Search Results (65)

Betula. platyphylla Sukaczev (B. platyphylla) forest is an important montane forest type. Global warming has impacted its distribution. However, how it affects suitable distribution across ecoregions and corresponding biodiversity protection measures remains unclear. This study used the Maxent model to analyze the suitable distribution and driving variables of B. platyphylla forest in China and its four ecoregions. The minimum cumulative resistance (MCR) model was applied to construct corridors nationwide. Results show that B. platyphylla forest in China is currently mainly distributed in the four ecoregions; specifically, in Gansu and Shaanxi Province in Northwest China, Heilongjiang Province in Northeast China, Sichuan Province in Southwest China, and Hebei Province and Inner Mongolia Autonomous Region in North China. Precipitation and temperature are the main factors affecting suitable distribution. With global warming, the suitable areas in China including the North, Northwest China ecoregions are projected to expand, while Northeast and Southwest China ecoregions will decline. Based on the suitable areas, we considered 45 corridors in China, spanning the four ecoregions. Our results help understand dynamic changes in the distribution of B. platyphylla forest in China under global warming, providing scientific guidance for montane forests’ sustainable development. Full article

The near-surface air temperature lapse rate (SATLR) is a crucial parameter in climate, hydrology, and ecology research conducted in mountainous regions. However, existing research has difficulty characterizing its dynamic changes on an hourly scale. Obtaining data with high spatiotemporal resolution in complex terrains using existing methods poses challenges. This study introduces a hierarchical method for estimating SATLR at high spatiotemporal resolutions based on Fengyun-4A (FY-4A) Advanced Geostationary Radiation Imager (AGRI) land surface temperature (LST) data and machine learning techniques. Based on reconstructed FY-4A AGRI LST data, this study downscales the 4 km resolution data to a 1 km resolution using machine learning. It then estimates the spatial distribution of near-surface air temperature (SAT) and normalized near-surface air temperature (nSAT) by integrating station observations. Subsequently, high spatiotemporal resolution SATLRs are estimated, and their spatial and temporal distribution characteristics in the Beijing–Tianjin–Hebei mountainous region are analyzed. The results indicate that the SATLR exhibits a predominant distribution of 2~6 °C/km annually across the study area. However, in specific regions such as Taihang Mountains in the southwest, Damajun Mountain in the northwest, and certain areas of central Beijing City, the SATLR exceeds 6 °C/km in depth. Conversely, in Chengde City in the northeast and Huapiling in Damajun Mountain in the northwest, the SATLR is shallower than 2 °C/km. Seasonally, the average SATLR displays significant variation, with 3~5 °C/km being prevalent in spring, summer, and autumn, and 2~4 °C/km in winter. Moreover, the diurnal SATLR patterns from the second to fifth altitude grades exhibit consistency throughout the year and across seasons, albeit with varying overall values at different altitudes. Notably, the SATLR of the first altitude grade demonstrates stability within a day at lower elevations. Full article

As a dominant ecological stress factor of climate change, soil drought has become a key challenge restricting food security. Based on soil moisture data, this paper uses the cumulative anomaly method, coefficient of variation, Sen + Mann–Kendall trend analysis, and center of gravity shift model to study the spatiotemporal changes in soil drought in Hebei Province from 2001 to 2020 and uses the optimal parameter geographic detector model to analyze the key factors affecting soil drought. The results show the following: (1) over the past 20 years, soil drought in Hebei Province has shown a trend of “first intensifying and then easing”, experiencing two turning points, and its spatial distribution showed significant agglomeration characteristics. (2) Soil moisture showed single-peak seasonal fluctuation, with severe drought from January to May, peak soil moisture from June to August, soil moisture balance from September to October, and soil moisture deficit intensified in winter. (3) Soil moisture stability showed spatial differentiation, being high in the northeast and low in the southwest. Soil drought in about 70% of the region has improved, and the center of gravity of drought-prone areas has moved to the southwest. (4) NDVI and altitude are the main drivers of soil drought spatial differentiation, and the multi-factor interaction shows a nonlinear enhancement effect. Among them, the parameter thresholds such as NDVI > 0.512 and altitude −32~16 m have a significant inhibitory effect on soil drought. This study can make a contribution to improving water resource management and increasing agricultural productivity in the region. Full article

This longitudinal study applies decade-spanning socioeconomic indicators (2013–2022) from the Beijing–Tianjin–Hebei urban agglomeration. An integrated analytical framework was developed, merging the super-efficiency slack-based measurement (SBM) methodology with entropic weighting techniques to quantify tourism efficiency and economic development. Subsequent phases employed a multi-method analytical cascade: coupling coordination assessment modeling for system interaction analysis, standard deviation ellipses for spatial dispersion characterization, and Markovian transition matrices for temporal pattern identification. The investigation concludes with evolutionary trajectory projections using gray system forecasting GM(1,1) modeling. The analytical findings reveal the following patterns: (1) Within the Beijing–Tianjin–Hebei metropolitan cluster, tourism efficiency demonstrates a consistent upward trajectory, manifesting spatial differentiation characteristics characterized by a dual-core structure centered on Tianjin and Baoding, with higher values observed in northwestern areas compared to southeastern regions. Concurrently, regional disparities exhibit progressive convergence over temporal progression. (2) The level of economic development in the Beijing–Tianjin–Hebei city cluster has been rising steadily, demonstrating a geospatial distribution of ‘central concentration with peripheral attenuation, with the north-east being better than the southwest’, and the gap between the regional differences has become broader over time. (3) The coupling between tourism efficiency and the level of economic development in the Beijing–Tianjin–Hebei city cluster has generally improved, with Beijing and Tianjin predominantly in a coordinated regime, and some cities in Hebei Province about to shift from dysfunctional to coordinated, and, spatially, the coupling and coordination in northern sectors demonstrate superior performance compared to southern counterparts nationally. (4) The coupling coordination degree of the Beijing–Tianjin–Hebei city cluster in the next eight years is predicted by the gray GM(1,1) prediction model and the overall continuation of the growth trend of the Beijing–Tianjin–Hebei city cluster over the past ten years, thus verifying the importance of the regional integrated policy frameworks in the system integration of the Beijing–Tianjin–Hebei metropolitan system. Full article

With the change in climate and rapid social development, the problems of low agricultural water resource utilization efficiency (AWUE) and significant spatiotemporal variability in the Hebei Province of China are becoming increasingly prominent. This paper constructed a framework that considers environmental exogenous variables and selects evaluation indicators based on the Lasso model. It also used the Data Envelopment Analysis (DEA) model to measure AWUE from 2012 to 2021. Furthermore, the Global Moran’s Index (GMI) and Getis Ord Gi * Index (GOGI) were applied to explore characteristics and trends of the spatiotemporal of AWUE. The conclusions are as follows: (1) The AWUE showed a fluctuating development trend of first rising and then falling. However, it did not achieve the effectiveness of DEA in general, and AWUE still had the potential and room for improvement. (2) From the perspective of spatiotemporal variability of AWUE, the northeast region shows better performance than the southwest region. The AWUE among cities and areas had a significant but relatively loose spatial correlation. (3) From 2012 to 2021, the centroid distribution of AWUE hotspots showed a shift from central areas to northeast, with an average annual transfer distance of 11.14 km. In summary, this study emphasizes the urgent need to improve AWUE, which can provide a reference for water resources departments to formulate policy planning and management decisions tailored to local conditions. 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 development of new agricultural business entities in China, a complex competitive evolutionary dynamic has emerged among diversified agricultural business entities (abbreviated as ABEs), including farmers (traditional ABEs), cooperatives, agricultural enterprises, and family farms (new ABEs). Based on the Lotka–Volterra model, the dominance index, the Shannon–Wiener index of ecological theories, and the geo-detector, this study examines the spatiotemporal evolution and driving factors of ABEs’ structural changes across 286 Chinese cities from 2012 to 2021. Key findings include: (1) Farmers maintain absolute numerical dominance, but their relative advantage has declined. (2) The Shannon–Wiener index of diversified ABEs has increased significantly, indicating that differences between ABEs decreased, which means a trend toward structural homogenization. High Shannon–Wiener index values were observed in the Northeast Plain, Xinjiang, Hebei, Gansu, and Shanxi, while low values were concentrated in Yunnan, Guizhou, and the Guangdong-Guangxi region. Both areas experienced a shrinking trend. (3) Agricultural production factors such as multiple cropping indexes and theindustrial structure strongly explained the structural changes to ABEs, while the explanatory power of socio-economic factors can be enhanced after the interaction with agricultural production factors. (4) The relationship between farmers and new ABEs has shifted from a symbiotic relationship favoring farmers to a symbiotic relationship favoring new ABEs, with a significant spatial heterogenous layout among 286 cities. This study proposes a three-stage differentiation framework for ABEs: a simple structure dominated by traditional farmers, a competitive evolutionary dynamic among diversified ABEs, and a modernized structure led by new agricultural business entities. Based on these stages, this paper provides targeted recommendations for building a high-quality ABE system and advancing agricultural modernization. Full article

With rapid economic development and the change in land use patterns, the region faces the environmental challenge of increasing carbon emission risk. The research on analyzing and identifying carbon emission risk of land use is helpful to realize regional sustainable development. This study takes the Yanshan-Taihang Mountain area of Hebei Province as a case study. Based on the remote sensing monitoring data of land use in 2010, 2015, and 2020, the carbon emissions of land use are calculated by direct and indirect calculation methods. Then, the carbon footprint pressure index and land use carbon emission risk index are introduced to analyze the temporal and spatial differentiation characteristics of land use carbon emission risk in the study area. The findings indicate that carbon emissions associated with land use in the study area initially exhibited an increasing trend, followed by a subsequent decline over time. In space, the high-value areas of carbon emissions are mainly distributed in the south of the study area, and the low-value areas of carbon emissions are mainly concentrated in the northeast of the study area. The region experiences significant carbon-cycling pressure and environmental risk, with the proportion of counties in carbon balance areas decreasing from 27.27% in 2010 to 18.18% in 2020, and the proportion of counties in carbon imbalance areas increasing from 72.72% in 2010 to 81.82% in 2020. The carbon emission risk of land use is divided into micro-risk area, low-risk area, medium-risk area, high-risk area, and severe-risk area. From 2010 to 2020, there was an 18.18% increase in the percentage of counties classified as high-risk and severe-risk areas. Additionally, the regions identified as hotspots for land use emissions exhibited a trend in expansion. This phenomenon indicates that these areas have not successfully managed to mitigate environmental pollution or ensure the sustainable use of resources in the context of their economic development efforts. This series of dynamic changes shows that the study area is facing the challenge of increasing carbon emission risk from land use. Governments at all levels should strengthen environmental governance in high-risk areas, implement stricter land use policies, and promote green development and cleaner production to attain a mutually beneficial outcome for both economic development and ecological protection. Full article

Urbanization and industrialization have led to obvious changes in the ecological environment and landscape pattern in the Beijing–Tianjin–Hebei region. Therefore, it is crucial to clarify the spatial–temporal changes in vegetation cover and its landscape pattern and conduct its analysis with the driving factors for ecological preservation in the Beijing–Tianjin–Hebei region. This study combined AVHRR GIMMS NDVI and MODIS NDVI data based on the ESTARFM model to obtain a high spatial–temporal resolution for vegetation cover; it then analyzed the vegetation cover changes at the type and landscape scales using a landscape index and explored the driving factors of the landscape pattern through principal component analysis. The results show that (1) the vegetation is mainly of medium and higher coverage and is distributed in the northeast, the western part of the Taihang Mountains and the central plains in the study area. From 1985 to 2022, there was no statistically significant difference in the overall change in its coverage. (2) From 1985 to 2022, at the landscape level, the vegetation cover landscape exhibited the following characteristics: increased fragmentation, an increase in the complexity of the landscape shape, a decrease in connectivity, a discrete landscape and a decrease in species diversity. At the type level, the medium vegetation demonstrated the most significant degree of fragmentation. The high-vegetation-cover areas exhibited a more concentrated distribution. Additionally, the low, lower and higher vegetation types displayed an increase in complexity, shape, discreteness and heterogeneity within the landscape. (3) Meanwhile, the principal component analysis showed that the changes in the landscape pattern of vegetation cover were mainly the result of the combined effects of climatic and anthropogenic factors in the Beijing–Tianjin–Hebei region. The human factor played the dominant role; this was followed by larger contributions from climatic factors. In addition to offering pertinent scientific insights for the maximization of the ecological environment and the fostering of regional ecological and sustainable development in the Beijing–Tianjin–Hebei region, the aforementioned analysis and research could serve as the foundation for the sustainable management and planning of vegetation cover. Full article

Genetic diversity analysis provides the scientific basis for the preservation, evaluation, and utilization of the germplasm resources of tree species. We explored the genetic diversity and structure of Populus tomentosa elite trees in North China using 13 nuclear microsatellite markers. We compared nine groups of accessions including 20 originating from Beijing (BJ), 122 from Hebei (HB), 20 from Shandong (SD), 113 from Henan (HN), 270 from Shanxi (SX), 54 from Shaanxi (SAX), 8 from Gansu (GS), 10 from Anhui (AH), and 6 from Jiangsu (JS). All of the studied primer pairs were polymorphic and generated 125 alleles. Analyses of molecular variance revealed that 79%, 14%, and 8% of the total variation was due to variations within the individual, among individuals, and among populations, respectively. Based on principal coordinate and STRUCTURE cluster analyses, individuals distributed in the southern region (HN, SAX, AH, and JS) were roughly classified into one group, while those distributed in the northeastern region (BJ, HB, and SD) and northwestern regions (SX) were separately divided into one group each. Moreover, the northwestern region included two-thirds of the SX trees, and the remainder were in the northeast region. By analyzing genetic diversity and structure within populations, individuals with different genetic backgrounds were screened for constituent training populations (TRS), including broad allelic variation for related traits. This ensures that the genomic prediction model can accurately capture genetic effects and provide reliable predictions across a broad spectrum of genetic backgrounds. Therefore, our results will benefit genome breeding technology. Full article

Acer truncatum is a unique multipurpose woody oil species in China. It is crucial to study the geographical distribution patterns of fruit utilization of A. truncatum under climate change scenarios to ensure the rational site selection and germplasm resource protection of this tree. In this study, the Maxent model and Geographic Information System (GIS) spatial analysis technology were used to construct a suitable area model for the plant under current climate conditions by selecting 138 sample points and 15 ecological factors, and to predict the potentially suitable areas under four climate scenarios in 2050 and 2070. The results showed that under current conditions, the main suitable areas were concentrated in China, such as Inner Mongolia, Shaanxi and Hebei, with an area of 1.64 × 10⁶ km². Under future conditions, the suitable area in 2050 and 2070 showed an expanding trend compared with that in the current period, and the expansion ratios were as high as 36.52% and 45.80% under the RCP2.6-2050 and RCP8.5-2070 scenarios, respectively. The expansion area is concentrated in the middle latitudes of China (38° N~52° N), basically covering the middle and northeast of Inner Mongolia and the middle and north of Heilongjiang, while the loss area is mainly located in northern Sichuan, northern Hubei and eastern Henan. The center of the suitable area is expected to migrate to the northeast in 2050 and 2070, with a maximum migration distance of 355.46 km. Under future conditions, the suitable area shrinks in low-latitude regions and expands in high-latitude regions, and the expanded area becomes larger than the contracted area. This conclusion provides important guidelines for the directional cultivation of A. truncatum for utilization of its fruit. Full article

The Beijing–Tianjin–Hebei region (BTH) is one of the crucial areas for economic development in China. However, rapid urban expansion and industrial development in this region have severely impacted the surrounding ecological environment. The air quality, water, and soil resources face significant pressure. Due to the close relationship between land utilization, population, investment, and industry, effective land use is a key factor in the coordinated development of the region. Therefore, clarifying the patterns of urban land use change and revealing its influencing factors can provide important scientific evidence for the coordinated development of the BTH region. This study aims to improve urban land use efficiency (ULUE) in the BTH region. Firstly, based on the input and output data of land elements for the 13 cities in the BTH region, the Data Envelopment Analysis (DEA) method is used to quantify the ULUE of the BTH urban agglomeration and analyze the spatiotemporal characteristics of ULUE. Input indicators includes capital, labor, and land. Output indicators includes economy, society, and environment. The results show that the overall ULUE in the BTH region has increased, albeit with notable fluctuations. Between 2000 and 2010, ULUE rose swiftly across all cities except Beijing and Tianjin, where changes were minimal. Post-2010, cities exhibited varied trends: steady growth, slow growth, sustained growth, step-wise growth, and initial growth followed by decline. Spatially, before 2010, the BTH showed a “high in the northeast and low in the southwest” pattern, transitioning post-2010 to a smoother “core-periphery” pattern. Mid-epidemic, high ULUE values reverted to the core area, shifting southward post-epidemic. Secondly, panel data analysis is conducted to explore the factors influencing ULUE. The results indicate that fiscal balance, the level of openness, the level of digitalization, industrial structure, and the level of green development are significant factors affecting ULUE. Finally, strategies are proposed to improve ULUE in the BTH region, including national spatial planning, industrial layout, existing land use, infrastructure construction, optimization of local fiscal revenue, and improvement in the business environment, aiming to enhance ULUE and promote the coordinated development of industries in the BTH region. Full article

The evaluation and analysis of the ecological vulnerability of urban green-space systems are conducive to the sustainable development of urban green-space systems. Taking the urban green-space system in the Beijing–Tianjin–Hebei region in 2010, 2015, and 2020 as the research object, an ESSR model was first constructed, and a total of ten types of impact factors were integrated into the four dimensions of “Exposure, Sensitivity, State and Response”. The weight of the impact factors was objectively determined via spatial principal component analysis, and the ecological vulnerability of the urban green-space system was evaluated via superposition analysis; the evaluation’s results were graded. Moreover, the transfer matrix, center-of-gravity migration model, standard deviation ellipse, and spatial autocorrelation analysis were used to study the temporal and spatial variation characteristics of the evaluation results; then, the driving force of impact factors was analyzed based on a geographical detector. Finally, the rationality of the evaluation results was verified using the changing trend of the remote sensing ecological index (RSEI). The results show that the ecological vulnerability of the urban green-space system in the Beijing–Tianjin–Hebei region has decreased year by year for the past ten years. The distribution law of “Hebei surrounds Beijing and Tianjin” is presented in this space, and 2015 is the mutation node. In 2010, the moderately and severely vulnerable areas of Hebei surrounded the mildly vulnerability areas of Beijing and Tianjin. Moreover, in 2015 and 2020, the mildly vulnerable areas of Hebei surrounded the severely vulnerable areas of Beijing and Tianjin. Vulnerability expands slightly in the east–west direction and shrinks slightly in the north–south direction, and the center of gravity shifts towards Beijing year by year along the northeast direction. Moreover, the spatial distribution of vulnerability shows significant positive spatial autocorrelations and exhibits very obvious agglomeration. In addition, vulnerability is the result of the combined effect of various factors, and education degree, human disturbance index, and annual average precipitation are the dominant factors. The analysis results provide a reference for the effective application and sustainable development of urban green-space ecological functions. Full article

Contemporary research on terrestrial carbon exchange processes is paramount for a nuanced comprehension of global and local climatic fluctuations and their interaction with anthropogenic activities. This study delves into the spatiotemporal dynamics of vegetation carbon exchanges within the Three Northern Protection Forest Project Area, leveraging two decades of MODIS NPP data and an innovative NEP estimation model. Our analysis highlights a generally increasing trend in Net Ecosystem Productivity (NEP) from 2000 to 2020, with significant growth in approximately 32.97% of the study area and slight increases in 24.18%. Notably, lower NEP values were found in desert and arid zones, whereas higher values were observed in more vegetated regions like Ningxia, Hebei, Inner Mongolia, and the northeast. The study also assesses the impact of climate variables and land-use changes on NEP, identifying both negative and positive correlations in specific regions. Despite the overall positive trend towards ecological restoration and enhancement, significant uncertainties remain, emphasizing the urgent need for further research to support ecosystem resilience and sustainable management practices. Full article

The mechanism of aerosol pollution transport remains highly elusive owing to the myriad of influential factors. In this study, ground station data, satellite data, ground-based LiDAR remote sensing data, sounding data, ERA5 reanalysis and a backward trajectory model were combined to investigate the formation process and optical properties of winter aerosol pollution in Beijing and surrounding areas. The analysis of ground station data shows that compared to 2019 and 2021, the pandemic lockdown policy resulted in a decrease in the total number of pollution days and a decrease in the average concentration of particulate matter in the Beijing area in 2020. The terrain characteristics of the Beijing-Tianjin-Hebei (BTH) made it prone to northeast and southwest winds. The highest incidence of aerosol pollution in Beijing occurs in February and March during the spring and winter seasons. Analysis of a typical heavy aerosol pollution process in the Beijing area from 28 February to 5 March 2019 shows that dust and fine particulate matter contributed to the primary pollution; surface air temperature inversion and an average wind speed of less than 3 m/s were conducive to the continuous accumulation of pollutants, which was accompanied by the oxidation reaction of NO₂ and O₃, forming photochemical pollution. The heavy aerosol pollution was transmitted and diffused towards the southeast, gradually eliminating the pollution. Our results provide relevant research support for the prevention and control of aerosol pollution. Full article