The Impact of Urban Development Intensity on Ecological Carrying Capacity: A Case Study of Ecologically Fragile Areas

Ecological performance assessment of ecologically fragile areas: a perspective of spatiotemporal analysis

Sustainable development in ecologically fragile areas (EFAs) has faced significant challenges in recent years, but the traditional analytical approaches fail to provide an ideal assessment for ecological performance due to spatiotemporal variability in EFAs. This paper evaluates the ecological performance of EFAs based on a modified ecological footprint model, and ecological footprint intensity (EFI) is considered an essential indicator to measure ecological performance, especially for EFAs. Empirically, taking the Π-shaped Curve Area in the Yellow River basin of China as the study area, the spatiotemporal heterogeneity of EFI of 17 cities in the area is analyzed. Then, the extended STIRPAT and geographically and temporally weighted regression (GTWR) models are employed to explore the spatiotemporal heterogeneity of the factors driving EFI. The results show that from 2006 to 2019, the overall level of EFI in the area has decreased; EFI of the area offers a significant spatial agglomeration effect; results of the GTWR model suggest that factors driving EFI have spatiotemporal heterogeneity; the impact of population size, openness, marketization, technology, industrial structure rationalization, and information communication level on EFI was two-sided, while that of affluence, government scale, environmental regulation, and industrial structure advancement show inhibitory impact with the intensity of inhibition varying across periods and cities.

Sustainable Population Size at the County Level under Limited Development Policy Constraints: Case Study of the Xihaigu Mountain Area, Northwest China

Understanding the extent to which demographic changes may affect the prospects of sustainable development is a priority for both academics and policy makers. Accordingly, we attempted to explore the population growth limit of the Xihaigu Mountain area in China. To analyze the optimum population at the county level, the relationship curve between population size and environmental quality was fitted using panel data (2009–2018). The sustainable population size of each county was determined by integrating the population carrying capacity of land resources and optimum population. The results show that the relationship between regional population size and environmental quality conforms to an inverted N-shaped curve. To maintain sustainable development, the population size of Tongxin, Xiji, and Haiyuan should be in the range of 320,800–379,800, 315,800–416,900, and 333,500–416,900, respectively. The current population size of other counties should be maintained, and their surplus construction lands are acceptable to be used for environmentally friendly industries rather than population expansion. We demonstrated a practical approach to calculate a dynamic range of population size under the dual constraints of resource and environment, which overcomes the shortcoming of only considering the maximum carrying capacity to a limited extent. We also identified the population boundary in a “steady-state economy” and quantified planetary boundaries of population in Xihaigu Mountain area using a dynamic sustainable population size. The findings provide decision-making references for the local government.

Evaluation of Ecological Carrying Capacity and Identification of Its Influencing Factors Based on Remote Sensing and Geographic Information System: A Case Study of the Yellow River Basin in Shaanxi

Ecological carrying capacity (ECC), which requires simple scientific evaluation methods, is an important evaluation index for assessing the sustainability of ecosystems. We integrate an innovative research method. Geographic information systems (GIS) and remote sensing (RS) were used to evaluate the ECC of the Yellow River Basin in Shaanxi (YRBS) and to identify the underlying factors that influence it. A calculation method that combines RS and GIS data to estimate ECC based on net primary productivity (NPP) was established. The Carnegie–Ames–Stanford approach model was applied to estimate NPP. The NPP of each land type was used as an indicator to determine the yield factors. The ECC of the watershed was calculated with the carrying capacities of each land-use type. The geographical detector model was used to study the influencing factors of ECC, which provides a scientific basis for the formulation of ecological management policies in YRBS. The results show that from 2000 to 2010, it first decreased by 45.46%, and then increased by 37.06% in 2020, an overall decrease of 13.49 × 105 wha in 20 years. Precipitation is the dominant factor that affects ECC, while the impact of human activities on ECC was significantly enhanced during the study period. The developed method based on RS data serves as a reference for ecological evaluation in other similar regions.

Rethinking the Contribution of Land Element to Urban Economic Growth: Evidence from 30 Provinces in China

In China, disputes regarding the benefits and drawbacks of land finance have been heated, but the role of land in urban economic growth has received insufficient attention, particularly on a macro scale. This research used the Cobb–Douglas production function model to investigate the role of land in urban economic growth. Then, we conducted an empirical test using panel data from 30 provinces from 2000 to 2019, with the goal of revealing the role of land in urban growth and spatio-temporal inequalities in China. Furthermore, to find the spatial steady-state level of land contributions, σ convergence, absolute β convergence, and condition β convergence tests were applied. The results show that: (1) China’s urban economic development was influenced by the combined element of land, capital, and labor; (2) the contribution of land to China’s urban economy experienced a turning point during the “12th Five-Year Plan”; (3) the spatio-temporal convergence of the contribution of land showed convergence in the east but nonconvergence in the central and western regions; and (4) β convergence demonstrated convergence in eastern, central, and western China. Given the complex and turbulent international political and economic context, the Chinese government should think about how to foster continuous energy by supporting land-supply policies that are adapted to local needs.