Coupled 3D SINMOD Models show that Primary Production, Secondary Production, and Sea-Ice Cover will be affected by Global Warming

The rise of temperatures in the Arctic is predicted to change ice cover, primary production, and secondary production.  Warmer air temperatures will melt existing ice.  Primary production depends upon ice cover and nutrient availability, which is influenced by climate-sensitive oceanographic processes.  Secondary production is correspondingly linked to the amount of primary production taking place.  Slagstad et al. used a physically-biologically coupled 3D SINMOD model to measure the extent and severity of these effects.  The SINMOD model was paired with atmospheric forcing data from the European Centre for Medium-Range Weather Forecasts (ECMWF) to produce five scenarios, or cases; an increase by 2, 4, 6, 8 C, and present day.  As temperature increased, the ice cover decreased.  Salinity and nutrient abundance differed by area.  Gross primary production increased in most areas of the Arctic, but to a lesser extent on the Canadian and Greenland shelves.  It remained constant in the Barents Sea, which may become the major source of gross primary production in the Arctic.  The model used two species of mesozooplankton to represent how secondary production might change.  Calanusfinmarchicus, a sub-Arctic species, will continue to flourish in the Barents Sea as well as spread eastward along the Eurasian shelf boundary.  C. glacialisand other Arctic species may move further north.  A species not factored into the model, C. hyperboreus, could possibly thrive in warmer Arctic waters. —Katherine Recinos  
Slagstad, D., Ellingsen, I.H., Wassmann, P., 2011.  Evaluating primary and secondary production in an Arctic Ocean void of summer sea ice: An experimental simulation approach. Progress in Oceanography 90, 117—131.
Climate change will cause a greater increase in temperature in the Arctic than for the rest of the world; 68 C as opposed to 13 C over the next 100 years.  This rise in temperature could, and will, have serious effects Arctic marine ecosystems.  The authors wanted to investigate how exactly the Arctic Ocean and surrounding sub-Arctic seas (Barents, Chukchi, shelf waters) might shift, both in terms of oceanographic-physiological process and biologic populations.  For this purpose they used the abovementioned coupled SINMOD model.  The SINMOD model is actually a system of models, including ones for hydrodynamics, ice, chemistry, and planktonic food web.  The hydrodynamic model incorporates an ice model that takes into account average ice thickness and ice compactness.  The planktonic food web, or ecological, sub model accounts for nitrate, ammonium, silicate, diatoms, autotrophic flagellates, bacteria, heterotrophic nanoflagellates, microzooplankton, fast sinking detritus, slow sinking detritus, dissolved organic carbon, bottom sediment, and two representative mesozooplankton: C. finmarchicus (sub-Arctic)and C. glacialis(Arctic).  The model used a horizontal grid with a 20 km grid point distance and 25 vertical levels starting 10 m below the water surface.  It also incorporated current velocities, four tidal variables, heat flux, dissolved organic material, freshwater flux, initial ice distribution, water temperature, and salinity.  The temperature of the air, often referenced as T NPair (from an ECMWF equation), is the variable which was increased in the experiment.
Slagstad et al. reaffirmed that as air temperature increases, sea ice cover decreases, especially in sub-Arctic seas.  At temperature increases of 6 C and 8 C (Case IV and Case V), there will be no ice during the summers and many sub-Arctic seas could begin to experience near ice free winters, such as the Barents Sea.  Water temperature and salinity were also looked at, but they are highly variable.  The most important results concerned primary and secondary production.  In the central Arctic Ocean and Eurasian shelf, gross primary production increased from 1030 gCm-2y-1 to 4060 gCm-2y-1.  It also increased in the Chukchi Sea, the East Siberian Sea, and Siberian shelf.  As stated in the introduction, gross primary production did not change much in the Barents Sea, because production increased in the northern part while decreasing in the southern part.  Areas of the Eurasian and Siberian shelves near rivers will experience less growth in primary production because river runoff reduces gross primary production.  There is a “band” near Canada and Greenland where gross primary production will decrease from 60 gCm-2y-1to 10 gCm-2y-1.  The net primary production, for all the models, is around 65% of the gross primary production.          
As temperature increases, the receding ice cover will trigger earlier plankton blooms, which play a role in increasing primary production.  This leads to a corresponding increase in secondary production at lower latitudes and the highest latitudes, and a reduction in secondary production in the mid-latitudes of the Arctic.  Higher temperatures will also stratify the waters and even reinforce the halocline in some areas.  The central Arctic Ocean will become much more saline at the surface due to freshwater.  Stratification reduces nutrient availability for primary production.  The two secondary producers factored into the model are affected in different ways.  C. finmarchicus will remain in the Barents Sea, suggesting that other sub-Arctic mesozooplankton could be unaffected or even benefit from a rise in temperature.  C. finmarchicus will also extend its range eastward along the Eurasian shelf following currents.  C. glacialiswill retreat northward, and may get pushed out of the Barents Sea.  As previously mentioned, a third mesozooplankton species, C. hyperboreus, could potentially survive in areas with no summer ice; moving in to replace more sensitive species. 
The authors discuss the flaws of the experiment.  Advanced models and more base data are needed.  New models could better incorporate physical forcing and mesozooplankton adaptation to new climates among others.  Sea ice algae was not factored into this model, yet plays a big part in primary production.  The grid size could be smaller to more accurately predict ice cover.  They note that the model seems to work very well for the Barents Sea, but it less accurate for other areas of the Arctic.  The results are too highly variable at times.  Further experiments need to be done to better understand the effects of climate change on Arctic marine ecosystems.                           

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