Modeling the impacts of temperature and precipitation changes on soil CO_2 fluxes from a Switchgrass stand recently converted from cropland

Switchgrass（Panicum virgatum L.） is a perennial C_4 grass native to North America and successfully adapted to diverse environmental conditions. It offers the potential to reduce soil surface carbon dioxide（CO_2） fluxes and mitigate climate change. However, information on how these CO_2 fluxes respond to changing climate is still lacking. In this study, CO_2 fluxes were monitored continuously from 2011 through 2014 using high frequency measurements from Switchgrass land seeded in 2008 on an experimental site that has been previously used for soybean（Glycine max L.） in South Dakota, USA. DAYCENT, a process-based model, was used to simulate CO_2 fluxes. An improved methodology CPTE[Combining Parameter estimation（PEST） with ＂Trial and Error＂ method] was used to calibrate DAYCENT. The calibrated DAYCENT model was used for simulating future CO_2 emissions based on different climate change scenarios. This study showed that：（i） the measured soil CO_2 fluxes from Switchgrass land were higher for 2012 which was a drought year, and these fluxes when simulated using DAYCENT for long-term（2015–2070） provided a pattern of polynomial curve;（ii） the simulated CO_2 fluxes provided different patterns with temperature and precipitation changes in a long-term,（iii） the future CO_2 fluxes from Switchgrass land under different changing climate scenarios were not significantly different, therefore, it can be concluded that Switchgrass grown for longer durations could reduce changes in CO_2 fluxes from soil as a result of temperature and precipitation changes to some extent.