Improving model performance in mapping cropland soil organic matter using time-series remote sensing data

Faced with increasing global soil degradation,spatially explicit data on cropland soil organic matter(SOM)provides crucial data for soil carbon pool accounting,cropland quality assessment and the formulation of effective management policies.As a spatial information prediction technique,digital soil mapping(DSM)has been widely used to spatially map soil information at different scales.However,the accuracy of digital SOM maps for cropland is typically lower than for other land cover types due to the inherent difficulty in precisely quantifying human disturbance.To overcome this limitation,this study systematically assessed a framework of“information extractionfeature selection-model averaging”for improving model performance in mapping cropland SOM using 462 cropland soil samples collected in Guangzhou,China in 2021.The results showed that using the framework of dynamic information extraction,feature selection and model averaging could efficiently improve the accuracy of the final predictions(R^(2):0.48 to 0.53)without having obviously negative impacts on uncertainty.Quantifying the dynamic information of the environment was an efficient way to generate covariates that are linearly and nonlinearly related to SOM,which improved the R^(2)of random forest from 0.44 to 0.48 and the R^(2)of extreme gradient boosting from 0.37to 0.43.Forward recursive feature selection(FRFS)is recommended when there are relatively few environmental covariates(<200),whereas Boruta is recommended when there are many environmental covariates(>500).The Granger-Ramanathan model averaging approach could improve the prediction accuracy and average uncertainty.When the structures of initial prediction models are similar,increasing in the number of averaging models did not have significantly positive effects on the final predictions.Given the advantages of these selected strategies over information extraction,feature selection and model averaging have a great potential for high-accuracy soil mapping at any scales,so this approach can provide more reliable references for soil conservation policy-making.

Mapping soil organic matter in cultivated land based on multi-year composite images on monthly time scales

Rapid and accurate acquisition of soil organic matter(SOM)information in cultivated land is important for sustainable agricultural development and carbon balance management.This study proposed a novel approach to predict SOM with high accuracy using multiyear synthetic remote sensing variables on a monthly scale.We obtained 12 monthly synthetic Sentinel-2 images covering the study area from 2016 to 2021 through the Google Earth Engine(GEE)platform,and reflectance bands and vegetation indices were extracted from these composite images.Then the random forest(RF),support vector machine(SVM)and gradient boosting regression tree(GBRT)models were tested to investigate the difference in SOM prediction accuracy under different combinations of monthly synthetic variables.Results showed that firstly,all monthly synthetic spectral bands of Sentinel-2 showed a significant correlation with SOM(P<0.05)for the months of January,March,April,October,and November.Secondly,in terms of single-monthly composite variables,the prediction accuracy was relatively poor,with the highest R^(2)value of 0.36 being observed in January.When monthly synthetic environmental variables were grouped in accordance with the four quarters of the year,the first quarter and the fourth quarter showed good performance,and any combination of three quarters was similar in estimation accuracy.The overall best performance was observed when all monthly synthetic variables were incorporated into the models.Thirdly,among the three models compared,the RF model was consistently more accurate than the SVM and GBRT models,achieving an R^(2)value of 0.56.Except for band 12 in December,the importance of the remaining bands did not exhibit significant differences.This research offers a new attempt to map SOM with high accuracy and fine spatial resolution based on monthly synthetic Sentinel-2 images.

Effects of Biochar and Soil Organic Matter Levels on Physicochemical Properties of Mollisol and Soybean's Biomass

Long term tillage in mollisol of Northeast China has led to an inhomogeneous distribution of soil organic matter content.Biochar,a carbon material,changes the soil carbon pool and physical-chemical characteristics after adding to the soil.However,the mechanism remains unclear for the relation between the soil organic matter level and biochar amount.So,the soil physical and chemical properties and soybean growth in a two-year pot experiment were detected at three levels of soil organic matter and three biochar additions(0,1%and 10%).The difference was found in two biochar application rates.The 1%biochar addition had no positive effect on the soil chemical properties based the two-year experiment.However,10%biochar application significantly increased the soil water content(8.0%-39.7%),the total porosity(9.7%-21.3%),pH(0.26-0.84 unit),organic matter content(89.0%-261.2%),and the available potassium content(29.0%-109.1%).The biomass of soybean increased by 19.4%-78.1%after biochar addition,yet,the soil bulk density reduced at the range of 12.6%-26.0%by 10%biochar addition.Only the 100-grain weight was correlated to the interaction of biochar and the native soil organic matter.All the indicators showed that the interaction between biochar and soil organic matter level was weak in mollisol.The effects of biochar on the physical-chemical properties relied on its amount.When biochar is applied to the soil,the amount of biochar should be considered rather than the native soil organic matter level.

Deadwood affects the soil organic matter fractions and enzyme activity of soils in altitude gradient of temperate forests

The main objective of our study has been to determine the role of deadwood in the shaping of the amount of soil organic matter fractions in mountain forest soils.For this purpose,a climosequence approach comprising north(N)and south(S)exposure along the altitudinal gradient(600,800,1000 and 1200 m a.s.l.)was set up.By comparing the properties of decomposing deadwood and those of the soils located directly beneath the decaying wood we drew conclusions about the role of deadwood in the shaping of soil organic matter fractions and soil carbon storage in different climate conditions.The basic properties,enzymatic activity and fractions of soil organic matter(SOM)were determined in deadwood and affected directly by the components released from decaying wood.Heavily decomposed deadwood impacts soil organic matter stabilization more strongly than the less decayed deadwood and the light fraction of SOM is more sensitive to deadwood effects than the heavy fraction regardless of the location in the altitude gradient.Increase in SOM mineral-associated fraction C content is more pronounced in soils under the influence of deadwood located in lower locations of warmer exposure.Nutrients released from decaying wood stimulate the enzymatic activity of soils that are within the range of deadwood influence.

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.

Regression-Kriging of Soil Organic Matter Using the Environmental Variables Derived from MODIS and DEM

[Objective] The objective of this project was to evaluate and compare spa- tial estimation accuracy by ordinary kriging and regression kriging with MODIS data, predicting SOM contents using limited available data in Shimen County, Hunan Province, China. [Method] Terrain parameters （derived from DEM） and Normalized differential vegetation index （NDVI）, Land surface temperature （LST） （derived from MODIS data） were used as auxiliary data to predict the SOM spatial distribution. The mean error （ME） and mean square error （RMSE） were adopted to validate the SOM prediction accuracy. The descriptive statistics and data transformation were conducted by using computer technology. [Result] Regression kriging with terrain and remotely sensed data was superior to ordinary kriging in the case of limited available samples; even the linear relationship between environmental variables and SOM content was moderate. The accuracy assessment showed that the regression kriging method combining with environmental factors obtained a lower mean predication error and root mean square prediction error. The relative improvement was 6.03% compared with ordinary kriging. [Conclusion] Remotely sensed data such as MODIS im- age have the potential as useful auxiliary variables for improving the precision and reliability of SOM prediction in the hilly regions.

Extraction of Soil Organic Matter Information by Multi-spectral Remote Sensing Based on Diverse Landforms

Based on diverse landforms, the correlation between soil organic matter content and multi-spectral band of remote sensing image was analyzed in this pa- per. In addition, the inversion models were built for the soil organic matter content in different landforms. The results showed that the spectral reflectance was nega- tively related to soil organic matter content; linear regression analysis of remove was performed throughout the bands using SPSS. When the inversion models were built based on all the bands, better fitting effect was obtained. The precision of in- version models built based on different landforms was higher than those built re- gardless landforms. Compared with the actual value, the identification level of soil organic matter content was 91 65% under the allowable error was 7%. It indicated that the extraction of soil organic matter with inversion model that was built based on different landforrrs was feasible with higher precision.

Effect of Cultivation on Soil Organic Matter and Aggregate Stability

Agricultural sustainability relates directly to maintaining or enhancing soil quality. Soil quality studies in Canada during the 1980 s showed that loss of soil organic matter (SOM) and soil aggregate stability was standard features of non-sustainable land management in agroecosystems. In this study total soil organic carbon (SOC), particulate organic matter (POM), POM-C as a percentage of total SOC, and aggregate stability were determined for three cultivated fields and three adjacent grassland fields to a…

Impacts of soil organic matter, pH and exogenous copper on sorption behavior of norfloxacin in three soils

Norfloxacin sorption and the factors （soil organic matter （SOM）, pH, and exogenous copper （Cu） influencing the sorption were investigated in a black soil （soil B）, a fluvo-aquic soil （soil F）, and a red soil （soil R）. With increasing norfloxacin concentrations, sorption amount of norfloxacin increased in both the bulk soils and their SOM-removed soils, but the sorption capacity of SOM-removed soils was higher than that of their corresponding bulk soils, indicating that the process of norfloxacin sorption in soil was influenced by the soil properties including SOM. The sorption data in all bulk soils and SOM-removed soils were fitted to Freundlich and Langmuir models. The correlation coefficients suggested that the experimental data fitted better to Freundlich equation than to Langmuir equation. Furthermore, the data from soil F and SOM-removed F could not be described by Langmuir equation. The norfloxacin sorption amount decreased in soil B and soil F, whereas it increased in soil R as solution pH increased. The maximum KD and Koc were achieved in soil R when the equilibrium solution pH was 6. The norfloxacin sorption was also influenced by the exogenous Cu^2＋, which depended on the soil types and Cu^2＋ concentrations. With increasing Cu^2＋ concentrations in solution, generally, sorption amount, KD and Koc for norfloxacin in soils increased and were up to a peak at 100 mg/L Cu^2＋, and then the sorption amount decreased regardless of norfloxacin levels.

Effects of free iron oxyhydrates and soil organic matter on copper sorption-desorption behavior by size fractions of aggregates from two paddy soils

Effects of free iron oxyhydrates （Fed） and soil organic matter （SOM） on copper （Cu^2＋） sorption-desorption behavior by size fractions of aggregates from two typical paddy soils （Ferric-Accumulic Stagnic Anthrosol （Soil H） and Gleyic Stagnic Anthrosol （Soil W）） were investigated with and without treatments of dithionite-citrate-bicarbonate and of H2O2. The size fractions of aggregates were obtained from the undisturbed bulk topsoil using a low energy ultrasonic dispersion procedure. Experiments of equilibrium sorption and subsequent desorption were conducted at soil water ratio of 1：20, 25℃. For Soil H, Cu^2＋ sorption capacity of the DCB-treated size fractions was decreased by 5.9% for fine sand fraction, by 40.4% for coarse sand fraction, in comparison to 2.9% for the bnlk sample. However, Cu^2＋ sorption capacities of the H2O2-treated fractions were decreased by over 80% for the coarse sand fraction and by 15% for the clay-sized fraction in comparison to 88% for bulk soil. For Soil W, Cu^2＋ sorption capacity of the DCB-treated size fraction was decreased by 30% for the coarse sand fraction and by over 75% for silt sand fraction in comparison to 44.5% for the bulk sample. Cu^2＋ sorption capacities of the H2O2-treated fractions were decreased by only 2.0% for the coarse sand fraction and by 15% for the fine sand fraction in comparison to by 3.4% for bulk soil. However, Cu^2＋ desorption rates were increased much in H2O2-treated samples by over 80% except the clay-sized fraction （only 9.5%） for Soil H. While removal of SOM with H2O2 tendend to increase the desorption rate, DCB- and H2O2-treatments caused decrease in Cu^2＋ retention capacity of size fractions, Particularly, there hardly remained Cu^2＋ retention capacity by size fractions from Soil H after H2O2 treatment except for clay-sized fraction. These findings supported again the dominance of the coarse sand fraction in sorption of metals and the preference of absorbed metals bound to SOM in differently stabilized status among the size fractions. Thus, enrichment and turnover of SOM in paddy soils may have great effects on metal retention and chemical mobility in paddy soils.

Comparative study on active soil organic matter in Chinese fir plantation and native broad-leaved forest in subtropical China

Active soil organic matter (ASOM) has a main effect on biochemical cycles of soil nutrient elements such as N, P and S, and the quality and quantity of ASOM reflect soil primary productivity. The changes of ASOM fractions and soil nutrients in the first rotation site and the second rotation site of Chinese fir plantation and the native broad-leaved forest were investigated and analyzed by soil sampling at the Huitong Experimental Station of Forestry Ecology (at latitude 26°48′N and longitude 109°30′E under a subtropical climate conditions), Chinese Academy of Sciences in March, 2004. The results showed that values of ASOM fractions for the Chinese fir plantations were lower than those for the broad-leaved forest. The contents of easily oxidisable carbon (EOC), microbial biomass carbon (MBC), water soluble carbohydrate (WSC) and water-soluble organic carbon (WSOC) for the first rotation of Chinese fir plantation were 35.9%, 13.7%, 87.8% and 50.9% higher than those for the second rotation of Chinese fir plantation, and were 15.8%, 47.3%, 38.1% and 30.2% separately lower than those for the broad-leaved forest. For the three investigated forest sites, the contents of MBC and WSOC had a larger decrease, followed by WSC, and the change of EOC was least. Moreover, soil physico-chemistry properties such as soil nutrients in Chinese fir plantation were lower than those in broad-leaved forest. It suggested that soil fertility declined after Chinese fir plantation replaced native broad-leaved forest through continuous artificial plantation.

Spatial Distribution of Soil Organic Matter and Nutrients in the Pear Orchard Under Clean and Sod Cultivation Models

The soil organic matter and nutrients are fundamental for the sustainability of pear production, but little is known about the spatial distribution of soil organic matter and nutrients in a pear orchard. With the soil of the pear （cv. Dangshansu on P.betulifolia Bunge. rootstock） orchard under clean and sod cultivation models as test materials, the experiment was conducted to evaluate spatial variability of soil organic matter （SOM）, total nitrogen （STN）, total phosphorus （STP）, total potassium （STK）, available nitrogen （SAN）, and available potassium （SAK） in and between rows at different soil depths （0-60 cm）. The SOM, STN, STP, STK, SAN and SAK of the different soil layers under the two tillage models were different in the vertical direction. The SOM, STN, STP and SAN in the 0-20 cm soil layer were higher than those in the 20-40 and 40- 60 cm soil layers. The STK of 40-60 cm soil layer was higher than that in the 0-20 and 20-40 cm soil layers. The STK increased with the depth of soil in the vertical direction in the clean cultivated pear orchard. Variability of the SOM, STN, STP, STK, SAN and SAK of sample sites in between rows of the same soil layer was found in the pear orchard soil in the horizontal direction under clean and sod cultivation management systems, except that STK of all sites did not show the difference in identical soil layers in the pear orchard under clean cultivation. The sod cultivation model improved the SOM, STN, and STK in the 0-20 cm soil layer in the pear orchard, and the three components increased by 12.8, 12.7 and 7.3% compared to clean cultivation, respectively. The results can be applicable to plan collection of orchard soil samples, assess orchard soil quality, and improve orchard soil management practices.

Soil Organic Matter Fractions under Different Vegetation Types in Permafrost Regions along the Qinghai-Tibet Highway, North of Kunlun Mountains, China

As a key attribute of soil quality, soil organic matter(SOM) and its different fractions play an important role in regulating soil nutrient cycling and soil properties.This study evaluated the soil carbon(C) and nitrogen(N) concentrations in different SOM fractions(light– and heavy fractions,microbial biomass) under different vegetation types and analyzed their influencing factors in continuous permafrost regions along the Qinghai-Tibet Highway in the North of Kunlun Mountains, China.Soil samples were collected in pits under four vegetation types — Alpine swamp meadow(ASM), Alpine meadow(AM), Alpine steppe(AS) and Alpine desert(AD) — at the depth of 0-50 cm.The vegetation coverage was the highest at ASM and AM, followed byAS and AD.The results indicated that the concentrations of light fraction carbon(LFC) and nitrogen(LFN), and microbial biomass carbon(MBC)and nitrogen(MBN) decreased as follows: ASM > AM >AS > AD, with the relatively stronger decrease of LFC,whereas the heavy fraction carbon(HFC) and nitrogen(HFN) concentrations were lower in AS soils than in the AD soils.The relatively higher proportions of LFC/SOC and MBC/SOC in the 0-10 cm depth under the ASM soils are mainly resulted from its higher substrate input and soil moisture content.Correlation analysis demonstrated that aboveground biomass, soil moisture content, soil organic carbon(SOC) and total nitrogen(TN) positively correlated to LFC, LFN, HFC, HFN, MBC and MBN, while p H negatively correlated to LFC, LFN, HFC, HFN, MBC and MBN.There was no relationship between active layer thickness and SOM fractions, except for the LFC.Results suggested that vegetation cover, soil moisture content, and SOC and TN concentrations were significantly correlated with the amount and availability of SOM fractions, while permafrost had less impact on SOM fractions in permafrost regions of the central Qinghai–Tibet Plateau.

Sorption of Triton X-100 on soil organic matter fractions:Kinetics and isotherms

Kinetics and isotherms of Triton X-100 sorption on soil,base-extracted soil（BE）,humic acid（HA） and humin（HM） were investigated respectively to get better understanding on characteristics of the surfactant sorption onto different soil organic matters（SOMs）.It was demonstrated that the kinetics results could be satisfactorily described by the pseudo-second order model.The half of the time to reach equilibrium（t1/2） for different sorbents followed the sequence of soil 〉 HA 〉 BE 〉 HM.Furthermore,the calculated equilibrium sorption capacity（Ceq） was found in the sequence of HA 〉 BE 〉 HM 〉 soil,which agreed well with the experimental results.The isotherms of Triton X-100 sorption on soil and HA could be well described by the S-type isotherm,but BE and HM by the L-type.The isotherms of all the four sorbents were found reasonably fitted to the Langmuir equation.The Kd value,defined as the ratio of Triton X-100 in sorbent and in the equilibrium solution for given concentrations,generally followed the order of HM 〉 HA 〉 soil 〉 BE.Separated HM and HA showed high affnity for Triton X-100,but the HA and HM in soil and BE were tightly bounded by the minerals.Thus,the HA on the soil surface might dominate the sorption,whereas the bounded HM would play a key role upon the surfactants being penetrated inside the soil.

Modeling Soil Organic Matter Dynamics Under Intensive Cropping Systems on the Huang-Huai-Hai Plain of China

A modified CQESTR model, a simple yet useful model frequently used for estimating carbon sequestration in agricultural soils, was developed and applied to evaluate the effects of intensive cropping on soil organic matter （SOM） dynamics and mineralization as well as to estimate carbon dioxide emission from agricultural soils at seven sites on the Huang-Huai-Hai Plain of China. The model was modified using site-specific parameters from short- and mid-term buried organic material experiments at four stages of biomass decomposition. The predicted SOM results were validated using independent data from seven long-term （10- to 20-year） soil fertility experiments in this region. Regression analysis on 1 151 pairs of predicted and measured SOM data had an r2 of 0.91 （P≤0.01）. Therefore, the modified model was able to predict the mineralization of crop residues, organic amendments, and native SOM. Linear regression also showed that SOM mineralization rate （MR） in the plow layer increased by 0.22% when annual crop yield increased by 1 t ha^-1 （P ≤ 0.01）, suggesting an improvement in SOM quality. Apparently, not only did the annual soil respiration efftux merely reflect the intensity of soil organism and plant metabolism, but also the SOM MR in the plow layer. These results suggested that the modified model was simple yet valuable in predicting SOM trends at a single agricultural field and could be a powerful tool for estimating C-storage potential and reconstructing C storage on the Huang-Huai-Hai Plain of China.

Trends of soil organic matter turnover in the salt marsh of the Yangtze River estuary

Characteristics and tidal flat trends of soil organic matter （SOM） turnover were studied for the Chongmingdongtan Salt Marsh in the Yangtze River estuary, based on analyses of stable carbon isotope composition （δ^13C）, grain sizes and contents of particulate organic carbon （POC）, total nitrogen （TN） and inorganic carbon （TIC） for three cores excavated from high tidal flat, middle tidal flat and bare flat. Results demonstrate that correlations between soil POC contents and δ^13C values of the salt marsh cores were similar to those between soil organic carbon （SOC） contents and δ^13C values of the upper soil layers of mountainous soil profiles with different altitudes. SOM of salt marsh was generally younger than 100 years, and originated mainly from topsoil erosions in catchments of the Yangtze River. Correlations of TN content with C/N ratio, POC content with TIC content and POC content with δ^13C values for the cores suggest that turnover degrees of SOM from the salt marsh are overall low, and trends of SOM turnover are clear from the bare flat to the high tidal flat. Bare flat samples show characteristics of original sediments, with minor SOM turnover. Turnover processes of SOM have occurred and are discernable in the high and middle tidal flats, and the mixing degrees of SOM compartments with different turnover rates increase with evolution of the muddy tidal flat. The exclusive strata structure of alternate muddy laminae and silty laminae originated from dynamic depositional processes on muddy tidal flat was a great obstacle to vertical migration of dissolved materials, and SOM turnover was then constrained. The muddy tidal flat processes exerted direct influences on sequestration and turnover of SOM in the salt marsh, and had great constraints on the spatial and temporal characteristics of SOM turnover of the Chongmingdongtan Salt Marsh in the Yangtze River estuary.

Effects of continuous nitrogen addition on microbial properties and soil organic matter in a Larix gmelinii plantation in China

Continuous increases in anthropogenic nitrogen（N） deposition are likely to change soil microbial properties, and ultimately to affect soil carbon（C） storage.Temperate plantation forests play key roles in C sequestration, yet mechanisms underlying the influences of N deposition on soil organic matter accumulation are poorly understood. This study assessed the effect of N addition on soil microbial properties and soil organic matter distribution in a larch（Larix gmelinii） plantation. In a 9-year experiment in the plantation, N was applied at100 kg N ha-1 a-1 to study the effects on soil C and N mineralization, microbial biomass, enzyme activity, and C and N in soil organic matter density fractions, and organic matter chemistry. The results showed that N addition had no influence on C and N contents in whole soil. However,soil C in different fractions responded to N addition differently. Soil C in light fractions did not change with N addition, while soil C in heavy fractions increased significantly. These results suggested that more soil C in heavy fractions was stabilized in the N-treated soils. However,microbial biomass C and N and phenol oxidase activity decreased in the N-treated soils and thus soil C increased in heavy fractions. Although N addition reduced microbial biomass and phenol oxidase activity, it had little effect on soil C mineralization, hydrolytic enzyme activities, d13 C value in soil and C–H stretch, carboxylates and amides, and C–O stretch in soil organic matter chemistry measured by Fourier transform infrared spectra. We conclude that N addition（1） altered microbial biomass and activity without affecting soil C in light fractions and（2） resulted in an increase in soil C in heavy fractions and that this increase was controlled by phenol oxidase activity and soil N availability.

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.

Influence of Climate and Socio-Economic Factors on the Spatio-Temporal Variability of Soil Organic Matter: A Case Study of Central Heilongjiang Province, China

For the scientific management of farmland, it is significant to understand the spatio-temporal variability of soil organic matter and to study the influences of related factors. Using geostatistical theory, GIS spatial analysis, trend analysis and a Geographically Weighted Regression （GWR） model, this study analyzed the response of soil organic matter to climate and socio-economic factors in central Heilongjiang Province during the past 25 years. Second soil survey data of China for 1979-1985, 2005 field sampling data, climate observations and socio-economic data for 1980-2005 were analyzed. First, soil organic matter in 2005 was spatially interpolated using the Co-Kriging method along with auxiliary data sets of soil type and pH. The spatio-temporal variability was then studied by comparison with the 1980s second soil census data. Next, the temporal trends in climate and socio-economic factors over the past 25 years were investigated. Finally, we examined the variation of the response of soil organic matter to climate and socio-economic factors using the GWR model spatially and temporally. The model showed that 53.82% area of the organic matter content remained constant and 29.39% has decreased during the past 25 years. The impact of precipitation on organic matter content is mainly negative, with increasing absolute values of the regression coefficient. The absolute value of regression coefficient of annual average temperature has decreased, and more areas are now under its negative effects. In addition, the areas of positive regression coefficient of annual sunshine hours have northward shifted, with the increasing absolute value of positive coefficient and decreasing absolute value of negative coefficient. The areas of positive regression coefficient of mechanized farming as a socio-economic factor have westward shifted, with the increasing absolute value of negative coefficient and decreasing absolute value of positive coefficient. The area of regions with the positive regression coefficient of irrigation has expanded. The regions with positive regression coefficient of fertilizer use have shrinked. The positive regression coefficient of mulch film consumption has significantly increased. The regression coefficient of pesticide consumption was mainly positive in the west of the study area, while it was negative to the east. Generally, GWR model is capable to investigate the influence of both climatic and socio-economic factors, avoided the insufficiency of other research based on the single perspective of climatic or socio-economic factors. Therefore, we can conclude that GWR model could provide methodological support for global change research and serve as basic reference for cultivated land quality improvement and agricultural decision making.

Determination and Analysis of Soil Organic Matter Content in Greenhouses around Lhasa City

The soil organic matter content in the greenhouses around Lhasa City was determined by potassium dichromate-sulfuric acid digestion method. The results showed that the soil organic matter content differed among different soil layers of the greenhouses around Lhasa City, and it was relatively low in the deep soil. The soil organic matter content also differed among greenhouses with different cultivation modes. In the same soil layer, the organic matter content in arched greenhouse was lower than that in semi-arched greenhouse. Among all the soil samples, the samples with organic matter content below the critical value （20 g/kg） accounted for 61.33%, and the samples with higher organic matter content （≥30 g/kg） accounted for 10.64%. The soil organic matter content in the greenhouses of different counties of Lhasa City ranked as Dazi County＇s〉Duilongdeqing County＇s〉Qushui County＇s. In overall, the organic matter content in the soil of greenhouses around Lhasa City was medium-low, and the fertility of the greenhouse soil was at the middle level.