Northeast Region Of China Research Articles

Quantifying the effect of freeze–thaw on the soil erodibility of gully heads of typical gullies in the Mollisols region of Northeast China

The soil erodibility of gully headwalls is a critical factor influencing gully erosion. In some cold regions, the soil of gully headwalls is subjected to a bidirectional freeze–thaw effect (FT), while the quantification of the influence of FT on the soil erodibility of gully heads is unclear. Therefore, five typical and representative gullies developed in farmlands (GF1 and GF2), along unpaved road (GR), in the woodland (GW) and in stabilized gully bed (GS) were selected to quantify the influence of FT on the soil erodibility of gully heads reflected by five soil erodibility parameters including the K factor (K), soil disintegration rate (SDR), mean weight diameter (MWD), soil shear strength (SS) and saturated soil hydraulic conductivity (SHC). A comprehensive soil erodibility index (CSEI) was constructed by combining the above five soil erodibility parameters. This study revealed that FT significantly affected the five soil erodibility parameters and CSEI, of which the K and SDR increased by 22.7 % and 52.3 %, respectively, but the MWD, SHC and SS decreased by 29.3 %, 30.4 % and 26.1 %, respectively. The change in soil erodibility of the gully heads was closely related to the soil and root properties, of which the contribution of roots to the change in soil erodibility of gully heads was increased by 78.5 % after FT on average. Furthermore, FT significantly increased the CSEI at depths of 0–50 cm in GF1, GF2 and GR, and at depths of 0–80 cm in Gw and GS. FT increased the CSEIs of the five gully heads by 20.1 %-37.3 %, with an average of 26.1 %. Evidently, the organic matter content (OMC), soil texture and temperature dominated the change in the CSEI, of which the extremely low temperature and temperature rangeability during freeze–thaw period exhibited the greatest impact on the soil erodibility of the gully heads.

Multi-Scenario Land Use Change Simulation and Spatial Response of Ecosystem Service Value in Black Soil Region of Northeast China

Simulating the spatial response of ecosystem service value (ESV) caused by land use change in Heilongjiang Province under different scenarios in the future is of great significance for ensuring ecological security and sustainable development in the region. Heilongjiang Province, an important grain-producing region in China, is taken as the research area in this study. Five land use maps (2000, 2005, 2010, 2015, and 2020) were used to evaluate the change of ecosystem service value in Heilongjiang Province in the past 20 years. In addition, the area of each land use type under different future scenarios was predicted by Markov model and MOP model, the future land use pattern was simulated based on PLUS model, the ESV under different scenarios was calculated, and the spatial distribution and the degree of ESV clustering were further explored. The results show that: (1) During 2000–2020, the built-up land in Heilongjiang Province continued to grow, with a total increase of 5076 km2 during the 20-year period, the area of water continued to grow, the area of unused land gradually decreased, and the area of farmland and forest land changed less. (2) During the study period, the ESV in 2000, 2005, 2010, 2015, and 2020 were 1320.8 billion yuan, 1334.5 billion yuan, 1342.1 billion yuan, 1327.6 billion yuan, and 1328.4 billion yuan, respectively. Generally, it shows a fluctuating trend. (3) The ESV of natural development scenario (NDS), economic priority scenario (ERS) and ecological protection scenario (EPS) are 1334.3 billion yuan, 1254.8 billion yuan and 1455.6 billion yuan, respectively. The ESV of different scenarios is quite different. (4) The spatial distribution of ESV was higher in the northwest, central, and southeast, and lower in the east and west. The hot and cold spots of ESV are widely distributed and the degree of polymerization is high. The methods and conclusions of this study can provide scientific reference for the optimization of national spatial pattern and the formulation of sustainable development policy.

Changes in drought characteristics over China during 1961–2019

Drought is extremely complex and can be influenced by various factors. This study uses Penman-Monteith (PM) method to calculate the potential evapotranspiration and get the monthly drought metric of Standardized Precipitation-Evapotranspiration Index (SPEI) across China during the period of 1961–2019. Results show that the regions of the west of Northwest China (WNWC), Northeast China (NEC), and South China (SC) are reported to experience a wetting trend, while the droughts in the regions of the east of Northwest China (ENWC), North China (NC), and Southwest China (SWC) deteriorated over the past decades. Seasonally, the significant wetting trends mainly occurred in summer, autumn, and winter for WNWC, while mainly in winter for the region of NEC. Additionally, the droughts in China show an obvious interdecadal variability, with more severe droughts for the periods of 1961–1979 and 2000–2019, but with relatively fewer events in the period of 1980–1999. During the 1960 s and 1970 s, droughts in China are observed to mainly happen in summer and winter, while the droughts mainly occurred in autumn and winter during the 1980 s and 1990 s. Since the early 21st century, both the frequency and intensity of spring droughts have increased obviously and played a dominant role in seasonal droughts. Further studies indicate that the drought changes in southern China are mainly affected by the precipitation anomalies, while that in northern China are mainly influenced by the temperature and wind speed anomalies. Hence, our analyses provide theoretical basis for further understanding the drought changes and the prevention control of drought disasters in China.

Innovation Potential of Private Enterprises in Northeast China Region

The article is devoted to the study of the impact of innovation on private enterprises in the Northeast region of China. The author justifies the relevance and significance of the research topic. In order to revitalize the economy of Northeast China, it is necessary for local enterprises to improve the efficiency of their production, through independent reform and innovative development. However, as a major part of the market economy, private enterprises face many difficulties in the process of innovation. However, private enterprises, as the backbone of the market economy, face many difficulties in the implementation of innovative tasks and projects. They lack the intrinsic motivation of the three basic elements of innovation — entrepreneurship, corporate innovation culture and corporate innovation system. The Chinese government attaches great importance to the economic development of the Northeast region, implementing a set of government support measures aimed at the development of the region. Based on the systems theory and social learning theory of Albert Bandura, the enterprises in question should competently use corporate policies to increase the motivation of employees to implement innovation in production, and also use a fair corporate environment with minimal resistance and close attention of employees as a starting point to stimulate innovative behavior of employees, improve the effectiveness of individual and corporate innovation, and as a result, promote other cultures.

Changes in Soil Freeze Depth in Response to Climatic Factors in the High-Latitude Regions of Northeast China

The changing climate in recent decades has caused rapid, widespread frozen ground degradation of the cryosphere, and changes in frozen ground may largely affect the ecosystem function. This study presents the long-term shrinkage of frozen ground, driven forces and resultant ecological impacts at three high-latitude sites (namely Nenjiang, Jiagedaqi, and Tahe, from low to high latitude) in Northeast China, an area that has received less attention in previous permafrost studies. As the key indicators of frozen ground, the ground surface and subsurface soil temperature (down to 40 cm) were found to increase in the period from the 1970s to the 2000s. The annual mean air temperatures at observation sites have increased significantly at rates of 0.24~0.40 °C/decade from 1971 to 2019, and were found to be negatively correlated to the change in soil freeze depth at the Jiagedaqi and Tahe sites. The annual snow depth at Jiagedaqi was found to decrease at a rate of 1.8 cm/decade, and positively correlate to the soil freezing index. The vegetation status of the three watersheds improved, as indicated by the increased normalized difference vegetation index (NDVI) from 2000 to 2017. Our results can make a valuable contribution to knowledge of climate–frozen ground interactions, and can highlight the importance of examining such interaction for permafrost protection in similar high-latitude permafrost-dominated basins.

Estimation of Spring Maize Evapotranspiration in Semi-Arid Regions of Northeast China Using Machine Learning: An Improved SVR Model Based on PSO and RF Algorithms

Accurate estimation of crop evapotranspiration (ETc) is crucial for effective irrigation and water management. To achieve this, support vector regression (SVR) was applied to estimate the daily ETc of spring maize. Random forest (RF) as a data pre-processing technique was utilized to determine the optimal input variables for the SVR model. Particle swarm optimization (PSO) was employed to optimize the SVR model. This study used data obtained from field experiments conducted between 2017 and 2019, including crop coefficient and daily meteorological data. The performance of the innovative hybrid RF–SVR–PSO model was evaluated against a standalone SVR model, a back-propagation neural network (BPNN) model and a RF model, using different input meteorological variables. The ETc values were calculated using the Penman–Monteith equation, which is recommended by the FAO, and used as a reference for the models’ estimated values. The results showed that the hybrid RF–SVR–PSO model performed better than all three standalone models for ETc estimation of spring maize. The Nash–Sutcliffe efficiency coefficient (NSE), root mean square error (RMSE), mean absolute error (MAE) and coefficient of determination (R2) ranges were 0.956–0.958, 0.275–0.282 mm d−1, 0.221–0.231 mm d−1 and 0.957–0.961, respectively. It is proved that the hybrid RF–SVR–PSO model is appropriate for estimation of daily spring maize ETc in semi-arid regions.

Reconstructing the ecological restoration pattern from the perspective of ecosystem health assessment in a typical black soil region of Northeast China

Assessments on the spatial pattern of ecological restoration potential provide insights into the current status of ecosystem health, facilitate the identification of hotspots of ecosystem degradation, and further serves as a link that bridges regional ecological planning with specific restoration efforts. The goal of this study was to reconstruct the ecological restoration pattern, through establishing an ecosystem health assessment model encompassing four elements of vigor, organization, resilience and service of an ecosystem. Siping City, a typical black soil region located in central Jilin Province of Northeast China, was selected as the study area, and ecological protection and restoration units were identified based on temporal changes in ecosystem health levels from 2000 to 2020. Getis-Ord Gi* analysis was adopted to classify the restoration zones and depict the spatial pattern of ecological restoration. From 2000 to 2020, the ecosystem health index of Siping City generally increased from 0.49 to 0.51 due to increases in forestland area and precipitation, but a fraction of suburban areas also experienced decreases. Four different restoration zones were delineated, including the windbreak and sand-fixing zone in the western part, the black soil protection and reclamation zone in the middle part, the Daheishan ecological shelter zone in the central and eastern part, and the water restoration zone in the eastern part, which account for 28.12%, 37.05%, 16.53% and 18.29% of the total area. The protection units covered an area of 1,189.83 km2 and the restoration units covered an area of 2009.83 km2, which could be further classified into 10 types and accounted for 31.24% of the total area. It was suggested that the restoration methods applied to different units should be tailored towards specific restoration objectives. This proposed methodological framework serves as a basis for reconstructing ecological restoration in the black soil region, and a reference for making restoration plans elsewhere.

Spatial Distribution of Soil Organic Carbon and Total Nitrogen in a Micro-Catchment of Northeast China and Their Influencing Factors

This study aimed to analyze the spatial distribution of soil organic carbon (SOC) and total nitrogen (STN) in a micro-catchment area comprising farmland and a gully with vegetation restoration (artificial forest and grassland) and their influencing factors. We surveyed a total of 52 topsoil sampling sites to measure the SOC and STN content, as well as topographical factors (elevation, curvature, slope gradient, and aspect), soil properties (bulk density, aggregate distribution, soil texture, and soil moisture), and land use and management. We used traditional statistical and geostatistical methods to analyze the spatial variability of SOC and STN. The results of this study indicate that SOC and STN content varied moderately across the entire micro-catchment area, with greater values in the west (gully head area) than in the east (gully mouth area). Additionally, SOC and STN were significantly positively correlated with soil water content, >2 mm size aggregate fraction, and elevation, but negatively correlated with <0.053 mm size fraction. Land use types also influenced the spatial distribution of SOC and STN contents, with the highest averages of SOC and STN content found at the edge of farmland road and grassland, respectively, and the lowest values in bare land. This study provides a valuable supplement to the understanding of SOC and STN in micro-catchment areas, and the research results also support the evaluation of the impact of gully erosion control on SOC and STN dynamics after vegetation restoration. Overall, vegetation restoration should be adopted for gully erosion control and sustainable agricultural development in the Mollisols region of Northeast China.

Stand Structure Management and Tree Diversity Conservation Based on Using Stand Factors: A Case Study in the Longwan National Nature Reserve

The management of stand structure and the protection of species diversity are crucial to forest ecosystem service functions. Changbai Mountain is one of the three major forest regions in Northeast China, and understanding the characteristics of stand structure and the allometric relationship between stand structure variables and the correlation between stand factors and species diversity is the basis for achieving effective forest management and ecological function improvement. In this study, the typical deciduous broad-leaved mixed forest and coniferous and broad-leaved mixed forest of the Longwan Nature Reserve in the Changbai Mountain were taken as the research objects, and the stand structure and diversity were investigated in detail. Allometric growth equations were established using the breast height diameter (DBH), tree height, and crown width of the main dominant species. Pearson correlation analysis was conducted on the stand structure and diversity of the forest community. The experimental results showed that young forests with small diameters and small individuals were the main part of the stands. Optimal allometric growth models of the main tree species (Acer mandshuricum, Ulmus davidiana var. japonica, Juglans mandshurica, Acer mono, and Tilia amurensis) were 0.807D0.646, 0608D0.381H0.390, 0.502D0.533H0.295, 0.795D0.540H0.157, and 0.541D0.484H0.301, respectively, with R2 values ranging between 0.6 and 0.8, indicating a good fit for the models. Furthermore, tree density, crown width, and DBH were the main factors affecting tree diversity. The research results will provide theoretical support for the efficient management of forest stand structure and diversity conservation in the Longwan Reserve.

Evaluation of monthly-scale soil erosion spatio-temporal dynamics and identification of their driving factors in Northeast China

Soil water erosion has caused an enormous damage to agricultural production and ecosystems worldwide. Soil erosion exhibits certain seasonal variation patterns within year under the influence of multiple factors. In this study, we calculated the multi-year average monthly-scale soil erosion modulus from 2001 to 2019 to evaluate the soil erosion risk using the revised universal soil loss equation (RUSLE) in the black soil region of Northeast China. The results showed that the average annual soil erosion modulus in this region was 8.53 t•ha−1•year−1, and the average monthly soil erosion modulus was 0.78 t•ha−1•month−1. The months of April-July and October were identified as critical periods for erosion, with erosion modulus values of 1.17, 1.89, 1.61, 1.13, and 0.93 t•ha−1•month−1 during these five months, respectively. High soil erosion was mainly distributed in southern Liaoning province and western Inner Mongolia, and these high erosion areas were mostly distributed in the regions with complex landforms, in grasslands, and in the southern temperate climatic zone. Among multiple driving factors, the topographic factor LS (L = slopelength,S = slopesteepness) was one of the dominant factors determining the spatial distribution pattern of soil erosion with 30 % of the contribution. The rainfall erosivity (R) and cover management (C) were the major factors driving significantly the intra-annual variation of soil erosion in Northeast China with 27.2 % and 28.9 % of the contribution, respectively. The intra-annual erosion varied with the rainfall and the vegetation growth, and the period of high erosion occurs in the early part of the wet season when the rainfall intensity increases and the vegetation growth is insufficient to protect the soil. Our findings highlight the need to take dynamic factors into consideration in the RUSLE model and the importance for identifying the areas at high erosion risk so as to take soil conservation actions.

Drought Risk Assessment in China Based on Water Resources System

Based on the risk theory, drought hazard, drought exposure and drought vulnerability were evaluated by precipitation, water consumption and water supply, respectively. A model of drought risk assessment method was thus proposed and it is finally applied in China. The results showed that the drought hazard index in the eastern monsoon region was higher, the drought exposure index in the Yangtze River Economic Belt, north China Plain, Heilongjiang Province, Inner Mongolia Autonomous Region and Xinjiang Autonomous Region was higher, the drought vulnerability in the southern region is higher. The middle and lower reaches of the Yangtze River, north China Plain, southwest China, Heilongjiang province in northeast China and Xinjiang Autonomous Region in northwest China are at high risk of drought.

Regional differences in the green use level of cultivated land in the Heilongjiang reclamation area

Scientific understanding of the connotation of Green Use of Cultivated Land (GU-CL) is important to promote sustainable use of cultivated land. This study aims to analyze the regional heterogeneity of the Green Use Level of Cultivated Land (GUL-CL) in Heilongjiang Reclamation Area (HRA). Using entropy power method and coupled coordination degree model, statistical analysis was carried out based on the data of the HRA in 2020. The results show that the degree of GUL-CL in the study area is generally well-developed, but internal differences exist. Specifically, the GUL-CL ranges from 0.590 to 38.179, with a mean value of 8.818. Additionally, 29.204% of the total farms are above the higher level, mainly in Jiansanjiang and Baoquanling. In environmental friendliness practices, the high-level areas are concentrated primarily on the Songnen Plain Reclamation Area. Or, the Sanjiang Plain Reclamation Area positively presents significant effects on resource conservation. In the study area, spatial intensification and output efficiency are relatively balanced. The coupling coordination degree of green use of cultivated land (GU-CL) (0.20–0.50) is at a low coupling coordination stage. Consequently, this study can provide practical knowledge for the GU-CL in the black soil region of Northeast China.

Film-mulched drip irrigation achieves high maize yield and low N losses in semi-arid areas of northeastern China

Traditional flood irrigation (FI) and excessive nitrogen (N) fertilizer application are the main causes of unrealized yield potential and low water and N use efficiency (NUE) of maize in semi-arid regions of northeast China. The yield gap, NUE, and N losses were adopted to quantify the yield potential and optimal N fertilizer rate of maize under film-mulched drip irrigation (MDI), and different N fertilizer levels (0, 70, 140, 210, 280, and 350 kg N ha−1, denoted as N0, N70, N140, N210, N280, and N350, respectively) were applied under MDI and FI conditions from 2018 to 2020. The maize yield first increased and then decreased with increasing N fertilizer in both MDI and FI, but the highest yield was 23.5% higher in MDI (210 kg N ha–1) compared to that in FI (280 kg N ha–1). Compared with FI, MDI significantly increased the proportion of N accumulation and its contribution to grain N at the post-silking stage, and improved water productivity and NUE at the same N rate. Under the conditions of obtaining the highest yield treatment (N210 under MDI and N280 under FI), MDI increased N recovery efficiency (REN), agronomic efficiency (AEN), partial factor productivity (PFPN), water productivity, and irrigation water productivity by 29.2% points, 16.2 kg kg−1, 22.3 kg kg−1, 1.3 kg m−3, and 4.4 kg m−3, respectively. In addition, MDI significantly reduced NO3-N leaching in the 60–200 cm soil layer and apparent N loss, while NO3-N content in the 0–60 cm layer increased over FI. The range of N fertilizer required to obtain high maize yield under MDI and FI were 199–220 and 236–260 kg ha−1, respectively, by simulating the relationship between the N fertilize rate and maize yield, apparent N loss, and REN. Overall, MDI resulted in a 24.3% higher maize yield, 27.4% points higher REN, 15.7% lower N fertilizer application, and 45.3% lower N loss compared to FI. Therefore, the N fertilizer application strategy of MDI in this study could achieve higher maize yield, water productivity, and NUE, and reduce the risk of soil NO3-N leaching in continuous maize cropping systems. The results of this study can provide a scientific basis for N fertilizer management under MDI in the semi-arid region of northeastern China.

Soil erosion resistance factors in different types of gully heads developed in four main land-uses in the Mollisols region of Northeast China

Soil erosion resistance of gully head determines gully headcut process and further affects gully erosion. However, few studies were conducted to clarify the vertical change in soil resistance of gully heads and its influencing factors, which is not conducive to the revelation of gully erosion mechanism and gully erosion prevention. Therefore, this study aimed to investigate the vertical change in soil resistance of six kinds of typical gully heads developed in farmland (Gf1, Gf2), woodland (Gw), grassland (Gg), abandoned land (Ga) and stable gully channel (Gz) and its influencing factors in the Mollisols region of Northeast China. Soil samples were collected at seven soil depths (0–10 cm, 10–30 cm, 30–50 cm, 50–80 cm, 80–120 cm, 120–160 cm, and 160–200 cm) of each type of gully heads (including three repetitions) to measure soil and root properties. Soil detachment rate (Dr) of gully head at seven soil depths was determined by a hydraulic flume experiment under five runoff shear stresses (4.02–10.89 Pa), and then soil erodibility (K) and critical shear stress (τ0) of gully heads at seven soil depths were calculated by the equation [Dr=K·(τ-τ0)]. Results showed that Dr and K of six types of gully heads increased firstly and then declined with soil depth increased and the most erodible position occurred at a changed depth of 50–100 cm of gully heads. On average, Dr of Gz was significantly 1.6–9.3 times greater than that of other types of gully heads. Dr of all gully heads was better simulated by stream power than by runoff velocity and runoff shear stress, and it was positively related to soil disintegration rate (DR) and negatively related to soil bulk density (SBD), saturated hydraulic conductivity (SHC), soil shear strength (SSS), mean weight diameter of aggregate (MWD) and root length density (RLD) significantly. The mean Ks of Gz and Gg were 1.5–7.8 times greater than that of other types of gully heads, and the K was positively related to DR but negatively related to SHC, SSS, MWD and RLD. τ0 showed a great fluctuation with soil layer and no significant difference occurred among six types of gully heads. τ0 was only related with SHC. Soil properties have the larger effect on Dr and K of gully heads than root characteristics, implying that it is not reliable to use only vegetation to control the gully headcut. It is suggested that the first consideration should be given to preventing soil from runoff scouring and improving soil erosion resistance of gully head.

Phytolith evidence for changes in the vegetation diversity and cover of a grassland ecosystem in Northeast China since the mid-Holocene

Accurate estimates of changes in the composition and diversity of grassland ecosystems, and an understanding of the mechanisms responsible, are essential for predicting future changes and for conservation planning. Here, we synthesize stratigraphic records of phytoliths, together with previously published pollen, diatom, carbonate and grain-size records, from a peat profile (LDBS) in the Songnen region of Northeast China. The results demonstrate that since the mid-Holocene this region was occupied by grassland, with C3 grasses always dominant but with C4 grasses progressively increasing. The species richness and plant cover were high and relatively stable for most of the studied interval, but they decreased significantly in the last ∼1,000 years. The long-term evolution of this grassland ecosystem was dominated by climate changes, but it was also affected by human activities and local habitat factors. The plant cover and several dominant plant taxa were climatically sensitive, while the C4 grasses also responded to changes in the water table and human activities. Species richness was relatively stable but it responded to long-term climatic changes. Phytolith-based reconstruction of Holocene plant community composition and diversity and their driving mechanisms can potentially be used to facilitate conservation planning in this temperate grassland ecosystem.

City-Level CH4 Emissions from Anthropogenic Sources and Its Environmental Behaviors in China’s Cold Cities

Distinguished features of cities influence the characteristics of CH4 emissions. A city-level emission inventory represents the characteristics of CH4 on a smaller scale, according to the special factors in each city. A city-level emission inventory was established to reveal the characteristics and source profile of CH4 emissions in the coldest province, which is a typical provincial cold region in northeast China. The dominant sources were identified for targeted cities. Rice cultivation, coal mining, oil and gas exploitation, and livestock are the dominant emission sectors. Emissions from other sectors, including wastewater disposal, biomass burning, landfill, etc. were also estimated. The provincial CH4 emissions increased gradually from 2003 to 2012, up to 2993.26 Gg with an annual increase rate of 2.85%; the emissions were 2740.63 in 2020. The emissions of CH4 in Harbin, Daqing, Jiamusi, and Hegang cities were higher than in the other nine cities, which were 337.23 Gg, 330.01 Gg, 328.55 Gg, and 307.42 Gg in 2020, respectively. Agriculture, including the rice cultivation, livestock, and biomass burning sectors contributed to 51.24–62.12% of total emissions, and the contributions increased gradually. Coal mining, oil and gas exploration, and fossil fuel combustion are energy-related sources, which contributed up to 37.91% of the total emissions, and the proportion kept decreasing to 23.87% in 2020. Furthermore, meteorological factors are especially relevant to the region, by which the differences of ambient temperature are over 60 °C (±30 °C). In the summer, CH4 emissions from the rice cultivation, biomass burning, livestock, and landfill sectors are obviously distinct from the heating period (winter), while few differences in CH4 emissions are found from wastewater disposal and the fossil fuel production sectors.

Mapping Maize Tillage Practices over the Songnen Plain in Northeast China Using GEE Cloud Platform

As the population grows, the development of conservation tillage offers a means of promoting the sustainability of agricultural engineering. Remote sensing images with high spatial and temporal resolutions enable the accurate monitoring of conservation tillage on a broad spatial scale, further promoting conservation tillage research. This paper describes using streamlined time series Sentinel-2 images based on the Google Earth Engine (GEE) cloud platform for mapping maize tillage practices in the Songnen Plain region of Northeast China. Based on the correlation with the normalized difference tillage index (NDTI) and maize residue coverage (MRC) data, the optimal time series and streamlining functions in the GEE cloud platform are determined. Estimates of MRC and the mapping of tillage practices in the Songnen Plain for 2019–2022 are then determined using GEE and a previous model. Geostatistical analysis using ArcGIS is applied to analyze the spatial and temporal distribution characteristics of MRC and conservation tillage over the Songnen Plain. The results show that time series images from 20–30 May achieve an r value of 0.902 and an R2 value of 0.8136 when using the median streamlining function. The mean MRC for the study area in 2022 is 2.3%, and an overall upward trend in conservation tillage is observed (from 0.08% in 2019 to 0.25% in 2022). Our analysis shows that MRC monitoring and conservation tillage mapping can be performed over a broad spatial scale using remote sensing technology based on the GEE cloud platform. Spatial and temporal information on farm practices provides a theoretical basis for agricultural development planning efforts, which can promote sustainable agricultural development.

Metagenomic strategies uncover the soil bioavailable phosphorus improved by organic fertilization in Mollisols

Microorganisms play essential roles in soil phosphorus (P) cycling and the regulation of P bioavailability, however, genetic information on microbial P cycling in response to nutrient inputs is largely unclear. Here, metagenomic sequencing and genome binning were used to investigate microbial functional traits under chemical and organic fertilization in three long-term field experiments across black soil region of Northeast China. The results revealed that manure amendments strongly affected microbial P cycle-related functional gene patterns, which were significantly and positively correlated with the contents of soil total P (TP) and available P (AP). Manure addition directly increased soil AP concentrations, and indirectly acted through the alterations of microbial functional genes involved in soil P cycling. Specifically, manure amendments consistently decreased abundances of phnC gene and increased gene abundances of phnP, opd, and phoN across three locations, suggesting the potentially inhibition of soil microbial P-uptake and transport and the promotion of soil microbial organic P- mineralization. Manure addition promoted microbial inorganic P-solubilization by enriching the ppa, gcd, and pqqC genes at two out of three locations, while chemical fertilizer (CF) addition slightly stimulated the functional gene abundances involved in microbial P-uptake and transport and P-starvation response regulation. In addition, soil AP content was negatively correlated with the phnC gene abundance but positively correlated with the gene abundances of opd and phoN. Moreover, 23 metagenome-assembled genomes (MAGs) were reconstructed covering all soil samples, all of which contained the phnC gene with the copy numbers varying from 1 to 19. Nevertheless, only bin44 had a negative correlation with soil AP (r = −0.361, P = 0.030) and could be considered as a potential indicator regulating microbial P-uptake and transport. Taken together, manure inputs positively accelerated microbial P-transformations, which was beneficial for the establishment of efficient P management strategies in sustainable-intensive agriculture.

RAC-GAN-Based Scenario Generation for Newly Built Wind Farm

Due to the lack of historical output data of new wind farms, there are difficulties in the scheduling and planning of power grid and wind power output scenario generation. The randomness and uncertainty of meteorological factors lead to the results of traditional scenario generation methods not having the ability to accurately reflect their uncertainty. This article proposes a RAC-GAN-based scenario generation method for a new wind farm output. First, the Pearson coefficient is adopted in this method to screen the meteorological factors and obtain the ones that have larger impact on wind power output; Second, based on the obtained meteorological factors, the Grey Relation Analysis (GRA) is used to analyze the meteorological correlation between multiple wind farms with sufficient output data and new wind farms (target power stations), so that the wind farm with high meteorological correlation is selected as the source power station. Then, the K-means method is adopted to cluster the meteorological data of the source power station, thus generating the target power station scenario in which the cluster information serves as the label of the robust auxiliary classifier generative adversarial network (RAC-GAN) model and the output data of the source power station is considered as the basis. Finally, the actual wind farm output and meteorological data of a region in northeast China are employed for arithmetic analysis to verify the effectiveness of the proposed method. It is proved that the proposed method can effectively reflect the characteristics of wind power output and solve the problem of insufficient historical data of new wind farm output.

Detection of Soil Erosion Hotspots in the Croplands of a Typical Black Soil Region in Northeast China: Insights from Sentinel-2 Multispectral Remote Sensing

Global efforts to restore the world’s degraded croplands require knowledge on the degree and extent of accelerated soil organic carbon (SOC) loss induced by soil erosion. However, the methods for assessing where and to what extent erosion takes place are still inadequate for precise detection of erosion hotspots at high spatial resolution. Drawing on recent advances in multitemporal Sentinel-2 remote sensing to create a bare soil composite that reflects erosion-induced variations in soil spectral signatures, this study attempted to develop a spectra-based soil erosion mapping approach to pinpoint eroded hotspots in a typical catchment located in the black soil region of northeast China as characterized by undulating landscapes. We built a ground-truth dataset consisting of three classes of soils representing Severe, Moderate and Low erosion intensity because of their inter-class contrasts in estimated erosion rates from 137Cs tracing. The spectral separability of different erosion classes was first tested by a combined principal component and linear discriminant analysis (PCA-LDA) against laboratory hyperspectral data and then validated against Sentinel-2-derived broadband spectra. The results show that PCA-LDA produced excellent classification accuracy (Kappa coefficient > 0.9) for both data sources and even more so for Sentinel-2 spectra, highlighting the effectiveness of the multitemporal approach to extract bare soil pixels. Further investigations into the spectral curves enabled identification of distinctive spectral features representative of shifting soil albedo and biochemical composition due to erosion-induced SOC mobilization. A classification scheme comprising the spectral features was applied to the Sentinel-2 bare soil composite for pixel-wise soil erosion mapping, in which 15.9% of the cropland area was detected as erosion hotspots, while the Moderate class occupied 65.4%. Comparing the erosion map to a NDVI map demonstrated the negative impact of soil erosion on crop growth from a spatial perspective, highlighting the potential of the proposed approach to aid targeted cropland management for food security and climate.