Partitioning evapotranspiration and carbon flux in ungrazed and grazed tallgrass prairie

The effect of cattle grazing on water and carbon cycling in grasslands is not fully understood. The goal of this study was to evaluate how grazing affects carbon and water cycles in a tallgrass prairie. Eddy covariance measurements were carried out from 2003 to 2005 growing seasons (from May to September) in Manhattan, Kansas, U.S., in grazed (GR) and ungrazed (UG) tallgrass prairie paddocks. Net ecosystem CO2 exchange (NEE) was partitioned into gross primary productivity (GPP) and ecosystem respiration (Reco) using the relationship between the air temperature and nighttime NEE data. Evapotranspiration (ET) was partitioned into transpiration (T) and evaporation (E) using an approach based on the concept of underlying water use efficiency. Our results revealed that grazing reduced maximum aboveground biomass (AGB) and green leaf area index (GLAI) by 22.5% and 24.3%, respectively. Grazing also reduced GPP, NEE and T in the middle of the growing seasons but enhanced these flux components at the end of the growing seasons compared to the UG paddock. Grazing reduced the growing season cumulative NEE by 11.9% and enhanced ET by 3.3% compared to the UG paddock. The reduction in NEE at UG was associated with an increase in Reco (9.4%). In turn, changes in ET in response to grazing were driven more by the increase in E (26.6%) than by the decrease in T (5.9%). Despite the reduction in AGB and GLAI caused by grazing, similar cumulative GPP values at the canopy scale at both paddocks suggest that there are compensatory mechanisms that maintain similar CO2 assimilation at UG and GR. Our findings suggest that the grazing regime adopted in this tallgrass prairie impacts the carbon cycle more strongly than the water cycle, given the higher reduction in NEE compared to the slight increase in ET on GR compared to UG. These results can be useful to outline strategies to improve management practices aimed at improving the efficiency of rangelands.