Search Results (143)

Seed oil represents a key trait in soybeans, which holds substantial economic significance, contributing to roughly 60% of global oilseed production. This research employed genome-wide association mapping to identify genetic loci associated with oil content in soybean seeds. A panel comprising 341 soybean accessions, primarily sourced from Northeast China, was assessed for seed oil content at Heilongjiang Province in three replications over two growing seasons (2021 and 2023) and underwent genotyping via whole-genome resequencing, resulting in 1,048,576 high-quality SNP markers. Phenotypic analysis indicated notable variation in oil content, ranging from 11.00% to 21.77%, with an average increase of 1.73% to 2.28% across all growing regions between 2021 and 2023. A genome-wide association study (GWAS) analysis revealed 119 significant single-nucleotide polymorphism (SNP) loci associated with oil content, with a prominent cluster of 77 SNPs located on chromosome 8. Candidate gene analysis identified four key genes potentially implicated in oil content regulation, selected based on proximity to significant SNPs (≤10 kb) and functional annotation related to lipid metabolism and signal transduction. Notably, Glyma.08G123500, encoding a receptor-like kinase involved in signal transduction, contained multiple significant SNPs with PROVEAN scores ranging from deleterious (−1.633) to neutral (0.933), indicating complex functional impacts on protein function. Additional candidate genes include Glyma.08G110000 (hydroxycinnamoyl-CoA transferase), Glyma.08G117400 (PPR repeat protein), and Glyma.08G117600 (WD40 repeat protein), each showing distinct expression patterns and functional roles. Some SNP clusters were associated with increased oil content, while others correlated with decreased oil content, indicating complex genetic regulation of this trait. The findings provide molecular markers with potential for marker-assisted selection (MAS) in breeding programs aimed at increasing soybean oil content and enhancing our understanding of the genetic architecture governing this critical agricultural trait. Full article

Carbon emissions from freshwater aquaculture can exacerbate the greenhouse effect, thereby impacting human life and health. Consequently, it is of great significance to explore the carbon peak process and the role of emission reduction data in China’s freshwater aquaculture industry. This study innovatively employs the Logarithmic Mean Divisia Index model (LMDI) and the Tapio decoupling model to conduct an in-depth analysis of the relationship between carbon emissions and output values in the freshwater aquaculture industry, accurately identifying the main driving factors. Meanwhile, the global and local Moran’s I indices are introduced to analyze its spatial correlation from a new perspective. The results indicate that from 2013 to 2023, carbon emissions from China’s freshwater aquaculture industry exhibited a quasi-“N”-shaped trend, reaching a peak of 38 million tons in 2015. East China was the primary contributor to carbon emissions, accounting for 46%, while South China, Central China, and Northeast China each had an average annual share of around 14%, with Southwest, North China, and Northwest China contributing relatively small proportions. The global Moran’s I index showed a decreasing trend, with a p-value ≤ 0.0010 and a z-score > 3.3, indicating a 99% significant spatial correlation. High-high clusters were concentrated in some provinces of East China, while low-low clusters were found in Northwest, North, and Southwest China. The level of fishery economic development positively drove carbon emissions, whereas freshwater aquaculture production efficiency, industrial structure, and the scale of the aquaculture population had negative effects on carbon emissions. During the study period, carbon emissions exhibited three states: weak decoupling, strong decoupling, and expansive negative decoupling, with alternating strong and weak decoupling occurring after 2015. Full article

Currently, the Longmaxi shale in the Sichuan Basin is the most successful stratum of shale gas production in China. However, because Longmaxi shale mostly has high over-maturity, a low-maturity sample cannot be obtained for gas generation thermal simulations, and as a result, a gas generation model has not yet been established for it. Therefore, models of other shales are usually used to calculate the amount of gas generated from Longmaxi shale, but they may produce inaccurate results. In this study, a Longmaxi shale sample with an equivalent vitrinite reflectance calculated from Raman spectroscopy (EqVR_o) of 1.26% was obtained from Well Yucan 1 in the Chengkou area, northeast Sichuan Province. This Longmaxi shale may have the lowest maturity in nature. Pyrolysis simulations based on gold tubes were performed on this sample, and the gas generation line was obtained. The amount of gas generated during the low-maturity stage was compensated by referring to gas generation data obtained from Lower Silurian black shale in western Lithuania. Thus, a gas generation model of the Longmaxi shale was built. The model showed that the gas generation process of Longmaxi shale could be divided into three stages: (1) First, there is the quick generation stage (EqVR_o 0.5–3.0%), where hydrocarbon gases were generated quickly and constantly, and the generation rate was steady. A maximum of 458 mL/g TOC was reached at a maturity of 3.0% EqVR_o. (2) Second, there is the stable stage (EqVR_o 3.0–3.25%), where the amount of generated gas reached a plateau of 453–458 mL/g TOC. (3) Third, there is the rapid descent stage (EqVR_o > 3.25%), where the amount of generated gas started to decrease, and it was 393 mL/g TOC at an EqVR_o of 3.34%. This model allows us to more accurately calculate the amount of gas generated from the Longmaxi shale in the Sichuan Basin. Full article

On 5 September 2022, a Mw 6.6 earthquake occurred in Luding, Sichuan Province, China. The epicenter of this earthquake was located in the vicinity of Mt. Gongga. The China Earthquake Administration employed the Global Navigation Satellite System (GNSS) to conduct concurrent deformation field monitoring of the main fault associated with the Luding earthquake. The research area surrounding Mt. Gongga exhibits intricate structural and dynamic processes. However, previous studies have lacked a comprehensive three-dimensional analysis of the uplift mechanism of Mt. Gongga. This study utilizes GNSS data to constrain simulations and employs the FLAC3D numerical model to simulate the primary fault movement during the earthquake and the subsequent changes in the uplift of Mt. Gongga. These investigations are supported by seismic analysis, mechanical analysis, and inversion studies, facilitating the formulation of its uplift mechanism. The results indicate the following: (1) The seismic source analysis of the earthquake reveals a steep dip angle of the primary fault plane, with a predominant inclination toward the northeast. (2) Numerical simulations demonstrate a consistent correlation between the horizontal displacement pattern and the arcuate structure of the Sichuan–Yunnan block, promoting the counterclockwise uplift of Mt. Gongga. The vertical displacement pattern indicates that this earthquake accelerated the overall uplift of Mt. Gongga. (3) Mt. Gongga undergoes a multiple coupling uplift mechanism characterized by “clockwise uplift + rotational flexure + asthenospheric upwelling”. Seismic analysis, mechanical analysis and the results of numerical inversion serve as a useful basis for understanding the uplift of Mt. Gongga and for understanding high mountain uplift in orogen-foreland systems in general. 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

Against the backdrop of sustainable development and from a macro perspective, this paper focuses on the cultural and tourism industry, measures its sustainable development efficiency, analyzes influencing factors, and systematically explores improvement paths. Based on the theoretical perspective of sustainable development, this study has constructed an evaluation index system for measuring the sustainable development level of the cultural and tourism industry across four dimensions, as follows: cultural and tourism economic construction, cultural and tourism basic resources, social basic support, and ecological environment quality. The range entropy value was adopted to measure the sustainable development level of the cultural and tourism industry in 31 provinces of China from 2006 to 2023. The results show that the sustainable development level of China’s cultural and tourism industry is generally low, but shows an increasing trend. In terms of the annual growth rate of regional scores, the trend is as follows: North China (7.05%) > Central South (6.00%) > East China (5.97%) > Southwest (5.03%) > Northwest (4.56%) > Northeast (2.94%). This indicates considerable room for improvement in the future. Furthermore, this study used kernel density estimation to analyze the distribution dynamics and evolution trends of the sustainable development level of the cultural and tourism industry and its scores at all levels, revealing differences in development levels among provinces and regions. Finally, this study has innovatively adopted the fsQCA method to explore improvement paths for the sustainable development level of the cultural and tourism industry, and identified three implementation paths: “openness–human resources–consumption–environment-driven”, “human resources–consumption–environment-driven”, and “openness–environment-driven”. By constructing a multi-condition combination model, this study breaks through the limitations of traditional single-factor analysis and reveals multiple concurrent causal relationships in complex situations. This approach showcases the differentiated development models of each province under the interacting effects of multi-dimensional factors, and provides policymakers with a basis for precise policy implementation “tailored to local conditions and multi-dimensional collaboration”. Full article

Ensuring the security of agricultural systems is essential for achieving national food security and sustainable development. Given that agricultural systems are inherently complex and composed of coupled subsystems—such as water, land, and energy—a comprehensive and multidimensional assessment of system security is necessary. This study focuses on Northeast China, a major food-producing region, and introduces the concept of agricultural system coupling security, defined as the integrated performance of an agricultural system in terms of resource adequacy, internal coordination, and adaptive resilience under external stress. To operationalize this concept, a coupling security evaluation framework is constructed based on three key dimensions: reliability (Rel), coordination (Cor), and resilience (Res). An Agricultural System Coupling Security Index (AS-CSI) is developed using the entropy weight method, the Criteria Importance Through Intercriteria Correlation (CRITIC) method, and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method, while obstacle factor diagnosis is employed to identify key constraints. Furthermore, bivariate and trivariate Copula models are used to estimate joint risk probabilities. The results show that from 2001 to 2022, the AS-CSI in Northeast China increased from 0.38 to 0.62, indicating a transition from insecurity to relative security. Among the provinces, Jilin exhibited the highest CSI due to balanced performance across all Rel-Cor-Res dimensions, while Liaoning experienced lower Rel, hindering its overall security level. Five indicators, including area under soil erosion control, reservoir storage capacity per capita, pesticide application amount, rural electricity consumption per capita, and proportion of agricultural water use, were identified as critical threats to regional agricultural system security. Copula-based risk analysis revealed that the probability of Rel–Cor reaching the relatively secure threshold (0.8) was the highest at 0.7643, and the probabilities for Rel–Res and Cor–Res to reach the same threshold were lower, at 0.7164 and 0.7318, respectively. The probability of Rel–Cor-Res reaching the relatively secure threshold (0.8) exceeds 0.54, with Jilin exhibiting the highest probability at 0.5538. This study provides valuable insights for transitioning from static assessments to dynamic risk identification and offers a scientific basis for enhancing regional sustainability and economic resilience in agricultural systems. Full article

As urbanization progresses at an accelerating pace, the depletion of natural resources and environmental degradation are becoming increasingly severe. Constructing ecological security patterns (ESPs) has become a crucial strategy for mitigating environmental stress and promoting sustainable social development. Currently, the methods for constructing ESPs remain under exploration. Particularly, in the identification of ecological sources, insufficient emphasis has been placed on trade-offs among ecosystem services (ESs). This study focuses on Liaoning Province, situated in China’s northeast revitalization area—a region with a developed heavy industry and abundant ecological resources. The InVEST model was employed to assess ESs, and the ordered weighted average (OWA) method was utilized to identify ecological sources. By integrating both natural and social factors, the ecological resistance surface was constructed, and circuit theory was applied to determine ecological corridors, ultimately leading to the development of an ESP. The results show that (1) between 2010, 2015, and 2020, water yield continued to increase, habitat quality continuously declined, soil conservation tended to decrease and then gradually increase, and carbon storage tended to increase and then decrease. The four ESs show similar spatial features, characterized by elevated levels in the eastern and western areas and a comparatively reduced level in the central region; (2) a total of 179 ecological sources were identified, covering 26,235.34 km². The overall distribution showed a concentration in the east, with a fragmented and dispersed pattern in the southwest. The identification of 435 ecological corridors, with an overall length totaling 8794.59 km, resulted in a network-like distribution pattern. Additionally, 65 ecological pinch points and 67 barrier points were identified; and (3) a “four zones, three corridors, and two belts” pattern of ecological protection and restoration has been proposed. The findings offer valuable insights for Liaoning Province and other rapidly developing regions facing escalating environmental pressures. Full article

Multiple occurrences of adakitic rocks, with crystallization ages clustering around ~160 Ma, have been documented in the Zhuxi district, northeast Jiangxi Province, South China. This research identifies a new adakitic biotite granite porphyry within the Zhuxi W-Cu polymetallic deposit. Zircon U-Pb geochronology of this porphyry yields a crystallization age of 161.6 ± 2.1 Ma. Integrated with previously published data, the adakitic rocks in the study area—comprising diorite porphyrite, biotite quartz monzonite porphyry, and the newly identified biotite granite porphyry—are predominantly calc-alkaline and peraluminous. They exhibit enrichment in light rare-earth elements (LREEs) and depletion in heavy rare-earth elements (HREEs), with slight negative Eu anomalies. The trace element patterns are characterized by enrichment in Ba, U, K, Pb, and Sr, alongside negative Nb, Ta, P, and Ti anomalies, indicative of arc-like magmatic signatures. Comparative analysis of geological and geochemical characteristics suggests that these three rock types are not comagmatic. Petrogenesis of the Zhuxi adakitic suite is linked to a dynamic tectonic regime involving Mesozoic crustal thickening, subsequent delamination, and lithospheric extension. Asthenospheric upwelling likely triggered partial melting of the overlying metasomatized lithospheric mantle, generating primary mantle-derived magmas. Underplating and advection of heat by these magmas induced partial melting of the thickened lower crust, forming the biotite granite porphyry. Partial melting of delaminated lower crustal material, interacting with the asthenosphere or asthenosphere-derived melts, likely generated the diorite porphyrite. The biotite quartz monzonite porphyry is interpreted to have formed from mantle-derived magmas that underwent assimilation of, or mixing with, silicic crustal melts during ascent. The ~160 Ma crystallization ages of these adakitic rocks are broadly contemporaneous with W-Mo mineralization in the Taqian mining area of the Zhuxi district. Furthermore, their geochemical signatures imply a prospective metallogenic setting for Cu-Mo mineralization around this period in the Taqian area. Full article

The Cuyu gold deposit in central Jilin Province in Northeast China is located in the eastern segment of the northern margin of the North China Craton (NCC), as well as the eastern segment of the Xing’an–Mongolian Orogenic Belt (XMOB). Gold ore-bodies are controlled by NW-trending faults and mainly occur in late Hercynian granodiorite. The mineralization process in the Cuyu deposit can be divided into three stages: quartz + coarse grained arsenopyrite + pyrite (stage I), quartz + sericite + pyrite + arsenopyrite + electrum + chalcopyrite + sphalerite (stage II), and quartz + calcite ± pyrite (stage III). Stage II is the most important for gold mineralization. We conducted analyses including petrography, microthermometry, laser Raman spectroscopy of fluid inclusions, and H–O–S–Pb isotopic analysis to elucidate the mineralization processes in the Cuyu deposit. Five types of primary fluid inclusions (FIs) are present in the hydrothermal quartz and calcite grains of the ore: liquid-rich two-phase aqueous fluid inclusions (L-type), vapor-rich two-phase aqueous fluid inclusions (V-type), CO₂-bearing two- or three-phase inclusions (C1-type), CO₂-rich two- or three-phase inclusions (C2-type), and pure CO₂ mono-phase inclusions (C3-type). From stages I to III, the fluid inclusion assemblages changed from L-, C2-, and C3-types to L-, V-, C1-, C2-, and C3-types and, finally, to L-types only. The corresponding homogenization temperatures for stages I to III were 242–326 °C, 202–298 °C, and 106–188 °C, and the salinities were 4.69–9.73, 1.63–7.30, and 1.39–3.53 wt.% NaCl equiv., respectively. The ore-forming fluid system evolved from a NaCl-H₂O-CO₂ ± CH₄ ± H₂S fluid system in stage I and II with immiscible characteristics to a homogeneous NaC-H₂O fluid system in stage III. Microthermometric data for stages I to III show a decreasing trend in homogenization temperatures and salinities. The mineral assemblages, fluid inclusions, and H–O–S–Pb isotopes indicate that the initial ore-forming fluids of stage I were exsolved from diorite porphyrite and characterized by a high temperature and low salinity. The addition of meteoric water in large quantities led to decreases in temperature and pressure, resulting in a NaCl-H₂O-CO₂ ± CH₄ ± H₂S fluid system with significant immiscibility in stage II, facilitating the deposition of gold and associated polymetallic sulfides. The Cuyu gold deposit has a similar ore genesis to those of gold deposits in the Jiapigou–Haigou gold belt (JHGB) of southeastern Jilin Province indicating potential for gold prospecting in the northwest-trending seam of the JHGB. Full article

The Wenchuan earthquake (Ms8.0), which struck Sichuan Province, China, on 12 May 2008, was one of the most devastating seismic events in recent Chinese history. It resulted in the deaths of nearly 90,000 people, left millions homeless, and caused widespread destruction of infrastructure across a vast area. In addition to the severe ground shaking and surface rupture, a variety of unusual atmospheric/ionospheric and geophysical phenomena were reported in the days and hours leading up to the earthquake. Notably, iridescent clouds were observed just before the earthquake at three distinct locations approximately 450–550 km northeast of the epicenter. These clouds appeared as fragmented rainbows located beneath the sun and were characterized by their short lifespan, lasting only 1–10 min. Moreover, they exhibited striped patterns within the iridescent regions, suggesting the influence of an external electric field. These features cannot be adequately explained by the well-known meteorological phenomenon of circumhorizontal arcs, raising the possibility of a different origin. The formation mechanism of these clouds remains unclear. In this study, we explore the hypothesis that the iridescent clouds were precursory phenomena associated with the impending earthquake. Specifically, we examine a potential causal relationship between the appearance of these clouds and the geological environment of the earthquake source. We propose a novel model in which electrical disturbances generated along the fault system immediately before the mainshock propagated upward and interacted with the ionosphere, resulting in the creation of a localized electric field. This electric field, in turn, induced electro-optic effects that altered the scattering of sunlight and projected iridescent patterns onto cirrus clouds, leading to the observed phenomena. Full article

Land urbanization (LU) is a defining feature of China’s urbanization process and has led to significant carbon emission challenges. To clarify the interaction mechanism between LU and carbon emissions (CEs), this study examines the temporal and spatial characteristics of LU and CEs as well as the direct and spatial spillover effects in the east of the Hu Line. Specifically, three representative regions are selected for heterogeneity analysis: the Three Northeast Provinces region (TNP), the Beijing–Tianjin–Hebei region (BTH), and the Southeast Coastal region (SC). The findings are as follows: (1) Both LU and CEs exhibited consistent upward trends, with average annual growth rates of 4.3% and 3.5%, respectively. (2) Empirical results demonstrate that the direct and indirect effect coefficients of LU on CEs are 0.129 and −0.224, respectively. (3) The direct effect of LU on CEs is significantly positive in both the TNP and the SC, with respective coefficients of 0.336 and 0.177. Notably, a positive spatial spillover effect is observed exclusively in the TNP, with a coefficient of 0.174. In contrast, LU exerts no significant influence on CEs in the BTH. The research findings offer valuable insights into the formulation of differentiated urbanization policies and effective carbon emission reduction policies. Full article

With the transformation of the global energy structure and the rapid development of new power generation technologies, new power system planning faces the challenge of multi-source–storage coordinated deployment. This paper proposes a new power system planning method, the collaborative planning of source–grid–load–storage, considering wind and photovoltaic power generation systems. First, taking into account the access of renewable energy such as wind and solar power, a renewable energy output model is constructed. Secondly, a typical intraday dispatch model of the new power system is constructed; on this basis, by adding constraints of different types of power sources, a multi-source and storage coordinated deployment planning model is constructed. Finally, through actual case studies in three provinces of Northeast China, the effectiveness of the proposed method is analyzed and verified. The results show that compared with traditional planning methods, the method proposed in this paper can significantly improve the economy and environmental friendliness of the system while meeting the requirements of power supply security. 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 flow of resources and participation of diverse entities in the information age drive the formation of innovation networks, yet how these networks evolve in strategic emerging industries—particularly in transitioning regions like Northeast China—remains underexplored. This study investigates the spatial formation and evolution of cooperative innovation networks in strategic emerging industries, as well as the underlying mechanisms driving their development and transformation. Focusing on China’s three northeastern provinces—a representative old industrial base undergoing transformation—we construct and analyze inter- and intra-city cooperative innovation networks from 2009 to 2023 using invention patent data. Employing social network analysis and spatial econometric models, we reveal that while the external network exhibits limited expansion with Beijing as a dominant hub, the internal network demonstrates increasing cohesion, transitioning to a multi-core structure. Factors such as urban innovation capacity, economic proximity, and institutional proximity play key roles in shaping these networks. These findings offer policymakers empirical evidence to strategically optimize cross-regional innovation ecosystems in resource-dependent regions, supporting urban sustainability and fostering innovation-driven development. Full article