Search Results (51)

The agronomic effectiveness of biofertilizers is influenced by strain origin, genetic identity, crop genotype, soil type, and environmental conditions. For best results, both the plant and rhizobia strain must be adapted to the common harsh soil conditions in the tropics. While plant varieties have changed over the years, complementary research on new strains effectiveness under varying soil fertility conditions has lagged in southern Africa. Seven field experiments were established in the main soybean-producing areas of Zimbabwe in the north, central, and north–east regions to evaluate agronomic benefits of new rhizobia strains against the current exotic commercial strain (MAR1491). One site was irrigated (site 3), and the other six sites were rainfed (sites 1, 2, 4, 5, 6, and 7). While trends in inoculation response varied from site to site due to site conditions, inoculation with the strains NAZ15, NAZ25, and NAK128 consistently yielded high grain yields, which were similar to the current commercial strain MAR1491 and to application of mineral fertilizer (51.75 and 100 kg N ha⁻¹). Grain yield levels were generally below 2 t ha⁻¹ for sites 2, 3, and 5 and above 2 t ha⁻¹ for sites 1, 4, and 6, while for the irrigated site 3, they ranged upwards of 3 t ha⁻¹. When irrigated, all strains except NAK9 performed similarly in terms of grain yields and aboveground N uptake. Further testing on the inclusion of the indigenous strains NAZ15, NAZ25, and NAK128 in multi-strain commercial inoculant production targeting application in regions and soils where they excel beyond the current exotic strain MAR1491 is recommended. Full article

Drought impacts agricultural production and regional sustainable development. Accordingly, timely and accurate drought monitoring is essential for ensuring food security in rain-fed agricultural regions. Alternating drought and flood events frequently occur in the Heilongjiang River Basin, the largest grain-producing area in Far East Asia. However, spatiotemporal variability in drought is not well understood, in part owing to the limitations of the traditional Temperature Vegetation Dryness Index (TVDI). In this study, an Improved Temperature Vegetation Dryness Index (ITVDI) was developed by incorporating Digital Elevation Model data to correct land surface temperatures and introducing a constraint line method to replace the traditional linear regression for fitting dry–wet boundaries. Based on MODIS (Moderate-resolution Imaging Spectroradiometer) normalized vegetation index and land surface temperature products, the Heilongjiang River Basin, a cross-border basin between China, Mongolia, and Russia, exhibited pronounced spatiotemporal variability in drought conditions of the growing season from 2001 to 2023. Drought severity demonstrated clear geographical zonation, with a higher intensity in the western region and lower intensity in the eastern region. The Mongolian Plateau and grasslands were identified as drought hotspots. The Far East Asia forest belt was relatively humid, with an overall lower drought risk. The central region exhibited variation in drought characteristics. From the perspective of cross-national differences, the drought severity distribution in Northeast China and Inner Mongolia exhibits marked spatial heterogeneity. In Mongolia, regional drought levels exhibited a notable trend toward homogenization, with a higher proportion of extreme drought than in other areas. The overall drought risk in the Russian part of the basin was relatively low. A trend analysis indicated a general pattern of drought alleviation in western regions and intensification in eastern areas. Most regions showed relatively stable patterns, with few areas exhibiting significant changes, mainly surrounding cities such as Qiqihar, Daqing, Harbin, Changchun, and Amur Oblast. Regions with aggravation accounted for 52.29% of the total study area, while regions showing slight alleviation account for 35.58%. This study provides a scientific basis and data infrastructure for drought monitoring in transboundary watersheds and for ensuring agricultural production security. Full article

Jilin Province is an important ecological security barrier and major grain-producing region in northeast China, playing a crucial role in ensuring ecological security and promoting regional sustainable development. This study examines ecological resilience from three dimensions: resistance, adaptability, and resilience. Based on multi-source data from 2000 to 2020, an ecological resilience indicator system was constructed. Spatial autocorrelation and OPGD models were employed to analyze temporal and spatial evolution and the driving mechanisms. The results indicate that ER exhibits an overall spatial pattern of “high in the east, low in the west, and under pressure in the central region.” The eastern mountainous areas demonstrate high and stable resilience, while the central plains and western ecologically fragile regions exhibit weaker resilience. In terms of resistance, the eastern mountainous regions are primarily forested, with high and sustained ESV, while the western sandy edge regions primarily have low ESV, making ecosystems susceptible to disturbance. In terms of adaptability, the large-scale farmland landscapes in the central regions exhibit strong disturbance resistance, while water resource adaptability in the western ecologically fragile regions has locally improved. However, adaptability in the eastern mountainous regions is relatively low due to development impacts. In terms of resilience, the eastern core regions possess stable recovery capabilities, while the central and western regions generally exhibit lower resistance with fluctuating changes. Between 2000 and 2020, the ecological resilience Moran’s I index slightly decreased from 0.558 to 0.554, with the spatial aggregation pattern remaining largely stable. Among the driving factors, DEM remains the most stable. The influence of NDVI has weakened, while temperature (TEM) and NPP-VIIRS have become more significant. Overall, factor interactions have grown stronger, as reflected by the q-value rising from 0.507 to 0.5605. This study provides theoretical support and decision-making references for enhancing regional ecological resilience, optimizing ecological spatial layout, and promoting sustainable ecosystem management. Full article

Drought significantly reduces global agricultural productivity and destabilizes ecosystems. As the primary grain-producing region and a key ecological buffer zone in China, Northeast China is experiencing intensifying drought stress. However, the regional-scale characteristics of refined drought and the impact mechanisms on different types of vegetation in the Northeast are rarely investigated. In this study, we analyzed the spatial and temporal characteristics of drought over 30-, 60-, 90-, 180-, 270-, and 360-day time scales in Northeast China using the Standardized Precipitation Index (SPI) based on high-precision daily precipitation data simulated by CLM3.5 from 2008 to 2023. Additionally, we used the MODIS Normalized Difference Vegetation Index (NDVI) to elucidate the response of vegetation to drought across different land use types. The results showed that SPI-30 was the most sensitive for drought detection, and there was a clear trend of drought aggravation in the northern part of the Northeast region. The strongest correlation between vegetation and drought was found in September. A significant lag in the response of vegetation to drought was observed in May, June, July, and August, with the best correlation observed at a one-month lag. In addition, the degree of response to drought varies among different types of vegetation. Grasslands are the most sensitive to drought, while woodlands and wetlands have a weaker response. This study provides a reference for assessing the dynamics of refined climates at different spatial and temporal scales and offers actionable insights for ecosystem management in climate-sensitive agricultural regions. Full article

Financial support for agriculture has mainly focused on grain production, while insufficient efforts have been made to ensure water security, potentially intensifying water pressure in grain production (WPGP). This study applies the entropy weight Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method to measure WPGP from the perspective of sustainable agricultural water use, investigating the impact of agricultural fiscal expenditure on WPGP. Our findings reveal several key points. First, there is a clear linkage between the spatial and temporal patterns of fiscal support and WPGP. Projections indicate that water pressure for grain production in China will continue to rise from 2019 to 2030, with the fastest increases in the Northeast and Huang-Huai-Hai regions, at 20.53% and 13.39%, respectively. Second, agricultural fiscal expenditure distorts the allocation of grain production factors, causing cultivation areas to expand beyond local water resource capacity and, thus, exacerbating WPGP. This effect exhibits a time lag due to the gradual nature of factor allocation. Further analysis shows that in non-major grain-producing regions, lower production efficiency and higher opportunity costs of factor use weaken the impact of fiscal expenditure on WPGP compared to major grain-producing regions. Third, in regions with advanced technical conditions for grain production, the negative impact of agricultural fiscal expenditure on WPGP is mitigated by higher irrigation technology levels, improved water allocation efficiency, and lower water demand per unit of grain. Fourth, the public good characteristics of water resources and water conservancy facilities—namely, strong externalities and non-exclusivity—along with the agronomic demonstration effect, lead to a spatial spillover effect of agricultural fiscal expenditure on WPGP. 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

Northeast China, as a primary grain-producing region, has long drawn attention for its intensive groundwater extraction for irrigation. However, previous studies on the future spatiotemporal changes of groundwater storage (GWS) are lacking. Utilizing the Global Land Data Assimilation System Version 2.2 (GLDAS-2.2), which simulates groundwater storage (as Equivalent Water Height) using the Catchment Land Surface Model (CLSM-F2.5) and calibrates it with terrestrial water storage data from the GRACE satellite, we analyzed the spatiotemporal variations of GWS in northeast China and employed a Long Short-Term Memory (LSTM) neural network model to quantify the responses of GWS to future climate change. Maintaining current socio–economic factors and combining climate factors from four scenarios (SSP126, SSP245, SSP370, and SSP585) under the CMIP6 model, we predicted GWS from 2022 to 2100. The results indicate that historically, groundwater storage exhibits a decreasing trend in the south and an increasing trend in the north, with a 44° N latitude boundary. Under the four scenarios, the predicted GWS increments in northeast China are 0.08 ± 0.09 mm/yr in SSP126, 0.11 ± 0.08 mm/yr in SSP245, 0.12 ± 0.09 mm/yr in SSP370, and 0.20 ± 0.07 mm/yr in SSP585. Although overall groundwater storage has slightly increased and the model projections indicate a continued increase, the southern part of the region may not return to past levels and faces water stress risks. This study provides an important reference for the development of sustainable groundwater management strategies. Full article

Rice (Oryza sativa L.) is a staple food crop for over half of the world’s population, with China being the largest producer. However, the growth rate of rice yield per hectare has slowed in recent years, emphasizing the need for in-depth studies on the evolution of rice cultivar performance. This study presents a comprehensive analysis of the yield and key agronomic traits of rice cultivars across China over three decades, utilizing data from 11,811 cultivar trials conducted between 1990 and 2023. We assessed the spatial distribution and temporal evolution of rice cultivar performance, exploring regional differences and the interplay between agronomic traits and environmental factors. Our results reveal significant variations in growth duration, plant height, grains per panicle, thousand-grain weight, effective panicle number, and seed setting rate across different regions. Temporal trends showed diverse patterns of improvement, with some regions experiencing rapid advancements (up to 1.42% annual yield increase in Jiangxi Province of Central China) and others nearing yield plateaus (0.16% in Jilin Province and 0.45% in Heilongjiang Province of Northeast China). Correlation analysis between agronomic traits and grain yield highlighted the complex relationships and potential for further genetic gains through targeted breeding. This study underscores the importance of region-specific breeding strategies to optimize rice production in the face of environmental challenges and yield ceilings. The insights gained provide a scientific basis for future rice cultivar development and regional agricultural policies aimed at enhancing sustainability and efficiency in China’s diverse rice-growing regions. Full article

Northeast China plays a crucial role as a major grain-producing region, and attention to its land use and land cover changes (LUCC), especially farmland changes, are crucial to ensure food security and promote sustainable development. Based on the Moderate Resolution Imaging Spectroradiometer (MODIS) data and a decision tree model, land types, especially those of paddy fields in Northeast China from 2000 to 2020, were extracted, and the spatiotemporal changes in paddy fields and their drivers were analyzed. The development trends of paddy fields under different future scenarios were explored alongside the Coupled Model Intercomparison Project Phase 6 (CMIP6) data. The findings revealed that the kappa coefficients of land use classification from 2000 to 2020 reached 0.761–0.825, with an overall accuracy of 80.5–87.3%. The proposed land classification method can be used for long-term paddy field monitoring in Northeast China. The LUCC in Northeast China is dominated by the expansion of paddy fields. The centroids of paddy fields gradually shifted toward the northeast by a distance of 292 km, with climate warming being the main reason for the shift. Under various climate scenarios, the temperature in Northeast China and its surrounding regions is projected to rise. Each scenario is anticipated to meet the temperature conditions necessary for the northeastward expansion of paddy fields. This study provides support for ensuring sustainable agricultural development in Northeast China. Full article

Maize (Zea mays L.) is one of the most important grain crops in the world. Drought caused by climate change in recent years may greatly threaten water supply and crop production, even if the drought only lasts for a few days or weeks. Therefore, effective daily drought monitoring for maize is crucial for ensuring food security. A pivotal challenge in current related research may be the selection of data collection and the methodologies in the construction of these indices. Therefore, orthorectified reflectance in the short-wave infrared (SWIR) band, which is highly sensitive to variations in vegetation water content, was daily obtained from the MODIS MCD43A4 product. Normalized Difference Water Index (NDWI) calculated using the NIR and SWIR bands and days after planting (DAP) were normalized to obtain the Vegetation Water Index (VWI) and normalized days after planting (NDAP), respectively. The daily dynamic threshold model for different agricultural drought grades was constructed based on the VWI and NDAP with double-logistic fitting functions during the maize growing season, and its specific threshold was determined with historical drought records. Verification results indicated that the VWI had a good effect on the daily agricultural drought monitoring of spring maize in the “Golden Maize Belt” in northeast China. Drought grades produced by the VWI were completely consistent with historical records for 84.6% of the validation records, and 96.2% of the validation records differed by only one grade level or less. The VWI can not only daily identify the occurrence and development process of drought, but also well reflect the impact of drought on the yield of maize. Moreover, the VWI could be used to monitor the spatial evolution of drought processes at both regional and precise pixel scales. These results contribute to providing theoretical guidance for the daily dynamic monitoring and evaluation of spring maize drought in the “Golden Maize Belt” of China. Full article

Fungal contamination in rice and mycotoxins present significant challenges to both rice quality and food safety. However, there is a dearth of comprehensive research on the compositional and structural changes within fungal colonies in rice, particularly in typical rice-producing regions, as well as their underlying influencing factors. In this study, a comprehensive analysis of fungal taxa in rice grains was conducted using amplicon sequencing and bioinformatics methods on 99 rice samples collected in three major rice-producing regions in China: Northeast Plain (NP), Yangtze River Basin (YR), and Southeast Coastal Area (SC). A total of 6,019,722 fungal ITS sequences were obtained with an average sequence length of 235 base pairs, and effective ASVs (2014) accounted for approximately 97.58% of the total ASVs (2064). The fungal community diversity in rice grains exhibited significant variations across the three regions, with deterministic processes playing a predominant role in shaping the ecological dynamics of fungal taxa. Among the core microbiota (92 shared ASVs), the first five species (Alternaria, Fusarium, Curvularia, Epicoccum, and Ustilaginoidea) accounting for a proportion greater than 5% had been reported as potential pathogens for plants. Geographical variations in fungal community composition were evident, with a significantly higher number of shared populations observed between YR and CS regions compared to those in the NP region. Nutrient elements and climatic conditions were the internal and external driving factors of rice fungal community composition. Additionally, notable regional variations in fungal functionality were observed. The findings have significant implications for gaining a comprehensive understanding of the distribution patterns of fungal communities in the major rice-producing regions in China. Additionally, it provides valuable insights into controlling key influencing factors to effectively reduce the occurrence of toxin-producing fungi and mitigate the associated risks related to mycotoxin contamination, thereby contributing to improved risk management and assessment. Full article

For the main grain-producing areas worldwide that balance multi-tasks of grain production, ecological protection, and economic development, quantitatively revealing the correlation between human activity intensity (HAI) and ecosystem service value (ESV) is conducive to formulating adapted ecological protection policies and promoting the coordinated development of the regional economy, society, and ecosystem. In this paper, we took the Songnen Plain of China as an example, employed a modified Equivalent Factor Method (integrating socio-economic data, the normalized difference vegetation index (NDVI), and land use data), and the HAI Assessment Model (based on the data of land use, night-time light, and population spatial distribution) to measure the ESV and HAI in the Songnen Plain of China for the years 1990, 1995, 2000, 2005, 2010, 2015, and 2020. We further applied the standard deviational ellipse method, the coupled coordination degree model, and the bivariate spatial autocorrelation models to reveal the spatiotemporal dynamics and correlation characteristics of ESV and HAI. The results showed the following: (1) Temporally, the ESV declined from 950.96 billion yuan in 1990 to 836.31 billion yuan in 2015, and then increased to 864.60 billion yuan in 2020, with the total loss attributed to the significant decline in the ESV of the natural ecosystem. Spatially, the ESV in the western and northeastern regions was relatively high, with a significant increase in the northeast. (2) HAI showed an upward trend from 1990 to 2020, while the high HAI levels gradually shrank after reaching the peak in 2000. Low HAI levels were mainly distributed in the northeast and southwest, aligning with the ecological space, while high HAI levels were distributed in the middle and southeast. (3) The interaction between ESV and HAI was marked by a negative correlation, transitioning from conflict to coordination. The spatial pattern of HAI and ESV showed H (HAI)-L (ESV) and L-H clustering, with H-H and L-L scattered distributions. This study contributes to providing a framework, methods, and suggestions for the sustainable planning and utilization of land and ecological protection in order to offer scientific references for the Songnen Plain, other major grain-producing areas, and related studies. Full article

Atmospheric volatile organic compounds (VOCs), such as olefins and aromatics, released from synthetic chemical pesticide sprays can increase regional air pollution, public health risks, and food security risks. However, significant uncertainties remain regarding the measurement methods and chemical profiles of VOC emissions. Using an agricultural city, Changchun City in Northeast China, as a case study, we quantified real-time concentration and composition data based on online monitoring instruments for the year 2023. This study optimized data collection methods for emission factors and activity levels and developed a high-precision emission inventory of VOCs in pesticides at the city scale. The emission factors for VOCs from the seven categories of pesticides were estimated as follows: 78 g/kg (nicosulfuron and atrazine, oil-dispersible [OD] and suspension emulsion [SE], respectively), 4 g/kg (chlorpyrifos and indoxair conditioningarb, suspension concentrate [SC]), 5 g/kg (fluopicolide and propamocarb hydrochloride, SC), 217 g/kg (MCPA-dimethylammonium, aqueous solution [AS]), 34 g/kg (glyphosate, AS), 575 g/kg (beta-cypermethrin and malathion, emulsifiable concentrate [EC]), and 122 g/kg (copper abietate, emulsion in water [EW]), depending on the pesticide formulation components and formulation types. The orchard insecticide exhibited the highest emission factors among all pesticides owing to its emulsifiable concentrate formulation and 80% content of inactive ingredients (both factors contribute to the high content of organic solvents in the pesticide). The major components of VOC emissions from pesticide spraying were halocarbons (27–44%), oxygenated VOCs (OVOCs) (25–38%), and aromatic hydrocarbons (15–28%). The total VOC emissions from pesticide spraying in the Changchun region accounted for 10.6 t, with Yushu City contributing 28% of the VOC emissions and Gongzhuling City and Dehui City contributing 18.7% and 16.0%, respectively. Herbicides were the main contributors to VOC emissions because of their high emission factors and extensive use in fields (used for spraying maize and rice, the main crops in Changchun City). May and June exhibited the highest VOC emissions from pesticide application, with May accounting for 57.0% of annual pesticide emissions, predominantly from herbicides (95.1%), followed by insecticides (4.9%). June accounted for 30.1% of the annual pesticide emissions, with herbicides being the largest contributor of VOC emissions. An emission inventory of VOC with a monthly scale and spatial grid resolutions of 0.083° and 0.5° in 2023 was developed. These emission factors and inventories of pesticide applications provide valuable information for air quality modeling. This study also provides an important scientific basis for enhancing regional air quality and mitigating the environmental impact of pesticide use in major grain-producing areas. Full article

As the economic center and major grain-producing area in Southwest China, the calculation of the carbon budget and the protection of cultivated land in the Chengdu Plain are of vital significance for China to achieve a carbon peak strategy and ensure food security. For the purpose of clarifying the trend of land use focus and carbon emissions in the Chengdu Plain, the carbon peak level of land use in 33 counties in the Chengdu Plain was explored. Based on the gravity center model and IPCC carbon emission coefficient method, the changing trend of land use gravity center and carbon emission in Chengdu Plain from 2006 to 2022 was clarified. PLS regression model and LMDI model were used to explore the main influencing factors of the carbon emission of cropland and the carbon emission of building land. PLUS model was used to simulate future land use patterns and carbon emissions. (1) The center of gravity of cropland, building land, water, and other and unused land shifted to the northeast by 4.23 km, 5.46 km, 8.44 km, and 31.58 km, respectively, and that of forest and grass shifted to the southeast by 11.12 km and 3.41 km, respectively. For major food crops, the centers of gravity of rice and maize moved northeastward by 15.47 km and 7.52 km, respectively, while wheat moved southwestward by 17.77 km. (2) From 2006 to 2022, carbon emissions from land use in the 33 counties of the Chengdu Plain are all on the rise, with a total increase of 13.552 million tons, and carbon sinks in the 31 counties continue to decline, with a total decrease of 0.691 million tons. (3) Under the natural scenario, carbon sink scenario, and carbon reduction scenario, the carbon emissions from land use decrease by 0.5391 million tons, 3.4728 million tons, and 4.5265 million tons from 2022, respectively. Among the 33 counties in the Chengdu Plain, 11 counties did not achieve carbon peak under the natural scenario, 5 counties did not achieve carbon peak under the carbon sink scenario, and all the counties achieved carbon peak under the carbon sink scenario. During the study period, there was a serious loss of cropland in the Chengdu Plain, mainly to building land in the central part of the Chengdu Plain and to forests within the Longmen Mountain, Longquan Mountain, and Leshan City, and there is a need to strengthen cropland protection in this region in the future. Under the natural scenario, carbon sink scenario, and carbon reduction scenario, land use in the Chengdu Plain region can achieve carbon peak, and the carbon reduction model will be more helpful for the counties to achieve carbon peak. Full article

The Northeast China Plain (NCP) is the country’s most important grain-producing area. Unraveling how bacterial communities in this region assemble and distribute according to soil type is essential for sustainable agricultural development and optimizing the precise management of soil resources. In this study, 106 soil samples were collected from three typical zonal soil types (black calcium soil (BCS), black soil (BS), and dark brown soil (DBS)) spanning from west to east in the NCP. By combining soil field surveys and high-throughput microbial sequencing analysis, we found that bacterial diversity and community structure differed significantly by soil type. Proteobacteria, Gemmatimonadetes, and Acidobacteria were enriched in BCS, BS, and DBS, respectively. Compared to BSC and DBS, BS had the highest nutrient concentration and most neutral pH values, which may recruit more diverse bacterial communities and construct a more connected ecological network. Network analysis further identified Burkholderiales, Sphingomonadales, and SC_I_84 as key hubs in BS, BCS, and BCS, respectively. The majority of classified hubs consistent with the results of the linear discriminant analysis effect size belonged to the predominant biomarkers. Redundancy and Mantel test analyses revealed that the bacterial composition in various soil types showed distinctive responses to heterogeneity in soil physicochemical properties. Soil pH and TP were the primary factors shaping the soil bacterial community structure in these three soil types on the NCP. Moreover, bacterial composition and diversity were strongly related to changes in soil multifunctionality in BCS, and the relative abundances of three classes (TM1, Opitutae, and Deinococci) were the most important biotic variables for predicting BCS ecosystem multifunctionality. In summary, our results suggest that soil type variation has a strong influence in terms of shaping bacterial community structure and affecting soil multifunctionality. Correspondingly, diverse co-occurrence patterns were observed in different soil types. Full article