Visualizing Oceanographic Data to Depict Long-term Changes in Phytoplankton

Authors

Patricia S. Thibodeau
Jongsun Kim, The University of Texas Rio Grande ValleyFollow

Document Type

Article

Publication Date

7-28-2023

Abstract

Oceanographic time series provide an important perspective on environmental processes in ecosystems. The Narragansett Bay Long-Term Plankton Time Series (NBPTS) in Narragansett Bay, Rhode Island, USA, represents one of the longest plankton time series (1959-present) of its kind in the world and presents a unique opportunity to visualize long-term change within an aquatic ecosystem. Phytoplankton represent the base of the food web in most marine systems, including Narragansett Bay. Therefore, communicating their importance to the 2.4 billion people who live within the coastal ocean is critical. We developed a protocol with the goal of visualizing the diversity and magnitude of phytoplankton by utilizing Adobe Illustrator to convert microscopic images of phytoplankton collected from the NBPTS into vector graphics that could be conformed into repetitive visual patterns through time. Numerically abundant taxa or those that posed economic and health threats, such as the harmful algal bloom taxa, Pseudo-nitzschia spp., were selected for image conversion. Patterns of various phytoplankton images were then created based on their relative abundance for select decades of data collected (1970s, 1990s, and 2010s). Decadal patterns of phytoplankton biomass informed the outline of each decade while a background color gradient from blue to red was used to reveal a long-term temperature increase observed in Narragansett Bay. Finally, large, 96-inch by 34-inch panels were printed with repeating phytoplankton patterns to illustrate potential changes in phytoplankton abundance over time. This project enables visualization of literal shifts in phytoplankton biomass, that are typically invisible to the naked eye while leveraging real-time series data (e.g., phytoplankton biomass and abundance) within the art piece itself. It represents an approach that can be utilized for many other plankton time series for data visualization, communication, education, and outreach efforts.

Comments

Copyright © 2023 JoVE Journal of Visualized Experiments

Recommended Citation

Thibodeau, P. S., & Kim, J. (2023). Visualizing Oceanographic Data to Depict Long-term Changes in Phytoplankton. Journal of visualized experiments : JoVE, (197), 10.3791/65571. https://doi.org/10.3791/65571

Publication Title

Journal of Visualized Experiments

DOI

10.3791/65571