Modeling study on the reponse of lower trophic level production to climate change

funded by North Pacific Research Board (NPRB), June 1, 2006-May 30, 2008

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Last updated in July 2007

by Meibing Jin

 

 



















































































PI: Meibing Jin

Co-PI: Clara Deal and Jia Wang

Research Goal:

The most prominent climate trends resulting from global climate warming in the southeastern Bering Sea: reduced sea ice cover and rising seawater temperature, have profound impacts on lower trophic level production and fishery production. These impacts have aroused concerns in recent years and some explanatory hypotheses relating sea ice variability to marine ecosystems were proposed, such as the Oscillating Control Hypothesis (OCH, Hunt et al. 2002). Hypothesis testing has been hindered, however, because observational data describing productivity within sea ice are rare and coupled ice-ocean ecosystem models in the southeastern Bering Sea are lacking. In the past few years, we established a complete set of coupled ice-ocean ecosystem models including both pelagic and sea ice habitats. The models will be based on the existing pelagic ecosystem model (Jin et al. 2006b) for the southeastern Bering Sea and the ice-ocean ecosystem model (Jin et al. 2006a) for offshore Barrow. We will conduct sensitivity studies of the impact of physical and biological process variations on primary production, nutrient cycling, phytoplankton species composition, and carbon export to benthos. We will provide recommendations on how, when and which observations should be made to ensure effective improvement in understanding of the Bering Sea ecosystem. Using historical observations from National Oceanic and Atmospheric Administration (NOAA) biophysical mooring site 2, a multi-year model run is conducted to produce a long time series of biogeochemical model results. Seasonal variations and interannual changes in the results will be used to elucidate the lower trophic level productivity response to climate changes.

 

High lights from previous studies:

 

Figure 13a from Jin et al. (2006) showed that mixed-layer depth (MLD) against primary production during April to September 2000. Dominant species change from flagellates when MLD<15m to diatom when MLD>15m for both gross primary production (GPP) and net primary production (NPP).

 

High lights on ice associated blooms

We established the coupled ice-ocean ecosystem model for the Bering Sea. The model includes both pelagic and sea ice habitats, based on the existing pelagic ecosystem model (Jin et al. 2006a) for the Bering Sea and the ice-ocean ecosystem model (Jin et al. 2006b) for offshore Barrow. A multi-year (1995-2000) model run has been performed to test the Oscillating Control Hypothesis (OCH, Hunt et al., 2002). forced by SSMI sea ice concentration, NCEP meteorological data and sea surface temperature and salinity from NOAA/PMEL moor 2. Our model successfully reproduced the observed ice-associated blooms in 1997 and 1999 at the NOAA/PMEL mooring M2. The model results suggest that the ice-associated blooms were seeded by sea ice algae released from melting sea ice. For an ice-associated bloom to grow and reach the typical magnitude of phytoplankton bloom in the region, ice melting-resulted low-salinity stratification must not be followed by strong wind that could breakup the stratification. The ice-associated blooms had little impacts on the annual primary production, but had significant impacts in terms of shifting phytoplankton species, and the timing and magnitude of the bloom. These changes, superimposed on a gradual ecosystem shift attributed by global warming, can dramatically alter the Bering Sea ecosystem.

 

Ongoing progrss:

Figure by Meibing Jin, in June 2006. Preliminary results in multi-year run at M2 site of Southeastern Bering Sea. Modeled surface phytoplankton is compared with daily SeaWiFS Chl a data and imposed with daily SSMI sea ice concentration. Note that there appears to be discrepancies at the peak of bloom in certain year (e.g. 1998 and 1999), however that could be due to gaps of missing SeaWiFS Chl a data in cloudy days which are common in the Bering Sea.

 

Outreach and education:

  • Student intern in summer 2006.
  • A graduate student is working on statistics of the model variables, climate index and fishery catch data in summer 2007.
  • Jin, Deal and Lee (in Korea) will chair a session in the 2008 Ocean Science Meeting in Orlando on March 2-7. Session title is "Ecosystem in sea ice influenced areas: observations and modeling studies".
 

Manuscripts written during the project

References