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Grazing activity is a fundamental behavior in pasture ecosystems and, globally, is a major disturbance that leads to destruction of terrestrial biomass. However, its impact on ecosystem C sequestration at large scales is not well understood due to its obvious anthropogenic property. In this study, we proposed a Data-Process combined Grazing Scheme (DPGS) to quantify the regional grazing impact on ecosystem C sequestration in the typical pasture ecosystem, Temperate Eurasian Steppe. First, a pixel-based livestock distribution map was generated based on fine-scale (province/prefecture) inventory data using a resource-oriented livestock distribution approach. Then the C consumption due to grazing (C-loss,C-graze) was simulated by combining a late version of a remote-sensing-based terrestrial model, the Boreal Ecosystem Productivity Simulator and the Shiyomi grazing model. The modeled regional livestock density was evaluated against the Gridded Livestock of the World data set. The DPGS was able to reproduce the spatial distribution of livestock. Because extralarge herbivores (camel and horse) were involved in the calculation, the DPGS predicts higher livestock density than the Gridded Livestock of the World data set over 70% of the region. The modeled C-loss,C-graze and its seasonal variability were validated against multiple site-based data sets. The results showed good agreements with the field observations of C-loss,C-graze. With further tests and data incorporations, this scheme has the potential to produce high-resolution data sets of livestock distribution and C-loss,C-graze and become a useful diagnostic instrument for model evaluation, parameterization, and intercomparison.