The Study On Characters And Numerical Simulation Of Phytoplankton Dynamics In Chesapeake Bay

Phytoplankton, the producer in the food-chain, is one of the important parts inmarine eco-system, which maintains the energy import of the system. Phytoplanktonbloom is a specific character of phytoplankton dynamics in estuaries. The variation ofphytoplankton bloom has significant effect on the species composition, nutrients cyclingand transfer in estuary ecosystem. In recent years, the change of environmental factors,such as temperature, salinity, wind and nutrients, resulted from the climate change hasaffected on the phytoplankton dynamics, which attracted more and more attention.Climatic perturbations by drought-flood cycles, tropical storms, and hurricanes areincreasingly important in Mid-Atlantic estuaries, leading to ecosystem-scale response ofthe phytoplankton system with significant tropic implications. This study chooses thelargest estuary in the east coast of the United States to evaluate the key factor thatregulate the spring phytoplankton dynamics through the physical-biogeochemical model.The research is to quantify the effects of key factor on planktonic processes forChesapeake Bay eco-system and the eco-response to the changes. We also resolved long-term simulation for the biological elements in Chesapeake Bay in order to support thelong-term modeling research on phytoplankton dynamics. With this study, it is also agood example and reference to the ecological dynamics in China area.Through the simulation of phytoplankton dynamics for Chesapeake Bay in1996.The model results mainly match the observeation, which are the spring phytoplanktonbiomass maximum and summer primary production maximum. Based on the resultsfromt the analysis, we can figure out the the nutrients from Susquehanna River supportthe spring bloom and the regenerated nutrients from bottom layer fueled the high summerprimary production. We present results from two realistic cases for1998and1999, with different riverflow. The model qualitatively reproduced the horizontal and vertical distribution ofphytoplankton biomass during spring and showed a reasonable match compared with thehorizontal remote sensing observation. Nutrients and salinity results helped to understandthe mechanistic links between phytoplankton biomass and river discharge of freshwaterand nutrients. In order to study the response of phytoplankton to the inter annual variationof river flow, we used resource limitation to figure out the main factor affecting thegrowth of phytoplankton. Sensitive cases were set up to provide further analysis tosustain the hypothesis. Model results showed that the spring bloom in1998had highphytoplankton biomass and large area with high river flow. The simulation of1999withlow river flow showed low phytoplankton biomass during spring and the size of springbloom is smaller than1998.Based on the short-term simulation cases, we chose a long-term period (1995-2004)to resolve long-term trends of plankton biomass/production from high variability drivenby climatic forcing. Under the comparison with remote sensing observation, the long-term results showed reasonable simulation. The model captured the seasonal variation ofdissolved inorganic nutrients well and the skill values were all above0.8except summer.The simulation of surface phytoplankton biomass in2004was higher than theobservation, but in other years, the model did a good job to reproduce the results, whichalso supported the hypothesis that the river inflow is the dominate factor that regulate thephytoplankton dynamics in Chesapeake Bay.