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Data from: Grazing effects on surface energy fluxes in a desert steppe on the Mongolian Plateau

Cite this dataset

Shao, Changliang et al. (2016). Data from: Grazing effects on surface energy fluxes in a desert steppe on the Mongolian Plateau [Dataset]. Dryad.


Quantifying the surface energy fluxes of grazed and ungrazed steppes is essential to understand the roles of grasslands in local and global climate and in land use change. We used paired eddy-covariance towers to investigate the effects of grazing on energy balance (EB) components: net radiation (Rn), latent heat (LE), sensible heat (H), and soil heat (G) fluxes on adjacent grazed and ungrazed areas in a desert steppe of the Mongolian Plateau for a two-year period (2010-2012). Near 95% of Rn was partitioned as LE and H, whereas the contributions of G and other components of the EB were 5% at an annual scale. H dominated the energy partitioning and shared ~50% of Rn. When comparing the grazed and the ungrazed desert steppe, there was remarkably lower Rn and a lower H, but higher G at the grazed site than at the ungrazed site. Both reduced available energy (Rn˗G) and H through grazing indicated a “cooling effect” feedback onto the local climate. Grazing reduced the dry year LE but enhanced the wet year LE. Energy partitioning of LE/Rn was positively correlated with the canopy conductivity, leaf area index, and soil moisture. H/Rn was positively correlated with the vapor pressure deficit but negatively correlated with the soil moisture. Boosted regression tree results showed that LE/Rn was dominated by soil moisture in both years and at both sites, while grazing shifted the H/Rn domination from temperature to soil moisture in the wet year. Grazing not only caused a LE shift between the dry and the wet year, but also triggered a decrease in the H/Rn because of changes in vegetation and soil properties, indicating that the ungrazed area had a greater resistance while the grazed area had a greater sensitivity of EB components to the changing climate.

Usage notes


National Science Foundation, Award: 1313761