Black Soil Area Research Articles

Construction of Evaluation Model of Surface Soil Erodibility Factors in Black Soil Area

The increasing soil erosion in black soil area has caused widespread concern from all walks of life. Based on this background, the evaluation model of surface soil erodibility factor in black soil area is studied and constructed. The data of erosion gully is from the general survey data of surface soil erosion gully in black soil area. After quantifying the morphological characteristics of the data, the vector data of erosion gully are gridded by fractal theory. The number of non-empty grids is calculated by the attribute query function of ArcGIS, and the pixel size is transformed in turn to obtain different coverage grids and corresponding fractal parameters. The surface soil runoff and soil erosion process in black soil area are simulated by PESERA model. To build the surface soil erosion model of black soil area, in the process of building the user-defined model, it needs to carefully select the parameters used for modeling, and it needs to consider all the factors that may play a role in the whole process of soil erosion. The factors of surface soil erodibility in black soil area are analyzed, including spatial distribution characteristics of soil erodibility’s K value, semivariance function analysis of soil erodibility’s K value, and spatial distribution characteristics analysis of soil erodibility’s K value. Finally, the evaluation model of surface soil erodibility factor in black soil area is constructed. By testing the quantitative performance and evaluation accuracy of erodibility factors, it is proved that this method has good quantitative performance and evaluation accuracy of erodibility factors, and has strong practicability.

Regional mapping of soil organic matter content using multitemporal synthetic Landsat 8 images in Google Earth Engine

Accurate assessment of the spatial distribution of soil organic matter (SOM) is of great significance for regional sustainable development, especially in fertile black soil areas. The present study proposed a regional-scale high spatial resolution (30 m) SOM mapping method based on multitemporal synthetic images. The study area is located on the Songnen Plain of Northeast China. First, all available Landsat 8 surface reflectance (SR) data during the bare soil period (April and May) from 2014 to 2019 in the study area were screened in the Google Earth Engine (GEE), and the cloud mask was constructed. The median, average, maximum, and minimum values of the image set were synthesized according to single-year multimonth, multiyear single-month and multiyear multimonth time ranges, and the spectral index of the synthesized image was constructed. Second, the bands and spectral indices of different synthetic images were used as input to establish a random forest (RF) model of SOM prediction, and the accuracies of different spatial prediction models of SOM were compared to evaluate the optimal regional remote sensing prediction model of SOM. The following results were show. 1) The use of the spectral index combined with the image band as input had a greater improvement in the accuracy of SOM prediction than the use of only the image band. 2) Compared to the average, maximum and minimum synthesized images, the median synthesized image had higher accuracy in SOM prediction. 3) More years of synthesized images provided more robust SOM prediction results. 4) May was the best time window for SOM mapping on the Songnen Plain. This study presents a large-scale and high spatial resolution SOM mapping method that is suitable for black soil areas in Northeast China and extends the application of GEE in digital soil mapping.

No tillage and residue mulching method on bacterial community diversity regulation in a black soil region of Northeastern China.

Soil microorganisms are important components of agricultural ecosystems; they are important in agricultural soil nutrient cycle and are easily affected by soil tillage. The response of soil microbial community to tillage is very complex, and the effect of the no tillage and residue mulching method on soil microbial diversity remains unclear. In 2019, the soil was collected from an experimental field after 10 years of continuous cultivation in the black soil area of the Sanjiang Plain in Northeastern China. In this study, the diversity and composition of the soil bacterial community and their relationship with soil properties were explored via high-throughput sequencing under no tillage with four residue mulching treatments. No tillage with 60% residue mulching (NTR3) significantly increased the alpha diversity of the rhizosphere soil bacteria and changed the composition of the bacterial community—consistent with changes in soil physicochemical properties. Proteobacteria, Acidobacteria, and Actinobacteria were the dominant phyla in the sample soil. Soil physicochemical properties explained 80.6% of the changes in soil diversity and composition, of which soil organic carbon, soil pH, and soil temperature were the principal contributors. Our results suggest that no tillage and residue mulching is conducive to increasing soil organic carbon and soil nutrient content, which is a beneficial conservation tillage measure for black soil protection in Sanjiang Plain of Northeast China. The no tillage with residue mulching, especially 60% residue mulching, alters soil bacterial community and highlights the importance of soil physicochemical properties in shaping the diversity and composition of the soil bacterial community. Our findings contribute to a broad understanding of the effects of no tillage and residue mulching on bacterial community differences and provide a scientific basis for the optimization of no tillage measures and sustainable utilization of the black soil of the Sanjiang Plain in Northeastern China.

National scale assessment of the soil erosion and conservation function of terraces in China

Terraces are not only productive but also have outstanding ecological functions, becoming an important soil and water conservation measure worldwide. Although there are many studies on soil and water conservation in terraces, due to the lack of data on the spatial distribution of terraces, most of the current studies are focused on small areas, lacking large-scale studies. This study is the first to quantitatively measure soil erosion and soil and water conservation capacity of terraces and their spatial distribution throughout China. The spatialization method and Revised Universal Soil Loss Equation model were used to calculate the soil erosion modulus and quantity of terraces and slope farmland at the pixel scale. The results showed that the average soil erosion modulus and soil erosion quantity for the terraces in China in 2017 were 273.56 t km−2 a-1 and 4.88 × 107 t, respectively. The average soil conservation modulus and soil conservation quantities in 2017 were 2132.59 t km−2 a-1 and 3.81 × 108 t, respectively. The terraces maintained 88.63% of the soil from erosion at the national scale. The vast majority of terraces experienced micro erosion (84.53%) and slight erosion (14.97%), with only a small percentage area of terraces experiencing moderate erosion and above. Spatially, the terraces in the Black Soil Area, Red Soil Area, and Rocky Mountain Area had better soil conservation effects, while the terraces in the Loess Plateau and Tibetan Plateau had poor soil conservation effects. Findings from this study will help to understand regional differences in soil erosion in terraces in China, which in turn will help to formulate environmental protection policies.

Application of 3D Laser Image Scanning Technology and Cellular Automata Model in the Prediction of the Dynamic Process of Rill Erosion

Black soil areas are strongly affected by rill erosion due to the geomorphic characteristics of flood plains and heavy rainfall. To study the problem of rill erosion in black soil areas and achieve ecological restoration, based on the method of artificially simulated rainfall, the effects of rainfall intensity and slope on the characteristics of flow and sand production on the slope surface of black soil areas were studied, and the erosion pattern of the slope surface after rainfall was monitored by a 3D laser scanner to analyze the erosion of the soil on the slope surface. The slope erosion model was constructed on the basis of the cellular automata (CA) method, and the results of the model’s operation were compared with actual rainfall measurement results to deepen research on the slope erosion mechanism in black soil areas. By analyzing the slope erosion pattern after rainfall, it was found that the surface area and erosion volume of serious slope erosion areas increased with increases in slope gradient. Based on the physical model test results combined with the CA model to simulate flow and sand production on bare slopes under different rainfall intensities, comparison showed that the CA model can accurately simulate flow and sand production on a slope where the Ens coefficient of the flow production rate is between 0.70 and 0.97, thus theoretically verifying the reliability of the model, and on this basis, the erosion pattern of the slope after rainfall was predicted to explore the evolution and development law of erosion.

Effects of Biochar on Sediment Transport and Rill Erosion after Two Consecutive Years of Seasonal Freezing and Thawing

This research explored the effects of biochar on slope runoff and sediment transport processes and the hydrodynamic mechanism of rill erosion under the seasonal freeze–thaw climate in the black soil area of Northeast China. The four slopes of 1.8, 3.6, 5.4 and 7.2° were set, corn straw biochar was used, and three biochar contents of 0 kg m−2 (B0 treatment), 6 kg m−2 (B6 treatment) and 12 kg m−2 (B12 treatment) were applied. The experimental plot was placed outdoors to simulate the freeze–thaw cycle of sloping farmland under natural conditions. Three artificial simulated rainfall tests were carried out before the end of seasonal freeze–thaw cycles and spring sowing date (May) in 2018 and 2019. The sediment transport process of runoff and the variation of hydrodynamic parameters in rills were analyzed under one and two seasons of freezing and thawing in natural outdoor conditions. The results show that biochar has a positive effect on reducing rainfall runoff and soil loss after one year and two years of seasonal freezing and thawing. The effect of biochar on the sediment concentration of slope runoff increased with increasing application time; in the second year, the B6 and B12 treatments reduced the sediment concentration by 5.5–14.8% and 3.3–13.6%, respectively, compared with the values of the first year. The Reynolds number (Re) in the rill flow after the B6 and B12 treatments decreased with increasing duration, which effectively reduced the turbulence degree of the flow on the rill of the slope. With the increase in duration, the rill critical erosion power increased; in 2018 and 2019, the critical shear force, critical runoff power and critical unit runoff power were 0.403 Pa, 0.098 m s−1, and 0.002 N m−1 and 0.497 Pa, 0.124 m s−1, and 0.003 N m−1, respectively. This result indicates that increasing the duration and number of seasonal freeze–thaws can promote the development of biochar control of the runoff and sediment processes on slope and rill development.

The Suitability of Remote Sensing Images at Different Resolutions for Mapping of Gullies in the Black Soil Region, Northeast China

Remote sensing images with different spatial resolutions have different performance capabilities for gully extraction, so it is very important to study the suitability of different spatial resolutions for this purpose. In this study, part of the black soil area in Northeast China with serious gully erosion was taken as the study area, and Google Earth images with seven spatial resolutions ranging from 0.51 to 32.64 m, commonly used in gully erosion research, were selected as data sources. Combined with auxiliary data, gullies were extracted by visual interpretation. The interpretation results of images of different spatial resolutions were analyzed qualitatively and quantitatively, and the interpretation suitability of images of different spatial resolutions for different types of gullies under different classification systems was emphatically explored. The results indicate that the image with a spatial resolution of 1.02 m has the best performance when not considering the types of gullies. However, the image with a spatial resolution of 2.04 m is the most cost-effective and, therefore, the most suitable for general research. When it is necessary to distinguish the type of gully, the image with a spatial resolution of 0.51 m can be adapted for all situations. However, research on ephemeral gullies is of little practical significance. Therefore, the image with a spatial resolution of 1.02 m is the most universally useful image, being cheaper and easier to obtain. When the spatial resolution is 2.04 m or lower, it is necessary to select the spatial resolution according to the gully type required for practical application. When the spatial resolution is 8.16 or lower, the interpretation of gullies becomes very difficult or even impossible.

Reducing the Moisture Effect and Improving the Prediction of Soil Organic Matter With VIS-NIR Spectroscopy in Black Soil Area

Soil organic matter (SOM) is rich in black soil area. It has a significant effect on soil health and luxuriant vegetation. The agricultural production activities can thus be guided by measurements of SOM at different periods. Most of previous work estimated SOM using reflectance spectra measurements on dried soil samples, to remove the effect of soil moisture content (SMC). However, it is time-consuming and almost conduct-prohibitive in the field. In this study, we utilized the continuous wavelet transform (CWT) on visible (VIS) and near infrared (NIR) spectra to test its effect on eliminating the SMC influence, and proposed to use the PCA-RF method coupled with CWT to predict SOM from the wet samples. Multi-scale coefficients can amplify the response of spectra to SOM in varying degrees, while improving the correlation of characteristic wavebands and minimizing the moisture interference on SOM specific wavelength. By analysing the multi-scale coefficients, we found that wavelengths ranging around the peaks of $580nm$ , $820nm$ , and especially the narrow region around $1400nm$ are highly correlated regions to SOM. Furthermore, the accuracy of SOM estimation models illustrated the effectiveness of the CWT. Results of the validation model using the dataset of wet samples on CWT scale 6 ( $R^{2}$ = 0.84, $Mse$ = 0.23%, and $RPD$ = 2.53) can be statistically equivalent to dataset of dried samples ( $R^{2}$ = 0.86, $Mse$ = 0.20%, and $RPD$ = 2.68). Combined with the PCA-RF method, SOM estimation can be perfectly performed with fewer features as input variables and has a great improved. The best prediction of validation model was on scale 6 with features extracted from 4 PCs, compared with the EPO-PLSR method ( $R^{2}$ = 0.85, $Mse$ = 0.25%, and $RPD$ = 2.54), the proposed method has a better result ( $R^{2}$ = 0.94, $Mse$ = 0.09%, and $RPD$ = 4.08).

Exploring Appropriate Preprocessing Techniques for Hyperspectral Soil Organic Matter Content Estimation in Black Soil Area

Black soil in northeast China is gradually degraded and soil organic matter (SOM) content decreases at a rate of 0.5% per year because of the long-term cultivation. SOM content can be obtained rapidly by visible and near-infrared (Vis–NIR) spectroscopy. It is critical to select appropriate preprocessing techniques for SOM content estimation through Vis–NIR spectroscopy. This study explored three categories of preprocessing techniques to improve the accuracy of SOM content estimation in black soil area, and a total of 496 ground samples were collected from the typical black soil area at 0–15 cm in Hai Lun City, Heilongjiang Province, northeast of China. Three categories of preprocessing include denoising, data transformation and dimensionality reduction. For denoising, Svitzky-Golay filter (SGF), wavelet packet transform (WPT), multiplicative scatter correction (MSC), and none (N) were applied to spectrum of ground samples. For data transformation, fractional derivatives were allowed to vary from 0 to 2 with an increment of 0.2 at each step. For dimensionality reduction, multidimensional scaling (MDS) and locally linear embedding (LLE) were introduced and compared with principal component analysis (PCA), which was commonly used for dimensionality reduction of soil spectrum. After spectral pretreatments, a total of 132 partial least squares regression (PLSR) models were constructed for SOM content estimation. Results showed that SGF performed better than the other three denoising methods. Low-order derivatives can accentuate spectral features of soil for SOM content estimation; as the order increases from 0.8, the spectrum were more susceptible to spectral noise interferences. In most cases, 0.2–0.8 order derivatives exhibited the best estimation performance. Furthermore, PCA yielded the optimal predictability, the mean residual predictive deviation (RPD) and maximum RPD of the models using PCA were 1.79 and 2.60, respectively. The application of appropriate preprocessing techniques could improve the efficiency and accuracy of SOM content estimation, which is important for the protection of ecological and agricultural environment in black soil area.

Effective Tiller Numbers, Photosynthetic and Yield Response of Rice (Oryza sativa) to Shallow Wet–Dry Irrigation Water Controlled at Tillering Stage in Black Soil Area

In order to study the effects of shallow wet–dry irrigation at tillering stage on effective tiller numbers, photosynthetic activity, yield and water use efficiency (WUE) of rice in black soil region, a pot experiment was conducted at Qingan National Irrigation Test Station of Heilongjiang Province from May to September in 2019. Four irrigation treatments were set up at tillering stage, namely light shallow wet–dry irrigation (T1), moderate shallow wet–dry irrigation (T2), severe shallow wet–dry irrigation (T3) and shallow water irrigation (CK). The results showed that under water controlled conditions at tillering stage, the ineffective tiller numbers were reduced and earing rate was increased as compared to CK. The photosynthetic (Pn), stomatal conductance (gs) and transpiration rate (Tr) were decreased with the decrease in soil water potential while SPAD and intercellular CO2 concentration (Ci) were opposite. The Pn, gs, Tr and Ci in T1 and T2 treatments reached the normal level after re-watering at heading and milk-ripening stages. The yield (Y) and WUE in T1 treatment were higher than that of the other treatments, significantly (P < 0.05). Therefore, the study can provide the theoretical basis and reference for water-saving and high yield of rice in black soil region.

An Innovative Approach for Improving the Accuracy of Digital Elevation Models for Cultivated Land

The redistribution of solar radiation, temperature, soil moisture and heat by topography affects the physical and chemical properties of the soil and the spatial distribution characteristics of crop growth. Analyses of the relationship between topography and these variables may help to improve the accuracy of digital elevation models (DEMs). The purpose of correcting Shuttle Radar Topography Mission (SRTM) data is to obtain high-precision DEM data in cultivated land. A typical black soil area was studied. A high-precision reference DEM was generated from an unmanned aerial vehicle (UAV) and extensive measured ground elevation data. The normalized differential vegetation index (NDVI), perpendicular drought index (PDI) extracted from SPOT-6 remote sensing images and potential solar radiation (PSR) extracted from SRTM. The interactions between topography and NDVI, PDI, and PSR were analyzed. The NDVI, PDI and PSR in June, July, August and September of 2016 and the SRTM were used as independent variables, and the UAV DEM was used as the dependent variable. Linear stepwise regression (LSR) and a back-propagation neural network (BPNN) were used to establish an elevation prediction model. The results indicated that (1) The correlation between topography and NDVI, PSR, PDI was significant at 0.01 level. The PDI and PSR improved the spatial resolution of SRTM data and reduce the vertical error. (2) The BPNN (R21 = 0.98, root mean square error, RMSE1 = 0.54) yielded a higher SRTM accuracy than did the studied linear model (RMSE1 = 1.00, R21 = 0.90). (3) A series of significant improvements in the SRTM were observed when assessed with the reference DEMs for two different areas, with RMSE reductions of 91% (from 14.95 m to 1.23 m) and 93% (from 15.6 m to 0.94 m). The proposed method improved the accuracy of existing DEMs and could provide support for accurate farmland management.

Grass barriers for mitigating diffuse pollution within a source water area - A case study of Northeast China

Agricultural diffuse pollution caused by runoff and soil loss from cropland has been a serious environmental problem in the black soil area of Northeast China. While water and soil conservation measures have led to a sharp decrease in overland flow within source water sub-watersheds, they have, on the other end, affected the water security of agricultural and domestic use as the water storage capacity of downstream reservoirs decreases year by year. For this study, grass barriers, which are generally considered to have high sediment reduction efficiency, were evaluated for their efficiency as a mitigation measure of diffuse pollution within source water areas. Standard field plots were used to monitor two groups of grass barriers, alfalfa (Medicago sativaL.) and native grass (dominated by Setaria viridis(L.)Beauv.), and slope gradients (3° and 5°) under natural rainfall events over the 2012–2015 period. The results indicated that, during the maize (Zea maysL.) growing season, runoff and sediment reduction efficiencies for the alfalfa barrier were 37.91 % and 62.30 %, respectively. And more than 50 % of the nutrient loads (e.g., total nitrogen (TN), total phosphorus (TP), and nitrate (NO3--N)) could be removed by the alfalfa barrier. The environmental loads mitigation efficiency of grass barrier in spring was relatively low and unstable. Both slope and barrier width had a significant impact on the water and soil conservation function of grass barriers, while rainfall intensity and grass type were mainly related to runoff reduction. Overall, these finding could provide some specific recommendations for future grass barrier design and large-scale application in a source water area of Northeast China.

Effects of multifunctional plant rhizosphere promoting bacteria on maize growth in black soil areas in Northeast China

The application of microbial fertilizer plays an important role in improving soil restoration and fertilizer utilization. The effects of microbial fertilizer are greatly affected by crop genotypes and ecological conditions. Little is known about the effects of microbial fertilizers on maize production in Northeast China. To develop microbial fertilizer specific to the black soil and the climate characteristics of Northeast China, we isolated five plant rhizosphere-promoting bacteria (PGPR), named as MZ1, MZ2, MZ3, MZ4 and MZ5, with different degrees of biological functions such as IAA synthesis, phosphate-solubilizing, potassium-solubilizing and siderophore-releasing, from the rhizosphere of maize field. The analysis of ecological adaptability showed that those five strains differed in salt resistance, drought tolerance, acid and alkali resistance, pesticide resistance. The 16S rRNA gene sequences analysis showed that the strains MZ1, MZ2, MZ3, MZ4 and MZ5 belonged to the genus of Sphingomonas, Enterobacter, Pseudomonas, Bacillus and Rhizobium, respectively. In maize field experiment with 50% nitrogen fertilizer reduction, the inoculation with MZ1, MZ3 and MZ5 increased grain yield by 19.9%-25.0%. MZ1, MZ3, and MZ5 could be used as microbial fertilizers for maize in Northeast China.

Dynamic model of crops’ normalized difference vegetation index in central federal district environment

The article describes a mathematical model which represents dynamics of the normalized difference vegetation index for winter wheat plantings in central black soil areas. As opposed to the approaches considered during our theoretical study, which, as a rule, are based on averaged data related to respectively vast territories (districts, regions, agricultural enterprises), this article describes a model which relates to rather small areas, namely to particular fields measuring 30-200 ha. The multiplicative model under consideration takes into account two opposite tendencies in the development of winter wheat: the process of phytomass increase and the process of plastic substances production. Parameters of the suggested model were estimated for winter wheat plantings in central black soil area on the fields with different levels of productivity for 2017 in accordance with normalized difference vegetation index data. We estimated the parameters by least square method. We performed model functional tests on the basis of the data received during remote sounding of the soil at more than one hundred of fields in Central Federal District. The test results are very promising. The suggested model allows for estimation of ripening period and the time of harvesting. The model can be applied for approximation of normalized difference vegetation index missing values, as well as for estimation of time required to attain maximum index value and, consequently, for forecasting of harvesting terms.

Effect of Extending Seedling-raising Period on Yield of Transplanting Sugar Beet (Beta vulgaris) in Black Soil Area of Northeast China

Paper pot seedling-raising technique is generally regarded as a high-yield strategy for sugar beet (Beta vulgaris) because it can accelerate leaf formation in early spring. But little is known about the optimal seedling-raising period in black soil area of Northeast China. In order to investigate the effect of extension of seedling-raising duration on yield of sugar beet, two field trials were carried out in 2011–2012 in black soil area of Northeast China. The results showed that leaf and root yield formation could well be described by thermal time in the whole season. The extension of seedling-raising period was helpful to cultivate good quality seedlings. The transplanted sugar beet with 35–40 days seedling-raising period had the highest yield, with average yield ranging from 60.5 to 62.7 t ha−1, 10.4–13.6% higher than that with 25 days seedling-raising period. There were no detectable differences in seedling-raising periods for sugar concentration. In a regular year, it was suggested that transplanting sugar beet in black soil area of Northeast China should be sown before April 8 and raised for 35–40 days in greenhouse in order to obtain a marked yield increase.

K 12 (TKA 9102/3) - A high yielding superior medium staple Gossypium arboreum cotton variety suited for rainfed vertisol tracts of Tamil Nadu

TKA 9102/3 is a high yielding superior medium staple G.arboreum cotton culture developed at Agricultural Research Station, Kovilpatti in the year 2017 for winter rainfed vertisol tracts of Tamil Nadu. It is also suitable for low rainfall zone (&lt;250 mm rainfall during cropping season), marginal fertility areas of coastal belt and black cotton soil tracts of Tamil Nadu. TKA 9102/3 is a hybrid derivative of the cross between K 11 and K 9. It has recorded an average seed cotton yield of 193 kg/ha as against the existing variety K 11 (1066 kg/ha). The yield of TKA 9102/3 is 11.9 per cent higher than K 11. TKA 9102/3 recorded moderate boll weight (2.7 g) and superior medium staple fibre quality of 27.7 mm 2.5 % span length and bundle strength of 22.1 g/tex than check K 11 (24.0 mm and 21.4 g/tex). TKA 9102/3 is resistant to leaf hopper and moderately resistant to thrips. It is also tolerant to drought and has recorded the maximum yield potential of 2365 kg kapas per hectare under rainfed condition. Hence, the culture TKA 9102/3 was released as K 12 for the coastal rainfed and black cotton soil areas of Tamil Nadu during 2017 from Agricultural Research Station, Kovilpatti.

Effects of Polyacrylamide on Runoff and Sediment Characteristics of Slope in Northeast Black Soil Area

Soil erosion caused by hydraulic erosion has become the main driving force to destroy the ecosystem and has become a worldwide environmental problem. The effect of polyacrylamide (PAM) on slope erosion characteristics in black soil area was studied under different conditions. The method of artificial simulation of rainfall was adopted. At 4 slopes and 5 PAM concentrations, the rainfall lasted 60min and the rainfall intensity was 80mm/h. The results show that when the rainfall intensity and underlying surface conditions are the same, the slope increases from 10° to 25°, the average runoff on the slope increases first and then decreases, and the sediment yield increases with the increase of the slope. The sediment yield on the 25° slope is 1.64 times that of the 10° slope. With the same rainfall intensity and slope compared with bare land, the concentration of Polyacrylamide in 2g / m2 increased to 5g / m2, and the average yield decreased by 10.6% to 20%. The average sediment yield decreased with the increase of the concentration, which was 20.4%∼52.5% lower than that of the bare land. The variation law of PAM and bare slope sediment yield can be described by power function. Compared with the total sediment yield of PAM and bare slope, PAM is obviously decreased. The bare slope surface is mainly characterized by splash erosion and surface erosion. The application of PAM can reduce the erosion area of slope compared with bare slope, which plays an important role in corrosion prevention.

Screening of rhizosphere growth promoting bacteria and their growth promoting ability of sunflower in cold black soil area

High efficient growth promoting bacteria were screened from the rhizosphere soil of sunflower in the cold black soil area, and their growth promoting ability was tested to obtain the strains with comprehensive growth promoting ability. The phosphate solubilizing bacteria were screened out by inorganic phosphate bacteria culture medium, the phosphate solubilizing ability of the strain was determined by mo sb anti chromogenic method, the indoleacetic acid producing ability of the strain was determined by salkowski method, the iron carrier producing ability of the strain was determined by CAS method, and the growth promoting ability of the strain was evaluated comprehensively. Eleven strains of phosphate solubilizing bacteria were isolated and screened from soil samples. Among them, strain WP2 had the strongest phosphate solubilizing ability, and the concentration of phosphate radical was 12.75 μg/mL; strain WP1 had the strongest indoleacetic acid producing ability, and the concentration of indoleacetic acid was 25.37μg/mL; strain WP1 had the strongest iron producing ability, with Su = 72.76%, and the strength was 4+. It was found that WP1, WP2 and WP10 had strong ability of promoting growth and had strong potential of development and utilization. The above results can provide excellent strains for the development and promotion of special bio fertilizer suitable for the cold black soil.

Effects of soil erosion and land use patterns on the characteristics of soil water and gas transport in the black soil region

Soil erosion is one of the main causes for the degradation of black soil in Northeast China. Understanding the differences of soil water and air transport under different land use patterns can provide scientific basis for efficient utilization and protection of soil and water resources in the black soil area. In this study, we examined the in-situ soil saturated hydraulic conductivity, air permeability and relative gas diffusion of 0-5 cm soil layer in three typical land use patterns (cropland, woodland, abandoned land) in the Northeast black soil area and explored the impacts of soil erosion and land use pattern on water and gas transport. Results showed that there were significant differences in soil water and air transport between different eroded croplands and between different land use patterns. Soil bulk density of serious erosion cropland was higher than that of other lands, and that of ungraded cropland was significantly lower than other lands. Compared with the ungraded cropland, soil bulk density in the light erosion cropland, the moderate erosion cropland and the serious erosion cropland increased by 12.7%, 17.6% and 39.2%, saturated hydraulic conductivity decreased by 84.4%, 53.7% and 12.7%, air permeability decreased by 94.6%, 64.4% and 14.0%, and relative gas diffusion decreased by 91.3%, 82.6% and 4.3%, respectively. The saturated hydraulic conductivity, air permeability and relative gas diffusion of pine forest decreased by 86.5%, 83.0% and 91.3% respectively compared with that of ungraded cropland, saturated hydraulic conductivity, air permeability and relative gas diffusion of sea-buckthorn forest decreased by 51.7%, 45.6% and 82.6%, and saturated hydraulic conductivity, air permeability and relative gas diffusion of abandoned land decreased by 16.2%, 1.4% and 73.9% respectively compared with that of ungraded cropland. In addition, the measured result of soil air permeability and relative gas diffusion could be used to estimate saturated soil hydraulic conductivity. Soil water and gas transport characteristics were significantly affected by soil erosion and land use pattern.

Spatial Variability of Soil Moisture in Relation to Land Use Types and Topographic Features on Hillslopes in the Black Soil (Mollisols) Area of Northeast China

Soil moisture, as a crucial factor in the eco-hydrological process, is of great importance for food production, land management in response to water and soil loss, geomorphic processes, and environmental protection. Understanding the spatial variability of soil moisture induced by different land use types and topographic features is conducive to advancing the adjustment of the land use structure and preventing soil erosion on the hillslopes in the black soil (Mollisols) area of Northeast China. Classical statistical methods and Canonical Correspondence Analysis were used to analyze the spatial heterogeneity of soil moisture at 0–20, 20–40, and 40–60 cm on slopes, to identify the main controlling factors and their relative contributions. The results suggested that: the average soil moisture content followed a decreasing order of grassland &gt; shrubland &gt; soybean land &gt; maize land &gt; adzuki bean (Vigna angularis) land &gt; forestland; the profile soil moisture content (SMC) patterns could be divided into four types, related to the comprehensive influence of vegetation types, root system characteristics, and topographic attributes; the spatial variability of soil moisture was strongly influenced by slope gradient, followed by land use types and elevation and slope position, while slope aspect had the least impact; and finally, land use type had a greater impact on the deep layer than the surface layer, while on the contrary, the influence of the topographic attributes on the deep layer was smaller than on the surface layer. Land use types and topographical elements work together on the soil moisture variability and vertical patterns at differing depths. This study provides an insight into policy making of land resource management and can be used in the modeling of hydrological processes.