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可视化海洋学数据以描绘浮游植物的长期变化。

Visualizing Oceanographic Data to Depict Long-term Changes in Phytoplankton.

机构信息

Graduate School of Oceanography, University of Rhode Island;

School of Earth, Environmental and Marine Sciences, The University of Texas - Rio Grande Valley.

出版信息

J Vis Exp. 2023 Jul 28(197). doi: 10.3791/65571.

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.

摘要

海洋时间序列为生态系统中的环境过程提供了重要视角。美国罗德岛州纳拉甘塞特湾的长期浮游生物时间序列(NBPTS)是世界上同类浮游生物时间序列中最长的时间序列之一(1959 年至今),为可视化水生生态系统中的长期变化提供了独特的机会。浮游植物是大多数海洋系统(包括纳拉甘塞特湾)食物网的基础。因此,向生活在沿海水域的 24 亿人传达它们的重要性至关重要。我们制定了一个协议,目标是通过利用 Adobe Illustrator 将从 NBPTS 收集的浮游植物微观图像转换为矢量图形,通过时间将其转化为重复的视觉模式,从而可视化浮游植物的多样性和规模。选择大量存在的浮游植物或对经济和健康构成威胁的浮游植物,例如有害藻类 bloom 类群 Pseudo-nitzschia spp.,用于图像转换。然后,根据相对丰度,为选定的几十年数据(20 世纪 70 年代、90 年代和 2010 年代)创建各种浮游植物图像的模式。浮游植物生物量的十年模式为每个十年提供了轮廓,而蓝色到红色的背景颜色梯度则用于揭示纳拉甘塞特湾观测到的长期温度升高。最后,用重复的浮游植物模式打印出 96 英寸乘 34 英寸的大幅面面板,以说明浮游植物丰度随时间的潜在变化。该项目通过利用艺术作品本身中的实时时间序列数据(例如浮游植物生物量和丰度),使人们能够直观地看到浮游植物生物量的实际变化,而这些变化通常肉眼无法察觉。它代表了一种可以用于许多其他浮游生物时间序列的数据可视化、交流、教育和推广工作的方法。

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