Thursday, 10 November 2005 - 9:30 AM
311-6

Canopy Processes Impacting Temporal and Seasonal Net Ecosystem Co2 Flux in Grassland Ecosystems.

Tagir G. Gilmanov, Department of Biology and Microbiology, South Dakota State University, Ag Hall 304, Box 2207B, Brookings, SD 57007

Data sets of long-term tower measurements of net CO2 exchange (FNEE) in 26 grassland ecosystems in North America, Europe, and Asia were partitioned into gross primary productivity (Pg) and ecosystem respiration (Re) components according the equation Pg = Re + FNEE – dSCO2/dt, where SCO2 describes storage of carbon dioxide in the layer between the soil surface the CO2 flux sensor. Partitioning FNEE into assimilation and respiration components representing major biogeochemical fluxes of carbon was carried out using analysis of light-response functions relating daytime fluxes to radiation and soil temperature, when appropriate, supplemented by modeling of the relation between night-time fluxes and soil temperature and moisture for the relevant (ca. 7 days) time window. Basic ecosystem-scale characteristics of apparent quantum yield, maximum photosynthesis, and daytime respiration are obtained from this analysis. Using mostly daytime fluxes to estimate daytime respiration (and eventually, daily Pg) allows incorporation of light-dependent metabolic processes that remain unaccounted for when daytime respiration is estimated using night-time measurements only. Datasets of diurnal and seasonal dynamics, Pg(t), Re(t), and FNEE(t), resulting from light-response functions analysis reveal important patterns of interaction of assimilation and respiration in ecosystems which are shaping carbon balance at the daily, seasonal, and annual scale. Calculation of the gross ecosystem-scale light use efficiency (LUE) as the ratio of daily assimilation, Pg, and daily total of photosynthetically active radiation, Q, leads to a measurement-based estimates of the seasonal dynamics curves, LUE(t). These serve are an effective compliment to the light-use efficiency estimates provided by remote sensing methods. Stratifying obtained eco-physiological, biogeochemical, and energetic characteristics of grasslands with respect to climatic conditions and utilization regimes reveals essential patterns that may be used to predict the effect of global change and management and to quantitatively estimate the role of grasslands in the global carbon budget

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