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Response of gross ecosystem productivity, light use efficiency, and water use efficiency of Mongolian steppe to seasonal variations in soil moisture

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AMER GEOPHYSICAL UNION
DOI: 10.1029/2006JG000349

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The examination of vegetation productivity and use of light and water resources is important for understanding the carbon and water cycles in semiarid and arid environments. We made continuous measurements of carbon dioxide and water vapor fluxes over an arid steppe ecosystem in Mongolia by using the eddy covariance (EC) technique. These measurements allow an examination of EC-estimated gross ecosystem productivity (GEP), light use efficiency (LUE), and water use efficiency (WUE) of the steppe. Daily variations of GEP, LUE, and WUE were associated with daily variations of incident photosynthetically active radiation ( PAR), ambient temperature ( T-a), and vapor pressure deficit ( VPD). The magnitudes of these variations were also dependent on canopy development. On the daily basis, GEP linearly correlated with evapotranspiration rate and PAR. LUE correlated positively with leaf area index, Ta, and soil moisture availability but negatively with the surface reflectivity for short-wave solar radiation. Throughout the growing season, both GEP and LUE responded strongly to precipitation-fed soil moisture in the top 20 cm of the soil. An examination of the responses of LUE and WUE to PAR under different soil moisture conditions shows that when soil water availability exceeded VPD, the steppe was most efficient in light use, whereas it was less efficient in water use. The multivariate analysis of variance also suggests that soil moisture availability, especially water status in the upper 20-cm soil layer with dense distribution of grass roots, is the most significant factor that governs GEP, WUE, and LUE. This study provides a preliminary assessment of the use of available water and light by the Mongolian arid steppe ecosystems under seasonally varying soil moisture conditions. A better understanding of these functional responses is required to predict how climate change may affect arid steppe ecosystems.

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