Quantifying the Temporal and Spatial Patterns of Ecosystem Services and Exploring the Spatial Differentiation of Driving Factors: a Case Study of Sichuan Basin, China - Hu, Chunguang; Wang, Ziyi; Li, Jiaming; Liu, Huan; Sun, Dongqi (Frontiers in Environmental Science, 2022)
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 Sichuan Basin in China as an example, the PCA-MGWR model was constructed to explore the temporal and spatial pattern of ES in 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, 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: (I) From the perspective of time series evolution, carbon storage (CS) and soil conservation (SC) in ES in Sichuan Basin showed an upward trend, while water yield (WY) showed a downward trend; From the perspective of spatial pattern, 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; (II) 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; (III) Combined with PCA-MGWR model, analyzed the comprehensive response and spatial differentiation of driving factors to ES in 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 of the impact degree of different indicators can be considered when formulating the countermeasures of ES in the Sichuan Basinl.