Denitrification and the challenge of scaling microsite knowledge to the globe

Our knowledge of microbial processes-who is responsible for what, the rates at which they occur, and the substrates consumed and products produced-is imperfect for many if not most taxa, but even less is known about how microsite processes scale to the ecosystem and thence the globe. In both natural and managed environments, scaling links fundamental knowledge to application and also allows for global assessments of the importance of microbial processes. But rarely is scaling straightforward: More often than not, process rates in situ are distributed in a highly skewed fashion, under the influence of multiple interacting controls, and thus often difficult to sample, quantify, and predict. To date, quantitative models of many important processes fail to capture daily, seasonal, and annual fluxes with the precision needed to effect meaningful management outcomes. Nitrogen cycle processes are a case in point, and denitrification is a prime example. Statistical models based on machine learning can improve predictability and identify the best environmental predictors but are-by themselves-insufficient for revealing process-level knowledge gaps or predicting outcomes under novel environmental conditions. Hybrid models that incorporate well-calibrated process models as predictors for machine learning algorithms can provide both improved understanding and more reliable forecasts under environmental conditions not yet experienced. Incorporating trait-based models into such efforts promises to improve predictions and understanding still further, but much more development is needed.

Greenhouse gas flux and crop productivity after 10 years of reduced and no tillage in a wheat-maize cropping system

Appropriate tillage plays an important role in mitigating the emissions of greenhouse gases (GHG) in regions with higher crop yields, but the emission situations of some reduced tillage systems such as subsoiling, harrow tillage and rotary tillage are not comprehensively studied. The objective of this study was to evaluate the emission characteristics of GHG (CH₄ and N₂O) under four reduced tillage systems from October 2007 to August 2009 based on a 10-yr tillage experiment in the North China Plain, which included no-tillage (NT) and three reduced tillage systems of subsoil tillage (ST), harrow tillage (HT) and rotary tillage (RT), with the conventional tillage (CT) as the control. The soil under the five tillage systems was an absorption sink for CH₄ and an emission source for N₂O. The soil temperature positive impacted on the CH₄ absorption by the soils of different tillage systems, while a significant negative correlation was observed between the absorption and soil moisture. The main driving factor for increased N₂O emission was not the soil temperature but the soil moisture and the content of nitrate. In the two rotation cycle of wheat-maize system (10/2007–10/2008 and 10/2008–10/2009), averaged cumulative uptake fluxes of CH₄ under CT, ST, HT, RT and NT systems were approximately 1.67, 1.72, 1.63, 1.77 and 1.17 t ha⁻¹ year⁻¹, respectively, and meanwhile, approximately 4.43, 4.38, 4.47, 4.30 and 4.61 t ha⁻¹ year⁻¹ of N₂O were emitted from soil of these systems, respectively. Moreover, they also gained 33.73, 34.63, 32.62, 34.56 and 27.54 t ha⁻¹ yields during two crop-rotation periods, respectively. Based on these comparisons, the rotary tillage and subsoiling mitigated the emissions of CH₄ and N₂O as well as improving crop productivity of a wheat-maize cropping system.

Response of CH4 and N2O emissions and wheat yields to tillage method changes in the North China plain

The objective of this study was to quantify soil methane (CH₄) and nitrous oxide (N₂O) emissions when converting from minimum and no-tillage systems to subsoiling (tilled soil to a depth of 40 cm to 45 cm) in the North China Plain. The relationships between CH₄ and N₂O flux and soil temperature, moisture, NH₄⁺-N, organic carbon (SOC) and pH were investigated over 18 months using a split-plot design. The soil absorption of CH₄ appeared to increase after conversion from no-tillage (NT) to subsoiling (NTS), from harrow tillage (HT) to subsoiling (HTS) and from rotary tillage (RT) to subsoiling (RTS). N₂O emissions also increased after conversion. Furthermore, after conversion to subsoiling, the combined global warming potential (GWP) of CH₄ and N₂O increased by approximately 0.05 kg CO₂ ha⁻¹ for HTS, 0.02 kg CO₂ ha⁻¹ for RTS and 0.23 kg CO₂ ha⁻¹ for NTS. Soil temperature, moisture, SOC, NH₄⁺-N and pH also changed after conversion to subsoiling. These changes were correlated with CH₄ uptake and N₂O emissions. However, there was no significant correlation between N₂O emissions and soil temperature in this study. The grain yields of wheat improved after conversion to subsoiling. Under HTS, RTS and NTS, the average grain yield was elevated by approximately 42.5%, 27.8% and 60.3% respectively. Our findings indicate that RTS and HTS would be ideal rotation tillage systems to balance GWP decreases and grain yield improvements in the North China Plain region.