creating phytoplankton panels from biomass and temperature data

Exploring Long-Term Shifts in Phytoplankton by Conversion of Microscopic Images

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 availability&#160;and providing context for episodic events, such as marine heatwaves4. Short-term time series, on the matter of years, give insights into phytoplankton community succession and seasonal dynamics (e.g., ref.5,6), whereas long-term time series, such as the Bermuda Atlantic Time Series (BATS) and Hawaii Ocean Times Series (HOTS) Programs, span&#160;more than two decades and enable the detection of long-term trends7,8. Such studies illustrate the benefit and importance of a highly resolved phytoplankton record for a complete understanding of long-term ecosystem change in dynamic marine environments. Further, visualizing and communicating these changes in phytoplankton, which cannot be seen by the naked eye, are more difficult to comprehend than for organisms that are large and readily visible, like fish and whales. Computer visualizations offer a technique to explore complex data sets9 and improved illustrative graphics are becoming readily available (e.g., Integration and Application Network, University of Maryland Center for Environmental Science). However, most studies in phytoplankton ecology, including many referenced here, still only present results as data graphs reducing their accessibility to general audiences. Given that phytoplankton represent the base of the food web in most marine systems, communicating their importance to the nearly 2.4 billion people who live within the coastal ocean is critical10. Here, we developed a protocol with the goal of visualizing the diversity and magnitude of phytoplankton, as collected by a phytoplankton monitoring program.
The Narragansett Bay Plankton Time Series (NBPTS) provides a long-term 60+ year (1959-Present) perspective on the effects of global change within a climate context on phytoplankton abundance, seasonality, and phenology (life history). Narragansett Bay (NBay) is a coastal estuary connected to the broader systems of the U.S. Northeast Shelf and Northwest Atlantic whose production has important implications for fisheries and human use along the coastal U.S.A.11. NBay is considered a highly seasonal system experiencing long-term (1950-2015) warming waters in the region as well as shifts in nutrients and an increase in water clarity12,13. In addition, a decline in phytoplankton biomass has occurred in upper NBay related to anthropogenic decreases in dissolved inorganic nitrogen, which is partially attributed to upgrades in wastewater treatment plants12. Shifts in phytoplankton taxa, particularly harmful algal blooms (HABs), are also occurring in NBay. Pseudo-nitzschia spp., which produces pervasive toxic blooms in upwelling regions along the U.S. west coast, led to notable shellfish closures for the first time in NBay&#39;s history&#160;in 2016 and 201714,15,16. Communicating these changes to diverse audiences is important for increasing science literacy and for promoting continued support of phytoplankton monitoring studies.
The goal of this project was to utilize microscopic images of phytoplankton from NBay, as well as data synthesized from NBPTS, to visualize the literal shifts in phytoplankton taxa and biomass that are occurring in NBay to communicate and enhance the importance of phytoplankton to general audiences. NBPTS provides 60+ years of publicly available weekly phytoplankton counts and biomass to leverage data from (https://web.uri.edu/gso/research/plankton/). The final product was a large mural of plankton patterns representative of the time series data (e.g., phytoplankton biomass and taxa, temperature) within the art piece itself. This approach represents a visualization method that can be utilized for many other plankton time series throughout the world and can be adapted for monitoring programs with short-term, seasonal data as well. The benefits of implementing this protocol include increasing efforts in data visualization, science communication, education, and engagement with local communities.

Author Spotlight: Unveiling Plankton Response to Climate Change Through Time-Series Data and Artistic Expression 

Visualizing Oceanographic Data to Depict Long-term Changes in Phytoplankton

I am a plankton ecologist focused on characterizing the effects of rapid climate change on phytoplankton and zooplankton ecology and physiology. Plankton ecology requires both a mix of traditional and modern approaches. More recently, plankton imaging technology, in addition to microscopy, is being used to quantify and measure plankton.This technology decreases the time it takes to manually count plankton by utilizing artificial intelligence to count and classify plankton for us. This research visualizes one of the longest plankton time series in the world. These data sets are critical for providing context to understanding shifts in plankton communities and food webs in regions affected by rapid climate change.My research has helped to visualize the mechanisms underpinning those shifts. Given the microscopic nature of plankton, it can be difficult, particularly for scientists to visualize in communicate how plankton communities are changing over time. My protocol aims to provide a clear method for visualizing shifts in plankton communities, leveraging scientific data within an artistic framework.This protocol will hopefully encourage the other scientists to think more creatively about how they visualize and present their data, particularly to non-sized audience. There is open gap between lab result and how they are interpreted and present in society. So, I hope this protocol will help reach this gap.My lab will continue to leverage plankton time series data sets to identify the environmental factors affecting long-term changes in plankton communities, as well as conduct physiological experiments in the lab to understand the physiologic mechanisms underpinning these community ships in the northeast United States and beyond.

Watch this Scientific Journal Video about Creating Phytoplankton Panels from Biomass and Temperature Data at JoVE.com

Creating Phytoplankton Panels from Biomass and Temperature Data  

Begin by opening a JPEG or PNG figure of the chlorophyll a decadal biomass into the Illustrator workspace. Then vectorize each of the three chlorophyll a seasonal cycles by removing the background and saving the image as an EPS file. Then create a new art board in a new Illustrator workspace by clicking and dragging the square art board tool in the toolbar.Adjust the size by clicking on properties and transform to make three identical art boards of the same size. Drag and drop the chlorophyll a EPS files onto the three art boards. Go to properties and embed to add it to the new art board.Create a new layer by selecting the sticky note icon. Next, create a rectangle within the new layer with the rectangle tool from the toolbar. Fill the rectangle with a light blue gradient using the gradient tool from the toolbar.Use the line segment tool from the toolbar to create a box attached to the trend line. Make the line straight and aligned by holding the Shift button, then press the Ctrl key and select all the components, including the lines and trend line, within the layer. Then select object, followed by path and join.Repeat creating a rectangle and fill it with a blue to red color gradient to represent warming water temperature across the three decadal panels. Create a third rectangle of equal size and fill it with the phytoplankton swatch pattern corresponding to that decade. Place the grouped line segments within the layer of rectangles.Next, select the two smaller rectangles and the grouped line segments. Select object, then clipping mask, followed by make. This will remove the top fill of the shape.Repeat creating a rectangle and fill it with a red to blue color gradient to represent a warming water temperature across the three decadal panels. To add images of microscopic phytoplankton onto the phytoplankton patterns, select open and click on the image file to open it in the Illustrator. Then create a circle with the ellipse tool from the toolbar and overlay it on top of the phytoplankton image.Hold the Shift key to select both the shape and the image. Then in the menu, click on object, then clipping mask, followed by make to fill the shape with the image. Repeat for selected phytoplankton images, and distribute across the three decades to look like a magnifying glass zooming in on the illustrative phytoplankton.Now use the rectangle tool from the toolbar to create a text box on each of the decade art boards. Use the type tool to click and type information about each decade. Add text at the top of each decade with the name of the decade, and add the names of the corresponding seasons at the bottom of each of the three panels.Import the saved Illustrator file and select to only import the three completed decades. Select all and export as a PDF file. Print the panels on heavyweight matter paper and install with hanging hardware.Visualization of phytoplankton data showed a decline in phytoplankton biomass from the 1970s to 1990s to 2010s. All decades exhibited a bimodal peak in chlorophyll a concentration with the first peak occurring in winter and the second occurring in summer. Also, Thalassiosira and Skeletonema species increased from the 1970s to 1990s.Other taxa, such as Eucampia, oscillated in abundance, as shown by the increased presence of more Eucampia zodiacus images in the 2010s compared to the 1970s and 1990s.

creating-phytoplankton-panels-from-biomass-and-temperature-data

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86 visualizações.  University of Rhode Island. Comece abrindo uma figura JPEG ou PNG da clorofila, uma biomassa decadal, no espaço de trabalho do Illustrator. Em seguida, vetorize cada um dos três ciclos sazonais de clorofila, removendo o fundo e salvando a imagem como um arquivo EPS. Em seguida, crie um novo quadro de arte em um novo espaço de trabalho do Illustrator clicando e arrastando a ferramenta quadro de arte quadrado na barra de ferramentas.Ajuste o tamanho clicando em propriedades e transforme para fazer três placas d...