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TRANSITIONING FROM MONITORING TO FORECASTING POTENTIAL HARMFUL ALGAL BLOOM: AN EXAMPLE FROM SHENZHEN BAY, P.R. CHINA

The frequency and intensity of harmful algal blooms (HAB) are likely to increase with climate change and eutrophication. To manage the environmental and health threat, it is essential to improve our capability to predict HABs. Using Noctiluca scintillans, a dinoflagellates often blooming in Asia with a rapid worldwide expansion, we demonstrate a potential way to predict Noctiluca blooms by deploying a plankton imaging system: PlanktonScope. PlanktonScope is shadowgraph imaging system, capable of imaging organisms 30µm – 7cm. This system was deployed in Shenzhen Bay during March-April 2016 for a three week period with the system recording images at 0.5Hz. Using the automated image processing procedure, we found that PlanktonScope recorded a full cycle of a N. scintillans bloom. Time series (Markov Chain Monte Carlo (MCMC)) uncertainty analysis, was then applied to develop a prediction framework for the outburst of N scintillans. Our study demonstrated that if we were able to acquire images in real time, we could have forecast this Noctiluca bloom. This framework is applicable to other HAB species and demonstrates an early warning system for proactive management.

Authors

Bi, H., University of Maryland Center for Environmental Science, USA, hbi@umces.edu

Cai, Z., Graduate School at Shenzhen, Tsinghua University, China, caizh@sz.tsinghua.edu.cn

Cheng, X., Graduate School at Shenzhen, Tsinghua University, China, chengxm@sz.tsinghua.edu.cn

He, Y., Graduate School at Shenzhen, Tsinghua University, China, heyh@sz.tsinghua.edu.cn

Benfield, M. C., Louisiana State University, USA, mbenfie@lsu.edu

Fan, C., Morgan State University, USA, chunlei.fan@morgan.edu

Details

Oral presentation

Session #:021
Date: 03/02/2017
Time: 16:45
Location: 323 B

Presentation is given by student: No