Annually recurrent green-tides in the Yellow Sea have been shown to result from direct disposal into the sea of fouling Ulva from Pyropia aquaculture. The role abiotic factors play in Ulva biomass accumulation on rafts was studied to find ways to mitigate this problem. Dissolved inorganic nitrogen (DIN) was very high at all sites, but the highest Ulva biomass was associated with the lowest DIN and anthropogenic N. Under luxuriant background nutrient conditions, variability in temperature and periods of emersion, rather than pH, light and salinity determined Ulva biomass. Two dominant species of Ulva displayed differing tolerances to temperature and desiccation which helped explain why Ulva prolifera dominates floating green-tides. Rather than trying to mitigate green-tides only by reducing nutrient pollution, an earlier harvest of Pyropia in southern Jiangsu Province especially before temperatures increase greatly above 10°C during April, could reduce the biomass of U. prolifera disposed from rafts.

δ15N of annual (Ulva sp., Porphyra sp.) and perennial intertidal seaweed species (Chondrus crispus, Fucus sp.) collected on 17 sampling points along the French coast of the English Channel in 2012 and 2013 were assessed on their suitability as bioindicators of N pollution in coastal areas. A sine function applied for δ15N time series data showed for all the species the same seasonal trend with lowest δ15N values in April and highest in summer but with no significant interspecific differences of amplitude (α) and phase angle (ϕ). This model provides a useful tool for monitoring the inter-annual changes of N pollution. An interspecific variability of δ15N values was observed, probably due to their tolerance to emersion. An in vitro study for comparing the kinetic acquisition of the isotopic signal and N uptake mechanisms of each species underlined the influence of algal physiology on the δ15N interspecific variability.

Compositions, changes and biomass of attached Ulva species on Porphyra rafts along the radial sandbank in the Yellow Sea were investigated, and potential contributions to green tides was analyzed. Ulva prolifera, Ulva flexuosa and Ulva linza were all appeared throughout the investigated period. U. prolifera and U. flexuosa dominated attached Ulva population on Porphyra rafts. Attached Ulva species biomass showed obviously spatial and temporal variations. Temperature, Ulva microscopic propagules and human activities were main factors to influence attached Ulva species biomass. The total attached Ulva species biomass was more than 20,000 fresh weight tons in April, and the green tide causative species U. prolifera accounted 51.03% in April 2013 before green tides occurred. The high biomass of attached Ulva species would contribute most to green tides in the Yellow Sea. But how attached Ulva species on Porphyra rafts contributing to green tides in the Yellow Sea should be further studied.

The large green-tide events that occurred in the Yellow Sea in 2008 (3489km²) and 2009 (4994km²) are shown to be novel events preceded only once by a much smaller event in 2007 (82km²). The blooms originated in the coastal area of Jiangsu province and spread north-east towards the Shandong Peninsula. The blooms grew at different rates and mesoscale variability in surface winds explained the differences in the spatial and temporal patterns of blooms in 2008 and 2009. The 2009 bloom was tracked to its origin immediately offshore of extensive intertidal flats between Yancheng and Nantong where recent rapid expansion of Porphyra aquaculture has occurred. We review published hypotheses which have been advanced to explain the occurrence of blooms and in light of our findings, we conclude that the accumulation and disposal of waste Ulva prolifera from Porphyra aquaculture rafts is the most likely cause of the blooms.

The green tides caused by Ulva prolifera have become a recurrent phenomenon in Yellow Sea, China. Investigating the factors governing the biomass of green tides is important for developing management strategies. In this study, an U. prolifera growth model was combined with a hydrodynamic model. This biophysical model can reasonably reproduce the spatiotemporal variation of the green tides in 2012. Among three zones (northern, central, and southern-zones) of Porphyra mariculture region, the northern and central zones were more important in controlling the bloom intensity, and the central zone was the key area in controlling the amount of biomass landed on beaches. Due to the limitation of temperature and nutrients, an earlier or postponed facility recycling might effectively reduce the magnitude of green tides in 2012. This study provides useful information for mitigation of green tides and management of Porphyra mariculture.

Besides being food and a refuge to marine species, macroalgae are a powerful and renewable economic resource. However, they may introduce microplastics (MPs) in the trophic chain. We developed a reliable analytical method to characterize and quantify MPs in common and edible macroalgae. Several digestion methods and filters, along with various measurement options, were studied. A new enzymatic-oxidative protocol with a unique final filtration was selected and validated with a mixture of 5 commercial macroalgae (Undaria pinnatifida spp, Porphyra spp, Ulva spp, Laminaria ochroleuca and Himanthalia elongate). Further, it was shown that washing the macroalgae to release MPs is suboptimal and the potential adhesion of MPs to macroalgae was evaluated. A filter subsampling strategy that scans 33.64 % of its surface reduced the time required to characterize <70 μm particles and fibres directly on the 47 mm diameter filter using an IR microscope (1 sample/day).

Since 2007, green tide blooms with Ulva prolifera as the dominant species have occurred every summer in the Yellow Sea. Biomass is a critical parameter used to describe the severity of green tide blooms. In this study, we analyzed the relationships between several indices (normalized difference vegetation index (NDVI), floating algae index (FAI), ratio vegetation index (RVI), enhanced vegetation index (EVI), ocean surface algal bloom index (OSABI), Korea Ocean Satellite Center (KOSC) approach) and the biomass per unit area of Ulva prolifera by using the in situ measurements from a water tank experiment. EVI, NDVI, and FAI showed strong exponential relationships with Ulva prolifera biomass per unit area. In order to apply the relationships to satellite remote sensing data, the impacts of the atmosphere (different aerosol optical depth at 550 nm) and mixed pixels to the relationships were analyzed. The results show that atmosphere has little effect on the relationship between EVI and Ulva prolifera biomass per unit area with R2 = 0.94 and APD (the average percentage deviation) = 19.55% when EVI is calculated from Rrc (Rayleigh-corrected reflectance), and R2 = 0.95 and APD = 17.53% when EVI is calculated from Rtoa (top-of-atmosphere reflectance). Due to the low sensitivity to the atmosphere, the EVI relationship can be directly utilized in the top-of-atmosphere (TOA) reflectance without atmospheric correction. In addition, the EVI was slightly affected by mixed pixels with the APD only increased by ~10%. The EVI relationship was then applied to a long MODIS image time series to obtain the maximal total biomass of floating Ulva prolifera in the Yellow Sea from 2007 to 2016. The results showed that the maximum and minimum total biomass occurred in 2016 (~1.17 million tons) and 2012 (~0.074 million tons), respectively. The main factors that caused the inter-annual biomass variability were analyzed. The total amount of nutrients from Sheyang River which was the largest river on the northern coast of Jiangsu Province, and Porphyra cultivation in the Radial Sand Ridges of Jiangsu Province had both strong correlation with Ulva prolifera total biomass.