91 research outputs found

    Linear relation between daily gross primary production (GPP) and canopy surface conductance (<i>g<sub>c</sub></i>).

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    <p>Data were obtained from May to September of each of the three study years. Rainy days were excluded from the analysis.</p

    Comparison of carbon fluxes in temperate desert steppe, Inner Mongolia, during 2008 to 2010.

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    <p>GPP, the gross primary production (g C m<sup>βˆ’2</sup>); R<sub>eco</sub>, the ecosystem respiration (g C m<sup>βˆ’2</sup>); NEE, the net ecosystem carbon exchange (g C m<sup>βˆ’2</sup>); R<sub>eco</sub>/GPP, the ratio of R<sub>eco</sub> to GPP.</p

    Regression coefficients as described in Eqs. 8–9, lower than 25Β°C.

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    <p>SWC, soil water content (%); Q<sub>10</sub>, the temperature sensitivity coefficient of ecosystem respiration.</p

    Relationships between light use efficiency (LUE) and EF and AET/PET at the two sites.

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    <p>EF (evaporative fraction) is ratio of latent heat flux to available energy (LE+H); AET/PET is ratio of actual evapotranspiration to potential evapotranspiration, calculated using the Penman-Monteith equation.</p

    Sensitivity of Temperate Desert Steppe Carbon Exchange to Seasonal Droughts and Precipitation Variations in Inner Mongolia, China

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    <div><p>Arid grassland ecosystems have significant interannual variation in carbon exchange; however, it is unclear how environmental factors influence carbon exchange in different hydrological years. In this study, the eddy covariance technique was used to investigate the seasonal and interannual variability of CO<sub>2</sub> flux over a temperate desert steppe in Inner Mongolia, China from 2008 to 2010. The amounts and times of precipitation varied significantly throughout the study period. The precipitation in 2009 (186.4 mm) was close to the long-term average (183.9Β±47.6 mm), while the precipitation in 2008 (136.3 mm) and 2010 (141.3 mm) was approximately a quarter below the long-term average. The temperate desert steppe showed carbon neutrality for atmospheric CO<sub>2</sub> throughout the study period, with a net ecosystem carbon dioxide exchange (NEE) of βˆ’7.2, βˆ’22.9, and 26.0 g C m<sup>βˆ’2</sup> yr<sup>βˆ’1</sup> in 2008, 2009, and 2010, not significantly different from zero. The ecosystem gained more carbon in 2009 compared to other two relatively dry years, while there was significant difference in carbon uptake between 2008 and 2010, although both years recorded similar annual precipitation. The results suggest that summer precipitation is a key factor determining annual NEE. The apparent quantum yield and saturation value of NEE (NEE<sub>sat</sub>) and the temperature sensitivity coefficient of ecosystem respiration (R<sub>eco</sub>) exhibited significant variations. The values of NEE<sub>sat</sub> were βˆ’2.6, βˆ’2.9, and βˆ’1.4 Β΅mol CO<sub>2</sub> m<sup>βˆ’2</sup> s<sup>βˆ’1</sup> in 2008, 2009, and 2010, respectively. Drought suppressed both the gross primary production (GPP) and R<sub>eco</sub>, and the drought sensitivity of GPP was greater than that of R<sub>eco</sub>. The soil water content sensitivity of GPP was high during the dry year of 2008 with limited soil moisture availability. Our results suggest the carbon balance of this temperate desert steppe was not only sensitive to total annual precipitation, but also to its seasonal distribution.</p> </div

    Seasonal dynamics of leaf area index (LAI) in 2008 and 2009.

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    <p>Seasonal dynamics of leaf area index (LAI) in 2008 and 2009.</p

    Responses of gross primary productivity (GPP) and ecosystem respiration (R<sub>eco</sub>) to soil water content (SWC).

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    <p>GPP and R<sub>eco</sub> data from May to September were averaged with a bin width of 1% for SWC. Error bars represent one standard error. Rainy days were excluded from the analysis.</p

    Exponential relation between canopy surface conductance (<i>g<sub>c</sub></i> and soil water content (SWC).

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    <p>Data were obtained from May to September of each of the three study years. Rainy days were excluded from the analysis.</p

    Seasonal variations of light use efficiency (LUE) at the two sites.

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    <p>LUE was calculated by dividing GPP by PAR<sub>a</sub> (FPAR*PAR).</p
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