A new technique of dimension reduction named projection pursuit is applied to model and evaluatewetland soil quality variations in the Sanjiang Plain, Helongjiang Province, China. By adopting the im-proved real-coded ...A new technique of dimension reduction named projection pursuit is applied to model and evaluatewetland soil quality variations in the Sanjiang Plain, Helongjiang Province, China. By adopting the im-proved real-coded accelerating genetic algorithm (RAGA), the projection direction is optimized and multi-dimensional indexes are converted into low-dimensional space. Classification of wetland soils and evaluationof wetland soil quality variations are realized by pursuing optimum projection direction and projection func-tion value. Therefore, by adopting this new method, any possible human interference can be avoided andsound results can be achieved in researching quality changes and classification of wetland soils.展开更多
Mining operations can usually lead to environmental deteriorations. Underground mining activities could cause an extensive decrease in groundwater level and thus a dramatic variation in soil moisture content（SMC）. I...Mining operations can usually lead to environmental deteriorations. Underground mining activities could cause an extensive decrease in groundwater level and thus a dramatic variation in soil moisture content（SMC）. In this study, the spatial and temporal variations of SMC from 2001 to 2015 at two spatial scales（i.e., the Shendong coal mining area and the Daliuta Coal Mine） were analyzed using an improved thermal inertia model with a long-term series of Landsat TM/OLI（TM=Thematic Mapper and OLI=Operational Land Imager） data. Our results show that at large spatial scale（the Shendong coal mining area）, underground mining activities had insignificant negative impacts on SMC and that at small spatial scale（the Daliuta Coal Mine）, underground mining activities had significant negative impacts on SMC. Trend analysis of SMC demonstrated that areas with decreasing trend of SMC were mainly distributed in the mined area, indicating that underground mining is a primary cause for the drying trend in the mining region in this arid environment.展开更多
High-resolution and detailed regional soil spatial distribution information is increasingly needed for ecological modeling and land resource management. For areas with no point data, regional soil mapping includes two...High-resolution and detailed regional soil spatial distribution information is increasingly needed for ecological modeling and land resource management. For areas with no point data, regional soil mapping includes two steps： soil sampling and soil mapping. Because sampling over a large area is costly, efficient sampling strategies are required. A multi-grade representative sampling strategy, which designs a small number of representative samples with different representative grades to depict soil spatial variations at different scales, could be a potentially efficient sampling strategy for regional soil mapping. Additionally, a suitable soil mapping approach is needed to map regional soil variations based on a small number of samples. In this study, the multi-grade representative sampling strategy was applied and a fuzzy membership-weighted soil mapping approach was developed to map soil sand percentage and soil organic carbon （SOC） at 0-20 and 20-40 cm depths in a study area of 5 900 km2 in Anhui Province of China. First, geographical sub-areas were delineated using a parent lithology data layer. Next, fuzzy c-means clustering was applied to two climate and four terrain variables in each stratum. The clustering results （environmental cluster chains） were used to locate representative samples. Evaluations based on an independent validation sample set showed that the addition of samples with lower representativeness generally led to a decrease of root mean square error （RMSE）. The declining rates of RMSE with the addition of samples slowed down for 20-40 cm depth, but fluctuated for 0-20 cm depth. The predicted SOC maps based on the representative samples exhibited higher accuracy, especially for soil depth 20-40 cm, as compared to those based on legacy soil data. Multi-grade representative sampling could be an effective sampling strategy at a regional scale. This sampling strategy, combined with the fuzzy membership-based mapping approach, could be an optional effective framework for regional soil property mapping. A more detailed and accurate soft parent material map and the addition of environmental variables representing human activities would improve mapping accuracy.展开更多
Plastic mulched ridge-furrow irrigation is a useful method to improve crop productivity and decrease salt accumulation in arid saline areas.However,inappropriate irrigation and fertilizer practices may result in ecolo...Plastic mulched ridge-furrow irrigation is a useful method to improve crop productivity and decrease salt accumulation in arid saline areas.However,inappropriate irrigation and fertilizer practices may result in ecological and environmental problems.In order to improve the resource use efficiency in these areas,we investigated the effects of different irrigation amounts(400(I1),300(I2)and 200(I3)mm)and nitrogen application rates(300(F1)and 150(F2)kg N/hm^(2))on water consumption,salt variation and resource use efficiency of spring maize(Zea mays L.)in the Hetao Irrigation District(HID)of Northwest China in 2017 and 2018.Result showed that soil water contents were 0.2%-8.9%and 13.9%-18.1%lower for I2 and I3 than for I1,respectively,but that was slightly higher for F2 than for F1.Soil salt contents were 7.8%-23.5%and 48.5%-48.9%lower for I2 than for I1 and I3,but that was 1.6%-5.5%higher for F1 than for F2.Less salt leaching at the early growth stage(from sowing to six-leaf stage)and higher salt accumulation at the peak growth stage(from six-leaf to tasseling stage and from grain-filling to maturity stage)resulted in a higher soil salt content for I3 than for I1 and I2.Grain yields for I1 and I2 were significantly higher than that for I3 and irrigation water use efficiency for I2 was 14.7%-34.0%higher than that for I1.Compared with F1,F2 increased the partial factor productivity(PFP)of nitrogen fertilizer by more than 80%.PFP was not significantly different between I1F2 and I2F2,but significantly higher than those of other treatments.Considering the goal of saving water and nitrogen resources,and ensuring food security,we recommended the combination of I2F2 to ensure the sustainable development of agriculture in the HID and other similar arid saline areas.展开更多
Anthropogenic activities largely influence the soil quality of agricultural fields and the composition of soil. Samples of typical anthropogenic Loutu soil in the Guanzhong area of the Loess Plateau, Shaanxi Province,...Anthropogenic activities largely influence the soil quality of agricultural fields and the composition of soil. Samples of typical anthropogenic Loutu soil in the Guanzhong area of the Loess Plateau, Shaanxi Province, China were collected and measured for soil compaction, bulk density, total organic carbon（TOC）, active organic carbon（AOC）, and soil enzyme activities to investigate spatial variations in soil quality. The results indicate that soil compaction and bulk density increased with increasing distance from the farm village, whereas soil TOC, AOC, and soil enzyme activities firstly increased and subsequently decreased with increasing distance from the farm village. All of the tested parameters presented clear concentric distribution. Vertically, soil compaction and bulk density in the topsoil were lower than those in the subsoil, but all other tested parameters in the topsoil were significantly higher than those in the subsoil. In addition, there was a significant positive correlation between organic carbon content and enzyme activities, confirming that the spatial distribution of Loutu soil characteristics has been affected by long-term anthropogenic activities to some extent. The results of this study imply that the use of farmyard manure and appropriate deep plowing are important and effective ways to maintain and improve soil quality.展开更多
The impact of land consolidation on the soil microbial PLFA diversity is of great importance for understanding the effective arable land usage,improving agricultural ecological conditions and environment.In this study...The impact of land consolidation on the soil microbial PLFA diversity is of great importance for understanding the effective arable land usage,improving agricultural ecological conditions and environment.In this study,we collected the soil samples(0–20 cm)in experimental plots with 0(Z0),1(Z1a)and 4(Z4a)years of land consolidation in the forest station of Ningbo City,Zhejiang Province,southeastern China.The results were analyzed using ANOVA for randomized block design.Compared with control(Z0),the soil pH value under Z1a treatment increased by 14.6%,soil organic carbon(SOC)content decreased by 65.4%,so did the PLFA contents and relative abundance of all the microbial PLFA diversity(P<0.05),respectively.Meanwhile,for the Z1a treatment,the ratio of fungi to bacteria(F/B)significantly decreased by 35.9%(P<0.05),while the ratio of Gram-positive bacteria to Gram-negative bacteria(G+/G−)signific antly increased by 56.1%.This was strongly related to the increased soil pH values and the decrease of SOC.The Shannon index(H)and evenness index(E)of soil microbial PLFA diversity were significantly decreased after land consolidation(P<0.05).Compared to the Z1 treatment,the microbial PLFA diversity was improved slightly.Therefore,the land consolidation could significantly affect the composition of soil microbial PLFA diversity,and decrease the soil ecosystem stability.展开更多
The emergence rate and vitality of maize are directly affected by the sowing depth,and the uniformity of this depth is an important performance indicator of a planter,while the effective soil surface height informatio...The emergence rate and vitality of maize are directly affected by the sowing depth,and the uniformity of this depth is an important performance indicator of a planter,while the effective soil surface height information acquisition is the prerequisite for ensuring the accuracy of sowing depth control.The soil surface height variation acquisition system of a precision corn planter often produces profiling errors when performing active profiling due to interference from ground debris.In this study,a multipoint soil surface height variation information acquisition system was investigated,which consists of a ranging sensor group and a microcontroller unit(MCU)using a data comparison and screening method.The structure and specifications of the ranging sensors were determined according to the soil surface height variation and debris size,and a nonessential profiling control program was developed.Performed tests on the information acquisition system indicated that the measurement accuracy of the system was 3 mm,and when advancing at a speed of 8 km/h,the accuracy of the profiling decision and the system stability were 97.1%and 94.1%,respectively,indicating that the system was capable of nonessential profile control.The designed ranging system could provide a reference for the design of a ground information acquisition system of precision planters with an active profiling mechanism.展开更多
Soil spatial information has traditionally been presented as polygon maps at coarse scales. Solving global and local issues, including food security, water regulation, land degradation, and climate change requires hig...Soil spatial information has traditionally been presented as polygon maps at coarse scales. Solving global and local issues, including food security, water regulation, land degradation, and climate change requires higher quality, more consistent and detailed soil information. Accurate prediction of soil variation over large and complex areas with limited samples remains a challenge, which is especially significant for China due to its vast land area which contains the most diverse soil landscapes in the world. Here, we integrated predictive soil mapping paradigm with adaptive depth function fitting, state-of-the-art ensemble machine learning and high-resolution soil-forming environment characterization in a highperformance parallel computing environment to generate 90-m resolution national gridded maps of nine soil properties(pH, organic carbon, nitrogen, phosphorus, potassium, cation exchange capacity, bulk density, coarse fragments, and thickness) at multiple depths across China. This was based on approximately5000 representative soil profiles collected in a recent national soil survey and a suite of detailed covariates to characterize soil-forming environments. The predictive accuracy ranged from very good to moderate(Model Efficiency Coefficients from 0.71 to 0.36) at 0–5 cm. The predictive accuracy for most soil properties declined with depth. Compared with previous soil maps, we achieved significantly more detailed and accurate predictions which could well represent soil variations across the territory and are a significant contribution to the GlobalSoilMap.net project. The relative importance of soil-forming factors in the predictions varied by specific soil property and depth, suggesting the complexity and non-stationarity of comprehensive multi-factor interactions in the process of soil development.展开更多
基金Project supported by the China Postdoctoral Science Foundation,the Youth Foundation of Sichuan University(No.432028)and the National High-Tech Research and Development Program of China(863 Program)(No.2002AA2Z4251).
文摘A new technique of dimension reduction named projection pursuit is applied to model and evaluatewetland soil quality variations in the Sanjiang Plain, Helongjiang Province, China. By adopting the im-proved real-coded accelerating genetic algorithm (RAGA), the projection direction is optimized and multi-dimensional indexes are converted into low-dimensional space. Classification of wetland soils and evaluationof wetland soil quality variations are realized by pursuing optimum projection direction and projection func-tion value. Therefore, by adopting this new method, any possible human interference can be avoided andsound results can be achieved in researching quality changes and classification of wetland soils.
基金supported by the National Natural Science Foundation of China (U1361214)the National Key Research and Development Program of China (2016YFC0501107)
文摘Mining operations can usually lead to environmental deteriorations. Underground mining activities could cause an extensive decrease in groundwater level and thus a dramatic variation in soil moisture content（SMC）. In this study, the spatial and temporal variations of SMC from 2001 to 2015 at two spatial scales（i.e., the Shendong coal mining area and the Daliuta Coal Mine） were analyzed using an improved thermal inertia model with a long-term series of Landsat TM/OLI（TM=Thematic Mapper and OLI=Operational Land Imager） data. Our results show that at large spatial scale（the Shendong coal mining area）, underground mining activities had insignificant negative impacts on SMC and that at small spatial scale（the Daliuta Coal Mine）, underground mining activities had significant negative impacts on SMC. Trend analysis of SMC demonstrated that areas with decreasing trend of SMC were mainly distributed in the mined area, indicating that underground mining is a primary cause for the drying trend in the mining region in this arid environment.
基金supported by the National Natural Science Foundation of China (Nos. 41471178, 41530749, and 41431177)the State Key Laboratory of Soil and Sustainable Agriculture, China (No. Y052010002)+2 种基金the Natural Science Research Program of Jiangsu, China (No. 14KJA170001)the National Key Technology Innovation Project for Water Pollution Control and Remediation, China (No. 2013ZX07103006)the National Basic Research Program (973 Program) of China (No. 2015CB954102)
文摘High-resolution and detailed regional soil spatial distribution information is increasingly needed for ecological modeling and land resource management. For areas with no point data, regional soil mapping includes two steps： soil sampling and soil mapping. Because sampling over a large area is costly, efficient sampling strategies are required. A multi-grade representative sampling strategy, which designs a small number of representative samples with different representative grades to depict soil spatial variations at different scales, could be a potentially efficient sampling strategy for regional soil mapping. Additionally, a suitable soil mapping approach is needed to map regional soil variations based on a small number of samples. In this study, the multi-grade representative sampling strategy was applied and a fuzzy membership-weighted soil mapping approach was developed to map soil sand percentage and soil organic carbon （SOC） at 0-20 and 20-40 cm depths in a study area of 5 900 km2 in Anhui Province of China. First, geographical sub-areas were delineated using a parent lithology data layer. Next, fuzzy c-means clustering was applied to two climate and four terrain variables in each stratum. The clustering results （environmental cluster chains） were used to locate representative samples. Evaluations based on an independent validation sample set showed that the addition of samples with lower representativeness generally led to a decrease of root mean square error （RMSE）. The declining rates of RMSE with the addition of samples slowed down for 20-40 cm depth, but fluctuated for 0-20 cm depth. The predicted SOC maps based on the representative samples exhibited higher accuracy, especially for soil depth 20-40 cm, as compared to those based on legacy soil data. Multi-grade representative sampling could be an effective sampling strategy at a regional scale. This sampling strategy, combined with the fuzzy membership-based mapping approach, could be an optional effective framework for regional soil property mapping. A more detailed and accurate soft parent material map and the addition of environmental variables representing human activities would improve mapping accuracy.
基金This work was supported by the National Natural Science Foundation of China(51879224,51609237)the Key Research and Development Projects of Shaanxi Province,China(2019NY-190).
文摘Plastic mulched ridge-furrow irrigation is a useful method to improve crop productivity and decrease salt accumulation in arid saline areas.However,inappropriate irrigation and fertilizer practices may result in ecological and environmental problems.In order to improve the resource use efficiency in these areas,we investigated the effects of different irrigation amounts(400(I1),300(I2)and 200(I3)mm)and nitrogen application rates(300(F1)and 150(F2)kg N/hm^(2))on water consumption,salt variation and resource use efficiency of spring maize(Zea mays L.)in the Hetao Irrigation District(HID)of Northwest China in 2017 and 2018.Result showed that soil water contents were 0.2%-8.9%and 13.9%-18.1%lower for I2 and I3 than for I1,respectively,but that was slightly higher for F2 than for F1.Soil salt contents were 7.8%-23.5%and 48.5%-48.9%lower for I2 than for I1 and I3,but that was 1.6%-5.5%higher for F1 than for F2.Less salt leaching at the early growth stage(from sowing to six-leaf stage)and higher salt accumulation at the peak growth stage(from six-leaf to tasseling stage and from grain-filling to maturity stage)resulted in a higher soil salt content for I3 than for I1 and I2.Grain yields for I1 and I2 were significantly higher than that for I3 and irrigation water use efficiency for I2 was 14.7%-34.0%higher than that for I1.Compared with F1,F2 increased the partial factor productivity(PFP)of nitrogen fertilizer by more than 80%.PFP was not significantly different between I1F2 and I2F2,but significantly higher than those of other treatments.Considering the goal of saving water and nitrogen resources,and ensuring food security,we recommended the combination of I2F2 to ensure the sustainable development of agriculture in the HID and other similar arid saline areas.
基金supported by the National Natural Science Foundation of China (41471420)the Natural Science Foundation of Shaanxi Province (2016JQ4016)+1 种基金the Fundamental Research Funds for the Central University (GK201603076, GK201601009, GK201701010)the Youth Innovation Team Project in the Tourism and Environment College of Shaanxi Normal University
文摘Anthropogenic activities largely influence the soil quality of agricultural fields and the composition of soil. Samples of typical anthropogenic Loutu soil in the Guanzhong area of the Loess Plateau, Shaanxi Province, China were collected and measured for soil compaction, bulk density, total organic carbon（TOC）, active organic carbon（AOC）, and soil enzyme activities to investigate spatial variations in soil quality. The results indicate that soil compaction and bulk density increased with increasing distance from the farm village, whereas soil TOC, AOC, and soil enzyme activities firstly increased and subsequently decreased with increasing distance from the farm village. All of the tested parameters presented clear concentric distribution. Vertically, soil compaction and bulk density in the topsoil were lower than those in the subsoil, but all other tested parameters in the topsoil were significantly higher than those in the subsoil. In addition, there was a significant positive correlation between organic carbon content and enzyme activities, confirming that the spatial distribution of Loutu soil characteristics has been affected by long-term anthropogenic activities to some extent. The results of this study imply that the use of farmyard manure and appropriate deep plowing are important and effective ways to maintain and improve soil quality.
基金the Key Research and Development Plan of Zhejiang Province(No.2019C02008-03)Natural Science Foundation of Zhejiang Province(LY20C160004).
文摘The impact of land consolidation on the soil microbial PLFA diversity is of great importance for understanding the effective arable land usage,improving agricultural ecological conditions and environment.In this study,we collected the soil samples(0–20 cm)in experimental plots with 0(Z0),1(Z1a)and 4(Z4a)years of land consolidation in the forest station of Ningbo City,Zhejiang Province,southeastern China.The results were analyzed using ANOVA for randomized block design.Compared with control(Z0),the soil pH value under Z1a treatment increased by 14.6%,soil organic carbon(SOC)content decreased by 65.4%,so did the PLFA contents and relative abundance of all the microbial PLFA diversity(P<0.05),respectively.Meanwhile,for the Z1a treatment,the ratio of fungi to bacteria(F/B)significantly decreased by 35.9%(P<0.05),while the ratio of Gram-positive bacteria to Gram-negative bacteria(G+/G−)signific antly increased by 56.1%.This was strongly related to the increased soil pH values and the decrease of SOC.The Shannon index(H)and evenness index(E)of soil microbial PLFA diversity were significantly decreased after land consolidation(P<0.05).Compared to the Z1 treatment,the microbial PLFA diversity was improved slightly.Therefore,the land consolidation could significantly affect the composition of soil microbial PLFA diversity,and decrease the soil ecosystem stability.
基金This study was financially supported by the Special Funding Project for Public Welfare Industries(Agriculture)Scientific Research:Research on Mechanized Cultivation Model in Maize Planting Area of State Farm(201503116-04-04)and conducted in the Conservation Tillage Technology Center of the Heilongjiang Provincial Education Department jointly established by both corporations and universities.
文摘The emergence rate and vitality of maize are directly affected by the sowing depth,and the uniformity of this depth is an important performance indicator of a planter,while the effective soil surface height information acquisition is the prerequisite for ensuring the accuracy of sowing depth control.The soil surface height variation acquisition system of a precision corn planter often produces profiling errors when performing active profiling due to interference from ground debris.In this study,a multipoint soil surface height variation information acquisition system was investigated,which consists of a ranging sensor group and a microcontroller unit(MCU)using a data comparison and screening method.The structure and specifications of the ranging sensors were determined according to the soil surface height variation and debris size,and a nonessential profiling control program was developed.Performed tests on the information acquisition system indicated that the measurement accuracy of the system was 3 mm,and when advancing at a speed of 8 km/h,the accuracy of the profiling decision and the system stability were 97.1%and 94.1%,respectively,indicating that the system was capable of nonessential profile control.The designed ranging system could provide a reference for the design of a ground information acquisition system of precision planters with an active profiling mechanism.
基金the National Key Basic Research Special Foundation of China(2008FY110600 and 2014FY110200)the National Natural Science Foundation of China(41930754 and42071072)+1 种基金the 2nd Comprehensive Scientific Survey of the Qinghai-Tibet Plateau(2019QZKK0306)the Project of “OneThree-Five”Strategic Planning&Frontier Sciences of the Institute of Soil Science,Chinese Academy of Sciences(ISSASIP1622)。
文摘Soil spatial information has traditionally been presented as polygon maps at coarse scales. Solving global and local issues, including food security, water regulation, land degradation, and climate change requires higher quality, more consistent and detailed soil information. Accurate prediction of soil variation over large and complex areas with limited samples remains a challenge, which is especially significant for China due to its vast land area which contains the most diverse soil landscapes in the world. Here, we integrated predictive soil mapping paradigm with adaptive depth function fitting, state-of-the-art ensemble machine learning and high-resolution soil-forming environment characterization in a highperformance parallel computing environment to generate 90-m resolution national gridded maps of nine soil properties(pH, organic carbon, nitrogen, phosphorus, potassium, cation exchange capacity, bulk density, coarse fragments, and thickness) at multiple depths across China. This was based on approximately5000 representative soil profiles collected in a recent national soil survey and a suite of detailed covariates to characterize soil-forming environments. The predictive accuracy ranged from very good to moderate(Model Efficiency Coefficients from 0.71 to 0.36) at 0–5 cm. The predictive accuracy for most soil properties declined with depth. Compared with previous soil maps, we achieved significantly more detailed and accurate predictions which could well represent soil variations across the territory and are a significant contribution to the GlobalSoilMap.net project. The relative importance of soil-forming factors in the predictions varied by specific soil property and depth, suggesting the complexity and non-stationarity of comprehensive multi-factor interactions in the process of soil development.
