Great uncertainties in modeling grazing impact on carbon sequestration: a multi-model inter-comparison in temperate Eurasian Steppe

The impact of grazing activity on terrestrial carbon (C) sequestration has been noticed and studied worldwide. Recent efforts have been made to incorporate the disturbance into process-based land models. However, the performance of grazing models has not been well investigated at large scales. In this study, we performed a spatially explicit model uncertainty assessment in the world's largest pasture ecosystem, the temperate Eurasian Steppe. Five grazing models were explicitly incorporated into a single terrestrial biogeochemical model to simulate regional C consumption from grazing activity (C-graze). First, we summarized the underlying mechanisms and explicitly compared the general functions used to describe the processes in different models. Then, the models (five models with 12 simulations) were run in parallel using the same forcing data and livestock distribution map in 2006. Results indicated that the modeled regional C-graze varied from 0.1-16.1 gCm(-2) for the year. The corresponding ratios of C(graz)e to aboveground net primary productivity ANPP and net primary productivity (NPP) ranged from 0.08%-24.6% and 0.028%-11.2%, respectively. Parameter sensitivity was further analyzed. Model outputs are highly sensitive to the intake rate (i.e. feeding rate of livestock per day), half maximum intake rate, and initial livestock weight. Our results indicate that great uncertainty exists in simulating C-graze. We ascribed the major uncertainty to the different process description and poor parameterization. This study calls for more efforts to the comprehensive synthesis of usable dataset, the foundation of a standard observation system and the observe-based inter-comparison to evaluate models, which would facilitate more accurate assessment of C sequestration by pasture ecosystems and lead to better representation in earth system models.