Dissimilatory nitrate reduction processes, including denitrification, anaerobic ammonium oxidation (ANAMMOX), and dissimilatory nitrate reduction to ammonium (DNRA), play an important role in controlling the nitrate dynamics and fate in estuarine and coastal environments. We investigated potential rates of denitrification, ANAMMOX, and DNRA in the sediments of the Yangtze Estuary via slurry incubation experiments combined with isotope-tracing techniques to reveal their respective contributions to total nitrate reduction in this hypereutrophic estuarine ecosystem. Measured rates of denitrification, ANAMMOX, and DNRA ranged from 0.06 to 4.51 μmol N kg À1 h À1, 0.01 to 0.52 μmol N kg À1 h À1, and 0.03 to 0.89 μmol N kg À1 h À1, respectively. These potential dissimilatory nitrate reduction process rates correlated significantly with salinity, sulfide, organic carbon, and nitrogen. Denitrification contributed 38-96% total nitrate reduction in the Yangtze Estuary, as compared to 3-45% for DNRA and 1-36% for ANAMMOX. In total, the denitrification and ANAMMOX processes removed approximately 25% of the external inorganic nitrogen transported annually into the estuary. In contrast, most external inorganic nitrogen was retained in the estuary and contributes substantially to the severe eutrophication of the Yangtze Estuary.

This study investigated net anthropogenic nitrogen inputs (NANI, including atmospheric nitrogen deposition, nitrogenous fertilizer use, net nitrogen import in food and feed, and agricultural nitrogen fixation) and the associated relationship with riverine dissolved inorganic nitrogen (DIN) export in the Yangtze River basin during the 1980–2012 period. The total NANI in the Yangtze River basin has increased by more than twofold over the past three decades (3537.0 ± 615.3 to 8176.6 ± 1442.1 kg N km−2 yr−1). The application of chemical fertilizer was the largest component of NANI in the basin (51.1%), followed by net nitrogen import in food and feed (26.0%), atmospheric nitrogen deposition (13.2%), and agricultural nitrogen fixation (9.7%). A regression analysis showed that the riverine DIN export was strongly correlated with NANI and the annual water discharge (R2 = 0.90, p < 0.01). NANI in the Yangtze River basin was estimated to contribute 37–66% to the riverine DIN export. We also forecasted future variations in NANI and riverine DIN export for the years 2013 to 2030, based on possible future changes in human activities and the climate. This work provides a quantitative understanding of NANI in the Yangtze River basin and its effects on riverine DIN export and helps to develop integrated watershed nitrogen management strategies.

Over the past several decades, human activities have caused substantial enrichment of reactive nitrogen in China’s coastal wetlands. Although anaerobic ammonium oxidation (anammox), the process of oxidizing ammonium into dinitrogen gas through the reduction of nitrite, is identified as an important process for removing reactive nitrogen, little is known about the dynamics of anammox and its contribution to nitrogen removal in nitrogen-enriched environments. Here, we examine potential rates of anammox and associate them with bacterial diversity and abundance across the coastal wetlands of China using molecular and isotope tracing techniques. High anammox bacterial diversity was detected in China’s coastal wetlands and included Candidatus Scalindua, Kuenenia, Brocadia, and Jettenia. Potential anammox rates were more closely associated with the abundance of anammox bacteria than to their diversity. Among all measured environmental variables, temperature was a key environmental factor, causing a latitudinal distribution of the anammox bacterial community composition, biodiversity and activity along the coastal wetlands of China. Based on nitrogen isotope tracing experiments, anammox was estimated to account for approximately 3.8–10.7% of the total reactive nitrogen removal in the study area. Combined with denitrification, anammox can remove 20.7% of the total external terrigenous inorganic nitrogen annually transported into China’s coastal wetland ecosystems.

Denitrification plays a critical role in nitrogen removal in estuarine and coastal ecosystems. In this study, the community composition, diversity, abundance, and distribution of cytochrome cd1-type nitrite reductase gene (nirS)-harboring denitrifiers in intertidal sediments of the Yangtze Estuary were analyzed using polymerase chain reaction (PCR)-based clone libraries and quantitative PCR techniques. Clone library analysis showed that the nirS-encoding bacterial biodiversity was significantly higher at the lower salinity sites than at the higher salinity sites. However, there was no significant seasonal difference in the nirS gene diversity between summer and winter. Phylogenetic analysis revealed that the nirS-harboring denitrifier communities at the study area had distinctive spatial heterogeneity along the estuary. At the lower salinity sites, the nirS-harboring bacterial community was co-dominated by clusters III and VII; while at the higher salinity sites, it was dominated by cluster I. Canonical correspondence analysis indicated that the community compositions of nirS-type denitrifiers were significantly correlated with salinity, ammonium, and nitrate. Quantitative PCR results showed that the nirS gene abundance was in the range of 1.01 × 10(6) to 9.00 × 10(7) copies per gram dry sediment, without significant seasonal variation. Among all the environmental factors, the nirS gene abundance was only significantly related to the change of salinity. These results can extend our current knowledge about the composition and dynamics of denitrification microbial community in the estuarine ecosystem.

Nitrogen mineralization is a key biogeochemical process transforming organic nitrogen to inorganic nitrogen in estuarine and coastal sediments. Although sedimentary nitrogen mineralization is an important internal driver for aquatic eutrophication, few studies have investigated sedimentary nitrogen mineralization in these environments. Sediment-slurry incubation experiments combined with 15N isotope dilution technique were conducted to quantify the potential rates of nitrogen mineralization in surface sediments of the Yangtze Estuary. The gross nitrogen mineralization (GNM) rates ranged from 0.02 to 5.13 mg N kg-1 d-1 in surface sediments of the study area. The GNM rates were generally higher in summer than in winter, and the relative high rates were detected mainly at sites near the north branch and frontal edge of this estuary. The spatial and temporal distributions of GNM rates were observed to depend largely on temperature, salinity, sedimentary organic carbon and nitrogen contents, and extracellular enzyme (urease and L-glutaminase) activities. The total mineralized nitrogen in the sediments of the Yangtze Estuary was estimated to be about 6.17 × 105 t N yr-1, and approximately 37% of it was retained in the estuary. Assuming the retained mineralized nitrogen is totally released from the sediments into the water column, which contributed 12–15% of total dissolved inorganic nitrogen (DIN) sources in this study area. This result indicated that the mineralization process is a significant internal nitrogen source for the overlying water of the Yangtze Estuary, and thus may contribute to the estuarine and coastal eutrophication.

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Finding hot topics in scholarly fields can help researchers to keep up with the latest concepts, trends, and inventions in their field of interest. Due to the rarity of complete large-scale scholarly data, earlier studies target this problem based on manual topic extraction from a limited number of domains, with their focus solely on a single feature such as coauthorship, citation relations, and etc. Given the compromised effectiveness of such predictions, in this paper we use a real scholarly dataset from Microsoft Academic Graph [1], which provides more than 12000 topics in the field of Computer Science (CS), including 1200 venues, 14.4 million authors, 30 million papers and their citation relations over the period of 1950 till now. Aiming to find the topics that will trend in CS area, we innovatively formalize a hot topic prediction problem where, with joint consideration of both inter-and intra-topical influence, 17 different scientific features are extracted for comprehensive description of topic status.By leveraging all those 17 features, we observe good accuracy of topic scale forecasting after 5 and 10 years with R 2 values of 0.9893 and 0.9646, respectively. Interestingly, our prediction suggests that the maximum value matters in finding hot topics in scholarly fields, primarily from three aspects: (1) the maximum value of each factor, such as authors' maximum h-index and largest citation number, provides three times the amount of information than the average value in prediction; (2) the mutual influence between the most correlated topics serve as the most telling factor in long-term topic trend prediction, interpreting that those currently exhibiting the maximum growth rates will drive the correlated topics to be hot in the future; (3) we predict in the next 5 years the top 100 fastest growing (maximum growth rate) topics that will potentially get the major attention in CS area. All our findings are further demonstrated through an online visualization system.