Driving factors of ecosystem services and their spatiotemporal change assessment based on land use types in the Loess Plateau

Wang, Xiaozhen; Jing, Wu; Liu, Yulin; Hai, Xuying; Shanguan, Zhouping; Deng, Lei

doi:10.1016/j.jenvman.2022.114835

Cited by 123 publications

(51 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In general, the higher the GDP, population density, and percentage of built-up land, the higher the degree of human interference with the ecosystem. In addition, geographic locations, such as distance to the county center, road, and water system, also have impacts on ES, mainly affecting the spatial patterns of ESV [ 52 ].…”

Section: Methodsmentioning

confidence: 99%

Quantifying the Relationship between Land Use Intensity and Ecosystem Services’ Value in the Hanjiang River Basin: A Case Study of the Hubei Section

Yang

Zheng

Wang

et al. 2022

IJERPH

View full text Add to dashboard Cite

An increased land use intensity due to rapid urbanization and socio-economic development would alter the structure and function of regional ecosystems and cause prominent environmental problems. Revealing the impact of land use intensity on ecosystem services (ES) would provide guidance for more informed decision making to promote the sustainable development of human and natural systems. In this study, we selected the Hanjiang River Basin (HRB) in Hubei Province (China) as our study area, explored the correlation between land use intensity and ecosystem Services’ Value (ESV), and investigated impacts of natural and socio-economic factors on ESV variations based on the Geographical Detector Model (GDM) and Geographically Weighted Regression (GWR). The results show that (1) from 2000 to 2020, land use intensity in HRB generally showed an upward trend, with a high spatial agglomeration in the southeast and low in the northwest; (2) the total ESV increased from 295.56 billion CNY in 2000 to 296.93 billion CNY in 2010, and then decreased to 295.63 CNY in 2020, exhibiting an inverted U-shaped trend, with regulation services contributing the most to ESV; (3) land use intensity and ESV had a strong negative spatial correlation, with LH (low land use intensity vs. high ESV) aggregations mainly distributed in the northwest, whereas HL (high land use intensity vs. low ESV) aggregations were located in the southeast; (4) natural factors, including annual mean temperature, the percentage of forest land, and slope were positively associated with ESV, while socio-economic factors, including GDP and population density, were negatively associated with ESV. To achieve the coordinated development of the socio-economy and the environment, ES should be incorporated into spatial planning and socio-economic development policies.

show abstract

Section: Methodsmentioning

confidence: 99%

Quantifying the Relationship between Land Use Intensity and Ecosystem Services’ Value in the Hanjiang River Basin: A Case Study of the Hubei Section

Yang

Zheng

Wang

et al. 2022

IJERPH

View full text Add to dashboard Cite

show abstract

“…Nevertheless, problems of ecological degradation in the region persist. With the acceleration of urbanization, the demand for construction land has expanded rapidly, and human activities have exacerbated the division and occupation of cultivated land [65,66].…”

Section: Ecc Spatiotemporal Evolution and Its Determinantsmentioning

confidence: 99%

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

Zhu

Mei

et al. 2022

Land

View full text Add to dashboard Cite

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.

show abstract

“…However, apple planting is greatly affected by weather, such as late spring coldness, hail, and persistent drought, which may cause heavy losses to apple growers. Shaanxi Province is one of the provinces prone to natural disasters, with severe drought and hail disasters (Wang et al, 2022). Therefore, it is representative and signi cant to select apple growers in Shaanxi Province as the research object to analyze the impact of extreme weather on farmers' climateadaptive technology adoption behavior.…”

Section: Datamentioning

confidence: 99%

Farmers’ Adaptation to Extreme Weather: Evidence from Rural China

Mao

Zhang

2022

Preprint

View full text Add to dashboard Cite

Climate change is a huge challenge for agricultural production. Climate-adaptive technology is an effective measure for farmers to adapt to climate change and improve their ability to cope with natural disasters. The low adoption rate of climate-adaptive technology has become an important factor restricting the sustainable development of China’s agriculture. Extreme weather may affect farmers' decisions to adopt climate-adaptive technology. This paper uses the survey data of 622 apple growers in Shaanxi Province to study the impact of extreme weather on farmers’ climate-adaptive technology adoption behavior and its mechanism. The results show that extreme weather has a significant positive effect on farmers’ adoption of climate-adaptive technology. This result still holds after robustness checks such as changing the measurement methods of key variables. In terms of the mechanism, one is that extreme weather can improve farmers’ risk perception and promote their adoption of climate-adaptive technology; the other is that extreme weather can promote farmers’ participation in credit, which in turn promotes their adoption of climate-adaptive technology. Heterogeneity analysis shows that compared with areas without policy incentives, extreme weather has a greater effect on farmers’ climate-adaptive technology adoption behavior in areas with policy incentives. Overall, the results suggest that promoting farmers’ adoption of climate-adaptive technology and understanding how well farmers respond to climate shocks can inform policy design and help reduce risks to agricultural production from extreme weather.

show abstract

Driving factors of ecosystem services and their spatiotemporal change assessment based on land use types in the Loess Plateau

Cited by 123 publications

References 54 publications

Quantifying the Relationship between Land Use Intensity and Ecosystem Services’ Value in the Hanjiang River Basin: A Case Study of the Hubei Section

Quantifying the Relationship between Land Use Intensity and Ecosystem Services’ Value in the Hanjiang River Basin: A Case Study of the Hubei Section

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

Farmers’ Adaptation to Extreme Weather: Evidence from Rural China

Contact Info

Product

Resources

About