Abstract
ContextComprehending the intricacies of crop growth and its impact on greenhouse gas (GHG) emissions is crucial for food security and agricultural resilience to climate change. Research questionAgroecosystem models are instrumental in this endeavor, yet their regional applicability remains constrained. MethodsIn our study, we conducted a rigorous verification of the DNDC (DeNitrification-DeComposition) model across eight representative sites in the Bohai Rim region and determined its efficacy in accurately simulating crop yield, soil organic carbon (SOC), and nitrous oxide (N2O) emissions. We developed a coupled framework, DNDC-RF (DeNitrification-DeComposition-Random Forest), using the RF algorithm in conjunction with DNDC simulation results across fertilization and climate scenarios. Employing the DNDC-RF, we quantitatively evaluated the impact of diverse fertilization strategies on yield and net GHG (including SOC and N2O emissions) under future climate scenarios, spanning the period from 2008 to 2100. ResultsThe DNDC-RF framework accurately predicts SOC, yield, and N2O with high R2 and LCCC, lower RMSE and MAE. Under the RCP4.5 scenario, spring maize yields exhibited a reduction under conventional fertilization measures. However, with organic matters input could achieve the yield increase, particularly additional manure input (9.6 kg C ha−1 yr−1). Summer maize yields were projected to increase under future climate change, with the fastest increase occurring under the RCP8.5 scenario with additional manure input (26 kg C ha−1 yr−1). Wheat yields also increased under future climate change, with the highest growth rate observed with straw return under the RCP8.5 (17.1 kg C ha−1 yr−1). Under different fertilization practices, spring maize fields exhibited a net GHG sink. The best performance was observed with additional manure input and straw return under RCP4.5 and RCP8.5, respectively. In contrast, conventional fertilization in winter wheat-summer maize fields resulted in a net GHG source under both RCP4.5 and RCP8.5. However, the application of organic matter mitigated the net GHG emissions, with additional manure input resulting in the largest increase rate of the net GHG sink. ConclusionsDNDC-RF framework can quickly and effectively solve the difficulties of DNDC model in regional scale prediction (such as complex parameter setting, difficult to accurately and quickly simulate at regional scale and time series), and can accurately simulate regional crop yield, SOC change and N2O emission. With the input of organic matter, the projected yields of maize and wheat are expected to increase, and the field’s ability to act as a net GHG sink could be enhanced. SignificanceOur findings have important scientific significance and practical value for promoting the sustainable development of regional agriculture and formulating effective regional agricultural management measures.
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