Torrens, Christa L.听1听;听Lyons, W. Berry听2听;听Welch, Kathleen A.听3听;听Gooseff, Michael N.听4
1听Institute of Arctic and Alpine Research, University of Colorado - 麻豆影院
2听Byrd Polar Research Center, Ohio State University
3听Institute of Arctic and Alpine Research, University of Colorado - 麻豆影院
4听Institute of Arctic and Alpine Research, University of Colorado - 麻豆影院
In the McMurdo Dry Valleys [MDV], Antarctica, glacial meltwater streams are the primary biogeochemical connectors linking glaciers, soils and lakes. These streams control the supply of nutrients and carbon to their terminal lakes, yet little is known about the magnitude, timing or distribution of these fluxes. The McMurdo Long Term Ecological Research project [MCM LTER] has collected over 20 years of sample data on dissolved organic and inorganic carbon in Taylor Valley streamwater; this is the first spatial and temporal analysis of this data.
MDV streams are characterized by strong diel pulses in streamflow, specific electrical conductance [EC], and temperature. Unlike temperate stream systems, there is no terrestrial vegetation, lateral overland flow or deep groundwater connection in MDV streams. As a result, the organic carbon is autochthonous, originating from stream microbial mats. Inorganic carbon is primarily bicarbonate; its source is hyporheic zone weathering. The carbonate system is in atmospheric equilibrium, reflecting the wide and shallow stream channels. Preliminary data show that DIC has a positive relationship with EC and increases with stream length, consistent with increased hyporheic weathering. MDV streams have high DIC and low DOC compared to world rivers. Preliminary DOC analysis shows no clear temporal or spatial patterns, and even appears chemostatic in one short stream.
Stream flood pulse dynamics control carbon loading to MDV lakes. As the climate changes, so will the timing and magnitude of diel flood pulses. This is likely to increase carbon loading to the Dry Valley lakes, altering the ecosystem carbon balance. This study increases our understanding of past and current patterns of carbon fluxes from streams to lakes; understanding past patterns will improve predictions of future changes.