Chinese Geographical Science最新文献

With the loss of substantial natural wetlands in coastal zones, artificial wetlands provide alternative habitats for many shorebirds. Scientific management of artificial wetlands used by shorebirds plays an important role in maintaining the stability of shorebird population. Satellite tracking technique can obtain high-precision location information of individuals day and night, providing a good technical support for the study of quantitative relationship between waterfowls and their habitats. In this study, satellite tracking method, Remote Sensing (RS) and Geographic Information System (GIS) technology were used to analyze the activity pattern and habitat utilization characteristics of Pied Avocet during breeding period in an artificial wetland complex in the Yellow River Delta (YRD), China. The results showed that the breeding Pied Avocets had a small range of activity, with a total core and main home range of 33.10 km² and 216.30 km², respectively. This species tended to forage in the pond and salt pan during the day and night, respectively, with an unfixed staying time in the breeding ground. The distance between breeding ground and feeding ground was less than 6 km. It is emphasized that in addition to improving the conditions of the remaining natural habitats, effective managing artificial habitats is a priority for shorebird conservation. This research could provide reference for the management of artificial wetlands in coastal zones and supply technique support for the protection of shorebirds and their habitats, and alleviate human-bird conflicts and sustainable development of coastal zones.

There are significant differences between urban and rural bed-and-breakfasts (B&Bs) in terms of customer positioning, economic strength and spatial carrier. Accurately identifying the differences in spatial characteristics and influencing factors of each type, is essential for creating urban and rural B&B agglomeration areas. This study used density-based spatial clustering of applications with noise (DBSCAN) and the multi-scale geographically weighted regression (MGWR) model to explore similarities and differences in the spatial distribution patterns and influencing factors for urban and rural B&Bs on the Jiaodong Peninsula of China from 2010 to 2022. The results showed that: 1) both urban and rural B&Bs in Jiaodong Peninsula went through three stages: a slow start from 2010 to 2015, rapid development from 2015 to 2019, and hindered development from 2019 to 2022. However, urban B&Bs demonstrated a higher development speed and agglomeration intensity, leading to an increasingly evident trend of uneven development between the two sectors. 2) The clustering scale of both urban and rural B&Bs continued to expand in terms of quantity and volume. Urban B&B clusters characterized by a limited number, but a higher likelihood of transitioning from low-level to high-level clusters. While the number of rural B&B clusters steadily increased over time, their clustering scale was comparatively lower than that of urban B&Bs, and they lacked the presence of high-level clustering. 3) In terms of development direction, urban B&B clusters exhibited a relatively stable pattern and evolved into high-level clustering centers within the main urban areas. Conversely, rural B&Bs exhibited a more pronounced spatial diffusion effect, with clusters showing a trend of multi-center development along the coastline. 4) Transport emerged as a common influencing factor for both urban and rural B&Bs, with the density of road network having the strongest explanatory power for their spatial distribution. In terms of differences, population agglomeration had a positive impact on the distribution of urban B&Bs and a negative effect on the distribution of rural B&Bs. Rural B&Bs clustering was more influenced by tourism resources compared with urban B&Bs, but increasing tourist stay duration remains an urgent issue to be addressed. The findings of this study could provide a more precise basis for government planning and management of urban and rural B&B agglomeration areas.

Mangroves play a pivotal role in tropical and subtropical coastal ecosystem, yet they are highly vulnerable to the effects of climate change, particularly the accelerated global sea level rise (SLR) and stronger tropical cyclones (TCs). However, there is a lack of research addressing future simultaneous combined impacts of the slow-onset of SLR and rapid-onset of TCs on China’s mangroves. In order to develop a comprehensive risk assessment method considering the superimposed effects of these two factors and analyze risk for mangroves in Dongzhaigang, Hainan Island, China, we used observational and climate model data to assess the risks to mangroves under low, intermediate, and very high greenhouse gas (GHG) emission scenarios (such as SSP1-2.6, SSP2-4.5, and SSP5-8.5) in 2030, 2050, and 2100, and compiled a risk assessment scheme for mangroves in Dongzhaigang, China. The results showed that the combined risks from SLR and TCs will continue to rise; however, SLRs will increase in intensity, and TCs will decrease. The comprehensive risk of the Dongzhaigang mangroves posed by climate change will remain low under SSP1-2.6 and SSP2-4.5 scenarios by 2030, but it will increase substantially by 2100. While under SSP5-8.5 scenario, the risks to mangroves in Dongzhaigang are projected to increase considerably by 2050, and approximately 68.8% of mangroves will be at very high risk by 2100. The risk to the Dongzhaigang mangroves is not only influenced by the hazards but also closely linked to their exposure and vulnerability. We therefore propose climate resilience developmental responses for mangroves to address the effects of climate change. This study for the combined impact of TCs and SLR on mangroves in Dongzhaigang, China can enrich the method system of mangrove risk assessment and provide references for scientific management.

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.