Chinese Geographical Science最新文献

It is of importance to enhance the urban areas’ capacity for population aggregation in underdeveloped regions, aiming to rectify the imbalanced and insufficient pattern of economic development in China. Taking the Taiyuan Metropolitan Area (TMA) in central China as a case study, this paper examines the evolutionary process and characteristics of population agglomeration from 2000 to 2020, and identifies factors associated with agglomeration and their spatial effects. The findings indicated that: 1) against the background of sustained population shrinkage in the provincial area, the TMA showed a demographic trend of steady increase, albeit with a decelerated growth rate. In the metropolitan area, urban population size continued to grow rapidly, whereas the rural areas endured sustained losses. Disparities in city size continued to widen, and the polarization of concentrated population in the core cities kept increasing. 2) Agglomerations in both secondary and service industries had significant positive effects on local population agglomeration, with the former effect being stronger. Regional economic development, government fiscal expenditure, and financial advancement all contributed to facilitating local population clustering. From a spatial spillover perspective, service agglomeration and financial development promoted population agglomeration in surrounding areas. Conversely, fiscal expenditure inhibited such agglomeration. As for industrial agglomeration and regional economic development, their spatial spillover effects were non-significant. The results obtained reveal several policy implications aimed at enhancing the population agglomeration capacity of the metropolitan area in underdeveloped regions during the new era.

Changes in vegetation status generally also represents changes in the ecological health of islands and reefs (IRs). However, studies are limited of drivers and trends of vegetation change of Nansha Islands, China and how they relate to climate change and human activities. To resolve this limitation, we studied changes to the Normalized Difference Vegetation Index (NDVI) vegetation-greenness index for 22 IRs of Nansha Islands during normal and extreme conditions. Trends of vegetation greenness were analyzed using Sen’ s slope and Mann-Kendall test at two spatial scales (pixel and island), and driving factor analyses were performed by time-lagged partial correlation analyses. These were related to impacts from human activities and climatic factors under normal (temperature, precipitation, radiation, and Normalized Difference Built-up Index (NDBI)) and extreme conditions (wind speed and latitude of IRs) from 2016 to 2022. Results showed: 1) among the 22 IRs, NDVI increased/decreased significantly in 15/4 IRs, respectively. Huayang Reef had the highest NDVI change-rate (0.48%/mon), and Zhongye Island had the lowest (−0.29%/mon). Local spatial patterns were in one of two forms: dotted-form, and degradation in banded-form. 2) Under normal conditions, human activities (characterized by NDBI) had higher impacts on vegetation-greenness than other factors. 3) Under extreme conditions, wind speed (R² = 0.2337, P < 0.05) and latitude (R² = 0.2769, P < 0.05) provided limited explanation for changes from typhoon events. Our results provide scientific support for the sustainable development of Nansha Islands and the United Nations ‘Ocean Decade’ initiative.

The identification of dominant driving factors for different ecosystem services (ESs) is crucial for ecological conservation and sustainable development. However, the spatial heterogeneity of the dominant driving factors affecting various ESs has not been adequately elucidated, particularly in ecologically fragile regions. This study employed the integrated valuation of ESs and trade-offs (InVEST) model to evaluate four ESs, namely, water yield (WY), soil conservation (SC), habitat quality (HQ), and carbon storage (CS), and then to identify the dominant driving factors of spatiotemporal differentiation of ES and further to characterize the spatial heterogeneity characteristics of the dominant driving factors in the eco-fragile areas of the upper Yellow River, China from 2000 to 2020. The results demonstrated that WY exhibited northeast-high and northwest-low patterns in the upper Yellow River region, while high values of SC and CS were distributed in central forested areas and a high value of HQ was distributed in vast grassland areas. The CS, WY, and SC exhibited decreasing trends over time. The most critical factors affecting WY, SC, HQ, and CS were the actual evapotranspiration, precipitation, slope, and normalized difference vegetation index, respectively. In addition, the effects of different factors on various ESs exhibited spatial heterogeneity. These results could provide spatial decision support for eco-protection and rehabilitation in ecologically fragile areas.

Increased human activities in China’s coastal zone have resulted in the depletion of ecological land resources. Thus, conducting current and future multi-scenario simulation research on land use and land cover change (LUCC) is crucial for guiding the healthy and sustainable development of coastal zones. System dynamic (SD)-future land use simulation (FLUS) model, a coupled simulation model, was developed to analyze land use dynamics in China’s coastal zone. This model encompasses five scenarios, namely, SSP1-RCP2.6 (A), SSP2-RCP4.5 (B), SSP3-RCP4.5 (C), SSP4-RCP4.5 (D), and SSP5-RCP8.5 (E). The SD model simulates land use demand on an annual basis up to the year 2100. Subsequently, the FLUS model determines the spatial distribution of land use for the near term (2035), medium term (2050), and long term (2100). Results reveal a slowing trend in land use changes in China’s coastal zone from 2000–2020. Among these changes, the expansion rate of construction land was the highest and exhibited an annual decrease. By 2100, land use predictions exhibit high accuracy, and notable differences are observed in trends across scenarios. In summary, the expansion of production, living, and ecological spaces toward the sea remains prominent. Scenario A emphasizes reduced land resource dependence, benefiting ecological land protection. Scenario B witnesses an intensified expansion of artificial wetlands. Scenario C sees substantial land needs for living and production, while Scenario D shows coastal forest and grassland shrinkage. Lastly, in Scenario E, the conflict between humans and land intensifies. This study presents pertinent recommendations for the future development, utilization, and management of coastal areas in China. The research contributes valuable scientific support for informed, long-term strategic decision making within coastal regions.

Coastal zones are dynamic, rich environments, now densely populated, and increasingly challenged by human and climate-change pressures. Effective long-term integrated coastal zone planning is needed to ensure sustainable environmental protection and economic development. In this study, we reviewed the history of coastal zone planning since its birth in the 1950s based on the literature retrieved from the Web of Science (Core Collection) from 2000–2023, then summarized the tools and spatial allocation methods commonly used in the planning process, and finally proposed potential solutions to the challenges faced. The results show that after decades of development, coastal zone planning has changed from a decentralized activity to a targeted and integrated one, with an increasing emphasis on the ecosystem approach and the use of multiple planning tools. Spatial analysis techniques and environmental modelling software have become increasingly popular. Linear programming and overlay analysis are common approaches when performing spatial optimization, but land-sea interactions and planning in the marine parts still lack in-depth analysis and practical experience. We are also aware that the challenges posed by the integration of administrative hierarchies, scoping and conservation objectives, stakeholder participation, consideration of social dimensions, and climate change are pervasive throughout the planning process. There is an urgent need to develop more flexible and accurate spatial modelling tools, as well as more efficient participatory methods, and to focus on the holistic nature of the land-sea system to create more resilient and sustainable coastal zones.

Ecosystem services (ESs) refer to the continuous provisioning of ecosystem goods and services that benefit human beings. Over recent decades, rapid urbanization has exerted significant pressure on coastal ecosystems, resulting in biodiversity and habitat loss, environmental pollution, and the depletion of natural resources. In response to these environmental challenges, the Sustainable Development Goals (SDGs) were proposed. Given the pressing need to address these issues, understanding the changes in ESs under the SDGs is crucial for formulating specific ecological strategies. In this study, we first analyzed land use and cover change in the Zhejiang coasts of China during 2000–2020. Then, we investigated the spatiotemporal configuration of ESs by integrating carbon storage (CS), soil retention (SR), habitat quality (HQ) and water yield (WY) using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. The driving mechanisms of ESs, which varied by space and time, were also explored using the Geo-detector method. The results revealed that, over the past two decades: 1) the Zhejiang coasts have experienced a significant increase of 2783.72 km² in built-up land areas and a continuous decrease in farmland areas due to rapid urbanization; 2) owing to higher precipitation, extensive vegetation cover, and reduced anthropogenic disturbances, forests emerge as a crucial land use type for maintaining ecosystem services such as HQ, CS, WY, and SR; 3) ESs have generally declined across the entire Zhejiang coasts, with a significant decrease observed in the northern areas and an increase in the southern areas spatially; 4) the expansion of built-up land areas emerged as the primary factor affecting ecosystem services, while the vegetation factor has been increasingly significant and is expected to become predominant in the near future. Our study provides insights of understanding of ecosystem service theory and emphasizing the importance of preserving biodiversity for long-term sustainable development, and valuable scientific references to support the ecological management decision-making for local governments.

The rise in online home delivery services (OHDS) has had a significant impact on how urban services are supplied and used in recent years. Studies on the spatial accessibility of OHDS are emerging, but few is known about the temporal dimension of OHDS accessibility as well as the geographic and socioeconomic differences in the spatiotemporal accessibility of OHDS. This study measures the spatiotemporal accessibility of four types of OHDS, namely leisure, fresh and convenient, medical, and catering services. The geographic and socioeconomic disparities in the spatiotemporal accessibility of these four types of OHDS are then identified using spatial statistical methods and the Kruskal-Wallis test (K-W test). The case study in Nanjing, China, suggests that: 1) spatiotemporal accessibility better reflects the temporal variation of OHDS accessibility and avoids overestimation of OHDS accessibility when only considering its spatial dimension. 2) The spatiotemporal accessibility of OHDS varies geographically and socioeconomically. Neighborhoods located in the main city or neighborhoods with higher housing prices, higher population density, and higher point of interest (POI) mix have better OHDS spatiotemporal accessibility. Our study contributes to the understanding of OHDS accessibility from a spatiotemporal perspective, and the empirical insights can assist policymakers in creating intervention plans that take into account variations in OHDS spatiotemporal accessibility.

The spatial and temporal variation of green economic efficiency and its driving factors are of great significance for the construction of high-efficiency and low-consumption green development model and sustainable socio-economic development. The research focused on the Yangtze River Economic Belt (YREB) and employed the miniumum distance to strong efficient frontier DEA (MinDs) model to measure the green economic efficiency of the municipalities in the region between 2008 and 2020. Then, the spatial autocorrelation model was used to analyze the evolution characteristics of its spatial pattern. Finally, Geodetector was applied to reveal the drivers and their interactions on green economic efficiency. It is found that: 1) the overall green economic efficiency of the YREB from 2008 to 2020 shows a W-shaped fluctuating upward trend, green economic efficiency is greater in the downstream and smallest in the upstream; 2) the spatial distribution of green economic efficiency shows clustering characteristics, with multi-core clustering based on ‘city clusters-central cities’ becoming more obvious over time; the High-High agglomeration type is mainly clustered in Jiangsu and Zhejiang, while the Low-Low agglomeration type is clustered in the western Sichuan Plateau area and southwestern Yunnan; 3) from input-output factors, whether it is the YREB as a whole or the upper, middle and lower reaches regions, the economic development level, labor input, and capital investment are the leading factors in the spatial-temporal evolution of green economic efficiency, with the comprehensive influence of economic development level and pollution index being the most important interactive driving factor; 4) from socio-economic factors, information technology drivers such as government intervention, transportation accessibility, information infrastructure, and Internet penetration are always high impact influencers and dominant interaction factors for green economic efficiency in the YREB and the three major regions in the upper, middle and lower reaches. Accordingly, the article puts forward relevant policy recommendations in terms of formulating differentiated green transformation strategies, strengthening network leadership and information technology construction and coordinating multi-factor integrated development, which could provide useful reference for promoting synergistic green economic efficiency in the YREB.

Chinese Loess Plateau has achieved a win-win situation concerning ecological restoration and socio-economic development. However, synergistic development may not be realized at the local scale. In areas undergoing ecological restoration, livelihood vulnerability may be more pronounced due to the inflexibility, policy protection, and susceptibility to climate and market changes in forestry production. Although this issue has attracted academic interest, empirical studies are relatively scarce. This study, centered on Jiaxian County, Shaanxi Province of China explored the households’ livelihood vulnerability and coping strategies and group heterogeneity concerned with livelihood structures or forestry resources through field investigation, comprehensive index assessment, and nonparametric tests. Findings showed that: 1) the percentage of households with high livelihood vulnerability indicator (LVI) (> 0.491) reached 46.34%. 2) Eight groups in livelihood structures formed by forestry, traditional agriculture, and non-farm activities were significantly different in LVI, land resources (LR), social networks (SN), livelihood strategies (LS), housing characteristics (HC), and socio-demographic profile (SDP). 3) The livelihood vulnerability of the groups with highly engaged/reliance on jujube (Ziziphus jujuba) forest demonstrated more prominent livelihood vulnerability due to the increased precipitation and cold market, where the low-engaged with reliance type were significantly more vulnerable in LVI, SDP, LR, and HC. 4) The threshold of behavioral triggers widely varied, and farmers dependent on forestry livelihoods showed negative coping behavior. Specifically, the cutting behavior was strongly associated with lagged years and government subsidies, guidance, and high returns of crops. Finally, the findings can provide guidance on the direction of livelihood vulnerability mitigation and adaptive government management in ecologically restored areas. The issue of farmers’ livelihood sustainability in the context of ecological conservation calls for immediate attention, and eco-compensations or other forms of assistance in ecologically functional areas are expected to be enhanced and diversified.

Vegetation restoration can alter carbon (C), nitrogen (N), and phosphorus (P) cycles in coastal wetlands affecting C: N: P stoichiometry. However, the effects of restoration age on soil C: N: P stoichiometry are unclear. In this study, we examined the responses of soil C, N, and P contents and their stoichiometric ratios to vegetation restoration age, focusing on below-ground processes and their relationships to aboveground vegetation community characteristics. We conducted an analysis of temporal gradients based on the ‘space for time’ method to synthesize the effects of restoration age on soil C: N: P stoichiometry in the Yellow River Delta wetland of China. The findings suggest that the combined effects of restoration age and soil depth create complex patterns of shifting soil C: N: P stoichiometry. Specifically, restoration age significantly increased all topsoil C: N: P stoichiometries, except for soil total phosphorus (TP) and the C: N ratio, and slightly affected subsoil C: N: P stoichiometry. The effects of restoration age on the soil C: N ratio was well constrained owing to the coupled relationship between soil organic carbon (SOC) and total nitrogen (TN) contents, while soil TP content was closely related to changes in plant species diversity. Importantly, we found that the topsoil C: N: P stoichiometry was significantly affected by plant species diversity, whereas the subsoil C: N: P stoichiometry was more easily regulated by pH and electric conductivity (EC). Overall, this study shows that vegetation restoration age elevated SOC and N contents and alleviated N limitation, which is useful for further assessing soil C: N: P stoichiometry in coastal restoration wetlands.