Soil Organic Carbon Content and Distribution in a Small Landscape of Dongguan, South China

Global warming has become an increasing concern, and using soil as a carbon sink to sequester carbon dioxide has attracted much attention in recent years. In this study, soil organic carbon (SOC) content and organic carbon density were estimated based on a soil survey of a small landscape in Dongguan, South China, with spatial heterogeneity of SOC distribution and the impacts of land-use patterns on soil organic carbon content assessed. Field sampling was carried out based on a 150 m×150 m grid system overlaid on the topographic map of the study area and samples were collected in three 20-cm layers to a depth of 60 cm. Spatial variability in the distribution of SOC was assessed using the Kruskal-Wallis test. Results showed that SOC in the topsoil layer (0-20 cm) was not much higher or even lower in some sites than the underlying layers, and except for the two sites covered with natural woodland, it did not exhibit a pronounced vertical gradient. The difference in both horizontal and vertical distribution of SOC was not statistically significant. However, in the topsoil layer among land-use/land-cover patterns, significant differences (P≤0.05) in SOC distribution existed, indicating that management practices had great impact on SOC content. SOC storage in the study area to a depth of 20, 40, and 60 cm was estimated as 2.13×106 kg, 3.46×106 kg, and 4.61×106 kg, respectively.

Elevation and Land Use Types Have Significant Impacts on Spatial Variability of Soil Organic Matter Content in Hani Terraced Field of Yuanyang County,China

Soil organic matter （SOM） content is one of the most important indicators of the sustainability of soil. To maintain sustainable soil utilization and management in fragile Hani terraced field, it is meaningful to investigate the effects of topography and land use type on SOM content. Descriptive statistics and geostatistics were used to analyze the data and the kriging method was applied to map the spatial patterns of SOM content. The results showed that the mean SOM content was 32.76 g/kg, with a variation coefficient of 40%. The SOM content was affected by elevation and land use type. As the increase of elevation, the SOM content in Hani terraced field also increased obviously. The SOM content in tea garden, which is almost at high elevation, was the highest in all six land use types, and the SOM content decreased in a following sequence： tea garden 〉 paddy field 〉 corn field 〉 banana garden 〉 cassava field 〉 sugarcane field. In addition, at the same elevation, the paddy field had the highest SOM content compared with other land use types. All these results demonstrate that paddy field is the most efficient and suitable land use type for SOM conservation at high, middle or low elevations in the fragile Hani terraced field. In order to protect soil quality and maintain the sustainable agricultural development, it is necessary to maintain or even to enlarge the area of paddy field in Yuanyang county, Yunnan Province, China.

Temporal variation in biodeposit organic content and sinking velocity in long-line shellfish culture

We measured the organic content and sinking velocities of biodeposits from two scallop species(Chlamys farreri,Patinopecten yessoensis) and abalone(Haliotis discus hannai) that were cultured on suspended long-lines.Measurements were conducted every two months from April 2010 to February 2011.The shellfish were divided into three size groups(small,middle,and big sizes).At each sample point,we assessedbiodeposit organic content,average sinking velocity,the frequency distribution of sinkingvelocities,and the correlation between organic content and sinking velocity.The organic content of biodeposits varied significantly among months(P<0.05) and the pattern of change varied among species.Sinking velocities varied significantly,ranging from <0.5 cm/s to >1.9 cm/s.The sinking velocities of biodeposits from C.farreri and P.yessoensis were 0.5-1.5 cm/s and from H.discus hannai were <0.7 cm/s.The organic content was significantly negatively correlated to the sinking velocity of biodeposits in C.farreri(P<0.001) and P.yessoensis(P<0.05).

Identifying the influence of urbanization on soil organic matter content and p H from soil magnetic characteristics

Soil magnetic characteristics are correlated with soil p H and organic matter content. Analyzing soil magnetic characteristics, organic matter content and p H can indirectly evaluate soil pollution caused by human activities. This study analyzed the soil magnetic characteristics, organic matter content and p H in surface soil samples from different land use types in Shihezi city, a newly and rapidly developing oasis city in Xinjiang of China. The aims of this study were to explore the possible relationships among the soil magnetic parameters and thereby improve the understanding of influence of urbanization on soil properties. Eighty surface soil samples at the depth of 0–10 cm were collected from 29 July to 4 August 2013. The results showed that the magnetic minerals in surface soil were dominated by ferromagnetic minerals. Spatially, the magnetic susceptibility（χLF）, anhysteretic remanent magnetization susceptibility（χARM）, saturation isothermal remanent magnetization（SIRM） and ＂soft＂ isothermal remanent magnetization（SOFT） were found to be most dominant in the new northern urban area B（N-B）, followed by built-up areas（U）, suburban agricultural land（F）, and then the new northern urban area A（N-A）. The values of χLF, χARM, SIRM and SOFT were higher in the areas with high intensities of human activities and around the main roads. Meanwhile, the property ＂hard＂ isothermal remanent magnetization（HIRM） followed the order of U〉N-B〉F〉N-A. Built-up areas had an average p H value of 7.93, which was much higher than that in the new northern urban areas as well as in suburban agricultural land, due to the increased urban pollutant emissions. The average value of soil organic matter content in the whole study area was 34.69 g/kg, and the values in the new northern urban areas were much higher than those in the suburban agricultural land and built-up areas. For suburban agricultural land, soil organic matter content was significantly negatively correlated with χLF, and had no correlation with other magnetic parameters, since the soil was frequently ploughed. In the new northern urban areas（N-A and N-B）, there were significant positive correlations of soil organic matter contents with χARM, SIRM, SOFT and HIRM, because natural grasslands were not frequently turned over. For the built-up areas, soil organic matter contents were significantly positively correlated with χLF, χARM, SIRM and SOFT, but not significantly correlated with frequency-dependent susceptibility（χFD, expressed as a percentage） and HIRM, because the soil was not frequently turned over or influenced by human activities. The results showed that soil magnetic characteristics are related to the soil turnover time.

Total organic carbon content logging prediction based on machine learning:A brief review

The total organic carbon content usually determines the hydrocarbon generation potential of a formation.A higher total organic carbon content often corresponds to a greater possibility of generating large amounts of oil or gas.Hence,accurately calculating the total organic carbon content in a formation is very important.Present research is focused on precisely calculating the total organic carbon content based on machine learning.At present,many machine learning methods,including backpropagation neural networks,support vector regression,random forests,extreme learning machines,and deep learning,are employed to evaluate the total organic carbon content.However,the principles and perspectives of various machine learning algorithms are quite different.This paper reviews the application of various machine learning algorithms to deal with total organic carbon content evaluation problems.Of various machine learning algorithms used for TOC content predication,two algorithms,the backpropagation neural network and support vector regression are the most commonly used,and the backpropagation neural network is sometimes combined with many other algorithms to achieve better results.Additionally,combining multiple algorithms or using deep learning to increase the number of network layers can further improve the total organic carbon content prediction.The prediction by backpropagation neural network may be better than that by support vector regression;nevertheless,using any type of machine learning algorithm improves the total organic carbon content prediction in a given research block.According to some published literature,the determination coefficient(R^(2))can be increased by up to 0.46 after using machine learning.Deep learning algorithms may be the next breakthrough direction that can significantly improve the prediction of the total organic carbon content.Evaluating the total organic carbon content based on machine learning is of great significance.

Influence of soil organic matter contents on soil water characteristics of forests on east slope of Gongga Mountain

By testing soil organic matter （SOM） contents, soil water contents （SWC） within low suctions, and saturated infiltration rates of samples taken from east slope of Gongga Mountain of China, the enhancive effects of SOM contents on SWC within low suctions and saturated infiltration rates were quantified. The simulated functions might be applied on regional experience forest-hydrology model. The improving function of protecting forest floor and increasing SOM contents on forest ecosystem hydrological effects were also embodied.

Application of a Method for Calculating the Organic Carbon Content by Well Logs to Faulted Basins

The source rock model used in this project was developed by French Petroleum Research Institute. The total organic carbon content was estimated primarily and directly by using continuous conventional logging curves (such as sonic and resistivity curves), which are calibrated through the laboratory analysis data of organic carbon of cores, cuttings or sidewall cores. Regional evaluations have been carried out in downwarping basins abroad. The Haila′er Basin is a faulted basin and the evaluation of such a basin is a new subject. On the basis of a regional evaluation method for the downwarping basins, a new method suitable to faulted basins was developed. The effect is satisfactory when this new method is applied to the Wu′erxun Sag and the Bei′er Sag.

Factors Acquisition and Content Estimation of Farmland Soil Organic Carbon Based upon Internet of Things

Aiming at the shortage of sufficient continuous parameters for using models to estimate farmland soil organic carbon(SOC) content, an acquisition method of factors influencing farmland SOC and an estimation method of farmland SOC content with Internet of Things(IOT) are proposed in this paper. The IOT sensing device and transmission network were established in a wheat demonstration base in Yanzhou Distict of Jining City, Shandong Province, China to acquire data in real time. Using real-time data and statistics data, the dynamic changes of SOC content between October 2012 and June 2015 was simulated in the experimental area with SOC dynamic simulation model. In order to verify the estimation results, potassium dichromate external heating method was applied for measuring the SOC content. The results show that: 1) The estimated value matches the measured value in the lab very well. So the method is feasible in this paper. 2) There is a clear dynamic variation in the SOC content at 0.2 m soil depth in different growing periods of wheat. The content reached the highest level during the sowing period, and is lowest in the flowering period. 3) The SOC content at 0.2 m soil depth varies in accordance with the amount of returned straw. The larger the amount of returned straw is, the higher the SOC content.

Study of elastic-plastic damage model of cement consolidated soil with high organic content

On the basis of elastic-plastic damage model of cement consolidated soil,the authors took organic contents into reasonable damage variable evolution equation in order to seek relation between the organic contents and parameters in the equation,and established the elastic-plastic damage model of cement consolidated soil considering organic contents.The results show that the parameters change correspondingly with difference of the organic contents.The higher the organic contents are,the less the valves of the parameters such as elastic modulus(E),material parameters(K,n) and damage evolution parameter(ε) become,but the larger strain damage threshold value(εd) of the sample is.Meanwhile,the calculation results obtained from established model are compared with the test data in the condition of common indoors test,which is testified with reliability.

The Empirical Research of Native Thinking in the Process of English Composition

The method of questionnaire is employed to investigate the impact of Chinese thinking in the writing processes of 80 college English majors.It reveals that the English writing process is a bilingual event(namely,English writers have both Chinese and English at their disposal when they are composing in English).And no matter whether the English proficiency of the learners is high or low,the learners have a great dependence on Chinese thinking in the process of English writing.In the categories of task reacting and content organizing,there is no great difference between the high and low English proficiency students.But in the category of linguistic form,the influence of Chinese thinking on the low level students is far greater than the high level students.

Characterization of the Songhua River sediments and evaluation of their adsorption behavior for nitrobenzene

The explosion at a plant of the Jilin Petrochemical Corporation on 13 November,2005,and the spill of an estimated 100 t of toxic substances (nitrobenzene as the main component) into the Songhua River received worldwide attention.This study has focused on the adsorption behavior of nitrobenzene that spilled onto sediments along the Songhua River,which was one of the efforts to evaluate the fate of nitrobenzene after the spillage event.The organic carbon contents of these sediments along the Songhua River var...

Impact of Fenton and ozone on oxidation of wastewater containing nitroaromatic compounds

Fenton and ozone treatment was investigated at laboratory scale for the degradation of aqueous solutions of nitrobenzene （NB）. Effects of reactants concentration （O3, H2O2, and Fe（Ⅱ））, temperature, and pH on NB degradation were monitored. Reaction kinetic of these processes was also assessed. A rapid reaction took place for Fenton process at higher initial concentration of H2O2, higher temperatures, and more acidic conditions （pH 3）. Similarly, ozonation reaction exhibited rapid rates for higher ozone dose, higher temperatures, and more basic conditions （pH 11）. Complete NB degradation in 65 min was achieved using Fenton process. The conditions of complete elimination of 100 mg/L of initial NB concentration, were 250 mg/L of H202 concentration, pH 3, and 10 mg/L of Fe（Ⅱ） concentration. Under these conditions, 55% organic carbon elimination was achieved. Total organic carbon mineralization was attained in 240 rain reaction time by Fenton process with 900 mg/L of H202 concentration, and 30 mg/L of Fe（Ⅱ） concentration. Fenton reaction showed a pseudo-first order kinetic; the reaction rate constant was ranged from 0.0226 to 0.0658 min^-1. Complete NB degradation was also achieved for an ozone dose of the order of 2.5 g/L. The ozonation was studied at different ozone doses, different initial pH （7-11） and at different temperatures （15-35℃）. NB ozonation kinetic was represented by a bi-molecular kinetic model which was reduced to pseudo-first order kinetic. The pseudo-first order reaction rate constant was determined to increase at 20℃ from 0.004 to 0.020 min^-1 as the used ozone increased from 0.4 to 1.9 g/L.

Coupled Eulerian-Lagrangian simulation of a modified direct shearapparatus for the measurement of residual shear strengths

The simulation of large-strain geotechnical laboratory tests with conventional Lagrangian finite element method(FEM)techniques is often problematic due to excessive mesh distortion.The multiple reversal direct shear(MRDS)test can be used to measure the residual shear strength of soils in a laboratory setting.However,modelling and simulation generally require advanced numerical methods to accommodate the large shear strains concentrated in the shear plane.In reality,when the standard direct shear(DS)apparatus is used,the MRDS method is prone to two major sources of measurement error:load cap tilting and specimen loss.These sources of error make it difficult or even impossible to correctly determine the residual shear strength.This paper presents a modified DS apparatus and multi-reversal multi-stage test method,simulated using the coupled Eulerian-Lagrangian(CEL)method in a finite element environment.The method was successful in evaluating equipment and preventing both load cap tilting and specimen loss,while modelling large-deformation behaviour that is not readily simulated with the conventional FEM or arbitrary Lagrangian-Eulerian(ALE)analysis.Thereafter,a modified DS apparatus was created for the purpose of analysing mixtures of organic materials found in an Australian clay.The results obtained from the modified DS CEL model in combination with laboratory tests show a great improvement in the measured residual shear strength profiles compared to those from the standard apparatus.The modified DS setup ensures that accurate material residual shear strengths are calculated,a factor that is vital to ensure appropriate soil behaviour is simulated for numerical analyses of large-scale geotechnical projects.

How does organic matter affect the physical and mechanical properties of forest soil?

Determining the physical and mechanical properties of soil and its behavior for engineering projects is essential for road construction operations. One of the most important principles in forest road construction, which is usually neglected, is to avoid mixing organic matter with road materials during excavation and embankment construction. The current study aimed to assess the influence of organic matter on the physical properties and mechanical behaviors of forest soil and to analyze the relation between the amount of organic matter and the behavior of forest soil as road material. A typical soil sample from the study area was collected beside a newly constructed roadbed. The soil was mixed with different percentages of organic matter（control treatment, 5, 10, and 15% by mass） and different tests including Atterberg limits, standard compaction, and California bearing ratio（CBR） tests were conducted on these different soil mixtures. The results showed that soil plasticity increased linearly with increasing organic matter.Increasing the organic matter from 0%（control） to 15%resulted in an increase of 11.64% of the plastic limit and 15.22% of the liquid limit after drying at 110 ℃. Also,increasing the organic matter content reduced the soil maximum dry density and increased the optimum moisture content. Increasing the organic matter from 0 to 15% resulted in an increase of 11.0% of the optimum moisture content and a decrease of 0.29 g/cm;of the maximum dry density. Organic matter decreased the CBR, which is used as the index of road strength. Adding 15% organic matter to the soil resulted in a decrease of the CBR from 15.72 to 4.75%. There was a significant difference between the two drying temperatures（60 and 110 ℃） for the same organic matter mixtures with lower water content values after drying at 60 ℃. The results revealed the adverse influence of organic matter on soil engineering properties and showed the importance of organic matter removal before excavation and fill construction.

Effects of Returning Methods on Wheat Stem Rot and Yield

[Objectives]This study was conducted to improve the quality of straw returning to the field,enhance wheat disease resistance and ensure high and stable yield of wheat.[Methods]The effects of four returning modes on wheat stem rot and yield were studied by observation and experiments.[Results]The incidence rate and disease index of stem rot and white head rate of wheat were significantly reduced and the yield was significantly increased by adopting the method of straw returning to the field with the separation of"returning and seeding".The incidence rate and disease index of stem rot and white head rate of wheat were higher than those of the CK and the yield was significantly reduced when adopting the straw returning method of direct sowing.Treatment T_(1)(after maize was harvested,fertilizers,a nutrient-loaded microbial agent and a soil conditioner were evenly spread on the surface of straw,which was then returned to the field using a straw returning machine twice,and then ploughing,soil preparation and wheat sowing were carried out)showed an incidence rate of wheat crown rot 54.8%lower than that of the CK and a white head rate 87.5%lower than that of the CK,and the yield was 2305 kg/hm^(2) higher than that of the CK.[Conclusions]Straw returning can increase soil organic matter content,reduce soil bulk density,enhance soil respiration,and improve wheat disease resistance and yield.

Effects of Method for Returning Straw to Field on Soil Properties,Straw Decomposition and Nutrient Release

[Objectives]To alleviate the influence of meteorological conditions on soil environment(temperature and water content)and maintain high and stable grain yield.[Methods]Taking Sunzhen Experimental Station of Weinan Academy of Agricultural Sciences as the experimental base,the effects of returning double-crop wheat and corn straw to field(Twm),returning single-crop corn straw to field(Tm),returning single-crop wheat straw to field(Tw)on soil temperature,water content,straw decomposition rate and nutrient release,soil organic matter and bulk density were studied systematically.[Results]Twm treatment could effectively alleviate the effects of meteorological conditions on soil temperature and water content.The decomposition rate of straw treated with Twm was 4.7%higher than that of Tm treatment,3.8%higher than that of Tw treatment,10.5%higher than that of Tm treatment,and the decomposition rate of straw showed a trend of"first fast,then slow and then fast".The release of nitrogen from straw was basically similar to that of straw decay,and the release of potassium and phosphorus increased at first and then remained basically unchanged.The release rate of potassium was the highest,followed by phosphorus and nitrogen.The content of soil organic matter in Twm treatment increased by 11.67%annually,an annual average of 0.998 g/kg.The soil bulk density of Twm treatment decreased by 0.058 g/cm^(3) annually,an annual average of 4.29%.The fundamental reason is that Twm treatment provides conditions(temperature,water content,nutrition)for microbial growth,reproduction,enzyme production and biochemical reaction,and increases the exchange capacity of soil and external water,heat,gas and fertilizer.[Conclusions]It is expected is to help people change their understanding of returning straw to field from"quick harvest"to"fertilizer transformation".

Estimation of soil organic matter in the Ogan-Kuqa River Oasis, Northwest China, based on visible and near-infrared spectroscopy and machine learning

Visible and near-infrared(vis-NIR)spectroscopy technique allows for fast and efficient determination of soil organic matter(SOM).However,a prior requirement for the vis-NIR spectroscopy technique to predict SOM is the effective removal of redundant information.Therefore,this study aims to select three wavelength selection strategies for obtaining the spectral response characteristics of SOM.The SOM content and spectral information of 110 soil samples from the Ogan-Kuqa River Oasis were measured under laboratory conditions in July 2017.Pearson correlation analysis was introduced to preselect spectral wavelengths from the preprocessed spectra that passed the 0.01 level significance test.The successive projection algorithm(SPA),competitive adaptive reweighted sampling(CARS),and Boruta algorithm were used to detect the optimal variables from the preselected wavelengths.Finally,partial least squares regression(PLSR)and random forest(RF)models combined with the optimal wavelengths were applied to develop a quantitative estimation model of the SOM content.The results demonstrate that the optimal variables selected were mainly located near the range of spectral absorption features(i.e.,1400.0,1900.0,and 2200.0 nm),and the CARS and Boruta algorithm also selected a few visible wavelengths located in the range of 480.0–510.0 nm.Both models can achieve a more satisfactory prediction of the SOM content,and the RF model had better accuracy than the PLSR model.The SOM content prediction model established by Boruta algorithm combined with the RF model performed best with 23 variables and the model achieved the coefficient of determination(R2)of 0.78 and the residual prediction deviation(RPD)of 2.38.The Boruta algorithm effectively removed redundant information and optimized the optimal wavelengths to improve the prediction accuracy of the estimated SOM content.Therefore,combining vis-NIR spectroscopy with machine learning to estimate SOM content is an important method to improve the accuracy of SOM prediction in arid land.

A brief introduction to recent applications of several sediment-analysis techniques in palaeolimnological studies-dry bulk density and water content, mineral magnetism, carbonate content, and content of total organic carbon,nitrogen content and carbon/nitrogen ratio

Determination of dry bulk density and water content measurement of magnetic susceptibility (x) and saturation isothermal remanent magnetization (SIRM), determination of carbonate content, and determination of total organic carbon (TOC) content nitrogen content (N%) and carbon/nitrogen (C/N) ratio are some of the techniques which have been widely applied to lacustrine-sediment analyses. The techniques,complemented by others, are usually useful for revealing characteristics of lacustrine-sediments and thus for postulating hydrological regimes in the lake and environmental conditions and human activity around it in palaeolimnological studies. A very brief review is presented on recent applications of these techniques in palaeolimnological work with English literatures published mainly since 1985 and focus given on interpretations of results of these analyses related to palaeoenvironmental reconstructions. Low dry bulk density and high water content often imply relatively warm and wet conditions. High X and SIRM are usually resulted from reduced dilutions in the lake and intensified erosions on its catchment. both of which can be in turn attributed to environmental changes. While variations in patterns of X and SIRM may give further insight on mineral magnetism and thus implications on environmental conditions. Increased carbonate content seems likely to associate to warm and dry conditions.Increased TOC content is virtually used as one of indicators of warm and wet conditions and variations in C/N ratio may hint variations in relative contributions of different sources, aquatic and terrestrial, to the total organic matter in lake sediments and hence to lake-level fluctuations and climate changes.

Comparison of Acidity Parameters for Soils under Perennial and Annual Pastures in Victoria

There are about 5 million ha of strongly acid soils (pH < 4.8 in 0.01 mol·L -1 CaCl 2 ) in Victoria and about 11 million ha of mildly acid soils (pH 4.8～5.5) that are considered susceptible to further acidification under current agricultural use. However, there appear to be differences in the rate of acidification, as measured by soil pH change, between soils under perennial pastures in the higher rainfall areas of southern Victoria and soils under annual pastures in the sheep-wheat areas of the north-east. Measurements made on representative soils from both regions showed that the southern soils generally had a higher pH buffer capacity, which was primarily determined by the organic carbon content. There was a consistent relationship between the short-term buffer capacity (measured by titration) and the long-term buffer capacity (measured by incubation), irrespective of the origin of the soils. Exchangeable Al, measured in 0.01 mol·L -1 CaCl 2 , was strongly negatively correlated with pH and the relationship for all soils suggested that Al was adsorbed as a cation with an average charge of 1.2