As a critical index for monitoring the response of terrestrial ecosystems to climate change, net primary productivity (NPP) is widely used to reflect the vegetation productivity under natural conditions. However, little is known about vegetation NPP in Buryatiya Republic, Russia. To fully understand temporal and spatial variations in vegetation NPP and its response to climate change, satellite images of Moderate-resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) products in conjunction with ground-based observations of climatology were used to estimate vegetation NPP in Buryatiya Republic from 2000 to 2008. Observed values of vegetation NPP and MODIS NPP products were jointly utilized to verify simulations of vegetation NPP in this area. The Carnegie Ames Stanford Approach (CASA) model was improved by adjusting its parameters with bio-temperature instead of monthly average temperature in a sub-model of soil water content. Model reliability was tested with observed vegetation NPP. Variation in vegetation NPP, and its relationship with climatic factors, was analyzed in detail. Results showed that the modified CASA model can be used to estimate vegetation NPP in Buryatiya Republic, and that the accuracy of the model was generally high with a correlation coefficient of 0.91 (P<0.01). The vegetation average annual NPP was 542.45 g C m^-2 y^-1 and the total NPP was estimated as 1.91E 14 g C y^-1 from 2000 to 2008. Monthly vegetation NPP increased significantly from April to July, decreased rapidly from August to November, and remained steady from December to March of the next year. Vegetation NPP increased with increasing longitude and decreased with increasing latitude. Different vegetation types differ in total NPP, with the highest NPP in forests, followed by forest-steppe, high mountain vegetation, steppe and meadow-swamp. Temperature and precipitation were the primary factors limiting vegetation NPP in this area.