Northeast Region Of China Research Articles

Feasibility study on natural cold energy utilization in negative temperature underground space rock mass in permafrost region of northeast China

This study aims to investigate the possibility of using natural cold energy to establish a negative temperature space in northeast China by combining previous studies on natural cold energy and the ground temperature data obtained in northeast China. The temperature field changes of different rock masses after joining different depths of the subsurface space were simulated and analyzed by the finite element software COMSOL, exploring the feasibility of establishing underground spaces that maintain a temperature below 0 °C. The numerical simulation results show that the maximum melting depths of granite, limestone and basalt rocks are −6.4 m, −7.85 m and −5.34 m after adding underground space in the Genhe area under the proposed conditions. The temperature in the underground space is lower than the initial setting temperature after a year of temperature change influence, this indicates a surplus of cold energy, Therefore, the goal of maintaining negative temperature in the underground space year-round with zero energy consumption in the Genhe region is feasible. This paper provides new ideas for the utilization of cold resources in China and helps to better achieve the goal of sustainable development.

Integrated transcriptomics and metabolomics analyses reveal key genes and essential metabolic pathways for the acquisition of cold tolerance during dormancy in apple

Low temperature is a primary abiotic stress that significantly affects plant growth and development in the cool regions of Northeast China. It is the primary limiting factor in the development of the global apple industry. Numerous studies have investigated the alterations in transcriptional metabolism under low-temperature stress in various plants. However, research on the role of dormancy in regulating differences in cold tolerance among apple varieties is limited. Therefore, this study conducted a comprehensive analysis of the physiological and biochemical indices, transcriptome, and metabolome of the cold-tolerant variety ‘Hanfu’ (HF) and cold-sensitive variety ‘Naganofuji 2′ (CF) during endodormancy and ecodormancy. Under the low-temperature treatment, the cross-section of a 1-year-old branch of CF exhibited more severe browning than HF did, and the relative electrolyte leakage value of CF was higher than that of HF. Transcriptomics and metabolomics analysis revealed the key pathways of apples in response to low-temperature stress. Functional enrichment analysis showed that hormone signal transduction pathways and amino acid metabolism-related pathways were significantly enriched during endodormancy and ecodormancy, and these pathways were considered an important way for apples to respond to low-temperature freezing injury. The galactose metabolism pathway was significantly enriched only during endodormancy, while the membrane lipid metabolism pathway was significantly enriched only during ecodormancy. A gene co-expression network was constructed using weighted gene correlation network analysis, and six modules with biological significance were selected from the network. Among them, genes encoding transcription factors such as DREB1C/CBF2, JUB1, CCCH, and VIP1 are hub genes in different modules, which can be used as candidate genes to explore the network regulation pathway of apple response to low-temperature stress. Overall, these findings help to elucidate the molecular mechanism underlying freeze-tolerance in apples and provide novel insights into the regulatory network involved in the response of apples to low-temperature stress during dormancy.

Aggregate pore structure, stability characteristics, and biochemical properties induced by different cultivation durations in the Mollisol region of Northeast China

Long-term cultivation tends to cause thinning and even partial disappearance of Mollisols, which largely limits the sustainable development of agriculture. Cultivation duration greatly affects soil pore structure and biochemical properties of Mollisols. This study aims to elucidate the response of aggregate pore structure, stability, and biochemical properties of soil during degradation under long-term cultivation in Mollisols. The study involved four croplands with different cultivation durations (20, 40, 60, and 100 years; designated as AL20, AL40, AL60, and AL100, respectively) and one undisturbed forest land (FR). Samples were collected from three soil depths (0–20, 20–40, and 40–60 cm). Pore structure and biochemical properties were analyzed by X-ray Computed Tomography (CT) and standard method. As a result, the aggregate stability and biochemical properties of soil showed different degrees of degradation with the extension of cultivation duration. The mean weight diameter, soil organic carbon, total nitrogen, and microbial biomass carbon followed the order of AL20 > FR > AL40 > AL60 > AL100, while the soil bulk density exhibited an opposite trend. FR and AL20 showed significant differences from other sites (P < 0.05). The CT results revealed that total porosity and pore number approximately decreased with cultivation duration, with their maximum appearing in FR and minimum occurring in AL100. The pore shape and pore size of aggregates were dominated by elongated pores (> 65%) and porosity > 100 µm, respectively, both of which declined with increasing cultivation duration. Similarly, the fractal dimension and connectivity were the highest in FR. These results demonstrated that the pore structure of soil aggregates tended to be "simplified" with increasing cultivation duration. Soil structure index, which varied significantly with cultivation duration, was used to comprehensively evaluate the soil structure. The results provide important insights into soil structural degradation caused by long-term cultivation.

Spatial-Temporal Characteristics and Influencing Factors of Carbon Emissions from Land Use and Land Cover in Black Soil Region of Northeast China Based on LMDI Simulation

Land use change accounts for a large proportion of the carbon emissions produced each year, especially in highly developed traditional heavy industry and agriculture areas. In this study, we estimated the carbon emissions from land use in the Black Soil Region of Northeast China (BSRNC) from 1990 to 2020. We utilized seven periods of land use remote sensing image data spanning the years 1990, 1995, 2000, 2005, 2010, 2015, and 2020, with a 30-m grid resolution. Additionally, socio-economic data was incorporated into the analysis. The preprocessing of the remote sensing images involved several steps using ENVI 5.5, including radiometric correction, fusion, mosaic, and cropping. The land types were classified into six major categories: cropland, forest land, grassland, water area, construction land, and unused land, using the LUCC classification system. The IPCC coefficient method was used to calculate the trends in carbon emissions from land use, and the logarithmic mean Divisia index (LMDI) method was applied to analyze the influencing factors. The main conclusions are as follows: (1) From 1990 to 2020, the net carbon emissions from land use in the BSRNC increased from 11.91 × 104 t to 253.29 × 104 t, with an annual growth rate of 8.04%. (2) Spatially, land use carbon emissions exhibited an agglomeration pattern that gradually weakened and the regional emission differences gradually narrowed. (3) Income level was identified as the most important factor influencing land use carbon emissions in the BSRNC from 1990 to 2020. Land use efficiency had a inhibitory effect on net carbon emissions, reducing land use carbon emissions by 1730.63 × 104 t.

Investigating Drought Events and Their Consequences in Wildfires: An Application in China

Understanding the impact of drought on fire dynamics is crucial for assessing the potential effects of climate change on wildfire activity in China. In this study, we present a series of multiple linear regression (MLR) models linking burned area (BA) during mainland China’s fire season from 2001 to 2019, across seven regions, to concurrent drought, antecedent drought, and time trend. We estimated burned area using Collection 6 Moderate Resolution Imaging Spectradiometer (MODIS) and drought indicators using either the Standardized Precipitation Evapotranspiration Index (SPEI) or the self-calibrated Palmer Drought Severity Index (sc-PDSI). Our findings indicate that the wildfire season displays a spatial variation pattern that increases with latitude, with the Northeast China (NEC), North China (NC), and Central China (CC) regions identified as the primary areas of wildfire occurrence. Concurrent and antecedent drought conditions were found to have varying effects across regions, with concurrent drought as the dominant predictor for NEC and Southeast China (SEC) regions and antecedent drought as the key predictor for most regions. We also found that the Northwest China (NWC) and CC regions exhibit a gradual decrease in burned area over time, while the NEC region showed a slight increase. Our multiple linear regression models exhibited a notable level of predictive power, as evidenced by the average correlation coefficient of 0.63 between the leave-one-out cross-validation predictions and observed values. In particular, the NEC, NWC, and CC regions demonstrated strong correlations of 0.88, 0.80, and 0.76, respectively. This indicates the potential of our models to contribute to the prediction of future wildfire occurrences and the development of effective wildfire management and prevention strategies. Nevertheless, the intricate relationship among fire, climate change, human activities, and vegetation distribution may limit the generalizability of these findings to other conditions. Consequently, future research should consider a broad range of factors to develop more comprehensive models.

Changes of spring wind erosion based on wind erosion climate factor in the black soil region of Northeast China

Changes of spring wind erosion based on wind erosion climate factor in the black soil region of Northeast China

Critical thresholds for stage division of water erosion process in different ridge systems in mollisol region of Northeast China

Critical thresholds for stage division of water erosion process in different ridge systems in mollisol region of Northeast China

Screening of Cellulose and Pectin Degrading Actinomycetes and Evaluation of the Ability of Composite Flora to Degrade Corn Straw

Corn straw is a type of high-yield agricultural waste in China, but it has not been fully utilized owing to the diffi culty of degrading it and its low utilization rate. To improve the rate of degradation of corn straw and ensure that the straw resources are utilized more fully, we obtained an actinomycete that could simultaneously degrade cellulose and pectin from the cold region and black glebe of northeast China. The strain was named DPA-3-18, and its biological morphology and the sequence of its 16S rRNA were identifi ed. These analyses determined that it is a species of Streptomyces. The strain was combined with the lab-stored GS-30 and Bacillus subtilis to construct composite fl ora and conduct a single factor experiment. Signifi cantly higher factors were selected by Plackett Burman, and its fermentation conditions were optimized using response surface methodology. The optimal cultivation conditions were 4% of inoculum, a culture temperature of 28.51°C, an initial pH value of the medium of 7.43, and the oscillation during fermentation took place at 199.62 rpm. Under these conditions, 40.38% of the corn straw was degraded. F rom the results of SEM, we found that the structure of corn straw before degradation was complete, and the internal structure of corn straw after degradation with c omposite fl ora was destructed. The FT-IR spectra shown that the absorption peaks in all places of corn straw were reduced after degradation by the composite fl ora, the absorption peaks at 1640 cm-1 of corn straw after degradation were lower than that of before degrad ation, which confi rmed the decrease in cellulose. It indicated that the corn straw was signifi cantly degraded by the composite fl ora. This study contributed to understanding the change in corn straw after fermentation by the composite fl ora, and providing a theoretical basis for comprehensive utilization of corn straw.

Changes in carbon stock in the Xing’an permafrost regions in Northeast China from the late 1980s to 2020

ABSTRACT The degradation of Xing’an permafrost affects the stability of carbon pool and carbon emissions of the hemiboreal ecosystem in Northeast China. Due to the lack of long-term monitoring and detailed research, changes in carbon stock in terrestrial ecosystems in the Xing’an permafrost regions in Northeast China remain little known. In this study, we conducted more accurate simulations for the aboveground biomass (AGB), belowground biomass (BGB), dead organic carbon (DOC), and soil organic carbon (SOC) in the top 0–30 cm in permafrost regions in Northeast China using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. The model was applied using multi-period land use/land cover (LULC) and carbon density data from the late 1980s, 2000, 2010, and 2020. In Northeast China, the permafrost extent shrank rapidly by 108,600 km2 from 365,300 km2 in the 1980s to 256,700 km2 in the 2010s. The total carbon stock in permafrost regions in Northeast China was estimated at 4293.04 Tg C in the 1980s and at 4049.56 Tg C in the 2010s. Based on the permafrost extent of the 1980s, it was estimated that from the late 1980s to 2020, the LULC transformation resulted in the reduction of carbon stock by 33.53 Tg C, while the carbon fixation of vegetation growth increased by 1205.18 Tg C, i.e. a net carbon accumulation of 1149.15 Tg C. However, this estimate of the increasing carbon pool still awaits more systematic studies on the carbon budgets at larger soil depths of the top 2–3 m soils. This estimate can provide a timely preliminary estimate of the carbon pool as the baseline in the permafrost region of Northeast China for national and regional initiatives of carbon neutralization.

Comparing simulated tree biomass from daily, monthly, and seasonal climate input of terrestrial ecosystem model

Terrestrial ecosystem models are driven by climate data, which often have daily, monthly, and seasonal resolutions, but few have examined the effects of different temporal resolutions of climate data on modeled vegetation change. In this study, we investigated the effects of daily, monthly, and seasonal climate data on simulated tree-species biomass in a temperate forest region of northeast China. We conducted the study by using the LINKAGES terrestrial ecosystem model to quantify the relative importance of climate data resolutions (daily, monthly and seasonal) and interspecific competition on predicted tree-species biomass from short-term (<40 years) to long-term (70–100 years) simulations. Results showed that simulated tree-species biomass was sensitive to daily, monthly, and seasonal climate data. The difference in the simulated biomass based on daily vs. monthly climate data was not significant for tree species monocultures, suggesting that monthly climate data can be used as a surrogate for daily climate data in such simulations. However, interspecific competition amplifies the differences in biomass simulations under daily and monthly climate data, thus increasing prediction uncertainties in mixed-species systems. Results based on climate data at the seasonal resolution showed the greatest departure from the daily and monthly climate data, because averaging climate data over a season may result in unrealistic climate estimates for modeling tree biomass growth. Simulated biomass of shade-intolerant tree species was highest when using climate data at the daily resolution, followed by monthly and seasonal climate data. The opposite pattern was true for shade-tolerant tree species. At the early stages of simulated tree growth, inter-tree competition was a more important factor affecting the biomass of late-successional, shade-tolerant tree species while different temporal resolutions of climate data were more important for early- and mid-successional species. This trend reverses at the late stages of stand development. These results can help guide choosing climate input of terrestrial ecosystem models and aiding results interpretation.

Comprehensive Analysis of the NF-YB Gene Family and Expression under Abiotic Stress and Hormone Treatment in Larix kaempferi.

NF-YB, a subfamily of Nuclear Factor Y (NF-Y) transcription factor, play crucial role in many biological processes of plant growth and development and abiotic stress responses, and they can therefore be good candidate factors for breeding stress-resistant plants. However, the NF-YB proteins have not yet been explored in Larix kaempferi, a tree species with high economic and ecological values in northeast China and other regions, limiting the breeding of anti-stress L. kaempferi. In order to explore the roles of NF-YB transcription factors in L. kaempferi, we identified 20 LkNF-YB family genes from L. kaempferi full-length transcriptome data and carried out preliminary characterization of them through series of analyses on their phylogenetic relationships, conserved motif structure, subcellular localization prediction, GO annotation, promoter cis-acting elements as well as expression profiles under treatment of phytohormones (ABA, SA, MeJA) and abiotic stresses (salt and drought). The LkNF-YB genes were classified into three clades through phylogenetic analysis and belong to non-LEC1 type NF-YB transcription factors. They have 10 conserved motifs; all genes contain a common motif, and their promoters have various phytohormones and abiotic stress related cis-acting elements. Quantitative real time reverse transcription PCR (RT-qPCR) analysis showed that the sensitivity of the LkNF-YB genes to drought and salt stresses was higher in leaves than roots. The sensitivity of LKNF-YB genes to ABA, MeJA, SA stresses was much lower than that to abiotic stress. Among the LkNF-YBs, LkNF-YB3 showed the strongest responses to drought and ABA treatments. Further protein interaction prediction analysis for LkNF-YB3 revealed that LkNF-YB3 interacts with various factors associated with stress responses and epigenetic regulation as well as NF-YA/NF-YC factors. Taken together, these results unveiled novel L. kaempferi NF-YB family genes and their characteristics, providing the basic knowledge for further in-depth studies on their roles in abiotic stress responses of L. kaempferi.

Organic Matter Retrieval in Black Soil Based on Oblique Extremum Signatures

How to extract the indicative signatures from the spectral data is an important issue for further retrieval based on remote sensing technique. This study provides new insight into extracting indicative signatures by identifying oblique extremum points, rather than local extremum points traditionally known as absorption points. A case study on retrieving soil organic matter (SOM) contents from the black soil region in Northeast China using spectral data revealed that the oblique extremum method can effectively identify weak absorption signatures hidden in the spectral data. Moreover, the comparison of retrieval outcomes using various indicative signature extraction methods reveals that the oblique extremum method outperforms the correlation analysis and traditional extremum methods. The experimental findings demonstrate that the radial basis function (RBF) neural network retrieval model exposes the nonlinear relationship between reflectance (or reflectance transformation results) and the SOM contents. Additionally, an improved oblique extremum method based on the second-order derivative is provided. Overall, this research presents a novel perspective on indicative signature extraction, which could potentially offer better retrieval performance than traditional methods.

Evaluation and Driving Force Analysis of Cultivated Land Quality in Black Soil Region of Northeast China

Evaluation and Driving Force Analysis of Cultivated Land Quality in Black Soil Region of Northeast China

Inter-Continental Transfer of Pre-Trained Deep Learning Rice Mapping Model and Its Generalization Ability

Monitoring of rice planting areas plays an important role in maintaining food security. With powerful automatic feature extraction capability, crop mapping based on deep learning methods has become one of the most important research directions of crop remote sensing recognition. However, the training of deep learning models often requires a large number of samples, which restricts the application of these models in areas with a lack of samples. To address this problem, based on time-series Sentinel-1 SAR data, this study pre-trained the temporal feature-based segmentation (TFBS) model with an attention mechanism (attTFBS) using abundant samples from the United States and then performed an inter-continental transfer of the pre-trained model based on a very small number of samples to obtain rice maps in areas with a lack of samples. The results showed that an inter-continental transferred rice mapping model was feasible to achieve accurate rice maps in Northeast China (F-score, kappa coefficient, recall, and precision were 0.8502, 0.8439, 0.8345, and 0.8669, respectively). The study found that the transferred model exhibited a strong spatiotemporal generalization capability, achieving high accuracy in rice mapping in the three main rice-producing regions of Northeast China. The phenological differences of rice significantly affected the generalization capability of the transferred model, particularly the significant differences in transplanting periods, which could have resulted in a decrease in the generalization capability of the model. Furthermore, the study found that the model transferred based on an extremely limited number of samples could attain a rice recognition accuracy equivalent to that of the model trained from scratch with a substantial number of samples, indicating that the proposed method possessed strong practicality, which could dramatically reduce the sample requirements for crop mapping based on deep learning models, thereby decreasing costs, increasing efficiency, and facilitating large-scale crop mapping in areas with limited samples.

Ecological Security Assessment and Warning of Cultivated Land Quality in the Black Soil Region of Northeast China

The ecological security of cultivated land critically depends on maintaining the quality of the land under cultivation. For the security of the nation’s grain supply, the evaluation and early warning of cultivated land quality (CLQ) are essential. However, previous studies on the assessment of the ecological safety of CLQ only rigidly standardized the assessment indicators and failed to investigate the positive and negative trends and spatiotemporal driving factors of the indicators. The main objective of this study was to develop a drive–pressure–state–response (DPSR) model to identify the hierarchical structure of indicators, using an improved matter–element model to assess the CLQ in the black soil region of northeastern China from 2001 to 2020. A panel data model was employed to explore the crucial drivers of CLQ warnings. The findings reveal that socioeconomic development has a potential impact on the improvement of CLQ. CLQ is generally in a secure state, with 69.71% of cities with no warnings and only 3.46% and 0.13% of cities under serious and extreme warnings, respectively. Compared with 2001, the CLQ in 2020 effectively improved by socioeconomic development and the conservation and reasonable utilization of arable land. According to the early warning results, the cultivated land in the northern regions was of higher quality than that in the southern regions. Moreover, the CLQ was significantly positively correlated with the agricultural GDP growth rate, grain yield per unit of cultivated land area, annual precipitation, and the habitat quality index, and was significantly negatively correlated with land carrying capacity. The findings of this study can provide a scientific and targeted basis for black soil conservation and utilization.

The driving mechanism of soil organic carbon biodegradability in the black soil region of Northeast China

The biodegradability of soil organic carbon (BSOC), defined as soil mineralization C per unit of soil organic carbon (SOC), is considered to be an important indicator of SOC stability and is closely related to the global C cycle. However, the magnitude and driving mechanism of BSOC in farmland remain largely unexplored, especially at the regional scale. Here, we conducted regional scale sampling to investigate latitude distribution pattern of BSOC and the relative contributions of biotic (soil micro-food web) and abiotic (climate and soil) drivers to BSOC in the black soil region of Northeast China. Results showed that BSOC declined with increasing latitude, which indicates that as the latitude increases, SOC becomes more stable in the black soil region of Northeast China. Over a range of latitude from 43°N to 49°N, BSOC was negatively correlated with soil micro-food web metrics of diversity (indicated by species richness), biomass and connectance, and soil factors of soil pH and clay content (CC), while it was positively correlated with climate factors of mean annual temperature (MAT), mean annual precipitation (MAP) and soil factor of soil bulk density (SBD). Among those predictors, soil micro-food web metrics were the most direct factors contributing to the variations of BSOC, which exerted the largest total effect on BSOC (−0.809). Collectively, our results provide convincing evidence that soil micro-food web metrics play a direct vital role in determining the distribution pattern of BSOC over a range of latitudes in the black soil region of Northeast China. This highlights the necessity of considering the role of soil organisms in regulating C dynamics in prediction of SOC mineralization and retention in the terrestrial ecosystem.

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.