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In This Article

  • Summary
  • Abstract
  • Introduction
  • Protocol
  • Representative Results
  • Discussion
  • Acknowledgements
  • Materials
  • References
  • Reprints and Permissions

Summary

Here, we present a protocol for converting phytoplankton microscopic images into vector graphics and repetitive patterns to enable visualization of shifts in phytoplankton taxa and biomass over 60 years. This protocol represents an approach that can be utilized for other plankton time series and datasets globally.

Abstract

Oceanographic time series provideĀ 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 representĀ 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.

Introduction

Phytoplankton are primary producers representing the base of the food web across aquatic ecosystems1,2. While phytoplankton monitoring programs are key to identifying current and future changes in marine ecosystems, their support is declining over time 3. Due to their relatively short generation times and limited mobility, phytoplankton are particularly responsive to climate change, which makes them an important tool in time series monitoring. Phytoplankton time series are also important for informing ecosystem-based management of resource availabilityĀ and providing context for epi....

Protocol

1. Converting phytoplankton images into vector graphics

  1. Select phytoplankton microscopic images taken from the Narragansett Bay Long Term Plankton Time Series (NBPTS) as either .JPG, .PNG, or .PDF files (Figure 1A).
    NOTE: Taxa include Thalassiosira nordenskioeldii, Thalassionema nitzschioides, Tripos spp., Odontella aurita, Skeletonema species complex, Chaetoceros diadema, Eucampia zodiacus, Dinophysis spp., and.......

Representative Results

Results document a decline in phytoplankton biomass from the 1970s to 1990s to 2010s (Figure 1). All decades exhibited a bimodal peak in chlorophyll a (chl a) concentration with the first peak occurring in winter and the second occurring in summer. The 1970s exhibited higher average chl a in winter than in summer. Conversely, the 1990s showed lower chl a in winter than in summer. The 2010s returned to a higher mean chl a concentration in winter th.......

Discussion

Critical steps of the protocol include obtaining microscopic images of phytoplankton and converting them into vector graphics. Making the images of phytoplankton, which are not noticeable to the naked eye, large enough to be seen without a magnifying glass on the mural, helps to bring them to life for the viewer. To accomplish this mural as not only a work of art but also a data visualization method, it is important to incorporate observed data into the project. In the case of the phytoplankton mural, the chlorophyll

Acknowledgements

This research was supported by the National Science Foundation (OIA-1655221, OCE-1655686) and Rhode Island Sea Grant (NA22-OAR4170123, RISG22-R/2223-95-5-U). We thank the multiple captains for providing field assistance and the many students and researchers who collected data since 1970. We thank Stewart Copeland and Georgia Rhodes for developing the Vis-A-Thon project that produced the plankton mural as well as Rafael Attias from the Rhode Island School of Design for his artistic guidance during project development.

....

Materials

NameCompanyCatalog NumberComments
Adobe IllustratorAdobeversion 23.0.6Free alternatives include: Inkscape, GIMP, Vectr, Vectornator
Eclipse E800NikonECLIPSE Ni/Ci Upright MicroscopeNow succeeded by Eclipse Ni-U
Epson Large Format PrinterEpsonSCT5475SR
Heavy Matte PaperEpsonS041596
RStudioRstudio, PBCversion 2022.07.1Any statistical software tool will suffice

References

  1. Cloern, J. E., Jassby, A. D. Complex seasonal patterns of primary producers at the land-sea interface. Ecology Letters. 11 (12), 1294-1303 (2008).
  2. Cloern, J. E., Jassby, A. D. Patterns and Scales of ....

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Plankton EcologyPhytoplanktonZooplanktonPlankton Imaging TechnologyArtificial IntelligencePlankton Time SeriesClimate ChangeNarragansett BayFood WebVisualizationOceanographic Data

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