Spatial Distribution Patterns Research Articles

Analytical solution of surrounding rock stress and plastic zone of rectangular roadway under non-uniform stress field

The shape and extent of the plastic zone can effectively reflect the degree of deformation and failure of the surrounding rock. By applying complex variable functions and the theory of elasticity, a mechanical model for the surrounding rock of a rectangular roadway is established. The analytical solution for the stress in the surrounding rock of a rectangular roadway under a non-uniform stress field is derived, and the spatial stress distribution pattern in the surrounding rock of the rectangular roadway is obtained. Furthermore, using the Mohr-Coulomb criterion, the boundary equation of the plastic zone in the surrounding rock of a rectangular roadway is derived, and the morphological characteristics of the plastic zone are obtained. The results indicate that the plastic zones on both sides of the rectangular roadway are arc-shaped. The asymmetry of the stress environment has a significant impact on the plastic zones in the roof and floor of the rectangular roadway, causing the shape of the plastic zones to resemble a “petal” pattern. The lateral pressure coefficient and the height-to-width ratio have a significant impact on the stress distribution and the morphological characteristics of the plastic zone in the surrounding rock of the rectangular roadway. By validating the computational accuracy of the analytical solution through numerical simulations and conducting an engineering applicability analysis based on a coal mine roadway, it has been demonstrated that the analytical calculation method is both rational and possesses good engineering applicability. This provides reliable theoretical guidance for the design calculations and construction planning of similar roadway projects.

Spatiotemporal Dynamics and Prediction of Habitat Quality Based on Land Use and Cover Change in Jiangsu, China

Analyzing the spatiotemporal evolution characteristics of urban land use and habitat quality is crucial for the sustainable development of urban ecological environments. This study utilizes the land use data of Jiangsu Province for the years 2000, 2010, and 2020, applying the FLUS model to investigate the driving force behind land expansion and to simulate a prediction for the land use of 2030. By integrating the InVEST model and landscape pattern indices, this study analyzes the spatiotemporal evolution characteristics of habitat quality in Jiangsu Province and uses geographical detector analysis to examine the synergistic effects of influencing factors. The results indicate that, from 2000 to 2020, habitat degradation in Jiangsu Province progressively increased, with the spatial distribution of degradation levels showing a gradual change. Under the ecological protection scenario in 2030, habitat fragmentation was alleviated. Conversely, under the economic development scenario, habitat quality further deteriorated, resulting in the largest area of low-quality regions. Minimal changes occurred under the natural development scenario. (2) The landscape indices in Jiangsu Province experienced significant changes from 2000 to 2020. The continuous expansion of urban land into other land use types led to a trend of fragmentation, with a clear increasing trend in dispersion, sprawl, and Shannon’s diversity index, accompanied by a decrease in cohesion. (3) The dominant interacting factors affecting habitat quality were combinations of socioeconomic factors with other factors, indicating that the economy largely determines the spatial distribution pattern of habitat quality. The findings of this study provide optimization strategies for future spatial planning of land use types in Jiangsu Province and offer references for habitat quality restoration efforts in the region.

Spatial Patterns and Influencing Factors of People’s Commune Sites: A Case Study of Henan Province, China

The people’s commune was a social practice for achieving a communist society after the establishment of New China, but they were dismantled in the early 1980s, along with their legacy. This paper analyzes people’s commune sites, offering guidance for their protection and development. This study used the historical place names of the communes recorded in the Overview of People’s Commune, compiled a comprehensive database of people’s commune sites, and mathematically analyzed the quantity and type of communes. The spatial pattern of people’s commune sites was described via average nearest neighbors, spatial variability, kernel density analysis, and spatial correlation. Moreover, the driving mechanism was measured using the geodetector model. The survey results revealed 327 points related to people’s communes, which were categorized into three main types: agriculture-oriented, industry-oriented, and integrated. Agriculture-oriented communes are the most significant type of people’s commune, accounting for 87.0%. Communes in the northern region of Henan Province are more densely clustered, whereas those in the southeastern region are less concentrated. Moreover, precipitation is the most critical factor affecting the spatial pattern of people’s commune sites, followed by railroad accessibility. A comprehensive literature analysis revealed that water conservancy projects limited the development of communes during the people’s commune period. This paper analyzes the spatial distribution patterns of the sites that have existed historically according to historical gazetteers, revealing the factors that influenced the development of this particular political system. It enriches the spatial scope of the study of people’s communes and provides theoretical references for the future preservation of communal heritage from the perspective of regional heritage.

Topography Dominates the Spatial and Temporal Variability of Soil Bulk Density in Typical Arid Zones

Soil bulk density is a crucial indicator for assessing soil matter storage and soil quality. Due to the complexity of sampling soil bulk density, particularly in deeper layers, it is essential to study the spatial distribution patterns of soil bulk density and their influencing factors. To address the gap in large-scale studies of vertical (from surface to deeper layers) and horizontal (across a broad area) variations in soil bulk density in arid regions, this study focuses on Changji Prefecture, located in the central northern slope of the Tianshan Mountains and characterized by typical vertical zonation. By integrating classical statistics, geostatistics, and geographic information systems (GISs), this study investigates the spatial distribution patterns and driving factors of soil bulk density. The results indicate that soil bulk density in Changji Prefecture increases with soil depth, with significantly lower values in the surface layer than in deeper layers. Spatially, despite minimal variation in latitude, there is considerable elevation difference within the study area, with the lowest elevations in the central region. Soil bulk density exhibits a spatial distribution pattern of higher values in the northeast (desert areas) and lower values in the southwest (forest areas). The nugget effect in the surface layer (0–20 cm) is substantial at 44.9%, while the deeper layers (20–100 cm) show nugget effects below 25%, suggesting that the influence of both natural and anthropogenic factors on deep soil bulk density is limited and mainly affects the surface layer. Stepwise regression analysis indicates that among topographic factors, slope and elevation are the primary controls of spatial variability in soil bulk density across layers. This research demonstrates that, in arid regions, soil bulk density is influenced primarily by natural factors, with limited impact from human activities. These findings provide valuable data support and theoretical guidance for soil management, agricultural planning, and sustainable ecosystem development in arid regions.

Assessment and Application of Multi-Source Precipitation Products in Cold Regions Based on the Improved SWAT Model

In hydrological modeling, the accuracy of precipitation data and the reflection of the model’s physical mechanisms are crucial for accurately describing hydrological processes. Identifying reliable data sources and exploring reasonable hydrological evolution mechanisms for hydrology and water resources research in high-altitude mountainous regions with sparse stations and limited data constitute a significant challenge and focus in the field of hydrology. This study focuses on the Yarkant River Basin in Xinjiang, which originates from glaciers and contains a substantial amount of meltwater runoff. A dynamic glacier melt module considering the synergistic effects of multiple meteorological factors was developed and integrated into the original Soil and Water Assessment Tool (SWAT) model. Four precipitation datasets (ERA5-land, MSWEP, CMA V2.0, and CHM-PRE) were selected to train the model, including remote sensing precipitation products and station-interpolated precipitation data. The applicability of the improved SWAT model and precipitation datasets in the source region of the Yarkant River was evaluated and analyzed using statistical indicators, hydrological characteristic values, and watershed runoff simulation effectiveness. The optimal dataset was further used to analyze glacier evolution characteristics in the basin. The results revealed the following: (1) The improved model fills the gap in glacier runoff simulation with respect to the original SWAT model, with the simulation results more closely aligning with the actual runoff variation patterns in the study area, better describing the meltwater runoff process. (2) CMA V2.0 precipitation data has the best applicability in the study area. This is specifically reflected in the rationality of the spatial and temporal distribution patterns of the inverted precipitation, the accuracy observed in capturing precipitation events and actual precipitation characteristics, the goodness of fit in driving hydrological models, and the observed precision in reflecting the composition of watershed runoff, all of which are superior to those pertaining to other precipitation products. (3) The glacier melt calculated using the improved SWAT model informed by CMA V2.0 shows that during the study period, the basin formed a pattern with a positive–negative glacier balance demarcation at 36.5° N, featuring melting at higher latitudes and accumulation at lower latitudes. The results of this study are of significant importance for hydrometeorological applications and hydrological and water resources research in this region.

Temporal and spatial patterns of riparian vegetation in the Colastiné Basin (Argentina) and riparian ecological quality estimation as tools for water management

ABSTRACT Information on the riverbanks can improve our ability to monitor water quality and generate adequate management strategies. This research seeks insights into the riverbanks of eight Colastiné River Basin (Argentina) streams, which have been influenced by intensive agricultural land use for decades. We aim to (a) describe the temporal and spatial distribution patterns of riparian vegetation, (b) assess their current riparian quality through riverbank quality indices, and (c) estimate whether the riparian quality is linked to the water quality. Results of the Normalized Difference Vegetation Index (NDVI) showed an increasing trend in the vegetation cover with seasonal periodicities during the last 22 years in only 2 streams. Overall, 41% of plant species registered were exotic although native species dominated in most streams. The overall riverbank quality, based on the mean values of four riverbank quality indexes, was regular-to-bad. The overall water quality of the streams was low and significantly correlated to the Riparian Quality Index, suggesting a link between both compartments. More studies are needed to determine the main variables that establish this connection. Further effort is also needed to generate appropriate indices for this region, as no current ones are still developed.

Spatial and Temporal Variation of GPP and Its Response to Urban Environmental Changes in Beijing

The carbon sequestration capacity of vegetation is the key to the carbon cycle in terrestrial ecosystems. It is significant to analyze the spatiotemporal variation and influencing factors of vegetation carbon sequestration ability to improve territorial carbon sink and optimize its spatial pattern. However, there is a lack of understanding of the impact of environmental conditions and human activity on the vegetation’s carbon sequestration ability, especially in highly urbanized areas. For example, effective vegetation management methods can enhance vegetation Gross Primary Productivity, while emissions of air pollutants like O3, CO, NO2, and PM2.5 can suppress it. This paper mainly explores the factors influencing vegetation carbon sequestration capacity across different regions of Beijing. Based on remote sensing data and site observation data, this paper analyzed the spatiotemporal variation trend of Annual Gross Primary Production (AGPP) and the influence of environmental factors and human activity factors on GPP in Beijing from 2000 to 2020 by using the Theil−Sen’s slope estimator, Mann−Kendall trend test, and comparing Geographically Weighted Regression method (GWR) and Geographically and Temporally Weighted Regression method (GTWR). GWR is a localized multiple regression technique used to estimate variable relationships that vary spatially. GTWR extends GWR by adding temporal analysis, enabling a comprehensive examination of spatiotemporal data variations. Besides, we used land use cover data to discuss the influence of land use cover change on AGPP. The results showed that the spatial distribution pattern of GPP in Beijing was higher in the northwest and lower in the southeast, and it showed an overall upward trend from 2000 to 2020, with an average annual growth rate of 14.39 g C·m−2·a−1. From 2000 to 2020, excluding the core urban areas, the GPP of 95.8% of Beijing increased, and 10.6% of Beijing showed a trend of significant increase, concentrated in Mentougou, Changping, and Miyun. GPP decreased in 4.1% of the regions in Beijing and decreased significantly in 1.4% of the areas within the sixth ring. The areas where AGPP significantly decreased were concentrated in those where land use types were converted to Residential land (impervious land), while AGPP showed an upward trend in other areas. CO and NO2 are the main driving forces of GPP change in Beijing. O3 and land surface temperature (LST) also exert certain influences, while the impact of precipitation (PRE) is relatively minor. O3 and CO have a positive impact on AGPP as a whole, while LST and NO2 generally exhibit negative impacts. PRE has a positive impact in the central area of Beijing, while it has a negative impact in the peripheral areas. This study further discusses opinions on future urbanization and environmental management policies in Beijing, which will promote the carbon peak and carbon neutrality process of ecological space management in Beijing. Besides, this study was conducted at the urban scale rather than at ecological sites, encompassing a variety of factors that influence vegetation AGPP. Consequently, the results also offer fresh insights into the intricate nexus between human activities, pollutants, and the GPP of vegetation.

Spatiotemporal Variations and Driving Factors of Ecological Sensitivity in the West Qinling Mountains, China, Under the Optimal Scale

This study selected the five indicators of soil erosion, climate environment, geological hazards, biodiversity, and human disturbances and uses the entropy weight method to calculate the ecological sensitivity of the West Qinling Mountains from 2000 to 2020. The analysis produced a spatiotemporal distribution of ecological sensitivity over the 20-year period. An equal step size of 500 m was used to progressively increase the spatial scale from 500 m to 6 km. The optimal scale for the spatial differentiation of ecological sensitivity in the West Qinling Mountains was determined by analyzing the characteristics of changes at different scales, response mechanisms, and optimal parameters for geographical detector spatial scale identification. Based on this scale, the change in intensity and pattern and the influencing factors of ecological sensitivity were analyzed. The results show the following: (1) The 5.5 km spatial scale balances the requirements of accuracy, spatial heterogeneity, and data adequacy, making it the optimal scale for analyzing the spatiotemporal variation patterns of ecological sensitivity in the West Qinling Mountains. (2) From 2000 to 2020, the mean ecological sensitivity in the West Qinling Mountains exhibited a decreasing trend, indicating an improvement in the ecological environment. Spatially, the ecological sensitivity of the West Qinling Mountains showed a spatial distribution pattern of “low in the west and high in the east, low in the south and high in the north”. During the study period, the ecological sensitivity in the West Qinling region remained generally stable, with no high-frequency changes observed. (3) Population density is the primary driving factor of spatial differentiation of ecological sensitivity in the West Qinling Mountains, while GDP serves as a secondary factor. Overall, socioeconomic factors have the most significant impact on ecological sensitivity. (4) Over 75% of the ecological sensitivity trends exhibit patterns of perennial unchanged and fluctuating unchanged trends, with areas of fluctuating increase smaller than areas of fluctuating decrease. Regions of perennial high sensitivity are primarily concentrated in the northeastern part of the West Qinling Mountains, while areas with increased fluctuation in ecological sensitivity are mainly located in the western and southern parts of the West Qinling Mountains. Future efforts should focus on these regions.

Evaluation of the Predictive Capability of CMA Climate Prediction System Model for Summer Surface Heat Source on the Tibetan Plateau

Surface heat source (SHS) is a crucial factor affecting local weather systems. Particularly SHS on the Tibetan Plateau (TP) significantly influences East Asian atmospheric circulation and global climate. Accurate prediction of summer SHS on the TP is of urgent demand for economic development and local climate change. To evaluate the performance of SHS on the TP, the observed SHS data from the eleven sites on the TP verified against CRA40-land (CRA) is evidenced significantly better than ERA5-land (ERA5), another widely used reanalysis. The predictive capability of the CMA Climate Prediction System Model (CMA-CPS) for SHS on the TP was assessed using multiple scoring methods, including the anomaly correlation coefficient and temporal correlation coefficient, among others. Furthermore, relative variability and trend analysis were conducted. Finally, based on these assessments, the causes of the biases were preliminarily discussed. The CMA-CPS demonstrates a reasonable ability to predict the spatial distribution patterns of SHS, sensible heat (SH), and latent heat (LH) on the TP in summer. Specifically, the prediction results of SHS and LH exhibit an “east-high and west-low” distribution, while the distribution of the predicted SH is opposite. Nevertheless, the predicted values are generally lower than CRA, particularly in interannual variations and trends. Among the predictions, LH exhibits the highest temporal correlation coefficients, consistently above 0.6, followed by SHS, while SH predictions are less accurate. The spatial distribution and skill scores indicate that LH on the TP contributes more significantly to SHS than SH in summer. Furthermore, discrepancies in the predictions of surface temperature gradients, ground wind speed, and humidity on the TP may partly explain the biases in SHS and their components.

Multimodel-based quantitative source apportionment and risk assessment of soil heavy metals: A reliable method to achieve regional pollution traceability and management

To strengthen the control of pollution sources and promote soil pollution management of agricultural land, this study constructed a comprehensive source apportionment framework, which significantly improved the reliability of potential source analysis compared with the traditional single model. The spatial distribution pattern of agricultural soil heavy metals (SHMs) content in Lintong, a typical river valley city in China, was determined and the degree of contamination was evaluated. A scientific source apportionment methodological framework was constructed through correlation analysis methods together with multiple source apportionment receptor models. Finally, the Monte Carlo simulation method was used to derive the results of the human health risk assessment (HHRA). The results revealed the following: (1) Agricultural soils were moderately and mildly polluted, accounting for 28.8 % and 71.2 % of the total number of sampling points, respectively. (2) The overall correlation of heavy metals (HMs) was strong according to the coupling analysis of the SHMs, in which a strong correlation (0.8–1) was reached among Cu, Ni, Pb, Cr and Zn, indicating that these HMs were most likely homologous or composite. (3) Multimodel analysis of the SHMs sources revealed that the first and second principal components were agricultural (41.36 %) and industrial (19.69 %) sources, respectively, and the remaining principal components were road traffic, natural factors, and atmospheric deposition or surface runoff, respectively. (4) The average comprehensive noncarcinogenic health risk indices for adults and children were 4.2259E-02 and 1.4194E-01, respectively, which were within the slight risk range, indicating that the risk caused by SHMs to the human body can be almost negligible. This study adopted a mixed method to reveal the risk of SHMs pollution and its sources, which provides some reference and technical support for traceability analysis, zoning control, and health risk studies of regional pollutants and is helpful for formulating scientific management measures and targeting control policies.

Patterns of spatial dynamics and distribution of african elephants (Loxodonta africana) in the Central Kalahari Game Reserve, Botswana

The African elephant (Loxodonta africana), once thought to be absent from the Kalahari Desert in Southern Africa, has recently reestablished or expanded its range into the Central Kalahari Game Reserve (CKGR), Botswana, with documented occurrences over the past decade. This study explores the temporal and spatial dynamics of elephants in and around the CKGR, focusing on their largely understudied movement patterns. Movement and home range data was obtained from two adult female and eight adult male elephants using GPS/UHF collars. The analysis revealed distinct seasonal ranging behaviours. Collared females migrated between CKGR and the Okavango Delta periphery, while collared male showed both migratory and sedentary patterns around artificial water points and Gope mine in CKGR. Some collared male elephants migrated to the Kavango Zambezi Transfrontier Conservation Area (KAZA) during the wet season, returning to the CKGR in the dry season. This pattern confirms established migration routes and the emergence of pseudo-resident male elephants within CKGR. These findings highlight the importance of management strategies that integrate water distribution, elephant movement, and human-elephant conflicts. Ensuring ecological connectivity beyond the KAZA region is vital for the long-term survival of elephants and other key species.

Research on identification and zoning control of territorial spatial risk pattern based on deep learning: A case study of Shenzhen, China

In the era of globalization, digitalization, and diversification, currently societal cities face risks intertwined by uncertainty and complexity. Thus, it is crucial to address risks concerns to achieve modernization of spatial management. Moreover, how to scientifically identify the risk pattern of territorial space and how to map and control it in space becomes a critical and urgent issue to be addressed for achieving modernization of spatial management. Understanding the intricate relationship between land use, environmental factors, and population density is essential for identifying risk patterns that can inform effective disaster management strategies. By employing advanced analytical methods, this study aims to provide a comprehensive framework for recognizing and mitigating territorial spatial risks in an increasingly complex urban landscape. This study used a case study to conduct the unsupervised algorithm of stack autoencoder self-organizing map to analyze the distribution and spatial clustering of Shenzhen's land spatial risk pattern and reveal the driving mechanism of its risk pattern formation in detail. It was found that: (1) The overall territorial spatial risk pattern of Shenzhen presents a distribution trend of "high in the west and low in the east, high in the south and low in the north"; that is, I and II risk areas are clustered in the hilly areas in the northeast and IV and V risk areas in the coastal areas in the southwest; (2) Population density, land use intensity, seawater intrusion, geological disasters, relief amplitude, soil type, soil erosion intensity are the main driving forces for the formation of Shenzhen's territorial spatial risk pattern. In particular, seawater intrusion, population density and land use intensity, soil type were found having significantly synergistic impact on the risk pattern.

Origin of biomarkers (PAH, n-alkane, hopane, estrane) in different colors of plastic resin pellets and surface sediments from coastal area of the Makuran-Oman Sea

The unique attributes of the study area, situated near the Strait of Hormuz—an extensively utilized oil shipping corridor for Iran and neighboring Arabian nations—encompass oil extraction and exploitation, the establishment of an oil export hub, the advancement of petrochemical industries, as well as tourism and transportation activities. This research represents the first examination of the sources of plastic resin pellet release, addressing both local and non-local contributions. To conduct this study, samples of plastic resin pellet and coastal and intertidal surface sediments were collected from seven stations on the shores of the Oman Sea in Hormozgan province (Sirik, Garook, Ziarat, Karpan, Koohestak, Gohardo, and Kargan) with four replications to determine the origin and spatial distribution pattern of hydrocarbons and the diffusion source of plastic resin pellets (offshore or regional). Plastic resin pellets were separated based on color (white, yellow, brown, and black). Soxhlet was used to extract hydrocarbons, two stages of column chromatography were used to separate compounds, and gas chromatography–mass spectrometry (GC–MS) was used to identify and determine their concentration. The total n-alkanes concentration ranged from 2940 to 18,711 (μg/g) in coastal surface sediments, from 19,721–1678 (μg/g) in intertidal surface sediments, and from 11,481.50 to 55,601.41 (μg/g) in plastic resin pellets. A similar trend was found for the total PAH concentration which ranged from 135.57 to 3890.62 (ng/g) in coastal sediments, from 1820.28 to 6579.55 (ng/g) in intertidal sediments, and from 3714.19 to 66/1920451 (ng/g) in plastic resin pellets. According to the sediment pollution criteria, a high pollution level was assessed in most of the stations. In most of the surface sediments and plastic resin pellets, the presence of unresolved complex mixture (UCM), the carbon preference index (CPI) lower than 1, and the diagnostic ratios of PAH, hopane, and sterane compounds indicated petrogenic origin for hydrocarbons. The results of principal component analysis based on 16 diagnostic ratios of PAH, n-alkane, hopane, and sterane compounds showed that brown and black plastic resin pellets were placed in a different group than the coastal and intertidal sediments and white and yellow plastic resin pellets. Most likely, the diffusion source of brown and black plastic resin pellets is different and through open water.

Sustainable Development of Urban Agglomerations around Lakes in China: Achieving SDGs by Regulating Ecosystem Service Supply and Demand through New-type Urbanization

The mechanism through which New-type Urbanization (NU), as a new direction in urban development, influences the Sustainable Development Goals (SDGs) by regulating the Ecosystem Services (ES) supply and demand remains to be determined. It is particularly true in urban agglomerations around lakes, characterized by severe human-land conflicts, where socio-economic development is closely linked to water. We selected China’s urban agglomerations around lakes as the study area. We investigated the spatio-temporal heterogeneity of NU and the Ecosystem Service Supply and Demand Ratio (ESDR) from 2000 to 2018. We specifically focused on the dynamic trends of SDG 2 (Zero Hunger), SDG 13 (Climate Action), and SDG 15 (Life on Land). Furthermore, we utilized Structural Equation Modeling (SEM) to reveal the direct effects and indirect pathways through which NU influences the achievement of SDGs in the study area, emphasizing the differentiated performance of this mechanism across various urban agglomerations around Lakes. The results indicated that the ESDR has a particularly evident downward trend in urban centers along lakes, rivers, and road networks in spatial terms. The level of NU in urban agglomerations around lakes has increased by about 50% overall. It geographically exhibits three main spatial distribution patterns: “diffusion along the lake,” “homogeneous distribution,” and “diffusion along the river.” NU directly inhibits the achievement of SDGs but indirectly promotes the improvement of ESDR for food production and soil conservation, thereby indirectly facilitating the achievement of SDG 2 and SDG 15, but has an inhibitory effect on SDG 13. By regulating ESDR, NU is most effective in achieving SDGs in the urban agglomerations around Poyang Lake and Dongting Lake but has a significant inhibitory effect on the urban agglomeration around Hongze Lake. This research provides quantitative evidence for the urban planning shift, terrestrial ecosystem function restoration, and SDGs achievement in urban agglomerations around lakes. It also offers new insights from China for the sustainable urban construction of urban agglomerations around lakes worldwide.

Multi-scenario simulation and optimization of habitat quality under karst desertification management

IntroductionInvestigation of the evolutionary trend of habitat quality in karst and rocky desertification zones is crucial for enhancing ecological security and conservation.MethodsAnalysis of land use statistics from the years 2000, 2010, and 2020, changes in habitat quality (HQ) and land use (LULC) between 2000 and 2020 were analyzed using Huize County in Yunnan Province as an example. The InVEST and FLUS models were applied to simulate LULC under different scenarios in 2030 and 2040 and assess changes in spatial gradients of habitat quality at each timepoint and factors influencing them.ResultsThe findings indicated that (1) The predominant land use types are grassland and woodland, experiencing the most significant growth in urbanized areas, the main sources of which are paddy fields and high-cover grassland. (2) The habitat quality between 2000 and 2020 was average and displayed a consistent decline. The spatial distribution pattern indicates low HQ in urban areas, high HQ in the outskirts, low HQ in the south-west, and high HQ in the north-east. In all four scenarios, habitat quality predominantly decreases in urban areas and regions with a dense concentration of built-up land. (3) Habitat quality spatial distribution is primarily affected by the type of land use, with NDVI being the secondary determinant.DiscussionThe ecological environment of Huize County must be restored and safeguarded with a focus on ecological priorities and harmonious development scenarios. This study provides methodological lessons for ecorestoration and policymakers in areas of karstic rocky desertification.

Mortality from type 2 diabetes mellitus across municipalities in Mexico

BackgroundOne in six Mexican adults’ lives with type 2 diabetes mellitus (T2DM), which is the third leading cause of death in the country. Analyzing the geographic distribution of T2DM mortality helps identify regions with higher mortality rates. This study aimed to examine the spatial patterns of mortality from type 2 diabetes mellitus (T2DM) across municipalities in Mexico and to analyze the main contextual factors linked to this cause of death in 2020.MethodsWe employed a spatial Bayesian hierarchical regression model to estimate the risk and probability of death from type 2 diabetes mellitus (T2DM) across Mexico’s municipalities.ResultsThe SMR results revealed geographic and age-specific patterns. Central Mexico and the Yucatán Peninsula exhibited the highest excess mortality rates. For the population under 50 years of age, municipalities in Oaxaca had the highest T2DM mortality rates, whereas those aged 50 years old and older had the highest rates in Tlaxcala and Puebla. Socioeconomic factors such as low levels of educational attainment, lack of health services, dietary deficiency, and marginalization were positively associated with increased T2DM mortality risk. By contrast, GDP per capita showed a negative association. High-risk areas for T2DM mortality were prominent along the south of the Pacific Coast, the Bajío, Central Mexico, and southern Yucatán for those under 50, and along a central strip extending to the Yucatán Peninsula for the older population. Significant uncertainties in mortality risk were identified, with Central Mexico, Oaxaca, Chiapas, and Tabasco showing high probabilities of excess risk for those under 50 years of age and extended risk areas along the Gulf of Mexico for those 50 years old and older.ConclusionsThe assessment and identification of spatial distribution patterns associated with T2DM mortality, and its main contextual factors, are crucial for informing effective public health policies aimed at reducing the impact of this chronic disease in Mexico.

Alkalinity sources in the Dutch Wadden Sea

Abstract. Total alkalinity (TA) is an important chemical property that plays a decisive role in the oceanic buffering capacity with respect to CO2. TA is mainly generated by weathering on land as well as by various anaerobic metabolic processes in the water and sediments. The Wadden Sea, located in the southern North Sea, is hypothesized to be a source of TA for the North Sea, but quantifications are scarce. This study shows observations of TA, dissolved inorganic carbon (DIC), and nutrients in the Dutch Wadden Sea in May 2019. Surface samples were taken along several transects in order to investigate spatial distribution patterns and compare them with data from the late 1980s. A tidal cycle was sampled to further shed light on TA generation and potential TA sources. We identified the Dutch Wadden Sea as a source of TA and estimated an export of 6.6 Mmol TA per tide to the North Sea. TA was generated in the sediments, with deep pore water flow during low tide enriching the surface water. A combination of anaerobic processes and CaCO3 dissolution were potential TA sources in the sediments. We deduce that seasonality and the associated nitrate availability specifically influence TA generation by denitrification, which is low in spring and summer.

Research on the Synergistic Development of China’s Pension Industry and Pension Career

To adapt to the new demographic trends and foster high-quality and sustainable population growth, this study analyzes the synergistic development of the pension industry and pension career based on the data of 31 provinces in China from 2016 to 2022, using a distance coordination model, the latest Vague set similarity measure method, new grey relational analysis, kernel density estimation, and Markov chain. The findings indicate that (1) the development levels of China’s pension industry and pension career have shown a steady upward trend, with the gap between them gradually narrowing, though the overall development of the pension career remains higher than that of the pension industry. (2) The synergistic degree of China’s pension industry and pension career is high, with the degree of synergy fluctuating but generally increasing. (3) The synergistic development degree of the pension industry and pension career has continued to rise. The increase in the synergistic development degree shows a spatial distribution pattern of “Central > East > West”. (4) The spatial distribution of synergistic development of China’s pension industry and pension career is uneven, and in the long term, regions with higher synergistic development levels tend to positively influence less developed regions.

Resilience Assessment and Influencing Factors Analysis of Water Security System in the Yellow River Basin

The assessment and regulation of water security system resilience (WSSR) are important ways to alleviate water resource crises. On the basis of the three characteristics of resilience, namely, resistance, restoration, and adaptability, an evaluation index system of the WSSR was built for the Yellow River Basin (YRB). A projection pursuit model based on the sparrow search algorithm (SSA-PP model) was constructed to assess the WSSR at the overall and provincial scales from 2009 to 2022. The factors influencing the spatial distribution patterns of WSSR was identified through factor detector and interactive detector techniques. The results revealed that: (1) From 2009 to 2022, the YRB exhibited a rising trend in WSSR, with the western region attaining the peak level, and the eastern region recording the lowest magnitude. (2) the adaptability capacity of most provinces and regions in the YRB tended to decrease to about 1.0, whereas the resistance and restoration capacities tended to increase towards 2.0. (3) Factors relevant to the restoration and adaptability subsystems, such as the development and utilization ratio of water resources and surface water resources (B2 and B3), water resource load index (C1), water consumption per 10,000 yuan of GDP (C8), and total precipitation (A1), significantly affected the WSSR. The interaction between factors exhibited significant enhancement effects on explanatory. Therefore, targeted countermeasures and recommendations were provided to improve the WSSR in the YRB.

Impact of land-use change on coupling coordination degree of regional water–food–carbon system

IntroductionThe objective of this study is to investigate the impact of land use changes on the coupling coordination of the regional water-food-carbon system in Hebei Province. Moreover, the findings aim to offer insights for achieving comprehensive and coordinated development of regional resources.MethodsBy constructing an evaluation index system of the coupled coordinated development of the water-food-carbon system, using the coupled coordination model to study the coupled coordination of the water-food-carbon (WFC) system in Hebei Province from 2010 to 2020, and applying the Pearson correlation coefficient and ArcGIS to analyze the impacts of land-use changes on the degree of coupled coordination.ResultsThe results show that: (1) The most notable characteristics of land type changes include a decrease in cropland and an increase in construction land, primarily driven by the conversion of cropland to construction sites. The total area converted amounts to 8207.20 km2. (2) The degree of coupled coordination of the water-food-carbon system in the study area as a whole shows an upward and then downward trend, and shows a spatial distribution pattern of “high in the north-east and low in the south-west”; (3) In Hebei Province, the degree of coupling coordination within the water-food-carbon system exhibits a stable positive correlation with forest land, grassland, and water area. Additionally, the transfer of forest land and grassland are significant factors influencing the delineation of cold and hot spots within the region.DiscussionTherefore, in addressing the coordinated development of the water-food-carbon system, it is essential to consider the influence of land. Resources should be allocated judiciously based on regional advantages to promote sustainable development effectively.