HR: 0800h
AN: OS41D-0517    [Abstracts]
TI: A One-Dimensional Physical-Ecosystem Model Study of Plankton, Nutrient and Dimethylsulfide Dynamics in the Southeastern Bering Sea middle shelf domain
AU: * Deal, C
EM: deal@iarc.uaf.edu
AF: International Arctic Research Center, University of Alaska Fairbanks 930 Koyukuk Drive P.O. Box 757335, Fairbanks, AK 99775-7335 United States
AU: Jin, M
AF: International Arctic Research Center, University of Alaska Fairbanks 930 Koyukuk Drive P.O. Box 757335, Fairbanks, AK 99775-7335 United States
AU: Wang, J
EM: jwang@iarc.uaf.edu
AF: International Arctic Research Center, University of Alaska Fairbanks 930 Koyukuk Drive P.O. Box 757335, Fairbanks, AK 99775-7335 United States
AU: Takada, N
EM: norit@iarc.uaf.edu
AF: International Arctic Research Center, University of Alaska Fairbanks 930 Koyukuk Drive P.O. Box 757335, Fairbanks, AK 99775-7335 United States
AB: As a high-latitude sea exhibiting great variability in sea ice extent and high productivity, the Bering Sea is an opportune location for studies on how geophysical phenomena (such as climate variability) influence plankton dynamics and thus biogeochemical cycling in the Arctic. With this in mind, we have developed a one-dimensional physical model coupled to a one-dimensional ecosystem model and applied it to the time series data from the NOAA-PMEL biophysical mooring M2 in the middle shelf domain of the Southeastern Bering Sea (Hunt and Stabeno, 2002, Progress in Oceanography, 55, 5-22). The ecosystem submodel is a depth-resolved, N-based model of the lower trophic level ecosystem. Two types of phytoplankton (diatoms and flagellates), three nutrients (nitrate + nitrite, ammonium, and silicon), three size-classes of zooplankton, detritus and dimethylsulfide cycling are included in the model. The model is driven by meteorological data: wind velocity, air temperature, sea surface temperature, specific humidity, cloud cover and light. The model realistically simulates the spring bloom, seasonal cycles of temperature and chlorophyll, and large seasonal variations of nutrients. Simulations for the southeastern Bering Sea middle-shelf domain in relatively high and low sea surface temperature years, 2000 and 1999, respectively, suggest that increased water column mixing in spring delays phytoplankton bloom onset and that zooplankton grazing pressure is an important factor in the maintenance of the coccolithopore bloom in the Bering Shelf. Model sensitivity studies point out several important factors, such as, that the timing of the spring phytoplankton bloom is most sensitive to cloud cover (light) and phytoplankton growth rates, the latter also affecting bloom strength. Maximum rate of grazing on flagellates appears to control the timing of the end of the spring bloom and the strength of the autumn diatom bloom. Work in progress and recent model developments are described, moving towards a three-dimensional version of the model, including sea ice and having applications elsewhere in the Arctic.
DE: 4805 Biogeochemical cycles (1615)
DE: 4815 Ecosystems, structure and dynamics
DE: 4842 Modeling
DE: 4255 Numerical modeling
DE: 0400 Biogeosciences
SC: Ocean Sciences [OS]
MN: 2004 AGU Fall Meeting