scholarly journals Spatial variability of soil organic carbon and total nitrogen in the hilly red soil region of Southern China

2019 ◽  
Vol 31 (6) ◽  
pp. 2385-2394 ◽  
Author(s):  
Xiong Yao ◽  
Kunyong Yu ◽  
Yangbo Deng ◽  
Jian Liu ◽  
Zhuangjie Lai

Abstract To obtain accurate spatial distribution maps of soil organic carbon (SOC) and total nitrogen (TN) in the Hetian Town in Fujian Province, China, soil samples from three depths (0–20, 20–40, and 40–60 cm) at 59 sampling sites were sampled by using traditional analysis and geostatistical approach. The SOC and TN ranged from 2.26 to 47.54 g kg−1, and from 0.28 to 2.71 g kg−1, respectively. The coefficient of variation for SOC and TN was moderate at 49.02–55.87% for all depths. According to the nugget-to-sill ratio values, a moderate spatial dependence of SOC content and a strong spatial dependence of TN content were found in different soil depths, demonstrating that SOC content was affected by both extrinsic and intrinsic factors while TN content was mainly influenced by intrinsic factors. Indices of cross-validation, such as mean error, mean standardized error, were close to zero, indicating that ordinary kriging interpolation is a reliable method to predict the spatial distribution of SOC and TN in different soil depths. Interpolation using ordinary kriging indicated the spatial pattern of SOC and TN were characterized by higher in the periphery and lower in the middle. To improve the accuracy of spatial interpolation for soil properties, it is necessary and important to incorporate a probabilistic and machine learning methods in the future study.

2021 ◽  
pp. 1-19
Author(s):  
Yingcong Ye ◽  
Yefeng Jiang ◽  
Lihua Kuang ◽  
Yi Han ◽  
Zhe Xu ◽  
...  

2015 ◽  
Vol 153 ◽  
pp. 161-168 ◽  
Author(s):  
Jian-Fu Xue ◽  
Chao Pu ◽  
Sheng-Li Liu ◽  
Zhong-Du Chen ◽  
Fu Chen ◽  
...  

2018 ◽  
Vol 64 (1-4) ◽  
pp. 25-34
Author(s):  
Yong-hua Zhu ◽  
Sheng Zhang ◽  
Biao Sun ◽  
Xiao-kang Xi ◽  
Yu Liu ◽  
...  

Quantification of the pattern and spatial distribution of soil organic carbon (SOC) is essential to comprehending many eco-hydrological processes. To obtain a better understanding of the spatial variability of SOC in a typical farming-pastoral zone, 270 soil samples were collected at 45 sampling sites from every 20 cm soil layer. Semi-variance function theory and ordinary Kriging interpolation were applied to identify the spatial variability of SOC. The results showed that SOC in the area was relatively low and decreased with depth and from the basin edge to the centre with a measured mean content of 0.07–0.65 g/kg. The strongest variability in the zone in the top soil layer (0–40 cm) was in the centre part of the zone, which was supposed to be the most concentrated area of human activities in the zone. As soil depth increase, the degree of variation of SOC decreased. Gaussian, exponential, and spherical models were suggested to successfully simulate SOC in different soil depth zones. The spatial distribution of SOC showed strong variability in the same soil depth zone, with a nugget to sill ratio of less than 14% and a range of 30–160 km.


2018 ◽  
Vol 77 (17) ◽  
Author(s):  
Igor Bogunovic ◽  
Paulo Pereira ◽  
Radica Coric ◽  
Stjepan Husnjak ◽  
Eric C. Brevik

2021 ◽  
Vol 120 ◽  
pp. 106930
Author(s):  
Qing Qi ◽  
Dongjie Zhang ◽  
Mingye Zhang ◽  
Shouzheng Tong ◽  
Wuehong Wang ◽  
...  

Water ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 197
Author(s):  
Xiuying Yao ◽  
Dandan Yan ◽  
Jingtai Li ◽  
Yao Liu ◽  
Yufeng Sheng ◽  
...  

The invasion and expansion of Spartina alterniflora in coastal salt marsh wetlands have greatly affected the material cycle of the ecosystem. A total of 372 topsoil samples were collected from 124 sites representing two land-cover types by implementing an unprecedented high sampling density study in the Dafeng Milu National Nature Reserve. Classical statistics and geostatistics were used to quantify soil organic carbon (SOC) and total nitrogen (TN) spatial distribution. Redundancy analysis (RDA) was used to detect correlations between environmental factors, SOC, and TN. The results showed that SOC and TN have moderate variability. The spatial distributions of SOC and TN were similar, and the highest values were observed in the southwest of the study area. In different land cover types, the SOC and TN in the vegetation coverage areas with Spartina alterniflora as the dominant species were significantly higher than those in bare land. RDA showed that TN and aboveground biomass significantly affected the spatial distribution of SOC, while SOC and AGB dominated the spatial distribution of TN.


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