In most agroecosystems, nitrogen (N) is the most important nutrient limiting plant growth. One management strategy that affects N cycling and N use efficiency (NUE) is conservation agriculture (CA), an agricultural system based on minimum tillage, crop residue retention and crop rotation. This review summarizes the current knowledge of N management in CA and identifies research gaps that need to be addressed to optimize N management with the ultimate goal to minimize N losses into the environment and to reduce farmers' input costs. Soil physical, biological and chemical processes in CA are compared with those in conventional systems focusing on their relationship to N cycling in the soil and how they are affected by N fertilizer type, method and number of applications. Based on the little available data, CA has lower NUE rates than conventional systems, which seems largely due to N fertilizer immobilization through crop residues and increased fertilizer rates with CA. Fertilizer use recovery and NUE change with different tillage and residue management, thus the adjustment of N fertilization in CA is inevitable. Finally, the review provides a short overview of methodologies to measure NUE and its components. Available results on the optimization of NUE in CA are inconsistent and studies that cover all three components of CA are scarce. Interactions between components of CA and their effects on crop yield, grain quality, soil and fertilizer parameters are complex and will likely require site-specific management options.

There is an urgent need to develop sustainable agricultural land use schemes. Intensive crop production has induced increased greenhouse gas emissions and enhanced nutrient and pesticide leaching to groundwater and streams. Climate change is also expected to increase drought risk as well as the frequency of extreme precipitation events in many regions. Consequently, sustainable management schemes require sound knowledge of site-specific soil water processes that explicitly take into account the interplay between soil heterogeneities and crops. In this study, we applied a principal component analysis to a set of 64 soil moisture time series from a diversified cropping field featuring seven distinct crops and two weeding management strategies. Results showed that about 97 % of the spatial and temporal variance of the data set was explained by the first five principal components. Meteorological drivers accounted for 72.3 % of the variance and 17.0 % was attributed to different seasonal behaviour of different crops. While the third (4.1 %) and fourth (2.2 %) principal components were interpreted as effects of soil texture and cropping schemes on soil moisture variance, respectively, the effect of soil depth was represented by the fifth component (1.7 %). However, neither topography nor weed control had a significant effect on soil moisture variance. Contrary to common expectations, soil and rooting pattern heterogeneity seemed not to play a major role. Findings of this study highly depend on local conditions. However, we consider the presented approach generally applicable to a large range of site conditions.