scholarly journals World’s Largest Macroalgal Blooms Altered Phytoplankton Biomass in Summer in the Yellow Sea: Satellite Observations

2015 ◽  
Vol 7 (9) ◽  
pp. 12297-12313 ◽  
Author(s):  
Qianguo Xing ◽  
Chuanmin Hu ◽  
Danling Tang ◽  
Liqiao Tian ◽  
Shilin Tang ◽  
...  
Keyword(s):  
Yellow Sea ◽  
Phytoplankton Biomass ◽  
Satellite Observations ◽  
The Yellow Sea ◽  
Macroalgal Blooms

scholarly journals Monitoring seaweed aquaculture in the Yellow Sea with multiple sensors for managing the disaster of macroalgal blooms

2019 ◽  
Vol 231 ◽  
pp. 111279 ◽  
Author(s):  
Qianguo Xing ◽  
Deyu An ◽  
Xiangyang Zheng ◽  
Zhenning Wei ◽  
Xinhua Wang ◽  
...  
Keyword(s):  
Yellow Sea ◽  
The Yellow Sea ◽  
Seaweed Aquaculture ◽  
Multiple Sensors ◽  
Macroalgal Blooms

scholarly journals Ocean Upwelling Along the Yellow Sea Coast of China Revealed by Satellite Observations and Numerical Simulation

2017 ◽  
Vol 55 (1) ◽  
pp. 526-536 ◽  
Author(s):  
Shaowu Bao ◽  
Xiaofeng Li ◽  
Dongliang Shen ◽  
Zizang Yang ◽  
Leonard J. Pietrafesa ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Yellow Sea ◽  
Satellite Observations ◽  
The Yellow Sea ◽  
Sea Coast

scholarly journals Annual patterns of macroalgal blooms in the Yellow Sea during 2007–2017

PLoS ONE ◽  
2019 ◽  
Vol 14 (1) ◽  
pp. e0210460 ◽  
Author(s):  
Jianheng Zhang ◽  
Jinting Shi ◽  
Song Gao ◽  
Yuanzi Huo ◽  
Jianjun Cui ◽  
...  
Keyword(s):  
Yellow Sea ◽  
The Yellow Sea ◽  
Macroalgal Blooms ◽  
Annual Patterns

scholarly journals High-Resolution Satellite Observations of a New Hazard of Golden Tides Caused by Floating Sargassum in Winter in the Yellow Sea

2017 ◽  
Vol 14 (10) ◽  
pp. 1815-1819 ◽  
Author(s):  
Qianguo Xing ◽  
Ruihong Guo ◽  
Lingling Wu ◽  
Deyu An ◽  
Ming Cong ◽  
...  
Keyword(s):  
High Resolution ◽  
Yellow Sea ◽  
Satellite Observations ◽  
The Yellow Sea

scholarly journals The Lagrangian-based Floating Macroalgal Growth and Drift Model (FMGDM v1.0): application to the Yellow Sea green tide

2021 ◽  
Vol 14 (10) ◽  
pp. 6049-6070
Author(s):  
Fucang Zhou ◽  
Jianzhong Ge ◽  
Dongyan Liu ◽  
Pingxing Ding ◽  
Changsheng Chen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Yellow Sea ◽  
Surface Wind ◽  
Late Summer ◽  
Ocean Model ◽  
The Yellow Sea ◽  
Green Tide ◽  
Observation Data ◽  
Macroalgal Blooms ◽  
Drift Model

Abstract. Massive floating macroalgal blooms in the ocean result in many ecological consequences. Tracking their drifting pattern and predicting their biomass are essential for effective marine management. In this study, a physical–ecological model, the Floating Macroalgal Growth and Drift Model (FMGDM), was developed. Based on the tracking, replication, and extinction of Lagrangian particles, FMGDM is capable of determining the dynamic growth and drift pattern of floating macroalgae, with the position, velocity, quantity, and represented biomass of particles being updated synchronously between the tracking and the ecological modules. The particle tracking is driven by ocean flows and sea surface wind, and the ecological process is controlled by the temperature, irradiation, and nutrients. The flow and turbulence fields were provided by the unstructured grid Finite-Volume Community Ocean Model (FVCOM), and biological parameters were specified based on a culture experiment of Ulva prolifera, a phytoplankton species causing the largest worldwide bloom of green tide in the Yellow Sea, China. The FMGDM was applied to simulate the green tide around the Yellow Sea in 2014 and 2015. The model results, e.g., the distribution, and biomass of the green tide, were validated using the remote-sensing observation data. Given the prescribed spatial initialization from remote-sensing observations, the model was robust enough to reproduce the spatial and temporal developments of the green tide bloom and its extinction from early spring to late summer, with an accurate prediction for 7–8 d. With the support of the hydrodynamic model and biological macroalgae data, FMGDM can serve as a model tool to forecast floating macroalgal blooms in other regions.

scholarly journals Variability in phytoplankton biomass and effects of sea surface temperature based on satellite data from the Yellow Sea, China

PLoS ONE ◽  
2019 ◽  
Vol 14 (8) ◽  
pp. e0220058
Author(s):  
Chunli Liu ◽  
Qiwei Sun ◽  
Qianguo Xing ◽  
Sufen Wang ◽  
Danling Tang ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Satellite Data ◽  
Yellow Sea ◽  
Phytoplankton Biomass ◽  
Sea Surface ◽  
The Yellow Sea
Sign in / Sign up

Export Citation Format

Share Document