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

Abstract

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.

Comprehensive evaluation system for vegetation ecological quality: a case study of Sichuan ecological protection redline areas

“…The region has a complex topography, diverse landforms, rich vegetation, and significant regional climatic differences. The eastern basin of Sichuan belongs to the subtropical humid climate zone ( He et al., 2022 ), with annual average temperatures of 16°C-18°C and annual precipitation of 1000 mm-1300 mm. Northwest Sichuan belongs to the plateau alpine climate zone.…”

Landscape Ecological Risk Assessment and Zoning Control Based on Ecosystem Service Value: Taking Sichuan Province as an Example

“…Located in the upper reaches of the Yangtze River, Sichuan Province spans the first and second steps of mainland China's terrain, characterized by high elevations in the west and lower elevations in the east, creating a substantial height variation (Figure 2) [19]. The province encompasses approximately 486,000 km 2 , extending from a latitude of 26 [20], with an annual precipitation level ranging from 1000 to 1200 mm.…”

Remote Sensing Identification and the Spatiotemporal Variation of Drought Characteristics in Inner Mongolia, China

“…Decreasing precipitation and increasing temperature are the dominating elements resulting in a drought occurring [4]. Droughts are characterized by a wide range of impacts and great difficulty in management and have serious impacts on agricultural production and human life [5][6][7]. Therefore, information on how to monitor and predict drought occurrence and its development pattern on a large scale and in a timely and accurate manner will be crucial guidance for agricultural production and ecological environment management in Inner Mongolia.…”