Indexed on: 01 May '18Published on: 01 Jan '18Published in: Chinese Journal of Oceanology and Limnology
Using a three-dimensional coupled biophysical model, we simulated the responses of a lowtrophic ecosystem in the East China Sea (ECS) to long-term changes in nutrient load from the Changjiang (Yangtze) River over the period of 1960–2005. Two major factors affected changes in nutrient load: changes in river discharge and the concentration of nutrients in the river water. Increasing or decreasing Changjiang discharge induced different responses in the concentrations of nutrients, phytoplankton, and detritus in the ECS. Changes in dissolved inorganic nitrogen (DIN), silicate (SIL), phytoplankton, and detritus could be identified over a large area of the ECS shelf, but changes in dissolved inorganic phosphate (DIP) were limited to a small area close to the river mouth. The high DIN:DIP and SIL:DIP ratios in the river water were likely associated with the different responses in DIN, DIP, and SIL. As DIP is a candidate limiting nutrient, perturbations in DIP resulting from changes in the Changjiang discharge are quickly consumed through primary production. It is interesting that an increase in the Changjiang discharge did not always lead to an increase in phytoplankton levels in the ECS. Phytoplankton decreases could be found in some areas close to the river mouth. A likely cause of the reduction in phytoplankton was a change in the hydrodynamic field associated with the river plume, although the present model is not suitable for examining the possibility in detail. Increases in DIN and DIP concentrations in the river water primarily led to increases in DIN, DIP, phytoplankton, and detritus levels in the ECS, whereas decreases in the SIL concentration in river water led to lower SIL concentrations in the ECS, indicating that SIL is not a limiting nutrient for photosynthesis, based on our model results from 1960 to 2005. In both of the above-mentioned cases, the sediment accumulation rate of detritus exhibited a large spatial variation near the river mouth, suggesting that core sample data should be carefully interpreted.