Spatio-temporal variation in vegetation biomass and its relationships with climate factors in the Xilingol grasslands, Northern China.

Knowledge about grassland biomass and its dynamics is critical for studying regional carbon cycles and for the sustainable use of grassland resources. In this study, we investigated the spatio-temporal variation of biomass in the Xilingol grasslands of northern China. Field-based biomass samples and MODIS time series data sets were used to establish two empirical models based on the relationship of the normalized difference vegetation index (NDVI) with above-ground biomass (AGB) as well as that of AGB with below-ground biomass (BGB). We further explored the climatic controls of these variations. Our results showed that the biomass averaged 99.01 Tg (1 Tg=10(12) g) over a total area of 19.6 × 10(4) km(2) and fluctuated with no significant trend from 2001 to 2012. The mean biomass density was 505.4 g/m(2), with 62.6 g/m(2) in AGB and 442.8 g/m(2) in BGB, which generally decreased from northeast to southwest and exhibited a large spatial heterogeneity. The year-to-year AGB pattern was generally consistent with the inter-annual variation in the growing season precipitation (GSP), showing a robust positive correlation (R(2)=0.82, P<0.001), but an opposite coupled pattern was observed with the growing season temperature (GST) (R(2)=0.61, P=0.003). Climatic factors also affected the spatial distribution of AGB, which increased progressively with the GSP gradient (R(2)=0.76, P<0.0001) but decreased with an increasing GST (R(2)=0.70, P<0.0001). An improved moisture index that combined the effects of GST and GSP explained more variation in AGB than did precipitation alone (R(2)=0.81, P<0.0001). The relationship between AGB and GSP could be fit by a power function. This increasing slope of the GSP-AGB relationships along the GSP gradient may be partly explained by the GST-GSP spatial pattern in Xilingol. Our findings suggest that the relationships between climatic factors and AGB may be scale-dependent and that multi-scale studies and sufficient long-term field data are needed to examine the relationships between AGB and climatic factors.