To achieve the healthy and sustainable development of the primary grain-producing region, it is essential to assure a good coupling-coordination between grain production resilience (GPR) and ecosystem services (ESs). Taking the Shandong section of Yellow River irrigation district in China (SYRID) as the study region, we assessed the spatiotemporal coupling-coordination relationship and its primary driving factors between GPR and ESs with the improved spatiotemporal coupling coordination degree (ISTCCD) model and the geographically and temporally weighted regression (GTWR) model. Key findings reveal that GPR and the regulating services generally showed a weakening trend from 2000 to 2020, while the supply services improved. The coupling-coordination between GPR and habitat quality (HQ) was basically in an extremely or moderately imbalance state, with the average index from 0.276 to 0.267. Annual average temperature and vegetation coverage were the dominant factors influencing the coupling-coordination between GPR and ESs. However, the human footprint also influenced the coupling-coordination between GPR and carbon storage (CS), while the land use intensity also influenced the coupling-coordination between GPR and the others ESs. Optimization suggestions were proposed for agroecosystems in the SYRID from ecosystem services perspective, which is beneficial for optimizing the regional sustainable development strategies. This research breaks away from the previous single-faceted studies on GPR or ESs. It focuses on the coupling and coordination between GPR and ESs, integrating the ecological and socio-economic systems. This can provide data support and optimization strategies for the high-quality and sustainable development of the SYRID and the entire Yellow River Basin.

The Water-Energy-Food (WEF) Nexus, which provides a critical framework for coordinating the management of multiple interrelated fundamental resources, such as water, energy and food, is key to achieving the Sustainable Development Goals (SDGs). Urgently conduct the in-depth research on the spatiotemporal evolution driving mechanism of WEF efficiency, and scientific predictions of its dynamic response in different future development scenarios. Therefore, this study constructed a comprehensive framework that integrates the super-efficiency network SBM model, Geographically and Temporally Weighted Regression (GTWR) model, Explainable Machine Learning model and XGBoost-LSTM model, to conduct the quantitative evaluation, driving factor analysis, and multi-scenario simulation of the WEF system efficiency in the Yellow River Basin (YRB) of China. The results show that: (1) From 2000 to 2022, the efficiency of WEF system and its subsystems followed a declining-then-rising trend; (2) Driven by economic development and ecological resilience, the eastern and southern regions demonstrated higher system efficiency and better subsystem balance compared to the central and western regions; (3) The spatiotemporal heterogeneity significantly shapes the critical impact of government fiscal capacity in improving the WEF system and its energy and food subsystems, while water use control is crucial for enhancing the water subsystem efficiency; (4) Compared to single XGBoost and LSTM models, the XGBoost-LSTM integrated model improves prediction accuracy by approximately 12.11 % and 8.9 %, respectively; (5) Multi-scenario projections based on the XGBoost-LSTM model identify the WEF synergistic enhancement scenario as the optimal pathway for enhancing WEF system efficiency in the YRB. The WEF comprehensive framework proposed in this study can provide case demonstration and technical method for other regions in the world facing similarly resource management and sustainable development issues.

Demand for urban development and the exploration of sustainable development pathways cause increasing challenges in land use change management. Cultural ecosystem services play an important role in the maintenance and optimization of the urban system, and are non-substitutable. Research into the integration of land use change and the response of cultural ecosystem services can help to ensure socio-economic and human well-being in the context of government intervention. We leverage a social survey, land use maps, government statistics and environmental driving data, and construct an integrated research framework through geospatial model, system dynamics and land use simulation model to predict land use changes in Nanjing under different future development scenarios and simulate the influence of multiple land use scenarios on the supply of cultural services. The results demonstrate that under the ecological protection scenario (EOP), all cultural services were maximized, and under the coordinated development scenario (COD), the needs of the economy and cultural services are more balanced, under the economic priority scenario (ECP), biodiversity and recreation services are at risk of erosion. Tourism and development, aesthetic and historical services show a tendency to improve with economic development, but biodiversity and recreation services that rely more on the natural environment may be negatively affected. To maintain social, economic and ecological well-being in Nanjing our scenarios may need to be hybridized. For instance, administrative districts already considered to have strong economic development could apply the EOP, while others can apply the COD.

Monitoring and assessing the dynamic trajectory, spatial patterns, and sustainability of urban construction land expansion is crucial for achieving the Sustainable Development Goals (SDGs) and has become a key issue in current urban research. This study proposes an urban expansion assessment framework that leverages the ''trend-pattern-efficiency-coordination'' research path to monitor the spatiotemporal dynamics and sustainability of urban expansion in China's Lower Yellow River urban agglomeration (LYR) from 1990 to 2020 at 10-year intervals with multi-source remote sensing images and socioeconomic census data. The research findings indicated a significant acceleration in LYR's urban land growth over the past three decades, albeit with pronounced regional disparities in the magnitude and trend of urban land expansion across different prefectural cities. This study further integrated radar map and equal fan analysis to identify three dominant urban expansion patterns, explicitly showing the dominant direction and spatial shape features. Additionally, the EGRLCR and EGRPGR revealed a consistent downward trend from 1990 to 2020, with the LCRPGR ratio experiencing an initial decline followed by an increase over time. The investigation into the coupling coordination degree showed that most cities were in the high-level coupling stage accompanied by the continuously strengthening degree of coupling coordination. This paper also puts forward targeted countermeasures for cities experiencing uncoordinated urbanization to boost land use efficiency and sustainability.

With rapid economic development and urbanization, the natural ecosystems and ecosystem services (ESs) in the Lower Yellow River Region (LYRR) have undergone irreversible destruction, intensifying the conflict between ecological conservation and socioeconomic development. This study utilized multi-source spatial data from 1990 to 2020 and employed the InVEST and RUSLE models to quantify water yield (WY), carbon storage (CS), soil conservation (SC), and food production (FP). Spearman correlation and geographically weighted regression (GWR) were applied to analyze trade-offs and synergies, while random forest and partial least squares structural equation modeling were used to identify driving factors and their pathways. The results revealed significant changes in the spatial pattern of WY, whereas the other three ESs remained relatively stable. Significant spatiotemporal heterogeneity and scale effects were observed in ES interactions, leading to discrepancies between Spearman and GWR. The strongest trade-off between WY and CS, peaking at −0.42*** in 2010. Driving mechanisms showed that LUCC, Pre, DEM, and PET dominated WY; LUCC primarily drove CS; DEM strongly influenced SC; and LUCC, NDVI, and POP majorly affected FP. Over the 30-year period, the direction and intensity of drivers' impacts on ESs varied significantly. For instance, in 1990, Pre (0.734***) exerted the strongest positive effect on WY, while LUCC (−0.934***) had the most significant negative impact on CS. However, their indirect effects through intermediary pathways remained weak. These findings offer a scientific foundation for ecological management and sustainable development in rapidly urbanizing regions.

Understanding and managing the complex trade-offs among multiple ecosystem services (ESs) against the backdrop of rapid urbanization is critical for achieving sustainable ecological and socio-economic development in urbanized areas. Taking the rapidly urbanizing Lower Yellow River Region (LYRR) as a typical case area, this study investigated the spatiotemporal evolution characteristics of five ESs including water yield (WY), carbon storage (CS), soil conservation (SC), food production (FP), and habitat quality (HQ) from 1990 to 2020, utilizing multi-source spatiotemporal data and ecological process modeling. Next, correlation analysis was applied to assess their trade-offs and synergies. On this basis, a multi-objective land use spatial optimization model was constructed by integrating the non-dominated sorting genetic algorithm III (NSGA-III) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), aiming to identify optimal land use configuration scheme for balancing competing ESs under diverse policy scenarios. The results indicate that ESs exhibit diverse evolutionary trends and significant spatial heterogeneity from 1990 to 2020, with most being significantly negatively impacted by urban expansion. In addition, a strong trade-off relationship was observed between WY and CS, HQ, and SC, which intensified over time alongside urbanization. Importantly, optimizing land use spatial patterns can mitigate these trade-offs. For instance, converting 1.3 % of cropland into ecological land under the ecological conservation priority scenario increased CS by 0.26 % and improved HQ by 0.49 %, while maintaining stable FP and WY levels. The carbon sequestration priority scenario was realized by increasing woodland and cropland area, a strategy that not only enhanced HQ by 0.31 % and CS by 0.29 %, but also increased FP by 3.4 x 104 tons. Our findings advance the understanding of ESs trade-offs in rapidly urbanizing areas and provide a scientific foundation for land use optimization and ecosystem management in the Yellow River Basin.

Ecological security is of central significance for maintaining the integrity and stability of regional ecosystems. Nevertheless, current academic research systematically studying the complex driving mechanisms behind ecological security is deficient. Therefore, this study utilised ecological sources (ESs) and ecological resistance surfaces (ERSs) to calculate and obtain the Ecological Suitability Index (ESI), thereby reflecting the ecological security status. The drivers of ESI in different areas of the Yellow River Basin (YRB) from 1990 to 2020 were explored using the random forest (RF) model and GeoDetector. The results of the study show that: (1) according to the results of the RF model, LANDUSE, NDVI, and PRE are the most important driving factors of the ESI in the upper (UYR), middle (MYR), and lower (LYR) reaches of the YRB; (2) according to the results of GeoDetector factor detection, in the UYR and MYR, the ESI is primarily influenced by natural factors such as NDVI and PRE, showing particularly significant impacts in 2010 and 2020; (3) in the LYR, the ESI is mainly influenced by NDVI, but the degree of influence from socioeconomic factors has significantly strengthened. This study provides a decision-making direction for ecological protection and coordinated development in the YRB.

Urban regeneration (UR) can improve the physical, social, economic, and ecological environment of urban areas, which is the key path to achieving Sustainable Development Goals (SDGs). However, quantitative assessments of the SDGs dynamics before and after UR process are rarely studied. Taking Shenzhen, China, as a practical example, this study combined multi-source geographic data to proposed a fine-scale SDGs assessment index framework applicable to UR (URSDGi). A comprehensive index of urban regeneration SDGs (URSDGs) was then constructed to evaluate the SDGs performance for four types of UR (industrial, residential, commercial and other types) at street block scale. Results showed that Shenzhen’s 392 blocks underwent UR practice between 2012–2020. The industrial UR exhibited the highest degree of SDGs realization with an increase of 962.29 points in the URSDGs score between 2012 and 2020, followed by residential UR with an increase of 126.41 points, whereas commercial and other types of UR exhibited lower degrees of SDGs realization with an increase of 42.23 and 58.39 points, respectively. In addition, studies have found that all types of UR can obviously promote mixed land use (URSDG5) and improve land use efficiency (URSDG3), with an increase of at least 111.10 points in the URSDGi score between 2012 and 2020. Nevertheless, UR can impose additional pressures on residential housing (URSDG1) and lead to a reduction in urban green space (URSDG4), with a decrease of at least −0.66 points in the URSDGi score. The findings can enrich the research methods of SDGs performance assessment at finer scale and help to guide future UR practices.

Safeguarding ecological security is one of China's important development strategies. Identifying ecological security patterns (ESPs) is an effective way to collaboratively develop ecological and environmental security in different regions. Currently, studies on the construction of regional ESPs mainly focus on the innovation of ecosystem service functions, ignoring the differences in ecological sensitivities of different ecological environments on a large scale. In this paper, taking the Yellow River Basin (YRB) as an example, six important ecosystem service functions were selected to identify ecological sources (ESs), ecological sensitivity weights were set according to the ecological environment characteristics of different regions, and the ecological resistance surfaces (ERSs) were determined. And the ESPs of the YRB were further investigated based on the Minimum Cumulative Resistance (MCR) model and circuit theory. The research findings indicate:(1) We had identified 218 ESs on the YRB, covering an area of 387,165 km2, which was 19.36 % of the entire study area and highly concentrated in the upstream areas. There were 532 ecological corridors (ECs) identified with a total length of 39,015.95 km, with less distribution in the lower reaches of the YRB. There were 201 ecological pinch points (EPPs) mainly in forests and grasslands. (2) ERSs constructed with different sensitivities weights had a significant impact on the distribution of ECs and EPPs. There were significant variations in the ESPs of the YRB. The upstream areas were notably more secure than the middle and lower reaches, indicating an overall lower level of ecological security. (3) Different ecological sensitivity weights were adopted in different regions, which was more suitable for the construction of ESPs with regional environmental differences. This study provides a wise direction for coordinating the ecological protection and achieving high-quality development in the YRB.

Carbon storage (C-storage) is a critical indicator of ecosystem services, and it plays a vital role in maintaining ecological balance and driving sustainability. Its assessment provides essential insights for enhancing environmental protection, optimizing land use, and formulating policies that support long-term ecological and economic sustainability. Previous research on C-storage in the Yellow River Basin has mainly concentrated on the spatiotemporal fluctuations of C-storage and the investigation of natural influencing factors. However, research combining human activity factors to explore the influences on C-storage is limited. In this paper, based on the assessment of the spatiotemporal evolution of C-storage in the region along the Middle and Lower Yellow River (MLYR), the influences of anthropogenic and natural factors on C-storage were explored from the perspective of sustainable development. The findings reflected the relationship between socio-economic activities and the ecological environment from a sustainable development perspective, providing important scientific evidence for the formulation of sustainability policies in the region. We noticed the proportion of arable land was the highest, reaching 40%. The increase of construction land because of the fast urbanization mainly came from arable land and grassland. During the past 15 years, the cumulative loss of C-storage was 71.17 × 106 t. The high-value of C-storage was primarily situated in hilly areas, and the area of C-storage hotspots was shrinking. The aggregation effect of low-value C-storage was strengthening, while that of high-value C-storage was weakening. The dominant factors (q > 0.5) influencing the spatiotemporal variation of C-storage in the region along the Middle Yellow River (MYR) were temperature and precipitation, while the primary factor in the region along the Lower Yellow River (LYR) was temperature. Overall, meteorological factors were the main determinants across the entire study area. Additionally, compared to the MYR, anthropogenic factors had a smaller impact on the spatiotemporal evolution of C-storage in the LYR, but their influence has been increasing over time.

Integrating ecosystem services (ESs) into the land spatial planning can provide innovative insights for coordinating the spatial conflict between ecological protection and economic development so as to promoting regional sustainable development. However, current studies mostly focus on spatial identification and optimization of ecological protection areas to enable the maintenance of specific ESs, while ignoring human development needs and their impact on ecological protection. For this reason, based on the systematic conservation planning theory, this study proposed a cost-effective multi-zoning method with multiple management zones subject to corresponding management requirements of conservation or development to achieve the sustainable maintenance of multiple ESs that are compatible or incompatible. An empirical study of the Yangtze River Economic Belt (YREB) demonstrates how this systematic multi-zoning approach may be utilized to combine five ESs and three conservation costs to prioritize the spatial distribution of management zones under different management strategies. Our findings revealed significant differences in the spatial scale and priority of various management zones determined by the spatial characteristics of the ESs and the conservation costs associated with different management strategies or scenarios. Among all scenarios, scenario 4 allows for the simultaneous achievement of protection goals for all selected ESs with minimal spaces of management zones. Further conclude that the more flexible multi-zone configuration strategy can increase the opportunities to enhance the co‐benefits of compatible ESs by allocating its conservation targets to the same function zone, and reduces the trade-offs between incompatible ESs by avoiding the allocation of conservation targets in the same function zone. This method and relevant results can provide decision-making support for the land-use sustainable management and holistic land spatial planning of the YREB.

Against the background of ecological civilization construction, optimizing the control of territorial spatial zoning has become an important issue in maintaining regional ecological security. Clarifying different ecological processes and mechanisms within and among different ecological functional zones is of great practical significance for formulating refined spatial ecological management strategies. So far, research studies have focused on delineating ecological functional zones and analyzing linear processes and mechanisms within them, with little discussion on the differences in internal mechanisms and nonlinear characteristics of different ecological functional zones. Thus, it is necessary to elucidate key differences in the internal mechanisms and nonlinear threshold effects among different ecological functional zones to provide a scientific basis for establishing a territorial spatial zoning management system. In this study, the Integrated Valuation of Ecosystem Services and Trade-Offs model was used to evaluate ecosystem services in the Pearl River Delta region. Toward this, a self-organizing map was used to identify ecosystem service bundles, and geographically weighted regression and restrictive cubic spline analysis were used to clarify the key differences in trade-off/synergy networks and nonlinear thresholds among different ecosystem service bundles. Based on the results, suggestions for refined zoning and control of ecological spaces in the Pearl River Delta region are proposed. The results showed that: (1) In the Pearl River Delta, five different types of ecosystem service bundles are distributed in a circular pattern in space from the central to the surrounding areas: the urban-ecological, ecological-scarcity, agricultural-ecological, ecological-cooling, and ecological-conservation types. The ecological-conservation type accounted for 45.38% (the largest proportion), ecological-cooling for 32.80%, and ecological-scarcity for 10.73% of ecosystem service bundles; whereas neither the agricultural-ecological nor urban-ecological types accounted for more than 10%. (2) In the trade-off/synergy network of different ecosystem service bundles, the synergistic relationship between carbon storage and urban cooling remained stable, whereas the relationships between other ecosystem services showed significant differences. Among the five bundles, the trade-off/synergy interaction of the urban-ecological type was the strongest, followed by that of the agricultural-ecological and ecological-conservation types, whereas that of the ecological-cooling and ecological-scarcity types were relatively weak. (3) There were significant differences in the nonlinear threshold effects between the Multiple Ecosystem Services Landscape Index (MESLI) and six identified driving factors in the different ecosystem service bundles. In the ecological conservation and ecological scarcity types, the MESLI exhibited nonlinear relationships with all six factors and clear critical thresholds. The MESLIs of the agricultural ecological and ecological cooling types exhibited nonlinear relationships with elevation, night light, gross domestic product density, and population density, whereas that of the urban ecological type only exhibited nonlinear relationships with elevation and population density. (4) We suggest that decision makers use nonlinear thresholds as references to demarcate key control areas for each ecosystem service bundle, clarify their dominant mechanisms based on trade-off/synergy networks, and develop different control indicators in a targeted manner. In conclusion. this study identified key differences in trade-off/synergy networks and nonlinear threshold effects among different ecosystem service bundles and explored different ecological zoning and control strategies for the Pearl River Delta region, providing a theoretical basis and indicator references for refined management of territorial spaces in urban agglomeration areas.

As the forefront of implementing China's "Yellow River Major National Strategy," the lower Yellow River area has caused irreversible "constructive destruction" to the regional natural ecosystem and ecological functions while accelerating the process of urbanization and has become an area of sharp contradiction between ecological protection and high-quality development of the river basin. Therefore, based on ArcGIS and MATLAB software, this study used the InVEST and RUSLE models to quantitatively assess water yield, habitat quality, and soil conservation services of the lower Yellow River Region from 1990 to 2020 and analyzed the spatial and temporal characteristics and their interaction relationships of various ecosystem services. The results showed that： ① In the period from 1990 to 2020, the land urbanization process accelerated significantly, with the expansion of construction land increasing by 39.89%, whereas the area of other major land types had declined to varying degrees. ② From 1990 to 2020, the distribution patterns on the county scale and grid-scale in the lower Yellow River Region were relatively consistent. The water yield and soil conservation experienced a changing trend of first decreasing and then increasing, and the spatial distribution pattern of water yield gradually shifted to more in the east and less in the west. The spatial distribution patterns of soil conservation and habitat quality remained unchanged throughout the period, with the high values distributed in the hilly or mountainous regions of the higher terrain and the low values mainly in the plains of the gentle terrain. ③ At both the grid scale and county scale, the interaction relationships between various ecosystem services had been dominated by synergy and showed significant spatial heterogeneity. Especially at the county level, strong trade-offs were occurring in a few counties. For example, the relationship between water yields and habitat quality was a significant and strong trade-off between Weishan County and Huaiyin District. The study quantified the spatial and temporal evolution characteristics of ecosystem services in the lower Yellow River Region and clarified the trade-off synergistic relationships between ecosystem services, which can provide a scientific basis for ecological protection and watershed management under the rapid urbanization process.

Land systems and climate, which are the key elements of agricultural production and key drivers of crop yields, affect the quality of arable land. However, a quantitative model to reveal the mechanism of how potential grain yields are affected by macro-scale arable land evolution and climate change has not yet been developed. In this study, we constructed a Grey Prediction Model-Future Land Use Simulation (GM-FLUS), which combined land system evolution with climate change data, to simulate changes in China’s land system over the next 40 years. We improved the Global Agro-Ecological Zone (GAEZ) model, estimated China’s potential rice yields and their spatial distribution in the next 40 years under four scenarios (shared socioeconomic pathway SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) of the Sixth International Coupling Model Intercomparison Project, analysed the spatiotemporal variations in the potential rice yields and their drivers, and provided appropriate suggestions for increasing rice yields. The simulation results indicated an increase in China’s potential rice yields during 2020–2060 under the SSP1-2.6 and SSP3-7.0 scenarios and a decrease under the SSP2-4.5 and SSP5-8.5 scenarios. Moreover, China’s development strategy of “achieving carbon peaking by 2030 and carbon neutrality by 2060” was similar to the SSP1-2.6 scenario, under which rice yields were relatively stable. Furthermore, under China’s arable land protection policy, China’s paddy field area will change slightly during 2020–2060, and potential rice yields will be influenced by climate. Under the four climate change scenarios, air temperature increased and was negatively correlated with potential rice yields in main rice-producing regions. Additionally, potential rice yields were positively correlated with precipitation, which increased stably under the SSP1-2.6 and SSP3-7.0 scenarios and decreased under the SSP2-4.5 and SSP5-8.5 scenarios. These results suggest that the development of heat-resistant rice varieties and the implementation of measures that will mitigate the impacts of future temperature increases on rice yields are important for the conservation of paddy fields. Additionally, improving irrigation and drainage facilities is necessary to irrigate drought-prone paddy fields and drain flooded water.

The accuracy of grain yield estimation is critical for national food security. Because of the comprehensive influence of spatial differentiation conditions, such as temperature, precipitation, soil, rice variety, and irrigation, yield estimation requires integrated modeling that is based on dynamic conditions. These dynamic conditions include geographical background, biological factors, and human impact. Most existing studies focus on the observation and analysis of external factors; only a few reports on yield simulations are coupled with nature, management, and crop growth mechanism. Our study incorporates the crop growth mechanism of rice, along with data of rice varieties, soil, meteorology, and field management, to determine the rice yield in Jiangsu province, China. In addition, we have used a decision support system for the agrotechnology transfer model, along with Coupled Model Intercomparison Project data and geographic information system technology. Our results showed that: (1) A calibrated variety genetic coefficient could simulate rice biomass value (flowering stage, maturity stage, and yield) reasonably. The values of NRMSE (Normalized Root Mean Square Error) between the simulated and measured values after parameter calibration are all less than 10%, the values of d(index of agreement) are all close to 1, the simulated value of yield is in good agreement with the measured value. (2) A linear correlation between the meteorological elements and yield was observed. The linear correlation had regional differences. Notably, an increase in precipitation was conducive to the increase in yield. Except at the Huaiyin site, the other sites showed that the temperature rise could potentially lead to reduced production. We found that an increase in solar radiation was unfavorable to the production of rice in the northern and western sites in the Jiangsu province, whereas it was conducive in the southern and eastern sites. (3) Our study predicted the rice yield from typical sites in the Jiangsu province from 2019 to 2060 in the wake of climate change while excluding the extreme effects of diseases, pests, typhoons, and floods. The order of average yield per unit area is as follows: Xinghua site (8212.76 kg/ha) > Huaiyin site (7912.70 kg/ha) > Gaoyou site (7440.98 kg/ha) > Gaochun site (7512.29 kg/ha) > Ganyu site (7460.88 kg/ha) > Yixing site (7167.00 kg/ha). Notably, the average yields from the Xinghua and Huaiyin sites were higher than that from the Jiangsu province (7617.77 kg/ha). The fluctuation of the yield per unit area at each site was generally consistent with the fluctuation in the overall yield, showing a downward trend and tends to be stable. The dispersion of yield per unit area indicates that Gaochun had the most stable yield per unit area followed by Xinghua, Ganyu, Yixing, Huaiyin, and Gaoyou. The yield per unit area of the Huaiyin and Gaoyou sites was unstable and portrayed the biggest fluctuations. Future studies need to focus on how to deal with spatial variation and carry out adaptive verification to make the simulation results applicable to more dimensions.

以常州市为例,探索了基于生态足迹模型的人口与经济承载规模预测.结果表明,常州市人均生态足迹从2009年(2.9707 hm2)到2014年(3.9941 hm2)呈增长趋势,年均增长率为6.10％.生态足迹以农地、化石能源用地和水域为主,林地最小;常州市人均生态承载力从2009年(0.3040 hm2)到2014年(0.2908 hm2)基本呈下降趋势,年均变化率为-0.73％.农地(55.32％以上)和建设用地(37.18％以上)为主要生态承载力供给,二者占总生态承载力的比重从2009年的94.33％增长到2014年的94.64％,水域和化石能源用地供给不足,可开发利用的林地面积不大;2009—2014年人均生态赤字增长趋势明显,生态压力的增长趋势与人均生态赤字基本保持一致,到2014年人均生态赤字为3.7382 hm2,生态压力指数为12.8551.主要生态赤字是农地和化石能源用地导致,建设用地是主要生态盈余来源.总体来看,常州市的土地需求超过生态承载力范围,需要进一步调整土地利用结构,优化国土空间格局.

Corresponding Author: Penghui Jiang Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing, Jiangsu, China Email: jiangph1986@nju.edu.cn Abstract: Unexpected phenomena-natural disasters, accidents and wars-can disrupt regional traffic systems because of the incapacities of road networks to sustain inflicted impacts. Therefore, the assessment of road-network vulnerability becomes integral to traffic-safety-maintenance and accidentprevention procedures. This study demonstrates the development of a comprehensive network system based on suggested improvements in node extraction, road construction and network attribution. An indicator system for assessing road-network vulnerability was established to be compatible with the South Asian environment and its geographical characteristics by integrating multisource data-topography, geology and meteorological and geopolitical environments. Employing the GIS-based spatial-analysis technique, a vulnerability-assessment model for South Asian road networks was constructed and spatial distributions of vulnerability characteristics were examined under extreme natural and human-influenced environments. The results demonstrate that the road-network-vulnerability distribution in India follows a decreasing trend outwards from the central part of the country. The highest road-network-vulnerability levels of 7 and 8 were observed in the central and northern parts of the Deccan plateau as well as the western coastal and northern mountainous regions. The northernmost part of Pakistan is characterized by road-vulnerability levels in the range of 9-10. Owing to the heavy influence of India-Pakistan conflicts and terror attacks, road networks in proximity to the India-Pakistan border are assigned the highest vulnerability level of 10. The results of this study demonstrate that changes in and the impact of, the geopolitical environment are primary factors influencing road-network vulnerability in South Asia.