Characterizing scale-specific environmental factors affecting soil organic carbon along two landscape transects
Soil organic carbon (SOC) is one of the most important soil properties affecting many other soil and environmental properties and processes. In order to understand and manage SOC effectively, it is important to identify the scale-specific main factors affecting SOC distributions, which in this study occurred in a watershed on the Loess Plateau. Two transects were selected that passed along the upper slopes on each side of the main gully of the Liudaogou watershed. Transect 1 (3411-m length) had 27 sampling sites at 131-m intervals; transect 2 (3597 m length) had 30 sampling sites at 124-m intervals. The two transects were chosen in order to compare landscape patterns of differing complexity that were in close proximity, which reduced the effects of factors that would be caused by different locations. The landscape of transect 1 was more complex due to the greater diversity in cultivation. Multivariate empirical mode decomposition (MEMD) decomposed the total variation in SOC and five selected environmental factors into four intrinsic mode functions (IMFs) and a residual according to the scale of occurrence. Scale-specific correlation analysis was used to identify significant relationships between SOC and the environmental factors. The dominant scales were those that were the largest contributors to the total SOC variance; for transect 1, this was the IMF 1 (scale of 403 m), whereas for transect 2, it was the medium scale of the IMF 2 (scale of 688 m). For both transects, vegetation properties (vegetation cover and aboveground biomass) were the main factors affecting SOC distributions at their respective dominant scales. At each scale, the main effective factors could be identified although at the larger scales, their contributions to the overall variance were almost negligible. The distributions of SOC and the factors affecting it were found to be scale dependent. The results of this study highlighted the suitability of the MEMD method in revealing the main scale-specific factors that affect SOC distributions, which is necessary in understanding and managing this important soil property.
Spatial Scaling Effects to Enhance the Prediction for the Temporal Changes of Soil Nitrogen Density From 2007 to 2017 in Different Climatic Basins
Soil nitrogen density (SND), which is influenced by environmental factors operating at different spatial scales and intensities, is critical for agricultural production and soil quality. Although the spatiotemporal distribution of top-layer SND has been well explored, the scale effects of environmental factors on the temporal changes of SND (SNDT) are poorly studied, which might promote the predictive accuracy of SNDT. Thus, SNDT during a certain period was calculated to explore the multiscale effects of environmental factors on it. In the study, three sampling transects under the basins of warm-temperate, mid-temperate, and warm-temperate zones were established with 200 km long and 1 km intervals to explore the spatial variation of SNDT, examine the multiscale effect of environmental factors on it, construct the predicting models based on its scale-specific relations with environmental factors, and validate the models in each basin or in other climate-zone basins. The results indicated that the increment of SND during a certain period was the greatest in the mid-temperate basin, and the variation of SNDT was ranked as cool-temperate > mid-temperate > warm-temperate basins. Under different soil types, the spatial characteristics of SNDT were different in different climate-zone basins, but the average SNDT under cropland was the greatest in each basin. Considering the influencing factors (climatic, topographic, and vegetation factors), they had controls on SNDT operating at different spatial scales. In regard to the prediction of SNDT, the method of partial least square regression (PLSR) combined with a multiscale analysis was found to be more preferable for dependent SNDT prediction than the traditional method of stepwise multiple linear regression but could not be validated for the independent validation data in other basins. Thus, the spatial multiscale relations of SNDT with environmental factors could provide more information for each basin, and the integration of the extra information decomposed by wavelet transform into the method of PLSR could enhance the SNDT prediction for dependent datasets. These findings are of great significance for future studies in the spatial modeling of SND temporal dynamics under the influence of environmental changes.
Cadmium concentration in winter wheat as affected by nitrogen fertilization
Abstract Cadmium (Cd) is a toxic heavy metal which to a relatively large extent is ingested via wheat-based products. Conflicting results have been reported on how the application of nitrogen (N) fertilizers to winter wheat (Triticum aestivum L.) affects the Cd concentration in grain. The objectives of this study were to investigate how and to what degree application of N fertilizer affected the Cd concentration in winter wheat grain under field conditions and how consistent such effects were between sites and cultivars. Two wheat cultivars fertilized with four rates of nitrate of lime (100, 145, 190 and 235 kg N ha−1) were investigated in field trials, where the fertilizer was applied on two occasions as is common for bread wheat. In addition, data on Cd and N concentrations in grain of wheat, oats and barley from a Swedish soil monitoring programme were evaluated. In the field trials the grain Cd concentration increased with increasing N rate, irrespective of the Cd concentration in soil and grain. Each 10 kg increase in N application gave an increased Cd concentration in grain of approximately 0.001–0.003 mg kg−1. The relative increase in Cd concentration as a function of N rate varied between 6 and 14% across sites and cultivars when the N rate was increased from 145 to 175 kg N. The grain Cd concentration was also positively correlated to the grain N concentration. The data from the Swedish soil monitoring programme showed a significant positive correlation between the N and Cd concentrations in grain of winter wheat, oats and barley. A possible explanation for the increase in grain Cd concentration could be ion exchange reactions in the soil solution, where an increased concentration of the fertilizer cation Ca2+ may have caused an increased concentration of Cd2+ in soil solution and eventually in wheat grain.