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Abstract: Assessing the driving forces of sandy desertification is fundamental and important for its control. It has been widely accepted that both climatic conditions and land use have great impact on sandy desertification in northern China. However, the relative role and synergistic effect of each driving force of sandy desertification are still not clear. In this paper, an indicator named as SI was defined to represent the integrated probability of sandy desertification caused by land use. A quantitative method was developed for characterizing the relative roles of annual precipitation and land use to sandy desertification in both spatial and temporal dimensions at county level. Results showed that, at county level, land use was the main cause of sandy desertification for Naiman Banner since 1987–2009. In the case of spatial dimension, the different combination of land use types decided the distribution of sandy desertification probability and finally decided the spatial pattern of bared sand land. In the case of temporal dimension, the synergistic effect of land use and precipitation highly influenced the spatial distribution of sandy desertification. [Copyright &y& Elsevier]

Frequency and severity of droughts were projected to increase in many regions. However, their effects of temporal dynamics on the terrestrial carbon cycle remain uncertain, and hence deserve further investigation. In this paper, the droughts that occurred in China during 2001–2010 were identified by using the standardized precipitation index (SPI). Standardized anomaly index (SAI), which has been widely employed in reflecting precipitation, was extended to evaluate the anomalies of net primary productivity (NPP). In addition, influences of the droughts on vegetation were explored by examining the temporal dynamics of SAI–NPP along with area-weighted drought intensity at different time scales (1, 3, 6, 9 and 12 months). Year-to-year variability of NPP with several factors, including droughts, NDVI, radiation and temperature, was analyzed as well. Consequently, the droughts in the years 2001, 2006 and 2009 were well reconstructed. This indicates that SPI could be applied to the monitoring of the droughts in China during the past decade (2001–2010) effectively. Moreover, strongest correlations between droughts and NPP anomalies were found during or after the drought intensities reached their peak values. In addition, some droughts substantially reduced the countrywide NPP, whereas the others did not. These phenomena can be explained by the regional diversities of drought intensity, drought duration, areal extents of the droughts, as well as the cumulative and lag responses of vegetation to the precipitation deficits. Besides the drought conditions, normalized difference vegetation index (NDVI), radiation and temperature also contribute to the interannual variability of NPP. [Copyright &y& Elsevier]