The Experts below are selected from a list of 312 Experts worldwide ranked by ideXlab platform
Xingwu Duan - One of the best experts on this subject based on the ideXlab platform.
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Response of Soil Productivity to rehabilitation time in debris flow deposits behind check dams in Hunshui Gully, southwestern China
Archives of Agronomy and Soil Science, 2020Co-Authors: Zaizhi Yang, Xingwu Duan, Li Rong, Jiangcheng Huang, Liyun Zhang, Jiang LiuAbstract:Soil Productivity is a primary determinant of vegetation restoration and land resources utilization in debris flow deposits. However, little is known on the Soil Productivity change process of debr...
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A novel model to assess Soil Productivity in the dry-hot valleys of China
Journal of Mountain Science, 2017Co-Authors: Xingwu Duan, Xu Han, Detai Feng, Li RongAbstract:Accurate evaluation of Soil Productivity has been a long-standing challenge. Although numerous models for Productivity assessment exist, most are cumbersome to use and require substantial parameter inputs. We developed a new empirical Soil Productivity model based on field investigations of Soil erosion, Soil physicochemical properties, and crop yields in the dry-hot valleys (DHVs) in China. We found that Soil pH, and organic matter and available potassium contents significantly affected crop yields under eroded conditions of the DHVs. Moreover, available potassium content was the key factor affecting Soil Productivity. We then modified an existing Soil Productivity model by adding the following parameters: contents of effective water, potassium, organic matter, and clay, Soil pH, and root weighting factor. The modified Soil Productivity model explained 63.5% of the crop yield. We concluded that the new model was simple, realistic, and exhibited strong predictability. In addition to providing an accurate assessment of Soil Productivity, our model could potentially be applied as a Soil module in comprehensive crop models.
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A new method to calculate Soil loss tolerance for sustainable Soil Productivity in farmland
Agronomy for Sustainable Development, 2017Co-Authors: Xingwu Duan, Li Rong, Xiaoning Shi, Detai FenAbstract:AbstractSoil loss tolerance (T) is a widely used concept for assessing potential risks of Soil erosion and is a criterion for assessing the effectiveness of Soil and water conservation projects. However, current approaches for calculating T values lack a strong scientific basis, and few practicable methods are available. Many questions remain regarding which parameters, such as planning periods and offset damages, should be included in calculating T values. Here, we developed a new method to calculate Soil loss tolerance as a function of the Soil Productivity index (SPI) for farmland. To achieve sustainable Soil Productivity in farmland, erosion rates leading to SPI values lower than the lower boundary of Soil Productivity (SPI0) are not tolerable and must be controlled by Soil conservation measures. We applied this method in the Red River Basin of China based on the investigation of typical Soil profiles and crop yields. Our results show that the T values in the Red River Basin ranged from 0.91 to 10.24 t ha−1 a−1. The SPI0 and the lowest limit of Soil loss tolerance (T1) were 0.4 and 0.91 t ha−1 a−1, respectively. Here, we demonstrate that, when determining T values in farmland, (1) the Soil formation rate and offset damage should not be core items, (2) the “planning period” concept should be replaced by “sustainability”, (3) the management objective of T should be the sustainability of the Soil resource, and (4) the T values of farmland should be determined according to Soil Productivity. We provide a reasonable and feasible method to determine T for farmland, which will help maintain the sustainability of Soil Productivity.
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Quantifying Soil erosion effects on Soil Productivity in the dry-hot valley, southwestern China
Environmental Earth Sciences, 2016Co-Authors: Xingwu Duan, Li Rong, Bing Liu, Detai FengAbstract:The dry-hot valley region (DHV) in southwestern China is one of the most ecologically fragile zones in China with intensive Soil erosion. Few studies have focused on the effects of Soil erosion on Soil Productivity in this region. The objectives of this study were to quantify the effects of Soil erosion on Soil Productivity using the ‘Soil erosion class’ method. The degree of Soil erosion was investigated at 44 monitoring sites in typical DHV catchments, and Soil physicochemical properties, and corn yield at each site were monitored. The results showed that Soil Productivity was significantly affected by Soil erosion in the DHV. As the degree of Soil erosion progressed from ‘slight’ to ‘moderate’ to ‘severe,’ organic matter content decreased 15.29, 18.00, and 27.37 %, alkali-hydrolyzable nitrogen—0.06, 6.03, and 9.45 %, and available potassium content—7.07, 41.79, and 43.32 %, respectively. Compared with the ‘no’ erosion site, the decreases in the mean corn seed yields were 1.56 % for ‘slight,’ 29.18 % for ‘moderate,’ and 35.03 % for ‘severe’ erosion. These results indicated that once the erosion reached ‘moderate’ levels, significant reductions in Soil Productivity were present. The declining slope of corn seed yields was 0.13 Mg ha−1 cm−1 of topSoil loss. The estimated mean for the absolute corn loss was 0.01 Mg ha−1 year−1 in the DHV. These results increased the understanding of the mechanism of Soil degradation processes in the DHV and will be instrumental in developing a strategy for ecological restoration.
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Study on the method of Soil Productivity assessment in black Soil region of Northeast China.
Agricultural Sciences in China, 2009Co-Authors: Xingwu Duan, Yun Xie, Yan-jie Feng, Shuiqing YinAbstract:Abstract The objective of this paper is to investigate a simple and practical method for Soil Productivity assessment in the black Soil region of Northeast China. Firstly, eight kinds of physicochemical properties for each of 120 Soil samples collected from 25 black Soil profiles were analyzed using cluster and correlation analysis. Subsequently, parameter indices were calculated using physicochemical properties. Finally, a modified Productivity index (MPI) model were developed and validated. The results showed that the suitable parameters for Soil Productivity assessment in black Soil region of Northeast China were Soil available water, Soil pH, clay content, and organic matter content. Compared with original Productivity index (PI) model, MPI model added clay content and organic matter content in parameters while omitted bulk density. Simulation results of original PI model and MPI model were compared using crop yield of land block where investigated Soil profiles were located. MPI model was proven to perform better with a higher significant correlation with maize yield. The correlation equation between MPI and yield was: Y =3.2002Ln(MPI) +10.056, R2 = 0.7564. The results showed that MPI model was an effective and practical method to assess Soil Productivity in the research area.
Detai Fen - One of the best experts on this subject based on the ideXlab platform.
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A new method to calculate Soil loss tolerance for sustainable Soil Productivity in farmland
Agronomy for Sustainable Development, 2017Co-Authors: Xingwu Duan, Li Rong, Xiaoning Shi, Detai FenAbstract:AbstractSoil loss tolerance (T) is a widely used concept for assessing potential risks of Soil erosion and is a criterion for assessing the effectiveness of Soil and water conservation projects. However, current approaches for calculating T values lack a strong scientific basis, and few practicable methods are available. Many questions remain regarding which parameters, such as planning periods and offset damages, should be included in calculating T values. Here, we developed a new method to calculate Soil loss tolerance as a function of the Soil Productivity index (SPI) for farmland. To achieve sustainable Soil Productivity in farmland, erosion rates leading to SPI values lower than the lower boundary of Soil Productivity (SPI0) are not tolerable and must be controlled by Soil conservation measures. We applied this method in the Red River Basin of China based on the investigation of typical Soil profiles and crop yields. Our results show that the T values in the Red River Basin ranged from 0.91 to 10.24 t ha−1 a−1. The SPI0 and the lowest limit of Soil loss tolerance (T1) were 0.4 and 0.91 t ha−1 a−1, respectively. Here, we demonstrate that, when determining T values in farmland, (1) the Soil formation rate and offset damage should not be core items, (2) the “planning period” concept should be replaced by “sustainability”, (3) the management objective of T should be the sustainability of the Soil resource, and (4) the T values of farmland should be determined according to Soil Productivity. We provide a reasonable and feasible method to determine T for farmland, which will help maintain the sustainability of Soil Productivity.
Li Rong - One of the best experts on this subject based on the ideXlab platform.
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Response of Soil Productivity to rehabilitation time in debris flow deposits behind check dams in Hunshui Gully, southwestern China
Archives of Agronomy and Soil Science, 2020Co-Authors: Zaizhi Yang, Xingwu Duan, Li Rong, Jiangcheng Huang, Liyun Zhang, Jiang LiuAbstract:Soil Productivity is a primary determinant of vegetation restoration and land resources utilization in debris flow deposits. However, little is known on the Soil Productivity change process of debr...
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A novel model to assess Soil Productivity in the dry-hot valleys of China
Journal of Mountain Science, 2017Co-Authors: Xingwu Duan, Xu Han, Detai Feng, Li RongAbstract:Accurate evaluation of Soil Productivity has been a long-standing challenge. Although numerous models for Productivity assessment exist, most are cumbersome to use and require substantial parameter inputs. We developed a new empirical Soil Productivity model based on field investigations of Soil erosion, Soil physicochemical properties, and crop yields in the dry-hot valleys (DHVs) in China. We found that Soil pH, and organic matter and available potassium contents significantly affected crop yields under eroded conditions of the DHVs. Moreover, available potassium content was the key factor affecting Soil Productivity. We then modified an existing Soil Productivity model by adding the following parameters: contents of effective water, potassium, organic matter, and clay, Soil pH, and root weighting factor. The modified Soil Productivity model explained 63.5% of the crop yield. We concluded that the new model was simple, realistic, and exhibited strong predictability. In addition to providing an accurate assessment of Soil Productivity, our model could potentially be applied as a Soil module in comprehensive crop models.
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A new method to calculate Soil loss tolerance for sustainable Soil Productivity in farmland
Agronomy for Sustainable Development, 2017Co-Authors: Xingwu Duan, Li Rong, Xiaoning Shi, Detai FenAbstract:AbstractSoil loss tolerance (T) is a widely used concept for assessing potential risks of Soil erosion and is a criterion for assessing the effectiveness of Soil and water conservation projects. However, current approaches for calculating T values lack a strong scientific basis, and few practicable methods are available. Many questions remain regarding which parameters, such as planning periods and offset damages, should be included in calculating T values. Here, we developed a new method to calculate Soil loss tolerance as a function of the Soil Productivity index (SPI) for farmland. To achieve sustainable Soil Productivity in farmland, erosion rates leading to SPI values lower than the lower boundary of Soil Productivity (SPI0) are not tolerable and must be controlled by Soil conservation measures. We applied this method in the Red River Basin of China based on the investigation of typical Soil profiles and crop yields. Our results show that the T values in the Red River Basin ranged from 0.91 to 10.24 t ha−1 a−1. The SPI0 and the lowest limit of Soil loss tolerance (T1) were 0.4 and 0.91 t ha−1 a−1, respectively. Here, we demonstrate that, when determining T values in farmland, (1) the Soil formation rate and offset damage should not be core items, (2) the “planning period” concept should be replaced by “sustainability”, (3) the management objective of T should be the sustainability of the Soil resource, and (4) the T values of farmland should be determined according to Soil Productivity. We provide a reasonable and feasible method to determine T for farmland, which will help maintain the sustainability of Soil Productivity.
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Quantifying Soil erosion effects on Soil Productivity in the dry-hot valley, southwestern China
Environmental Earth Sciences, 2016Co-Authors: Xingwu Duan, Li Rong, Bing Liu, Detai FengAbstract:The dry-hot valley region (DHV) in southwestern China is one of the most ecologically fragile zones in China with intensive Soil erosion. Few studies have focused on the effects of Soil erosion on Soil Productivity in this region. The objectives of this study were to quantify the effects of Soil erosion on Soil Productivity using the ‘Soil erosion class’ method. The degree of Soil erosion was investigated at 44 monitoring sites in typical DHV catchments, and Soil physicochemical properties, and corn yield at each site were monitored. The results showed that Soil Productivity was significantly affected by Soil erosion in the DHV. As the degree of Soil erosion progressed from ‘slight’ to ‘moderate’ to ‘severe,’ organic matter content decreased 15.29, 18.00, and 27.37 %, alkali-hydrolyzable nitrogen—0.06, 6.03, and 9.45 %, and available potassium content—7.07, 41.79, and 43.32 %, respectively. Compared with the ‘no’ erosion site, the decreases in the mean corn seed yields were 1.56 % for ‘slight,’ 29.18 % for ‘moderate,’ and 35.03 % for ‘severe’ erosion. These results indicated that once the erosion reached ‘moderate’ levels, significant reductions in Soil Productivity were present. The declining slope of corn seed yields was 0.13 Mg ha−1 cm−1 of topSoil loss. The estimated mean for the absolute corn loss was 0.01 Mg ha−1 year−1 in the DHV. These results increased the understanding of the mechanism of Soil degradation processes in the DHV and will be instrumental in developing a strategy for ecological restoration.
Danfeng Sun - One of the best experts on this subject based on the ideXlab platform.
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Rapid diagnosis of agricultural Soil health: A novel Soil health index based on natural Soil Productivity and human management.
Journal of environmental management, 2020Co-Authors: Fei Lun, Ming Liu, Xiao Xiao, Chongyang Wang, Linlin Wang, Danfeng SunAbstract:Abstract It has become increasingly important to consider its Productivity for agricultural Soil health assessment. Moreover, one of the main challenges is that there are still few studies on addressing the complex dynamics of Soil health assessment by the rapid and cross-regional method. Thus, we proposed a novel conceptual model to evaluate agricultural Soil health in order to highlight the synergy and interaction of natural Soil Productivity and its external inputs; besides, the new proposed Soil health index (SHI) can be used to rapidly quantify their influences of Soil Productivity on Soil health assessment, based on the 10-day normalized difference vegetation index (NDVI) time series data. We applied the principal component analysis (PCA) to transform NDVI profiles into responses of crop primary Productivity due to different drivers. The results demonstrated that Soil Productivity in our study area can be identified for different cropping systems by the PCA method; and different principle components (PCs) for the same cropping system can also be used to estimate contributions of natural Soil Productivity and human management Productivity. The SHI indicator, defined by the equation of (PC1-PC2)/(PC1+PC2), was used to explore Soil health in our study area. We found that Soil in the orchard system was relatively healthier than that in other two cropping systems, indicating the natural Soil Productivity presented more contributions than that from external inputs. We concluded that it is useful to apply the SHI indicator into Soil health assessment, especially considering the local natural situation and human management practices.
Xiaoning Shi - One of the best experts on this subject based on the ideXlab platform.
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A new method to calculate Soil loss tolerance for sustainable Soil Productivity in farmland
Agronomy for Sustainable Development, 2017Co-Authors: Xingwu Duan, Li Rong, Xiaoning Shi, Detai FenAbstract:AbstractSoil loss tolerance (T) is a widely used concept for assessing potential risks of Soil erosion and is a criterion for assessing the effectiveness of Soil and water conservation projects. However, current approaches for calculating T values lack a strong scientific basis, and few practicable methods are available. Many questions remain regarding which parameters, such as planning periods and offset damages, should be included in calculating T values. Here, we developed a new method to calculate Soil loss tolerance as a function of the Soil Productivity index (SPI) for farmland. To achieve sustainable Soil Productivity in farmland, erosion rates leading to SPI values lower than the lower boundary of Soil Productivity (SPI0) are not tolerable and must be controlled by Soil conservation measures. We applied this method in the Red River Basin of China based on the investigation of typical Soil profiles and crop yields. Our results show that the T values in the Red River Basin ranged from 0.91 to 10.24 t ha−1 a−1. The SPI0 and the lowest limit of Soil loss tolerance (T1) were 0.4 and 0.91 t ha−1 a−1, respectively. Here, we demonstrate that, when determining T values in farmland, (1) the Soil formation rate and offset damage should not be core items, (2) the “planning period” concept should be replaced by “sustainability”, (3) the management objective of T should be the sustainability of the Soil resource, and (4) the T values of farmland should be determined according to Soil Productivity. We provide a reasonable and feasible method to determine T for farmland, which will help maintain the sustainability of Soil Productivity.