Department of Plant Science, South Dakota State University, Brookings, South Dakota 57007, USA.
Department of Plant Science, South Dakota State University, Brookings, South Dakota 57007, USA.
J Environ Sci (China). 2016 May;43:15-25. doi: 10.1016/j.jes.2015.08.019. Epub 2015 Dec 30.
Switchgrass (Panicum virgatum L.) is a perennial C4 grass native to North America and successfully adapted to diverse environmental conditions. It offers the potential to reduce soil surface carbon dioxide (CO2) fluxes and mitigate climate change. However, information on how these CO2 fluxes respond to changing climate is still lacking. In this study, CO2 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 CO2 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 CO2 emissions based on different climate change scenarios. This study showed that: (i) the measured soil CO2 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 CO2 fluxes provided different patterns with temperature and precipitation changes in a long-term, (iii) the future CO2 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 CO2 fluxes from soil as a result of temperature and precipitation changes to some extent.
柳枝稷(Panicum virgatum L.)是一种原产于北美的多年生 C4 草,成功适应了多种环境条件。它具有减少土壤表面二氧化碳(CO2)通量和缓解气候变化的潜力。然而,关于这些 CO2 通量如何响应气候变化的信息仍然缺乏。在这项研究中,从 2011 年到 2014 年,使用 2008 年在南达科他州大豆(Glycine max L.)实验田播种的柳枝稷土地的高频测量数据,连续监测 CO2 通量。基于过程的模型 DAYCENT 用于模拟 CO2 通量。一种改进的方法 CPTE(将参数估计(PEST)与“试错”方法相结合)用于校准 DAYCENT。校准后的 DAYCENT 模型用于模拟不同气候变化情景下的未来 CO2 排放。这项研究表明:(i)2012 年是干旱年,柳枝稷土地的实测土壤 CO2 通量较高,而 DAYCENT 长期(2015-2070 年)模拟的这些通量呈多项式曲线模式;(ii)长期内,模拟的 CO2 通量随温度和降水变化呈现不同模式;(iii)在不同气候变化情景下,柳枝稷土地的未来 CO2 通量没有显著差异,因此,可以得出结论,柳枝稷生长时间更长,可以在一定程度上减少由于温度和降水变化导致的土壤 CO2 通量变化。