Storm-induced changes in pCO2 at the sea surface over the northern South China Sea during Typhoon Wutip

In situ oceanographic measurements were made before and after the passage of Typhoon Wutip in September 2013 over the northern South China Sea. The surface geostrophic circulation over this region inferred from satellite altimetry data features a large‐size anticyclonic eddy, a small‐size cyclonic eddy, and smaller‐size eddies during this period. Significant typhoon‐induced changes occurred in the partial pressure of CO2 at the sea surface (pCO2sea) during Wutip. Before the passage of Wutip, pCO2sea was about 392.92 ± 1.83, 390.31 ± 0.50, and 393.04 ± 4.31 μatm over the cyclonic eddy water, the anticyclonic eddy water, and areas outside two eddies, respectively. The entire study region showed a carbon source (1.31 ± 0.46 mmol CO2 m?2 d?1) before Wutip. In the cyclonic eddy water after Wutip, high sea surface salinity (SSS), low sea surface temperature (SST), and high pCO2sea (413.05 ± 7.56 μatm) made this area to be a carbon source (3.30 ± 0.75 mmol CO2 m?2 d?1). In the anticyclonic eddy water after Wutip, both the SSS and SST were lower, pCO2sea was also lower (383.03 ± 3.72 μatm), and this area became a carbon sink (-0.11 ± 0.55 mmol CO2 m?2 d?1), in comparison with the pretyphoon conditions. The typhoon‐induced air‐sea CO2 flux reached about 0.03 mmol CO2 m?2 d?1. Noticeable spatial variations in pCO2sea were affected mainly by the typhoon‐induced mixing/upwelling and vertical stratifications. This study suggests that the local air‐sea CO2 flux in the study region was affected significantly by oceanographic conditions during the typhoon

Ecological Response of Phytoplankton to the Oil Spills in the Oceans

Oil spills in oceans have substantial influence on marine ecosystems. This study investigates 21 oil spills in the world. Analyzing Chlorophyll-a (Chl-a) from Moderate Resolution Imaging Spectroradiomerer (MODIS) data after Penglai oil spills on 4 June 2011, found a bloom with peak value of Chl-a (13.66 mg m−3) spread over an area of 800 km2 during 18–25 June 2011, and a pronounced increase in the monthly Chl-a concentration (6.40 mg m−3) on June 2012 in the Bohai Sea. Out of the 21 oil spills, 14 blooms were observed, while 11 blooms associated with oil spills in the time interval of 3–10 months. In total, about 75% blooms occurred during June–August. Among all 14 blooms, 72% appeared when temperature was warm (20–30 °C), 7% appeared when temperature was low (10–20 °C), and the remaining 21% occurred when temperature was lower than 10 °C. This research concludes that the odds of a phytoplankton bloom after an oil spillage are higher at the time of higher temperature (\u3e20 °C). The short-term impact of the oil spills on ecosystem could mainly depend on the quantity and composition of oil, while the long-term impact of the oil spills on ecosystem could be related to biodegradation of microorganisms

Dispensable role of Drosophila ortholog of LRRK2 kinase activity in survival of dopaminergic neurons

<p>Abstract</p> <p>Background</p> <p>Parkinson's disease (PD) is the most prevalent incurable neurodegenerative movement disorder. Mutations in <it>LRRK2 </it>are associated with both autosomal dominant familial and sporadic forms of PD. <it>LRRK2 </it>encodes a large putative serine/threonine kinase with GTPase activity. Increased LRRK2 kinase activity plays a critical role in pathogenic LRRK2 mutant-induced neurodegeneration <it>in vitro</it>. Little is known about the physiological function of LRRK2.</p> <p>Results</p> <p>We have recently identified a <it>Drosophila </it>line with a P-element insertion in an ortholog gene of human <it>LRRK2 </it>(<it>dLRRK</it>). The insertion results in a truncated <it>Drosophila </it>LRRK variant with N-terminal 1290 amino acids but lacking C-terminal kinase domain. The homozygous mutant fly develops normally with normal life span as well as unchanged number and pattern of dopaminergic neurons. However, <it>dLRRK </it>mutant flies were selectively sensitive to hydrogen peroxide induced stress but not to paraquat, rotenone and β-mercaptoethanol induced stresses.</p> <p>Conclusion</p> <p>Our results indicate that inactivation of <it>d</it>LRRK kinase activity is not essential for fly development and suggest that inhibition of LRRK activity may serve as a potential treatment of PD. However, <it>d</it>LRRK kinase activity likely plays a role in protecting against oxidative stress.</p

Detection and Monitoring of Marine Pollution Using Remote Sensing Technologies

Recently, the marine habitat has been under pollution threat, which impacts many human activities as well as human life. Increasing concerns about pollution levels in the oceans and coastal regions have led to multiple approaches for measuring and mitigating marine pollution, in order to achieve sustainable marine water quality. Satellite remote sensing, covering large and remote areas, is considered useful for detecting and monitoring marine pollution. Recent developments in sensor technologies have transformed remote sensing into an effective means of monitoring marine areas. Different remote sensing platforms and sensors have their own capabilities for mapping and monitoring water pollution of different types, characteristics, and concentrations. This chapter will discuss and elaborate the merits and limitations of these remote sensing techniques for mapping oil pollutants, suspended solid concentrations, algal blooms, and floating plastic waste in marine waters

Composite Analysis-Based Machine Learning for Prediction of Tropical Cyclone-Induced Sea Surface Height Anomaly

Sea surface height anomaly (SSHA) induced by tropical cyclones (TCs) is closely associated with oscillations and is a crucial proxy for thermocline structure and ocean heat content in the upper ocean. The prediction of TC-induced SSHA, however, has been rarely investigated. This study presents a new composite analysis-based random forest (RF) approach to predict daily TC-induced SSHA. The proposed method utilizes TC’s characteristics and pre-storm upper oceanic parameters as input features to predict TC-induced SSHA up to 30 days after TC passage. Simulation results suggest that the proposed method is skillful at inferring both the amplitude and temporal evolution of SSHA induced by TCs of different intensity groups. Using a TC-centered 5°×5° box, the proposed method achieves highly accurate prediction of TC-induced SSHA over the Western North Pacific with root mean square error of 0.024m, outperforming alternative machine learning methods and the numerical model. Moreover, the proposed method also demonstrated good prediction performance in different geographical regions, i.e., the South China Sea and the Western North Pacific subtropical ocean. The study provides insight into the application of machine learning in improving the prediction of SSHA influenced by extreme weather conditions. Accurate prediction of TC-induced SSHA allows for better preparedness and response, reducing the impact of extreme events (e.g., storm surge) on people and property

Comparison of machine learning algorithms for retrieval of water quality indicators in case-II waters: a case study of Hong Kong

Anthropogenic activities in coastal regions are endangering marine ecosystems. Coastal waters classified as case-II waters are especially complex due to the presence of different constituents. Recent advances in remote sensing technology have enabled to capture the spatiotemporal variability of the constituents in coastal waters. The present study evaluates the potential of remote sensing using machine learning techniques, for improving water quality estimation over the coastal waters of Hong Kong. Concentrations of suspended solids (SS), chlorophyll-a (Chl-a), and turbidity were estimated with several machine learning techniques including Artificial Neural Network (ANN), Random Forest (RF), Cubist regression (CB), and Support Vector Regression (SVR). Landsat (5,7,8) reflectance data were compared with in situ reflectance data to evaluate the performance of machine learning models. The highest accuracies of the water quality indicators were achieved by ANN for both, in situ reflectance data (89%-Chl-a, 93%-SS, and 82%-turbidity) and satellite data (91%-Chl-a, 92%-SS, and 85%-turbidity. The water quality parameters retrieved by the ANN model was further compared to those retrieved by “standard Case-2 Regional/Coast Colour” (C2RCC) processing chain model C2RCC-Nets. The root mean square errors (RMSEs) for estimating SS and Chl-a were 3.3 mg/L and 2.7 µg/L, respectively, using ANN, whereas RMSEs were 12.7 mg/L and 12.9 µg/L for suspended particulate matter (SPM) and Chl-a concentrations, respectively, when C2RCC was applied on Landsat-8 data. Relative variable importance was also conducted to investigate the consistency between in situ reflectance data and satellite data, and results show that both datasets are similar. The red band (wavelength ≈ 0.665 µm) and the product of red and green band (wavelength ≈ 0.560 µm) were influential inputs in both reflectance data sets for estimating SS and turbidity, and the ratio between red and blue band (wavelength ≈ 0.490 µm) as well as the ratio between infrared (wavelength ≈ 0.865 µm) and blue band and green band proved to be more useful for the estimation of Chl-a concentration, due to their sensitivity to high turbidity in the coastal waters. The results indicate that the NN based machine learning approaches perform better and, thus, can be used for improved water quality monitoring with satellite data in optically complex coastal waters

Vertical distribution of pH in the top ~10 m of deep-ocean sediments: Analysis of a unique dataset

We analyze, for the first time in the oceanographic literature, pH over the top ~10 m of the sediment (down to 11.9 m) in a deep-sea environment, together with the oxidation/reduction potential and concentrations of solid organic carbon (OC) and CaCO3. A total of 1157 sediment cores were collected from years 2000 to 2011 over &gt;300,000 km2 in the South China Sea, at water depths up to 3702 m. We found that there were marked downward pH increases in the upper 2 m of the sediment (first 20-40 ka, corresponding to the geochemically active period). In deeper, older sediment (up to 200 ka), pH was generally less variable with depth but not uniform, and solid OC may have been consumed down to ≥10 m depth. This reflected interactions between in situ geochemical diagenetic processes, which tended to create vertical variations, and vertical diffusion of ions, which tended to even out vertical variability. In other words, there were slow diagenetic geochemical processes in the sediment layer below 2 m, and the effects of these in situ processes were partly offset by vertical diffusion. Overall, our study identified a previously unknown consistent pH difference between the upper 2 m of the sediment and the underlying layer down to ≥10 m, and suggested combinations of geochemical diagenetic processes and vertical diffusion of ions in the porewater to explain it. These results provide a framework for further studies of pH in the top multi-meter layer of the sediment in the World Ocean

Pathogenic Connexin-31 Forms Constitutively Active Hemichannels to Promote Necrotic Cell Death

Mutations in Connexin-31 (Cx31) are associated with multiple human diseases including erythrokeratodermia variabilis (EKV). The molecular action of Cx31 pathogenic mutants remains largely elusive. We report here that expression of EKV pathogenic mutant Cx31R42P induces cell death with necrotic characteristics. Inhibition of hemichannel activity by a connexin hemichannel inhibitor or high extracellular calcium suppresses Cx31R42P-induced cell death. Expression of Cx31R42P induces ER stress resulting in reactive oxygen species (ROS) production, in turn, to regulate gating of Cx31R42P hemichannels and Cx31R42P induced cell death. Moreover, Cx31R42P hemichannels play an important role in mediating ATP release from the cell. In contrast, no hemichannel activity was detected with cells expressing wildtype Cx31. Together, the results suggest that Cx31R42P forms constitutively active hemichannels to promote necrotic cell death. The Cx31R42P active hemichannels are likely resulted by an ER stress mediated ROS overproduction. The study identifies a mechanism of EKV pathogenesis induced by a Cx31 mutant and provides a new avenue for potential treatment strategy of the disease

Satellite ocean colour algorithm for Prochlorococcus, Synechococcus, and picoeukaryotes concentration retrieval in the South China Sea

An algorithm for retrieval of surface waters cell concentrations (in cell/ml) for three picophytoplankton components, Prochlorococcus (Pro), Synechococcus (Syn), and picoeukaryotes (Peuk) in the South China Sea (SCS), from ocean colour satellite data was developed and tested. Level 3 merged multisensor Ocean Colour Climate Change Initiative satellite data is used. Training is performed using in situ data on abundances of the three phytoplankton components. Several predictors derived from satellite reflectance data were tested. The regression form that assures the highest accuracy of the algorithm was chosen based on cross-validation (CV). According to the CV on test data subset, the algorithm performance is characterized by the r value 0.89, 0.72, and 0.73 and MAPD 38, 71 and 51% for Peuk, Pro, and Syn respectively. This is one of the few studies aimed at the Peuk, Pro, and Syn distribution research in the northern SCS using ocean colour satellite data. This is the only research providing algorithm with accuracy estimates of the Peuk, Pro, and Syn concentrations retrieval from the ocean colour data. Analysis of the developed algorithm allows us to conclude that both mechanisms (specific spectral features caused by pigments composition and spectrum features sensitive to general primary productivity, e.g. band ratios in 443-510 nm range and spectrum absolute values) are important for getting accurate information on the picophytoplankton composition. (C) 2018 COSPAR. Published by Elsevier Ltd. All rights reserved