Spatial and temporal variability of biomass and composition of green tides in Ireland

Two bloom-forming species of Ulva (Chlorophyta) show different responses to seawater temperature and no antagonistic interaction

The generalized use of molecular identification tools indicated that multispecific green tides are more common than previously thought. Temporal successions between bloom-forming species on a seasonal basis were also revealed in different cold temperate estuaries, suggesting a key role of photoperiod and temperature controlling bloom development and composition. According to the Intergovernmental Panel on Climate Change, water temperatures are predicted to increase around 4°C by 2100 in Ireland, especially during late spring coinciding with early green tide development. Considering current and predicted temperatures, and photoperiods during bloom development, different eco-physiological experiments were developed. These experiments indicated that the growth of Ulva lacinulata was controlled by temperature, while U. compressa was unresponsive to the photoperiod and temperatures assayed. Considering a scenario of global warming for Irish waters, an earlier development of bloom is expected in the case of U. lacinulata. This could have significant consequences for biomass balance in Irish estuaries and the maximum accumulated biomass during peak bloom. The observed seasonal patterns and experiments also indicated that U. compressa may facilitate U. lacinulata development. When both species were co-cultivated, the culture performance showed intermediate responses to experimental treatments in comparison with monospecific cultures of both species.

Biomass and nutrient dynamics of major green tides in Ireland: Implications for biomonitoring

The control of macroalgal bloom development is central for protecting estuarine ecosystems. The identification of the nutrients limiting the development of macroalgal blooms, and their most likely sources is crucial for management strategies. Three Irish estuaries (Argideen, Clonakilty and Tolka) affected by green tides were monitored from June 2016 to August 2017. During each sampling occasion, biomass abundances, tissue N and P contents, and δ¹⁵N were determined for tubular and laminar morphologies of Ulva. All estuaries showed maximum biomass during summer and minimum during winter. Tissue nutrient contents revealed P rather than N limitation. The δ¹⁵N during the peak bloom indicated agriculture as the most likely source of nitrogen in the Argideen and Clonakilty, and urban wastewaters in the Tolka. No differences in the δ¹⁵N, and the tissue nutrients content were observed between morphologies. The period between May and July is most suitable for bioassessment of green tides.

Research on the dissipation of green tide and its influencing factors in the Yellow Sea based on Google Earth Engine

Since 2007, the outbreak of green tides has become the most serious ecological problem in the Yellow Sea. In this study, a new method was used to identify green tides in multi-source satellite data from 2007 to 2020, and the relationship between the conditions necessary for green tide dissipation and other environmental factors was discussed. We found a "wavy" trend of green tide scales over the 14-year dissipation period. The dissipation direction was influenced by sea surface wind (SSW) and sea surface circulation (SSC). Under the action of northeast moving SSW and SSC, green tides move away from the shore and drift northward; under the action of northwest or southwest moving SSW and SSC, they moved towards the shore and drift southward. The date of dissipation was influenced by sea surface temperature (SST) and precipitation, and high SST accelerated the process of green tide dissipation, while precipitation slowed it down.

To what extent can Ulva and Sargassum be detected and separated in satellite imagery?

Blooms of floating macroalgae have been reported around the world, among which are recurrent blooms of Ulva prolifera and Sargassum horneri in the Yellow Sea and East China Sea. While satellite remote sensing has often been used to estimate their distributions and abundance as well as to trace their origins, because the algae mats are often much smaller than the size of an image pixel, it is unclear to what extent they can be detected and discriminated from each other in satellite imagery. Using data collected from laboratory experiments and by the Sentinel-3 OLCI (Ocean and Land Colour Instrument) and Sentinel-2 MSI (Multi Spectral Instrument) satellite instruments, we conduct simulated experiments to determine the lower detection limit and discrimination limit for these two macroalgae in different water environments and under different atmospheric conditions. For OLCI, the detection limit for both macroalgae is about 0.5% of a pixel, while the discrimination limit varies between 0.8% for clear water and 2% for turbid water. For MSI, the detection limit is about 2%, while the discrimination limit is about 6% for all water types. Below these two limits, detection and discrimination of macroalgae in these regions using the two sensors are subject to large uncertainties, thus requiring additional caution when interpreting algae areas and tracing algae origins.

Assessing the Impact of Physical and Anthropogenic Environmental Factors in Determining the Habitat Suitability of Seagrass Ecosystems

Blue Carbon ecosystems such as mangroves, saltmarshes and seagrasses have been shown to sequester large amounts of carbon, and subsequently are receiving renewed interest from policy experts in light of climate change. Globally, seagrasses remain the most understudied of these ecosystems, with their total geographic extent largely unknown due to challenges in mapping dynamic coastal environments. As such, species distribution models (SDMs) have been used to identify areas of high suitability, in order to inform our understanding of where unmapped meadows may be located or to identify suitable sites for restoration and/or enhancement efforts. However, many SDMs parameterized to project seagrass distributions focus on physical and not anthropogenic variables (i.e., dredging, aquaculture), which can have negative impacts on seagrass meadows. Here we used verified datasets to identify the potential distribution of Zostera marina and Zostera noltei at a national level for the Republic of Ireland, using 19 environmental variables including both physical and anthropogenic. Using the Maximum Entropy method for developing the SDM, we estimated approximately 95 km2 of suitable habitat for Z. marina and 70 km2 for Z. noltei nationally with high accuracy metrics, including Area Under the Curve (AUC) values of 0.939 and 0.931, respectively for the two species. We found that bathymetry, maximum sea-surface temperature (SST) and minimum salinity were the most important environmental variables that explained the distribution of Z. marina and that high standard deviation of SST, mean SST and maximum salinity were the most important variables in explaining the distribution of Z. noltei. At a national level, we noted that it was primarily physical variables that determined the geographic distribution of seagrass, not anthropogenic variables. We unexpectedly modelled areas of high suitability in locations of anthropogenic disturbance (i.e., dredging, high pollution risk), although this may be due to the binary nature of SDMs capturing presence-absence and not the size and condition of the meadows, suggesting a need for future research to explore the finer scale impacts of anthropogenic activity. Subsequently, this research should foster discussion for researchers and practitioners working on sustainability projects related to Blue Carbon.

Characterization of the development stages and roles of nutrients and other environmental factors in green tides in the Southern Yellow Sea, China

Large-scale floating green tides in the Southern Yellow Sea (SYS) caused by the macroalgal species Ulva prolifera have been recurring for 13 years and have become one of the greatest marine ecological disasters in the world. In this study, we attempt to explore the development pattern of green tides and find its key environmental influencing factors. The satellite remote sensing data of the development process of green tides fit the logistic growth curve (R² = 0.93, P < 0.01) well, showing three distinct growth phases (lag, exponential growth, and short plateau phases). Correspondingly, the green tide-drifting area from the coast of Jiangsu to the nearshore waters of the Shandong Peninsula was divided into three sections: the lag phase zone (A), the exponential growth phase zone (B), and the plateau phase zone (C). Zone A in the south of Jiangsu coastal waters had abundant inorganic nutrients that were indispensable to the green tide initiation. Zone B was mainly located out of Haizhou Bay, south of 34.5° N and north of 35.5° N, where approximately 80% of the green tide biomass was generated. The rich bioavailable nutrient sources, suitable temperature, and irradiance in this area were the main promotion factors for the rapid growth and scale expansion of green tides. Wet precipitation in zone B in May and June also played an important role in the final scale of green tides. Zone C had poor nutrients, increasing temperature, and irradiance (high transparency), which limited the continued expansion of green tides, and organic nutrients might be an important support to green tides development in this region. The study based on the growth phases of green tides could help us further understand the eutrophication mechanism in the green tide outbreaks in SYS.

The arrival of a red invasive seaweed to a nutrient over-enriched estuary increases the spatial extent of macroalgal blooms

The red seaweed Agarophyton vermiculophyllum is an invasive species native to the north-west Pacific, which has proliferated in temperate estuaries of Europe, North America and Africa. Combining molecular identification tools, historical satellite imagery and one-year seasonal monitoring of biomass and environmental conditions, the presence of A. vermiculophyllum was confirmed, and the invasion was assessed and reconstructed. The analysis of satellite imagery identified the first bloom in 2014 and revealed that A. vermiculophyllum is capable of thriving in areas, where native bloom-forming species cannot, increasing the size of blooms (ca. 10%). The high biomass found during the peak bloom (>2 kg m^-2) and the observation of anoxic events indicated deleterious effects. The monitoring of environmental conditions and biomass variability suggests an essential role of light, temperature and phosphorous in bloom development. The introduction of this species could be considered a threat for local biodiversity and ecosystem functioning in a global change context.

Monitoring Water Transparency in Shallow and Eutrophic Lake Waters Based on GOCI Observations

Water transparency represented by the Secchi disk depth (Zsd) plays an important role in understanding water ecology environment variations, especially for optically complex and shallow lake waters. In this study, using in situ measured remote sensing reflectance (Rrs), diffuse attenuation coefficient (Kd), and Zsd data collected in Lake Taihu (China), a regional algorithm for estimating Kd from Rrs was designed, and the semi-analytical model proposed by Lee et al. (2015) (hereafter called Lee_2015 model) was refined using a linear scaling correction for remote sensing of Zsd. The results showed that a good agreement between the derived Kd and in situ measured data (mean absolute percentage error (MAPE) = 26% for Kd(490); MAPE < 5% for Kd at 443, 555, and 660 nm). The in situ Rrs-derived Zsd results using the refined Lee_2015 model compared well with the in situ measured Zsd (R2 = 0.72 and MAPE = 36%), which was an obvious improvement over the Lee_2015 model in our study region. Subsequently, the refined Lee_2015 model was applied to the geostationary ocean color imager (GOCI) observations between 2012 and 2018 to yield the spatial and temporal variations of water transparency in the Lake Taihu waters. The long-term mean distribution of Zsd revealed that water transparency values in the northeastern Lake Taihu were generally higher than those in the southwest part. Monthly climatological Zsd patterns suggested that the Zsd distributions had large temporal variability, and distinct monthly patterns of Zsd existed in different subregions of Lake Taihu. The significant interannual variations of Zsd in Lake Taihu are probably affected by a combination of the water column stability mainly caused by wind, water temperature, human activity, and riverine discharge. The present study can provide a new approach for quantifying water visibility and serve for water-color remote sensing of optically complex and highly turbid waters.

Green tides select for fast expanding Ulva strains

Green tides, the phenomenon whereby large volume of marine environment is taken over by the sea lettuce Ulva spp, are a seasonal occurrence thought to be caused mainly by anthropogenic eutrophication. The aggravation of green tide occurrence since the 1970s could however be due to the amplification of fast-growing strains within these areas. In this study, we compared the growth and metabolite content of 28 green tide Ulva strains against 100 non-green tide strains, under conditions close to those encountered in green tides areas. The aim was to determine whether the presence of specific characteristics intrinsic to green tide strains could in itself be a major factor for their reoccurrence. We confirmed that green tide strains have specific characteristics, with faster tissue expansion, higher protein and pigments, and lower starch content compared to non-green tide ones, thus highlighting a genetic component specific to green tide strains. Dry biomass accumulation, however, was not different between the two types of Ulva strains. Hence, we hypothesise that the selective pressure in green tide areas leads to the amplification of Ulva genotypes best adapted for this environment. Such selection of fast-growing strains would indicate that green tides are likely to become more prevalent and of higher magnitude over the coming years.