datasetposted on 02.01.2020 by Zhen Yu, Chaoqun lu, David Hennessy, Hongli Feng, Hanqin Tian
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
The simulation results for manuscript titled "Impacts of tillage practices on soil carbon stocks in the US corn-soybean cropping system during 1998 to 2016".
We set up simulation experiments (see manuscript) to distinguish and quantify the effects of tillage practices and tillage-intensity-change (TIC)on SOC changes. More specifically, the first simulation experiment (S1) was designed to produce our “best estimate” of C storage and change in the U.S., which was driven by historically varying tillage intensity and other drivers (e.g., climate, N deposition, atmospheric CO2, land conversion and crop rotation, crop technology improvement, and fertilizer use, manure application, irrigation, and tile drainage). The second simulation experiment (S2) was a “business as usual (BAU)-1998” reference case designed to keep intensity of conservation and conventional tillage “fixed” since 1998 (we keep areas under these two tillage types unchanged, assuming that new cropland adopted no-till practice). The impacts of TIC on C storage are distinguished by comparing S1 with S2 (see figure 2 in the manuscript). Similarly, the third simulation experiment (S3) was designed to hold the two tillage intensities “fixed” since 2008, which served as the “BAU-2008” reference. By comparing S1 and S3, we can identify the impact of TIC on C storage during the 2008-2016 period (see figure 2 in the manuscript). Based on the above experiments, we estimated how TIC has affected C storage in the US. Moreover, we set up a fourth simulation experiment (S4), which assumed that the no-till practice was adopted in all croplands since 1998, and the fifth simulation experiment (S5) assuming shifting all conventional tillage land to conservation tillage since 1998. Comparison of experiments S1 and S4 provides us with historical tillage impacts on cropland SOC (see figure 2 in the manuscript), while comparison of S1 and S5 implies potential SOC change of adopting conservation tillage in the U.S. corn-soybean cropping system.
Additional simulation experiments were designed to account for uncertainties of the TIC-induced C storage change. Three major uncertainty sources were quantified. The first uncertainty source is from the parameters used in LUCC-induced soil C and N loss in continuous cropland expansion area. Same as Yu et al. (2018, 2019), conversion-specific parameter values were adopted to describe instantaneous C loss during cropland expansion into different ecosystem types. Parameter-induced uncertainty from C storage change was derived from multiple simulation experiments using parameter values for average C/N loss percentage ± 1 standard deviation. The second uncertainty comes from the residual removal rate used in model simulations. The “best estimate” simulation we performed adopted a coefficient of 0.5 for residue removal assuming that 50% of the residue was removed from cropland. The residue removal rate determines C input amount after crop harvesting, which is directly related to soil C storage change. This roughly estimated coefficient may vary by location and crop type, and may affect soil C accumulation/loss. We then adopted 40% and 60% residue removal coefficients as alternatives to the 50% coefficient when implementing our uncertainty analysis. The third uncertainty is from the timing of tillage implementation. Generally, fall tillage may be adopted before spring tillage . Due to lack of timing information, we designed two types of experiments. One is with and one is without the fall tillage practice.