Search Results (116)

In this study, 14 palynological samples and nine AMS ¹⁴C dating samples were collected from two representative black soil profiles in the Xingkai Lake Plain to examine climate changes and their impacts on environmental evolution since the Holocene. The systematic identification, analysis, and research of palynological data reveal that the black soil profiles in the Xingkai Lake Plain can be categorized into the following three distinct palynological assemblage zones: the lower zone (11.7–7.5 ka BP) is characterized by Pinus-Laevgatomonoleti-Amaranthaceae-Artemisia, having a cold, dry climate; the middle zone (7.5–2.5 ka BP) features Quercus-Juglans-Polygonum-Cyperaceae, with a warm and humid climate; and the upper zone (2.5 ka BP to present) consists of Pinus-Quercus-Betula, indicating a cold and dry climate. Furthermore, field lithostratigraphic observations of the two black soil profiles suggest that late Pleistocene loessial clay serves as the parent material in this region. Quaternary geology, section lithology, palynology, and AMS ¹⁴C dating results indicate that a significant portion of black soil in the Xingkai Lake Plain was primarily formed during the Great Warm Period following the middle Holocene. These insights not only enhance our understanding of Holocene climate dynamics in Northeast China but also provide a substantial scientific foundation for further studies on related topics. Full article

Cultivated land quality is a key factor in ensuring sustainable agricultural development. Exploring differences in cultivated land quality under distinct cropping systems is essential for developing targeted improvement strategies. This study takes place in Shenyang City—located in the typical black soil region of Northeast China—as a case area to construct a cultivated land quality evaluation system comprising 13 indicators, including organic matter, effective soil layer thickness, and texture configuration. A minimum data set (MDS) was separately extracted for paddy and upland fields using principal component analysis (PCA) to conduct a comprehensive evaluation of cultivated land quality. Additionally, an obstacle degree model was employed to identify the limiting factors and quantify their impact. The results indicated the following. (1) Both MDSs consisted of seven indicators, among which five were common: ≥10 °C accumulated temperature, available phosphorus, arable layer thickness, irrigation capacity, and organic matter. Parent material and effective soil layer thickness were unique to paddy fields, while landform type and soil texture were unique to upland fields. (2) The cultivated land quality index (CQI) values at the sampling point level showed no significant difference between paddy (0.603) and upland (0.608) fields. However, their spatial distributions diverged significantly; paddy fields were dominated by high-grade land (Grades I and II) clustered in southern areas, whereas uplands were primarily of medium quality (Grades III and IV), with broader spatial coverage. (3) Major constraint factors for paddy fields were effective soil layer thickness (21.07%) and arable layer thickness (22.29%). For upland fields, the dominant constraints were arable layer thickness (27.57%), organic matter (25.40%), and ≥10 °C accumulated temperature (23.28%). Available phosphorus and ≥10 °C accumulated temperature were identified as shared constraint factors affecting quality classification in both systems. In summary, cultivated land quality under different cropping systems is influenced by distinct limiting factors. The construction of cropping-system-specific MDSs effectively improves the efficiency and accuracy of cultivated land quality assessment, offering theoretical and methodological support for land resource management in the black soil regions of China. Full article

Northeast China is a key grain production region yet achieving coordinated improvements in maize yield and quality across diverse environments remains challenging. This study conducted a meta-analysis to evaluate maize yield and quality responses to chemical fertilizer inputs under varying natural (climate, soil) and anthropogenic (fertilization, planting) conditions. The results indicated that fertilizer application increased yield by 20.0%, and protein, fat, and starch contents by 12.6, 1.4, and 1.2%, respectively, compared to no fertilization. Yield response was highest under precipitation <450 mm and temperatures >7 °C, while protein and fat gains were favored by >600 mm precipitation and 5–7 °C temperatures. Soils with pH <6.5 and saline–alkaline properties supported greater yield gains, while brown and black soils promoted protein and fat accumulation, respectively. Moderate nutrient inputs (N 180–240, P₂O₅ 75–120, K₂O 90–135 kg ha⁻¹) outperformed lower or higher levels in improving both traits, with planting density also affecting response magnitude. Yield gains were primarily driven by soil fertility, whereas quality improvements were influenced by climate and management. Moderate fertilization facilitated the simultaneous enhancement of yield and quality. Tailored nutrient strategies based on soil and climate conditions can support regional maize productivity and contribute to food security. Full article

Rapid and efficient evaluation of cultivated land quality in black soil regions at the farm scale using remote sensing techniques is crucial for resource protection. However, current studies face challenges in developing convenient and reliable models that directly leverage raw spectral reflectance. Therefore, this study develops and validates a deep learning framework specifically for this task. The framework first selects remote sensing images from typical periods using a Random Forest model in Google Earth Engine (GEE). Subsequently, the raw spectral reflectance data from these images, without any transformation into vegetation indices, are directly input into an optimized BO-Stacking-TabNet model. This model is enhanced through a two-step Stacking ensemble process and a Bayesian optimization algorithm. A case study at Shuanghe Farm in Northeast China shows that (1) compared to the BO-Stacking-TabNet model using vegetation indices as input, the BO-Stacking-TabNet model based on spectral reflectance as the input indicator achieved an improvement of 10.62% in Accuracy, 1.55% in Precision, 11.05% in Recall, and 10.18% in F1-score. (2) Compared to the original TabNet model, the BO-Stacking-TabNet model optimized by the two-step Stacking process and Bayesian optimization algorithm improved Accuracy by 2.13%, Precision by 12.59%, Recall by 1.83%, and F1-score by 2.19%. These results demonstrate the reliability of the new farm-scale black soil region cultivated land evaluation method we proposed. The method provides significant references for future research on cultivated land quality assessment at the farm scale in terms of remote sensing image data processing and model construction. Full article

A prerequisite for the efficient utilization of water and fertilizer in the traditional ridge farming model in the black soil region of Northeast China is the precise elucidation of the small-scale temporal and spatial characteristics of rainfall infiltration and redistribution. However, the existing research findings have yet to fully satisfy this requirement. To investigate soil water infiltration and redistribution at different positions (ridge bed, ridge side, and furrow) before ridge closure in ridge-furrow crops within the black soil regions of Northeast China, indoor simulation experiments and field natural rainfall monitoring were conducted. The indoor test involved rainfall settings of 12, 16, 20, 24, and 30 mm with a rain intensity of 90 mm/h. Field monitoring recorded a natural rainfall intensity of 56 mm/h lasting 22.5 min, with cumulative rainfall reaching 21 mm (randomly measured), to analyze the process of soil water movement post-rainfall. Results indicated that under conventional ridge planting in black soil areas, prior to ridge bed coverage, the infiltration amounts for ridge bed, ridge side, and furrow under 16 mm rainfall conditions equaled the rainfall itself, with ratios close to 1:1:1, showing no significant redistribution of precipitation during infiltration. For rainfall levels of 20 mm, 24 mm, and 30 mm, the ratios of infiltration to rainfall at the ridge bed, ridge side, and furrow positions were 0.92:1.03:1.04, 0.90:1.03:1.06, and 0.89:1.04:1.09, respectively. When rainfall exceeded 20 mm, the infiltration-to-rainfall ratio was approximately 0.9 and 1.04, respectively. Approximately 10% of the rainfall on the ridge platform migrated to the ridge side via splash and runoff, increasing the water volume at the ridge side by about 4%. For rainfall less than 24 mm, the ridge bed, ridge side, and furrow reached a stable state after approximately 50 min of infiltration and redistribution. For rainfall between 24 mm and 30 mm, the ridge platform stabilized within 50 min, whereas the ridge side and furrow required longer stabilization times. These findings elucidate the spatial variation laws of small-scale rainfall infiltration, providing insights for enhancing soil water and fertilizer utilization efficiency. Full article

This study reveals how microbial diversity relates to soil properties in Auricularia heimuer residue–chicken manure composting, presenting sustainable waste recycling solutions. These microbial-straw strategies are adaptable to various agroecological regions, offering flexible residue valorization approaches for local conditions, crops, and resources. This study examined the effects of composting Auricularia heimuer residue and chicken manure at three ratios (6:4, 7:3, 8:2) on soil properties, lignocellulose content, enzyme activity, microbial diversity, and maize growth. The compost was mixed into potting soil at different proportions (0:10 to 10:0). During composting, the temperature remained above 50 °C for more than 14 days, meeting safety and sanitation requirements. The composting process resulted in a pH range of 7–8, a stable moisture content of 60%, a color change from brown to gray-brown, the elimination of unpleasant odors, and the formation of loose aggregates. Lignocellulose content steadily decreased, while lignocellulosic enzyme activity and actinomycete abundance increased, indicating suitability for field application. Compared with the control (CK), total nitrogen, total phosphorus, and total potassium in the soil increased by 57.81–77.91%, 4.5–19.28%, and 301.09–577.2%, respectively. Lignin, cellulose, and hemicellulose increased 50.6–83.49%, 59.6–340.33%, and 150.86–310.5%, respectively. The activities of lignin peroxidase, cellulase, and hemicellulase increased by 9.05–36.31%, 6.7–36.66%, and 37.39–52.16%, respectively. Maize root weight, plant biomass, and root number increased by 120.87–138.59%, 117.83–152.86%, and 29.03–75.81%, respectively. In addition, composting increased the relative abundance of actinomycetes while decreasing the abundance of ascomycetes and ascomycetes. The relative abundance of Sphingomonas and Gemmatimonas increased, whereas pathogenic fungi such as Cladosporium and Fusarium decreased. Compost application also enhanced bacterial and fungal diversity, with bacterial diversity indices ranging from 6.744 to 9.491 (B1), 5.122 to 9.420 (B2), 8.221 to 9.552 (B3), and 6.970 to 9.273 (CK). Fungal diversity indices ranged from 4.811 to 8.583 (B1), 1.964 to 9.160 (B2), 5.170 to 9.022 (B3), and 5.893 to 7.583 (CK). Correlation analysis of soil physicochemical properties, lignocellulose content, enzymes, microbial community composition, and diversity revealed that total nitrogen, total phosphorus, total potassium, and lignocellulose content were the primary drivers of rhizosphere microbial community dynamics. These factors exhibited significant correlations with the dominant bacterial and fungal taxa. Additionally, bacterial and fungal diversity increased with the incorporation of Auricularia heimuer residue. In conclusion, this study elucidates the relationships between microbial diversity and soil properties across different proportions of Auricularia heimuer residue and chicken manure composting, offering alternative strategies for waste recycling and sustainable agricultural development. At present, the production of biobiotics using waste culture microorganisms is still in the laboratory research stage, and no expanded experiments have been carried out. Therefore, how to apply waste bacterial bran to the production of biocontrol biotics on a large scale needs further research. Full article

The cultivated land in the black soil of Northeast China (BSNC), due to long-term high-input and high-output utilization, is facing a series of challenges such as soil erosion, compaction, and nutrient loss. However, the existing cultivated land quality evaluation (CLQE) lacks regional specificity, making it difficult to accurately reflect the cultivated land quality (CLQ) characteristics across different areas. Therefore, this study proposes a comprehensive evaluation framework that integrates both cultivated land functionality and degradation risk, establishing an assessment system consisting of 18 indicators to comprehensively evaluate the CLQ in the BSNC from multiple perspectives. The results indicate that the CLQ in the BSNC exhibits a declining trend from north to south, with second- and third-grade land dominating, accounting for 75.68% of the total cultivated land area. The overall cultivated land functionality increases from west to east, with the Liaohe Plain Region (LHP) performing the best. Low-risk cultivated land is primarily concentrated in the Songnen Plain Region (SNP) and the Western Sandy Region (WS), covering 38.55% of the total cultivated land area. Additionally, this study finds a trade-off between the primary productivity function and the resource utilization efficiency function across different regions, while a synergistic relationship is observed between resource utilization efficiency and soil nutrient maintenance functions. This research emphasizes the necessity of balancing productivity and ecological protection to achieve the sustainable and efficient use of the BSNC. Full article

To investigate the levels of polychlorinated biphenyls (PCBs) in the black soils of Northeast China, we collected 59 surface soil samples from the central black soil region of Jilin Province. We analyzed the concentrations and sources of seven PCBs in the black soil, assessed the ecological risks associated with PCB contamination, and provided a risk assessment for PCBs in this soil type. The mean concentrations of the seven PCBs (PCB28, PCB52, PCB101, PCB118, PCB138, PCB153, and PCB180) were as follows: 1.61 μg/kg, 10.61 μg/kg, 0.37 μg/kg, 4.11 μg/kg, 0.70 μg/kg, 1.07 μg/kg, and 2.09 μg/kg, respectively. Principal component analysis revealed that PCB contamination in black soil is mainly attributed to automobile exhaust emissions during transportation, waste incineration processes, and insulation materials from electronic and electrical equipment. PCB28 and PCB52 are the primary causes of PCB danger, according to the findings of the ecological risk assessment, with Liaoyuan City having the highest risk. By applying contemporary industrial economic theory to analyze the annual accumulation of contaminants, we forecasted future PCB concentrations in black soil and issued a risk warning for these seven PCBs. Our results indicate that under the three scenarios considered, the presence of these seven PCBs in black soil does not pose a significant risk. However, given that our study examined only seven PCBs, the actual environmental risk may be underestimated. Full article

The rapid and accurate acquisition of soil moisture (SM) information is essential. Although Unmanned Aerial Vehicle (UAV) remote sensing technology has made significant advancements in SM monitoring, existing studies predominantly focus on developing models tailored to specific regions. The transferability of these models across different regions remains a considerable challenge. Therefore, this study proposes a transfer learning-based framework, using two representative small agricultural watersheds (Hongxing region and Woniutu region) in Northeast China as case studies. This framework involves pre-training a model on a source domain and fine-tuning it with a limited set of target domain samples to achieve high-precision SM inversion. This study evaluates the performance of three algorithms: Random Forest (RF), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM) network. Results show that the fine-tuned model significantly mitigates the decline in prediction accuracy caused by regional differences. The fine-tuned LSTM model achieved the highest retrieval accuracy, with the following results: 10% samples (R = 0.615, RRMSE = 15.583%), 30% samples (R = 0.682, RRMSE = 13.97%), and 50% samples (R = 0.767, RRMSE = 16.321%). Among these models, the LSTM model exhibited the most significant performance improvement and the best transferability. This study underscores the potential of transfer learning for enhancing cross-regional SM monitoring and providing valuable insights for future UAV-based SM monitoring. Full article

As a pivotal region for safeguarding China’s food security, Northeast China requires a quantitative evaluation of crop yield dynamics, planting structure shifts, and their interdependent mechanisms. Leveraging MODIS NPP data and remote sensing-derived crop classification data from 2001 to 2021, this study established a crop yield estimation model. By integrating the Theil–Sen median slope estimator and Mann–Kendall trend analysis, we systematically investigated the spatiotemporal characteristics of maize, rice, and soybean yields. Phased attribution analysis was further employed to quantify the effects of crop type conversions on total regional yield. The results revealed: (1) strong consistency between estimated yields and statistical yearbook data, with validation R² values of 0.76 (maize), 0.69 (rice), and 0.81 (soybean), confirming high model accuracy; (2) significant yield growth areas that spatially coincided with the core black soil zone, underscoring the productivity-enhancing role of conservation tillage practices; (3) all three crops exhibited upward yield trends, with annual growth rates of 1.33% (maize), 1.20% (rice), and 1.68% (soybean). Spatially, high-yield maize areas were concentrated in the southeast, rice productivity peaked along river basins, and soybean yields displayed a distinct north-high-south-low gradient; (4) crop type transitions contributed to a net yield increase of 35.9177 million tons, dominated by soybean-to-maize conversions (50.41% contribution), while maize-to-soybean shifts led to a 2.61% yield reduction. This study offers actionable insights for optimizing planting structures and tailoring grain production strategies in Northeast China, while providing a methodological framework for crop yield estimation in analogous regions. Full article

Enhancing chlorophyll retention in maize leaves and prolonging the grain-filling duration constitute critical strategies for yield improvement in agricultural production systems. This study investigated the mechanistic relationship between yield enhancement pathways and the leaf senescence process induced by high-input straw pellets amendment. We analyzed the impact mechanisms of green leaf area dynamics and dry matter redistribution on yield during late reproductive stages, establishing theoretical foundations for yield optimization through intensive straw pellets incorporation. The study used the maize variety Jingnongke 728 as the experimental material. Based on previous research, four treatments were set up, including no straw returning (CK), chopped straw (15 t/ha) returning to the field (FS1), a large amount of chopped straw (75 t/ha) returning to the field (FS5), and a large amount of pelletized straw (75 t/ha) returning to the field (KL5), with four replicates. A two-year experimental design systematically assessed green leaf area index (GLAI), dry matter accumulation, distribution, translocation, yield components, and grain yield to explore the differences among various treatments under different straw returning amounts and returning forms. The study detected no significant differences between FS1 and CK. Although KL5 and FS5 delayed leaf senescence, FS5 significantly depressed green leaf area index (GLAI) at the R1 stage (silking), which results in it not having more effective photosynthetic area during late phenological phases. In dry matter dynamics, KL5 exhibited 5.52–25.71% greater pre-anthesis accumulation, 2.73–60.74% higher post-anthesis accumulation, and 9.48–25.76% elevated ear dry matter allocation relative to other treatments. KL5’s post-anthesis assimilates contributed 2.43–17.02% more to grain development, concurrently increasing ear-to-total biomass ratio. Yield analysis ranked KL5 as the superior treatment with 0.68–25.15% yield advantage, driven by significantly enhanced kernel number per ear and 100-kernel mass, whereas FS5 displayed the lowest kernel count among all treatments. Returning 75 t/ha of straw pellets to the black soil area in Northeast China can significantly delay the senescence of maize leaves and increase the accumulation of dry matter after anthesis by maintaining the effective photosynthetic area of leaves in the later stage of growth, thereby achieving the goal of increasing yield. The research can offer a practical and novel approach for straw return in the black soil region of Northeast China and provide a new technological pathway for enhancing crop productivity. Full article

Soil biodiversity is profoundly affected by variations in climate conditions and land use practices. As one of the major grain-producing areas in China, the belowground biodiversity of the black soil region of the Northeast is also affected by the variations in climate conditions and land use types. However, most of the previous studies have focused on aboveground biodiversity, and the research of soil biodiversity is limited. The main aim of this study was to investigate the effects of variations in climate conditions and land use practices on Collembola communities of different life forms in the black soil region of Northeast China. Here, we selected three climatic areas from high to low latitudes in the black soil region of the Northeast, with three variations in land use practices (soybean, maize, and rice) sampled in each area. We found that higher temperatures and higher humidity and land use practices from rice to soybean and maize are associated with a higher Collembola density and species richness. Specifically, the density and species richness of euedaphic Colmbola are higher in climate conditions with higher temperatures and humidity, while the density and species richness of all three life forms of Collembola are higher in land use practices from rice to soybean and maize. Additionally, we discovered that environmental factors and feeding resources (soil microorganisms) both have significant effects on Collembola communities, with environmental factors exerting a more substantial influence. Our results suggest that euedaphic Collembola are more vulnerable to climate differences than epedaphic and hemiedaphic Collembola. Consequently, this may alter the vertical distribution characteristics of soil fauna (e.g., increasing soil-dwelling fauna) as well as the ecological processes associated with soil fauna in different agricultural environments. Full article

The delayed decomposition of rice straw in Northeast China’s cold regions (winter temperatures < −20 °C) due to insufficient accumulated temperature requires innovative solutions. This study developed a synergistic approach combining microbial decomposition with mechanical burial. Pre-experiments identified optimal parameters for the liquid decomposing agent (100 mg/mL concentration, 6 g/m application rate). A novel combined machine was engineered with adjustable parameters: knife roller speed (200–300 r/min), burial depth (15–25 cm), and ground clearance (80–120 mm). Field trials demonstrated a 91.3% straw return rate under optimized settings (220 r/min, 100 mm clearance, 1.7 m/s speed), representing a 28.5% improvement over conventional methods. Spring burial enhanced straw decomposition to 83.6% within 60 days (vs. 67.2% in autumn), significantly increasing soil organic matter and available nitrogen. The integrated technology achieved 1.5 hm²/h operational efficiency, meeting regional agronomic demands. This study provides a replicable model for cold-region straw utilization, aligning with carbon sequestration goals in black soil conservation. Full article

To assess the effects of prolonged no-tillage practices on soil health and crop output, an 18-year field study was carried out in the black soil region of Northeast China. We investigated the variations in soil physicochemical properties, bacterial community structure, and soybean yield under different no-tillage (NT) durations from year 10 to 18 and conventional tillage (CT) treatments for 18 years. The findings indicated that the 18-year no-tillage (NT18) treatment resulted in significantly greater levels of soil organic matter, total nitrogen, and available phosphorus—18.3%, 30.4%, and 65.8% higher, respectively (p < 0.05)—compared to the traditional tillage (CT18) treatment. In the 0–30 cm soil layer, the relative abundance of Acidobacteriota had risen with the duration of no-tillage, whereas Proteobacteria, Gemmatimonadota, and Verrucomicrobiota had shown a decline. In addition, no-tillage treatments increased network complexity, with longer durations of no-tillage leading to higher levels of complexity. Soybean yield increased by 8.5% under NT18 compared to CT18 (p < 0.05). These findings provide insights into the interaction between no-tillage treatments and soil bacterial microbial communities within the black soil region, thereby establishing a solid foundation for developing efficient, ecological, and sustainable conservation tillage systems in Northeast China. Full article

Ecosystem services (ESs) are essential for balancing environmental sustainability and socio-economic development. However, the sustainability of ESs and their relationships are increasingly threatened by global climate change and intensifying human activities, particularly in ecologically sensitive and agriculturally-intensive regions. The Songnen Plain, a crucial agricultural region in Northeast China, faces considerable challenges in sustaining its ESs due to the overexploitation of agricultural land, environmental degradation, and climate variability. This study assessed five key ESs in the Songnen Plain from 2000 to 2020 across multiple scales: habitat quality (HQ), soil conservation (SC), water yield (WY), food production (FP), and windbreaking and sand fixing (WS). We evaluated the trade-offs and synergies between these ESs, as well as the driving factors of the main ES trade-offs. Our findings indicate that provisioning services (WY and FP) and regulating services (SC and WS) improved over time, with FP exhibiting the most significant increase at 203.90%, while supporting services (HQ) declined by 32.61%. The primary ecosystem service multifunctionality areas were those that provided FP, SC, and WY, accounting for 58% of the total. ES trade-offs and synergies varied across spatial scales, with stronger synergies being observed at the pixel scale and more pronounced trade-offs at the county scale. Climate factors, particularly precipitation and temperature, played a more significant role in shaping ES trade-offs than anthropogenic factors. Our study provides valuable insights into the restoration and sustainable management of ESs in temperate agriculturally-intensive regions, with significant implications for the protection of the northeastern black soil region and safeguarding national food security. Full article