The resulting posterior densities for the crop parameters optimized for simulations were similar to values reported from prior numerical optimization schemes in the literature (Basche, Archontoulis, et al., 2016; Dietzel et al., 2015; Marcillo et al., 2019). Although the parameter ‘tt_end_of_juvenile’, which characterizes the thermal time from the end of juvenile stage to terminal spikelet stage, explained significant variability in phenology during GSA, it exhibited substantial variation even after optimization. We speculate this was due to the difference in genotype (G) × environment (E) interaction, and/or the inability of APSIM-Wheat to capture certain underlying processes in cereal rye phenology. Further investigation into unpacking the G × E interactions would require a significantly larger dataset that includes explicit genetic information about different cultivars over diverse environments. In previously conducted studies using APSIM, Basche et al. (2016) reported a relative root mean square error (RRMSE) of around 56% after calibration when optimizing cereal rye biomass from 2002 to 2014 at a single site in Iowa, U.S. With increased available data, Marcillo et al., (2019) reported RRMSE of 23% for fall and 56% for spring biomass for the same site in Iowa. Chatterjee et al., (2020) in a similar attempt obtained a RRMSE of just 11% for spring biomass when simulating cereal rye biomass for different planting dates at single site in Nebraska, U.S. However, all the above-mentioned studies employed numerical optimization approaches and were limited in terms of number of sites, data types or uncertainty quantification, potentially increasing the risk of overfitting and biased estimation of WCC impacts. Since we applied Bayesian optimization for constraining our model parameters, we were able to generate posterior distributions for crop growth parameters allowing to quantify the uncertainty around model parameters originated from various cereal rye genotypes and G × E interactions.
Due to the large spatial extent of the simulations, we observed substantial variation, both spatial and temporal, in the cereal rye biomass. However, when cereal rye preceded soybean, significantly greater rye biomass was produced. The underlying process for such variation could potentially be management decisions with respect to cereal rye as discussed by Pantoja et al. (2015), who studied the integration of cereal rye into a corn-soybean rotation in Iowa, US and observed that low temperatures in the fall hindered cereal rye growth. Moreover, most of the biomass accumulation took place in the spring. For the above mentioned study, soybean was planted within 7 days of cereal rye termination, whereas corn was planted at least 7 days after cereal rye termination. Thus, cereal rye preceding corn on average had 2 fewer weeks to grow during spring compared to cereal rye preceding soybean.
Additionally, there are several factors that influence SOC when WCCs are integrated into crop rotations but increased SOC as a function of increased carbon input to the soil (above-ground biomass) is well-documented (Blanco-Canqui et al., 2015). Moore et al. (2014) demonstrated this effectively by growing cereal rye in different combinations for a 2-yr corn silage – soybean rotation in Iowa, US and observed 15% increase in SOM at 0–5 cm depth, when rye was grown after both corn and soybean in comparison to control with no rye treatment. In our study, the southern areas of the state produced greater WCC biomass as compared to the north regardless of crop rotation and intuitively those areas reported higher SOC earlier in the simulations than low C input areas. Although SOC enhancement due to WCCs was reported across the state, the time required for significant soil carbon buildup was major factor as well, as is reported by Acuña and Villamil (2014). Blanco-Canqui and Ruis (2020) noted that increased SOC due to WCCs is one of the mechanisms by which soil physical properties are improved. This point, however, highlights an important limitation in the APSIM model structure since all soil physical properties including bulk density, hydraulic conductivity, etc. are not dynamically updated as function of time and management but are kept constant during the simulation. Therefore, future model improvements are essential for better representation of change in soil physical properties due to WCC integration.
Cover crop adoption in Illinois remains low, with only ~ 286,000 ha adopted for cover crops as reported by the 2017 census (USDA-NASS, 2017). The major concern in WCC adoption, as suggested by Plastina et al. (2020), is that WCCs reduce farm profitability in the short term. These losses can be usually supplemented by various cost-share programs (CTIC, 2020) or the biomass can be used for alternative purposes like cattle grazing (Rai et al., 2021). We suggest a precision WCC adoption strategy where we can segregate and quantify the ecosystem services based on different agroclimatic districts of the region (Vose et al., 2014). Our research suggests that most of the cropping area in the state of Illinois is responsive to the benefits that come with WCC adoption with potentially negligible yield penalties. However, the southern counties in the state tended to show promising results and faster carbon buildup and may be given priority for cover crop adoption programs. However, results may vary since WCCs require a long-term commitment by producers, policymakers, and all other stakeholders. The United Nations Food and Agricultural Organization supported the Lima Paris Action Agenda which aims at increasing the SOC stocks over current stocks by 0.4% annually to achieve sustainable development goals (Chabbi et al., 2017). We did observe a 0.4% annual increase in SOC stocks for our entire study period and the estimated soil carbon sequestration rates (0.15–0.22 Mg C ha− 1 yr− 1) were higher than those reported by Chambers et al. (2016). This indicates that sole adoption of WCCs and no tillage management has the potential to achieve sustainable development goals. However, from a practicality perspective there may still exist constrains such as sink saturation, or non-permanence of the benefits once the practices is altered (Jordon et al., 2022).
The probability of observing corn yield differences varied significantly across region as discussed previously. However, we observed an overall positive effect of long-term WCC adoption on corn production across IL despite variability in results. When aggregated across years, around 95% of the study area showed positive change in corn yield, when CRCR was compared to CC. Similarly, when CRSR rotation was compared to the CS rotation, around 97% of the area reported positive effect of incorporating WCC. Our results differ from those obtained by Qin et al., (2021), as we did not observe yield penalties for corn by inclusion of non-legume cover crops into the rotation. However, we speculate that terminating cereal rye less 14 days prior to corn planting may have different effect. Basche et al. (2016b) found that long-term application of WCCs improved soil water retention at field capacity when sand content in the WCC treatment was higher than the control. However, the authors credited increased SOC and improved soil aggregation due to WCCs with the improvement in soil water retention. Our analysis suggests that sand content did have a positive relationship with crop performance. Further analysis would be required to distinguish between the effect of sand, soil water content and SOC on yield differences of corn, which is beyond the scope of this study, since we observed increased SOC due to integration of WCCs (cereal rye) as well. Unlike corn, our results are in agreement with those of Qin et al. (2021) for soybean, as we did not observe any yield penalty due to non-legume WCCs. Additionally, the current results suggest the need to explore management options further for cereal rye preceding soybean.
Lal et al. (2021) has emphasized the importance of adopting a wide array of management practices including no-tillage, cover crops, integrated nutrient management, and precision agriculture to prevent land degradation, while noting that agroforestry and biochar application can provide substantial soil carbon sequestration as alternatives to cover crops. To provide a perspective on such practices, Dokoohaki et al. (2019) simulated impact of biochar application in a corn-corn system in Iowa and reported a 4% increase in SOC after 30 years. Similarly, Mohanty et al. (2020) reported a sequestration rate of 0.3 Mg C ha− 1 yr− 1 with integrated nutrient management strategy where the recommended dose of nutrients applied through chemical fertilizers was supplemented with 10 Mg ha− 1 of farmyard manure, under a soybean-wheat rotation in central India. The integrated nutrient management demonstrated significantly higher carbon sequestration rate than relying exclusively on chemical fertilizers. Hence, depending solely on WCCs for ecological benefits may not be in best interest of farmers and stakeholders in short-term.
Considering some of the questions that were left unanswered during this study, the focus of future studies should assess the impact of different cereal rye termination dates on crop performance, explore different agroclimatic zones for WCC adoption, and WCC benefits as a function of adoption rate and economic analysis. Apart from the current WCC study, we plan to evaluate the impact of various other cover crops species, such as legumes, using a similar methodology and similar temporal and spatial scales.