High-resolution Water Temperature Research Articles

High-resolution water temperature and salinity evolutions and associated drivers of the North Yellow Sea during the Late-Holocene

The mud deposit areas on continental shelf have developed in a relatively steady sedimentary condition with high sedimentation rates, thus rendering them ideal regions for exploring high-resolution paleo-sedimentary environment records. Since the sedimentary environment of the continental shelf is subject to the compound influence of multiple factors, the reconstruction of water salinity and temperature and comprehensive analysis of their response to global climate change remains challenging. Therefore, the present study characterized water salinity and temperature of the North Yellow Sea (NYS) using proxies, such as ratios of halogen elements of sediments and stable isotopic compositions of benthic foraminifera, and found the halogen elements of Cl in sediments was good proxy for water salinity. The evolutions of water salinity and temperature of the NYS for the past 3000 years were reconstructed, while the evolution stages and drivers of the sedimentary environment were explored. From approximately 3000 cal yr BP, the sea bottom salinity and temperature of the NYS were found to follow the same evolution trends predominantly consisting of the three stages: relatively low seawater salinity and temperature during 3000−2000 cal yr BP; relatively high seawater salinity and temperature during 2000−460 cal yr BP; and rapid changes of seawater salinity and temperature since 460 cal yr BP. The changes in seawater salinity and temperature of the NYS were largely driven by the East Asian winter monsoon (EAWM) as well as the influence of the Kuroshio Current. As the EAWM fluctuated, changes occurred in the flux of low temperature, low salinity coastal current water into the Yellow Sea, with concomitant changes in bottom temperature and salinity. Strengthening of the Kuroshio Current promoted the development of the Yellow Sea Warm Current, while the influx of warm, salty water into the Yellow Sea influenced the respective sea region. The abrupt global climate changes such as the “Little Ice Age” and the Medieval Warm Period first affected the East Asian monsoon, followed by the respective sea region.

Using qPCR and high-resolution sensor data to model a multi-species Pseudo-nitzschia (Bacillariophyceae) bloom in southeastern Australia

Harmful algal blooms, including those caused by the toxic diatom Pseudo-nitzschia, can have significant impacts on human health, ecosystem functioning and ultimately food security. In the current study we characterized a bloom of species of Pseudo-nitzschia that occurred in a south-eastern Australian oyster-growing estuary in 2019. Using light microscopy, combined with molecular (ITS/5.8S and LSU D1-D3 rDNA regions) and toxicological evidence, we observed the bloom to consist of multiple species of Pseudo-nitzschia including P. cf. cuspidata, P. hasleana, P. fraudulenta and P. multiseries, with P. cf. cuspidata being the only species that produced domoic acid (3.1 pg DA per cell). As several species of Pseudo-nitzschia co-occurred, only one of which produced DA, we developed a rapid, sensitive and efficient quantitative real-time polymerase chain reaction (qPCR) assay to detect only species belonging to the P. pseudodelicatissima complex Clade I, to which P. cf. cuspidata belongs, and this indicated that P. cuspidata or closely related strains may have dominated the Pseudo-nitzschia community at this time. Finally, using high resolution water temperature and salinity sensor data, we modeled the relationship between light microscopy determined abundance of P. delicatissima group and environmental variables (temperature, salinity, rainfall) at two sites within the estuary. A total of eight General Linear Models (GLMs) explaining between 9 and 54% of the deviance suggested that the temperature (increasing) and/or salinity (decreasing) data were generally more predictive of high cell concentrations than the rainfall data at both sites, and that overall, cell concentrations were more predictive at the more oceanic site than the more upstream site, using this method. We conclude that the combination of rapid molecular methods such as qPCR and real-time sensor data modeling, can provide a more rapid and effective early warning of harmful algal blooms of species of Pseudo-nitzschia, resulting in more beneficial regulatory and management outcomes.