students will also observe that chlorophyll-a fluorescence and FDOM fluorescence show no strong statistical relationship with pH, water temperature, or dissolved oxygen in this dataset. More broadly, the lesson helps students understand how small environmental changes can scale up to affect ecosystems, local livelihoods, and the broader economy.
