Spatial–Temporal Heterogeneity of Urbanization and Ecosystem Services in the Yellow River Basin

Zhang, Zhongwu; Zhang, Jinyuan; Liu, Liping; Gong, Jian Ping; Li, Jinqiang; Kang, Lei

doi:10.3390/su15043113

Cited by 10 publications

(9 citation statements)

References 45 publications

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“…The limited level of financial support for agriculture may be due to the fact that the government prefers objectives with long-term strategic or economic value when allocating financial assistance [42]. In addition, financial support for agriculture in China currently faces structural challenges that hinder its ability to have an ecological impact [43].…”

Section: Analysis Of Regression Resultsmentioning

confidence: 99%

Research on the Effect of Digital Economy Development on the Carbon Emission Intensity of Agriculture

Wang,

Mei

2024

Sustainability

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The integration of the digital economy with the real economy has facilitated the application of a variety of digital methods in agriculture, resulting in significant reductions in its carbon intensity. This study employs a spatial Durbin model to analyze the spatiotemporal effects of digital economic growth on agricultural carbon emissions, using Chinese inter-provincial panel data spanning from 2011 to 2020. The empirical results indicate a substantial decline in agricultural carbon emissions associated with the evolution of the digital economy. Additionally, a discernible spatial spillover effect is identified. The suppressive impact of the digital economy on agricultural carbon emission intensity exhibits clear heterogeneity, with more pronounced effects observed in the main grain-producing regions and western regions. Based on these findings, recommendations are proposed to accelerate the development of digital economy infrastructure tailored to local conditions, promote the integration of digital technology and agriculture, stimulate innovation in agricultural science and technology, and advocate for the adoption of energy-efficient and environmentally sustainable agricultural practices.

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Section: Analysis Of Regression Resultsmentioning

confidence: 99%

Research on the Effect of Digital Economy Development on the Carbon Emission Intensity of Agriculture

Wang,

Mei

2024

Sustainability

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“…Therefore, in the process of formulating development policies, prefecture-level cities in the Yellow River Basin should respect the general laws of the development of prefecture-level cities. Moreover, attention should be paid to the characteristics of each prefecture-level city, and targeted research and understanding are needed [52,53].…”

Section: Discussionmentioning

confidence: 99%

Study on Urban Spatial Expansion and Its Scale Benefit in the Yellow River Basin

Zhang,

Liu,

Zhang

2023

Sustainability

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Based on nighttime light data from 2000, 2005, 2010, 2015 and 2020, the urban built-up area of 90 prefecture-level cities in the Yellow River Basin was extracted, and the urban spatial expansion characteristics of 90 prefecture-level cities were explored from the two elements of expansion speed and expansion intensity. The entropy method was used to calculate the comprehensive level of economic-, social- and ecological-scale benefits of 90 prefecture-level cities. The gray correlation degree was used to measure the correlation between urban spatial expansion and scale benefits, and the geographical detector was used to identify the driving factors of urban spatial expansion. The results show the following: (1) The urban spatial expansion characteristics of 90 prefecture-level cities in the Yellow River Basin are clearly different. From 2000 to 2020, the urban spatial area increased to 2.94 times the original, and the expansion speed and intensity increased but fluctuated significantly. (2) The comprehensive level of economic-, social- and ecological-scale benefits of 90 prefecture-level cities in the Yellow River Basin has gradually improved. (3) There is a high correlation between urban spatial expansion and economic-, social- and ecological-scale benefits in 90 prefecture-level cities in the Yellow River Basin, but there are obvious regional differences in the eastern, central and western prefecture-level cities. (4) The urban spatial expansion of the Yellow River Basin is the result of the joint action of natural factors, the economic development level, industrial structure, government regulation ability, population size and opening level. Among them, per capita GDP, population density and the proportion of secondary and tertiary industry output value to the total output value are the most important driving factors.

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“…However, China's tourism industry has adopted an extensive growth mode, resulting in a severe threat to ecological security, especially in areas with fragile ecosystems, such as arid zones and large river basins. Among them, the Yellow River Basin (YRB), one of the most important ecological barriers in China, has received wide attention from scholars [18][19][20]. It is facing the crisis of ecosystem degradation due to unreasonable tourism development and overtourism [21].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Tourism Ecological Security and Its Driving Mechanism in the Yellow River Basin, China: Based on Open Systems Theory and DPSIR Model

Cai

Shi

2023

Systems

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Tourism ecological security (TES) has gradually become a frontier topic because it is related to the virtuous circle of ecosystems and sustainable development, especially in river basins with fragile ecosystems. Based on the Driver–Pressure–State–Impact–Response (DPSIR) model and open systems theory, we constructed a TES evaluation system in the Yellow River Basin (YRB), China. Then, the TES index was measured from 2004 to 2019 and its spatio-temporal characteristics and driving mechanism were analyzed. The results show that: (1) In terms of temporal evolution, the comprehensive TES index shows a steady upward trend, but the difference between cities increases over time. Moreover, the proportion of cities with low status levels of TES declined rapidly, while the proportion of cities with high status levels of TES has grown slowly. (2) Spatially, low-TES value cities have always been in the majority, and the high-value cities show a scattered spatial distribution, most of which are along the river. Moreover, TES is randomly distributed in space before 2013, but it shows a significant positive spatial clustering feature thereafter. Specifically, the range of hot spots extends from the intersection of the middle and upper reaches to downstream, while the cold spots are always scattered. Furthermore, the trend surface in the east–west direction is always smooth, while it gradually manifests an inverted U-shape in the north–south direction. (3) In the dynamic transfer, TES lacks the vitality of transfer, but the probability of shifting upward becomes more significant when adjacent to higher-level cities; the opposite is true when adjacent to lower-ranked cities. (4) In terms of the driving mechanism, the factors related to tourism and the economy are the most important driving forces, and the effect of tourism-related factors on TES is becoming increasingly significant. Moreover, the driving mechanism is constructed. Finally, this study provides targeted policy implications for improving TES in the YRB, which has reference value for the development of ecological protection and high-quality tourism.

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Spatial–Temporal Heterogeneity of Urbanization and Ecosystem Services in the Yellow River Basin

Cited by 10 publications

References 45 publications

Research on the Effect of Digital Economy Development on the Carbon Emission Intensity of Agriculture

Research on the Effect of Digital Economy Development on the Carbon Emission Intensity of Agriculture

Study on Urban Spatial Expansion and Its Scale Benefit in the Yellow River Basin

Evaluation of Tourism Ecological Security and Its Driving Mechanism in the Yellow River Basin, China: Based on Open Systems Theory and DPSIR Model

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