scholarly journals Spatiotemporal Patterns and Morphological Characteristics of Ulva prolifera Distribution in the Yellow Sea, China in 2016–2018

2019 ◽  
Vol 11 (4) ◽  
pp. 445 ◽  
Author(s):  
Yingzhi Cao ◽  
Yichen Wu ◽  
Zhixiang Fang ◽  
Xiaojian Cui ◽  
Jianfeng Liang ◽  
...  
Keyword(s):  
Yellow Sea ◽  
Vegetation Index ◽  
Morphological Changes ◽  
Surface Wind ◽  
Morphological Characteristics ◽  
Ulva Prolifera ◽  
Spatiotemporal Patterns ◽  
The Yellow Sea ◽  
Green Tide ◽  
Sea Surface Wind

The world’s largest macroalgal blooms, Ulva prolifera, have appeared in the Yellow Sea every summer on different scales since 2007, causing great harm to the regional marine economy. In this study, the Normalized Difference of Vegetation Index (NDVI) index was used to extract the green tide of Ulva prolifera from MODIS images in the Yellow Sea in 2016–2018, to investigate its spatiotemporal patterns and to calculate its occurrence probability. Using the standard deviational ellipse (SDE), the morphological characteristics of the green tide, including directionality and regularity, were analyzed. The results showed that the largest distribution and coverage areas occurred in 2016, with 57,384 km2 and 2906 km2, respectively and that the total affected region during three years was 163,162 km2. The green tide drifted northward and died out near Qingdao, Shandong Province, which was found to be a high-risk region. The coast of Jiangsu Province was believed to be the source of Ulva prolifera, but it was probably not the only one. The regularity of the boundary shape of the distribution showed a change that was opposite to the variation of scale. Several sharp increases were found in the parameters of the SDE in all three years. In conclusion, the overall situation of Ulva prolifera was still severe in recent years, and the sea area near Qingdao became the worst hit area of the green tide event. It was also shown that the sea surface wind played an important part in its migration and morphological changes.

scholarly journals Ulva prolifera green-tide outbreaks and their environmental impact in the Yellow Sea, China

2019 ◽  
Vol 6 (4) ◽  
pp. 825-838 ◽  
Author(s):  
Yongyu Zhang ◽  
Peimin He ◽  
Hongmei Li ◽  
Gang Li ◽  
Jihua Liu ◽  
...  
Keyword(s):  
Yellow Sea ◽  
Red Tide ◽  
Abiotic Factors ◽  
Management Strategies ◽  
Ulva Prolifera ◽  
The Yellow Sea ◽  
Green Tide ◽  
Biological Interactions ◽  
Green Tides ◽  
Carbon Cycles

Abstract The Ulva prolifera green tides in the Yellow Sea, China, which have been occurring since 2007, are a serious environmental problem attracting worldwide attention. Despite extensive research, the outbreak mechanisms have not been fully understood. Comprehensive analysis of anthropogenic and natural biotic and abiotic factors reveals that human activities, regional physicochemical conditions and algal physiological characteristics as well as ocean warming and biological interactions (with microorganism or other macroalgae) are closely related to the occurrence of green tides. Dynamics of these factors and their interactions could explain why green tides suddenly occurred in 2007 and decreased abruptly in 2017. Moreover, the consequence of green tides is serious. The decay of macroalgal biomass could result in hypoxia and acidification, possibly induce red tide and even have a long-lasting impact on coastal carbon cycles and the ecosystem. Accordingly, corresponding countermeasures have been proposed in our study for future reference in ecosystem management strategies and sustainable development policy.

scholarly journals Assessing Herbivorous Impacts of Apohale sp. on the Ulva prolifera Green Tide in China

2021 ◽  
Vol 12 ◽  
Author(s):  
Xiaoxiang Miao ◽  
Jie Xiao ◽  
Shiliang Fan ◽  
Yu Zang ◽  
Xuelei Zhang ◽  
...  
Keyword(s):  
Yellow Sea ◽  
Algal Biomass ◽  
Large Scale ◽  
Algal Growth ◽  
Ulva Prolifera ◽  
The Yellow Sea ◽  
Green Tide ◽  
Species Identity ◽  
Green Tides ◽  
The Southern Yellow Sea

An epiphytic gammarid species, Apohyale sp., was abundant in the floating Ulva prolifera (U. prolifera), which forms large-scale green tides in the Yellow Sea (YSGT). Field observation and laboratory experiments were subsequently conducted to study the species identity, abundance, and grazing effects on the floating algal biomass. The abundance of Apohyale sp. showed great spatial variation and varied from 0.03 to 1.47 inds g−1 in the YSGT. In average, each gram of Apohyale sp. body mass can consume 0.43 and 0.60 g algal mass of U. prolifera per day, and the grazing rates varied among the algae cultured with different nutritional seawaters. It was estimated that grazing of Apohale sp. could efficiently reduce ~0.4 and 16.6% of the algal growth rates in Rudong and Qingdao, respectively. The U. prolifera fragments resulting from gnawing of Apohyale sp. had a higher growth rate and similar photosynthetic activities compared to the floating algae, indicating probably positive feedback on the floating algal biomass. This research corroborated the significant impact of Apohyale sp. on the floating algal mass of YSGT through the top-down control. However, further research is needed to understand the population dynamics of these primary predators and hence their correlation with the expansion or decline of YSGT, especially under the complex food webs in the southern Yellow Sea.

scholarly journals A Lagrangian-based Floating Macroalgal Growth and Drift Model (FMGDM v1.0): application in the green tides of the Yellow Sea

2021 ◽  
Author(s):  
Fucang Zhou ◽  
Jianzhong Ge ◽  
Dongyan Liu ◽  
Pingxing Ding ◽  
Changsheng Chen
Keyword(s):  
Remote Sensing ◽  
Yellow Sea ◽  
Surface Wind ◽  
Ocean Model ◽  
Biological Data ◽  
The Yellow Sea ◽  
Green Tide ◽  
Observation Data ◽  
Green Tides ◽  
Drift Model

Abstract. Massive floating macroalgal blooms in the ocean have had an array of ecological consequences; thus, tracking their drifting pattern and predicting their biomass are important for their effective management. However, a high-resolution ecological dynamics model is lacking. In this study, a physical–ecological model, Floating Macroalgal Growth and Drift Model (FMGDM v1.0), was developed to determine the dynamic growth and drift pattern of floating macroalgal, based on the tracking, replication and extinction of Lagrangian particles. The position, velocity, quantity and represented biomass of particles are updated synchronously between the tracking module and the ecological module. The former is driven by ocean flows and sea surface wind, while the latter is controlled by the temperature, salinity, and irradiation. Based on the hydrodynamic models of the Finite-Volume Community Ocean Model and parameterized using a culture experiment of Ulva prolifera, which caused the largest bloom worldwide of the green tide in the Yellow Sea, China, this model was applied to simulate the green tides around the Yellow Sea in 2014 and 2015. The simulation result, distribution and biomass of green tides, was validated using remote sensing observation data and reasonably modeled the entire process of green tide bloom and its extinction from early spring to late summer. Given the prescribed spatial initialization from remote sensing observation, the model could provide accurate short-term (7–8 d) predictions of the spatial and temporal developments of the green tide. With the support of the hydrodynamic model and biological data of macroalgae, this model can forecast floating macroalgae blooms in other regions.

Ulva prolifera Monitoring Study in the Yellow Sea from Multi-Temporal Remote Sensing Images

2014 ◽  
Vol 675-677 ◽  
pp. 1201-1206
Author(s):  
Yan Zhou ◽  
Bin Zhou ◽  
Ying Ying Gai
Keyword(s):  
Remote Sensing ◽  
Yellow Sea ◽  
Wind Field ◽  
Surface Wind ◽  
Ulva Prolifera ◽  
Sea Surface ◽  
Remote Sensing Images ◽  
Sea Surface Wind ◽  
Multi Temporal ◽  
Surface Wind Field

Multi-temporal Moderate resolution Imaging Spectroradiometer (MODIS) remote sensing images were used to monitor the massive blooms of floating green tide algae Ulva prolifera in the midwest of Yellow Sea (YS). In addition, from the marine environment elements of sea surface temperature (SST) and sea surface wind field, the growth and drift characteristic of U. Prolifera were studied based on MODIS thermal infrared channel SST data and Windsat wind field data. In May 2014, U. Prolifera accumulation areas were first found in central YS north of Subei Bank. With summer arrival, seawater temperature of ocean surface gradually increased in YS, It provided a more suitable environment for the growth of U. Prolifera. Due to the prevailing northerly winds in central and western YS, U. Prolifera advected to the coastal waters of Shandong Peninsula, and spread to the northeastward. In late June, it had a massive bloom and reached the maximum coverage in the northern YS. The U. Prolifera drift characteristic was confirmed by the analysis on SST and sea surface wind field, and the result shows that under the environment of suitable sea surface temperature, the driving force of the prevailing sea surface wind field might be the main reason of YS U. Prolifera bloom occurrence.

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.

Variations of morphology and photosynthetic performances of Ulva prolifera during the whole green tide blooming process in the Yellow Sea

2013 ◽  
Vol 92 ◽  
pp. 35-42 ◽  
Author(s):  
Jian Heng Zhang ◽  
Yuan Zi Huo ◽  
Zheng Long Zhang ◽  
Ke Feng Yu ◽  
Qing He ◽  
...  
Keyword(s):  
Yellow Sea ◽  
Ulva Prolifera ◽  
The Yellow Sea ◽  
Green Tide ◽  
Photosynthetic Performances

Temporal succession of community structure and biphase ratio in a natural population of Ulva spp. (Chlorophyta) attached to Pyropia rafts in the Yellow Sea, China

2019 ◽  
Vol 62 (6) ◽  
pp. 549-561
Author(s):  
Yu Du ◽  
Yuan Ao ◽  
Yuan He ◽  
Yi Yin ◽  
Yafeng Ma ◽  
...  
Keyword(s):  
Yellow Sea ◽  
Internal Transcribed Spacer ◽  
Algal Blooms ◽  
Null Model ◽  
Ulva Prolifera ◽  
The Yellow Sea ◽  
Green Tide ◽  
Continuous Change ◽  
Green Tides ◽  
Temporal Succession

Abstract Green tide algal blooms occur worldwide, especially in China’s Yellow Sea, and have caused serious damage to local ecological environments and economies. As a dominant agent of green tides, the green macroalga Ulva has caused widespread concern. In this study, phylogenetic clades were constructed among related Ulva species isolated from Pyropia rafts at six sites over 1.5 years based on internal transcribed spacer (ITS) and tufA sequences. In addition, traditional observation ploidy methods and flow cytometry methods were used to analyse continuous change in the biphase and sex ratios of Ulva species and to assess the changes in phase advantages over time. The results showed that the perennial Ulva populations on rafts mainly consisted of Ulva flexuosa and Ulva prolifera, and the biphasic dominance of the attached Ulva populations changed with the seasons: sporophytes were predominant mainly in winter and spring, and gametophytes were predominant mainly in summer and autumn. At the same time, there were some differences in gametophyte and sporophyte frequencies (mainly sporophyte biased) compared to the null model prediction of a √2:1 ratio, while the sex ratio of male and female gametophytes remained 1:1 throughout the year. Our results indicate the presence of both phases of bloom-forming species of Ulva in green tides year round, and that multiple generations coexist and grow continuously.

scholarly journals Remote Sensing Observations of the Winter Yellow Sea Warm Current Invasion into the Bohai Sea, China

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Jie Guo ◽  
Hua Zhang ◽  
Tingwei Cui ◽  
Yijun He ◽  
Jie Zhang ◽  
...  
Keyword(s):  
Yellow Sea ◽  
Bohai Sea ◽  
Chlorophyll Concentration ◽  
Surface Wind ◽  
Sea Surface ◽  
The Yellow Sea ◽  
Yellow Sea Warm Current ◽  
Warm Current ◽  
The Bohai Sea ◽  
Sea Surface Wind

Using ASCAT, QuikSCAT, and MODIS data, we analyzed the sea surface wind field, temperature, salinity, and chlorophyll concentrations in the mixed zone between the Bohai Sea and Yellow Sea in the winter (the period of winter 2013 included December 2013 and January-February 2014) from 2002 to 2013. We found that the intrusion of the Yellow Sea Warm Current into the Bohai Sea occurred three times in the winters of 2007 (strongest), 2004, and 2013 (weakest) during this 12-year period. We present detailed validation of the intrusion in 2013. This study shows that the intrusion of the Yellow Sea Warm Current into the Bohai Sea occurred when the wind speed, sea surface temperature, and salinity were above (or close to) the multiyear average and the chlorophyll concentration was less than the multiyear average.

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