Spatiotemporal variations and factors affecting soil nitrogen in the purple hilly area of Southwest China during the 1980s and the 2010s

Spatial differentiation of soil nutrients and their ecological chemometrics based on geographic detector in National Agricultural Park of Tangchang, Southwest China

In order to analyze the spatial variability of soil nutrients and their ecological chemometrics in Tangchang Town, National Agricultural Park, 20 influencing factors were selected: soil pH, Cd, Hg, As, Cu, Pb, Cr, Zn, Ni, Se, elevation, slope, aspect, land use type, distance from industrial land, distance from commercial land, distance from railway, distance from residential area, distance from highway and distance from river. The effects of various influencing factors on the spatial variability of total organic carbon (TOC), total nitrogen (N), total phosphorus (P), total potassium (K) and ecological stoichiometry were analyzed by means of geographic detector. The results showed that average contents of soil TOC, N, P and K in the study area are 10.24 g kg-1, 1.33 g kg-1, 1.14 g kg-1 and 23.60 g kg-1, respectively, and there were significant differences in the spatial distribution of soil nutrients and their eco-stoichiometry in the study area, and TOC, N, P, K, C/N, C/P, C/K, N/P, N/K and P/K has a significant correlation with each other and most correlation coefficients are above 0.5 or below -0.5. Factor detection showed that soil properties, distance from railway and distance from residential area had the most significant explanatory power to the spatial heterogeneity of soil nutrients and eco-stoichiometry. Interaction detection showed that the interaction between soil properties with other factors was the most important factor affecting the spatial differentiation of soil nutrients and their ecological chemometrics, and elevation, distance from railway and distance from residential area were also important factors. Risk detection showed that the differences of soil nutrients and their ecological stoichiometry were most significant in the subregions of soil properties (pH, Cd, Hg, As, Cu, Pb, Cr, Zn, Ni and Se).

Divergent responses of cropland soil organic carbon to warming across the Sichuan Basin of China

Cropland soils are considered to have the potential to sequester carbon (C). Warming can increase soil organic C (SOC) by enhancing primary production, but it can also cause carbon release from soils. However, the role of warming in governing cropland SOC dynamics over broad geographic scales remains poorly understood. Using over 4000 soil samples collected in the 1980s and 2010s across the Sichuan Basin of China, this study assessed the warming-induced cropland SOC change and the correlations with precipitation, cropland type and soil type. Results showed mean SOC content increased from 11.10 to 13.85 g C kg^-1. Larger SOC increments were observed under drier conditions (precipitation < 1050 mm, dryland and paddy-dryland rotation cropland), which were 1.67-2.23 times higher than under wetter conditions (precipitation > 1050 mm and paddy fields). Despite the significant associations of SOC increment with crop productivity, precipitation, fertilization, cropland type and soil type, warming also acted as one of major contributors to cropland SOC change. The SOC increment changed parabolically with the rise in temperature increase rate under relatively drier conditions, while temperature increase had no impact on cropland SOC increment under wetter conditions. Meanwhile, the patterns of the parabolical relationship varied with soil types in drylands, where the threshold of temperature increase rate, the point at which the SOC increment switched from increasing to decreasing with warming, was lower for clayey soils (Ali-Perudic Argosols) than for sandy soils (Purpli-Udic Cambosols). These results illustrate divergent responses of cropland SOC to warming under different environments, which were contingent on water conditions and soil types. Our findings emphasize the importance of formulating appropriate field water management for sustainable C sequestration and the necessity of incorporating environment-specific mechanisms in Earth system models for better understanding of the soil C-climate feedback in complex environments.

Application of a combinatorial approach for soil organic carbon mapping in hills

Accurate mapping of soil organic carbon (SOC) is critical to improve C management and develop sustainable management policies. However, it is constrained by local variations of the model parameters under complex topography, especially in hills. This study applied a methodological framework to optimize the spatial prediction of SOC in the hilly areas during 1981-2012 by quantifying the relative importance of environmental factors, which include both qualitative factors and quantitative variables. Results showed that SOC increased twofold with a moderate spatial dependence during the past 32 years. During this period, land use patterns, soil groups, topographic factors, and vegetation coverage had significant impacts on the SOC changes (p < 0.01). Specifically, the impact of land use patterns has exceeded the impact of soil groups and became the dominant factor affecting SOC changes. Meanwhile, impacts from the topographic factors and vegetation coverage have substantially declined. Based on those results, a combinatorial approach (LS_RBF_HASM) was developed to map SOC using radial basis function neural network (RBF) and high accuracy surface modelling (HASM), and to generate more detailed spatial mapping relationships between SOC and the affecting factors. Compared with ordinary kriging (OK), land use-soil group units (LS) and HASM combined (LS_HASM), multiple linear regression (MLR) and HASM combined with LS (LS_MLR_HASM); LS_RBF_HASM showed a better performance with a decline of 6.3%-37.7% prediction errors and more accurate spatial patterns due to the quantitative combination of auxiliary environmental variables and more information on the SOC variations within local factors captured by RBF and HASM. Additionally, MLR may partially undermine the relationship of the internal spatial structure due to the highly nonlinear relation between SOC and environmental variables. This methodological framework highlights the optimization of more environmental factors and the calculation of spatial variability within local factors and provides a more accurate approach for SOC mapping in hills.

Spatial mapping of soil properties in Konkan region of India experiencing anthropogenic onslaught

Soils of Indian Konkan region, part of ecologically sensitive Western Ghats have been subjected to anthropogenic activities of late. This has endangered the ecological security through conspicuous losses in topsoil quality. The rationale of the present study was to map the soil properties and create management zones for ensuring food and nutritional security. The study was conducted in South Goa district of the state of Goa located in Konkan region. A total of 258 geo-referenced soil samples were collected and analyzed for pH, EC, SOC, available N, P, K and DTPA extractable micronutrients viz., Zn, Cu, Fe and Mn. Soil pH was found to be in acidic range. A wide variability existed in SOC content ranging from 0.12–5.85%. EC was mostly neutral with mean value 0.08±0.37 dSm^-1, while available nitrogen (AN), available phosphorus (AP) and available potassium (AK) varied in range from 56.4–621.6 kg ha^-1, 0.5–49.7 kg ha^-1 and 31.5–786.2 kg ha^-1 with mean values 211.2±76.9, 8.4±8.2 and 202.3±137.6 kg ha^-1, respectively. A wide range was exhibited by cationic DTPA extractable Zn, Cu, Fe and Mn with mean values, 0.22±0.30, 0.44±0.60, 7.78±5.98 and 7.86±5.86 mg kg^-1, respectively. Soil pH exhibited significant positive correlation with EC, AP AK and Zn and negative correlation with Fe and Cu. SOC exhibited significantly correlated with AN, AP, AK, Zn and Fe. Geo-statistical analysis revealed J-Bessel as best fit semivariogram model for pH, AP and AK; Rational Quadratic for EC, SOC, Zn and Mn; Hole effect for AN; Stable for Cu and K-Bessel for Fe for their spatial mapping. Four principal components showed eigenvalues more than one and cumulative variability of 59.38%. Three distinct soil management zones showing significant variation in soil properties were identified and delineated for wider scale management of soils. Precision nutrient management based on spatial variation and their mapping would enable refined agricultural and environmental management practices in the region.

The Influence of Climate, Soil Properties and Vegetation on Soil Nitrogen in Sloping Farmland

Soil nitrogen in farmland ecosystems is affected by climate, soil physical and chemical properties and planting activities. To clarify the effects of these factors on soil nitrogen in sloping farmland quantitatively, the distribution of soil total nitrogen (TN) content, nitrate nitrogen (NO3-N) content and ammonium nitrogen (NH4-N) content at depth of 0–100 cm on 11 profiles of the Luanhe River Basin were analyzed. Meanwhile, soil physical and chemical properties, climatic factors and NDVI (Normalized Difference Vegetation Index) were used to construct a structural equation which reflected the influence mechanism of environmental factors on soil nitrogen concentration. The results showed that TN and NO3-N content decreased with the increase of soil depth in the Luanhe River Basin, while the variation of NH4-N content with soil depth was not obvious. Soil organic carbon (SOC) content, soil pH, soil area average particle size (SMD) and NDVI6 (NDVI of June) explained variation of TN content by 77.4%. SOC was the most important environmental factor contributing to the variation of TN content. NDVI5 (NDVI of May), annual average precipitation (MAP), soil pH and SOC explained 49.1% variation of NO3-N content. Among all environmental factors, only NDVI8 (NDVI of August) had significant correlation with soil NH4-N content, which explained the change of NH4-N content by 24.2%. The results showed that soil nitrogen content in the sloping farmland ecosystem was mainly affected by natural factors such as soil parent material and climate.

Mapping soil organic matter in the Baranja region (Croatia): Geological and anthropic forcing parameters

Spatial mapping of soil organic matter (SOM) and evaluation of the related natural and anthropic influencing factors are crucial to monitor the extent of degraded land and the evolution of soil functions. The objective of this work is to study the spatial distribution of SOM in a highly exploited agricultural area in the Baranja Region (Croatia). The spatially dense dataset available (4825 top-soil samples from 0 to 30 cm) allowed to produce reliable SOM maps using geostatistical interpolation kriging algorithms and to study the relationships with possible influencing factors. The interpolation has been conducted by means of two approaches. In one approach, the overall data set is considered for computing a global variogram and performing a direct interpolation of SOM values. In the second approach, the data are stratified according to two different geological and morphogenetic domains, Holocene Domain (HD) and Pleistocene Domain (PD), and a distinct geostatistical analysis is performed in each domain. The results showed that average SOM in the studied region was 2.29%, indicating a future need for adopting sustainable soil management practices in this region. SOM was significantly higher in HD (2.64%) than PD (1.97%) domain. SOM in PD generally had a much lower global variability. Global dataset analysis reveals that regional intrinsic factors prevail over local intrinsic and extrinsic factors in determining SOM spatial patterns. In contrast, the stratified approach can filter the effect of regional variability related to the main geological and geomorphological setting. The structural spatial correlation in PD is weaker than in HD, as manifested by spatial patches of low and high SOM content with smaller extension in PD with respect to HD. The strong relationships between SOM spatial patterns and geological/geomorphological factors suggest the possibility of adopting finer subdivision criteria in future research.

Spatiotemporal Variability of Soil Nitrogen in Relation to Environmental Factors in a Low Hilly Region of Southeastern China

Soil total nitrogen (TN) plays a major role in agriculture, geochemical cycles and terrestrial ecosystem functions. Knowledge regarding the TN distribution is crucial for the sustainable use of soil resources. This paper therefore aims to characterize the spatiotemporal distribution of soil TN and improve the current understanding of how various factors influence changes in TN. Natural characteristics and remote sensing (RS) variables were used in conjunction with the random forest (RF) model to map the TN distribution in a low hilly region of southeastern China in 1979, 2004 and 2014. The means and changes of TN in different geographic regions and farmland protection regions were also analyzed. The results showed that: (1) the TN showed an increasing trend in the early periods and exhibited a decreasing trend from 2004 to 2014; (2) the geographic and RS variables played more important roles in predicting TN distribution than did the other variables; and (3) changes in the fertilization and crop planting structure caused by soil testing and formulated fertilization techniques (STFFT-Soil Testing and Formulated Fertilization Techniques) as well as farmland protection policies influenced the spatiotemporal variability of TN. Evidently, more attention should be focused on improving the quality and soil fertility in the surrounding low mountainous areas.

Spatio-temporal distribution of soil nitrogen in Poyang lake ecological economic zone (South-China)

Revealing the spatio-temporal distribution of soil nitrogen (N) contributes to N management and prevention of N pollution. The objective of this work is to study the spatio-temporal distribution of soil N and their driving factors in the topsoil (0-20 cm) of farmland in Yugan county, China in 1982 and 2012. Data were collected from 200 sampling sites of the second national soil survey in Yugan in 1982 and 423 sampling sites of the soil testing and formula fertilization project in 2012. On average total N (TN) and available N (AN) significantly increased from 1.50 g kg^-1 and 153.04 mg kg^-1 in 1982 to 1.58 g kg^-1 and 179.75 mg kg^-1 in 2012, respectively. The distance of spatial autocorrelation for TN increased from 2.79 to 6.18 km and from 2.97 to 18.00 km for AN from 1982 to 2012. The nugget/sill ratio for TN (0.472 in 1982 and 0.581 in 2012) indicated that soil TN driving by natural characteristics in 1982 to human activities in 2012. The nugget/sill ratio for soil AN (0.471 in 1982 and 0.688 in 2012) indicated that soil AN is more influenced by human activities. The major factors driving the spatio-temporal distribution of soil N was N application rate. To promote the sustainable development of agriculture and eco-environment, we should improve the awareness of farmers on chemical fertilizers (particularly N) and the level of N fertilizer management, increase the use of manure and organic fertilizer and facilitate rational fertilization by farmers.

Spatial variability of soil nitrogen in a hilly valley: Multiscale patterns and affecting factors

Estimating the spatial distribution of soil nitrogen at different scales is crucial for improving soil nitrogen use efficiency and controlling nitrogen pollution. We evaluated the spatial variability of soil total nitrogen (TN) and available nitrogen (AN) in the Fujiang River Valley, a typical hilly region composed of low, medium and high hills in the central Sichuan Basin, China. We considered the two N forms at single hill, landscape and valley scales using a combined method of classical statistics, geostatistics and a geographic information system. The spatial patterns and grading areas of soil TN and AN were different among hill types and different scales. The percentages of higher grades of the two nitrogen forms decreased from low, medium to high hills. Hill type was a major factor determining the spatial variability of the two nitrogen forms across multiple scales in the valley. The main effects of general linear models indicated that the key affecting factors of soil TN and AN were hill type and fertilization at the single hill scale, hill type and soil type at the landscape scale, and hill type, slope position, parent material, soil type, land use and fertilization at the valley scale. Thus, the effects of these key factors on the two soil nitrogen forms became more significant with upscaling.