Photosynthetic Production Determines Bottom Water Oxygen Variations in the Upwelling Coastal South China Sea Over Recent Decades

Dissolved oxygen (DO) in seawater is fundamental to marine ecosystem health. How DO in coastal upwelling areas responds to upwelling intensity under climate change is of particular interest and vital importance, because these productive regions account for a large fraction of global fishery production and marine biodiversity. The Yuedong upwelling (YDU) in the coastal northern South China Sea can be served as a study case to explore long-term responses of DO to upwelling and climate due to minor influence of riverine input. Here, bottom water DO conditions were recovered by sedimentary C28Δ22/Δ5,22 ratios of steroids in three short cores, with lower ratio value indicating higher DO concentration. The ratio records showed oscillations in varying degrees and exhibited no clear trends before ∼1980s, after which, however, there occurred a persistent decreasing trend or basically remained at lower values. Thus, inferred DO variations by the C28Δ22/Δ5,22 ratio records are not compatible with regional YDU-involved physical processes under climate change, such as southwesterly wind-induced onshore advection of reduced-oxygenated source waters from outer shelf and oceanic warming that would rather lead to less oxygenation in bottom waters in recent decades. Intriguingly, the alcohol records of n-C20:1/C28Δ5,22 and br-C15/C28Δ5,22 ratios, indicative of the relative strengths between biogeochemical oxygen consumption (i.e., by zooplankton and microbes) and photosynthetic oxygen production (i.e., by phytoplankton), changed almost in parallel with the C28Δ22/Δ5,22 records in three cores. Accordingly, we propose that net photosynthetic oxygen production outweighs source water– and warming-induced increasing deoxygenation in the study area. This study may suggest an important biogeochemical mechanism in determining bottom water DO dynamics in shallow coastal upwelling regions with minor contribution of riverine input.

Characteristics of the Russian shelf seas in the Arctic Ocean regarding the content of heavy minerals in surface sediments: new data

<p>Such factors as climate, currents, morphology, riverine input, and the source rocks influence the composition of the sediments in the Arctic Ocean. Heavy minerals being quite inert in terms of transport can reflect the geology of the source rock clearly and indicate the riverine input. There is a long history of studying the heavy mineral composition of the sediments in the Arctic Ocean. The works by Vogt (1997), Kosheleva (1999), Stein (2008), and others study the distribution of the minerals both on a sea scale and oceanwide. The current study covers Russian shelf seas: Barents, Kara, Laptev, East Siberian, and Chukchi Seas. To collect the material several data sources were used: data collected by the institute VNIIOkeangeologia during numerous expeditions since 2000 for mapping the shelf, data from the old expedition reports (earlier than 2000) taken from the geological funds, and datasets from PANGAEA (www.pangaea.de). About 82 minerals and groups of minerals were included in the joint dataset. The density of the sample points varied significantly in all seas: 1394 data points in the Barents Sea, 713 in the Kara Sea, 487 in the Laptev Sea, 196 in the East Siberian Sea, and 245 in the Chukchi Sea. These data allowed comparing the areas in terms of major minerals and associations. Maps of prevailing and significant components were created in ODV (Schlitzer, 2020) to demonstrate the differences between the seas and indicate the sites of remarkable changes in the source rocks. Additionally, the standardized ratio was calculated to perform quantitative comparison: the sea average was divided by the weighted sea average and then the ratio of that number to the mineral average was found. Only the minerals present in at least four seas and amounting to at least 20 points per sea were considered. As a result, water areas with the highest content of particular minerals were detected. The ratio varied from 0 to 3,4. Combining the ratio data for various minerals allowed mapping specific groups or provinces for every sea and within the seas.</p><p> </p><p>Kosheleva, V.A., & Yashin, D.S. (1999). Bottom Sediments of the Arctic Seas. St. Petersburg: VNIIOkeangeologia, 286pp. (in Russian).</p><p>PANGAEA. Data Publisher for Earth & Environmental Science https://www.pangaea.de/</p><p>Schlitzer, R. (2020). Ocean Data View, Retrieved from https://odv.awi.de.</p><p>Stein, R. (2008). Arctic Ocean Sediments: Processes, Proxies, and Paleoenvironment. Oxford: Elsevier, 602pp.</p><p>Vogt, C. (1997). Regional and temporal variations of mineral assemblages in Arctic Ocean sediments as a climatic indicator during glacial/interglacial changes. Berichte Zur Polarforschung, 251, 309pp.</p>

Modelling the Influence of Riverine Inputs on the Circulation and Flushing Times of Small Shallow Estuaries

Simple flushing time calculations for estuarine systems can be used as proxies for eutrophication susceptibility. However, more complex methods are required to better understand entire systems. Understanding of the hydrodynamics driving circulation and flushing times in small, eutrophic, temperate estuaries is less advanced than larger counterparts due to lack of data and difficulties in accurately modelling small-scale systems. This paper uses the microtidal Christchurch Harbour estuary in Southern UK as a case study to elucidate the physical controls on eutrophication susceptibility in small shallow basins. A depth-averaged hydrodynamic model has been configured of the estuary to investigate the physical processes driving circulation with particular emphasis on understanding the impact of riverine inputs to this system. Results indicate circulation control changes from tidally to fluvially driven as riverine inputs increase. Flushing times, calculated using a particle tracking method, indicate that the system can take as long as 132 h to flush when river flow is low, or as short as 12 h when riverine input is exceptionally high. When total river flow into the estuary is less than 30 m3 s−1, tidal flux is the dominant hydrodynamic control, which results in high flushing times during neap tides. Conversely, when riverine input is greater than 30 m3 s−1, the dominant hydrodynamic control is fluvial flux, and flushing times during spring tides are longer than at neaps. The methodology presented here shows that modelling at small spatial scales is possible but highlights the importance of particle tracking methods to determine flushing time variability across a system.