Journal Articles

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Optimizing nitrogen and phosphorus application to improve soil organic carbon and alfalfa hay yield in alfalfa fields
(Frontiers Media South Africa, 2023) Wei K; Zhao J; Sun Y; López IF; Ma C; Zhang Q; Wang LI
Soil organic carbon (SOC) is the principal factor contributing to enhanced soil fertility and also functions as the major carbon sink within terrestrial ecosystems. Applying fertilizer is a crucial agricultural practice that enhances SOC and promotes crop yields. Nevertheless, the response of SOC, active organic carbon fraction and hay yield to nitrogen and phosphorus application is still unclear. The objective of this study was to investigate the impact of nitrogen-phosphorus interactions on SOC, active organic carbon fractions and hay yield in alfalfa fields. A two-factor randomized group design was employed in this study, with two nitrogen levels of 0 kg·ha-1 (N0) and 120 kg·ha-1 (N1) and four phosphorus levels of 0 kg·ha-1 (P0), 50 kg·ha-1 (P1), 100 kg·ha-1 (P2) and 150 kg·ha-1 (P3). The results showed that the nitrogen and phosphorus treatments increased SOC, easily oxidized organic carbon (EOC), dissolved organic carbon (DOC), particulate organic carbon (POC), microbial biomass carbon (MBC) and hay yield in alfalfa fields, and increased with the duration of fertilizer application, reaching a maximum under N1P2 or N1P3 treatments. The increases in SOC, EOC, DOC, POC, MBC content and hay yield in the 0-60 cm soil layer of the alfalfa field were 9.11%-21.85%, 1.07%-25.01%, 6.94%-22.03%, 10.36%-44.15%, 26.46%-62.61% and 5.51%-23.25% for the nitrogen and phosphorus treatments, respectively. The vertical distribution of SOC, EOC, DOC and POC contents under all nitrogen and phosphorus treatments was highest in the 0-20 cm soil layer and tended to decrease with increasing depth of the soil layer. The MBC content was highest in the 10-30 cm soil layer. DOC/SOC, MBC/SOC (excluding N0P1 treatment) and POC/SOC were all higher in the 0-40 cm soil layer of the alfalfa field compared to the N0P0 treatment, indicating that the nitrogen and phosphorus treatments effectively improved soil fertility, while EOC/SOC and DOC/SOC were both lower in the 40-60 cm soil layer than in the N0P0 treatment, indicating that the nitrogen and phosphorus treatments improved soil carbon sequestration potential. The soil layer between 0-30 cm exhibited the highest sensitivity index for MBC, whereas the soil layer between 30-60 cm had the highest sensitivity index for POC. This suggests that the indication for changes in SOC due to nitrogen and phosphorus treatment shifted from MBC to POC as the soil depth increased. Meanwhile, except the 20-30 cm layer of soil in the N0P1 treatment and the 20-50 cm layer in the N1P0 treatment, all fertilizers enhanced the soil Carbon management index (CMI) to varying degrees. Structural equation modeling shows that nitrogen and phosphorus indirectly affect SOC content by changing the content of the active organic carbon fraction, and that SOC is primarily impacted by POC and MBC. The comprehensive assessment indicated that the N1P2 treatment was the optimal fertilizer application pattern. In summary, the nitrogen and phosphorus treatments improved soil fertility in the 0-40 cm soil layer and soil carbon sequestration potential in the 40-60 cm soil layer of alfalfa fields. In agroecosystems, a recommended application rate of 120 kg·ha-1 for nitrogen and 100 kg·ha-1 for phosphorus is the most effective in increasing SOC content, soil carbon pool potential and alfalfa hay yield
Effects of spatial data resolution on the modelling and mapping of soil organic carbon content in hill country grassland landscapes
(John Wiley and Sons Ltd on behalf of British Society of Soil Science, 2024-01-19) Tran DX; Dominati E; Lowry J; Mackay A; Vibart R; Pearson D; Devantier B; Noakes E
Limited use has been made of spatially explicit modelling of soil organic carbon (SOC) in highly complex farmed landscapes to advance current mapping efforts. This study aimed to address this gap in knowledge by evaluating the spatial prediction of SOC content in the 0–75 mm soil depth in hill country landscapes in New Zealand (NZ) using point-based training data, along with topographic covariates and Sentinel 2 spectral band ratios using an automated set of machine learning (AutoML) tools in ArcGIS. Subsequently, it also focused on quantifying the effects of spatial data resolution (i.e., 1, 8, 15, and 25 m) in terms of predicted map accuracy. Farmlets with contrasting phosphorus fertilizer and sheep grazing histories located at the Ballantrae Hill Country Research Station, NZ were selected to conduct the research. Six candidate algorithms incorporated in the AutoML tools (i.e., XGBoost, LightGBM, linear regression, decision trees, extra trees, random forest) and ensemble model were utilized to model the spatial pattern of SOC content. The results show that the ensemble model that combine predictions of various algorithms applied for 1 m data resolution enables the highest performance and accuracy (i.e., R2 =.76, RMSE = 0.66%). Among the predictive variables used in the model, slope, wetness, and topographic position indices were found to be the most important topographical features that explain SOC patterns in the study area. Inclusion of spectral indices derived from remote sensing, including surface soil moisture and clay minerals ratio, made further improvement to the SOC content prediction. The study reveals that a decrease in the resolution of the geospatial data does not substantively affect the mean SOC content estimation of a farm-scale modelling. However, using coarser resolution data reduces the ability of the model to predict changes in the spatial pattern of SOC content across a hill country grassland landscape.
C3 and C4 grass species: who can reduce soil nitrous oxide emissions in a continental arid region?
(MDPI AG, 8/09/2020) Ning J; He XZ; Hou F
In order to relieve grazing pressure, drought-tolerant grass species are widely cultivated in arid regions. However, soil N emission is largely neglected while pursuing forage yield. We carried out a randomized block study to investigate whether and how the C3 and C4 grass species differ in soil N emission in a typical salinized field with temperate continental arid climate in the northwest inland regions, China. We quantified soil N2O flux from two C3 (barley and rye) and two C4 grass species [corngrass and sorghum hybrid sudangrass (SHS)] in fields during the growing season (from May to September) by using the static box method, and then determined the relationships between soil N2O fluxes and forage yield and soil properties. Results show that soil available nitrogen, soil temperature, pH, soil organic carbon, and total nitrogen were correlated, but soil water was anti-correlated with soil N2O fluxes. In addition, N2O flux increased significantly faster with soil temperature in C4 than in C3 grass fields. Although the lower total N2O emission fluxes were detected for C3 species, the lower yield-scaled N2O was detected for C4 species. Our study provided insights into the determination of grass species and the understanding of mechanisms regulating N2O fluxes in C3 and C4 species in the continental arid regions.

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