RESULTS Frontier Newsletter No.13 Jan.2001

A marine ecosystem model coupled with Nitrogen-Silicon-Carbon cycles

Dr. Yasuhiro Yamanaka (Global Warming Research Program)

In 1990 s,to estimate the oceanic uptake of anthropogenic carbon dioxide and predict future atmospheric carbon dioxide levels, biogeochemical general circulation models (BGCMs)with simplified biological processes have been used.In previous BGCMs,export production is a function of phosphate concentration in the surface water,and is not based on the dynamics of marine ecosystems.For their predictions of future atmospheric CO2 levels,those models usually assume that marine ecosys- tems do not change as a result of global warming.

But,changes in ocean tempera- ture and circulation may change the func- tioning of oceanic ecosystems,and such changes can effect the predicted uptake of anthropogenic CO 2 .We therefore need to develop BGCMs which represent explicitly the dynamics of oceanic ecosystems and settling particles.With such models we may have a chance of predicting the effects of global warming on ecosystems dynamics and the effects of those changes in ecosys- tem dynamics on biogeochemical cycles and oceanic CO 2 uptake.

Most traditional ecosystem models deal only with the nitro- gen cycle,because nitrate and ammonium concentrations in the euphotic layer need to control primary production as nutrient limi- tation.We have developed a one dimen- sional ecosystem model with Nitrogen- Silicon- Carbon cycles as a preliminary ver- sion of an ecosystem model to be coupled with a three dimensional BGCM.We apply this model to Station A- 7 off Hokkaido, Japan (41 .5 N,145 .5 E),which is one of the stations along the A- line where the Hokkaido National Fisheries Research Institute has been conducting various cruis- es five or six times each year from 1987 to 2000 .

Fig 1 : Schematic view of interactions among the fifteen model compartments

Figure 1 .illustrates the interactions among the fifteen compartments in out model of biological processes.We divide phyto- plankton and zooplankton into two and three categories,respectively.

Figure 2 shows primary production by diatomes and others,and the partial pressure of CO 2 . The green line,primary production by diatoms,has its highest peak in spring and its second highest peak in fall.Simulated primary production during the spring bloom ranges from 800 through 600 mgC/m 2 day, which compares well with observations.

The spring bloom of diatoms has large interannual variations.The spring bloom of diatoms ceases because of increasing grazing pressure by copepods,although both nitrate and silicate in the surface water still remain over 10 micro mol/l,(larger than the half- saturation constants for their uptake)at the end of the bloom.After the diatom bloom,primary productions by PS increas- es,in the often- observed transition from a diatom- dominated bloom to a flagellate- dominated bloom which exhausts the nitrate in the surface waters by late summer. Many frequent downward spikes appear in the line representing primary production in Figure 2 .

These represent decreases in pri- mary productions resulting from decreases in solar radiation during rainy or cloudy days.The partial pressure of carbon diox- ide has its maximum associated with winter convection,rapidly decreases during the spring bloom,and remains almost constant from summer through fall,during which time the effect of increasing temperature (depressing p CO2 )cancels the effect of the biological pump (increasing p CO2 ).

Fig 2 : Primary productions by diatoms (PL, green line) and other phytoplankton (PS, red line)and partial pressure of carbon dioxide (black line) from 1991 to 1996

High frequency changes in boundary con- ditions such as hourly wind stress and solar radiation result in realistic fluctuations of primary production,resulting from chang- ing weather conditions.Thus,to accurately simulate time series of nutrients,production and/or biomass measured at a specific sta- tion,the model should ideally be driven by a time series of solar radiation and wind data from that same location (e.g.,from a continuously- deployed buoy).

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