Combined Impact of Socioeconomic Forces and Policy Implications: Spatial-Temporal Dynamics of the Ecosystem Services Value in Yangtze River Delta, China

Chen, Sha; Li, Guan; Zhang, Xu; Zhuo, Yuefei; Wu, Cifang; Ye, Yanmei

doi:10.3390/su11092622

Cited by 22 publications

(11 citation statements)

References 93 publications

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“…For instance, Wang's study identified the positive effects exerted by the proportion of renters, the floating population, wage levels, the cost of land, the housing market and city service levels on housing prices, and the negative influence exerted by living space by using these conventional spatial regression techniques (including SLM and SEM) [88]. Chen confirmed that population growth and economic advancement exerted a considerable influence on socioeconomic development, thereby affecting the change of ecosystem service value (ESV) based on the study of the impact of human activities on land use change and consequent dynamics of ESV by using spatial lag and spatial error models [130]. Furthermore, Zhang suggested that all air pollution emissions in China's 31 provinces had significant spatial dependence and strong spillover effects at different significance levels by using spatial lag models [131].…”

Section: Mechanism Explaining the High-vs Low-skilled Gap In Spatialmentioning

confidence: 86%

“…Furthermore, Zhang suggested that all air pollution emissions in China's 31 provinces had significant spatial dependence and strong spillover effects at different significance levels by using spatial lag models [131]. Given that many scholars conduct the similar research on migration, housing prices, and other socioeconomic problems based on these conventional spatial regression models [88,130,131], we also choose the ordinary least square (OLS), the spatial lag (SLM) and the spatial error (SEM) models in this study to look into migrant rent affordable stress issues in urban China. In this paper, we analyze the driving factors that can interpret the variance of the high-and low-skilled migrants in terms of the geographic distribution of high-rent-stress samples (rent-income ratios above 25 percent), by using the ordinary least square (OLS), the spatial lag (SLM) and the spatial error (SEM) models.…”

Section: Mechanism Explaining the High-vs Low-skilled Gap In Spatialmentioning

confidence: 99%

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Regional Heterogeneity of Migrant Rent Affordability Stress in Urban China: A Comparison between Skilled and Unskilled Migrants at Prefecture Level and Above

Liu

2019

Sustainability

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Rental housing unaffordability has been widely used to assess the housing poverty problem among immigrants in the developed and developing countries. China is experiencing an unprecedented urbanization process, with two-thirds of its 250 million migrants now being sheltered in private rental housing in the host cities. In this paper, we aimed to examine the rental housing unaffordability problems faced by migrant workers in urban China and provide policy recommendations for a more accessible and affordable migrant housing provision system. We used the household data on China’s Migrant Dynamics Monitoring Survey (MDMS), released in 2016, across China’s 329 prefecture-level cities and above to look into the sociality and spatiality of migrant rent expenses and rent-income ratio at the prefecture-level cities and above. The statistical tests were conducted to examine the socio- and spatial-variance of these rent stress indexes, and it was found that educational level is a significant and quite powerful indicator in predicting who will or will not assume the heavier rental housing pressure. We then continued to reveal the different spatiality of high-rent-stress migrants across the high- and low-skilled categories. An agglomeration of the high-skilled high-rent-stress migrants was witnessed in the coastal growth engines of urban clusters, while a more spillover-like pattern among the low-skilled high-rent-stress migrants was reported in our study. An ordinary least square and spatial regression analysis was conducted to explain their respective mechanisms.

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Section: Mechanism Explaining the High-vs Low-skilled Gap In Spatialmentioning

confidence: 86%

Section: Mechanism Explaining the High-vs Low-skilled Gap In Spatialmentioning

confidence: 99%

Regional Heterogeneity of Migrant Rent Affordability Stress in Urban China: A Comparison between Skilled and Unskilled Migrants at Prefecture Level and Above

Liu

2019

Sustainability

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“…Studies have shown that in order to pursue foreign investment, local governments even adjust their planning without limit to meet the demand for land development [63,64]. Moreover, in a top-down planning system, the development orientation and function of each town are different, thus forming different town rank that can affect the input of the above factors and directly affect the expansion of built-up land that determine the outcomes of plan implementation [65]. To this end, we select the potential impact factors, including the population density (PD), the rate of urbanisation (URB), the gross domestic product (GDP), the fiscal revenue (FR), the fixed assets investments (FAI), and the rank of town (RT).…”

Section: Potential Influencing Factorsmentioning

confidence: 99%

“…Moreover, the rank of town reflects the importance of the economic development of each township within a county. If the township is on a higher rank which is given by national economic and social development planning, it will get more investment from the upper government that more infrastructure projects and investment will be prioritized located in these townships [65]. It also means that planning is more likely to face the situation that development needs and land development requirements is out of expected.…”

Section: Economic Development Brings Significant Uncertainty To the Imentioning

confidence: 99%

Inside or Outside? The Impact Factors of Zoning–Land Use Mismatch

Zhang

et al. 2019

Sustainability

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A land-use plan is a core policy tool to curb excessive non-agriculturalization of agricultural land. The effect of plan implementation can affect sustainable land use and regional development. Empirical studies have shown that land development commonly and frequently fails to conform to land-use plans. However, neither qualitative nor quantitative studies are conducted to comprehensively explore the reasons for zoning-land use mismatch. To help bridge this gap, this study explored to what extent a plan has been implemented and what factors have affected zoning-land use mismatch. A new deviation discriminant framework of planning implementation was presented. Moreover, the logistics model was applied to discuss which factors substantially affect the zoning-land use mismatch. The plan implementation results were divided into the conformed, exceeded and unused areas. The general land-use plan failed in its spatial control over rural settlements and other built-up lands, with both more than 90% of the newly added construction land beyond zoning. In addition, the newly added construction land of rural settlements, other built-up lands, and transportation lands all exceeded the quota control. Furthermore, the physical factors of distance from the river, the elevation, the slope and the level, and the social-economic factors of the gross domestic product, the fiscal revenue, the fixed assets investments, and the rank of town have prominent effects on zoning-land use mismatch. Enhancing the flexibility of the land-use plan and strengthening the relationship between planning quotas and spatial zoning in the future are necessary to promote the effect of plan implementation.

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“…However, previous studies have shown that changes in ESVs are the result of a combination of multiple driving factors. Therefore, a comprehensive analysis of the impact of natural factors [ 46 , 47 , 48 , 49 ], socio-economic factors [ 49 , 50 , 51 ], and political factors [ 44 , 52 ] on the ESVs is helpful to understand the ecological environment protection and formation mechanism.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Variation and Driving Forces Analysis of Eco-System Service Values: A Case Study of Sichuan Province, China

Shao

Xian

2022

IJERPH

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Sichuan Province is an important ecological barrier in the upper reaches of the Yangtze River. Therefore, it is critical to investigate the temporal and spatial changes, as well as the driving factors, of ecosystem service values (ESVs) in Sichuan Province. This paper used land use data from 2000, 2005, 2010, 2015, and 2020 to quantify the spatiotemporal changes in the ESVs in Sichuan Province. Correlation coefficients and bivariate spatial autocorrelation methods were used to analyze the trade-offs and synergies of ESVs in the city (autonomous prefecture) and grid scales. At the same time, we used a Geographical Detector model (GDM) to explore the synergies between nine factors and ESVs. The results revealed that: (1) In Sichuan Province, the ESVs increased by 0.77% from 729.26 × 109 CNY in 2000 to 741.69 × 109 CNY in 2020 (unit: CNY = Chinese Yuan). Furthermore, ecosystem services had a dynamic degree of 0.13%. Among them, the ESVs of forestland were the highest, accounting for about 60.59% of the total value. Among the individual ecosystem services, only food production, environmental purification, and soil conservation decreased in value, while the values of other ecosystem services increased. (2) The ESVs increased with elevation, showing a spatial distribution pattern of first rising and then decreasing. The high-value areas of ESVs per unit area were primarily distributed in the forestland of the transition area between the basin and plateau; The low-value areas were distributed in the northwest, or the urban areas with frequent human activities in the Sichuan Basin. (3) The tradeoffs and synergies between multi-scale ecosystems showed that ecosystem services were synergies-dominated. As the scale of research increased, the tradeoffs between ecosystems gradually transformed into synergies. (4) The main driving factors for the spatial differentiation of ESVs in Sichuan Province were average annual precipitation, average annual temperature, and gross domestic product (GDP); the interaction between normalized difference vegetation index (NDVI) and GDP had the strongest driving effect on ESVs, generally up to 30%. As a result, the distribution of ESVs in Sichuan Province was influenced by both the natural environment and the social economy. The present study not only identified the temporal and spatial variation characteristics and driving factors of ESVs in Sichuan Province, but also provided a reference for the establishment of land use planning and ecological environmental protection mechanisms in this region.

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Combined Impact of Socioeconomic Forces and Policy Implications: Spatial-Temporal Dynamics of the Ecosystem Services Value in Yangtze River Delta, China

Cited by 22 publications

References 93 publications

Regional Heterogeneity of Migrant Rent Affordability Stress in Urban China: A Comparison between Skilled and Unskilled Migrants at Prefecture Level and Above

Regional Heterogeneity of Migrant Rent Affordability Stress in Urban China: A Comparison between Skilled and Unskilled Migrants at Prefecture Level and Above

Inside or Outside? The Impact Factors of Zoning–Land Use Mismatch

Spatiotemporal Variation and Driving Forces Analysis of Eco-System Service Values: A Case Study of Sichuan Province, China

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