Chinese Geographical Science最新文献

Due to long-term human activity interference, the Hainan Tropical Rainforest National Park (HTRNP) of China has experienced ecological problems such as habitat fragmentation and biodiversity loss, and with the expanding scope and intensity of human activity impact, the regional ecological security is facing serious challenges. A scientific assessment of the interrelationship between human activity intensity and habitat quality in the HTRNP is a prerequisite for achieving effective management of ecological disturbances caused by human activities and can also provide scientific strategies for the sustainable development of the region. Based on the land use change data in 2000, 2010, and 2020, the spatial and temporal variations and the relationship between habitat quality (HQ) and human activity intensity (HAI) in the HTRNP were explored using the integrated valuation of ecosystem services and trade-offs (InVEST) model. System dynamics and land use simulation models were also combined to conduct multi-scenario simulations of their relationships. The results showed that during 2000–2020, the habitat quality of the HTRNP improved, the intensity of human activities decreased each year, and there was a negative correlation between the two. Second, the system dynamic model could be well coupled with the land use simulation model by combining socio-economic and natural factors. The simulation scenarios of the coupling model showed that the harmonious development (HD) scenario is effective in curbing the increasing trend of human activity intensity and decreasing trend of habitat quality, with a weaker trade-off between the two compared with the baseline development (BD) and investment priority oriented (IPO) scenarios. To maintain the authenticity and integrity of the HTRNP, effective measures such as ecological corridor construction, ecological restoration, and the implementation of ecological compensation policies need to be strengthened.

Abstract

Transportation accessibility has been treated as an important means of reducing the urban-rural income disparity. However, only a few studies have examined the effects of different types of transportation accessibility on urban-rural income disparity and their spatial heterogeneity. Based on data from 285 prefecture-level (and above) Chinese cities in 2000, 2005, 2010, 2015, and 2020, this study uses spatial econometric models to examine how highway accessibility and railway accessibility influence the urban-rural income disparity and to identify their spatial heterogeneity. The result reveals that highway accessibility and railway accessibility have ‘coreperiphery’ ring-like circle structures. The urban-rural income disparity exhibits strong spatial clustering effects. Both highway accessibility and railway accessibility are negatively associated with urban-rural income disparity, and the former having a greater effect size. Moreover, there is a substitution effect between highway accessibility and railway accessibility in the whole sample. Furthermore, these associations differ in geographic regions. In the central region, highway accessibility is more important in reducing the urban-rural income disparity, but its effect is weakened with the increase of railway accessibility. In the western region, railway accessibility has a larger effect on narrowing the urban-rural income disparity, and this effect is strengthened by the increase of highway accessibility. We conclude that improving transportation accessibility is conducive to reducing the urban-rural income disparity but its effect is spatial heterogenetic. Highways and railways should be developed in a coordinated manner to promote an integrated transport network system.

Terrestrial carbon storage (CS) plays a crucial role in achieving carbon balance and mitigating global climate change. This study employs the Shared Socioeconomic Pathways and Representative Concentration Pathways (SSPs-RCPs) published by the Intergovernmental Panel on Climate Change (IPCC) and incorporates the Policy Control Scenario (PCS) regulated by China’s land management policies. The Future Land Use Simulation (FLUS) model is employed to generate a 1 km resolution land use/cover change (LUCC) dataset for China in 2030 and 2060. Based on the carbon density dataset of China’s terrestrial ecosystems, the study analyses CS changes and their relationship with land use changes spanning from 1990 to 2060. The findings indicate that the quantitative changes in land use in China from 1990 to 2020 are characterised by a reduction in the area proportion of cropland and grassland, along with an increase in the impervious surface and forest area. This changing trend is projected to continue under the PCS from 2020 to 2060. Under the SSPs-RCPs scenario, the proportion of cropland and impervious surface predominantly increases, while the proportions of forest and grassland continuously decrease. Carbon loss in China’s carbon storage from 1990 to 2020 amounted to 0.53 × 10¹² kg, primarily due to the reduced area of cropland and grassland. In the SSPs-RCPs scenario, more significant carbon loss occurs, reaching a peak of 8.07 × 10¹² kg in the SSP4-RCP3.4 scenario. Carbon loss is mainly concentrated in the southeastern coastal area and the Beijing-Tianjin-Hebei (BTH) region of China, with urbanisation and deforestation identified as the primary drivers. In the future, it is advisable to enhance the protection of forests and grassland while stabilising cropland areas and improving the intensity of urban land. These research findings offer valuable data support for China’s land management policy, land space optimisation, and the achievement of dual-carbon targets.

High-quality development is the primary task of comprehensively building a socialist, modern country, as well as the primary task of building urban agglomerations in China. Based on the five development concepts, this paper used the entropy method to measure the High Quality Development Index (HQDI) of the five major urban agglomerations. The results showed that the HQDI of the five major urban agglomerations shows a fluctuating upward trend. First, using the Dagum Gini coefficient to explore the sources of HQDI development differences in urban agglomerations, we found that the main source of HQDI differences in urban agglomerations was interregional differences, while intra-regional differences were not important. Second, kernel density estimation was used to test the dynamic evolution trend of HQDI within urban agglomerations. There was a polarisation phenomenon in the HQDI of urban agglomerations, such as the Pearl River Delta urban agglomeration and the Chengdu-Chongqing urban agglomeration. But overall, the degree of imbalance had decreased. Third, using geographic detectors to examine the driving factors of HQDI in urban agglomerations, we found that the main driving forces for improving HQDI in urban agglomerations were economic growth, artificial intelligence technology and fiscal decentralisation. All the interaction factors had greater explanatory power for the spatial differentiation of HQDI, which can be divided into two types: two-factor improvement and non-linear improvement. This study is conducive to improving and enriching the theoretical system for evaluating the high quality development of urban agglomerations, and provides policy references for promoting the high quality development of urban agglomerations.

Within the context of the Belt and Road Initiative (BRI) and the China-Myanmar Economic Corridor (CMEC), the Dulong-Irrawaddy (Ayeyarwady) River, an international river among China, India and Myanmar, plays a significant role as both a valuable hydro-power resource and an essential ecological passageway. However, the water resources and security exhibit a high degree of vulnerability to climate change impacts. This research evaluates climate impacts on the hydrology of the Dulong-Irrawaddy River Basin (DIRB) by using a physical-based hydrologic model. We crafted future climate scenarios using the three latest global climate models (GCMs) from Coupled Model Intercomparison Project 6 (CMIP6) under two shared socioeconomic pathways (SSP2-4.5 and SSP5-8.5) for the near (2025–2049), mid (2050–2074), and far future (2075–2099). The regional model using MIKE SHE based on historical hydrologic processes was developed to further project future streamflow, demonstrating reliable performance in streamflow simulations with a validation Nash-Sutcliffe Efficiency (NSE) of 0.72. Results showed that climate change projections showed increases in the annual precipitation and potential evapotranspiration (PET), with precipitation increasing by 11.3% and 26.1%, and PET increasing by 3.2% and 4.9%, respectively, by the end of the century under SSP2-4.5 and SSP5-8.5. These changes are projected to result in increased annual streamflow at all stations, notably at the basin’s outlet (Pyay station) compared to the baseline period (with an increase of 16.1% and 37.0% at the end of the 21st century under SSP2-4.5 and SSP5-8.5, respectively). Seasonal analysis for Pyay station forecasts an increase in dry-season streamflow by 31.3%–48.9% and 22.5%–76.3% under SSP2-4.5 and SSP5-8.5, respectively, and an increase in wet-season streamflow by 5.8%–12.6% and 2.8%–33.3%, respectively. Moreover, the magnitude and frequency of flood events are predicted to escalate, potentially impacting hydropower production and food security significantly. This research outlines the hydrological response to future climate change during the 21st century and offers a scientific basis for the water resource management strategies by decision-makers.

Clarifying China’s position in the global system is an important logical basis for developing national diplomacy. Although much research has been done on China’s development status, most studies have been based on country comparisons or institutional environment. In today’s networked era in which the global economy, trade, personnel, and information are closely connected, studies on China’s global position and its status changes and influencing factors in multiple contact networks are still insufficient. In this study, from the perspective of diverse global contact networks, we constructed economic, cultural, and political influence indices to explore the changes and influencing factors on China’s status in the global system from 2005 to 2018. The results show that during the study period, China’s global influence in the fields of economic ties, cultural exchanges, and political contacts increased significantly, but its influence in the fields of cultural exchanges and political contacts lagged far economic ties. The pattern of China’s economic influence on various economies around the world has shown a transformation from an ‘upright pyramid’ to an ‘inverted pyramid’ structure. The proportion of these economies in low-influence zones has decreased from more than 60% in 2005 to less than 20% in 2018. China’s cultural and political influence on various economies around the world has increased significantly; however, for the former, the percentage of high-influence areas is still less than 20%, whereas for the latter the percentage of these economies in medium- and high-influence areas is still less than 50%. Analyses such as a scatter plot matrix show that geographical proximity, economic globalization, close cooperation with developing countries, and a proactive and peaceful foreign policy are important factors in improving China’s status in the diverse global network system.

Precise and timely prediction of crop yields is crucial for food security and the development of agricultural policies. However, crop yield is influenced by multiple factors within complex growth environments. Previous research has paid relatively little attention to the interference of environmental factors and drought on the growth of winter wheat. Therefore, there is an urgent need for more effective methods to explore the inherent relationship between these factors and crop yield, making precise yield prediction increasingly important. This study was based on four type of indicators including meteorological, crop growth status, environmental, and drought index, from October 2003 to June 2019 in Henan Province as the basic data for predicting winter wheat yield. Using the sparrow search algorithm combined with random forest (SSA-RF) under different input indicators, accuracy of winter wheat yield estimation was calculated. The estimation accuracy of SSA-RF was compared with partial least squares regression (PLSR), extreme gradient boosting (XG-Boost), and random forest (RF) models. Finally, the determined optimal yield estimation method was used to predict winter wheat yield in three typical years. Following are the findings: 1) the SSA-RF demonstrates superior performance in estimating winter wheat yield compared to other algorithms. The best yield estimation method is achieved by four types indicators’ composition with SSA-RF) (R² = 0.805, RRMSE = 9.9%. 2) Crops growth status and environmental indicators play significant roles in wheat yield estimation, accounting for 46% and 22% of the yield importance among all indicators, respectively. 3) Selecting indicators from October to April of the following year yielded the highest accuracy in winter wheat yield estimation, with an R² of 0.826 and an RAISE of 9.0%. Yield estimates can be completed two months before the winter wheat harvest in June. 4) The predicted performance will be slightly affected by severe drought. Compared with severe drought year (2011) (R² = 0.680) and normal year (2017) (R² = 0.790), the SSA-RF model has higher prediction accuracy for wet year (2018) (R² = 0.820). This study could provide an innovative approach for remote sensing estimation of winter wheat yield, yield.

Abstract

The effect of urban shrinkage has gradually become a new topic. Theoretically, urban shrinkage may exert great influence on land use efficiency (LUE) through various urban subsystems, but there is currently limited research examining these pathways. Using the Super-SBM-Undesirable model and the Structural Equation Model (SEM), this study calculates the LUE of shrinking cities in Northeast China and simulates the process of urban shrinkage affecting LUE. To quantify the process of urban shrinkage affecting LUE, three mediation variables, namely the economy, public services, and innovation, are used as latent variables to apply SEM. The results show that urban shrinkage will affect LUE through a direct path and indirect paths. In the direct path, urban shrinkage leads to an improvement in LUE. In the indirect paths, the economy and innovation will transmit the negative effect of urban shrinkage on LUE, while public services will reverse this effect. An important contribution of this study is that it quantifies the paths of urban shrinkage affecting LUE, thereby expanding the understanding of urban shrinkage effect and laying a foundation for the sustainable development of shrinking cities.

Abstract

The literature on urban vitality tends to focus on the built environment. This paper argues that some important processes in shaping vitality may be overlooked without examining the intensity and diversity of economic and human activities. Using newly developed spatial big data and adopting the methods of multi-indicator measurement and spatial analysis methods, we analyzed the pattern of urban vitality in Chongqing, a provincial city in western China and, on this basis, evaluated the creation and maintenance of urban vitality from the economic and human activities perspective. Our findings indicate that the impacts of economic and human activities are positive and significant. Among the three intensity and diversity indicators, economic intensity and population density show an effect on urban vitality stronger than that of economic diversity. However, economic diversity has the strongest superposition or interactive effect, and is thus an important foundation dynamic. The positive effect of population density on urban vitality is largely a result of Chongqing’s jobs-housing balance. The case of Chongqing highlights the importance of topographic features, historical inheritance, large-scale migration, and cultural activities in shaping the distinctive vitality pattern of a city. This study contends that the creation and maintenance of urban vitality can not be fully explained without incorporating the impacts of economic and human activities. It contributes to a comprehensive measurement of urban vitality and enriches its connotations.

Virtual water trade (VWT) provides a new perspective for alleviating water crisis and has thus attracted widespread attention. However, the heterogeneity of virtual water trade inside and outside the river basin and its influencing factors remains further study. In this study, for better investigating the pattern and heterogeneity of virtual water trade inside and outside provincial regions along the Yellow River Basin in 2015 using the input-output model (MRIO), we proposed two new concepts, i.e., virtual water surplus and virtual water deficit, and then used the Logarithmic Mean Divisia Index (LMDI) model to identify the inherent mechanism of the imbalance of virtual water trade between provincial regions along the Yellow River Basin and the other four regions in China. The results show that: 1) in provincial regions along the Yellow River Basin, the less developed the economy was, the larger the contribution of the agricultural sector in virtual water trade, while the smaller the contribution of the industrial sector. 2) Due to the large output of agricultural products, the upstream and midstream provincial regions of the Yellow River Basin had a virtual water surplus, with a net outflow of virtual water of 2.7 × 10⁸ m³ and 0.9 × 10⁸ m³, respectively. 3) provincial regions along the Yellow River Basin were in a virtual water deficit with the rest of China, and the decisive factor was the active degree of trade with the outside. This study would be beneficial to illuminate the trade-related water use issues in provincial regions along the Yellow River Basin, which has far-reaching practical significance for alleviating water scarcity.