An important but rarely studied aspect of crop modeling is the uncertainty associated with model calibration and its effect on model prediction. Biomass and grain yield data from a four-year maize experiment (2008–2011) with six irrigation treatments were divided into subsets by either treatments (Calibration-by-Treatment) or years (Calibration-by-Year). These subsets were then used to calibrate crop cultivar parameters in CERES (Crop Environment Resource Synthesis)-Maize implemented within RZWQM2 (Root Zone Water Quality Model 2) using the automatic Parameter ESTimation (PEST) algorithm to explore model calibration uncertainties. After calibration for each subset, PEST also generated 300 cultivar parameter sets by assuming a normal distribution of each parameter within their reported values in the literature, using the Latin hypercube sampling (LHS) method. The parameter sets that produced similar goodness of fit (11–164 depending on subset used for calibration) were then used to predict all the treatments and years of the entire dataset. Our results showed that the selection of calibration datasets greatly affected the calibrated crop parameters and their uncertainty, as well as prediction uncertainty of grain yield and biomass. The high variability in model prediction of grain yield and biomass among the six (Calibration-by-Treatment) or the four (Calibration-by-Year) scenarios indicated that parameter uncertainty should be considered in calibrating CERES-Maize with grain yield and biomass data from different irrigation treatments, and model predictions should be provided with confidence intervals.
Abstract Categorization of soil organic carbon (SOC) into different functional subpools according to their recalcitrance and protective mechanisms helps better understand ecosystems organic carbon (OC) dynamics, and various attempts have been made to explore the suitable experimental fractionation method for such purpose. However, most previous studies neglected the influences of environmental factors on the effectiveness of varying fractionation methods. Density fractionation has shown great promise in elucidating SOC immobilization mechanisms. Here, we compared three varying types of density fractionation methods (density, density + dispersion, and density + other procedures) for categorizing the SOC into three functional pools, that is, active OC (OC active ), moderately stable OC (OC m‐stable ), and stable OC, (OC stable ) using global data compiled for 95 sites in 31 published studies, and examined the influences of climate (mean annual temperature [MAT] and annual precipitation), vegetation type, and soil properties (soil depth, clay content, and soil type) on SOC fractions determined by the three density fractionation methods. The percentage of OC m‐stable fraction was found to be highest using the density method and lowest using the density + dispersion method, due to differential density ranges between the two methods. At a global scale, the contents of total SOC and its OC fractions decreased with temperature. Precipitation had no apparent influences on the subdivided SOC fractions using either the density + dispersion method or the method of density + other procedures, whereas soil type constrained the effect of precipitation on SOC fractions using the density method. The percentage of OC m‐stable determined by the density + dispersion method was more responsive to MAT and vegetation type than that by the other two methods. The percentage of OC stable determined by the method of density + other procedures was significantly and positively related to the clay content as the OC stable based on this method included small particles. For all the three methods of fractionation, soil type had a greater influence than the clay content on the SOC fractions, especially the OC m‐stable and the OC stable . For soil type characterized by rich metal oxides, both the density method and the method of density + other procedures could be used for SOC fractionation. For soil type rich in nutrients, the density + dispersion method would have higher sensitivity for distinguishing the OC m‐stable .
Aims Our objective was to elucidate the response of crop photosynthesis, transpiration and water use efficiency to atmospheric CO2 concentration. This has great significance to predicting crop productivity and water-demand changes under increasing atmospheric CO2 concentration. Methods The photosynthesis rate, transpiration rate and water use efficiency of eight crops (soybean (Glycine max), sweet potato (Ipomoea batatas), peanut (Arachis hypogaea), rice (Oryza sativa), cotton (Gossypium hirsu- tum), corn (Zea mays), sorghum (Sorghum vulgare) and millet (Setaria italica)) were studied under natural CO2 concentration, doubled CO2 concentration and natural CO2 concentration after doubled CO2 conditions. Important findings Doubled CO2 concentration increased the photosynthesis rate and decreased the transpira- tion rate, and therefore water use efficiency was more significantly increased. The increase of water use efficiency showed greater dependence on the increase of photosynthesis rate than the decrease of transpiration rate. The variations of photosynthesis rate and water use efficiency of C3 crops were larger than those of C4 crops. The ef- fect of photosynthesis rate of C3 crops on the water use efficiency was larger than that of C4 crops. The photosyn- thesis rate under natural CO2 concentration after doubled CO2 concentration was lower than that under natural CO2 concentration, but no significant difference was found for the transpiration rate. The photosynthetic capacity under natural CO2 concentration after doubled CO2 concentration was decreased mainly by the decreasing of some non-stomatal factors, including the protein content, activation levels and specific activity of the enzyme Rubisco.
Potato is one of the staple food crops in North China. However, potato production in this region is threatened by the low amount and high spatial-temporal variation of precipitation. Increasing yield and water use efficiency (WUE) of potato by various water management practices under water resource limitation is of great importance for ensuring food security in China. However, the contributions of different water management practices to yield and WUE of potato have been rarely investigated across North China's potato planting region. Based on meta-analysis of field experiments from the literature and model simulation, this study quantified the potential yield of potatoes without water and fertilizer limitation, and yield under irrigated and rainfed conditions, and the corresponding WUE across four potato planting regions including the Da Hinggan Mountains (DH), the Foothills of Yanshan hilly (YH), the North foot of the Yinshan Mountains (YM), and the Loess Plateau (LP) in North China. Simulated potential potato tuber dry weight yield by the APSIM-Potato model was 12.4 t ha-1 for the YH region, 11.4 t ha-1 for the YM region, 11.2 t ha-1 for the DH region, and 10.7 t ha-1 for the LP region. Observed rainfed potato tuber dry weight yield accounted for 61, 30, 28 and 24% of the potential yield in the DH, YH, YM, and LP regions, respectively. Maximum WUE of 2.2 kg m-3 in the YH region, 2.1 kg m-3 in the DH region, 1.9 kg m-3 in the YM region and 1.9 kg m-3 in the LP region was achieved under the potential yield level. Ridge-furrow planting could boost yield by 8-49% and WUE by 2-36% while ridge-furrow planting with film mulching could boost yield by 35-89% and WUE by 7-57% across North China. Our study demonstrates that there is a large potential to increase yield and WUE simultaneously by combining ridge-furrow planting with film mulching and supplemental irrigation in different potato planting regions with limited water resources.
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