The diagnosis of the N status of crops is based on the concept of critical N concentration (Ncr), which is the minimum N concentration in shoot biomass (SB) required for maximizing growth. A reference curve of Ncr decrease (Ref‐Ncr) with SB increase proposed for C3 species (Ref‐Ncr=48 SB‐0.32) was validated for several crops growing without water deficiency in different sites and seasons; however, the validity of Ref‐Ncr is uncertain when water is limiting. The objective was to assess whether water stress affects Ncr. Five regrowths of a temperate‐type tall fescue [Lolium arundinaceum (Schreb.) Darbysh.] were followed during autumn, spring, and summer in Balcarce, Argentina. Several N rates were applied and SB accumulation and N concentration were measured in each of four to six sequential SB harvests performed at every regrowth. SB, Ncr, available soil water, reference evapotranspiration (ET0), and real evapotranspiration (RET) were estimated. Ncr agreed well with Ref‐Ncr when soil water was nonlimiting, but it was consistently lower than Ref‐Ncr whenever crop RET was reduced (RET/ET0<1). Indeed, crop average Ncr during an entire regrowth scaled linearly with the average level of water stress in the period: (Ncr/Ref‐Ncr)avg = 0.83 (RET/ET0)avg + 0.22 (R2 = 0.90, p < 0.0001). Hence, while Ref‐Ncr remains appropriate for assessing crop N status under adequate water availability conditions, the N nutrition management of water stressed crops should be guided by their actualNcr.

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Our ability to develop strategies to mitigate climate change includes an understanding of, and our capacity to predict soil organic carbon (SOC) dynamics in livestock systems. Here we assess the capability of the Sustainable Grazing System (SGS) Pasture Model for predicting pasture growth (elongated wheatgrass, Thinopyrum ponticum) and SOC accumulation in different environments and under a range of pasture management practices in hydrohalomorphic soils located in South‐eastern Buenos Aires Province, Argentina. After Model calibration, aerial net primary productivity (ANPP) and TSOC content under two grazing intensities (7.5 and 11 cm post‐grazing target heights) and two N fertilization levels (0 and 100 kg N ha−1 yr−1) were simulated over a 10 year‐period. The SGS Pasture Model predicted 87% of the observed ANPP, with observed and predicted ANPPs averaging 1.46 and 1.42 Mg ha−1 yr−1, respectively. There were differences in simulated ANPP between fertilized and unfertilized treatments both at high and low grazing intensities for the last year of the period. Total SOC contents from the modelling showed differences between high (83.7 to 84.2 Mg ha−1) and low (86.8 to 87.5 Mg ha−1) grazing intensities, with treatments receiving N also showing higher carbon stocks. The positive effect of reduced grazing intensity on soil carbon was explained by an increased input of aerial and subterranean dry matter into the soil. Sensitivity analysis showed that SGS is a robust model, capable of performing effectively under a variety of conditions. Hence, it can be used for exploring management practices to mitigate the impact of livestock systems on emissions and SOC stocks.