Spatial-Temporal Patterns of Ecosystem Services Supply-Demand and Influencing Factors: A Case Study of Resource-Based Cities in the Yellow River Basin, China

Li, Ming; Chang, Jiang; Li, Cheng; Chen, Yedong; Li, Cankun

doi:10.3390/ijerph192316100

Cited by 10 publications

(8 citation statements)

References 42 publications

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“…In this study, we consulted the equivalent factor table developed by Xie Gaodi [44], which was based on the research of Costanza et al [28]. Since equivalent factors for ecosystem services vary across regions, we established an equivalent factor table, which was accomplished by comparing the grain yield per unit area in the research area to the national grain yield per unit area [45]. To account for price fluctuations over the years, we used the average grain yield per unit area from 2011 to 2021 and the average grain price in 2021 to estimate the economic value of the grain yield per unit area during the research period [46].…”

Section: Calculate the Soil Safety Value And Biodiversity Value Using...mentioning

confidence: 99%

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The Spatial Protection and Governance of Territories Based on the Ecological Product Supply: A Case Study in Beijing–Tianjin–Hebei, China

Peng,

Yuchi,

Sun

et al. 2023

Land

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Territory space is an ecological resource carrier and place for human development. Human activities and ecological systems are the basis of ecological product supply. Promoting territories’ spatial protection and governance by improving the supply of ecological products is very important. In this study, we established an ecological product supply capacity evaluation index system involving three types of ecological products, i.e., ecological environmental products, ecological material products, and ecological cultural products. For the case of the Beijing–Tianjin–Hebei region, we comprehensively used principal component analysis, the equivalent factor method, and the entropy method to evaluate the supply capacity of ecological products from 2011 to 2021. Then, we analyzed the spatio-temporal pattern, combining the natural breakpoint and quantile classification methods, and analyzed the obstacle factors using the obstacle degree model of ecological supply. The results show that the supply capacity of different ecological products in each city are closely related to their ecological resource endowment. The supply capacity of ecological products exhibited an upward trend, with the highest ecological environmental product supply being relatively smaller than the ecological material product supply, while the largest growth rate was for ecological cultural product supply. The supply capacity of different ecological products varied across cities over time and displayed noticeable spatial differentiation. The main obstacle factors included eco-land, eco-tourism, eco-leisure, park green space, and fishery products, although there were variations among cities. Finally, based on the level, spatial-temporal pattern, and obstacle factors of ecological product supply, we proposed strategies for territory spatial protection and governance from the perspectives of the integrated protection of elements, structural regulation, and systematic governance. The results reflected the ecological functional heterogeneity of the territory space, which can provide spatial planning guidance for sustainable development.

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Section: Calculate the Soil Safety Value And Biodiversity Value Using...mentioning

confidence: 99%

“…X λij represents the value of the j indicator of the i city in the λ year. The extreme value method was used to normalize each indicator [45], transforming the indicator values to a range of 0-1, and the standardized values are denoted as X λij .…”

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confidence: 99%

The Spatial Protection and Governance of Territories Based on the Ecological Product Supply: A Case Study in Beijing–Tianjin–Hebei, China

Peng,

Yuchi,

Sun

et al. 2023

Land

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“…where n denotes the number of provinces; w ij represents the spatial weight matrix and the geographical distance matrix is used in this study; and D i and D j denote the CCD of region i and j, respectively. Global spatial autocorrelation cannot reveal the spatial agglomeration or heterogeneity of local regions, while local spatial autocorrelation has the advantage of revealing these spatial characteristics [74]. The formula is as follows:…”

Section: Spatial Autocorrelation Modelmentioning

confidence: 99%

Towards Sustainable Development Goals: Coupling Coordination Analysis and Spatial Heterogeneity between Urbanization, the Environment, and Food Security in China

Yin,

Chen,

et al. 2023

Land

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The interconnection between urbanization, the environment, and food security necessitates an exploration of their coupling coordination to advance the attainment of Sustainable Development Goals. However, limited research directly addresses the feasibility and strategies required to achieve such coordination. This study investigates the coupling coordination and spatial heterogeneity between urbanization, the environment, and food security in China from 2004 to 2020, employing the coupling coordination degree model, the spatial correlation model, the Dagum Gini coefficient, and the obstacle degree model. The results show that: (1) the level of coordinated development between urbanization, the environment, and food security in China has significantly increased, as evidenced by a remarkable rise in the coupling coordination degree; (2) a robust positive spatial correlation is observed in the coupling coordination degree, with “Low-Low” clusters predominantly concentrated in northwest China and “High-High” clusters primarily located in southeast China; (3) inter-regional differences are identified as the primary cause of this spatial heterogeneity; (4) food security has emerged as the foremost obstacle to coordinated development between urbanization, the environment, and food security in China. Optimizing the rational allocation of natural resources across different sectors, enhancing resource use efficiency, and strengthening environmental pollution control and management have been proven to be crucial measures and key strategies for promoting their coordinated development. This study provides a novel perspective on balancing the intricate relationship between urbanization, environmental protection, and food security, which is conducive to the achievement of Sustainable Development Goals in developing countries.

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“…Existing research has utilized various research methods and models to analyze the relationships between ES supply and demand. For example, methods such as nonlinear curve-fitting analysis [6], Kernel density estimation [7], and spatial correlation analysis [8] have been used to explore the matching coordination between ES supply and demand. In terms of research content, existing studies have analyzed the coordination between the ES supply and demand of various ES types, such as focusing on soil retention services [9,10], water conservation services [11,12], and cultural services [13].…”

Section: Introductionmentioning

confidence: 99%

Spatial–Temporal Pattern of Coordination between the Supply and Demand for Ecosystem Services in the Lhasa River Basin

Liu,

Wan,

et al. 2024

Land

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Quantifying the spatiotemporal patterns of the coordination between ecosystem service supply and demand is vital for regional sustainable development. To reveal the dynamic pattern of the coordination of ecosystem service (ES) supply and demand in the Lhasa River Basin, we quantified the supply of the following four ESs using the InVEST model from 2000 to 2018: carbon sequestration (CS), water conservation (WC), habitat quality (HQ), and soil conservation (SC). Using socio-economic data, including land development degree, GDP, and population density, the ES demand was quantified. The ES supply–demand ratio (ESDR) and coupling coordination degree (CCD) model were used to evaluate the coupling relationship and coordination of ES supply and demand. The spatial autocorrelation analysis was used to determine the spatial correlation and changes in the ES supply–demand coupling coordination degree. The results indicate that the distribution of ESDR exhibited significant spatial heterogeneity. The area with ES supply far greater than demand was always in the upstream area of the Lhasa River, while the ES demand of Chengguan District far exceeded supply. Grasslands and forests were the main contributors to ESDRs, providing positive ESDRs for three services, SC, HQ, and WC, with a total proportion above 80%. From 2000 to 2018, the mismatch between ES supply and demand was gradually spreading upstream, while the upstream areas had a relatively high CCD. The spatial correlations of the CCD in the Lhasa River basin all showed statistically significant differences (p < 0.01). The high–high aggregation areas were concentrated in the northeast of the Lhasa River basin, while the low–low aggregation areas were centered around Chengguan District. This study provides reference values for optimizing the land use spatial patterns in ecologically vulnerable areas with the goal of sustainable development.

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Spatial-Temporal Patterns of Ecosystem Services Supply-Demand and Influencing Factors: A Case Study of Resource-Based Cities in the Yellow River Basin, China

Cited by 10 publications

References 42 publications

The Spatial Protection and Governance of Territories Based on the Ecological Product Supply: A Case Study in Beijing–Tianjin–Hebei, China

The Spatial Protection and Governance of Territories Based on the Ecological Product Supply: A Case Study in Beijing–Tianjin–Hebei, China

Towards Sustainable Development Goals: Coupling Coordination Analysis and Spatial Heterogeneity between Urbanization, the Environment, and Food Security in China

Spatial–Temporal Pattern of Coordination between the Supply and Demand for Ecosystem Services in the Lhasa River Basin

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