Assessing the effect of crop residue removal on soil organic carbon storage and microbial activity in a no-till cropping system

2015 ◽  
Vol 31 (4) ◽  
pp. 450-460 ◽  
Author(s):  
S. Chowdhury ◽  
M. Farrell ◽  
G. Butler ◽  
N. Bolan
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Microbial Activity ◽  
Carbon Storage ◽  
Crop Residue ◽  
Cropping System ◽  
Residue Removal ◽  
No Till ◽  
Crop Residue Removal ◽  
Organic Carbon Storage

Microbial trade-off in soil organic carbon storage in a no-till continuous corn agroecosystem

2020 ◽  
Vol 96 ◽  
pp. 103146 ◽  
Author(s):  
Xuefeng Zhu ◽  
Hongtu Xie ◽  
Michael D. Masters ◽  
Yu Luo ◽  
Xudong Zhang ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Carbon Storage ◽  
Trade Off ◽  
Soil Organic Carbon Storage ◽  
Continuous Corn ◽  
No Till ◽  
Organic Carbon Storage

scholarly journals A Two-Stage Approach to the Estimation of High-Resolution Soil Organic Carbon Storage with Good Extension Capability

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 517
Author(s):  
Sunwei Wei ◽  
Zhengyong Zhao ◽  
Qi Yang ◽  
Xiaogang Ding
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Carbon Storage ◽  
Guangdong Province ◽  
Soil Samples ◽  
Estimation Accuracy ◽  
Ann Model ◽  
Soil Layers ◽  
Second Stage ◽  
Organic Carbon Storage

Soil organic carbon storage (SOCS) estimation is a crucial branch of the atmospheric–vegetation–soil carbon cycle study under the background of global climate change. SOCS research has increased worldwide. The objective of this study is to develop a two-stage approach with good extension capability to estimate SOCS. In the first stage, an artificial neural network (ANN) model is adopted to estimate SOCS based on 255 soil samples with five soil layers (20 cm increments to 100 cm) in Luoding, Guangdong Province, China. This method is compared with three common methods: The soil type method (STM), ordinary kriging (OK), and radial basis function (RBF) interpolation. In the second stage, a linear model is introduced to capture the regional differences and further improve the estimation accuracy of the Luoding-based ANN model when extending it to Xinxing, Guangdong Province. This is done after assessing the generalizability of the above four methods with 120 soil samples from Xinxing. The results for the first stage show that the ANN model has much better estimation accuracy than STM, OK, and RBF, with the average root mean square error (RMSE) of the five soil layers decreasing by 0.62–0.90 kg·m−2, R2 increasing from 0.54 to 0.65, and the mean absolute error decreasing from 0.32 to 0.42. Moreover, the spatial distribution maps produced by the ANN model are more accurate than those of other methods for describing the overall and local SOCS in detail. The results of the second stage indicate that STM, OK, and RBF have poor generalizability (R2 < 0.1), and the R2 value obtained with ANN method is also 43–56% lower for the five soil layers compared with the estimation accuracy achieved in Luoding. However, the R2 of the linear models built with the 20% soil samples from Xinxing are 0.23–0.29 higher for the five soil layers. Thus, the ANN model is an effective method for accurately estimating SOCS on a regional scale with a small number of field samples. The linear model could easily extend the ANN model to outside areas where the ANN model was originally developed with a better level of accuracy.

Estimations of soil organic carbon storage in cropland of China based on DNDC model

Geoderma ◽  
2006 ◽  
Vol 134 (1-2) ◽  
pp. 200-206 ◽  
Author(s):  
Huajun Tang ◽  
Jianjun Qiu ◽  
Eric Van Ranst ◽  
Changsheng Li
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Carbon Storage ◽  
Dndc Model ◽  
Soil Organic Carbon Storage ◽  
Organic Carbon Storage

Estimating soil organic carbon storage and distribution in a catchment of Loess Plateau, China

Geoderma ◽  
2010 ◽  
Vol 154 (3-4) ◽  
pp. 261-266 ◽  
Author(s):  
Fengpeng Han ◽  
Wei Hu ◽  
Jiyong Zheng ◽  
Feng Du ◽  
Xingchang Zhang
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Carbon Storage ◽  
Loess Plateau ◽  
Soil Organic Carbon Storage ◽  
Organic Carbon Storage
Sign in / Sign up

Export Citation Format

Share Document