Changes in aggregate-associated organic carbon and nitrogen after 27 years of fertilization in a dryland alfalfa grassland on the Loess Plateau of China

Changes in the distribution of soil aggregate sizes and concentrations of aggregate-associated organic carbon （OC） and nitrogen （N） in response to the fertilization of grasslands are not well understood. Understanding these changes is essential to the sustainable development of artificial grasslands. For understanding these changes, we collected soil samples at 0-20 and 20-40 cm depths from a semi-arid artificial alfalfa grassland after 27 years of applications of phosphorus （P） and nitrogen＋phosphorus＋manure （NPM） fertilizers on the Loess Pla- teau of China. The distribution of aggregate sizes and the concentrations and stocks of OC and N in total soils were determined. The results showed that NPM treatment significantly increased the proportions of 〉2.0 mm and 2.0-0.25 mm size fractions, the mean geometric diameter （MGD） and the mean weight diameter （MWD） in the 0-20 cm layer. Phosphorous fertilizer significantly increased the proportion of 〉2.0 mm size fractions, the MGD and the MWD in the 0-20 cm layer. Long-term application of fertilization （P and NPM） resulted in the accumulation of OC and N in soil aggregates. The largest changes in aggregate-associated OC and N in the 0-20 cm layer were found at the NPM treatment, whereas the largest changes in the 20-40 cm layer were found at the P treatment. The results suggest that long-term fertilization in the grassland leads to the accumulation of OC and N in the coarse size fractions and the redistribution of OC and N from fine size fractions to coarse size fractions.

Effects of desert plant communities on soil enzyme activities and soil organic carbon in the proluvial fan in the eastern foothills of the Helan Mountain in Ningxia,China

It is of great significance to study the effects of desert plants on soil enzyme activities and soil organic carbon(SOC)for maintaining the stability of the desert ecosystem.In this study,we studied the responses of soil enzyme activities and SOC fractions(particulate organic carbon(POC)and mineral-associated organic carbon(MAOC))to five typical desert plant communities(Convolvulus tragacanthoides,Ephedra rhytidosperma,Stipa breviflora,Stipa tianschanica var.gobica,and Salsola laricifolia communities)in the proluvial fan in the eastern foothills of the Helan Mountain in Ningxia Hui Autonomous Region,China.We recorded the plant community information mainly including the plant coverage and herb and shrub species,and obtained the aboveground biomass and plant species diversity through sample surveys in late July 2023.Soil samples were also collected at depths of 0–10 cm(topsoil)and 10–20 cm(subsoil)to determine the soil physicochemical properties and enzyme activities.The results showed that the plant coverage and aboveground biomass of S.laricifolia community were significantly higher than those of C.tragacanthoides,S.breviflora,and S.tianschanica var.gobica communities(P<0.05).Soil enzyme activities varied among different plant communities.In the topsoil,the enzyme activities of alkaline phosphatase(ALP)andβ-1,4-glucosidas(βG)were significantly higher in E.rhytidosperma and S.tianschanica var.gobica communities than in other plant communities(P<0.05).The topsoil had higher POC and MAOC contents than the subsoil.Specifically,the content of POC in the topsoil was 18.17%–42.73%higher than that in the subsoil.The structural equation model(SEM)indicated that plant species diversity,soil pH,and soil water content(SWC)were the main factors influencing POC and MAOC.The soil pH inhibited the formation of POC and promoted the formation of MAOC.Conversely,SWC stimulated POC production and hindered MAOC formation.Our study aimed to gain insight into the effects of desert plant communities on soil enzyme activities and SOC fractions,as well as the drivers of SOC fractions in the proluvial fan in the eastern foothills of the Helan Mountain and other desert ecosystems.

Can soil organic carbon sequestration and the carbon management index be improved by changing the film mulching methods in the semiarid region?

Plastic film mulching has been widely used to increase maize yield in the semiarid area of China.However, whether long-term plastic film mulching is conducive to agricultural sustainability in this region remains controversial.A field experiment was initiated in 2013 with five different film mulching methods:(i) control method, flat planting without mulching (CK),(ii) flat planting with half film mulching (P),(iii) film mulching on ridges and planting in narrow furrows(S),(iv) full film mulching on double ridges (D), and (v) film mulching on ridges and planting in wide furrows (R).The effects on soil organic carbon (SOC) content, storage, and fractions, and on the carbon management index (CMI)were evaluated after nine consecutive years of plastic film mulching.The results showed that long-term plastic film mulching generally maintained the initial SOC level.Compared with no mulching, plastic film mulching increased the average crop yield, biomass yield, and root biomass by 48.38, 35.06, and 37.32%, respectively, which led to the improvement of SOC sequestration.Specifically, plastic film mulching significantly improved CMI, and increased the SOC content by 13.59%, SOC storage by 7.47%and easily oxidizable organic carbon (EOC) by 13.78%on average,but it reduced the other labile fractions.SOC sequestration and CMI were improved by refining the plastic film mulching methods.The S treatment had the best effect among the four mulching methods, so it can be used as a reasonable film mulching method for sustainable agricultural development in the semiarid area.

A review of physicochemical properties of dissolved organic carbon and its impact over mountain glaciers

Investigating the characteristics and transformation of water-soluble carbonaceous matter in the cryosphere regions is important for understanding biogeochemical process in the earth system.Water-soluble carbonaceous matter is a heterogeneous mixture of organic compounds that is soluble in aquatic environments.Despite its importance,we still lack systematic understanding for dissolved organic carbon(DOC)in several aspects including exact chemical composition and physical interactions with microorganisms,glacier meltwater.This review presents the chemical composition and physical properties of glacier DOC deposited through anthropogenic emission,terrestrial,and biogenic sources.We present the molecular composition of DOC and its effect over snow albedo and associated radiative forcings.Results indicate that DOC in snow/ice is made up of aromatic protein-like species,fulvic acid-like materials,and humic acid-like materials.Light-absorbing impurities in surface snow and glacier ice cause considerable albedo reduction and the associated radiative forcing is definitely positive.Water-soluble carbonaceous matter dominated the carbon transport in the high-altitude glacial area.Owing to prevailing global warming and projected increase in carbon emission,the glacial DOC is expected to release,which will have strong underlying impacts on cryosphere ecosystem.The results of this work have profound implications for better understanding the carbon cycle in high altitude cryosphere regions.A new compilation of globally distributed work is required,including large-scale measurements of glacial DOC over high-altitude cryosphere regions,to overcome and address the scientific challenges to constrain climate impacts of light-absorbing impurities related processes in Earth system and climate models.

Key Physical Factors Affecting Spatial-temporal Variation of Labile Organic Carbon Fractions by Biochar Driven in Mollisols Region of Northeast China

Biochar is widely used to improve soil physical properties and carbon sequestration. However, few studies focuse on the impact of maize stalk biochar on labile organic carbon(LOC) pool and the relationship between physical properties and LOC fractions. A field positioning experiment was performed in Mollisols region of Northeast China to evaluate the influence of maize stalk biochar on the spatial distribution and temporal changes of physical properties and LOC fractions. Maize stalk biochar treatments included C1(1.5 kg·hm^(-2)), C2(3 kg·hm^(-2)), C3(15 kg·hm^(-2)), C4(30 kg·hm^(-2)), and CK(0). The results showed that maize stalk biochar increased soil water contents(SWC) and soil porosity(SP), but reduced bulk density(BD). Maize stalk biochar reduced dissolved organic carbon(DOC) contents in the 0-20 cm soil layer, ranging from 0.25 g·kg^(-1) to 0.31 g·kg^(-1) in harvest period, while increased in the 20-40 cm soil layer. In addition, the application of biochar had a significant impact on the spatial distribution and temporal change of SWC, BD, SP, DOC, hot-water extractable carbon(HWC), acid hydrolyzed organic carbon(AHC Ⅰ, Ⅱ), and readily oxidized organic carbon(ROC). High amounts of maize stalk biochar up-regulated the contents of soil organic carbon SOC, HWC, AHC Ⅰ, AHC Ⅱ, and ROC. In addition, SWC and SP were the key physical factors to affect LOC fractions. In conclusions, maize stalk biochar could improve physical properties, and then influence LOC fractions, and maize stalk biochar could be used as an organic amendment for restoring degraded soils governed by their rates of addition.

Fertilization and Soil Ploughing Practices under Changing Physical Environment Lead to Soil Organic Carbon Dynamics under Conservation Agriculture in Rice-Wheat Cropping System: A Scoping Review

Ploughing and fertilization practices in rice-wheat system have deteriorated the soil carbon (C) pools. Conservation agriculture (CA) based management approaches have proven to enhance C sequestration and reverse the loss of soil-organic-carbon (SOC), which further enhances soil fertility. Different fractions of SOC pools react to the alterations in management practices and indicate changes in SOC dynamics as compared to total C in the soil. Higher SOC levels in soil have been observed in case of reduced/no-till (NT) practices than conventional tillage (CT). However, between CT and zero tillage/NT, total SOC stocks diminished with an increase in soil depth, which demonstrated that the benefits of SOC are more pronounced in the topsoil under NT. Soil aggregation provides physical protection to C associated with different-sized particles, thus, the improvement in soil aggregation through CA is an effective way to mitigate soil C loss. Along with less soil disturbance, residual management, suitable crop rotation, rational application of manures and fertilizers, and integrated nutrient management have been found to be effective in not only improving soil C stock but also enhancing the soil health and productivity. Thus, CA can be considered as a potential method in the build-up of SOC of soil in rice-wheat system.

Persistence of fertilization effects on soil organic carbon in degraded alpine wetlands in the Yellow River source region

In the restoration of degraded wetlands,fertilization can improve the vegetation-soil-microorganisms complex,thereby affecting the organic carbon content.However,it is currently unclear whether these effects are sustainable.This study employed Biolog-Eco surveys to investigate the changes in vegetation characteristics,soil physicochemical properties,and soil microbial functional diversity in degraded alpine wetlands of the source region of the Yellow River at 3 and 15 months after the application of nitrogen,phosphorus,and organic mixed fertilizer.The following results were obtained:The addition of nitrogen fertilizer and organic compost significantly affects the soil organic carbon content in degraded wetlands.Three months after fertilization,nitrogen addition increases soil organic carbon in both lightly and severely degraded wetlands,whereas after 15 months,organic compost enhanced the soil organic carbon level in severely degraded wetlands.Structural equation modeling indicates that fertilization decreases the soil pH and directly or indirectly influences the soil organic carbon levels through variations in the soil water content and the aboveground biomass of vegetation.Three months after fertilization,nitrogen fertilizer showed a direct positive effect on soil organic carbon.However,organic mixed fertilizer indirectly reduced soil organic carbon by increasing biomass and decreasing soil moisture.After 15 months,none of the fertilizers significantly affected the soil organic carbon level.In summary,it can be inferred that the addition of nitrogen fertilizer lacks sustainability in positively influencing the organic carbon content.

National Soil Organic Carbon Stocks Inventories under Different Mangrove Forest Types in Gabon

Gabonese’s estuary is an important coastal mangrove setting and soil plays a key role in mangrove carbon storage in mangrove forests. However, the spatial variation in soil organic carbon (SOC) storage remain unclear. To address this gap, determining the SOC spatial variation in Gabonese’s estuarine is essential for better understanding the global carbon cycle. The present study compared soil organic carbon between northern and southern sites in different mangrove forest, Rhizophora racemosa and Avicennia germinans. The results showed that the mean SOC stocks at 1 m depth were 256.28 ± 127.29 MgC ha−1. Among the different regions, SOC in northern zone was significantly (p p < 0.001). The deeper layers contained higher SOC stocks (254.62 ± 128.09 MgC ha−1) than upper layers (55.42 ± 25.37 MgC ha−1). The study highlights that low deforestation rate have led to less CO2 (705.3 Mg CO2e ha−1 - 922.62 Mg CO2e ha−1) emissions than most sediment carbon-rich mangroves in the world. These results highlight the influence of soil texture and mangrove forest types on the mangrove SOC stocks. The first national comparison of soil organic carbon stocks between mangroves and upland tropical forests indicated SOC stocks were two times more in mangroves soils (51.21 ± 45.00 MgC ha−1) than primary (20.33 ± 12.7 MgC ha−1), savanna and cropland (21.71 ± 15.10 MgC ha−1). We find that mangroves in this study emit lower dioxide-carbon equivalent emissions. This study highlights the importance of national inventories of soil organic carbon and can be used as a baseline on the role of mangroves in carbon sequestration and climate change mitigation but the variation in SOC stocks indicates the need for further national data.

Carbon sequestration rate,nitrogen use efficiency and rice yield responses to long-term substitution of chemical fertilizer by organic manure in a rice–rice cropping system

Combined application of chemical fertilizers with organic amendments was recommended as a strategy for improving yield,soil carbon storage,and nutrient use efficiency.However,how the long-term substitution of chemical fertilizer with organic manure affects rice yield,carbon sequestration rate(CSR),and nitrogen use efficiency(NUE)while ensuring environmental safety remains unclear.This study assessed the long-term effect of substituting chemical fertilizer with organic manure on rice yield,CSR,and NUE.It also determined the optimum substitution ratio in the acidic soil of southern China.The treatments were:(i)NPK0,unfertilized control;(ii)NPK1,100%chemical nitrogen,phosphorus,and potassium fertilizer;(iii)NPKM1,70%chemical NPK fertilizer and 30%organic manure;(iv)NPKM2,50%chemical NPK fertilizer and 50%organic manure;and(v)NPKM3,30%chemical NPK fertilizer and 70%organic manure.Milk vetch and pig manure were sources of manure for early and late rice seasons,respectively.The result showed that SOC content was higher in NPKM1,NPKM2,and NPKM3 treatments than in NPK0 and NPK1 treatments.The carbon sequestration rate increased by 140,160,and 280%under NPKM1,NPKM2,and NPKM3 treatments,respectively,compared to NPK1 treatment.Grain yield was 86.1,93.1,93.6,and 96.5%higher under NPK1,NPKM1,NPKM2,and NPKM3 treatments,respectively,compared to NPK0 treatment.The NUE in NPKM1,NPKM2,and NPKM3 treatments was higher as compared to NPK1 treatment for both rice seasons.Redundancy analysis revealed close positive relationships of CSR with C input,total N,soil C:N ratio,catalase,and humic acids,whereas NUE was closely related to grain yield,grain N content,and phenol oxidase.Furthermore,CSR and NUE negatively correlated with humin acid and soil C:P and N:P ratios.The technique for order of preference by similarity to ideal solution(TOPSIS)showed that NPKM3 treatment was the optimum strategy for improving CSR and NUE.Therefore,substituting 70%of chemical fertilizer with organic manure could be the best management option for increasing CSR and NUE in the paddy fields of southern China.

Geophysical prediction of organic matter abundance in source rocks based on geochemical analysis:A case study of southwestern Bozhong Sag,Bohai Sea,China

The Bozhong Sag is the largest petroliferous sag in the Bohai Bay Basin,and the source rocks of Paleogene Dongying and Shahejie Formations were buried deeply.Most of the drillings were located at the structural high,and there were few wells that met good quality source rocks,so it is difficult to evaluate the source rocks in the study area precisely by geochemical analysis only.Based on the Rock-Eval pyrolysis,total organic carbon(TOC)testing,the organic matter(OM)abundance of Paleogene source rocks in the southwestern Bozhong Sag were evaluated,including the lower of second member of Dongying Formation(E_(3)d2L),the third member of Dongying Formation(E_(3)d_(3)),the first and second members of Shahejie Formation(E_(2)s_(1+2)),the third member of Shahejie Formation(E_(2)s_(3)).The results indicate that the E_(2)s_(1+2)and E_(2)s_(3)have better hydrocarbon generative potentials with the highest OM abundance,the E_(3)d_(3)are of the second good quality,and the E_(3)d2L have poor to fair hydrocarbon generative potential.Furthermore,the well logs were applied to predict TOC and residual hydrocarbon generation potential(S_(2))based on the sedimentary facies classification,usingΔlogR,generalizedΔlogR,logging multiple linear regression and BP neural network methods.The various methods were compared,and the BP neural network method have relatively better prediction accuracy.Based on the pre-stack simultaneous inversion(P-wave impedance,P-wave velocity and density inversion results)and the post-stack seismic attributes,the three-dimensional(3D)seismic prediction of TOC and S_(2)was carried out.The results show that the seismic near well prediction results of TOC and S_(2)based on seismic multi-attributes analysis correspond well with the results of well logging methods,and the plane prediction results are identical with the sedimentary facies map in the study area.The TOC and S_(2)values of E_(2)s_(1+2)and E_(2)s_(3)are higher than those in E_(3)d_(3)and E_(3)d_(2)L,basically consistent with the geochemical analysis results.This method makes up the deficiency of geochemical methods,establishing the connection between geophysical information and geochemical data,and it is helpful to the 3D quantitative prediction and the evaluation of high-quality source rocks in the areas where the drillings are limited.

Geotechnical investigation of low-plasticity organic soil treated with nano-calcium carbonate

Soil stabilization using nanomaterials is an emerging research area although,to date,its investigation has mostly been laboratory-based and therefore requires extensive study for transfer to practical field ap-plications.The present study advocates nano-calcium carbonate(NCC)material,a relatively unexplored nanomaterial additive,for stabilization of low-plasticity fine-grained soil having moderate organic content.The plasticity index,compaction,unconfined compressive strength(UCS),compressibility and permeability characteristics of the 0.2%,0.4%,0.6%and 0.8%NCC-treated soil,and untreated soil(as control),were determined,including investigations of the effect of up to 90-d curing on the UCS and permeability properties.In terms of UCS improvement,0.4%NCC addition was identified as the optimum dosage,mobilizing a UCS at 90-d curing of almost twice that for the untreated soil.For treated soil,particle aggregation arising from NCC addition initially produced an increase in the permeability coef-ficient,but its magnitude decreased for increased curing owing to calcium silicate hydrate(CSH)gel formation,although still remaining higher compared to the untreated soil for all dosages and curing periods investigated.Compression index decreased for all NCC-treated soil investigated.SEM micro-graphs indicated the presence of gel patches along with particle aggregation.X-ray diffraction(XRD)results showed the presence of hydration products,such as CSH.Significant increases in UCS are initially attributed to void filling and then because of CSH gel formation with increased curing.

Variations in Soil Organic Matter Content in Cultivated and Uncultivated Calcareous Soils from the Mediterranean Island of Malta after 15 Years of Cultivation

The soils of Malta are calcareous and generally undeveloped. Organic matter (OM) in these soils is low and farmers are constantly urged to increase it. The objective of this study was to evaluate any temporal variation in soil OM after 15 years of cultivation, and determine whether soil series, soil depth, and cultivation influence variation. OM was determined in the topsoil and subsoil of 7 agricultural and 4 non-agricultural sites. The sites represented 7 different soil series that are present on the island. In sampling periods 1 (t = 0 years) and 2 (t =15 years), the OM content in the collective (all soil series) bulk (topsoil and subsoil) uncultivated soil was 3.9 % and 3.8 % respectively. This was significantly greater than that of the collective bulk cultivated soil (2.4% and 2.3%). The OM in the collective uncultivated topsoil was 5.4% and 5.2% in periods 1 and 2 and was significantly higher than that of the cultivated topsoil (2.5% in both periods). The OM content in the collective uncultivated subsoil was 2.3% and 2.5% in periods 1 and 2 respectively but only that measured in period 2 was significantly higher than that of the cultivated subsoil (2.2% in both periods). On an individual soil series basis, the OM in the uncultivated topsoils was significantly higher than that of their cultivated counterparts. The differences in the subsoils were not significant. Across the uncultivated soil series, OM was significantly higher in the topsoil than in the subsoil but in the cultivated soil series the differences between topsoil and subsoil were not significant. There was no significant difference in OM between the uncultivated soils of different series, but in the cultivated the OM content was higher in soils that were more mature. After 15 years, no significant change in OM occurred in both the collective cultivated and uncultivated bulk soils, the collective topsoil and subsoil, and in most of the individual series. The OM content of each soil series was also similar to what was reported 60 and 50 years earlier by other researchers.

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.

Forest management causes soil carbon loss by reducing particulate organic carbon in Guangxi, Southern China

Background: The loss of soil organic carbon(SOC) following conversion of natural forests to managed plantations has been widely reported. However, how different SOC fractions and microbial necromass C(MNC) respond to forest management practices remains unclear.Methods: We sampled 0–10 cm mineral soil from three different management plantations and one protected forest in Guangxi, Southern China, to explore how forest management practices affect SOC through changing mineralassociated C(MAOC) and particulate organic C(POC), as well as fungal and bacterial necromass C.Results: Compared with the protected forest, SOC and POC in the abandoned, mixed and Eucalyptus plantations significantly decreased, but MAOC showed no significant change, indicating that the loss of SOC was mainly from decreased POC under forest management. Forest management also significantly reduced root biomass, soil extractable organic C, MNC, and total microbial biomass(measured by phospholipid fatty acid), but increased fungi-to-bacteria ratio(F:B) and soil peroxidase activity. Moreover, POC was positively correlated with root biomass, total microbial biomass and MNC, and negatively with F:B and peroxidase activity. These results suggested that root input and microbial properties together regulated soil POC dynamics during forest management.Conclusion: Overall, this study indicates that forest management intervention significantly decreases SOC by reducing POC in Guangxi, Southern China, and suggests that forest protection can help to sequester more soil C in forest ecosystems.

Reclamation during oasification is conducive to the accumulation of the soil organic carbon pool in arid land

Soil organic carbon(SOC)and its stable isotope composition reflect key information about the carbon cycle in ecosystems.Studies of carbon fractions in oasis continuous cotton-cropped fields can elucidate the SOC stability mechanism under the action of the human-land relationship during the oasification of arid land,which is critical for understanding the carbon dynamics of terrestrial ecosystems in arid lands under global climate change.In this study,we investigated the Alar Reclamation Area on the northern edge of the Tarim Basin,Xinjiang Uygur Autonomous Region of China,in 2020.In original desert and oasis farmlands with different reclamation years,including 6,10,18,and 30 a,and different soil depths(0-20,20-40,40-60 cm),we analyzed the variations in SOC,very liable carbon(C_(VL)),liable carbon(C_(L)),less liable carbon(C_(LL)),and non-liable carbon(C_(NL))using the method of spatial series.The differences in the stable carbon isotope ratio(δ^(13)C)and beta(β)values reflecting the organic carbon decomposition rate were also determined during oasification.Through redundancy analysis,we derived and discussed the relationships among SOC,carbon fractions,δ^(13)C,and other soil physicochemical properties,such as the soil water content(SWC),bulk density(BD),pH,total salt(TS),total nitrogen(TN),available phosphorus(AP),and available potassium(AK).The results showed that there were significant differences in SOC and carbon fractions of oasis farmlands with different reclamation years,and the highest SOC was observed at the oasis farmland with 30-a reclamation year.C_(VL),C_(L),C_(LL),and C_(NL) showed significant changes among oasis farmlands with different reclamation years,and C_(VL) had the largest variation range(0.40-4.92 g/kg)and accounted for the largest proportion in the organic carbon pool.The proportion of C_(NL) in the organic carbon pool of the topsoil(0-20 cm)gradually increased.δ^(13)C varied from-25.61‰to-22.58‰,with the topsoil showing the most positive value at the oasis farmland with 10-a reclamation year;while theβvalue was the lowest at the oasis farmland with 6-a reclamation year and then increased significantly.Based on the redundancy analysis results,the soil physicochemical properties,such as TN,AP,AK,and pH,were significantly correlated with C_(L),and TN and AP were positively correlated with C_(VL).However,δ^(13)C was not significantly influenced by soil physicochemical properties.Our analysis advances the understanding of SOC dynamics during oasification,revealing the risk of soil carbon loss and its contribution to terrestrial carbon accumulation in arid lands,which could be useful for the sustainable development of regional carbon resources and ecological protection in arid ecosystem.

Spatial-temporal variations and driving factors of soil organic carbon in forest ecosystems of Northeast China

Forest soil carbon is a major carbon pool of terrestrial ecosystems,and accurate estimation of soil organic carbon(SOC)stocks in forest ecosystems is rather challenging.This study compared the prediction performance of three empirical model approaches namely,regression kriging(RK),multiple stepwise regression(MSR),random forest(RF),and boosted regression trees(BRT)to predict SOC stocks in Northeast China for 1990 and 2015.Furthermore,the spatial variation of SOC stocks and the main controlling environmental factors during the past 25 years were identified.A total of 82(in 1990)and 157(in 2015)topsoil(0–20 cm)samples with 12 environmental factors(soil property,climate,topography and biology)were selected for model construction.Randomly selected80%of the soil sample data were used to train the models and the other 20%data for model verification using mean absolute error,root mean square error,coefficient of determination and Lin's consistency correlation coefficient indices.We found BRT model as the best prediction model and it could explain 67%and 60%spatial variation of SOC stocks,in 1990,and 2015,respectively.Predicted maps of all models in both periods showed similar spatial distribution characteristics,with the lower SOC in northeast and higher SOC in southwest.Mean annual temperature and elevation were the key environmental factors influencing the spatial variation of SOC stock in both periods.SOC stocks were mainly stored under Cambosols,Gleyosols and Isohumosols,accounting for 95.6%(1990)and 95.9%(2015).Overall,SOC stocks increased by 471 Tg C during the past 25 years.Our study found that the BRT model employing common environmental factors was the most robust method for forest topsoil SOC stocks inventories.The spatial resolution of BRT model enabled us to pinpoint in which areas of Northeast China that new forest tree planting would be most effective for enhancing forest C stocks.Overall,our approach is likely to be useful in forestry management and ecological restoration at and beyond the regional scale.

Tailoring the separation performance of a carbon nanotube-based mixed matrix membrane decorated with metal–organic framework

Synthesis of mixed matrix membranes(MMM)using carbon nanotubes(CNTs)has shown great prospects for achieving excellent selective separation because of its special structure.Nevertheless,the preparation of highly selective MMM faces challenges,which is attributed to the obstacles encountered by CNTs dispersion in polymer matrix and elimination of interface defects.A novel CNT-based composite decorated with metal–organic framework(MOF)was synthesized and applied to the preparation of MMM.MOF was post modified,and then carboxyl groups were inserted on the outer surface of CNTs.The synthetic MMM(Cu-MOF-en@MWCNT)not only has selective adsorption on dyes,but also has selective photodegradation on dyes.The method of using CNTs to wrap the outside of MOF has great potential in dye separation.The performance of MMM was further improved by decorating MOF on the filler to improve the selectivity to the designated dye.

Organic Carbon Deposition on the Inner Shelf of the East China Sea Constrained by Sea Level and Climatic Changes Since the Last Deglaciation

The East China Sea(ECS),which is located in the transitional zone between land and ocean,is the main site for the burial of sedimentary organic carbon.Despite good constraints of the modern source to the sinking process of organic carbon,its fate in response to changes in climate and sea level since the last deglaciation remains poorly understood.We aim to fill this gap by presenting a high-resolution sedimentary record of core EC2005 to derive a better understanding of the evolution of the depositional environment and its control on the organic deposition since 17.3 kyr.Our results suggest that sedimentary organic carbon was deposited in a terrestrial environment before the seawater reached the study area around 13.1 kyr.This significant transition from a terrestrial environment to a marine environment is reflected by the decrease in TOC/TN and TOC/TS ratios,which is attributed to deglacial sea level rise.The sea level continued to rise until it reached its highstand at approximately 7.3 kyr when the mud depocenter was developed.Our results further indicate that the deposition of the sedimentary organic carbon could respond quickly to abrupt cold events,including the Heinrich stadial 1 and the Younger Dryas during the last deglaciation,as well as‘Bond events'during the Holocene.We propose that the rapid response of the organic deposition to those cold events in the northern hemisphere is linked to the East Asian winter monsoon.These new findings demonstrate that organic carbon deposition and burial on the inner shelf could effectively document sea level and climatic changes.

Maize straw application as an interlayer improves organic carbon and total nitrogen concentrations in the soil profile: A four-year experiment in a saline soil

Soil salinization is a critical environmental issue restricting agricultural production.Deep return of straw to the soil as an interlayer (at 40 cm depth) has been a popular practice to alleviate salt stress.However,the legacy effects of straw added as an interlayer at different rates on soil organic carbon (SOC) and total nitrogen (TN) in saline soils still remain inconclusive.Therefore,a four-year (2015–2018) field experiment was conducted with four levels (i.e.,0,6,12and 18 Mg ha~(–1)) of straw returned as an interlayer.Compared with no straw interlayer (CK),straw addition increased SOC concentration by 14–32 and 11–57%in the 20–40 and 40–60 cm soil layers,respectively.The increases in soil TN concentration (8–22 and 6–34%in the 20–40 and 40–60 cm soil layers,respectively) were lower than that for SOC concentration,which led to increased soil C:N ratio in the 20–60 cm soil depth.Increases in SOC and TN concentrations in the 20–60 cm soil layer with straw addition led to a decrease in stratification ratios (0–20 cm:20–60 cm),which promoted uniform distributions of SOC and TN in the soil profile.Increases in SOC and TN concentrations were associated with soil salinity and moisture regulation and improved sunflower yield.Generally,compared with other treatments,the application of 12 Mg ha~(–1) straw had higher SOC,TN and C:N ratio,and lower soil stratification ratio in the2015–2017 period.The results highlighted that legacy effects of straw application as an interlayer were maintained for at least four years,and demonstrated that deep soil straw application had a great potential for improving subsoil fertility in salt-affected soils.

Spatial prediction of soil organic carbon in coal mining subsidence areas based on RBF neural network

A quantitative research on the effect of coal mining on the soil organic carbon(SOC)pool at regional scale is beneficial to the scientific management of SOC pools in coal mining areas and the realization of coal low-carbon mining.Moreover,the spatial prediction model of SOC content suitable for coal mining subsidence area is a scientific problem that must be solved.Tak-ing the Changhe River Basin of Jincheng City,Shanxi Province,China,as the study area,this paper proposed a radial basis function neural network model combined with the ordinary kriging method.The model includes topography and vegetation factors,which have large influence on soil properties in mining areas,as input parameters to predict the spatial distribution of SOC in the 0-20 and 2040 cm soil layers of the study area.And comparing the prediction effect with the direct kriging method,the results show that the mean error,the mean absolute error and the root mean square error between the predicted and measured values of SOC content predicted by the radial basis function neural network are lower than those obtained by the direct kriging method.Based on the fitting effect of the predicted and measured values,the R^(2) obtained by the radial basis artificial neural network are 0.81,0.70,respectively,higher than the value of 0.44 and 0.36 obtained by the direct kriging method.Therefore,the model combining the artificial neural network and kriging,and considering environmental factors can improve the prediction accuracy of the SOC content in mining areas.