Estimating the effects of driving forces on ecosystem services and their responses to environmental conditions

Huang, Ying; Wu, Yusi; Niu, Shaofei; Gan, Xiaoyu

doi:10.1007/s11356-022-20867-x

Cited by 4 publications

(6 citation statements)

References 64 publications

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“…NDVI, DEM, and SLO have significant positive effects on ES. These results are consistent with other studies but slightly different in the magnitude of the correlation coefficient (Lin et al, 2020), this is mainly due to the differences in research methods and scales, which provide a reference for enhancing ES in the Sichuan Basin research area (Sannigrahi et al, 2020;Huang et al, 2022) 4): geomorphological factors show the spatial characteristics of "centripetal trough", climatic factors show the spatial characteristics of "east high west low", anthropogenic factors show the spatial characteristics of "eastwest dual-core", and vegetation factors show the spatial characteristics of "planarization". The contribution rate of geomorphological factors, TEM, and EVA to the three natural factors is higher, the contribution rate of GDP and POP to the three social-economic factors is higher, and the contribution rate of other factors is lower.…”

Section: Quantitative Attribution Of the Driving Factors Of Ecosystem...supporting

confidence: 91%

“…This study refers to the methods of previous studies and the data requirements of the InVEST model to quantify the ES (Xie and Ng, 2013;Chen et al, 2020;Huang et al, 2022). SC is an important indicator to measure the water and soil conservation of the ecosystem.…”

Section: Datamentioning

confidence: 99%

“…However, these studies generally focus on the analysis of change patterns, paying less attention to the spatial change characteristics of driving forces, and often ignoring the scale differences of different driving factors. Therefore, some studies have used the spatial regression model to test the spatial non-stationary relationship between the four driving forces on SC and WY in Sichuan Province (Huang et al, 2022). This study not only adds the measurement indicators and driving factors of ES in the Sichuan Basin but also uses the MGWR model to explore the nature and intensity of the impact of various factors on ES in the Sichuan Basin.…”

Section: Introductionmentioning

confidence: 99%

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Quantifying the Temporal and Spatial Patterns of Ecosystem Services and Exploring the Spatial Differentiation of Driving Factors: a Case Study of Sichuan Basin, China

Wang

et al. 2022

Front. Environ. Sci.

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Exploring the factors that drive the change of ecosystem services (ES) is very important for maintaining ES function and zoning ecological management, especially in the Sichuan Basin area with high spatial heterogeneity such as natural and socio-economic characteristics. Taking the Sichuan Basin in China as an example, the PCA-MGWR model was constructed to explore the temporal and spatial patterns of ES in the Sichuan Basin from 2000 to 2015. The potential driving factors including anthropogenic factors, geomorphological factors, climate factors, and vegetation factors would be analyzed by principal component analysis (PCA). To illustrate the impact of spatial dependence in the data, the multi-scale geographically weighted regression (MGWR) technology was selected to explore the spatial differentiation of the impact of these four dimensions on ES to reflect the local differences of ecosystem service driving mechanisms in more detail. The results showed that 1) from the perspective of time series evolution, carbon storage (CS) and soil conservation (SC) in ES in the Sichuan Basin showed an upward trend, while water yield (WY) showed a downward trend; from the perspective of spatial patterns, except the main urban areas of Chengdu and Chongqing, the CS service level of other regions was high; The spatial distribution characteristics of SC services were “low in the middle and high in the periphery”; the high value area of WY service was located in Northeast Sichuan. 2) Among natural factors, elevation (DEM), slope (SLO), NDVI, annual average temperature (TEM), and annual average precipitation (PRE) had a higher contribution rate to ES, while among socio-economic factors, GDP density (GDP), night light (LIG), and population density (POP) had a higher contribution rate to ES, while other factors had a lower contribution rate. 3) Combined with the PCA-MGWR model, we analyzed the comprehensive response and spatial differentiation of driving factors to ES in the Sichuan Basin and explained in detail the influence of anthropogenic factors, geomorphological factors, climatic factors, and vegetation factors and their spatial heterogeneity in ES. It is expected that the spatial differences in the impact degree of different indicators can be considered when formulating the countermeasures of ES in the Sichuan Basin, to provide theoretical support for the implementation of regional ecological management and control.

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Section: Quantitative Attribution Of the Driving Factors Of Ecosystem...supporting

confidence: 91%

Section: Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Quantifying the Temporal and Spatial Patterns of Ecosystem Services and Exploring the Spatial Differentiation of Driving Factors: a Case Study of Sichuan Basin, China

Wang

et al. 2022

Front. Environ. Sci.

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“…Factors affecting ecosystem services mainly include two types: ecological factors and socio-economic factors (Hu et al, 2022;Huang et al, 2022;Lu et al, 2022;Zhuang et al, 2022). The ecological factors selected in this study include precipitation (PRE), temperature (TEM), fractional vegetation cover (FVC), slope (SL), and digital elevation model (DEM).…”

Section: Drivers Analysismentioning

confidence: 99%

“…The relationship between ecosystem services has also varied at different kilometer scales, and may even be the opposite (Liu et al, 2017;Sun et al, 2022). At the county level, the impact of driving forces on ecosystem services significantly differs in the east and west of Sichuan Province (Huang et al, 2022). Significant spatial heterogeneity affects a range of influencing factors in the Three Gorges Reservoir Area on the degree of coupling of ecosystem services and economic development (Li F. et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Differentiated factors drive the spatial heterogeneity of ecosystem services in Xinjiang Autonomous Region, China

et al. 2023

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Exploring the driving factors of changing ecosystem services is critical for supply capacity maintaining and ecological management zoning. Xinjiang of Northwest China, is considered one of the most fragile ecological environment areas. However, studies on how ecosystem services’ driving forces respond to the environmental conditions of Xinjiang are still insufficient, especially in sub–regions with considerable spatial heterogeneity. Based on 106 counties across Xinjiang, we employed models of the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) and Revised Wind Erosion Equation (RWEQ) to quantify four essential ecosystem services (carbon storage, habitat quality, and sand fixation and water yield). Then, we investigated the spatial distribution of four ecosystem services and drivers at the county scale in 2020 by using multi–scale geographically weighted regression (MGWR). The results showed that the spatial distribution of ecosystem services is higher in the north and lower in the south, and hotspots and high–value ecosystem services areas were consistent. Precipitation, temperature, and fractional vegetation cover were the dominant factors influencing the four ecosystem services. Therefore, regulating climate and increasing vegetation will maximize the improvement of regional ecosystem services in Xinjiang. Significant differences exist in the counties of the type, intensity, and direction of ecosystem services drivers. The correlation between carbon storage, habitat quality and fractional vegetation cover was more robust stronger in the south. Water yield was more closely related to fractional vegetation cover in southern Xinjiang. Under different ecological and social conditions, the impact of driving forces on ecosystem services showed different changing trends. Three suggestions for improving ecosystem services management were proposed based on our results. The comparative analysis of the driving factors of county ecosystem services in this study will help to formulate differentiated ecological protection policies and promote a sustainable supply of ecosystem services in Xinjiang. In the future, it is necessary to strengthen the long-term monitoring and evaluation of ecosystem services and the research on the interaction of multiple drivers.

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Factors influencing the spatiotemporal variation in the value of ecosystem services in Anxi county

Jiang¹,

Guo

Lin

et al. 2023

Heliyon

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Estimating the effects of driving forces on ecosystem services and their responses to environmental conditions

Cited by 4 publications

References 64 publications

Quantifying the Temporal and Spatial Patterns of Ecosystem Services and Exploring the Spatial Differentiation of Driving Factors: a Case Study of Sichuan Basin, China

Quantifying the Temporal and Spatial Patterns of Ecosystem Services and Exploring the Spatial Differentiation of Driving Factors: a Case Study of Sichuan Basin, China

Differentiated factors drive the spatial heterogeneity of ecosystem services in Xinjiang Autonomous Region, China

Factors influencing the spatiotemporal variation in the value of ecosystem services in Anxi county

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